Research classified by Journal of Economic Literature (JEL) codes

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Top JEL
/ C: Mathematical and Quantitative Methods
/ / C5: Econometric Modeling
/ / / C55: Large Data Sets: Modeling and Analysis

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This JEL code is mentioned in the following RePEc Biblio entries:

1. > Econometrics > Time Series Models > VAR Models > Bayesian Vector autoregressions (BVARs)
2. > Econometrics > Forecasting > Nowcasting
3. > Econometrics > Time Series Models > Dynamic Factor Models

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This topic is covered by the following reading lists:

1. SOEP based publications
2. Socio-Economics of Innovation

2024

• Kim, Hyeongwoo & Son, Jisoo, 2024. "What charge-off rates are predictable by macroeconomic latent factors?," Journal of Financial Stability, Elsevier, vol. 74(C).
  • Kim, Hyeongwoo & Son, Jisoo, 2023. "What Charge-Off Rates Are Predictable by Macroeconomic Latent Factors?," MPRA Paper 116880, University Library of Munich, Germany.
  • Hyeongwoo Kim & Jisoo Son, 2024. "What Charge-Off Rates Are Predictable by Macroeconomic Latent Factors?," Auburn Economics Working Paper Series auwp2024-01, Department of Economics, Auburn University.
  • Hyeongwoo Kim & Jisoo Son, 2023. "What Charge-Off Rates Are Predictable by Macroeconomic Latent Factors?," Auburn Economics Working Paper Series auwp2023-06, Department of Economics, Auburn University.
• Sarthak Behera & Hyeongwoo Kim & Soohyon Kim, 2024. "Predictive Power of U.S. Macroeconomic Factors for the Dollar/Won Real Exchange Rate," Auburn Economics Working Paper Series auwp2024-02, Department of Economics, Auburn University.
• Alexey A. Mironenkov & Alexey N. Kurbatskii & Marina V. Mironenkova, 2024. "The Quality-of-Life Measurement with a Stochastic Choice of Parameters of the Weighted Principal Component," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, vol. 23(1), pages 82-109.
• Algieri, Bernardina & Iania, Leonardo & Leccadito, Arturo, 2024. "Looking ahead: Forecasting total energy carbon dioxide emissions," LIDAM Reprints LFIN 2024007, Université catholique de Louvain, Louvain Finance (LFIN).
• Fetzer, Thiemo & Shaw, Callum & Edenhofer, Jacob, 2024. "Informational Boundaries of the State," CAGE Online Working Paper Series 697, Competitive Advantage in the Global Economy (CAGE).
  • Thiemo Fetzer & Callum Shaw & Jacob Edenhofer, 2024. "Informational Boundaries of the State," ECONtribute Discussion Papers Series 282, University of Bonn and University of Cologne, Germany.
  • Fetzer, Thiemo & Shaw, Callum & Edenhofer, Jacob, 2024. "Informational Boundaries of the State," The Warwick Economics Research Paper Series (TWERPS) 1487, University of Warwick, Department of Economics.
  • Thiemo Fetzer & Callum Shaw & Jacob Edenhofer, 2024. "Informational Boundaries of the State," CESifo Working Paper Series 10901, CESifo.
• Simon D Angus & Lachlan O'Neill, 2024. "Paired completion: quantifying issue-framing at scale with LLMs," SoDa Laboratories Working Paper Series 2024-02, Monash University, SoDa Laboratories.
• Ahrens, Achim & Hansen, Christian B. & Schaffer, Mark E & Wiemann, Thomas, 2024. "Model Averaging and Double Machine Learning," IZA Discussion Papers 16714, Institute of Labor Economics (IZA).
  • Achim Ahrens & Christian B. Hansen & Mark E. Schaffer & Thomas Wiemann, 2024. "Model Averaging and Double Machine Learning," Papers 2401.01645, arXiv.org, revised Sep 2024.
• M. Hashem Pesaran & Ron P. Smith, 2024. "High-Dimensional Forecasting with Known Knowns and Known Unknowns," CESifo Working Paper Series 10931, CESifo.
  • M. Hashem Pesaran & Ron P. Smith, 2024. "High-dimensional forecasting with known knowns and known unknowns," Papers 2401.14582, arXiv.org, revised Apr 2024.
  • Pesaran, M. H. & Smith, R. P., 2024. "High-Dimensional Forecasting with Known Knowns and Known Unknowns," Cambridge Working Papers in Economics 2406, Faculty of Economics, University of Cambridge.
• Christian Møller Dahl & Torben Johansen & Christian Vedel, 2024. "Breaking the HISCO Barrier: Automatic Occupational Standardization with OccCANINE," Working Papers 0255, European Historical Economics Society (EHES).
  • Christian M{o}ller Dahl & Torben Johansen & Christian Vedel, 2024. "Breaking the HISCO Barrier: Automatic Occupational Standardization with OccCANINE," Papers 2402.13604, arXiv.org, revised Apr 2024.
• Laura Battaglia & Timothy M. Christensen & Stephen Hansen & Szymon Sacher, 2024. "Inference for regression with variables generated from unstructured data," CeMMAP working papers 10/24, Institute for Fiscal Studies.
  • Laura Battaglia & Timothy Christensen & Stephen Hansen & Szymon Sacher, 2024. "Inference for Regression with Variables Generated from Unstructured Data," Papers 2402.15585, arXiv.org, revised May 2024.
  • Laura Battaglia & Timothy Christensen & Stephen Hansen & Szymon Sacher, 2024. "Inference for Regression with Variables Generated from Unstructured Data," CESifo Working Paper Series 11119, CESifo.
• Ballinari, Daniele, 2024. "Calibrating doubly-robust estimators with unbalanced treatment assignment," Economics Letters, Elsevier, vol. 241(C).
  • Daniele Ballinari, 2024. "Calibrating doubly-robust estimators with unbalanced treatment assignment," Papers 2403.01585, arXiv.org, revised Jun 2024.
• Adam Korniejczuk & Robert Ślepaczuk, 2024. "Statistical arbitrage in multi-pair trading strategy based on graph clustering algorithms in US equities market," Working Papers 2024-09, Faculty of Economic Sciences, University of Warsaw.
  • Adam Korniejczuk & Robert 'Slepaczuk, 2024. "Statistical arbitrage in multi-pair trading strategy based on graph clustering algorithms in US equities market," Papers 2406.10695, arXiv.org.
• Zuzanna Kostecka & Robert Ślepaczuk, 2024. "Improving Realized LGD approximation: A Novel Framework with XGBoost for handling missing cash-flow data," Working Papers 2024-12, Faculty of Economic Sciences, University of Warsaw.
  • Zuzanna Kostecka & Robert 'Slepaczuk, 2024. "Improving Realized LGD Approximation: A Novel Framework with XGBoost for Handling Missing Cash-Flow Data," Papers 2406.17308, arXiv.org.
• Natalia Roszyk & Robert Ślepaczuk, 2024. "The Hybrid Forecast of S&P 500 Volatility ensembled from VIX, GARCH and LSTM models," Working Papers 2024-13, Faculty of Economic Sciences, University of Warsaw.
  • Natalia Roszyk & Robert 'Slepaczuk, 2024. "The Hybrid Forecast of S&P 500 Volatility ensembled from VIX, GARCH and LSTM models," Papers 2407.16780, arXiv.org.
• Laura Battaglia & Timothy Christensen & Stephen Hansen & Szymon Sacher, 2024. "Inference for Regression with Variables Generated from Unstructured Data," Papers 2402.15585, arXiv.org, revised May 2024.
  • Laura Battaglia & Timothy M. Christensen & Stephen Hansen & Szymon Sacher, 2024. "Inference for regression with variables generated from unstructured data," CeMMAP working papers 10/24, Institute for Fiscal Studies.
  • Laura Battaglia & Timothy Christensen & Stephen Hansen & Szymon Sacher, 2024. "Inference for Regression with Variables Generated from Unstructured Data," CESifo Working Paper Series 11119, CESifo.
• Aifer Baimukhametova & Madina Tulegenova & Zhansaya Temerbulatova & Dinara Rakhmatullayeva, 2024. "Transformation of Innovative Business Models through the Digitalization of the Economic Space," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 4, pages 48-60.
• Prachi Mishra & Alvaro Ortiz & Antonio Spilimbergo & Tomasa Rodrigo & Sirenia Vázquez, 2024. "España | El comercio electrónico: un \"clic\" no es igual para todos [Spain | E-commerce: One \"Click\" does not fit all]," Working Papers 24/08, BBVA Bank, Economic Research Department.
• Ajit Desai & Jacob Sharples & Anneke Kosse, 2024. "Finding a needle in a haystack: a machine learning framework for anomaly detection in payment systems," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Granular data: new horizons and challenges, volume 61, Bank for International Settlements.
  • Ajit Desai & Anneke Kosse & Jacob Sharples, 2024. "Finding a needle in a haystack: a machine learning framework for anomaly detection in payment systems," BIS Working Papers 1188, Bank for International Settlements.
  • Ajit Desai & Anneke Kosse & Jacob Sharples, 2024. "Finding a Needle in a Haystack: A Machine Learning Framework for Anomaly Detection in Payment Systems," Staff Working Papers 24-15, Bank of Canada.
• Andres Alonso-Robisco & Jose Manuel Carbo & Emily Kormanyos & Elena Triebskorn, 2024. "Houston, we have a problem: can satellite information bridge the climate-related data gap?," Occasional Papers 2428, Banco de España.
• Francesco Braggiotti & Nicola Chiarini & Giulio Dondi & Luciano Lavecchia & Valeria Lionetti & Juri Marcucci & Riccardo Russo, 2024. "Predicting buildings' EPC in Italy: a machine learning based-approach," Questioni di Economia e Finanza (Occasional Papers) 850, Bank of Italy, Economic Research and International Relations Area.
• Donato Ceci & Orest Prifti & Andrea Silvestrini, 2024. "Nowcasting Italian GDP growth: a Factor MIDAS approach," Temi di discussione (Economic working papers) 1446, Bank of Italy, Economic Research and International Relations Area.
• Marco Lo Duca & Diego Moccero & Fabio Parlapiano, 2024. "The impact of macroeconomic and monetary policy shocks on the default risk of the euro-area corporate sector," Temi di discussione (Economic working papers) 1460, Bank of Italy, Economic Research and International Relations Area.
• Diego Solórzano & Lenin Arango-Castillo, 2024. "Price Duration Using Daily Online Data: Time- or State-Dependent?," Working Papers 2024-10, Banco de México.
• Jean-Charles Bricongne & Baptiste Meunier & Raquel Caldeira, 2024. "Should Central Banks Care About Text Mining? A Literature Review," Working papers 950, Banque de France.
• Henri Fraisse & Christophe Hurlin, 2024. "Modèles internes des banques pour le calcul du capital réglementaire (IRB) et intelligence artificielle," Débats économiques et financiers 44, Banque de France.
• Tatjana Dahlhaus & Angelika Welte, 2024. "Payment habits during Covid-19: Evidence from high-frequency transaction data," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Granular data: new horizons and challenges, volume 61, Bank for International Settlements.
  • Tatjana Dahlhaus & Angelika Welte, 2021. "Payment Habits During COVID-19: Evidence from High-Frequency Transaction Data," Staff Working Papers 21-43, Bank of Canada.
• Efrem Castelnuovo & Kerem Tuzcuoglu & Luis Uzeda, 2024. "Sectoral uncertainty," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Granular data: new horizons and challenges, volume 61, Bank for International Settlements.
  • Efrem Castelnuovo & Kerem Tuzcuoglu & Luis Uzeda, 2022. "Sectoral Uncertainty," Staff Working Papers 22-38, Bank of Canada.
  • Efrem Castelnuovo & Kerem Tuzcuoglu & Luis Uzeda, 2022. "Sectoral Uncertainty," "Marco Fanno" Working Papers 0288, Dipartimento di Scienze Economiche "Marco Fanno".
  • Efrem Castelnuovo & Kerem Tuzcuoglu & Luis Uzeda, 2022. "Sectoral Uncertainty," CESifo Working Paper Series 10034, CESifo.
  • Efrem Castelnuovo & Kerem Tuzcuoglu & Luis Uzeda, 2022. "Sectoral Uncertainty," CAMA Working Papers 2022-62, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Ajit Desai & Jacob Sharples & Anneke Kosse, 2024. "Finding a needle in a haystack: a machine learning framework for anomaly detection in payment systems," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Granular data: new horizons and challenges, volume 61, Bank for International Settlements.
  • Ajit Desai & Anneke Kosse & Jacob Sharples, 2024. "Finding a Needle in a Haystack: A Machine Learning Framework for Anomaly Detection in Payment Systems," Staff Working Papers 24-15, Bank of Canada.
  • Ajit Desai & Anneke Kosse & Jacob Sharples, 2024. "Finding a needle in a haystack: a machine learning framework for anomaly detection in payment systems," BIS Working Papers 1188, Bank for International Settlements.
• Ajit Desai & Jacob Sharples & Anneke Kosse, 2024. "Finding a needle in a haystack: a machine learning framework for anomaly detection in payment systems," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Granular data: new horizons and challenges, volume 61, Bank for International Settlements.
  • Ajit Desai & Anneke Kosse & Jacob Sharples, 2024. "Finding a Needle in a Haystack: A Machine Learning Framework for Anomaly Detection in Payment Systems," Staff Working Papers 24-15, Bank of Canada.
  • Ajit Desai & Anneke Kosse & Jacob Sharples, 2024. "Finding a needle in a haystack: a machine learning framework for anomaly detection in payment systems," BIS Working Papers 1188, Bank for International Settlements.
• Jurkatis, Simon, 2024. "An approach to cleaning MiFID II corporate bond transaction reports," Bank of England working papers 1071, Bank of England.
• M. Hashem Pesaran & Ron P. Smith, 2024. "High-Dimensional Forecasting with Known Knowns and Known Unknowns," CESifo Working Paper Series 10931, CESifo.
  • Pesaran, M. H. & Smith, R. P., 2024. "High-Dimensional Forecasting with Known Knowns and Known Unknowns," Cambridge Working Papers in Economics 2406, Faculty of Economics, University of Cambridge.
  • M. Hashem Pesaran & Ron P. Smith, 2024. "High-dimensional forecasting with known knowns and known unknowns," Papers 2401.14582, arXiv.org, revised Apr 2024.
• Vainora, J., 2024. "Asymptotic Theory Under Network Stationarity," Cambridge Working Papers in Economics 2439, Faculty of Economics, University of Cambridge.
• Vainora, J., 2024. "Latent Position-Based Modeling of Parameter Heterogeneity," Cambridge Working Papers in Economics 2455, Faculty of Economics, University of Cambridge.
• Pesaran, M. H. & Song, H., 2024. "Forecasting 2024 US Presidential Election by States Using County Level Data: Too Close to Call," Cambridge Working Papers in Economics 2464, Faculty of Economics, University of Cambridge.
• Ritesh Patel & Anand Kumar Mishra & Muhammad Zubair Chishti & Tejas M. Modi, 2024. "Relationship Between Internet Banking Service Quality, e-Customer Satisfaction, and Loyalty: A Comparative Study of India and Pakistan," Journal of Central Banking Theory and Practice, Central bank of Montenegro, vol. 13(2), pages 213-228.
• Jennifer Bernard & Kelsey Drotning & Katie R. Genadek, 2024. "Where Are Your Parents? Exploring Potential Bias in Administrative Records on Children," Working Papers 24-18, Center for Economic Studies, U.S. Census Bureau.
• Fetzer, Thiemo & Shaw, Callum & Edenhofer, Jacob, 2024. "Informational Boundaries of the State," The Warwick Economics Research Paper Series (TWERPS) 1487, University of Warwick, Department of Economics.
  • Thiemo Fetzer & Callum Shaw & Jacob Edenhofer, 2024. "Informational Boundaries of the State," CESifo Working Paper Series 10901, CESifo.
  • Fetzer, Thiemo & Shaw, Callum & Edenhofer, Jacob, 2024. "Informational Boundaries of the State," CAGE Online Working Paper Series 697, Competitive Advantage in the Global Economy (CAGE).
  • Thiemo Fetzer & Callum Shaw & Jacob Edenhofer, 2024. "Informational Boundaries of the State," ECONtribute Discussion Papers Series 282, University of Bonn and University of Cologne, Germany.
• M. Hashem Pesaran & Ron P. Smith, 2024. "High-dimensional forecasting with known knowns and known unknowns," Papers 2401.14582, arXiv.org, revised Apr 2024.
  • M. Hashem Pesaran & Ron P. Smith, 2024. "High-Dimensional Forecasting with Known Knowns and Known Unknowns," CESifo Working Paper Series 10931, CESifo.
  • Pesaran, M. H. & Smith, R. P., 2024. "High-Dimensional Forecasting with Known Knowns and Known Unknowns," Cambridge Working Papers in Economics 2406, Faculty of Economics, University of Cambridge.
• Laura Battaglia & Timothy Christensen & Stephen Hansen & Szymon Sacher, 2024. "Inference for Regression with Variables Generated from Unstructured Data," Papers 2402.15585, arXiv.org, revised May 2024.
  • Laura Battaglia & Timothy Christensen & Stephen Hansen & Szymon Sacher, 2024. "Inference for Regression with Variables Generated from Unstructured Data," CESifo Working Paper Series 11119, CESifo.
  • Laura Battaglia & Timothy M. Christensen & Stephen Hansen & Szymon Sacher, 2024. "Inference for regression with variables generated from unstructured data," CeMMAP working papers 10/24, Institute for Fiscal Studies.
• Thomas Fackler & Oliver Falck & Moritz Goldbeck & Fabian Hans & Annina Hering, 2024. "The Greener, the Higher: Labor Demand of Automotive Firms during the Green Transformation," CESifo Working Paper Series 11160, CESifo.
• Pesaran, M. H. & Song, H., 2024. "Forecasting 2024 US Presidential Election by States Using County Level Data: Too Close to Call," Cambridge Working Papers in Economics 2464, Faculty of Economics, University of Cambridge.
  • M. Hashem Pesaran & Hayun Song, 2024. "Forecasting 2024 US Presidential Election by States Using County Level Data: Too Close to Call," CESifo Working Paper Series 11415, CESifo.
• Fetzer, Thiemo & Shaw, Callum & Edenhofer, Jacob, 2024. "Informational Boundaries of the State," The Warwick Economics Research Paper Series (TWERPS) 1487, University of Warwick, Department of Economics.
  • Fetzer, Thiemo & Shaw, Callum & Edenhofer, Jacob, 2024. "Informational Boundaries of the State," CAGE Online Working Paper Series 697, Competitive Advantage in the Global Economy (CAGE).
  • Thiemo Fetzer & Callum Shaw & Jacob Edenhofer, 2024. "Informational Boundaries of the State," CESifo Working Paper Series 10901, CESifo.
  • Thiemo Fetzer & Callum Shaw & Jacob Edenhofer, 2024. "Informational Boundaries of the State," ECONtribute Discussion Papers Series 282, University of Bonn and University of Cologne, Germany.
• Penaranda, Francisco & Sentana, Enrique, 2024. "Portfolio management with big data," CEPR Discussion Papers 19314, C.E.P.R. Discussion Papers.
  • Francisco Peñaranda & Enrique Sentana, 2024. "Portfolio management with big data," Working Papers wp2024_2411, CEMFI.
• Muñetón Santa , Guberney & Pérez Aguirre , Carlos Andrés & Orozco-Arroyave , Juan Rafael, 2024. "Identificación de la pobreza en Colombia: Comparación entre el índice de pobreza multidimensional y el sistema de identificación de beneficiarios de programas sociales," Revista Desarrollo y Sociedad, Universidad de los Andes,Facultad de Economía, CEDE, vol. 98(3), pages 45-68, August.
• Fetzer, Thiemo & Shaw, Callum & Edenhofer, Jacob, 2024. "Informational Boundaries of the State," CEPR Discussion Papers 18773, C.E.P.R. Discussion Papers.
• Francisco Peñaranda & Enrique Sentana, 2024. "Portfolio management with big data," Working Papers wp2024_2411, CEMFI.
  • Penaranda, Francisco & Sentana, Enrique, 2024. "Portfolio management with big data," CEPR Discussion Papers 19314, C.E.P.R. Discussion Papers.
• Garrón Vedia, Ignacio & Rodríguez Caballero, Carlos Vladimir & Ruiz Ortega, Esther, 2024. "International vulnerability of inflation," DES - Working Papers. Statistics and Econometrics. WS 44814, Universidad Carlos III de Madrid. Departamento de Estadística.
• Jin Seo Cho & Peter C.B. Phillips, 2024. "GMM Estimation with Brownian Kernels Applied to Income Inequality Measurement," Working papers 2024rwp-232, Yonsei University, Yonsei Economics Research Institute.
  • Jin Seo Cho & Peter C. B. Phillips, 2024. "GMM Estimation with Brownian Kernels Applied to Income Inequality Measurement," Cowles Foundation Discussion Papers 2411, Cowles Foundation for Research in Economics, Yale University.
• Richard Schnorrenberger & Aishameriane Schmidt & Guilherme Valle Moura, 2024. "Harnessing Machine Learning for Real-Time Inflation Nowcasting," Working Papers 806, DNB.
• Lo Duca, Marco & Moccero, Diego & Parlapiano, Fabio, 2024. "The impact of macroeconomic and monetary policy shocks on credit risk in the euro area corporate sector," Working Paper Series 2897, European Central Bank.
• Allayioti, Anastasia & Venditti, Fabrizio, 2024. "The role of comovement and time-varying dynamics in forecasting commodity prices," Working Paper Series 2901, European Central Bank.
• Beck, Günter W. & Carstensen, Kai & Menz, Jan-Oliver & Schnorrenberger, Richard & Wieland, Elisabeth, 2023. "Nowcasting consumer price inflation using high-frequency scanner data: Evidence from Germany," Discussion Papers 34/2023, Deutsche Bundesbank.
  • Beck, Günter W. & Carstensen, Kai & Menz, Jan-Oliver & Schnorrenberger, Richard & Wieland, Elisabeth, 2024. "Nowcasting consumer price inflation using high-frequency scanner data: evidence from Germany," Working Paper Series 2930, European Central Bank.
• Richard Audoly & Rory McGee & Sergio Ocampo & Gonzalo Paz-Pardo, 2024. "The life-cycle dynamics of wealth mobility," IFS Working Papers W24/12, Institute for Fiscal Studies.
  • Audoly, Richard & Paz-Pardo, Gonzalo & McGee, Rory & Ocampo, Sergio, 2024. "The life-cycle dynamics of wealth mobility," Working Paper Series 2976, European Central Bank.
  • Audoly, Richard & McGee, Rory & Ocampo Díaz, Sergio & Paz Pardo, Gonzalo, 2024. "The life-cycle dynamics of wealth mobility," CLEF Working Paper Series 68, Canadian Labour Economics Forum (CLEF), University of Waterloo.
  • Richard Audoly & Rory McGee & Sergio Ocampo & Gonzalo Paz-Pardo, 2024. "The Life-Cycle Dynamics of Wealth Mobility," Staff Reports 1097, Federal Reserve Bank of New York.
• Restu Arisanti & Suci Purnamawati & Agus Muslim, 2024. "Determinants of Greenhouse Gas Emissions in the Transportation Sector in Indonesia: Official Statistics and Big Data Approach," International Journal of Energy Economics and Policy, Econjournals, vol. 14(1), pages 86-97, January.
• Farrukh Nawaz Kayani & Ismat Nasim & Khalil Abu Saleem, 2024. "Analyzing the Impact of Governance, Environment and Trade on Inward FDI: A Case of Cambodia, Thailand and Vietnam from ASEAN," International Journal of Energy Economics and Policy, Econjournals, vol. 14(2), pages 523-534, March.
• Klieber, Karin, 2024. "Non-linear dimension reduction in factor-augmented vector autoregressions," Journal of Economic Dynamics and Control, Elsevier, vol. 159(C).
• Ismail, I. & Stam, P.J.A. & Portrait, F.R.M. & van Witteloostuijn, A. & Koolman, X., 2024. "Addressing unanticipated interactions in risk equalization: A machine learning approach to modeling medical expenditure risk," Economic Modelling, Elsevier, vol. 130(C).
• Delogu, Marco & Lagravinese, Raffaele & Paolini, Dimitri & Resce, Giuliano, 2024. "Predicting dropout from higher education: Evidence from Italy," Economic Modelling, Elsevier, vol. 130(C).
  • Marco Delogu & Raffaelle Lagravinese & Dimitri Paolini & Giuliano Resce, 2020. "Predicting dropout from higher education: Evidence from Italy," DEM Discussion Paper Series 22-06, Department of Economics at the University of Luxembourg.
• Ren, Tingting & Li, Shaofang & Zhang, Siying, 2024. "Stock market extreme risk prediction based on machine learning: Evidence from the American market," The North American Journal of Economics and Finance, Elsevier, vol. 74(C).
• Hadji-Lazaro, Paul & Salin, Mathilde & Svartzman, Romain & Espagne, Etienne & Gauthey, Julien & Berger, Joshua & Calas, Julien & Godin, Antoine & Vallier, Antoine, 2024. "Biodiversity loss and financial stability as a new frontier for central banks: An exploration for France," Ecological Economics, Elsevier, vol. 223(C).
• Dubbert, Tore & Kempa, Bernd, 2024. "Nowcasting the output gap with shadow rates," Economics Letters, Elsevier, vol. 236(C).
• Ballinari, Daniele, 2024. "Calibrating doubly-robust estimators with unbalanced treatment assignment," Economics Letters, Elsevier, vol. 241(C).
  • Daniele Ballinari, 2024. "Calibrating doubly-robust estimators with unbalanced treatment assignment," Papers 2403.01585, arXiv.org, revised Jun 2024.
• Kunaschk, Max, 2024. "Enriching administrative data using survey data and machine learning techniques," Economics Letters, Elsevier, vol. 243(C).
• Lim, Dennis & Wang, Wenjie & Zhang, Yichong, 2024. "A conditional linear combination test with many weak instruments," Journal of Econometrics, Elsevier, vol. 238(2).
• Bai, Jushan & Duan, Jiangtao & Han, Xu, 2024. "The likelihood ratio test for structural changes in factor models," Journal of Econometrics, Elsevier, vol. 238(2).
  • Jushan Bai & Jiangtao Duan & Xu Han, 2022. "Likelihood ratio test for structural changes in factor models," Papers 2206.08052, arXiv.org, revised Dec 2023.
• Reuvers, Hanno & Wijler, Etienne, 2024. "Sparse generalized Yule–Walker estimation for large spatio-temporal autoregressions with an application to NO2 satellite data," Journal of Econometrics, Elsevier, vol. 239(1).
• Chang, Jinyuan & Hu, Qiao & Liu, Cheng & Tang, Cheng Yong, 2024. "Optimal covariance matrix estimation for high-dimensional noise in high-frequency data," Journal of Econometrics, Elsevier, vol. 239(2).
• Fan, Qingliang & Wu, Ruike & Yang, Yanrong & Zhong, Wei, 2024. "Time-varying minimum variance portfolio," Journal of Econometrics, Elsevier, vol. 239(2).
• Chang, Jinyuan & Chen, Cheng & Qiao, Xinghao & Yao, Qiwei, 2024. "An autocovariance-based learning framework for high-dimensional functional time series," Journal of Econometrics, Elsevier, vol. 239(2).
• Wan, Runzhe & Li, Yingying & Lu, Wenbin & Song, Rui, 2024. "Mining the factor zoo: Estimation of latent factor models with sufficient proxies," Journal of Econometrics, Elsevier, vol. 239(2).
• Chen, Dachuan & Mykland, Per A. & Zhang, Lan, 2024. "Realized regression with asynchronous and noisy high frequency and high dimensional data," Journal of Econometrics, Elsevier, vol. 239(2).
• Choi, Jungjun & Kwon, Hyukjun & Liao, Yuan, 2024. "Inference for low-rank completion without sample splitting with application to treatment effect estimation," Journal of Econometrics, Elsevier, vol. 240(1).
• Loaiza-Maya, Rubén & Nibbering, Didier & Zhu, Dan, 2024. "Hybrid unadjusted Langevin methods for high-dimensional latent variable models," Journal of Econometrics, Elsevier, vol. 241(2).
• Urga, Giovanni & Wang, Fa, 2024. "Estimation and inference for high dimensional factor model with regime switching," Journal of Econometrics, Elsevier, vol. 241(2).
• Mei, Ziwei & Shi, Zhentao, 2024. "On LASSO for high dimensional predictive regression," Journal of Econometrics, Elsevier, vol. 242(2).
• Ahelegbey, Daniel Felix & Billio, Monica & Casarin, Roberto, 2024. "Modeling Turning Points in the Global Equity Market," Econometrics and Statistics, Elsevier, vol. 30(C), pages 60-75.
  • Daniel Felix Ahelegbey & Monica Billio & Roberto Casarin, 2020. "Modeling Turning Points In Global Equity Market," DEM Working Papers Series 195, University of Pavia, Department of Economics and Management.
• Montorsi, Carlotta & Fusco, Alessio & Van Kerm, Philippe & Bordas, Stéphane P.A., 2024. "Predicting depression in old age: Combining life course data with machine learning," Economics & Human Biology, Elsevier, vol. 52(C).
• Sun, Chuanping, 2024. "Factor correlation and the cross section of asset returns: A correlation-robust machine learning approach," Journal of Empirical Finance, Elsevier, vol. 77(C).
• Trimborn, Simon & Peng, Hanqiu & Chen, Ying, 2024. "Influencer detection meets network autoregression — Influential regions in the bitcoin blockchain," Journal of Empirical Finance, Elsevier, vol. 78(C).
• Ouyang, Zisheng & Lu, Min & Ouyang, Zhongzhe & Zhou, Xuewei & Wang, Ren, 2024. "A novel integrated method for improving the forecasting accuracy of crude oil: ESMD-CFastICA-BiLSTM-Attention," Energy Economics, Elsevier, vol. 138(C).
• Hwang, Sam Il Myoung & Squires, Munir, 2024. "Linked samples and measurement error in historical US census data," Explorations in Economic History, Elsevier, vol. 93(C).
• Karim, Sitara & Shafiullah, Muhammad & Naeem, Muhammad Abubakr, 2024. "When one domino falls, others follow: A machine learning analysis of extreme risk spillovers in developed stock markets," International Review of Financial Analysis, Elsevier, vol. 93(C).
• Moffo, Ahmadou Mustapha Fonton, 2024. "A machine learning approach in stress testing US bank holding companies," International Review of Financial Analysis, Elsevier, vol. 95(PC).
• Jing, Zhongbo & Li, Qin & Zhao, Hongyi & Zhao, Yang, 2024. "Predicting stock price crash risk in China: A modified graph WaveNet model," Finance Research Letters, Elsevier, vol. 64(C).
• Bang, Jeongseok & Kang, Yeonchan & Ryu, Doojin, 2024. "Potential pricing factors in the Korean market," Finance Research Letters, Elsevier, vol. 67(PB).
• Ashwin, Julian, 2024. "Financial news media and volatility: Is there more to newspapers than news?," Journal of Financial Markets, Elsevier, vol. 69(C).
• Kim, Hyeongwoo & Son, Jisoo, 2024. "What charge-off rates are predictable by macroeconomic latent factors?," Journal of Financial Stability, Elsevier, vol. 74(C).
  • Kim, Hyeongwoo & Son, Jisoo, 2023. "What Charge-Off Rates Are Predictable by Macroeconomic Latent Factors?," MPRA Paper 116880, University Library of Munich, Germany.
  • Hyeongwoo Kim & Jisoo Son, 2024. "What Charge-Off Rates Are Predictable by Macroeconomic Latent Factors?," Auburn Economics Working Paper Series auwp2024-01, Department of Economics, Auburn University.
  • Hyeongwoo Kim & Jisoo Son, 2023. "What Charge-Off Rates Are Predictable by Macroeconomic Latent Factors?," Auburn Economics Working Paper Series auwp2023-06, Department of Economics, Auburn University.
• Nicodemo, Catia & Orso, Cristina E. & Tealdi, Cristina, 2024. "Overseas general practitioners (GPs) and prescription behaviour in England," Health Policy, Elsevier, vol. 140(C).
• Shemendyuk, Aleksandr & Wagner, Joël, 2024. "On the factors determining the health profiles and care needs of institutionalized elders," Insurance: Mathematics and Economics, Elsevier, vol. 114(C), pages 223-241.
• Ungolo, Francesco & van den Heuvel, Edwin R., 2024. "A Dirichlet process mixture regression model for the analysis of competing risk events," Insurance: Mathematics and Economics, Elsevier, vol. 116(C), pages 95-113.
• Coulibaly, Issiaka & Dembélé, Moustapha, 2024. "Impacts of remittances from internal and international migrants on poverty and inequality in Mali," International Economics, Elsevier, vol. 177(C).
• Crispino, Marta & Conteduca, Francesco Paolo, 2024. "It's a match! Linking foreign counterparts in Italian customs data to their balance sheets," International Economics, Elsevier, vol. 179(C).
  • Crispino Marta & Francesco Paolo Conteduca, 2023. "It's a match! Linking foreign counterparts in Italian customs data to their balance sheets," Questioni di Economia e Finanza (Occasional Papers) 823, Bank of Italy, Economic Research and International Relations Area.
• Furukawa, Kakuho & Hisano, Ryohei & Minoura, Yukio & Yagi, Tomoyuki, 2024. "A nowcasting model of industrial production using alternative data and machine learning approaches," Japan and the World Economy, Elsevier, vol. 71(C).
• Kurz, Konstantin & Bock, Carolin & Hanschur, Leonard, 2024. "Flip the tweet – the two-sided coin of entrepreneurial empathy and its ambiguous influence on new product development," Journal of Business Venturing, Elsevier, vol. 39(2).
• Bekaert, Els & Constant, Amelie F. & Foubert, Killian & Ruyssen, Ilse, 2024. "Longing for which home: A global analysis of the determinants of aspirations to stay, return or migrate onwards," Journal of Economic Behavior & Organization, Elsevier, vol. 219(C), pages 564-587.
• Nguyen, Ha Minh, 2024. "Beyond the annual averages: Impact of seasonal temperature on employment growth in US counties," Journal of Environmental Economics and Management, Elsevier, vol. 125(C).
  • Ha Nguyen, 2023. "Beyond the Annual Averages: Impact of Seasonal Temperature on Employment Growth in US Counties," IMF Working Papers 2023/142, International Monetary Fund.
• Ardia, David & Barras, Laurent & Gagliardini, Patrick & Scaillet, Olivier, 2024. "Is it alpha or beta? Decomposing hedge fund returns when models are misspecified," Journal of Financial Economics, Elsevier, vol. 154(C).
  • David Ardia & Laurent Barras & Patrick Gagliardini & Olivier Scaillet, 2020. "Is it Alpha or Beta? Decomposing Hedge Fund Returns When Models are Misspecified," Swiss Finance Institute Research Paper Series 20-82, Swiss Finance Institute, revised May 2023.
• Cao, Sean & Jiang, Wei & Wang, Junbo & Yang, Baozhong, 2024. "From Man vs. Machine to Man + Machine: The art and AI of stock analyses," Journal of Financial Economics, Elsevier, vol. 160(C).
• Tabe-Ojong, Martin Paul Jr. & Nana, Ibrahim & Zimmermann, Andrea & Jafari, Yaghoob, 2024. "Trends and evolution of global value chains in food and agriculture: Implications for food security and nutrition," Food Policy, Elsevier, vol. 127(C).
• Gerba, Eddie & Leiva-León, Danilo & Rubio, Margarita, 2024. "Inspecting cross-border macro-financial mechanisms," Journal of International Money and Finance, Elsevier, vol. 145(C).
• Sen, Abhibasu & Dutta Choudhury, Karabi, 2024. "Forecasting the Crude Oil prices for last four decades using deep learning approach," Resources Policy, Elsevier, vol. 88(C).
• Noailly, Joëlle & Nowzohour, Laura & van den Heuvel, Matthias & Pla, Ireneu, 2024. "Heard the news? Environmental policy and clean investments," Journal of Public Economics, Elsevier, vol. 238(C).
• Li, Zhao-Chen & Xie, Chi & Wang, Gang-Jin & Zhu, You & Zeng, Zhi-Jian & Gong, Jue, 2024. "Forecasting global stock market volatilities: A shrinkage heterogeneous autoregressive (HAR) model with a large cross-market predictor set," International Review of Economics & Finance, Elsevier, vol. 93(PB), pages 673-711.
• Hausladen, Carina I. & Fochmann, Martin & Mohr, Peter, 2024. "Predicting compliance: Leveraging chat data for supervised classification in experimental research," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 109(C).
• Atsebi, Jean-Marc B. & Ouedraogo, Rasmane & Séri-Atsebi, Regina, 2024. "Mining for delinking children’s occupation to that of their parents in Africa," World Development, Elsevier, vol. 184(C).
• Roshen Fernando, 2024. "Global Economic Impacts of Physical Climate Risks on Agriculture and Energy," CAMA Working Papers 2024-37, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Roshen Fernando, 2024. "Impact of Physical Climate Risks on Financial Assets," CAMA Working Papers 2024-38, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Roshen Fernando & Warwick McKibbin, 2024. "Global Economic Impacts of Antimicrobial Resistance," CAMA Working Papers 2024-41, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Aristide Houndetoungan & Abdoul Haki Maoude, 2024. "Inference for Two-Stage Extremum Estimators," THEMA Working Papers 2024-01, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
• Guillermo Cabanillas-Jiménez, 2024. "Testing the permanent income hypothesis using the Spanish Christmas Lottery," Applied Economic Analysis, Emerald Group Publishing Limited, vol. 32(96), pages 232-259, May.
• Prince Kumar Maurya & Rohit Bansal & Anand Kumar Mishra, 2024. "Dynamic connectedness among market volatilities: a perspective of COVID-19 and Russia-Ukraine conflict," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 41(5), pages 1119-1140, April.
• Lenka Nechvatalova, 2024. "Multi-Horizon Equity Returns Predictability via Machine Learning," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 74(2), pages 142-190, May.
  • Lenka Nechvatalova, 2021. "Multi-Horizon Equity Returns Predictability via Machine Learning," Working Papers IES 2021/02, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Feb 2021.
• Lenka Nechvatalova, 2024. "Autoencoder Asset Pricing Models and Economic Restrictions - International Evidence," Working Papers IES 2024/26, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Aug 2024.
• Celso Brunetti & Matthew Carl & Jacob Gerszten & Chiara Scotti & Chaehee Shin, 2024. "Interconnectedness in the Corporate Bond Market," Finance and Economics Discussion Series 2024-066, Board of Governors of the Federal Reserve System (U.S.).
• Matteo Barigozzi & Matteo Luciani, 2019. "Quasi Maximum Likelihood Estimation and Inference of Large Approximate Dynamic Factor Models via the EM algorithm," Papers 1910.03821, arXiv.org, revised Sep 2024.
  • Matteo Barigozzi & Matteo Luciani, 2024. "Quasi Maximum Likelihood Estimation and Inference of Large Approximate Dynamic Factor Models via the EM algorithm," Finance and Economics Discussion Series 2024-086, Board of Governors of the Federal Reserve System (U.S.).
• Tarek A. Hassan & Stephan Hollander & Aakash Kalyani & Markus Schwedeler & Ahmed Tahoun & Laurence van Lent, 2024. "Economic Surveillance using Corporate Text," Working Papers 2024-022, Federal Reserve Bank of St. Louis.
• Prodosh Eugene Simlai, 2024. "Risk Characterization of Firms with ESG Attributes Using a Supervised Machine Learning Method," JRFM, MDPI, vol. 17(5), pages 1-9, May.
• Tetiana Yukhymenko & Oleh Sorochan, 2024. "Impact of the central bank's communication on macro financial outcomes," IHEID Working Papers 01-2024, Economics Section, The Graduate Institute of International Studies.
• Dalloul, Ami, 2024. "The Fed Speaks, but does the Press Repeat? Investigating the Communication Channel between the Fed and the Written Press," Hannover Economic Papers (HEP) dp-724, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
• Christian M{o}ller Dahl & Torben Johansen & Christian Vedel, 2024. "Breaking the HISCO Barrier: Automatic Occupational Standardization with OccCANINE," Papers 2402.13604, arXiv.org, revised Apr 2024.
  • Christian Møller Dahl & Torben Johansen & Christian Vedel, 2024. "Breaking the HISCO Barrier: Automatic Occupational Standardization with OccCANINE," Working Papers 0255, European Historical Economics Society (EHES).
• Bertsch, Christoph & Hull, Isaiah & Lumsdaine, Robin L. & Zhang, Xin, 2024. "Four Facts about International Central Bank Communication," Working Paper Series 432, Sveriges Riksbank (Central Bank of Sweden).
• J. van den Berg, Gerard & Kunaschk, Max & Lang, Julia & Stephan, Gesine & Uhlendorff, Arne, 2023. "Predicting re-employment: machine learning versus assessments by unemployed workers and by their caseworkers," Working Paper Series 2023:22, IFAU - Institute for Evaluation of Labour Market and Education Policy.
  • Berg, Gerard J. van den & Kunaschk, Max & Lang, Julia & Stephan, Gesine & Uhlendorff, Arne, 2024. "Predicting Re-Employment: Machine Learning Versus Assessments by Unemployed Workers and by Their Caseworkers," IAB-Discussion Paper 202403, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
  • Gerard J. van den Berg & Max Kunaschk & Julia Lang & Gesine Stephan & Arne Uhlendorf, 2023. "Predicting Re-Employment: Machine Learning Versus Assessments by Unemployed Workers and by Their Caseworkers," Working Papers 2023-09, Center for Research in Economics and Statistics.
  • van den Berg, Gerard J. & Kunaschk, Max & Lang, Julia & Stephan, Gesine & Uhlendorff, Arne, 2023. "Predicting Re-Employment: Machine Learning versus Assessments by Unemployed Workers and by Their Caseworkers," IZA Discussion Papers 16426, Institute of Labor Economics (IZA).
• Mühlbauer, Sabrina & Weber, Enzo, 2024. "Predicting Job Match Quality: A Machine Learning Approach," IAB-Discussion Paper 202409, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
• Elok Heniwati & Angga Hervianto, 2024. "Logistic Regression to Predict BPK's Audit Opinion," Oblik i finansi, Institute of Accounting and Finance, issue 2, pages 118-127, June.
• Bjarni G. Einarsson, 2024. "Online Monitoring of Policy Optimality," Economics wp95, Department of Economics, Central bank of Iceland.
• Surabhi Garg & Srijit Mishra, 2024. "Effect of demand and supply side factors on school education outcomes in India," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2024-013, Indira Gandhi Institute of Development Research, Mumbai, India.
• Achim Ahrens & Christian B. Hansen & Mark E. Schaffer & Thomas Wiemann, 2024. "Model Averaging and Double Machine Learning," Papers 2401.01645, arXiv.org, revised Sep 2024.
  • Ahrens, Achim & Hansen, Christian B. & Schaffer, Mark E & Wiemann, Thomas, 2024. "Model Averaging and Double Machine Learning," IZA Discussion Papers 16714, Institute of Labor Economics (IZA).
• Lee, Wang-Sheng & Tran, Trang My, 2024. "Emissions from Military Training: Evidence from Australia," IZA Discussion Papers 16889, Institute of Labor Economics (IZA).
• Kumar, Pradeep & Nicodemo, Catia & Oreffice, Sonia & Quintana-Domeque, Climent, 2024. "Machine Learning and Multiple Abortions," IZA Discussion Papers 17046, Institute of Labor Economics (IZA).
• Zongwu Cai & Pixiong Chen, 2024. "Online Investor Sentiment via Machine Learning," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202411, University of Kansas, Department of Economics, revised Sep 2024.
• Yamin Ahmad & Adam Check & Ming Chien Lo, 2024. "Unit Roots in Macroeconomic Time Series: A Comparison of Classical, Bayesian and Machine Learning Approaches," Computational Economics, Springer;Society for Computational Economics, vol. 63(6), pages 2139-2173, June.
• Rama K. Malladi, 2024. "Benchmark Analysis of Machine Learning Methods to Forecast the U.S. Annual Inflation Rate During a High-Decile Inflation Period," Computational Economics, Springer;Society for Computational Economics, vol. 64(1), pages 335-375, July.
• Ghislain Geniaux, 2024. "Speeding up estimation of spatially varying coefficients models," Journal of Geographical Systems, Springer, vol. 26(3), pages 293-327, July.
• Muhammad Asad & Saeed Akbar & Sabur Mollah, 2024. "The role of independent directors’ tenure and network in controlling real-earnings management practices," Review of Quantitative Finance and Accounting, Springer, vol. 63(4), pages 1251-1279, November.
• Karolis Matikonis & Matthew Gobey, 2024. "Small Business Property Tax Reductions and Firm Productivity," Small Business Economics, Springer, vol. 62(1), pages 307-324, January.
• Marie Madeleine Meurer & Maksim Belitski & Christian Fisch & Roy Thurik, 2024. "What gets published and what doesn’t? Exploring optimal distinctiveness and diverse expectations in entrepreneurship articles," Small Business Economics, Springer, vol. 63(3), pages 1139-1170, October.
• Bachmann Ronald & Boockmann Bernhard & Vonnahme Christina & Wiemann Jan Simon, 2024. "Internationale Dateninnovationen: Potenziale für die deutsche Arbeitsmarkt- und Sozialpolitik," Zeitschrift für Wirtschaftspolitik, De Gruyter, vol. 73(1), pages 1-23, May.
• Latifi, Albina & Winker, Peter & Lenz, David, 2024. "Identification of innovation drivers based on technology-related news articles," VfS Annual Conference 2024 (Berlin): Upcoming Labor Market Challenges 302371, Verein für Socialpolitik / German Economic Association.
  • Albina Latifi & David Lenz & Peter Winker, 2024. "Identification of Innovation Drivers Based on Technology-Related News Articles," MAGKS Papers on Economics 202401, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
• Jenny Bethäuser, 2024. "Impact of Policy Measures and Behavior on the COVID Pandemic in Germany," MAGKS Papers on Economics 202411, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
• Paulo Barbosa & João Cortes & João Amador, 2024. "Distance to Export: A Machine Learning Approach with Portuguese Firms," GEE Papers 182, Gabinete de Estratégia e Estudos, Ministério da Economia, revised Jul 2024.
• Asia J. Biega, 2024. "Data Repurposing through Compatibility: A Computational Perspective," Journal of Institutional and Theoretical Economics (JITE), Mohr Siebeck, Tübingen, vol. 180(2), pages 368-392.
• Piroska Nagy Mohacsi & Tatiana Evdokimova & Olga Ponomarenko & Elina Ribakova, 2024. "Emerging Market Central Banking and Communication: The Great Catchup," Financial and Economic Review, Magyar Nemzeti Bank (Central Bank of Hungary), vol. 23(1), pages 29-49.
• James D. Hamilton & Jin Xi, 2024. "Principal Component Analysis for Nonstationary Series," NBER Working Papers 32068, National Bureau of Economic Research, Inc.
• Yi Chen & Hanming Fang & Yi Zhao & Zibo Zhao, 2024. "Recovering Overlooked Information in Categorical Variables with LLMs: An Application to Labor Market Mismatch," NBER Working Papers 32327, National Bureau of Economic Research, Inc.
• Damir Filipović & Markus Pelger & Ye Ye, 2022. "Shrinking the Term Structure," Swiss Finance Institute Research Paper Series 22-61, Swiss Finance Institute.
  • Damir Filipović & Markus Pelger & Ye Ye, 2024. "Shrinking the Term Structure," NBER Working Papers 32472, National Bureau of Economic Research, Inc.
• Antoine Didisheim & Shikun (Barry) Ke & Bryan T. Kelly & Semyon Malamud, 2024. "APT or “AIPT”? The Surprising Dominance of Large Factor Models," NBER Working Papers 33012, National Bureau of Economic Research, Inc.
• Ruslan Goyenko & Bryan T. Kelly & Tobias J. Moskowitz & Yinan Su & Chao Zhang, 2024. "Trading Volume Alpha," NBER Working Papers 33037, National Bureau of Economic Research, Inc.
• Rui Da & Stefan Nagel & Dacheng Xiu, 2024. "The Statistical Limit of Arbitrage," NBER Working Papers 33070, National Bureau of Economic Research, Inc.
• Mirko Djukic, 2024. "Topic classification of economic newspaper articles in a highly inflectional language – the case of Serbia," Working Papers Bulletin 21, National Bank of Serbia.
• Graham Pilgrim & Shirly Ang, 2024. "The OECD-UNSD Multinational Enterprise Information Platform," OECD Statistics Working Papers 2024/01, OECD Publishing.
• Graham Pilgrim & Emmanuelle Guidetti & Annabelle Mourougane, 2024. "An ocean of data: The potential of data on vessel traffic," OECD Statistics Working Papers 2024/02, OECD Publishing.
• Thiemo Fetzer & Ludovica Gazze & Menna Bishop, 2024. "Distributional and climate implications of policy responses to energy price shocks," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 39(120), pages 711-756.
• Tae-Hwy Lee & Ekaterina Seregina, 2024. "Optimal Portfolio Using Factor Graphical Lasso," Journal of Financial Econometrics, Oxford University Press, vol. 22(3), pages 670-695.
  • Tae-Hwy Lee & Ekaterina Seregina, 2020. "Optimal Portfolio Using Factor Graphical Lasso," Papers 2011.00435, arXiv.org, revised Apr 2023.
  • Tae-Hwy Lee & Ekaterina Seregina, 2023. "Optimal Portfolio Using Factor Graphical Lasso," Working Papers 202302, University of California at Riverside, Department of Economics.
  • Tae-Hwy Lee & Ekaterina Seregina, 2020. "Optimal Portfolio Using Factor Graphical Lasso," Working Papers 202025, University of California at Riverside, Department of Economics.
• Luca Mucciante & Alessio Sancetta, 2024. "Estimation of an Order Book Dependent Hawkes Process for Large Datasets," Journal of Financial Econometrics, Oxford University Press, vol. 22(4), pages 1098-1129.
• Leonardo Bargigli & Giulio Cifarelli, 2024. "Endogenous Volatility in the Foreign Exchange Market," Journal of Financial Econometrics, Oxford University Press, vol. 22(4), pages 773-807.
• Minseog Oh & Donggyu Kim, 2024. "Effect of the U.S.–China Trade War on Stock Markets: A Financial Contagion Perspective," Journal of Financial Econometrics, Oxford University Press, vol. 22(4), pages 954-1005.
  • Minseog Oh & Donggyu Kim, 2021. "Effect of the U.S.--China Trade War on Stock Markets: A Financial Contagion Perspective," Papers 2111.09655, arXiv.org.
• Anastasios Kagkadis & Ingmar Nolte & Sandra Nolte & Nikolaos Vasilas, 2024. "Factor Timing with Portfolio Characteristics," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 14(1), pages 84-118.
• Mihai Ciobotea & Marian Stan, 2024. "European Perspectives on Datafication," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(1), pages 175-183, August.
• Alina Bobasu & Lucia Quaglietti & Martino Ricci, 2024. "Tracking Global Economic Uncertainty: Implications for the Euro Area," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 72(2), pages 820-857, June.
  • Bobasu, Alina & Geis, André & Quaglietti, Lucia & Ricci, Martino, 2021. "Tracking global economic uncertainty: implications for the euro area," Working Paper Series 2541, European Central Bank.
• Yi Chen & Hanming Fang & Yi Zhao & Zibo Zhao, 2024. "Recovering Overlooked Information in Categorical Variables with LLMs: An Application to Labor Market Mismatch," PIER Working Paper Archive 24-017, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
• Nwaobi, Godwin, 2024. "Productive Sectors and Digital Diffusion(Adoption) in Nigeria: Empirical Evidence," MPRA Paper 122392, University Library of Munich, Germany.
• Yunus Karaömer & Arif Eser Guzel, 2024. "Effect of Economic Policy Uncertainty on Stock Returns: Analysing the Moderating Role of Government Size," Politická ekonomie, Prague University of Economics and Business, vol. 2024(1), pages 50-72.
• Luke Hartigan & Tom Rosewall, 2024. "Nowcasting Quarterly GDP Growth during the COVID-19 Crisis Using a Monthly Activity Indicator," Working Papers 2024-15, University of Sydney, School of Economics.
  • Luke Hartigan & Tom Rosewall, 2024. "Nowcasting Quarterly GDP Growth during the COVID-19 Crisis Using a Monthly Activity Indicator," RBA Research Discussion Papers rdp2024-04, Reserve Bank of Australia.
• Raj, Alok & Kumar, Rajeev Ranjan & Jeyaraj, Anand, 2024. "Antecedents and Outcomes of Big Data Adoption in Supply Chain: A Meta-Analytic Investigation," American Business Review, Pompea College of Business, University of New Haven, vol. 27(2), pages 775-797, November.
• Vlad TEODORESCU & Catalina-Ioana TOADER, 2024. "Using Machine Learning to Model Bankruptcy Risk in Listed Companies," PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON ECONOMICS AND SOCIAL SCIENCES, Bucharest University of Economic Studies, Romania, vol. 6(1), pages 610-619, August.
• Alexandra-Cristina-Daniela CIUVERCA, 2024. "Sentiment Analysis of Research on AI Ethics: A Web-Based Study," PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON ECONOMICS AND SOCIAL SCIENCES, Bucharest University of Economic Studies, Romania, vol. 6(1), pages 672-681, August.
• Nicola Caravaggio, 2024. "A first impact evaluation of the Italian Dignity Decree’s effects on young workers," Departmental Working Papers of Economics - University 'Roma Tre' 0280, Department of Economics - University Roma Tre.
• Riccardo Di Francesco, 2023. "Ordered Correlation Forest," Papers 2309.08755, arXiv.org.
  • Riccardo Di Francesco, 2024. "Ordered Correlation Forest," CEIS Research Paper 577, Tor Vergata University, CEIS, revised 06 May 2024.
• Chayanika Mitra, 2024. "Gender Bias in Education Expenditure among Religious and Social Groups: A Case Study for Below Class 10 Level in West Bengal," Arthaniti: Journal of Economic Theory and Practice, , vol. 23(1), pages 101-117, June.
• Christopher F. Baum & Hans Lööf & Andreas Stephan & Klaus F. Zimmermann, 2024. "Estimating the Wage Premia of Refugee Immigrants: Lessons from Sweden," ILR Review, Cornell University, ILR School, vol. 77(4), pages 562-597, August.
  • Christopher F. Baum & Hans Lööf & Andreas Stephan & Klaus F. Zimmermann, 2018. "Estimating the wage premia of refugee immigrants: Lessons from Sweden," Boston College Working Papers in Economics 963, Boston College Department of Economics, revised 29 May 2024.
  • Baum, Christopher F. & Lööf, Hans & Stephan, Andreas & Zimmermann, Klaus F., 2024. "Estimating the wage premia of refugee immigrants: Lessons from Sweden," GLO Discussion Paper Series 1400, Global Labor Organization (GLO).
  • Baum, Christopher F. & Lööf, Hans & Stephan, Andreas & Zimmermann, Klaus F., 2024. "Estimating the Wage Premia of Refugee Immigrants: Lessons from Sweden," Working Papers in Economics and Statistics 3/2024, Linnaeus University, School of Business and Economics, Department of Economics and Statistics.
  • Baum, Christopher F. & Lööf, Hans & Stephan, Andreas & Zimmermann, Klaus F., 2023. "Estimating the wage premia of refugee immigrants: Lessons from Sweden," Working Paper Series in Economics and Institutions of Innovation 496, Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies, revised 30 May 2024.
• Milen Arro-Cannarsa & Dr. Rolf Scheufele, 2024. "Nowcasting GDP: what are the gains from machine learning algorithms?," Working Papers 2024-06, Swiss National Bank.
• Francesco Audrino & Jessica Gentner & Simon Stalder, 2024. "Quantifying uncertainty: a new era of measurement through large language models," Working Papers 2024-12, Swiss National Bank.
• Gustavo Romero Cardoso & Marcio Issao Nakane, 2024. "What’s in a headline? News impact on the Brazilian economy," Working Papers, Department of Economics 2024_12, University of São Paulo (FEA-USP).
• Nikola Gradojevic & Dragan Kukolj, 2024. "Unlocking the black box: Non-parametric option pricing before and during COVID-19," Annals of Operations Research, Springer, vol. 334(1), pages 59-82, March.
• Marc-Aurèle Divernois & Damir Filipović, 2024. "StockTwits classified sentiment and stock returns," Digital Finance, Springer, vol. 6(2), pages 249-281, June.
• Axel Groß-Klußmann, 2024. "Learning deep news sentiment representations for macro-finance," Digital Finance, Springer, vol. 6(3), pages 341-377, September.
• Aleksandar Kešeljević & Rok Spruk, 2024. "Estimating the effects of Syrian civil war," Empirical Economics, Springer, vol. 66(2), pages 671-703, February.
  • Aleksandar Keseljevic & Rok Spruk, 2022. "Estimating the Effects of Syrian Civil War," Papers 2209.03046, arXiv.org.
• Massimiliano Caporin & C. Vladimir Rodríguez-Caballero & Esther Ruiz, 2024. "The factor structure of exchange rates volatility: global and intermittent factors," Empirical Economics, Springer, vol. 67(1), pages 31-45, July.
• André Nunes Maranhão, 2024. "Brazilian Business Cycle Analysis in a High-Dimensional and Time-Irregular Span Context," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 20(1), pages 1-58, August.
• Ferran Sancho, 2024. "Stone–Geary meets CES: the properties of an extended linear expenditure system," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 13(1), pages 1-11, December.
• Isaac K. Ofori & Camara K. Obeng & Simplice A. Asongu, 2024. "What Really Drives Economic Growth in Sub-Saharan Africa? Evidence from the Lasso Regularization and Inferential Techniques," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(1), pages 144-179, March.
  • Isaac K. Ofori & Camara K. Obeng & Simplice A. Asongu, 2022. "What Really Drives Economic Growth in Sub-Saharan Africa? Evidence from The Lasso Regularization and Inferential Techniques," Working Papers 22/061, European Xtramile Centre of African Studies (EXCAS).
  • Isaac K. Ofori & Camara K. Obeng & Simplice A. Asongu, 2022. "What Really Drives Economic Growth in Sub-Saharan Africa? Evidence from The Lasso Regularization and Inferential Techniques," Working Papers of the African Governance and Development Institute. 22/061, African Governance and Development Institute..
• Alkiviadis Panagopoulos & Ioannis A. Nikas, 2024. "Evaluation of Urban Landmarks Based on Primary and Secondary Points of Interest: The Case of Museums in the City of Athens in Greece," Springer Proceedings in Business and Economics, in: Vicky Katsoni & George Cassar (ed.), Recent Advancements in Tourism Business, Technology and Social Sciences, pages 639-652, Springer.
• Andre Rossi Oliveira, 2024. "Evaluating the Short-term Causal Effect of Early Alert on Student Performance," Research in Higher Education, Springer;Association for Institutional Research, vol. 65(7), pages 1395-1419, November.
• Philipp Wegmueller & Christian Glocker, 2024. "Capturing Swiss economic confidence," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 160(1), pages 1-17, December.
• Anne Darline Youmbi & Betrand Fesuh Nono & Christian Zamo Akono, 2024. "Inequality in opportunity of access to antenatal care in Cameroon: multilevel modelling, spatial analysis and decomposition methods," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 160(1), pages 1-17, December.
• Carlos Canizares Martinez & Arne Gieseck, 2024. "The effects of macro uncertainty shocks in the euro area: A FAVAR approach," Working and Discussion Papers WP 6/2024, Research Department, National Bank of Slovakia.
• Luke Hartigan & Tom Rosewall, 2024. "Nowcasting Quarterly GDP Growth during the COVID-19 Crisis Using a Monthly Activity Indicator," RBA Research Discussion Papers rdp2024-04, Reserve Bank of Australia.
  • Luke Hartigan & Tom Rosewall, 2024. "Nowcasting Quarterly GDP Growth during the COVID-19 Crisis Using a Monthly Activity Indicator," Working Papers 2024-15, University of Sydney, School of Economics.
• Salih Zeki Atilgan & Tarik Aydogdu & Mehmet Selman Colak & Muhammed Hasan Yilmaz, 2024. "Anticipating Credit Developments with Regularization and Shrinkage Methods: Evidence for Turkish Banking Industry," Working Papers 2402, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
• Christiane Baumeister & Danilo Leiva-León & Eric Sims, 2024. "Tracking Weekly State-Level Economic Conditions," The Review of Economics and Statistics, MIT Press, vol. 106(2), pages 483-504, March.
  • Christiane Baumeister & Danilo Leiva-León & Eric R. Sims, 2021. "Tracking Weekly State-Level Economic Conditions," NBER Working Papers 29003, National Bureau of Economic Research, Inc.
  • Christiane Baumeister & Danilo Leiva-Leon & Eric Sims, 2021. "Tracking Weekly State-Level Economic Conditions," Working Papers 202151, University of Pretoria, Department of Economics.
  • Christiane Baumeister & Danilo Leiva-León & Eric R. Sims, 2021. "Tracking Weekly State-Level Economic Conditions," CESifo Working Paper Series 9165, CESifo.
  • Baumeister, Christiane & Leiva-León, Danilo & Sims, Eric, 2021. "Tracking Weekly State-Level Economic Conditions," CEPR Discussion Papers 16317, C.E.P.R. Discussion Papers.
  • Christiane Baumeister & Danilo Leiva-León & Eric Sims, 2021. "Tracking weekly state-level economic conditions," Working Papers 2134, Banco de España.
  • Christiane Baumeister & Danilo Leiva-León & Eric Sims, 2021. "Tracking weekly state-level economic conditions," CAMA Working Papers 2021-55, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Tetiana Yukhymenko & Oleh Sorochan, 2024. "Impact of the Central Bank's Communication on Macrofinancial Outcomes," Working Papers 01/2024, National Bank of Ukraine.
• Hebdzyński Michał, 2024. "Are Hedonic Models Really Quality-Adjusted? The Role of Apartment Quality in Hedonic Models of Housing Rental Market," Real Estate Management and Valuation, Sciendo, vol. 32(2), pages 46-57.
• Adam Korniejczuk & Robert 'Slepaczuk, 2024. "Statistical arbitrage in multi-pair trading strategy based on graph clustering algorithms in US equities market," Papers 2406.10695, arXiv.org.
  • Adam Korniejczuk & Robert Ślepaczuk, 2024. "Statistical arbitrage in multi-pair trading strategy based on graph clustering algorithms in US equities market," Working Papers 2024-09, Faculty of Economic Sciences, University of Warsaw.
• Zuzanna Kostecka & Robert 'Slepaczuk, 2024. "Improving Realized LGD Approximation: A Novel Framework with XGBoost for Handling Missing Cash-Flow Data," Papers 2406.17308, arXiv.org.
  • Zuzanna Kostecka & Robert Ślepaczuk, 2024. "Improving Realized LGD approximation: A Novel Framework with XGBoost for handling missing cash-flow data," Working Papers 2024-12, Faculty of Economic Sciences, University of Warsaw.
• Natalia Roszyk & Robert 'Slepaczuk, 2024. "The Hybrid Forecast of S&P 500 Volatility ensembled from VIX, GARCH and LSTM models," Papers 2407.16780, arXiv.org.
  • Natalia Roszyk & Robert Ślepaczuk, 2024. "The Hybrid Forecast of S&P 500 Volatility ensembled from VIX, GARCH and LSTM models," Working Papers 2024-13, Faculty of Economic Sciences, University of Warsaw.
• Mahdi Ghodsi & Michael Landesmann & Nina Vujanović, 2024. "Can Multinationals Withstand Growing Trade Barriers?," wiiw Working Papers 239, The Vienna Institute for International Economic Studies, wiiw.
• Dylan Brewer & Alyssa Carlson, 2024. "Addressing sample selection bias for machine learning methods," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(3), pages 383-400, April.
  • Dylan Brewer & Alyssa Carlson, 2021. "Addressing Sample Selection Bias for Machine Learning Methods," Working Papers 2102, Department of Economics, University of Missouri.
  • Dylan Brewer & Alyssa Carlson, 2023. "Addressing Sample Selection Bias for Machine Learning Methods," Working Papers 2302, Department of Economics, University of Missouri.
  • Dylan Brewer & Alyssa Carlson, 2023. "Addressing Sample Selection Bias for Machine Learning Methods," Working Papers 2310, Department of Economics, University of Missouri.
  • Dylan Brewer & Alyssa Carlson, 2021. "Addressing Sample Selection Bias for Machine Learning Methods," Working Papers 2114, Department of Economics, University of Missouri.
• Thiemo Fetzer & Callum Shaw & Jacob Edenhofer, 2024. "Informational Boundaries of the State," ECONtribute Discussion Papers Series 282, University of Bonn and University of Cologne, Germany.
  • Fetzer, Thiemo & Shaw, Callum & Edenhofer, Jacob, 2024. "Informational Boundaries of the State," The Warwick Economics Research Paper Series (TWERPS) 1487, University of Warwick, Department of Economics.
  • Thiemo Fetzer & Callum Shaw & Jacob Edenhofer, 2024. "Informational Boundaries of the State," CESifo Working Paper Series 10901, CESifo.
  • Fetzer, Thiemo & Shaw, Callum & Edenhofer, Jacob, 2024. "Informational Boundaries of the State," CAGE Online Working Paper Series 697, Competitive Advantage in the Global Economy (CAGE).
• Li, Heng Ying, 2024. "Is buy-to-let still worthwhile? Estimating the impact of residential landlord tax reform on prices and demand of buy-to-let properties," Warwick-Monash Economics Student Papers 68, Warwick Monash Economics Student Papers.
• Asep Suryahadi & Arnita Rishanty & Robert Sparrow, 2024. "Social Capital and Economic Development in a Large and Multi-Ethnic Developing Country: Evidence from Indonesia," Asian Development Review (ADR), World Scientific Publishing Co. Pte. Ltd., vol. 41(02), pages 301-323, September.
• Jin Seo Cho & Peter C. B. Phillips, 2024. "GMM Estimation with Brownian Kernels Applied to Income Inequality Measurement," Cowles Foundation Discussion Papers 2411, Cowles Foundation for Research in Economics, Yale University.
  • Jin Seo Cho & Peter C.B. Phillips, 2024. "GMM Estimation with Brownian Kernels Applied to Income Inequality Measurement," Working papers 2024rwp-232, Yonsei University, Yonsei Economics Research Institute.
• Missbach, Leonard & Steckel, Jan Christoph, 2024. "Distributional impacts of climate policy and effective compensation: Evidence from 88 countries," EconStor Preprints 296491, ZBW - Leibniz Information Centre for Economics.
• Missbach, Leonard & Steckel, Jan Christoph & Renner, Sebastian & Kraus, Sebastian, 2024. "Coal-fired power plants and industrial development," EconStor Preprints 300209, ZBW - Leibniz Information Centre for Economics.
• Greyling, Talita & Rossouw, Stephanié, 2024. "Vaccination uptake, happiness and emotions: using a supervised machine learning approach," GLO Discussion Paper Series 1482, Global Labor Organization (GLO).
• Greyling, Talita & Rossouw, Stephanié, 2024. "Development and validation of a real-time happiness index using Google TrendsTM," GLO Discussion Paper Series 1493, Global Labor Organization (GLO).
• Büchel, Jan & Engler, Jan, 2024. "Generative KI in Deutschland: Künstliche Intelligenz in Gesellschaft und Unternehmen," IW-Reports 23/2024, Institut der deutschen Wirtschaft (IW) / German Economic Institute.
• Büchel, Jan & Monsef, Roschan, 2024. "Künstliche Intelligenz: Bessere Entlohnung durch Produktivitätsbooster? [Artificial Intelligence: Will boosted productivity lead to better pay?]," IW-Trends – Vierteljahresschrift zur empirischen Wirtschaftsforschung, Institut der deutschen Wirtschaft (IW) / German Economic Institute, vol. 51(2), pages 45-63.
• Latifi, Albina & Winker, Peter & Lenz, David, 2024. "Identification of innovation drivers based on technology-related news articles," VfS Annual Conference 2024 (Berlin): Upcoming Labor Market Challenges 302371, Verein für Socialpolitik / German Economic Association.

2023

• Hyeongwoo Kim & Jisoo Son, 2023. "Forecasting Net Charge-Off Rates of Large U.S. Bank Holding Companies using Macroeconomic Latent Factors," Auburn Economics Working Paper Series auwp2023-02, Department of Economics, Auburn University.
• Sarthak Behera & Hyeongwoo Kim & Soohyon Kim, 2023. "Superior Predictability of American Factors of the Dollar/Won Real Exchange Rate," Auburn Economics Working Paper Series auwp2023-05, Department of Economics, Auburn University.
• Kim, Hyeongwoo & Son, Jisoo, 2024. "What charge-off rates are predictable by macroeconomic latent factors?," Journal of Financial Stability, Elsevier, vol. 74(C).
  • Kim, Hyeongwoo & Son, Jisoo, 2023. "What Charge-Off Rates Are Predictable by Macroeconomic Latent Factors?," MPRA Paper 116880, University Library of Munich, Germany.
  • Hyeongwoo Kim & Jisoo Son, 2024. "What Charge-Off Rates Are Predictable by Macroeconomic Latent Factors?," Auburn Economics Working Paper Series auwp2024-01, Department of Economics, Auburn University.
  • Hyeongwoo Kim & Jisoo Son, 2023. "What Charge-Off Rates Are Predictable by Macroeconomic Latent Factors?," Auburn Economics Working Paper Series auwp2023-06, Department of Economics, Auburn University.
• Dorel Mihai Paraschiv & Narciz Balasoiu & Souhir Ben-Amor & Raul Cristian Bag, 2023. "Hybridising Neurofuzzy Model the Seasonal Autoregressive Models for Electricity Price Forecasting on Germany’s Spot Market," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 25(63), pages 463-463, April.
• Ovidiu-Ilie Stofor, 2023. "Quality Analysis Of Learning Improves The Quality Of Learning," Review of Economic and Business Studies, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, issue 31, pages 169-182, June.
• Sanjiv Das & Richard Stanton & Nancy Wallace, 2023. "Algorithmic Fairness," Annual Review of Financial Economics, Annual Reviews, vol. 15(1), pages 565-593, November.
• Elliott Ash & Stephen Hansen, 2023. "Text Algorithms in Economics," Annual Review of Economics, Annual Reviews, vol. 15(1), pages 659-688, September.
  • Ash, Elliott & Hansen, Stephen, 2023. "Text Algorithms in Economics," CEPR Discussion Papers 18125, C.E.P.R. Discussion Papers.
• Оливер де Грут // Oliver de Groot & Джозеф Конингс // Jozef Konings, 2023. "Инфляционное таргетирование, денежно-кредитная политика и возврат к таргетированию в Казахстане. // Inflation Targeting, Monetary Policy and the Transition Back to Target in Kazakhstan," Economic Review(National Bank of Kazakhstan), National Bank of Kazakhstan, issue 1 Special, pages 30-56.
• Муканов Н.С. // Mukanov N.S. & Алмагамбетов К.А. // Almagambetov K.A. & Джаржанов М.У. // Jarzhanov M.U. & Ильясов А.Б. // Ilyasov A.B., 2023. "Вопросы установления и достижения целевых ориентиров по инфляции. Выбор оптимальных характеристик цели по инфляции в Казахстане. // Setting and Achieving Inflation Targets. Choosing Optimal Characteri," Economic Review(National Bank of Kazakhstan), National Bank of Kazakhstan, issue 1 Special, pages 7-29.
• Оливер де Грут // Oliver de Groot & Джозеф Конингс // Jozef Konings, 2023. "Инфляционное таргетирование, денежно-кредитная политика и возврат к таргетированию в Казахстане. // Inflation Targeting, Monetary Policy and the Transition Back to Target in Kazakhstan," Economic Review(National Bank of Kazakhstan), National Bank of Kazakhstan, issue Special, pages 30-56.
• Муканов Н.С. // Mukanov N.S. & Алмагамбетов К.А. // Almagambetov K.A. & Джаржанов М.У. // Jarzhanov M.U. & Ильясов А.Б. // Ilyasov A.B., 2023. "Вопросы установления и достижения целевых ориентиров по инфляции. Выбор оптимальных характеристик цели по инфляции в Казахстане. // Setting and Achieving Inflation Targets. Choosing Optimal Characteri," Economic Review(National Bank of Kazakhstan), National Bank of Kazakhstan, issue Special, pages 7-29.
• Lukáš Bernat & Radka Michlová & Helena Mitwallyová, 2023. "Pattern classification on specifics of public sector investments and budgeting principles," International Journal of Economic Sciences, European Research Center, vol. 12(1), pages 15-37, May.
• Lukáš Bernat & Radka Michlová & Helena Mitwallyová, 2023. "Pattern classification on specifics of public sector investments and budgeting principles," International Journal of Economic Sciences, European Research Center, vol. 12(1), pages 31-53, May.
• Lukáš Bernat & Radka Michlová & Helena Mitwallyová, 2023. "Pattern classification on specifics of public sector investments and budgeting principles," International Journal of Economic Sciences, European Research Center, vol. 12(1), pages 32-54, May.
• Chan, Joshua C.C. & Poon, Aubrey & Zhu, Dan, 2023. "High-dimensional conditionally Gaussian state space models with missing data," Journal of Econometrics, Elsevier, vol. 236(1).
  • Joshua C. C. Chan & Aubrey Poon & Dan Zhu, 2023. "High-Dimensional Conditionally Gaussian State Space Models with Missing Data," Papers 2302.03172, arXiv.org.
• Bonsoo Koo & Benjamin Wong & Ze-Yu Zhong, 2023. "Disentangling Structural Breaks in High Dimensional Factor Models," CAMA Working Papers 2023-15, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Bonsoo Koo & Benjamin Wong & Ze-Yu Zhong, 2023. "Disentangling Structural Breaks in Factor Models for Macroeconomic Data," Papers 2303.00178, arXiv.org, revised Jun 2024.
• Ajit Desai, 2023. "Machine learning for economics research: when, what and how," Staff Analytical Notes 2023-16, Bank of Canada.
  • Ajit Desai, 2023. "Machine Learning for Economics Research: When What and How?," Papers 2304.00086, arXiv.org, revised Apr 2023.
• Riccardo Di Francesco, 2023. "Ordered Correlation Forest," Papers 2309.08755, arXiv.org.
  • Riccardo Di Francesco, 2024. "Ordered Correlation Forest," CEIS Research Paper 577, Tor Vergata University, CEIS, revised 06 May 2024.
• Clarke, Damian & Torres, Nicolás Paris & Villena-Roldan, Benjamin, 2023. "(Frisch-Waugh-Lovell)' On the Estimation of Regression Models by Row," IZA Discussion Papers 16630, Institute of Labor Economics (IZA).
  • Damian Clarke & Nicol'as Paris & Benjam'in Villena-Rold'an, 2023. "(Frisch-Waugh-Lovell)': On the Estimation of Regression Models by Row," Papers 2311.15829, arXiv.org.
• Alexander Chudik & M. Hashem Pesaran & Mahrad Sharifvaghefi, 2020. "Variable Selection in High Dimensional Linear Regressions with Parameter Instability," Globalization Institute Working Papers 394, Federal Reserve Bank of Dallas, revised 05 Aug 2024.
  • Alexander Chudik & M. Hashem Pesaran & Mahrad Sharifvaghefi, 2023. "Variable Selection in High Dimensional Linear Regressions with Parameter Instability," Papers 2312.15494, arXiv.org, revised Jul 2024.
  • Alexander Chudik & M. Hashem Pesaran & Mahrad Sharifvaghefi, 2023. "Variable Selection in High Dimensional Linear Regressions with Parameter Instability," CESifo Working Paper Series 10223, CESifo.
• DănuÅ£-Octavian SIMION, 2023. "Advanced Methods Of Including Classes And Objects In Application Modules Specific To Business Economic Systems," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 67(1), pages 35-43, March.
• Danut-Octavian SIMION, 2023. "The Support Given By Data Analysis In The Decision-Making Process In Interdependent Economic Systems," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 68(2), pages 17-29, September.
• Ferran Sancho, 2022. "Stone-Geary Meets CES: An Extended Linear Expenditure System," Working Papers 1328, Barcelona School of Economics.
  • Ferran Sancho, 2023. "Stone-Geary meets CES:An extended linear expenditure system," UFAE and IAE Working Papers 971.23, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
• Darab Molkabadi, Saeid, 2023. "Transition and Propagations of Oil Shock in the Oil Exporting Countries: Lessons from Iran (in Persian)," The Journal of Planning and Budgeting (٠صلنامه برنامه ریزی Ùˆ بودجه), Institute for Management and Planning studies, vol. 28(4), pages 111-139, December.
• Todor Krastevich, 2023. "Retargeting Customers Using Uplift Modeling," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 2, pages 78-99.
• Sonya Georgieva, 2023. "Application of Artificial Intelligence and Machine Learning in the Conduct of Monetary Policy by Central Banks," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 8, pages 177-199.
• Donald Coletti, 2023. "A Blueprint for the Fourth Generation of Bank of Canada Projection and Policy Analysis Models," Discussion Papers 2023-23, Bank of Canada.
• Lin Chen & Stephanie Houle, 2023. "Turning Words into Numbers: Measuring News Media Coverage of Shortages," Discussion Papers 2023-8, Bank of Canada.
• Stephanie Houle & Ryan Macdonald, 2023. "Identifying Nascent High-Growth Firms Using Machine Learning," Staff Working Papers 23-53, Bank of Canada.
• Ajit Desai, 2023. "Machine Learning for Economics Research: When What and How?," Papers 2304.00086, arXiv.org, revised Apr 2023.
  • Ajit Desai, 2023. "Machine learning for economics research: when, what and how," Staff Analytical Notes 2023-16, Bank of Canada.
• Marta Crispino & Vincenzo Mariani, 2023. "A tool to nowcast tourist overnight stays with payment data and complementary indicators," Questioni di Economia e Finanza (Occasional Papers) 746, Bank of Italy, Economic Research and International Relations Area.
• Crispino, Marta & Conteduca, Francesco Paolo, 2024. "It's a match! Linking foreign counterparts in Italian customs data to their balance sheets," International Economics, Elsevier, vol. 179(C).
  • Crispino Marta & Francesco Paolo Conteduca, 2023. "It's a match! Linking foreign counterparts in Italian customs data to their balance sheets," Questioni di Economia e Finanza (Occasional Papers) 823, Bank of Italy, Economic Research and International Relations Area.
• Juan Pablo Cote-Barón & Karen L. Pulido-Mahecha & Nicol Valeria Rodríguez-Rodríguez & Carlos D. Rojas-Martínez, 2023. "El ISAE: Un Indicador para Monitorear la Actividad Económica Colombiana en Alta Frecuencia," Borradores de Economia 1225, Banco de la Republica de Colombia.
• Menzie D. Chinn & Baptiste Meunier & Sebastian Stumpner, 2023. "Nowcasting World Trade with Machine Learning: a Three-Step Approach," NBER Working Papers 31419, National Bureau of Economic Research, Inc.
  • Menzie Chinn & Baptiste Meunier & Sebastian Stumpner, 2023. "Nowcasting World Trade with Machine Learning: a Three-Step Approach," Working papers 917, Banque de France.
  • Chinn, Menzie D. & Meunier, Baptiste & Stumpner, Sebastian, 2023. "Nowcasting world trade with machine learning: a three-step approach," Working Paper Series 2836, European Central Bank.
• Olivier De Bandt & Jean-Charles Bricongne & Julien Denes & Alexandre Dhenin & Annabelle De Gaye & Pierre-Antoine Robert, 2023. "Using the Press to Construct a New Indicator of Inflation Perceptions in France," Working papers 921, Banque de France.
• Konstantin Boss & Andre Groeger & Tobias Heidland & Finja Krueger & Conghan Zheng, 2023. "Forecasting Bilateral Refugee Flows with High-dimensional Data and Machine Learning Techniques," Working Papers 1387, Barcelona School of Economics.
• Pongpitch Amatyakul & Panchanok Jumrustanasan & Pornchanok Tapkham, 2023. "What can 20 billion financial transactions tell us about the impacts of Covid-19 fiscal transfers?," BIS Working Papers 1130, Bank for International Settlements.
• Anastasios Petropoulos & Evangelos Stavroulakis & Panagiotis Lazaris & Vasilis Siakoulis & Nikolaos Vlachogiannakis, 2023. "Is COVID-19 reflected in AnaCredit dataset? A big data - machine learning approach for analysing behavioural patterns using loan level granular information," Working Papers 315, Bank of Greece.
• Ryuichiro Hashimoto & Kakeru Miura & Yasunori Yoshizaki, 2023. "Application of Machine Learning to a Credit Rating Classification Model: Techniques for Improving the Explainability of Machine Learning," Bank of Japan Working Paper Series 23-E-6, Bank of Japan.
• Byrne, David & Goodhead, Robert & Mcmahon, Michael & Parle, Conor, 2023. "The Central Bank Crystal Ball: Temporal information in monetary policy communication," CEPR Discussion Papers 17930, C.E.P.R. Discussion Papers.
  • Byrne, David & Goodhead, Robert & McMahon, Michael & Parle, Conor, 2023. "The Central Bank Crystal Ball: Temporal information in monetary policy communication," Research Technical Papers 1/RT/23, Central Bank of Ireland.
• Byrne, David & Goodhead, Robert & Mcmahon, Michael & Parle, Conor, 2023. "Measuring the Temporal Dimension of Text: An Application to Policymaker Speeches," CEPR Discussion Papers 17931, C.E.P.R. Discussion Papers.
  • Byrne, David & Goodhead, Robert & McMahon, Michael & Parle, Conor, 2023. "Measuring the Temporal Dimension of Text: An Application to Policymaker Speeches," Research Technical Papers 2/RT/23, Central Bank of Ireland.
• Martha Cruz Zuniga & Dawit Senbet, 2023. "Does the Effectiveness of Monetary Policy Depend on the Choice of Policy Instrument? Empirical Evidence from South Korea," Journal of Central Banking Theory and Practice, Central bank of Montenegro, vol. 12(2), pages 239-265.
• Bloom, Nicholas & Davis, Steven J. & Hansen, Stephen & Lambert, Peter John & Sadun, Raffaella & Taska, Bledi, 2023. "Remote work across jobs, companies and space," LSE Research Online Documents on Economics 121302, London School of Economics and Political Science, LSE Library.
  • Nicholas Bloom & Steven J. Davis & Stephen Hansen & Peter Lambert & Raffaella Sadun & Bledi Taska, 2023. "Remote work across jobs, companies and space," CEP Discussion Papers dp1935, Centre for Economic Performance, LSE.
  • Stephen Hansen & Peter John Lambert & Nicholas Bloom & Steven J. Davis & Raffaella Sadun & Bledi Taska, 2023. "Remote Work across Jobs, Companies, and Space," NBER Working Papers 31007, National Bureau of Economic Research, Inc.
  • Hansen, Stephen & Lambert, Peter & Bloom, Nicholas & Davis, Steven & Sadun, Raffaella & Taska, Bledi, 2023. "Remote Work across Jobs, Companies, and Space," CEPR Discussion Papers 17964, C.E.P.R. Discussion Papers.
  • Nicholas Bloom & Steven J. Davis & Stephen Hansen & Peter Lambert & Raffaella Sadun & Bledi Taska, 2023. "Remote work across jobs, companies and space," POID Working Papers 067, Centre for Economic Performance, LSE.
  • Hansen, Stephen & Lambert, Peter John & Bloom, Nicholas & Davis, Steven J. & Sadun, Raffaella & Taska, Bledi, 2023. "Remote Work across Jobs, Companies, and Space," IZA Discussion Papers 15980, Institute of Labor Economics (IZA).
• Bloom, Nicholas & Davis, Steven J. & Hansen, Stephen & Lambert, Peter John & Sadun, Raffaella & Taska, Bledi, 2023. "Remote work across jobs, companies and space," LSE Research Online Documents on Economics 121302, London School of Economics and Political Science, LSE Library.
  • Nicholas Bloom & Steven J. Davis & Stephen Hansen & Peter Lambert & Raffaella Sadun & Bledi Taska, 2023. "Remote work across jobs, companies and space," POID Working Papers 067, Centre for Economic Performance, LSE.
  • Stephen Hansen & Peter John Lambert & Nicholas Bloom & Steven J. Davis & Raffaella Sadun & Bledi Taska, 2023. "Remote Work across Jobs, Companies, and Space," NBER Working Papers 31007, National Bureau of Economic Research, Inc.
  • Hansen, Stephen & Lambert, Peter & Bloom, Nicholas & Davis, Steven & Sadun, Raffaella & Taska, Bledi, 2023. "Remote Work across Jobs, Companies, and Space," CEPR Discussion Papers 17964, C.E.P.R. Discussion Papers.
  • Hansen, Stephen & Lambert, Peter John & Bloom, Nicholas & Davis, Steven J. & Sadun, Raffaella & Taska, Bledi, 2023. "Remote Work across Jobs, Companies, and Space," IZA Discussion Papers 15980, Institute of Labor Economics (IZA).
  • Nicholas Bloom & Steven J. Davis & Stephen Hansen & Peter Lambert & Raffaella Sadun & Bledi Taska, 2023. "Remote work across jobs, companies and space," CEP Discussion Papers dp1935, Centre for Economic Performance, LSE.
• Alexander Chudik & M. Hashem Pesaran & Mahrad Sharifvaghefi, 2020. "Variable Selection in High Dimensional Linear Regressions with Parameter Instability," Globalization Institute Working Papers 394, Federal Reserve Bank of Dallas, revised 05 Aug 2024.
  • Alexander Chudik & M. Hashem Pesaran & Mahrad Sharifvaghefi, 2023. "Variable Selection in High Dimensional Linear Regressions with Parameter Instability," CESifo Working Paper Series 10223, CESifo.
  • Alexander Chudik & M. Hashem Pesaran & Mahrad Sharifvaghefi, 2023. "Variable Selection in High Dimensional Linear Regressions with Parameter Instability," Papers 2312.15494, arXiv.org, revised Jul 2024.
• Donia Kamel & Laura Pollacci, 2023. "Academic Migration and Academic Networks: Evidence from Scholarly Big Data and the Iron Curtain," CESifo Working Paper Series 10377, CESifo.
• Anna Kerkhof & Valentin Reich, 2023. "Gender Stereotypes in User-Generated Content," CESifo Working Paper Series 10578, CESifo.
• Daniel Ershov & Yanting, He & Stephan Seiler, 2023. "How Much Influencer Marketing Is Undisclosed? Evidence from Twitter," CESifo Working Paper Series 10743, CESifo.
• Eugenia Gonzalez Ehlinger & Fabian Stephany, 2023. "Skills or Degree? The Rise of Skill-Based Hiring for AI and Green Jobs," CESifo Working Paper Series 10817, CESifo.
• Fetzer, Thiemo & Gazze, Ludovica & Bishop, Menna, 2023. "Distributional and climate implications of policy responses to energy price shocks," The Warwick Economics Research Paper Series (TWERPS) 1467, University of Warwick, Department of Economics.
  • Fetzer, Thiemo & Gazze, Ludovica & Bishop, Menna, 2023. "Distributional and climate implications of policy responses to energy price shocks," CAGE Online Working Paper Series 671, Competitive Advantage in the Global Economy (CAGE).
• Nicolas Camenzind & Damir Filipović, 2023. "Stripping the Swiss Discount Curve," Swiss Finance Institute Research Paper Series 23-97, Swiss Finance Institute.
• Espinosa, Oscar & Rodríguez, Jhonathan & Ávila, Diego & Rodríguez-Lesmes, Paul & Basto, Sergio & Romano, Giancarlo & Mesa, Lorena & Enríquez, Hernán, 2023. "The impact of updating health benefits plans on health technologies usage and expenditures: the case of Colombia," Documentos de Trabajo 20821, Universidad del Rosario.
• Sauvenier, Mathieu & Van Bellegem, Sébastien, 2023. "Direction Identification and Minimax Estimation by Generalized Eigenvalue Problem in High Dimensional Sparse Regression," LIDAM Discussion Papers CORE 2023005, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
• Marco Battaglini & Luigi Guiso & Chiara Lacava & Douglas L. Miller & Eleonora Patacchini, 2022. "Refining Public Policies with Machine Learning: The Case of Tax Auditing," NBER Working Papers 30777, National Bureau of Economic Research, Inc.
  • Battaglini, Marco & Guiso, Luigi & Lacava, Chiara & Miller , Douglas L. & Patacchini, Eleonora, 2023. "Refining Public Policies with Machine Learning: The Case of Tax Auditing," CEPR Discussion Papers 17796, C.E.P.R. Discussion Papers.
• Byrne, David & Goodhead, Robert & McMahon, Michael & Parle, Conor, 2023. "The Central Bank Crystal Ball: Temporal information in monetary policy communication," Research Technical Papers 1/RT/23, Central Bank of Ireland.
  • Byrne, David & Goodhead, Robert & Mcmahon, Michael & Parle, Conor, 2023. "The Central Bank Crystal Ball: Temporal information in monetary policy communication," CEPR Discussion Papers 17930, C.E.P.R. Discussion Papers.
• Byrne, David & Goodhead, Robert & McMahon, Michael & Parle, Conor, 2023. "Measuring the Temporal Dimension of Text: An Application to Policymaker Speeches," Research Technical Papers 2/RT/23, Central Bank of Ireland.
  • Byrne, David & Goodhead, Robert & Mcmahon, Michael & Parle, Conor, 2023. "Measuring the Temporal Dimension of Text: An Application to Policymaker Speeches," CEPR Discussion Papers 17931, C.E.P.R. Discussion Papers.
• O'Connell, Martin & Smith, Howard & Thomassen, Oyvind, 2023. "A two sample size estimator for large data sets," CEPR Discussion Papers 17941, C.E.P.R. Discussion Papers.
• Hansen, Stephen & Lambert, Peter John & Bloom, Nicholas & Davis, Steven J. & Sadun, Raffaella & Taska, Bledi, 2023. "Remote Work across Jobs, Companies, and Space," IZA Discussion Papers 15980, Institute of Labor Economics (IZA).
  • Hansen, Stephen & Lambert, Peter & Bloom, Nicholas & Davis, Steven & Sadun, Raffaella & Taska, Bledi, 2023. "Remote Work across Jobs, Companies, and Space," CEPR Discussion Papers 17964, C.E.P.R. Discussion Papers.
  • Nicholas Bloom & Steven J. Davis & Stephen Hansen & Peter Lambert & Raffaella Sadun & Bledi Taska, 2023. "Remote work across jobs, companies and space," CEP Discussion Papers dp1935, Centre for Economic Performance, LSE.
  • Bloom, Nicholas & Davis, Steven J. & Hansen, Stephen & Lambert, Peter John & Sadun, Raffaella & Taska, Bledi, 2023. "Remote work across jobs, companies and space," LSE Research Online Documents on Economics 121302, London School of Economics and Political Science, LSE Library.
  • Stephen Hansen & Peter John Lambert & Nicholas Bloom & Steven J. Davis & Raffaella Sadun & Bledi Taska, 2023. "Remote Work across Jobs, Companies, and Space," NBER Working Papers 31007, National Bureau of Economic Research, Inc.
  • Nicholas Bloom & Steven J. Davis & Stephen Hansen & Peter Lambert & Raffaella Sadun & Bledi Taska, 2023. "Remote work across jobs, companies and space," POID Working Papers 067, Centre for Economic Performance, LSE.
• Fetzer, Thiemo & Gazze, Ludovica & Bishop, Menna, 2022. "Distributional and climate implications of policy responses to the energy crisis: Lessons from the UK," CAGE Online Working Paper Series 644, Competitive Advantage in the Global Economy (CAGE).
  • Fetzer, Thiemo & Gazzè, Ludovica & Bishop, Menna, 2023. "Distributional and climate implications of policy responses to the energy crisis: Lessons from the UK," CEPR Discussion Papers 17990, C.E.P.R. Discussion Papers.
• Ash, Elliott & Hansen, Stephen, 2023. "Text Algorithms in Economics," CEPR Discussion Papers 18125, C.E.P.R. Discussion Papers.
• Ershov, Daniel & He, Yanting & Seiler, Stephan, 2023. "How Much Influencer Marketing is Undisclosed? Evidence from Twitter," CEPR Discussion Papers 18554, C.E.P.R. Discussion Papers.
• Paolo Andreini & Cosimo Izzo & Giovanni Ricco, 2020. "Deep Dynamic Factor Models," Papers 2007.11887, arXiv.org, revised May 2023.
  • Paolo Andreini & Cosimo Izzo & Giovanni Ricco, 2023. "Deep Dynamic Factor Models," Working Papers 2023-08, Center for Research in Economics and Statistics.
• J. van den Berg, Gerard & Kunaschk, Max & Lang, Julia & Stephan, Gesine & Uhlendorff, Arne, 2023. "Predicting re-employment: machine learning versus assessments by unemployed workers and by their caseworkers," Working Paper Series 2023:22, IFAU - Institute for Evaluation of Labour Market and Education Policy.
  • Gerard J. van den Berg & Max Kunaschk & Julia Lang & Gesine Stephan & Arne Uhlendorf, 2023. "Predicting Re-Employment: Machine Learning Versus Assessments by Unemployed Workers and by Their Caseworkers," Working Papers 2023-09, Center for Research in Economics and Statistics.
  • Berg, Gerard J. van den & Kunaschk, Max & Lang, Julia & Stephan, Gesine & Uhlendorff, Arne, 2024. "Predicting Re-Employment: Machine Learning Versus Assessments by Unemployed Workers and by Their Caseworkers," IAB-Discussion Paper 202403, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
  • van den Berg, Gerard J. & Kunaschk, Max & Lang, Julia & Stephan, Gesine & Uhlendorff, Arne, 2023. "Predicting Re-Employment: Machine Learning versus Assessments by Unemployed Workers and by Their Caseworkers," IZA Discussion Papers 16426, Institute of Labor Economics (IZA).
• Espasa, Antoni & Carlomagno Real, Guillermo, 2023. "Tall big data time series of high frequency: stylized facts and econometric modelling," DES - Working Papers. Statistics and Econometrics. WS 37746, Universidad Carlos III de Madrid. Departamento de Estadística.
• Bellocca, Gian Pietro Enzo & Alessi, Lucia & Poncela Blanco, Maria Pilar & Ruiz Ortega, Esther, 2023. "Effects of extreme temperature on the European equity market," DES - Working Papers. Statistics and Econometrics. WS 37973, Universidad Carlos III de Madrid. Departamento de Estadística.
• Fuwei Jiang & Wei Ning & Hao Xue, 2023. "Factor Timing with Investor Sentiment," Annals of Economics and Finance, Society for AEF, vol. 24(2), pages 401-437, November.
• Pfarrhofer, Michael, 2023. "Measuring International Uncertainty Using Global Vector Autoregressions with Drifting Parameters," Macroeconomic Dynamics, Cambridge University Press, vol. 27(3), pages 770-793, April.
  • Michael Pfarrhofer, 2019. "Measuring international uncertainty using global vector autoregressions with drifting parameters," Papers 1908.06325, arXiv.org, revised Dec 2019.
  • Pfarrhofer, Michael, 2019. "Measuring international uncertainty using global vector autoregressions with drifting parameters," Working Papers in Economics 2019-3, University of Salzburg.
• Heike Link & Dennis Gaus & Neil Murray & Maria Fernanda Guajardo Ortega & Flavien Gervois & Frederik von Waldow & Sofia Eigner, 2023. "Combining GPS Tracking and Surveys for a Mode Choice Model: Processing Data from a Quasi-Natural Experiment in Germany," Discussion Papers of DIW Berlin 2047, DIW Berlin, German Institute for Economic Research.
• Dorinth van Dijk & Jasper de Winter, 2023. "Nowcasting GDP using tone-adjusted time varying news topics: Evidence from the financial press," Working Papers 766, DNB.
• Hurlin, Christophe & Pérignon, Christophe, 2023. "Machine Learning and IRB Capital Requirements: Advantages, Risks, and Recommendations," HEC Research Papers Series 1480, HEC Paris.
• Emambakhsh, Tina & Fuchs, Maximilian & Kördel, Simon & Kouratzoglou, Charalampos & Lelli, Chiara & Pizzeghello, Riccardo & Salleo, Carmelo & Spaggiari, Martina, 2023. "The Road to Paris: stress testing the transition towards a net-zero economy," Occasional Paper Series 328, European Central Bank.
• Lelli, Chiara & Parisi, Laura & Heemskerk, Irene & Boldrini, Simone & Ceglar, Andrej, 2023. "Living in a world of disappearing nature: physical risk and the implications for financial stability," Occasional Paper Series 333, European Central Bank.
• Ceglar, Andrej & Boldrini, Simone & Lelli, Chiara & Parisi, Laura & Heemskerk, Irene, 2023. "The impact of the euro area economy and banks on biodiversity," Occasional Paper Series 335, European Central Bank.
• Horan, Aoife & Jarmulska, Barbara & Ryan, Ellen, 2023. "Asset prices, collateral and bank lending: the case of Covid-19 and real estate," Working Paper Series 2823, European Central Bank.
• Menzie D. Chinn & Baptiste Meunier & Sebastian Stumpner, 2023. "Nowcasting World Trade with Machine Learning: a Three-Step Approach," NBER Working Papers 31419, National Bureau of Economic Research, Inc.
  • Chinn, Menzie D. & Meunier, Baptiste & Stumpner, Sebastian, 2023. "Nowcasting world trade with machine learning: a three-step approach," Working Paper Series 2836, European Central Bank.
  • Menzie Chinn & Baptiste Meunier & Sebastian Stumpner, 2023. "Nowcasting World Trade with Machine Learning: a Three-Step Approach," Working papers 917, Banque de France.
• Jorge Barrientos Marin & Laura Marquez Marulanda & Fernando Villada Duque, 2023. "Analyzing Electricity Demand in Colombia: A Functional Time Series Approach," International Journal of Energy Economics and Policy, Econjournals, vol. 13(1), pages 75-84, January.
• Aiken, Emily L. & Bedoya, Guadalupe & Blumenstock, Joshua E. & Coville, Aidan, 2023. "Program targeting with machine learning and mobile phone data: Evidence from an anti-poverty intervention in Afghanistan," Journal of Development Economics, Elsevier, vol. 161(C).
• Camacho, Maximo & Caro, Angela & Peña, Daniel, 2023. "What drives industrial energy prices?," Economic Modelling, Elsevier, vol. 120(C).
• Rasciute, Simona & Downward, Paul & Simmons, Nick, 2023. "Valuation of subjective wellbeing and the role of marital status: Linear versus ordinal estimators," Economic Modelling, Elsevier, vol. 123(C).
• Mao Takongmo, Charles-O. & Touré, Adam, 2023. "Trade openness and connectedness of national productions: Do financial openness, economic specialization, and the size of the country matter?," Economic Modelling, Elsevier, vol. 125(C).
• Porras-Arena, M. Sylvina & Martín-Román, Ángel L., 2023. "The heterogeneity of Okun's law: A metaregression analysis," Economic Modelling, Elsevier, vol. 128(C).
  • Porras-Arena, M. Sylvina & Martín-Román, Ángel L., 2022. "The heterogeneity of Okun's law: A metaregression analysis," GLO Discussion Paper Series 1069, Global Labor Organization (GLO).
  • Porras, María Sylvina & Martín-Román, Ángel L., 2022. "The heterogeneity of Okun’s law: A metaregression analysis," MPRA Paper 112442, University Library of Munich, Germany.
• McKibbin, Warwick & Fernando, Roshen, 2023. "The global economic impacts of the COVID-19 pandemic," Economic Modelling, Elsevier, vol. 129(C).
• Yan, Wan-Lin, 2023. "Stock index futures price prediction using feature selection and deep learning," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
• Hayo, Bernd & Zahner, Johannes, 2023. "What is that noise? Analysing sentiment-based variation in central bank communication," Economics Letters, Elsevier, vol. 222(C).
• Agarwal, Shivam & Muckley, Cal B. & Neelakantan, Parvati, 2023. "Countering racial discrimination in algorithmic lending: A case for model-agnostic interpretation methods," Economics Letters, Elsevier, vol. 226(C).
• Fresoli, Diego & Poncela, Pilar & Ruiz, Esther, 2023. "Ignoring cross-correlated idiosyncratic components when extracting factors in dynamic factor models," Economics Letters, Elsevier, vol. 230(C).
• Berger, Tino & Morley, James & Wong, Benjamin, 2023. "Nowcasting the output gap," Journal of Econometrics, Elsevier, vol. 232(1), pages 18-34.
  • Tino Berger & James Morley & Benjamin Wong, 2020. "Nowcasting the output gap," CAMA Working Papers 2020-78, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Xiong, Ruoxuan & Pelger, Markus, 2023. "Large dimensional latent factor modeling with missing observations and applications to causal inference," Journal of Econometrics, Elsevier, vol. 233(1), pages 271-301.
  • Ruoxuan Xiong & Markus Pelger, 2019. "Large Dimensional Latent Factor Modeling with Missing Observations and Applications to Causal Inference," Papers 1910.08273, arXiv.org, revised Jan 2022.
• He, Yi & Jaidee, Sombut & Gao, Jiti, 2023. "Most powerful test against a sequence of high dimensional local alternatives," Journal of Econometrics, Elsevier, vol. 234(1), pages 151-177.
• Kueck, Jannis & Luo, Ye & Spindler, Martin & Wang, Zigan, 2023. "Estimation and inference of treatment effects with L2-boosting in high-dimensional settings," Journal of Econometrics, Elsevier, vol. 234(2), pages 714-731.
• Adamek, Robert & Smeekes, Stephan & Wilms, Ines, 2023. "Lasso inference for high-dimensional time series," Journal of Econometrics, Elsevier, vol. 235(2), pages 1114-1143.
  • Robert Adamek & Stephan Smeekes & Ines Wilms, 2020. "Lasso Inference for High-Dimensional Time Series," Papers 2007.10952, arXiv.org, revised Sep 2022.
• Lu, Xun & Su, Liangjun, 2023. "Uniform inference in linear panel data models with two-dimensional heterogeneity," Journal of Econometrics, Elsevier, vol. 235(2), pages 694-719.
• MacKinnon, James G., 2023. "Using large samples in econometrics," Journal of Econometrics, Elsevier, vol. 235(2), pages 922-926.
  • James G. MacKinnon, 2022. "Using Large Samples in Econometrics," Working Paper 1482, Economics Department, Queen's University.
• Chang, Jinyuan & Jiang, Qing & Shao, Xiaofeng, 2023. "Testing the martingale difference hypothesis in high dimension," Journal of Econometrics, Elsevier, vol. 235(2), pages 972-1000.
  • Jinyuan Chang & Qing Jiang & Xiaofeng Shao, 2022. "Testing the martingale difference hypothesis in high dimension," Papers 2209.04770, arXiv.org, revised Sep 2022.
• Chan, Joshua C.C. & Poon, Aubrey & Zhu, Dan, 2023. "High-dimensional conditionally Gaussian state space models with missing data," Journal of Econometrics, Elsevier, vol. 236(1).
  • Joshua C. C. Chan & Aubrey Poon & Dan Zhu, 2023. "High-Dimensional Conditionally Gaussian State Space Models with Missing Data," Papers 2302.03172, arXiv.org.
• Caner, Mehmet, 2023. "Generalized linear models with structured sparsity estimators," Journal of Econometrics, Elsevier, vol. 236(2).
  • Mehmet Caner, 2021. "Generalized Linear Models with Structured Sparsity Estimators," Papers 2104.14371, arXiv.org.
• Cheng, Mingmian & Liao, Yuan & Yang, Xiye, 2023. "Uniform predictive inference for factor models with instrumental and idiosyncratic betas," Journal of Econometrics, Elsevier, vol. 237(2).
• Bakalli, Gaetan & Guerrier, Stéphane & Scaillet, Olivier, 2023. "A penalized two-pass regression to predict stock returns with time-varying risk premia," Journal of Econometrics, Elsevier, vol. 237(2).
  • Gaetan Bakalli & Stéphane Guerrier & Olivier Scaillet, 2021. "A penalized two-pass regression to predict stock returns with time-varying risk premia," Swiss Finance Institute Research Paper Series 21-09, Swiss Finance Institute.
  • Gaetan Bakalli & Stéphane Guerrier & Olivier Scaillet, 2023. "A penalized two-pass regression to predict stock returns with time-varying risk premia," Post-Print hal-04325655, HAL.
  • Gaetan Bakalli & St'ephane Guerrier & Olivier Scaillet, 2022. "A penalized two-pass regression to predict stock returns with time-varying risk premia," Papers 2208.00972, arXiv.org.
• Lippi, Marco & Deistler, Manfred & Anderson, Brian, 2023. "High-Dimensional Dynamic Factor Models: A Selective Survey and Lines of Future Research," Econometrics and Statistics, Elsevier, vol. 26(C), pages 3-16.
• Hallin, Marc & Trucíos, Carlos, 2023. "Forecasting value-at-risk and expected shortfall in large portfolios: A general dynamic factor model approach," Econometrics and Statistics, Elsevier, vol. 27(C), pages 1-15.
• Rad, Hossein & Low, Rand Kwong Yew & Miffre, Joëlle & Faff, Robert, 2023. "The commodity risk premium and neural networks," Journal of Empirical Finance, Elsevier, vol. 74(C).
  • Joelle Miffre & Hossein Rad & Rand Kwong Yew Low & Robert Faff, 2023. "The commodity risk premium and neural networks," Post-Print hal-04322519, HAL.
• Favero, Filippo & Grossi, Luigi, 2023. "Analysis of individual natural gas consumption and price elasticity: Evidence from billing data in Italy," Energy Economics, Elsevier, vol. 118(C).
• Kraschewski, Tobias & Brauner, Tim & Heumann, Maximilian & Breitner, Michael H., 2023. "Disentangle the price dispersion of residential solar photovoltaic systems: Evidence from Germany," Energy Economics, Elsevier, vol. 121(C).
• Saâdaoui, Foued & Ben Jabeur, Sami, 2023. "Analyzing the influence of geopolitical risks on European power prices using a multiresolution causal neural network," Energy Economics, Elsevier, vol. 124(C).
• Okhrin, Yarema & Uddin, Gazi Salah & Yahya, Muhammad, 2023. "Nonlinear and asymmetric interconnectedness of crude oil with financial and commodity markets," Energy Economics, Elsevier, vol. 125(C).
• Kovvuri, Veera Raghava Reddy & Fu, Hsuan & Fan, Xiuyi & Seisenberger, Monika, 2023. "Fund performance evaluation with explainable artificial intelligence," Finance Research Letters, Elsevier, vol. 58(PB).
• Zhao, Chencheng & Yuan, Xianghui & Long, Jun & Jin, Liwei & Guan, Bowen, 2023. "Financial indicators analysis using machine learning: Evidence from Chinese stock market," Finance Research Letters, Elsevier, vol. 58(PD).
• Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2023. "Discovering the drivers of stock market volatility in a data-rich world," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
• Algaba, Andres & Borms, Samuel & Boudt, Kris & Verbeken, Brecht, 2023. "Daily news sentiment and monthly surveys: A mixed-frequency dynamic factor model for nowcasting consumer confidence," International Journal of Forecasting, Elsevier, vol. 39(1), pages 266-278.
  • Andres Algaba & Samuel Borms & Kris Boudt & Brecht Verbeken, 2021. "Daily news sentiment and monthly surveys: A mixed–frequency dynamic factor model for nowcasting consumer confidence," Working Paper Research 396, National Bank of Belgium.
• Aprigliano, Valentina & Emiliozzi, Simone & Guaitoli, Gabriele & Luciani, Andrea & Marcucci, Juri & Monteforte, Libero, 2023. "The power of text-based indicators in forecasting Italian economic activity," International Journal of Forecasting, Elsevier, vol. 39(2), pages 791-808.
  • Valentina Aprigliano & Simone Emiliozzi & Gabriele Guaitoli & Andrea Luciani & Juri Marcucci & Libero Monteforte, 2021. "The power of text-based indicators in forecasting the Italian economic activity," Temi di discussione (Economic working papers) 1321, Bank of Italy, Economic Research and International Relations Area.
• Borup, Daniel & Christensen, Bent Jesper & Mühlbach, Nicolaj Søndergaard & Nielsen, Mikkel Slot, 2023. "Targeting predictors in random forest regression," International Journal of Forecasting, Elsevier, vol. 39(2), pages 841-868.
  • Daniel Borup & Bent Jesper Christensen & Nicolaj N{o}rgaard Muhlbach & Mikkel Slot Nielsen, 2020. "Targeting predictors in random forest regression," Papers 2004.01411, arXiv.org, revised Nov 2020.
  • Daniel Borup & Bent Jesper Christensen & Nicolaj N. Mühlbach & Mikkel S. Nielsen, 2020. "Targeting predictors in random forest regression," CREATES Research Papers 2020-03, Department of Economics and Business Economics, Aarhus University.
• James, Robert & Leung, Henry & Prokhorov, Artem, 2023. "A machine learning attack on illegal trading," Journal of Banking & Finance, Elsevier, vol. 148(C).
• Krivorotov, George, 2023. "Machine learning-based profit modeling for credit card underwriting - implications for credit risk," Journal of Banking & Finance, Elsevier, vol. 149(C).
• Schilpzand, Annemiek & de Jong, Eelke, 2023. "Do market societies undermine civic morality? An empirical investigation into market societies and civic morality across the globe," Journal of Economic Behavior & Organization, Elsevier, vol. 208(C), pages 39-60.
• Fe, Hao, 2023. "Social networks and consumer behavior: Evidence from Yelp," Journal of Economic Behavior & Organization, Elsevier, vol. 209(C), pages 1-14.
• Qiu, Yue & Xie, Tian & Xie, Wenjing & Zheng, Xiangzhong, 2023. "Federal policy announcements and capital reallocation: Insights from inflow and outflow trends in the U.S," Journal of International Money and Finance, Elsevier, vol. 139(C).
• Schade, Philipp & Schuhmacher, Monika C., 2023. "Predicting entrepreneurial activity using machine learning," Journal of Business Venturing Insights, Elsevier, vol. 19(C).
• Zhao, Jing, 2023. "Time-varying impact of geopolitical risk on natural resources prices: Evidence from the hybrid TVP-VAR model with large system," Resources Policy, Elsevier, vol. 82(C).
• Vieira, Duarte Saldanha & Carvalho, Paulo Viegas de & Curto, José Dias & Laureano, Luís, 2023. "Gold's hedging and safe haven properties for European stock and bond markets," Resources Policy, Elsevier, vol. 85(PA).
• Foglia, Matteo & Palomba, Giulio & Tedeschi, Marco, 2023. "Disentangling the geopolitical risk and its effects on commodities. Evidence from a panel of G8 countries," Resources Policy, Elsevier, vol. 85(PB).
• Araujo, Gustavo Silva & Gaglianone, Wagner Piazza, 2023. "Machine learning methods for inflation forecasting in Brazil: New contenders versus classical models," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 4(2).
  • Gustavo Silva Araujo & Wagner Piazza Gaglianone, 2022. "Machine Learning Methods for Inflation Forecasting in Brazil: new contenders versus classical models," Working Papers Series 561, Central Bank of Brazil, Research Department.
• Meeks, Roland & Monti, Francesca, 2023. "Heterogeneous beliefs and the Phillips curve," Journal of Monetary Economics, Elsevier, vol. 139(C), pages 41-54.
  • Meeks, Roland & Monti, Francesca, 2019. "Heterogeneous beliefs and the Phillips curve," Bank of England working papers 807, Bank of England.
  • Roland Meeks & Francesca Monti, 2022. "Heterogeneous Beliefs and the Phillips Curve," CAMA Working Papers 2022-51, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Meeks, Roland & Monti, Francesca, 2022. "Heterogeneous beliefs and the Phillips curve," CEPR Discussion Papers 17537, C.E.P.R. Discussion Papers.
• Auer, Benjamin R. & Schuhmacher, Frank & Niemann, Sebastian, 2023. "Cloning mutual fund returns," The Quarterly Review of Economics and Finance, Elsevier, vol. 90(C), pages 31-37.
• Arendt, Lukasz & Gałecka-Burdziak, Ewa & Núñez, Fernando & Pater, Robert & Usabiaga, Carlos, 2023. "Skills requirements across task-content groups in Poland: What online job offers tell us," Technological Forecasting and Social Change, Elsevier, vol. 187(C).
• Bonsoo Koo & Benjamin Wong & Ze-Yu Zhong, 2023. "Disentangling Structural Breaks in Factor Models for Macroeconomic Data," Papers 2303.00178, arXiv.org, revised Jun 2024.
  • Bonsoo Koo & Benjamin Wong & Ze-Yu Zhong, 2023. "Disentangling Structural Breaks in High Dimensional Factor Models," CAMA Working Papers 2023-15, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Caterina Lepore & Roshen Fernando, 2023. "Global Economic Impacts of Physical Climate Risks," IMF Working Papers 2023/183, International Monetary Fund.
  • Roshen Fernando & Caterina Lepore, 2023. "Global Economic Impacts of Physical Climate Risks," CAMA Working Papers 2023-50, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Roshen Fernando, 2023. "Impact of Demographic Trends on Antimicrobial Resistance," CAMA Working Papers 2023-60, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Roshen Fernando, 2023. "Impact of Physical Climate Risks on Antimicrobial Resistance," CAMA Working Papers 2023-61, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Elaheh Fatemi Pour & Seyed Ali Madnanizdeh & Hosein Joshaghani, 2023. "Accept or reject a ride? This is the problem," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 50(7), pages 1346-1374, January.
• Paulo Rogério Faustino Matos & Felipe Bastos & Hecirlane Martins & Leilyanne Viana, 2023. "On the cross-city growth drivers of the most vulnerable region of Brazil," Journal of Financial Economic Policy, Emerald Group Publishing Limited, vol. 15(2), pages 77-103, January.
• Michael D. Plante, 2023. "Investing in the Batteries and Vehicles of the Future: A View Through the Stock Market," Working Papers 2314, Federal Reserve Bank of Dallas, revised 25 Mar 2024.
• Andrea Ajello & Diego Silva & Travis Adams & Francisco Vazquez-Grande, 2023. "More than Words: Twitter Chatter and Financial Market Sentiment," Finance and Economics Discussion Series 2023-034, Board of Governors of the Federal Reserve System (U.S.).
• Mary Chen & Matthew DeHaven & Isabel Kitschelt & Seung Jung Lee & Martin Sicilian, 2023. "Identifying Financial Crises Using Machine Learning on Textual Data," International Finance Discussion Papers 1374, Board of Governors of the Federal Reserve System (U.S.).
• Katie Baker & Martín Almuzara & Hannah O’Keeffe & Argia M. Sbordone, 2023. "Reintroducing the New York Fed Staff Nowcast," Liberty Street Economics 20230908, Federal Reserve Bank of New York.
• Anna I. Denisova & Dzhamilya A. Sozaeva & Konstantin V. Gonchar & Griegory A. Aleksandrov, 2023. "Improving the Methodology for Assessing the Economic Efficiency of Public E-procurement of Medicines," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 4, pages 63-81, August.
• James T. E. Chapman & Ajit Desai, 2023. "Macroeconomic Predictions Using Payments Data and Machine Learning," Forecasting, MDPI, vol. 5(4), pages 1-32, November.
  • James T. E. Chapman & Ajit Desai, 2022. "Macroeconomic Predictions using Payments Data and Machine Learning," Papers 2209.00948, arXiv.org.
  • James Chapman & Ajit Desai, 2022. "Macroeconomic Predictions Using Payments Data and Machine Learning," Staff Working Papers 22-10, Bank of Canada.
• Mihnea Constantinescu, 2023. "Sparse Warcasting," IHEID Working Papers 15-2023, Economics Section, The Graduate Institute of International Studies, revised 02 Oct 2023.
• Laurent Ferrara & Anna Simoni, 2023. "When are Google Data Useful to Nowcast GDP? An Approach via Preselection and Shrinkage," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(4), pages 1188-1202, October.
  • Laurent Ferrara & Anna Simoni, 2019. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working Papers 2019-04, Center for Research in Economics and Statistics.
  • Laurent Ferrara & Anna Simoni, 2023. "When are Google Data Useful to Nowcast GDP? An Approach via Preselection and Shrinkage," Post-Print hal-03919944, HAL.
  • Laurent Ferrara & Anna Simoni, 2020. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," EconomiX Working Papers 2020-11, University of Paris Nanterre, EconomiX.
  • Laurent Ferrara & Anna Simoni, 2019. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working papers 717, Banque de France.
  • Laurent Ferrara & Anna Simoni, 2020. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Papers 2007.00273, arXiv.org, revised Sep 2022.
  • Laurent Ferrara & Anna Simoni, 2020. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working Papers hal-04159714, HAL.
• Rad, Hossein & Low, Rand Kwong Yew & Miffre, Joëlle & Faff, Robert, 2023. "The commodity risk premium and neural networks," Journal of Empirical Finance, Elsevier, vol. 74(C).
  • Joelle Miffre & Hossein Rad & Rand Kwong Yew Low & Robert Faff, 2023. "The commodity risk premium and neural networks," Post-Print hal-04322519, HAL.
• Bakalli, Gaetan & Guerrier, Stéphane & Scaillet, Olivier, 2023. "A penalized two-pass regression to predict stock returns with time-varying risk premia," Journal of Econometrics, Elsevier, vol. 237(2).
  • Gaetan Bakalli & Stéphane Guerrier & Olivier Scaillet, 2021. "A penalized two-pass regression to predict stock returns with time-varying risk premia," Swiss Finance Institute Research Paper Series 21-09, Swiss Finance Institute.
  • Gaetan Bakalli & Stéphane Guerrier & Olivier Scaillet, 2023. "A penalized two-pass regression to predict stock returns with time-varying risk premia," Post-Print hal-04325655, HAL.
  • Gaetan Bakalli & St'ephane Guerrier & Olivier Scaillet, 2022. "A penalized two-pass regression to predict stock returns with time-varying risk premia," Papers 2208.00972, arXiv.org.
• Christopher F. Baum & Hans Lööf & Andreas Stephan & Klaus F. Zimmermann, 2024. "Estimating the Wage Premia of Refugee Immigrants: Lessons from Sweden," ILR Review, Cornell University, ILR School, vol. 77(4), pages 562-597, August.
  • Christopher F. Baum & Hans Lööf & Andreas Stephan & Klaus F. Zimmermann, 2018. "Estimating the wage premia of refugee immigrants: Lessons from Sweden," Boston College Working Papers in Economics 963, Boston College Department of Economics, revised 29 May 2024.
  • Baum, Christopher F. & Lööf, Hans & Stephan, Andreas & Zimmermann, Klaus F., 2023. "Estimating the wage premia of refugee immigrants: Lessons from Sweden," Working Paper Series in Economics and Institutions of Innovation 496, Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies, revised 30 May 2024.
  • Baum, Christopher F. & Lööf, Hans & Stephan, Andreas & Zimmermann, Klaus F., 2024. "Estimating the Wage Premia of Refugee Immigrants: Lessons from Sweden," Working Papers in Economics and Statistics 3/2024, Linnaeus University, School of Business and Economics, Department of Economics and Statistics.
  • Baum, Christopher F. & Lööf, Hans & Stephan, Andreas & Zimmermann, Klaus F., 2024. "Estimating the wage premia of refugee immigrants: Lessons from Sweden," GLO Discussion Paper Series 1400, Global Labor Organization (GLO).
• van den Berg, Gerard J. & Kunaschk, Max & Lang, Julia & Stephan, Gesine & Uhlendorff, Arne, 2023. "Predicting Re-Employment: Machine Learning versus Assessments by Unemployed Workers and by Their Caseworkers," IZA Discussion Papers 16426, Institute of Labor Economics (IZA).
  • J. van den Berg, Gerard & Kunaschk, Max & Lang, Julia & Stephan, Gesine & Uhlendorff, Arne, 2023. "Predicting re-employment: machine learning versus assessments by unemployed workers and by their caseworkers," Working Paper Series 2023:22, IFAU - Institute for Evaluation of Labour Market and Education Policy.
  • Gerard J. van den Berg & Max Kunaschk & Julia Lang & Gesine Stephan & Arne Uhlendorf, 2023. "Predicting Re-Employment: Machine Learning Versus Assessments by Unemployed Workers and by Their Caseworkers," Working Papers 2023-09, Center for Research in Economics and Statistics.
  • Berg, Gerard J. van den & Kunaschk, Max & Lang, Julia & Stephan, Gesine & Uhlendorff, Arne, 2024. "Predicting Re-Employment: Machine Learning Versus Assessments by Unemployed Workers and by Their Caseworkers," IAB-Discussion Paper 202403, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
• O’Connell, Martin & Smith, Howard & Thomassen, Øyvind, 2023. "A two sample size estimator for large data sets," Discussion Papers 2023/1, Norwegian School of Economics, Department of Business and Management Science.
• César Pérez López & María Jesús Delgado Rodríguez & Sonia de Lucas Santos, 2023. "Modelización de los factores que afectan al fraude fiscal con técnicas de minería de datos: aplicación al Impuesto de la Renta en España," Hacienda Pública Española / Review of Public Economics, IEF, vol. 246(3), pages 137-164, September.
• Heiko Stüber & Wolfgang Dauth & Johann Eppelsheimer, 2023. "A guide to preparing the sample of integrated labour market biographies (SIAB, version 7519 v1) for scientific analysis," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 57(1), pages 1-11, December.
  • Stüber, Heiko & Dauth, Wolfgang & Eppelsheimer, Johann, 2023. "A guide to preparing the sample of integrated labour market biographies (SIAB, version 7519 v1) for scientific analysis," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 57, pages 1-7.
• Oleksandr Lutsii & Oleksandr Helevei, 2023. "Formation of Components of the Marketing Information System for Agricultural Products Using Big Data Methods," Oblik i finansi, Institute of Accounting and Finance, issue 3, pages 145-150, September.
• Oleksandr LutsiÑ– & Oleksandr Helevei, 2023. "Formation of Components of the Marketing Information System for Agricultural Products Using Big Data Methods," Oblik i finansi, Institute of Accounting and Finance, issue 3, pages 145-151, September.
• Marra de Artiñano, Ignacio & Riottini Depetris, Franco & Volpe Martincus, Christian, 2023. "Automatic Product Classification in International Trade: Machine Learning and Large Language Models," IDB Publications (Working Papers) 12962, Inter-American Development Bank.
• Tatiana Evdokimova & Piroska Nagy Mohacsi & Olga Ponomarenko & Elina Ribakova, 2023. "Central banks and policy communication: How emerging markets have outperformed the Fed and ECB," Working Paper Series WP23-10, Peterson Institute for International Economics.
• Nguyen, Ha Minh, 2024. "Beyond the annual averages: Impact of seasonal temperature on employment growth in US counties," Journal of Environmental Economics and Management, Elsevier, vol. 125(C).
  • Ha Nguyen, 2023. "Beyond the Annual Averages: Impact of Seasonal Temperature on Employment Growth in US Counties," IMF Working Papers 2023/142, International Monetary Fund.
• Roshen Fernando & Caterina Lepore, 2023. "Global Economic Impacts of Physical Climate Risks," CAMA Working Papers 2023-50, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Caterina Lepore & Roshen Fernando, 2023. "Global Economic Impacts of Physical Climate Risks," IMF Working Papers 2023/183, International Monetary Fund.
• Nicodemo, Catia & Orso, Cristina E. & Tealdi, Cristina, 2023. "Overseas GPs and Prescription Behaviour in England," IZA Discussion Papers 15884, Institute of Labor Economics (IZA).
• Nicholas Bloom & Steven J. Davis & Stephen Hansen & Peter Lambert & Raffaella Sadun & Bledi Taska, 2023. "Remote work across jobs, companies and space," POID Working Papers 067, Centre for Economic Performance, LSE.
  • Hansen, Stephen & Lambert, Peter John & Bloom, Nicholas & Davis, Steven J. & Sadun, Raffaella & Taska, Bledi, 2023. "Remote Work across Jobs, Companies, and Space," IZA Discussion Papers 15980, Institute of Labor Economics (IZA).
  • Hansen, Stephen & Lambert, Peter & Bloom, Nicholas & Davis, Steven & Sadun, Raffaella & Taska, Bledi, 2023. "Remote Work across Jobs, Companies, and Space," CEPR Discussion Papers 17964, C.E.P.R. Discussion Papers.
  • Nicholas Bloom & Steven J. Davis & Stephen Hansen & Peter Lambert & Raffaella Sadun & Bledi Taska, 2023. "Remote work across jobs, companies and space," CEP Discussion Papers dp1935, Centre for Economic Performance, LSE.
  • Bloom, Nicholas & Davis, Steven J. & Hansen, Stephen & Lambert, Peter John & Sadun, Raffaella & Taska, Bledi, 2023. "Remote work across jobs, companies and space," LSE Research Online Documents on Economics 121302, London School of Economics and Political Science, LSE Library.
  • Stephen Hansen & Peter John Lambert & Nicholas Bloom & Steven J. Davis & Raffaella Sadun & Bledi Taska, 2023. "Remote Work across Jobs, Companies, and Space," NBER Working Papers 31007, National Bureau of Economic Research, Inc.
• J. van den Berg, Gerard & Kunaschk, Max & Lang, Julia & Stephan, Gesine & Uhlendorff, Arne, 2023. "Predicting re-employment: machine learning versus assessments by unemployed workers and by their caseworkers," Working Paper Series 2023:22, IFAU - Institute for Evaluation of Labour Market and Education Policy.
  • van den Berg, Gerard J. & Kunaschk, Max & Lang, Julia & Stephan, Gesine & Uhlendorff, Arne, 2023. "Predicting Re-Employment: Machine Learning versus Assessments by Unemployed Workers and by Their Caseworkers," IZA Discussion Papers 16426, Institute of Labor Economics (IZA).
  • Berg, Gerard J. van den & Kunaschk, Max & Lang, Julia & Stephan, Gesine & Uhlendorff, Arne, 2024. "Predicting Re-Employment: Machine Learning Versus Assessments by Unemployed Workers and by Their Caseworkers," IAB-Discussion Paper 202403, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
  • Gerard J. van den Berg & Max Kunaschk & Julia Lang & Gesine Stephan & Arne Uhlendorf, 2023. "Predicting Re-Employment: Machine Learning Versus Assessments by Unemployed Workers and by Their Caseworkers," Working Papers 2023-09, Center for Research in Economics and Statistics.
• Damian Clarke & Nicol'as Paris & Benjam'in Villena-Rold'an, 2023. "(Frisch-Waugh-Lovell)': On the Estimation of Regression Models by Row," Papers 2311.15829, arXiv.org.
  • Clarke, Damian & Torres, Nicolás Paris & Villena-Roldan, Benjamin, 2023. "(Frisch-Waugh-Lovell)' On the Estimation of Regression Models by Row," IZA Discussion Papers 16630, Institute of Labor Economics (IZA).
• Baumgartner Christoph & Srhoj Stjepan & Walde Janette, 2023. "Harmonization of Product Classifications: A Consistent Time Series of Economic Trade Activities," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 243(6), pages 643-662, December.
  • Christoph Baumgartner & Stjepan Srhoj & Janette F. Walde, 2022. "Harmonization of product classifications: A consistent time series of economic trade activities," Working Papers 2022-11, Faculty of Economics and Statistics, Universität Innsbruck.
• Becker, Annette & Di Girolamo, Francesca & Rho, Caterina, 2023. "Loan pricing and biodiversity exposure: Nature-related spillovers to the financial sector," Working Papers 2023-11, Joint Research Centre, European Commission.
• Barbaglia, Luca & Fatica, Serena & Rho, Caterina, 2023. "Flooded credit markets: physical climate risk and small business lending," Working Papers 2023-14, Joint Research Centre, European Commission.
  • Luca Barbaglia & Serena Fatica & Caterina Rho, 2024. "Flooded credit markets: physical climate risk and small business lending," Mo.Fi.R. Working Papers 186, Money and Finance Research group (Mo.Fi.R.) - Univ. Politecnica Marche - Dept. Economic and Social Sciences.
• Jan G. De Gooijer, 2023. "Penalized Averaging of Quantile Forecasts from GARCH Models with Many Exogenous Predictors," Computational Economics, Springer;Society for Computational Economics, vol. 62(1), pages 407-424, June.
• Ba Chu & Shafiullah Qureshi, 2023. "Comparing Out-of-Sample Performance of Machine Learning Methods to Forecast U.S. GDP Growth," Computational Economics, Springer;Society for Computational Economics, vol. 62(4), pages 1567-1609, December.
  • Ba Chu & Shafiullah Qureshi, 2021. "Comparing Out-of-Sample Performance of Machine Learning Methods to Forecast U.S. GDP Growth," Carleton Economic Papers 21-12, Carleton University, Department of Economics.
• Victoria Ateca-Amestoy & Concetta Castiglione, 2023. "Live and digital engagement with the visual arts," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 47(4), pages 643-692, December.
• Ateeb Akhter Shah Syed & Hassan Raza & Mohsin Waheed, 2023. "Easydata-MD: A Monthly Dataset for Macroeconomic Research on Pakistan," Lahore Journal of Economics, Department of Economics, The Lahore School of Economics, vol. 28(1), pages 63-88, Jan-June.
• Bo Zhang & Jiti Gao & Guangming Pan & Yanrong Yang, 2023. "Eigen-Analysis for High-Dimensional Time Series Clustering," Monash Econometrics and Business Statistics Working Papers 22/23, Monash University, Department of Econometrics and Business Statistics.
• Kris Boud & Arno De Block & Geert Langenus & Peter Reusens, 2023. "Nowcasting GDP through the lens of economic states," Working Paper Research 445, National Bank of Belgium.
• Hansen, Stephen & Lambert, Peter John & Bloom, Nicholas & Davis, Steven J. & Sadun, Raffaella & Taska, Bledi, 2023. "Remote Work across Jobs, Companies, and Space," IZA Discussion Papers 15980, Institute of Labor Economics (IZA).
  • Stephen Hansen & Peter John Lambert & Nicholas Bloom & Steven J. Davis & Raffaella Sadun & Bledi Taska, 2023. "Remote Work across Jobs, Companies, and Space," NBER Working Papers 31007, National Bureau of Economic Research, Inc.
  • Hansen, Stephen & Lambert, Peter & Bloom, Nicholas & Davis, Steven & Sadun, Raffaella & Taska, Bledi, 2023. "Remote Work across Jobs, Companies, and Space," CEPR Discussion Papers 17964, C.E.P.R. Discussion Papers.
  • Nicholas Bloom & Steven J. Davis & Stephen Hansen & Peter Lambert & Raffaella Sadun & Bledi Taska, 2023. "Remote work across jobs, companies and space," CEP Discussion Papers dp1935, Centre for Economic Performance, LSE.
  • Bloom, Nicholas & Davis, Steven J. & Hansen, Stephen & Lambert, Peter John & Sadun, Raffaella & Taska, Bledi, 2023. "Remote work across jobs, companies and space," LSE Research Online Documents on Economics 121302, London School of Economics and Political Science, LSE Library.
  • Nicholas Bloom & Steven J. Davis & Stephen Hansen & Peter Lambert & Raffaella Sadun & Bledi Taska, 2023. "Remote work across jobs, companies and space," POID Working Papers 067, Centre for Economic Performance, LSE.
• Bryan T. Kelly & Dacheng Xiu, 2023. "Financial Machine Learning," NBER Working Papers 31502, National Bureau of Economic Research, Inc.
• Bryan S. Graham & Andrin Pelican, 2023. "Scenario Sampling for Large Supermodular Games," NBER Working Papers 31511, National Bureau of Economic Research, Inc.
• Emily Aiken & Suzanne Bellue & Joshua Blumenstock & Dean Karlan & Christopher R. Udry, 2023. "Estimating Impact with Surveys versus Digital Traces: Evidence from Randomized Cash Transfers in Togo," NBER Working Papers 31751, National Bureau of Economic Research, Inc.
• Bryan T. Kelly & Semyon Malamud & Mohammad Pourmohammadi & Fabio Trojani, 2023. "Universal Portfolio Shrinkage," NBER Working Papers 32004, National Bureau of Economic Research, Inc.
• Dzyuba, Yu. & Bakalova, I., 2023. "CGE models for resource-based economy: A comprehensive bibliometric analysis," Journal of the New Economic Association, New Economic Association, vol. 61(4), pages 12-50.
• C. Welter-Medee & S.Quantin, 2023. "Estimate of hidden activity for the 2020 benchmark revision of national accounts," Documents de Travail de l'Insee - INSEE Working Papers 2023-18, Institut National de la Statistique et des Etudes Economiques.
• Sina Smid, 2023. "Understanding cultural differences and extreme attitudes in the 2021 OECD Trust Survey: Text analysis of open-ended responses," OECD Working Papers on Public Governance 57, OECD Publishing.
• Rachida Ouysse, 2023. "Asset Pricing with Endogenous Beliefs-Dependent Risk Aversion," Journal of Financial Econometrics, Oxford University Press, vol. 21(2), pages 368-411.
• Dillon Huddleston & Fred Liu & Lars Stentoft, 2023. "Intraday Market Predictability: A Machine Learning Approach," Journal of Financial Econometrics, Oxford University Press, vol. 21(2), pages 485-527.
• Luca Barbaglia & Sebastiano Manzan & Elisa Tosetti, 2023. "Forecasting Loan Default in Europe with Machine Learning," Journal of Financial Econometrics, Oxford University Press, vol. 21(2), pages 569-596.
• Alain Hecq & Luca Margaritella & Stephan Smeekes, 2023. "Granger Causality Testing in High-Dimensional VARs: A Post-Double-Selection Procedure," Journal of Financial Econometrics, Oxford University Press, vol. 21(3), pages 915-958.
  • Alain Hecq & Luca Margaritella & Stephan Smeekes, 2019. "Granger Causality Testing in High-Dimensional VARs: a Post-Double-Selection Procedure," Papers 1902.10991, arXiv.org, revised Dec 2020.
• Ye ChenCapital & Peter C B Phillips & Shuping Shi, 2023. "Common Bubble Detection in Large Dimensional Financial Systems," Journal of Financial Econometrics, Oxford University Press, vol. 21(4), pages 989-1063.
  • Ye Chen & Peter C.B. Phillips & Shuping Shi, 2020. "Common Bubble Detection in Large Dimensional Financial Systems," Cowles Foundation Discussion Papers 2251, Cowles Foundation for Research in Economics, Yale University.
• Sendhil Mullainathan & Ziad Obermeyer, 2023. "Diagnosing Physician Error: A Machine Learning Approach to Low-Value Health Care," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 137(2), pages 679-727.
  • Sendhil Mullainathan & Ziad Obermeyer, 2019. "Diagnosing Physician Error: A Machine Learning Approach to Low-Value Health Care," NBER Working Papers 26168, National Bureau of Economic Research, Inc.
• Ron Bekkerman & Eliezer M Fich & Natalya V Khimich & Jeffrey Pontiff, 2023. "The Effect of Innovation Similarity on Asset Prices: Evidence from Patents’ Big Data," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 13(1), pages 99-145.
• Simon Jäger & Benjamin Schoefer & Josef Zweimüller, 2023. "Marginal Jobs and Job Surplus: A Test of the Efficiency of Separations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 90(3), pages 1265-1303.
  • Simon Jäger & Benjamin Schoefer & Josef Zweimüller, 2018. "Marginal jobs and job surplus: a test of the efficiency of separations," ECON - Working Papers 314, Department of Economics - University of Zurich.
  • Simon Jäger & Benjamin Schoefer & Josef Zweimüller, 2019. "Marginal Jobs and Job Surplus: A Test of the Efficiency of Separations," NBER Working Papers 25492, National Bureau of Economic Research, Inc.
  • Jäger, Simon & Schoefer, Benjamin & Zweimüller, Josef, 2019. "Marginal Jobs and Job Surplus: A Test of the Efficiency of Separations," IZA Discussion Papers 12127, Institute of Labor Economics (IZA).
  • Zweimüller, Josef & Jäger, Simon & Schoefer, Benjamin, 2019. "Marginal Jobs and Job Surplus: A Test of the Efficiency of Separations," CEPR Discussion Papers 13473, C.E.P.R. Discussion Papers.
• Simona-Vasilica Oprea & Adela Bara & Niculae Oprea, 2023. "Big Data Management and NoSQL Databases," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(1), pages 466-475, August.
• Alin-Gabriel Vaduva & Simona-Vasilica Oprea & Dragos-Catalin Barbu, 2023. "Understanding Customers' Opinion using Web Scraping and Natural Language Processing," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(1), pages 537-544, August.
• Andreea-Maria Tanasa & Simona-Vasilica Oprea & Adela Bara, 2023. "Web Scraping and Review Analytics. Extracting Insights from Commercial Data," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(2), pages 370-379, December.
• Chengyan Gu, 2023. "Market segmentation and dynamic price discrimination in the U.S. airline industry," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 22(5), pages 338-361, October.
• Mansur, Alfan & Nizar, Muhammad Afdi, 2023. "Supply-leading or demand-following financial sector and economic development nexus: evidence from data-rich Indonesia," MPRA Paper 119132, University Library of Munich, Germany, revised 10 Nov 2023.
• Milan Cibuľa & Michal Tkáč, 2023. "Porovnanie algoritmov strojového učenia pre tvorbu predikčného modelu ceny bitcoinu [Comparison of Machine Learning Algorithms for Creation of a Bitcoin Price Prediction Model]," Politická ekonomie, Prague University of Economics and Business, vol. 2023(5), pages 496-517.
• Teona Shugliashvili, 2023. "The words have power: the impact of news on exchange rates," FFA Working Papers 5.006, Prague University of Economics and Business, revised 31 Jul 2023.
• António Rua & Nuno Lourenço & João Quelhas, 2023. "Navigating with a compass: Charting the course of underlying inflation," Working Papers w202317, Banco de Portugal, Economics and Research Department.
• Jonathan Hambur, 2023. "Did Labour Market Concentration Lower Wages Growth Pre-COVID?," RBA Research Discussion Papers rdp2023-02, Reserve Bank of Australia.
• Jonathan Hambur & Dan Andrews, 2023. "Doing Less, with Less: Capital Misallocation, Investment and the Productivity Slowdown in Australia," RBA Research Discussion Papers rdp2023-03, Reserve Bank of Australia.
• Maximo Camacho & Andres Romeu, 2023. "Tourism and Gross Domestic Product short-run causality revisited: A symbolic transfer entropy approach," Tourism Economics, , vol. 29(1), pages 235-247, February.
• Jan Janků & Zuzana KuÄ erová & FrantiÅ¡ek DaÅ™ena, 2023. "Behavioral Insights from Crowdfunding Financing: What Do Social Media Ties, Emotional Cues and Sentiment Tell Us?," Journal of Economics / Ekonomicky casopis, Institute of Economic Research, Slovak Academy of Sciences, vol. 71(2), pages 89-118, February.
• Laura Felber & Dr. Simon Beyeler, 2023. "Nowcasting economic activity using transaction payments data," Working Papers 2023-01, Swiss National Bank.
• Marie-Catherine Bieri, 2023. "Assessing economic sentiment with newspaper text indices: evidence from Switzerland," Working Papers 2023-07, Swiss National Bank.
• Byron Botha & Rulof Burger & Kevin Kotzé & Neil Rankin & Daan Steenkamp, 2023. "Big data forecasting of South African inflation," Empirical Economics, Springer, vol. 65(1), pages 149-188, July.
  • Byron Botha & Kevin Kotze & Neil Rankin & Rulof P. Burger, 2022. "Big data forecasting of South African inflation," Working Papers 873, Economic Research Southern Africa.
  • Byron Botha & Rulof Burger & Kevin Kotz & Neil Rankin & Daan Steenkamp, 2022. "Big data forecasting of South African inflation," Working Papers 11022, South African Reserve Bank.
  • Byron Botha & Rulof Burger & Kevin Kotze & Neil Rankin & Daan Steenkamp, 2022. "Big data forecasting of South African inflation," School of Economics Macroeconomic Discussion Paper Series 2022-03, School of Economics, University of Cape Town.
• Hwee Kwan Chow & Yijie Fei & Daniel Han, 2023. "Forecasting GDP with many predictors in a small open economy: forecast or information pooling?," Empirical Economics, Springer, vol. 65(2), pages 805-829, August.
• Francisco Corona & Elio Atenógenes Villaseñor & Jesús López-Pérez & Ranyart R. Suárez, 2023. "Estimating Mexican municipal-level economic activity indicators using nighttime lights," Empirical Economics, Springer, vol. 65(3), pages 1197-1214, September.
• Bhanu Pratap & Nalin Priyaranjan, 2023. "Macroeconomic effects of uncertainty: a Google trends-based analysis for India," Empirical Economics, Springer, vol. 65(4), pages 1599-1625, October.
• Nuno Lourenço & António Rua, 2023. "Business cycle clocks: Time to get circular," Empirical Economics, Springer, vol. 65(4), pages 1513-1541, October.
• Seyed Ali Madanizadeh & Hosein Joshaghani & Reza Moradi, 2023. "Ride-hailing demand elasticity: a regression discontinuity method," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 50(4), pages 907-932, December.
• India Flint & Jasmina Medjedovic & Ewa Drogon O’Flaherty & Elena Alvarez-Baron & Karthinathan Thangavelu & Natasa Savic & Aurelie Meunier & Louise Longworth, 2023. "Mapping analysis to predict SF-6D utilities from health outcomes in people with focal epilepsy," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 24(7), pages 1061-1072, September.
• James Yae & Yang Luo, 2023. "Robust monitoring machine: a machine learning solution for out-of-sample R $$^2$$ 2 -hacking in return predictability monitoring," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-28, December.
• Nhung Nghiem & June Atkinson & Binh P. Nguyen & An Tran-Duy & Nick Wilson, 2023. "Predicting high health-cost users among people with cardiovascular disease using machine learning and nationwide linked social administrative datasets," Health Economics Review, Springer, vol. 13(1), pages 1-13, December.
• Saulius Jokubaitis & Dmitrij Celov, 2023. "Business Cycle Synchronization in the EU: A Regional-Sectoral Look through Soft-Clustering and Wavelet Decomposition," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 19(3), pages 311-371, November.
• Andrei Shynkevich, 2023. "Law of one price and return on Arbitrage Trading: Bitcoin vs. Ethereum," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 47(3), pages 763-792, September.
• Stüber, Heiko & Dauth, Wolfgang & Eppelsheimer, Johann, 2023. "A guide to preparing the sample of integrated labour market biographies (SIAB, version 7519 v1) for scientific analysis," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 57, pages 1-7.
  • Heiko Stüber & Wolfgang Dauth & Johann Eppelsheimer, 2023. "A guide to preparing the sample of integrated labour market biographies (SIAB, version 7519 v1) for scientific analysis," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 57(1), pages 1-11, December.
• Pawan Kumar & Vipul Kumar Singh, 2023. "Examining the Time Varying Spillover Dynamics of Indian Financial Indictors from Global and Local Economic Uncertainty," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 21(1), pages 99-121, March.
• Ioannis A. Nikas & Athanasios Koutras & Alkiviadis Panagopoulos, 2023. "Dynamic Areas of Interest Inside an Urban Destination Using Visitors’ Geolocation," Springer Proceedings in Business and Economics, in: Vicky Katsoni (ed.), Tourism, Travel, and Hospitality in a Smart and Sustainable World, pages 291-306, Springer.
• Indra Budi & Yaniasih Yaniasih, 2023. "Understanding the meanings of citations using sentiment, role, and citation function classifications," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(1), pages 735-759, January.
• Nataliya Matveeva & Vladimir Batagelj & Anuška Ferligoj, 2023. "Scientific collaboration of post-Soviet countries: the effects of different network normalizations," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(8), pages 4219-4242, August.
• Emmanuel O. Akande & Elijah O. Akanni & Oyedamola F. Taiwo & Jeremiah D. Joshua & Abel Anthony, 2023. "Predicting inflation component drivers in Nigeria: a stacked ensemble approach," SN Business & Economics, Springer, vol. 3(1), pages 1-32, January.
• Antonio Marsi, 2023. "Predicting European stock returns using machine learning," SN Business & Economics, Springer, vol. 3(7), pages 1-25, July.
• Jiexiang Li, 2023. "Estimation of the scale parameter in truncated Rayleigh distribution," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 12(4), pages 1-3.
• Odd E. Nygård & Thor O. Thoresen, 2023. "Controlling for fixed effects in studies of income underreporting," Discussion Papers 1000, Statistics Norway, Research Department.
• Joshua C. C. Chan, 2023. "Large Hybrid Time-Varying Parameter VARs," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(3), pages 890-905, July.
  • Joshua C.C. Chan, 2019. "Large hybrid time-varying parameter VARs," CAMA Working Papers 2019-77, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Joshua C. C. Chan, 2022. "Large Hybrid Time-Varying Parameter VARs," Papers 2201.07303, arXiv.org, revised Jun 2022.
• Laurent Ferrara & Anna Simoni, 2023. "When are Google Data Useful to Nowcast GDP? An Approach via Preselection and Shrinkage," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(4), pages 1188-1202, October.
  • Laurent Ferrara & Anna Simoni, 2019. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working Papers 2019-04, Center for Research in Economics and Statistics.
  • Laurent Ferrara & Anna Simoni, 2023. "When are Google Data Useful to Nowcast GDP? An Approach via Preselection and Shrinkage," Post-Print hal-03919944, HAL.
  • Laurent Ferrara & Anna Simoni, 2020. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," EconomiX Working Papers 2020-11, University of Paris Nanterre, EconomiX.
  • Laurent Ferrara & Anna Simoni, 2019. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working papers 717, Banque de France.
  • Laurent Ferrara & Anna Simoni, 2020. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Papers 2007.00273, arXiv.org, revised Sep 2022.
  • Laurent Ferrara & Anna Simoni, 2020. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working Papers hal-04159714, HAL.
• Sylvia A. Allegretto & Dave Graham-Squire, 2023. "Monopsony in Professional Labor Markets: Hospital System Concentration and Nurse Wages," Working Papers Series inetwp197, Institute for New Economic Thinking.
• Jacques Minlend, 2023. "European Low-Carbon Policy: Impact on fossil energy markets," Economics Working Paper Archive (University of Rennes & University of Caen) 2023-04, Center for Research in Economics and Management (CREM), University of Rennes, University of Caen and CNRS.
• Tae-Hwy Lee & Ekaterina Seregina, 2024. "Optimal Portfolio Using Factor Graphical Lasso," Journal of Financial Econometrics, Oxford University Press, vol. 22(3), pages 670-695.
  • Tae-Hwy Lee & Ekaterina Seregina, 2020. "Optimal Portfolio Using Factor Graphical Lasso," Papers 2011.00435, arXiv.org, revised Apr 2023.
  • Tae-Hwy Lee & Ekaterina Seregina, 2023. "Optimal Portfolio Using Factor Graphical Lasso," Working Papers 202302, University of California at Riverside, Department of Economics.
  • Tae-Hwy Lee & Ekaterina Seregina, 2020. "Optimal Portfolio Using Factor Graphical Lasso," Working Papers 202025, University of California at Riverside, Department of Economics.
• Jianghao Chu & Tae-Hwy Lee & Aman Ullah, 2023. "Asymmetric AdaBoost for High-dimensional Maximum Score Regression," Working Papers 202306, University of California at Riverside, Department of Economics.
• Saman Banafti & Tae-Hwy Lee, 2022. "Inferential Theory for Granular Instrumental Variables in High Dimensions," Working Papers 202203, University of California at Riverside, Department of Economics.
  • Saman Banafti & Tae-Hwy Lee, 2023. "Inferential Theory for Granular Instrumental Variables in High Dimensions," Working Papers 202308, University of California at Riverside, Department of Economics.
  • Saman Banafti & Tae-Hwy Lee, 2022. "Inferential Theory for Granular Instrumental Variables in High Dimensions," Papers 2201.06605, arXiv.org, revised Sep 2023.
• Tae-Hwy Lee & Ekaterina Seregina, 2022. "Combining Forecasts under Structural Breaks Using Graphical LASSO," Working Papers 202213, University of California at Riverside, Department of Economics.
  • Tae-Hwy Lee & Ekaterina Seregina, 2023. "Combining Forecasts under Structural Breaks Using Graphical LASSO," Working Papers 202310, University of California at Riverside, Department of Economics.
  • Tae-Hwy Lee & Ekaterina Seregina, 2022. "Combining Forecasts under Structural Breaks Using Graphical LASSO," Papers 2209.01697, arXiv.org, revised Sep 2023.
• Gloria Gonzalez-Rivera & Vladimir Rodriguez-Caballero & Esther Ruiz, 2023. "Expecting the unexpected: Stressed scenarios for economic growth," Working Papers 202314, University of California at Riverside, Department of Economics.
• Mihnea Constantinescu, 2023. "Sparse Warcasting," Working Papers 01/2023, National Bank of Ukraine.
• Dylan Brewer & Alyssa Carlson, 2024. "Addressing sample selection bias for machine learning methods," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(3), pages 383-400, April.
  • Dylan Brewer & Alyssa Carlson, 2021. "Addressing Sample Selection Bias for Machine Learning Methods," Working Papers 2102, Department of Economics, University of Missouri.
  • Dylan Brewer & Alyssa Carlson, 2023. "Addressing Sample Selection Bias for Machine Learning Methods," Working Papers 2302, Department of Economics, University of Missouri.
  • Dylan Brewer & Alyssa Carlson, 2023. "Addressing Sample Selection Bias for Machine Learning Methods," Working Papers 2310, Department of Economics, University of Missouri.
  • Dylan Brewer & Alyssa Carlson, 2021. "Addressing Sample Selection Bias for Machine Learning Methods," Working Papers 2114, Department of Economics, University of Missouri.
• Dylan Brewer & Alyssa Carlson, 2024. "Addressing sample selection bias for machine learning methods," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(3), pages 383-400, April.
  • Dylan Brewer & Alyssa Carlson, 2021. "Addressing Sample Selection Bias for Machine Learning Methods," Working Papers 2102, Department of Economics, University of Missouri.
  • Dylan Brewer & Alyssa Carlson, 2023. "Addressing Sample Selection Bias for Machine Learning Methods," Working Papers 2310, Department of Economics, University of Missouri.
  • Dylan Brewer & Alyssa Carlson, 2023. "Addressing Sample Selection Bias for Machine Learning Methods," Working Papers 2302, Department of Economics, University of Missouri.
  • Dylan Brewer & Alyssa Carlson, 2021. "Addressing Sample Selection Bias for Machine Learning Methods," Working Papers 2114, Department of Economics, University of Missouri.
• Matevosova Anastasia, 2023. "Modeling the impact of sanctions on inflation expectations," Working Papers 0053, Moscow State University, Faculty of Economics.
• Matevosova Anastasia, 2023. "The research of Russian’s inflation expectations under sanctions based on big data," Working Papers 0057, Moscow State University, Faculty of Economics.
• Luca Mingarelli & Jonas Wendelborn & Tamarah Shakir, 2023. "On the identification of zombie firms," Aussenwirtschaft, University of St. Gallen, School of Economics and Political Science, Swiss Institute for International Economics and Applied Economics Research, vol. 73(01), pages 57-64, December.
• Fengler, Matthias & Phan, Minh Tri, 2023. "A Topic Model for 10-K Management Disclosures," Economics Working Paper Series 2307, University of St. Gallen, School of Economics and Political Science.
• Bogner Alexandra & Jerger Jürgen, 2023. "Big data in monetary policy analysis—a critical assessment," Economics and Business Review, Sciendo, vol. 9(2), pages 27-40, April.
• Gere István, 2023. "Mapping the Parameter Space of Simulated Lotteries," Journal of Social and Economic Statistics, Sciendo, vol. 12(2), pages 38-52, December.
• Denise Desjardins & Georges Dionne & Yang Lu, 2023. "Hierarchical random‐effects model for the insurance pricing of vehicles belonging to a fleet," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(2), pages 242-259, March.
  • Desjardins, Denise & Dionne, Georges & Lu, Yang, 2021. "Hierarchical random effects model for insurance pricing of vehicles belonging to a fleet," Working Papers 21-2, HEC Montreal, Canada Research Chair in Risk Management.
• Fetzer, Thiemo & Gazze, Ludovica & Bishop, Menna, 2023. "Distributional and climate implications of policy responses to energy price shocks," CAGE Online Working Paper Series 671, Competitive Advantage in the Global Economy (CAGE).
  • Fetzer, Thiemo & Gazze, Ludovica & Bishop, Menna, 2023. "Distributional and climate implications of policy responses to energy price shocks," The Warwick Economics Research Paper Series (TWERPS) 1467, University of Warwick, Department of Economics.
• Szydlo, Jan, 2023. "Forecasting Credit Dynamics : VAR, VECM or modern Factor-Augmented VAR approach?," Warwick-Monash Economics Student Papers 63, Warwick Monash Economics Student Papers.
• Beck, Günter W. & Carstensen, Kai & Menz, Jan-Oliver & Schnorrenberger, Richard & Wieland, Elisabeth, 2023. "Nowcasting consumer price inflation using high-frequency scanner data: Evidence from Germany," Discussion Papers 34/2023, Deutsche Bundesbank.
  • Beck, Günter W. & Carstensen, Kai & Menz, Jan-Oliver & Schnorrenberger, Richard & Wieland, Elisabeth, 2024. "Nowcasting consumer price inflation using high-frequency scanner data: evidence from Germany," Working Paper Series 2930, European Central Bank.
• Fridgen, Gilbert & Kräussl, Roman & Papageorgiou, Orestis & Tugnetti, Alessandro, 2023. "The fundamental value of art NFTs," CFS Working Paper Series 709, Center for Financial Studies (CFS).
• Büchel, Jan & Engler, Jan & Mertens, Armin, 2023. "Gesuchte Datenkompetenzen in Deutschland [The demand for data skills in Germany]," IW-Trends – Vierteljahresschrift zur empirischen Wirtschaftsforschung, Institut der deutschen Wirtschaft (IW) / German Economic Institute, vol. 50(2), pages 3-17.
• Lavko, Matus & Klein, Tony & Walther, Thomas, 2023. "Reinforcement Learning and Portfolio Allocation: Challenging Traditional Allocation Methods," QBS Working Paper Series 2023/01, Queen's University Belfast, Queen's Business School.
• Bagnara, Matteo & Goodarzi, Milad, 2023. "Clustering-based sector investing," SAFE Working Paper Series 397, Leibniz Institute for Financial Research SAFE.
• Iva Tolic Mandic & Sanja Tisma & Daniela Angelina Jelincic & Damir Demonja, 2023. "Smart Solutions for Sustainable Tourism Pearls: How to Live Between Culture and Tourism in Dubrovnik," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, vol. 21(3), pages 272-296.

2022

• Kristoffer Pons Bertelsen, 2022. "The Prior Adaptive Group Lasso and the Factor Zoo," CREATES Research Papers 2022-05, Department of Economics and Business Economics, Aarhus University.
• Sarthak Behera & Hyeongwoo Kim & Soohyon Kim, 2021. "Superior Predictability of American Factors of the Won/Dollar Real Exchange Rate," Auburn Economics Working Paper Series auwp2021-03, Department of Economics, Auburn University.
  • Sarthak Behera & Hyeongwoo Kim & Soohyon Kim, 2022. "Superior Predictability of American Factors of the Won/Dollar Real Exchange Rate," Auburn Economics Working Paper Series auwp2022-03, Department of Economics, Auburn University.
• Laurence Kotlikoff, 2022. "Does Prediction Machines Predict Our AI Future? A Review," Journal of Economic Literature, American Economic Association, vol. 60(3), pages 1052-1057, September.
• Susanne Schennach, 2022. "Measurement Systems," Journal of Economic Literature, American Economic Association, vol. 60(4), pages 1223-1263, December.
• Gheorghe Zaman & Nicoleta Valentina Florea & Constantin Aurelian Ionescu & Dan Marius Coman & Doina Constanta Mihai & Nicoleta Luminita Gudanescu Nicolau, 2022. "Mathematical Model for Determining Costs of Unsatisfied Customers of HoReCa Industry," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 24(59), pages 268-268.
• Isaac K. Ofori & Camara K. Obeng & Simplice A. Asongu, 2024. "What Really Drives Economic Growth in Sub-Saharan Africa? Evidence from the Lasso Regularization and Inferential Techniques," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(1), pages 144-179, March.
  • Isaac K. Ofori & Camara K. Obeng & Simplice A. Asongu, 2022. "What Really Drives Economic Growth in Sub-Saharan Africa? Evidence from The Lasso Regularization and Inferential Techniques," Working Papers 22/061, European Xtramile Centre of African Studies (EXCAS).
  • Isaac K. Ofori & Camara K. Obeng & Simplice A. Asongu, 2022. "What Really Drives Economic Growth in Sub-Saharan Africa? Evidence from The Lasso Regularization and Inferential Techniques," Working Papers of the African Governance and Development Institute. 22/061, African Governance and Development Institute..
• Iania, Leonardo & Algieri, Bernardina & Leccadito, Arturo, 2022. "Forecasting total energy’s CO2 emissions," LIDAM Discussion Papers LFIN 2022003, Université catholique de Louvain, Louvain Finance (LFIN).
• Stefano Giglio & Bryan Kelly & Dacheng Xiu, 2022. "Factor Models, Machine Learning, and Asset Pricing," Annual Review of Financial Economics, Annual Reviews, vol. 14(1), pages 337-368, November.
• Агамбаева С.Б. // Agambayeva S.B. & Джусангалиева К.Е. // Jussangaliyeva K.E. & Акылбеков А.А. // Akylbekov A.A. & Ханетова А.Б. // Khanetova A.B., 2022. "Таргет по инфляции: формулировка цели и последствия ее смены. Обзор международного опыта. // Inflation Target: Formulation of the Goal and Implications of its Change. Overview of international experie," Economic Review(National Bank of Kazakhstan), National Bank of Kazakhstan, issue 3/4, pages 4-25.
• Аринова Айжан // Arinova Aizhan & Ержан Ислам // Yerzhan Islam, 2022. "Использование транзакционных данных в качестве оперативного показателя экономической активности // Use of transactional data as an operational measure of economic activity," Working Papers #2022-11, National Bank of Kazakhstan.
• Christina Carty & Oscar Claveria, 2022. ""The nexus between variable renewable energy, economy and climate: Evidence from European countries by means of exploratory graphical analysis"," IREA Working Papers 202207, University of Barcelona, Research Institute of Applied Economics, revised May 2022.
  • Christina Carty & Oscar Claveria, 2022. "“The nexus between variable renewable energy, economy and climate: Evidence from European countries by means of exploratory graphical analysis”," AQR Working Papers 202205, University of Barcelona, Regional Quantitative Analysis Group, revised May 2022.
• Saman Banafti & Tae-Hwy Lee, 2022. "Inferential Theory for Granular Instrumental Variables in High Dimensions," Working Papers 202203, University of California at Riverside, Department of Economics.
  • Saman Banafti & Tae-Hwy Lee, 2023. "Inferential Theory for Granular Instrumental Variables in High Dimensions," Working Papers 202308, University of California at Riverside, Department of Economics.
  • Saman Banafti & Tae-Hwy Lee, 2022. "Inferential Theory for Granular Instrumental Variables in High Dimensions," Papers 2201.06605, arXiv.org, revised Sep 2023.
• Joshua C. C. Chan, 2023. "Large Hybrid Time-Varying Parameter VARs," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(3), pages 890-905, July.
  • Joshua C.C. Chan, 2019. "Large hybrid time-varying parameter VARs," CAMA Working Papers 2019-77, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Joshua C. C. Chan, 2022. "Large Hybrid Time-Varying Parameter VARs," Papers 2201.07303, arXiv.org, revised Jun 2022.
• Christophe Bellégo & David Benatia & Louis-Daniel Pape, 2022. "Dealing with Logs and Zeros in Regression Models," Working Papers 2022-08, Center for Research in Economics and Statistics.
  • Christophe Bell'ego & David Benatia & Louis Pape, 2022. "Dealing with Logs and Zeros in Regression Models," Papers 2203.11820, arXiv.org.
• Christophe Hurlin & Christophe Perignon & Sébastien Saurin, 2021. "The Fairness of Credit Scoring Models," Working Papers hal-03501452, HAL.
  • Christophe Hurlin & Christophe P'erignon & S'ebastien Saurin, 2022. "The Fairness of Credit Scoring Models," Papers 2205.10200, arXiv.org, revised Feb 2024.
  • Hurlin, Christophe & Pérignon, Christophe & Saurin, Sébastien, 2021. "The Fairness of Credit Scoring Models," HEC Research Papers Series 1411, HEC Paris.
  • Christophe HURLIN & Christophe PERIGNON & Sébastien SAURIN, 2021. "The Fairness of Credit Scoring Models," LEO Working Papers / DR LEO 2912, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
• Urga, Giovanni & Wang, Fa, 2022. "Estimation and inference for high dimensional factor model with regime switching," MPRA Paper 113172, University Library of Munich, Germany.
  • Giovanni Urga & Fa Wang, 2022. "Estimation and Inference for High Dimensional Factor Model with Regime Switching," Papers 2205.12126, arXiv.org, revised Apr 2023.
• Bai, Jushan & Duan, Jiangtao & Han, Xu, 2024. "The likelihood ratio test for structural changes in factor models," Journal of Econometrics, Elsevier, vol. 238(2).
  • Jushan Bai & Jiangtao Duan & Xu Han, 2022. "Likelihood ratio test for structural changes in factor models," Papers 2206.08052, arXiv.org, revised Dec 2023.
• Chan, Joshua C.C. & Yu, Xuewen, 2022. "Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
  • Joshua C.C. Chan & Xuewen Yu, 2020. "Fast and accurate variational inference for large Bayesian VARs with stochastic volatility," CAMA Working Papers 2020-108, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Joshua C. C. Chan & Xuewen Yu, 2022. "Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility," Papers 2206.08438, arXiv.org.
• Bakalli, Gaetan & Guerrier, Stéphane & Scaillet, Olivier, 2023. "A penalized two-pass regression to predict stock returns with time-varying risk premia," Journal of Econometrics, Elsevier, vol. 237(2).
  • Gaetan Bakalli & Stéphane Guerrier & Olivier Scaillet, 2021. "A penalized two-pass regression to predict stock returns with time-varying risk premia," Swiss Finance Institute Research Paper Series 21-09, Swiss Finance Institute.
  • Gaetan Bakalli & St'ephane Guerrier & Olivier Scaillet, 2022. "A penalized two-pass regression to predict stock returns with time-varying risk premia," Papers 2208.00972, arXiv.org.
  • Gaetan Bakalli & Stéphane Guerrier & Olivier Scaillet, 2023. "A penalized two-pass regression to predict stock returns with time-varying risk premia," Post-Print hal-04325655, HAL.
• James T. E. Chapman & Ajit Desai, 2023. "Macroeconomic Predictions Using Payments Data and Machine Learning," Forecasting, MDPI, vol. 5(4), pages 1-32, November.
  • James Chapman & Ajit Desai, 2022. "Macroeconomic Predictions Using Payments Data and Machine Learning," Staff Working Papers 22-10, Bank of Canada.
  • James T. E. Chapman & Ajit Desai, 2022. "Macroeconomic Predictions using Payments Data and Machine Learning," Papers 2209.00948, arXiv.org.
• Tae-Hwy Lee & Ekaterina Seregina, 2022. "Combining Forecasts under Structural Breaks Using Graphical LASSO," Working Papers 202213, University of California at Riverside, Department of Economics.
  • Tae-Hwy Lee & Ekaterina Seregina, 2023. "Combining Forecasts under Structural Breaks Using Graphical LASSO," Working Papers 202310, University of California at Riverside, Department of Economics.
  • Tae-Hwy Lee & Ekaterina Seregina, 2022. "Combining Forecasts under Structural Breaks Using Graphical LASSO," Papers 2209.01697, arXiv.org, revised Sep 2023.
• Aleksandar Kešeljević & Rok Spruk, 2024. "Estimating the effects of Syrian civil war," Empirical Economics, Springer, vol. 66(2), pages 671-703, February.
  • Aleksandar Keseljevic & Rok Spruk, 2022. "Estimating the Effects of Syrian Civil War," Papers 2209.03046, arXiv.org.
• Chang, Jinyuan & Jiang, Qing & Shao, Xiaofeng, 2023. "Testing the martingale difference hypothesis in high dimension," Journal of Econometrics, Elsevier, vol. 235(2), pages 972-1000.
  • Jinyuan Chang & Qing Jiang & Xiaofeng Shao, 2022. "Testing the martingale difference hypothesis in high dimension," Papers 2209.04770, arXiv.org, revised Sep 2022.
• Jan Ditzen & Francesco Ravazzolo, 2022. "Dominant Drivers of National Inflation," BEMPS - Bozen Economics & Management Paper Series BEMPS97, Faculty of Economics and Management at the Free University of Bozen.
  • Jan Ditzen & Francesco Ravazzolo, 2022. "Dominant Drivers of National Inflation," Papers 2212.05841, arXiv.org.
• Emilia VASILE & Danut Octavian SIMION, 2022. "Establishing And Achieving The Objectives Of Economic Information Systems Through Algorithms Specific To Business Applications," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 65(1), pages 9-18, March.
• Danut Octavian SIMION & Emilia VASILE, 2022. "Optimizing Economic Applications By Optimizing Data Flows Present In Different Modules Integrated In Informatics Technology Systems," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 66(2), pages 54-63, September.
• Maxim Ralchenko & Adrian Walton, 2022. "Historical Data on Repurchase Agreements from the Canadian Depository for Securities," Technical Reports 121, Bank of Canada.
• Thibaut Duprey & Daniel E. Rigobon & Philip Schnattinger & Artur Kotlicki & Soheil Baharian & T. R. Hurd, 2022. "Business Closures and (Re)Openings in Real Time Using Google Places," Staff Working Papers 22-1, Bank of Canada.
• James T. E. Chapman & Ajit Desai, 2023. "Macroeconomic Predictions Using Payments Data and Machine Learning," Forecasting, MDPI, vol. 5(4), pages 1-32, November.
  • James T. E. Chapman & Ajit Desai, 2022. "Macroeconomic Predictions using Payments Data and Machine Learning," Papers 2209.00948, arXiv.org.
  • James Chapman & Ajit Desai, 2022. "Macroeconomic Predictions Using Payments Data and Machine Learning," Staff Working Papers 22-10, Bank of Canada.
• Efrem Castelnuovo & Kerem Tuzcuoglu & Luis Uzeda, 2024. "Sectoral uncertainty," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Granular data: new horizons and challenges, volume 61, Bank for International Settlements.
  • Efrem Castelnuovo & Kerem Tuzcuoglu & Luis Uzeda, 2022. "Sectoral Uncertainty," CAMA Working Papers 2022-62, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Efrem Castelnuovo & Kerem Tuzcuoglu & Luis Uzeda, 2022. "Sectoral Uncertainty," Staff Working Papers 22-38, Bank of Canada.
  • Efrem Castelnuovo & Kerem Tuzcuoglu & Luis Uzeda, 2022. "Sectoral Uncertainty," "Marco Fanno" Working Papers 0288, Dipartimento di Scienze Economiche "Marco Fanno".
  • Efrem Castelnuovo & Kerem Tuzcuoglu & Luis Uzeda, 2022. "Sectoral Uncertainty," CESifo Working Paper Series 10034, CESifo.
• Araujo, Gustavo Silva & Gaglianone, Wagner Piazza, 2023. "Machine learning methods for inflation forecasting in Brazil: New contenders versus classical models," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 4(2).
  • Gustavo Silva Araujo & Wagner Piazza Gaglianone, 2022. "Machine Learning Methods for Inflation Forecasting in Brazil: new contenders versus classical models," Working Papers Series 561, Central Bank of Brazil, Research Department.
• Andrés Alonso & José Manuel Carbó, 2022. "Accuracy of explanations of machine learning models for credit decisions," Working Papers 2222, Banco de España.
• Giuseppe Cascarino & Mirko Moscatelli & Fabio Parlapiano, 2022. "Explainable Artificial Intelligence: interpreting default forecasting models based on Machine Learning," Questioni di Economia e Finanza (Occasional Papers) 674, Bank of Italy, Economic Research and International Relations Area.
• Valerio Astuti & Marta Crispino & Marco Langiulli & Juri Marcucci, 2022. "Textual analysis of a Twitter corpus during the COVID-19 pandemics," Questioni di Economia e Finanza (Occasional Papers) 692, Bank of Italy, Economic Research and International Relations Area.
• Fadda, Pietro & Hanifi, Rayane & Istrefi, Klodiana & Penalver, Adrian, 2022. "Central Bank Communication of Uncertainty," CEPR Discussion Papers 17728, C.E.P.R. Discussion Papers.
  • Rayane Hanifi & Klodiana Istrefi & Adrian Penalver, 2022. "Central Bank Communication of Uncertainty," Working papers 898, Banque de France.
• Ferran Sancho, 2022. "Stone-Geary Meets CES: An Extended Linear Expenditure System," Working Papers 1328, Barcelona School of Economics.
  • Ferran Sancho, 2023. "Stone-Geary meets CES:An extended linear expenditure system," UFAE and IAE Working Papers 971.23, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
• Elena Shulyak, 2022. "Macroeconomic Forecasting Using Data from Social Media," Russian Journal of Money and Finance, Bank of Russia, vol. 81(4), pages 86-112, December.
• Oyenyinka Sunday Omoshoro‐Jones & Lumengo Bonga‐Bonga, 2022. "Intra‐regional spillovers from Nigeria and South Africa to the rest of Africa: New evidence from a FAVAR model," The World Economy, Wiley Blackwell, vol. 45(1), pages 251-275, January.
  • Omoshoro-Jones, Oyeyinka Sunday & Bonga-Bonga, Lumengo, 2020. "Intra-regional spillovers from Nigeria and South Africa to the rest of Africa: New evidence from a FAVAR model," MPRA Paper 99514, University Library of Munich, Germany.
• Jan Ditzen & Francesco Ravazzolo, 2022. "Dominant Drivers of National Inflation," BEMPS - Bozen Economics & Management Paper Series BEMPS97, Faculty of Economics and Management at the Free University of Bozen.
  • Hilde C. Bjørnland, 2022. "The effect of rising energy prices amid geopolitical developments and supply disruptions," Working Papers No 07/2022, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • Jan Ditzen & Francesco Ravazzolo, 2022. "Dominant Drivers of National Inflation," Papers 2212.05841, arXiv.org.
• Takashi Nakazawa, 2022. "Constructing GDP Nowcasting Models Using Alternative Data," Bank of Japan Working Paper Series 22-E-9, Bank of Japan.
• Kakuho Furukawa & Ryohei Hisano & Yukio Minoura & Tomoyuki Yagi, 2022. "A Nowcasting Model of Industrial Production using Alternative Data and Machine Learning Approaches," Bank of Japan Working Paper Series 22-E-16, Bank of Japan.
• Kakuho Furukawa & Ryohei Hisano, 2022. "A Nowcasting Model of Exports Using Maritime Big Data," Bank of Japan Working Paper Series 22-E-19, Bank of Japan.
• Miren Azkarate-Askasua & Miguel Zerecero, 2022. "Correcting Small Sample Bias in Linear Models With Many Covariates," CRC TR 224 Discussion Paper Series crctr224_2022_376, University of Bonn and University of Mannheim, Germany.
• Jan Ditzen & Francesco Ravazzolo, 2022. "Dominant Drivers of National Inflation," Papers 2212.05841, arXiv.org.
  • Jan Ditzen & Francesco Ravazzolo, 2022. "Dominant Drivers of National Inflation," BEMPS - Bozen Economics & Management Paper Series BEMPS97, Faculty of Economics and Management at the Free University of Bozen.
• Hannes Mueller & Christopher Rauh, 2022. "Using past violence and current news to predict changes in violence," International Interactions, Taylor & Francis Journals, vol. 48(4), pages 579-596, July.
  • Mueller, H. & Rauh, C., 2022. "Using Past Violence and Current News to Predict Changes in Violence," Janeway Institute Working Papers 2209, Faculty of Economics, University of Cambridge.
  • Mueller, H. & Rauh, C., 2022. "Using Past Violence and Current News to Predict Changes in Violence," Cambridge Working Papers in Economics 2220, Faculty of Economics, University of Cambridge.
• Linton, O. B. & Tang, H. & Wu, J., 2022. "A Structural Dynamic Factor Model for Daily Global Stock Market Returns," Cambridge Working Papers in Economics 2237, Faculty of Economics, University of Cambridge.
• Vogt, M. & Walsh, C. & Linton, O., 2022. "CCE Estimation of High-Dimensional Panel Data Models with Interactive Fixed Effects," Cambridge Working Papers in Economics 2242, Faculty of Economics, University of Cambridge.
• Linton, O. B. & Tang, H. & Wu, J., 2022. "A Structural Dynamic Factor Model for Daily Global Stock Market Returns," Cambridge Working Papers in Economics camjip:2214, Faculty of Economics, University of Cambridge.
• Hannes Mueller & Christopher Rauh, 2022. "Using past violence and current news to predict changes in violence," International Interactions, Taylor & Francis Journals, vol. 48(4), pages 579-596, July.
  • Mueller, H. & Rauh, C., 2022. "Using Past Violence and Current News to Predict Changes in Violence," Cambridge Working Papers in Economics 2220, Faculty of Economics, University of Cambridge.
  • Mueller, H. & Rauh, C., 2022. "Using Past Violence and Current News to Predict Changes in Violence," Janeway Institute Working Papers 2209, Faculty of Economics, University of Cambridge.
• Vogt, M. & Walsh, C. & Linton, O., 2022. "CCE Estimation of High-Dimensional Panel Data Models with Interactive Fixed Effects," Janeway Institute Working Papers 2218, Faculty of Economics, University of Cambridge.
• Linton, O. B. & Tang, H. & Wu, J., 2022. "A Structural Dynamic Factor Model for Daily Global Stock Market Returns," Janeway Institute Working Papers camjip:2214, Faculty of Economics, University of Cambridge.
• Efrem Castelnuovo & Kerem Tuzcuoglu & Luis Uzeda, 2024. "Sectoral uncertainty," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Granular data: new horizons and challenges, volume 61, Bank for International Settlements.
  • Efrem Castelnuovo & Kerem Tuzcuoglu & Luis Uzeda, 2022. "Sectoral Uncertainty," Staff Working Papers 22-38, Bank of Canada.
  • Efrem Castelnuovo & Kerem Tuzcuoglu & Luis Uzeda, 2022. "Sectoral Uncertainty," CESifo Working Paper Series 10034, CESifo.
  • Efrem Castelnuovo & Kerem Tuzcuoglu & Luis Uzeda, 2022. "Sectoral Uncertainty," "Marco Fanno" Working Papers 0288, Dipartimento di Scienze Economiche "Marco Fanno".
  • Efrem Castelnuovo & Kerem Tuzcuoglu & Luis Uzeda, 2022. "Sectoral Uncertainty," CAMA Working Papers 2022-62, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Pilar Rey del Castillo, 2022. "Building Daily Economic Sentiment Indicators," CESifo Working Paper Series 10087, CESifo.
• Fetzer, Thiemo & Gazze, Ludovica & Bishop, Menna, 2022. "Distributional and climate implications of policy responses to the energy crisis: Lessons from the UK," CAGE Online Working Paper Series 644, Competitive Advantage in the Global Economy (CAGE).
  • Fetzer, Thiemo & Gazzè, Ludovica & Bishop, Menna, 2023. "Distributional and climate implications of policy responses to the energy crisis: Lessons from the UK," CEPR Discussion Papers 17990, C.E.P.R. Discussion Papers.
• Damir Filipović & Markus Pelger & Ye Ye, 2022. "Stripping the Discount Curve - a Robust Machine Learning Approach," Swiss Finance Institute Research Paper Series 22-24, Swiss Finance Institute.
• Oksana Bashchenko, 2022. "Bitcoin Price Factors: Natural Language Processing Approach," Swiss Finance Institute Research Paper Series 22-48, Swiss Finance Institute.
• Damir Filipović & Markus Pelger & Ye Ye, 2022. "Shrinking the Term Structure," Swiss Finance Institute Research Paper Series 22-61, Swiss Finance Institute.
  • Damir Filipović & Markus Pelger & Ye Ye, 2024. "Shrinking the Term Structure," NBER Working Papers 32472, National Bureau of Economic Research, Inc.
• Damir Filipović & Puneet Pasricha, 2022. "Empirical Asset Pricing via Ensemble Gaussian Process Regression," Swiss Finance Institute Research Paper Series 22-95, Swiss Finance Institute.
• Victoria Ateca-Amestoy & Concetta Castiglione, 2022. "Live And Digital Engagement With The Visual Arts," Working Papers 202206, Università della Calabria, Dipartimento di Economia, Statistica e Finanza "Giovanni Anania" - DESF.
• Andrei Dubovik & Adam Elbourne & Bram Hendriks & Mark Kattenberg, 2022. "Forecasting World Trade Using Big Data and Machine Learning Techniques," CPB Discussion Paper 441, CPB Netherlands Bureau for Economic Policy Analysis.
• Yu Bai & Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022. "Macroeconomic forecasting in a multi‐country context," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(6), pages 1230-1255, September.
  • Yu Bai & Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022. "Macroeconomic Forecasting in a Multi-country Context," Working Papers 22-02, Federal Reserve Bank of Cleveland.
  • Bai, Yu & Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano, 2022. "Macroeconomic Forecasting in a Multi-country Context," CEPR Discussion Papers 16994, C.E.P.R. Discussion Papers.
• Andreou, Elena & Gagliardini, Patrick & Ghysels, Eric & Rubin, Mirco, 2022. "Three Common Factors," CEPR Discussion Papers 17225, C.E.P.R. Discussion Papers.
• Simonov, Andrey & Ursu, Raluca & Zheng, Carolina, 2022. "Suspense and Surprise in Media Product Design: Evidence from Twitch.tv," CEPR Discussion Papers 17353, C.E.P.R. Discussion Papers.
• Meeks, Roland & Monti, Francesca, 2023. "Heterogeneous beliefs and the Phillips curve," Journal of Monetary Economics, Elsevier, vol. 139(C), pages 41-54.
  • Meeks, Roland & Monti, Francesca, 2019. "Heterogeneous beliefs and the Phillips curve," Bank of England working papers 807, Bank of England.
  • Meeks, Roland & Monti, Francesca, 2022. "Heterogeneous beliefs and the Phillips curve," CEPR Discussion Papers 17537, C.E.P.R. Discussion Papers.
  • Roland Meeks & Francesca Monti, 2022. "Heterogeneous Beliefs and the Phillips Curve," CAMA Working Papers 2022-51, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Jewson, Jack & Li, Li & Battaglia, Laura & Hansen, Stephen & Rossell, David & Zwiernik, Piotr, 2022. "Graphical model inference with external network data," CEPR Discussion Papers 17638, C.E.P.R. Discussion Papers.
• Rayane Hanifi & Klodiana Istrefi & Adrian Penalver, 2022. "Central Bank Communication of Uncertainty," Working papers 898, Banque de France.
  • Fadda, Pietro & Hanifi, Rayane & Istrefi, Klodiana & Penalver, Adrian, 2022. "Central Bank Communication of Uncertainty," CEPR Discussion Papers 17728, C.E.P.R. Discussion Papers.
• Christophe Bell'ego & David Benatia & Louis Pape, 2022. "Dealing with Logs and Zeros in Regression Models," Papers 2203.11820, arXiv.org.
  • Christophe Bellégo & David Benatia & Louis-Daniel Pape, 2022. "Dealing with Logs and Zeros in Regression Models," Working Papers 2022-08, Center for Research in Economics and Statistics.
• Poncela Blanco, Maria Pilar & Fresoli, Diego Eduardo, 2022. "Ignoring cross-correlated idiosyncratic components when extracting factors in dynamic factor models," DES - Working Papers. Statistics and Econometrics. WS 36251, Universidad Carlos III de Madrid. Departamento de Estadística.
• Byron Botha & Rulof Burger & Kevin Kotzé & Neil Rankin & Daan Steenkamp, 2023. "Big data forecasting of South African inflation," Empirical Economics, Springer, vol. 65(1), pages 149-188, July.
  • Byron Botha & Kevin Kotze & Neil Rankin & Rulof P. Burger, 2022. "Big data forecasting of South African inflation," Working Papers 873, Economic Research Southern Africa.
  • Byron Botha & Rulof Burger & Kevin Kotze & Neil Rankin & Daan Steenkamp, 2022. "Big data forecasting of South African inflation," School of Economics Macroeconomic Discussion Paper Series 2022-03, School of Economics, University of Cape Town.
  • Byron Botha & Rulof Burger & Kevin Kotz & Neil Rankin & Daan Steenkamp, 2022. "Big data forecasting of South African inflation," Working Papers 11022, South African Reserve Bank.
• Ryan, Ellen & Horan, Aoife & Jarmulska, Barbara, 2022. "Commercial real estate and financial stability – new insights from the euro area credit register," Macroprudential Bulletin, European Central Bank, vol. 19.
• Mingarelli, Luca & Ravanetti, Beatrice & Shakir, Tamarah & Wendelborn, Jonas, 2022. "Dawn of the (half) dead: the twisted world of zombie identification," Working Paper Series 2743, European Central Bank.
• Chan, Joshua C.C. & Yu, Xuewen, 2022. "Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
  • Joshua C.C. Chan & Xuewen Yu, 2020. "Fast and accurate variational inference for large Bayesian VARs with stochastic volatility," CAMA Working Papers 2020-108, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Joshua C. C. Chan & Xuewen Yu, 2022. "Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility," Papers 2206.08438, arXiv.org.
• Anatolyev, Stanislav & Pyrlik, Vladimir, 2022. "Copula shrinkage and portfolio allocation in ultra-high dimensions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
• Caporin, Massimiliano & Poli, Francesco, 2022. "News and intraday jumps: Evidence from regularization and class imbalance," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
• Belloni, Alexandre & Hansen, Christian & Newey, Whitney, 2022. "High-dimensional linear models with many endogenous variables," Journal of Econometrics, Elsevier, vol. 228(1), pages 4-26.
• Angelico, Cristina & Marcucci, Juri & Miccoli, Marcello & Quarta, Filippo, 2022. "Can we measure inflation expectations using Twitter?," Journal of Econometrics, Elsevier, vol. 228(2), pages 259-277.
  • Cristina Angelico & Juri Marcucci & Marcello Miccoli & Filippo Quarta, 2021. "Can we measure inflation expectations using Twitter?," Temi di discussione (Economic working papers) 1318, Bank of Italy, Economic Research and International Relations Area.
• Yu, Long & He, Yong & Kong, Xinbing & Zhang, Xinsheng, 2022. "Projected estimation for large-dimensional matrix factor models," Journal of Econometrics, Elsevier, vol. 229(1), pages 201-217.
• Freyaldenhoven, Simon, 2022. "Factor models with local factors — Determining the number of relevant factors," Journal of Econometrics, Elsevier, vol. 229(1), pages 80-102.
  • Simon Freyaldenhoven, 2021. "Factor Models with Local Factors—Determining the Number of Relevant Factors," Working Papers 21-15, Federal Reserve Bank of Philadelphia.
• Agudze, Komla M. & Billio, Monica & Casarin, Roberto & Ravazzolo, Francesco, 2022. "Markov switching panel with endogenous synchronization effects," Journal of Econometrics, Elsevier, vol. 230(2), pages 281-298.
  • Komla M. Agudze & Monica Billio & Roberto Casarin & Francesco Ravazzolo, 2021. "Markov Switching Panel with Endogenous Synchronization Effects," BEMPS - Bozen Economics & Management Paper Series BEMPS82, Faculty of Economics and Management at the Free University of Bozen.
• Doanh, Nguyen Khanh & Gam, Nguyen Thi & Heo, Yoon, 2022. "The impact of intellectual property rights protection on trade: The role of a “third country” in market power and market expansion effects," Economic Systems, Elsevier, vol. 46(1).
• Tsang, Kwok Ping & Yang, Zichao, 2022. "Do connections pay off in the bitcoin market?," Journal of Empirical Finance, Elsevier, vol. 67(C), pages 1-18.
• Kang, Jieyi & Reiner, David M., 2022. "What is the effect of weather on household electricity consumption? Empirical evidence from Ireland," Energy Economics, Elsevier, vol. 111(C).
  • Kang, J. & Reiner, D., 2021. "What is the effect of weather on household electricity consumption? Empirical evidence from Ireland," Cambridge Working Papers in Economics 2141, Faculty of Economics, University of Cambridge.
  • Jieyi Kang & David Reiner, 2021. "What is the effect of weather on household electricity consumption? Empirical evidence from Ireland," Working Papers EPRG2112, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
• Nazlioglu, Saban & Kassouri, Yacouba & Kucukkaplan, Ilhan & Soytas, Ugur, 2022. "Convergence of oil consumption: A historical perspective with new concepts," Energy Policy, Elsevier, vol. 168(C).
• Ellington, Michael & Stamatogiannis, Michalis P. & Zheng, Yawen, 2022. "A study of cross-industry return predictability in the Chinese stock market," International Review of Financial Analysis, Elsevier, vol. 83(C).
• Ding, Shusheng & Cui, Tianxiang & Zhang, Yongmin, 2022. "Futures volatility forecasting based on big data analytics with incorporating an order imbalance effect," International Review of Financial Analysis, Elsevier, vol. 83(C).
• Salisu, Afees A. & Tchankam, Jean Paul, 2022. "US Stock return predictability with high dimensional models," Finance Research Letters, Elsevier, vol. 45(C).
• Duan, Yuejiao & Goodell, John W. & Li, Haoran & Li, Xinming, 2022. "Assessing machine learning for forecasting economic risk: Evidence from an expanded Chinese financial information set," Finance Research Letters, Elsevier, vol. 46(PA).
• García-Uribe, Sandra, 2022. "Multidimensional media slant: Complementarities in news reporting by US newspapers," Information Economics and Policy, Elsevier, vol. 61(C).
• Buse, Rebekka & Schienle, Melanie & Urban, Jörg, 2022. "Assessing the impact of policy and regulation interventions in European sovereign credit risk networks: What worked best?," Journal of International Economics, Elsevier, vol. 139(C).
• Xu, Shuzhe & Zhang, Chuanlong & Hong, Don, 2022. "BERT-based NLP techniques for classification and severity modeling in basic warranty data study," Insurance: Mathematics and Economics, Elsevier, vol. 107(C), pages 57-67.
• Borochin, Paul & Rush, Stephen, 2022. "Information networks in the financial sector and systemic risk," Journal of Banking & Finance, Elsevier, vol. 134(C).
• Faryna, Oleksandr & Pham, Tho & Talavera, Oleksandr & Tsapin, Andriy, 2022. "Wage and unemployment: Evidence from online job vacancy data," Journal of Comparative Economics, Elsevier, vol. 50(1), pages 52-70.
• Scoles, Brooke & Nicodemo, Catia, 2022. "Doctors’ attitudes toward specific medical conditions," Journal of Economic Behavior & Organization, Elsevier, vol. 204(C), pages 182-199.
• Gómez-Cram, Roberto & Grotteria, Marco, 2022. "Real-time price discovery via verbal communication: Method and application to Fedspeak," Journal of Financial Economics, Elsevier, vol. 143(3), pages 993-1025.
• Leippold, Markus & Wang, Qian & Zhou, Wenyu, 2022. "Machine learning in the Chinese stock market," Journal of Financial Economics, Elsevier, vol. 145(2), pages 64-82.
• Moench, Emanuel & Soofi-Siavash, Soroosh, 2022. "What moves treasury yields?," Journal of Financial Economics, Elsevier, vol. 146(3), pages 1016-1043.
  • Soroosh Soofi-Siavash & Emanuel Moench, 2021. "What Moves Treasury Yields?," Bank of Lithuania Working Paper Series 88, Bank of Lithuania.
  • Moench, Emanuel & Soofi Siavash, Soroosh, 2022. "What Moves Treasury Yields?," CEPR Discussion Papers 15978, C.E.P.R. Discussion Papers.
• Anderegg, Benjamin & Ulmann, Florian & Sornette, Didier, 2022. "The impact of option hedging on the spot market volatility," Journal of International Money and Finance, Elsevier, vol. 124(C).
• Crane, Leland D. & Decker, Ryan A. & Flaaen, Aaron & Hamins-Puertolas, Adrian & Kurz, Christopher, 2022. "Business exit during the COVID-19 pandemic: Non-traditional measures in historical context," Journal of Macroeconomics, Elsevier, vol. 72(C).
  • Leland D. Crane & Ryan A. Decker & Aaron Flaaen & Adrian Hamins-Puertolas & Christopher J. Kurz, 2020. "Business Exit During the COVID-19 Pandemic: Non-Traditional Measures in Historical Context," Finance and Economics Discussion Series 2020-089r1, Board of Governors of the Federal Reserve System (U.S.), revised 15 Apr 2021.
• Bolton, Ruth N. & Gustafsson, Anders & Tarasi, Crina O. & Witell, Lars, 2022. "Managing a Global Retail Brand in Different Markets: Meta-Analyses of Customer Responses to Service Encounters," Journal of Retailing, Elsevier, vol. 98(2), pages 294-314.
• Kumar, Pawan & Singh, Vipul Kumar, 2022. "Systemic spillover dynamics of crude oil with Indian Financial indicators in post WPI revision and COVID era," Resources Policy, Elsevier, vol. 77(C).
• Koomen, Miriam & Backes-Gellner, Uschi, 2022. "Occupational tasks and wage inequality in West Germany: A decomposition analysis," Labour Economics, Elsevier, vol. 79(C).
  • Miriam Koomen & Uschi Backes-Gellner, 2015. "Occupational Tasks and Wage Inequality in West Germany: A Decomposition Analysis," Economics of Education Working Paper Series 0112, University of Zurich, Department of Business Administration (IBW), revised Oct 2022.
• Ahelegbey, Daniel Felix & Giudici, Paolo, 2022. "NetVIX — A network volatility index of financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 594(C).
  • Daniel Felix Ahelegbey & Paolo Giudici, 2020. "NetVIX - A Network Volatility Index of Financial Markets," DEM Working Papers Series 192, University of Pavia, Department of Economics and Management.
• Parle, Conor, 2022. "The financial market impact of ECB monetary policy press conferences — A text based approach," European Journal of Political Economy, Elsevier, vol. 74(C).
  • Parle, Conor, 2021. "The financial market impact of ECB monetary policy press conferences - a text based approach," Research Technical Papers 4/RT/21, Central Bank of Ireland.
• Diaf, Sami & Döpke, Jörg & Fritsche, Ulrich & Rockenbach, Ida, 2022. "Sharks and minnows in a shoal of words: Measuring latent ideological positions based on text mining techniques," European Journal of Political Economy, Elsevier, vol. 75(C).
• Nathan, Max & Rosso, Anna, 2022. "Innovative events: product launches, innovation and firm performance," Research Policy, Elsevier, vol. 51(1).
• Yankol-Schalck, Meryem, 2022. "The value of cross-data set analysis for automobile insurance fraud detection," Research in International Business and Finance, Elsevier, vol. 63(C).
• Saha, Shree & Narayanan, Sudha, 2022. "A simplified measure of nutritional empowerment: Using machine learning to abbreviate the Women’s Empowerment in Nutrition Index (WENI)," World Development, Elsevier, vol. 154(C).
  • Shree Saha & Sudha Narayanan, 2020. "A Simplified measure of nutritional empowerment using machine learning to abbreviate the Women's Empowerment in Nutrition Index (WENI)," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2020-031, Indira Gandhi Institute of Development Research, Mumbai, India.
• Meeks, Roland & Monti, Francesca, 2023. "Heterogeneous beliefs and the Phillips curve," Journal of Monetary Economics, Elsevier, vol. 139(C), pages 41-54.
  • Meeks, Roland & Monti, Francesca, 2019. "Heterogeneous beliefs and the Phillips curve," Bank of England working papers 807, Bank of England.
  • Roland Meeks & Francesca Monti, 2022. "Heterogeneous Beliefs and the Phillips Curve," CAMA Working Papers 2022-51, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Meeks, Roland & Monti, Francesca, 2022. "Heterogeneous beliefs and the Phillips curve," CEPR Discussion Papers 17537, C.E.P.R. Discussion Papers.
• Efrem Castelnuovo & Kerem Tuzcuoglu & Luis Uzeda, 2024. "Sectoral uncertainty," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Granular data: new horizons and challenges, volume 61, Bank for International Settlements.
  • Efrem Castelnuovo & Kerem Tuzcuoglu & Luis Uzeda, 2022. "Sectoral Uncertainty," "Marco Fanno" Working Papers 0288, Dipartimento di Scienze Economiche "Marco Fanno".
  • Efrem Castelnuovo & Kerem Tuzcuoglu & Luis Uzeda, 2022. "Sectoral Uncertainty," CAMA Working Papers 2022-62, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Efrem Castelnuovo & Kerem Tuzcuoglu & Luis Uzeda, 2022. "Sectoral Uncertainty," CESifo Working Paper Series 10034, CESifo.
  • Efrem Castelnuovo & Kerem Tuzcuoglu & Luis Uzeda, 2022. "Sectoral Uncertainty," Staff Working Papers 22-38, Bank of Canada.
• Pierre Guérin & Danilo Leiva-León, 2022. "Heterogeneous Switching in FAVAR Models," Advances in Econometrics, in: Essays in Honour of Fabio Canova, volume 44, pages 65-98, Emerald Group Publishing Limited.
• Luca Tiozzo Pezzoli & Elisa Tosetti, 2022. "Exploring the Economic Effects of COVID-19 in the United States through the Seismograph," Contributions to Economic Analysis, in: The Economics of COVID-19, volume 127, pages 85-93, Emerald Group Publishing Limited.
• Isaac K. Ofori & Camara K. Obeng & Simplice A. Asongu, 2024. "What Really Drives Economic Growth in Sub-Saharan Africa? Evidence from the Lasso Regularization and Inferential Techniques," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(1), pages 144-179, March.
  • Isaac K. Ofori & Camara K. Obeng & Simplice A. Asongu, 2022. "What Really Drives Economic Growth in Sub-Saharan Africa? Evidence from The Lasso Regularization and Inferential Techniques," Working Papers of the African Governance and Development Institute. 22/061, African Governance and Development Institute..
  • Isaac K. Ofori & Camara K. Obeng & Simplice A. Asongu, 2022. "What Really Drives Economic Growth in Sub-Saharan Africa? Evidence from The Lasso Regularization and Inferential Techniques," Working Papers 22/061, European Xtramile Centre of African Studies (EXCAS).
• Kirstin Hubrich & Daniel F. Waggoner, 2022. "The transmission of financial shocks and leverage of financial institutions: An endogenous regime switching framework," Finance and Economics Discussion Series 2022-034, Board of Governors of the Federal Reserve System (U.S.).
  • Kirstin Hubrich & Daniel F. Waggoner, 2022. "The Transmission of Financial Shocks and Leverage of Financial Institutions: An Endogenous Regime-Switching Framework," FRB Atlanta Working Paper 2022-5, Federal Reserve Bank of Atlanta.
• Kirstin Hubrich & Daniel F. Waggoner, 2022. "The Transmission of Financial Shocks and Leverage of Financial Institutions: An Endogenous Regime-Switching Framework," FRB Atlanta Working Paper 2022-5, Federal Reserve Bank of Atlanta.
  • Kirstin Hubrich & Daniel F. Waggoner, 2022. "The transmission of financial shocks and leverage of financial institutions: An endogenous regime switching framework," Finance and Economics Discussion Series 2022-034, Board of Governors of the Federal Reserve System (U.S.).
• Nelson P. Rayl & Nitish R. Sinha, 2022. "Integrating Prediction and Attribution to Classify News," Finance and Economics Discussion Series 2022-042, Board of Governors of the Federal Reserve System (U.S.).
• Alexey S. Evseev & Rodion R. Latypov & Egor A. Postolit & Elena S. Sinelnikova-Muryleva, 2022. "Technical and Methodological Challenges of Collecting Price Data from Online Retailers [Технические И Методологические Проблемы Сбора Данных О Ценах Онлайн-Ритейлеров]," Russian Economic Development, Gaidar Institute for Economic Policy, issue 11, pages 36-45, November.
• Alexey S. Evseev & Rodion R. Latypov & Egor A. Postolit & Elena S. Sinelnikova-Muryleva, 2022. "Техданные О Ценах Онлайн-Ритейлеров Обладают Огромной Ценностью С Точки Зрения Экономической Науки: Их Использование Позволяет Уточнять Прогнозы Инфляции И Предвосхищать Будущие Тенденции В Моменте, К," Russian Economic Development (in Russian), Gaidar Institute for Economic Policy, issue 11, pages 36-45, November.
• Hector F. Calvo-Pardo & Tullio Mancini & Jose Olmo, 2022. "Machine Learning the Carbon Footprint of Bitcoin Mining," JRFM, MDPI, vol. 15(2), pages 1-30, February.
  • Calvo Pardo, Héctor & Olmo, Jose & Mancini, Tullio, 2021. "Machine Learning the Carbon Footprint of Bitcoin Mining," CEPR Discussion Papers 16267, C.E.P.R. Discussion Papers.
• Hagher Ben Rhomdhane & Brahim Mehdi Benlallouna, 2022. "Nowcasting real GDP in Tunisia using large datasets and mixed-frequency models," IHEID Working Papers 02-2022, Economics Section, The Graduate Institute of International Studies.
• Antonio Musa, 2022. "Nowcasting Bosnia and Herzegovina GDP in Real Time," IHEID Working Papers 08-2022, Economics Section, The Graduate Institute of International Studies.
• Marcela De Castro-Valderrama & Santiago Forero-Alvarado & Nicolas Moreno-Arias & Sara Naranjo-Saldarriaga, 2022. "Unravelling the Narratives Behind Macroeconomic Forecasts," IHEID Working Papers 18-2022, Economics Section, The Graduate Institute of International Studies.
• Miguel Cabello & Rafael Nivin, 2022. "Measuring Uncertainty and its effects in a Small Open Economy," IHEID Working Papers 25-2022, Economics Section, The Graduate Institute of International Studies.
• Marco Avarucci & Maddalena Cavicchioli & Mario Forni, 2022. "Frequency-band estimation of the number of factors detecting the main business cycle shocks," Working Papers 2022_13, Business School - Economics, University of Glasgow.
• Caroline Jardet & Baptiste Meunier, 2022. "Nowcasting world GDP growth with high‐frequency data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1181-1200, September.
  • Jardet Caroline & Meunier Baptiste, 2020. "Nowcasting World GDP Growth with High-Frequency Data," Working papers 788, Banque de France.
  • Caroline Jardet & Baptiste Meunier, 2022. "Nowcasting world GDP growth with high‐frequency data," Post-Print hal-03647097, HAL.
• Owoo, Nkechi Srodah & Lambon-Quayefio, Monica Puoma & Amaechina, Ebele, 2022. "Exploring the Evidence for Inward Diffusion of Soil Practices among Farmers in Nigeria: A Spatiotemporal Analysis," EfD Discussion Paper 22-8, Environment for Development, University of Gothenburg.
• Bertsch, Christoph & Hull, Isaiah & Lumsdaine, Robin L. & Zhang, Xin, 2022. "Central Bank Mandates and Monetary Policy Stances: through the Lens of Federal Reserve Speeches," Working Paper Series 417, Sveriges Riksbank (Central Bank of Sweden), revised 01 Sep 2024.
• Mühlbauer, Sabrina & Weber, Enzo, 2022. "Machine Learning for Labour Market Matching," IAB-Discussion Paper 202203, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
• Baumgartner Christoph & Srhoj Stjepan & Walde Janette, 2023. "Harmonization of Product Classifications: A Consistent Time Series of Economic Trade Activities," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 243(6), pages 643-662, December.
  • Christoph Baumgartner & Stjepan Srhoj & Janette F. Walde, 2022. "Harmonization of product classifications: A consistent time series of economic trade activities," Working Papers 2022-11, Faculty of Economics and Statistics, Universität Innsbruck.
• Christina Carty & Oscar Claveria, 2022. "“The nexus between variable renewable energy, economy and climate: Evidence from European countries by means of exploratory graphical analysis”," AQR Working Papers 202205, University of Barcelona, Regional Quantitative Analysis Group, revised May 2022.
  • Christina Carty & Oscar Claveria, 2022. ""The nexus between variable renewable energy, economy and climate: Evidence from European countries by means of exploratory graphical analysis"," IREA Working Papers 202207, University of Barcelona, Research Institute of Applied Economics, revised May 2022.
• Koomen, Miriam & Backes-Gellner, Uschi, 2022. "Occupational Tasks and Wage Inequality in Germany: A Decomposition Analysis," IZA Discussion Papers 15702, Institute of Labor Economics (IZA).
• Erwin, Christopher & Hennecke, Juliane & Meehan, Lisa & Pacheco, Gail, 2022. "Dynamic Relationships between Criminal Offending and Victimization," IZA Discussion Papers 15757, Institute of Labor Economics (IZA).
• William A. Barnett & Kun He & Jingtong He, 2022. "Consumption Loan Augmented Divisia Monetary Index and China Monetary Aggregation," JRFM, MDPI, vol. 15(10), pages 1-17, October.
  • William Barnett & Kun He & Jingtong He, 2022. "Consumption Loan Augmented Divisia Monetary Index and China Monetary Aggregation," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202217, University of Kansas, Department of Economics.
• Ivana Lolić & Petar Sorić & Marija Logarušić, 2022. "Economic Policy Uncertainty Index Meets Ensemble Learning," Computational Economics, Springer;Society for Computational Economics, vol. 60(2), pages 401-437, August.
  • Ivana Loli? & Petar Sori? & Marija Logaru?i?, 0000. "Economic Policy Uncertainty index meets ensemble learning," Proceedings of International Academic Conferences 11313180, International Institute of Social and Economic Sciences.
• Gabriele Mazzolini & Laura Pagani & Alessandro Santoro, 2022. "The deterrence effect of real-world operational tax audits on self-employed taxpayers: evidence from Italy," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 29(4), pages 1014-1046, August.
• Michela Giorcelli & Nicola Lacetera & Astrid Marinoni, 2022. "How does scientific progress affect cultural changes? A digital text analysis," Journal of Economic Growth, Springer, vol. 27(3), pages 415-452, September.
  • Michela Giorcelli & Nicola Lacetera & Astrid Marinoni, 2019. "How Does Scientific Progress Affect Cultural Changes? A Digital Text Analysis," NBER Working Papers 25429, National Bureau of Economic Research, Inc.
• Haoying Wang & Guohui Wu, 2022. "Modeling discrete choices with large fine-scale spatial data: opportunities and challenges," Journal of Geographical Systems, Springer, vol. 24(3), pages 325-351, July.
• Jonas Klos & Tim Krieger & Sven Stöwhase, 2022. "Measuring intra-generational redistribution in PAYG pension schemes," Public Choice, Springer, vol. 190(1), pages 53-73, January.
  • Klos, Jonas & Krieger, Tim & Stöwhase, Sven, 2020. "Measuring intra-generational redistribution in PAYG pension schemes," Discussion Paper Series 2020-01, University of Freiburg, Wilfried Guth Endowed Chair for Constitutional Political Economy and Competition Policy.
  • Jonas Klos & Tim Krieger & Sven Stöwhase, 2020. "Measuring Intra-Generational Redistribution in PAYG Pension Schemes," CESifo Working Paper Series 8200, CESifo.
• N. Meltem Daysal & Sendhil Mullainathan & Ziad Obermeyer & Suproteem K. Sarkar & Mircea Trandafir, 2022. "An Economic Approach to Machine Learning in Health Policy," CEBI working paper series 22-24, University of Copenhagen. Department of Economics. The Center for Economic Behavior and Inequality (CEBI).
• Bernd Hayo & Johannes Zahner, 2022. "What’s that noise? Analysing sentiment-based variation in central bank communication," MAGKS Papers on Economics 202241, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
• Daniele Spinelli & Paolo Berta & Alessandro Santoro, 2022. "The Optimal Number of Tax Audits: Evidence from Italy," Working Papers 497, University of Milano-Bicocca, Department of Economics, revised Apr 2022.
• Balazs J. Csillag & Marcell P. Granat & Gabor Neszveda, 2022. "Media Attention to Environmental Issues and ESG Investing," Financial and Economic Review, Magyar Nemzeti Bank (Central Bank of Hungary), vol. 21(4), pages 129-149.
• Marianna Brunetti & Roberta De Luca, 2023. "Pre-selection in cointegration-based pairs trading," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(5), pages 1611-1640, December.
  • Marianna Brunetti & Roberta De Luca, 2020. "Pre-selection in Cointegration-based Pairs Trading," CEIS Research Paper 500, Tor Vergata University, CEIS, revised 10 Mar 2021.
  • Marianna Brunetti & Roberta de Luca, 2022. "Pre-selection in cointegration-based pairs trading," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0089, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
• Marianna Brunetti & Roberta De Luca, 2022. "Sensitivity of Profitability in Cointegration-Based Pairs Trading," CEIS Research Paper 540, Tor Vergata University, CEIS, revised 11 Apr 2022.
  • Marianna Brunetti & Roberta de Luca, 2022. "Sensitivity of profitability in cointegration-based pairs trading," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0090, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
• Cody Cook & Lindsey Currier & Edward L. Glaeser, 2022. "Urban Mobility and the Experienced Isolation of Students," NBER Working Papers 29645, National Bureau of Economic Research, Inc.
• Michael L. Anderson & Jeremy Magruder, 2022. "Highly Powered Analysis Plans," NBER Working Papers 29843, National Bureau of Economic Research, Inc.
• Veli Andirin & Yusuf Neggers & Mehdi Shadmehr & Jesse M. Shapiro, 2022. "Real-time Surveillance of Repression: Theory and Implementation," NBER Working Papers 30167, National Bureau of Economic Research, Inc.
• Joelle Noailly & Laura Nowzohour & Matthias van den Heuvel, 2022. "Does Environmental Policy Uncertainty Hinder Investments Towards a Low-Carbon Economy?," NBER Working Papers 30361, National Bureau of Economic Research, Inc.
• Galiani, Sebastian & Quistorff, Brian, 2024. "Assessing external validity in practice," Research in Economics, Elsevier, vol. 78(3).
  • Sebastian Galiani & Brian Quistorff, 2022. "Assessing External Validity in Practice," NBER Working Papers 30398, National Bureau of Economic Research, Inc.
• Florenta Teodoridis & Jino Lu & Jeffrey L. Furman, 2022. "Mapping the Knowledge Space: Exploiting Unassisted Machine Learning Tools," NBER Working Papers 30603, National Bureau of Economic Research, Inc.
• Mirko Ðukic, 2022. "Assessment of inflationary pressures using newspaper text analysis," Working Papers Bulletin 12, National Bank of Serbia.
• S. Quantin & C. Welter-Mã‰Dã‰E, 2022. "Estimation des montants manquants de versements de TVA: exploitation des données du contrôle fiscal," Documents de Travail de l'Insee - INSEE Working Papers 2022-11, Institut National de la Statistique et des Etudes Economiques.
• Michael J Mahony & Josh Martin, 2022. "Matching UK Business Microdata – A Study Using ONS and CBI Business Surveys," Economic Statistics Centre of Excellence (ESCoE) Technical Reports ESCOE-TR-14, Economic Statistics Centre of Excellence (ESCoE).
• Bhattacharjee, Arnab & Aravena, Claudia & Castillo, Natalia & Ehrlich, Marco & Taou, Nadia & Wagner, Thomas, 2022. "Agroforestry Programs in the Colombian Amazon: Selection, Treatment and Exposure Effects on Deforestation," National Institute of Economic and Social Research (NIESR) Discussion Papers 537, National Institute of Economic and Social Research.
• David Kohns & Arnab Bhattacharjee, 2020. "Nowcasting Growth using Google Trends Data: A Bayesian Structural Time Series Model," Papers 2011.00938, arXiv.org, revised May 2022.
  • Bhattacharjee, Arnab & Kohns, David, 2022. "Nowcasting Growth using Google Trends Data: A Bayesian Structural Time Series Model," National Institute of Economic and Social Research (NIESR) Discussion Papers 538, National Institute of Economic and Social Research.
• Hannes Mueller & Christopher Rauh, 2022. "The Hard Problem of Prediction for Conflict Prevention," Journal of the European Economic Association, European Economic Association, vol. 20(6), pages 2440-2467.
  • Hannes Mueller & Christopher Rauh, 2019. "The hard problem of prediction for conflict prevention," Cahiers de recherche 2019-02, Universite de Montreal, Departement de sciences economiques.
  • Hannes Mueller & Christopher Rauh, 2021. "The Hard Problem of Prediction for Conflict Prevention," Working Papers 1244, Barcelona School of Economics.
  • Mueller, H. & Rauh, C., 2021. "The Hard Problem of Prediction for Conflict Prevention," Cambridge Working Papers in Economics 2103, Faculty of Economics, University of Cambridge.
  • Mueller, H. & Rauh, C., 2020. "The Hard Problem of Prediction for Conflict Prevention," Cambridge Working Papers in Economics 2015, Faculty of Economics, University of Cambridge.
  • Hannes Mueller & Christopher Rauh, 2019. "The Hard Problem of Prediction for Conflict Prevention," Cahiers de recherche 02-2019, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
  • Mueller, Hannes & Rauh, Christopher, 2019. "The Hard Problem of Prediction for Conflict Prevention," CEPR Discussion Papers 13748, C.E.P.R. Discussion Papers.
• Julian Nyarko & Sarath Sanga, 2022. "A Statistical Test for Legal Interpretation: Theory and Applications," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 38(2), pages 539-569.
• Andrew J Patton & Brian M Weller, 2022. "Risk Price Variation: The Missing Half of Empirical Asset Pricing," The Review of Financial Studies, Society for Financial Studies, vol. 35(11), pages 5127-5184.
• Guellil, Mohammed Seghir & Sari-Hassoun, Salah Eddine & Chica-Olmo, Jorge & Saraç, Mehmet, 2022. "What are the main factors driving behind the MENA countries current account deficit? A panel logit approach analysis [¿Cuáles son los principales factores que impulsan el déficit de cuenta corrient," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 33(1), pages 134-153, June.
• Efrem Castelnuovo & Kerem Tuzcuoglu & Luis Uzeda, 2024. "Sectoral uncertainty," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Granular data: new horizons and challenges, volume 61, Bank for International Settlements.
  • Efrem Castelnuovo & Kerem Tuzcuoglu & Luis Uzeda, 2022. "Sectoral Uncertainty," Staff Working Papers 22-38, Bank of Canada.
  • Efrem Castelnuovo & Kerem Tuzcuoglu & Luis Uzeda, 2022. "Sectoral Uncertainty," "Marco Fanno" Working Papers 0288, Dipartimento di Scienze Economiche "Marco Fanno".
  • Efrem Castelnuovo & Kerem Tuzcuoglu & Luis Uzeda, 2022. "Sectoral Uncertainty," CESifo Working Paper Series 10034, CESifo.
  • Efrem Castelnuovo & Kerem Tuzcuoglu & Luis Uzeda, 2022. "Sectoral Uncertainty," CAMA Working Papers 2022-62, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Christoph J. Börner & Ingo Hoffmann & Jonas Krettek & Tim Schmitz, 2022. "Bitcoin: like a satellite or always hardcore? A core–satellite identification in the cryptocurrency market," Journal of Asset Management, Palgrave Macmillan, vol. 23(4), pages 310-321, July.
• Simone Arrigoni & Alina Bobasu & Fabrizio Venditti, 2022. "Measuring Financial Conditions using Equal Weights Combination," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 70(4), pages 668-697, December.
• Anna Nowak & Armand Kasztelan, 2022. "Economic competitiveness vs. green competitiveness of agriculture in the European Union countries," Oeconomia Copernicana, Institute of Economic Research, vol. 13(2), pages 379-405, June.
• Eloisa T. Glindro & Jean Christine A. Armas & V. Bruce J. Tolentino & Lorna Dela Cruz-Sombe, 2022. "Heterogenous impact of monetary policy on the Philippine rural banking system," Philippine Review of Economics, University of the Philippines School of Economics and Philippine Economic Society, vol. 59(2), pages 111-134, December.
• Syed Ateeb Akhter Shah & Muhammad Ishtiaq & Sumbal Qureshi & Kaneez Fatima, 2022. "Inflation Forecasting for Pakistan in a Data-rich Environment (Article)," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 61(4), pages 643-658.
• Levy, Daniel & Mayer, Tamir & Raviv, Alon, 2022. "Economists in the 2008 financial crisis: Slow to see, fast to act," Journal of Financial Stability, Elsevier, vol. 60(C).
  • Levy, Daniel & Mayer, Tamir & Raviv, Alon, 2022. "Economists in the 2008 Financial Crisis: Slow to See, Fast to Act," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, issue Forthcomi.
  • Daniel Levy & Tamir Mayer & Alon Raviv, 2022. "Economists in the 2008 Financial Crisis: Slow to See, Fast to Act," Working Paper series 22-04, Rimini Centre for Economic Analysis.
  • Levy, Daniel & Mayer, Tamir & Raviv, Alon, 2022. "Economists in the 2008 Financial Crisis: Slow to See, Fast to Act," MPRA Paper 112008, University Library of Munich, Germany.
  • Daniel Levy & Tamir Mayer & Alon Raviv, 2022. "Economists in the 2008 Financial Crisis: Slow to See, Fast to Act," Working Papers 2022-01, Bar-Ilan University, Department of Economics.
• Porras-Arena, M. Sylvina & Martín-Román, Ángel L., 2023. "The heterogeneity of Okun's law: A metaregression analysis," Economic Modelling, Elsevier, vol. 128(C).
  • Porras-Arena, M. Sylvina & Martín-Román, Ángel L., 2022. "The heterogeneity of Okun's law: A metaregression analysis," GLO Discussion Paper Series 1069, Global Labor Organization (GLO).
  • Porras, María Sylvina & Martín-Román, Ángel L., 2022. "The heterogeneity of Okun’s law: A metaregression analysis," MPRA Paper 112442, University Library of Munich, Germany.
• Giovanni Urga & Fa Wang, 2022. "Estimation and Inference for High Dimensional Factor Model with Regime Switching," Papers 2205.12126, arXiv.org, revised Apr 2023.
  • Urga, Giovanni & Wang, Fa, 2022. "Estimation and inference for high dimensional factor model with regime switching," MPRA Paper 113172, University Library of Munich, Germany.
• Mputu Losala Lomo, Denis-Robert, 2022. "Application de la Classification Ascendante Hiérarchique à la Répartition des Ressources Budgétaires dans la Ville-Province de Kinshasa [Application of Hierarchical Ascendant Clustering to the Dist," MPRA Paper 113774, University Library of Munich, Germany.
• Urga, Giovanni & Wang, Fa, 2022. "Estimation and Inference for High Dimensional Factor Model with Regime Switching," MPRA Paper 117012, University Library of Munich, Germany, revised 10 Apr 2023.
• Lycheva, Maria & Mironenkov, Alexey & Kurbatskii, Alexey & Fantazzini, Dean, 2022. "Forecasting oil prices with penalized regressions, variance risk premia and Google data," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 68, pages 28-49.
  • Fantazzini, Dean & Kurbatskii, Alexey & Mironenkov, Alexey & Lycheva, Maria, 2022. "Forecasting oil prices with penalized regressions, variance risk premia and Google data," MPRA Paper 118239, University Library of Munich, Germany.
• António Rua & Nuno Lourenço, 2022. "Business cycle clocks: Time to get circular," Working Papers w202201, Banco de Portugal, Economics and Research Department.
• Filipe B. Caires & Hugo Reis & Paulo M. M. Rodrigues, 2023. "Survival of the fittest: tourism exposure and firm survival," Applied Economics, Taylor & Francis Journals, vol. 55(60), pages 7150-7177, December.
  • Hugo Reis & Paulo M.M. Rodrigues & Filipe B. Caires, 2022. "Survival of the fittest: Tourism Exposure and Firm Survival," Working Papers w202206, Banco de Portugal, Economics and Research Department.
• MacKinnon, James G., 2023. "Using large samples in econometrics," Journal of Econometrics, Elsevier, vol. 235(2), pages 922-926.
  • James G. MacKinnon, 2022. "Using Large Samples in Econometrics," Working Paper 1482, Economics Department, Queen's University.
• Byron Botha & Rulof Burger & Kevin Kotzé & Neil Rankin & Daan Steenkamp, 2023. "Big data forecasting of South African inflation," Empirical Economics, Springer, vol. 65(1), pages 149-188, July.
  • Byron Botha & Kevin Kotze & Neil Rankin & Rulof P. Burger, 2022. "Big data forecasting of South African inflation," Working Papers 873, Economic Research Southern Africa.
  • Byron Botha & Rulof Burger & Kevin Kotz & Neil Rankin & Daan Steenkamp, 2022. "Big data forecasting of South African inflation," Working Papers 11022, South African Reserve Bank.
  • Byron Botha & Rulof Burger & Kevin Kotze & Neil Rankin & Daan Steenkamp, 2022. "Big data forecasting of South African inflation," School of Economics Macroeconomic Discussion Paper Series 2022-03, School of Economics, University of Cape Town.
• Karymshakov, Kamalbek & Azhgaliyeva, Dina & Mishra, Ranjeeta & Aseinov, Dastan, 2022. "Evaluating COVID-19’s Impact on Firm Performance in the CAREC Region Using Night-Time Light Data: Azerbaijan, Georgia, Kazakhstan, and Mongolia," ADBI Working Papers 1332, Asian Development Bank Institute.
• Zubarev, Andrei & Kirillova, Maria, 2022. "Modeling COVID-19 spread in the Russian Federation using global VAR approach," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 65, pages 117-138.
• Lycheva, Maria & Mironenkov, Alexey & Kurbatskii, Alexey & Fantazzini, Dean, 2022. "Forecasting oil prices with penalized regressions, variance risk premia and Google data," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 68, pages 28-49.
  • Fantazzini, Dean & Kurbatskii, Alexey & Mironenkov, Alexey & Lycheva, Maria, 2022. "Forecasting oil prices with penalized regressions, variance risk premia and Google data," MPRA Paper 118239, University Library of Munich, Germany.
• Ocasio, Emily & Potter, Tristan, 2023. "Demographic Correlates of Humanizing Language in Media Coverage of Crime: Evidence from the Boston Globe, 1976-84," School of Economics Working Paper Series 2023-1, LeBow College of Business, Drexel University.
• Marianna Brunetti & Roberta de Luca, 2022. "Sensitivity of profitability in cointegration-based pairs trading," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0090, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
  • Marianna Brunetti & Roberta De Luca, 2022. "Sensitivity of Profitability in Cointegration-Based Pairs Trading," CEIS Research Paper 540, Tor Vergata University, CEIS, revised 11 Apr 2022.
• Riccardo Di Francesco, 2022. "Aggregation Trees," CEIS Research Paper 546, Tor Vergata University, CEIS, revised 20 Nov 2023.
• Eduard van der Merwe & Matthew Clance & Eleni Yitbarek, 2022. "Climate Change and Child Health: A Nigerian Perspective," Working Papers 202223, University of Pretoria, Department of Economics.
  • Eduard van der Merwe & Eleni Yitbarek & Matthew W. Clance, 2022. "Climate change and child health: A Nigerian perspective," Working Papers 871, Economic Research Southern Africa.
• Byron Botha & Rulof Burger & Kevin Kotzé & Neil Rankin & Daan Steenkamp, 2023. "Big data forecasting of South African inflation," Empirical Economics, Springer, vol. 65(1), pages 149-188, July.
  • Byron Botha & Rulof Burger & Kevin Kotze & Neil Rankin & Daan Steenkamp, 2022. "Big data forecasting of South African inflation," School of Economics Macroeconomic Discussion Paper Series 2022-03, School of Economics, University of Cape Town.
  • Byron Botha & Kevin Kotze & Neil Rankin & Rulof P. Burger, 2022. "Big data forecasting of South African inflation," Working Papers 873, Economic Research Southern Africa.
  • Byron Botha & Rulof Burger & Kevin Kotz & Neil Rankin & Daan Steenkamp, 2022. "Big data forecasting of South African inflation," Working Papers 11022, South African Reserve Bank.
• Tomasz P. Kostyra, 2022. "Yield Curve Modelling with the Nelson-Siegel Method for Poland," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 2, pages 44-56.
• Dimitar Haralampiev Popov, 2022. "SME Viability Assessment Methodology: Combining Altman's Z-Score with Big Data," Bulgarian Economic Papers bep-2022-04, Faculty of Economics and Business Administration, Sofia University St Kliment Ohridski - Bulgaria // Center for Economic Theories and Policies at Sofia University St Kliment Ohridski, revised Jun 2022.
• Eduardo A. Haddad & Renato S. Vieira & Inácio F. Araújo & Silvio M. Ichihara & Fernando S. Perobelli & Karina S. S. Bugarin, 2022. "COVID-19 crisis monitor: assessing the effectiveness of exit strategies in the State of São Paulo, Brazil," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 68(2), pages 501-525, April.
  • Haddad, Eduardo & Vieira, Renato & Araújo, Inácio & Ichihara, Silvio & Perobelli, Fernando & Bugarin, Karina, 2020. "COVID-19 Crisis Monitor: Assessing the Effectiveness of Exit Strategies in the State of São Paulo, Brazil," TD NEREUS 6-2020, Núcleo de Economia Regional e Urbana da Universidade de São Paulo (NEREUS).
  • Eduardo A Haddad & Renato S Vieira & Inacio F Araujo & Silvio Ichihara & Fernando S Perobelli & Karina Bugarin, 2022. "COVID-19 Crisis Monitor: Assessing the Effectiveness of Exit Strategies in the State of São Paulo, Brazil," Working Papers, Department of Economics 2022_10, University of São Paulo (FEA-USP).
• Jose Antonio Leon & Mario Ordaz & Eduardo A Haddad & Inacio F. Araujo, 2022. "Riesgo Causado por la Propagación de las Pérdidas por Terremoto a través de la Economía Mediante el uso de Modelos CGE Espaciales," Working Papers, Department of Economics 2022_11, University of São Paulo (FEA-USP).
• Eduardo A. Haddad & Renato S. Vieira & Inácio F. Araújo & Silvio M. Ichihara & Fernando S. Perobelli & Karina S. S. Bugarin, 2022. "COVID-19 crisis monitor: assessing the effectiveness of exit strategies in the State of São Paulo, Brazil," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 68(2), pages 501-525, April.
  • Haddad, Eduardo & Vieira, Renato & Araújo, Inácio & Ichihara, Silvio & Perobelli, Fernando & Bugarin, Karina, 2020. "COVID-19 Crisis Monitor: Assessing the Effectiveness of Exit Strategies in the State of São Paulo, Brazil," TD NEREUS 6-2020, Núcleo de Economia Regional e Urbana da Universidade de São Paulo (NEREUS).
  • Eduardo A Haddad & Renato S Vieira & Inacio F Araujo & Silvio Ichihara & Fernando S Perobelli & Karina Bugarin, 2022. "COVID-19 Crisis Monitor: Assessing the Effectiveness of Exit Strategies in the State of São Paulo, Brazil," Working Papers, Department of Economics 2022_10, University of São Paulo (FEA-USP).
• Joseph Junior Aduba, 2022. "Framework for firm-level performance evaluations using multivariate linear correlation with MCDM methods: application to Japanese firms," Asia-Pacific Journal of Regional Science, Springer, vol. 6(1), pages 1-44, February.
• Maral Taşcılar & Kerem Yavuz Arslanlı, 2022. "Forecasting commercial real estate indicators under COVID-19 by adopting human activity using social big data," Asia-Pacific Journal of Regional Science, Springer, vol. 6(3), pages 1111-1132, October.
• Helmut Wasserbacher & Martin Spindler, 2022. "Machine learning for financial forecasting, planning and analysis: recent developments and pitfalls," Digital Finance, Springer, vol. 4(1), pages 63-88, March.
• Sylwia Sysko-Romańczuk & Piotr Zaborek & Anna Wróblewska & Jacek Dąbrowski & Sergiy Tkachuk, 2022. "Data modalities, consumer attributes and recommendation performance in the fashion industry," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(3), pages 1279-1292, September.
• Shuolin Shi & Ralf A. Wilke, 2022. "Variable selection with group structure: exiting employment at retirement age—a competing risks quantile regression analysis," Empirical Economics, Springer, vol. 62(1), pages 119-155, January.
• Matthias Raddant & Hiroshi Takahashi, 2022. "Corporate boards, interorganizational ties and profitability: the case of Japan," Empirical Economics, Springer, vol. 62(3), pages 1365-1406, March.
  • Raddant, Matthias & Takahashi, Hiroshi, 2020. "Corporate boards, interorganizational ties and profitability: The case of Japan," Economics Working Papers 2020-02, Christian-Albrechts-University of Kiel, Department of Economics.
• Mohammad Vesal & Amir Hossein Tavakoli & Mohammad H. Rahmati, 2022. "What do one hundred million transactions tell us about demand elasticity of gasoline?," Empirical Economics, Springer, vol. 62(6), pages 2693-2711, June.
  • Rahmati, Mohammad Hossein & Tavakoli, Amirhossein & Vesal, Mohammad, 2019. "What do one hundred million transactions tell us about demand elasticity of gasoline?," MPRA Paper 97858, University Library of Munich, Germany.
• Christian Glocker & Serguei Kaniovski, 2022. "Macroeconometric forecasting using a cluster of dynamic factor models," Empirical Economics, Springer, vol. 63(1), pages 43-91, July.
  • Christian Glocker & Serguei Kaniovski, 2020. "Macroeconometric Forecasting Using a Cluster of Dynamic Factor Models," WIFO Working Papers 614, WIFO.
• Nadezhda Baryshnikova & Shannon Davidson & Dennis Wesselbaum, 2022. "Do you feel the heat around the corner? The effect of weather on crime," Empirical Economics, Springer, vol. 63(1), pages 179-199, July.
  • Nadezdha Baryshnikova & Shannon. F. Davidson & Dennis Wesselbaum, 2019. "Do you Feel the Heat Around the Corner? The Effect of Weather on Crime," School of Economics and Public Policy Working Papers 2019-07, University of Adelaide, School of Economics and Public Policy.
• Ioannis A. Nikas & Athanasios Koutras & Alkiviadis Panagopoulos & Anastasios Vasileiadis, 2022. "Exploring Tourists’ Food and Beverage Spots in an Urban Destination Using a Spatial–temporal Approach," Springer Proceedings in Business and Economics, in: Vicky Katsoni & Andreea Claudia Şerban (ed.), Transcending Borders in Tourism Through Innovation and Cultural Heritage, pages 977-989, Springer.
• Oleksandr Bartkoviak & Viktor Shpyrko & Oleksandr Chernyak & Yevgen Chernyak, 2022. "Statistical Arbitrage Using Cointegration and Principal Component Analysis Approach," Springer Proceedings in Business and Economics, in: Pantelis Sklias & Persefoni Polychronidou & Anastasios Karasavvoglou & Victoria Pistikou & Nikolaos (ed.), Business Development and Economic Governance in Southeastern Europe, pages 167-182, Springer.
• Steven T. Joanis & Vivek H. Patil, 2022. "First-author gender differentials in business journal publishing: top journals versus the rest," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(2), pages 733-761, February.
• Karen Miranda & Pilar Poncela & Esther Ruiz, 2022. "Dynamic factor models: Does the specification matter?," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 13(1), pages 397-428, May.
• Hannes Mueller & Christopher Rauh, 2022. "Using past violence and current news to predict changes in violence," International Interactions, Taylor & Francis Journals, vol. 48(4), pages 579-596, July.
  • Mueller, H. & Rauh, C., 2022. "Using Past Violence and Current News to Predict Changes in Violence," Janeway Institute Working Papers 2209, Faculty of Economics, University of Cambridge.
  • Mueller, H. & Rauh, C., 2022. "Using Past Violence and Current News to Predict Changes in Violence," Cambridge Working Papers in Economics 2220, Faculty of Economics, University of Cambridge.
• Daniel Borup & Erik Christian Montes Schütte, 2022. "In Search of a Job: Forecasting Employment Growth Using Google Trends," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 186-200, January.
  • Daniel Borup & Erik Christian Montes Schütte, 2019. "In search of a job: Forecasting employment growth using Google Trends," CREATES Research Papers 2019-13, Department of Economics and Business Economics, Aarhus University.
• Mengheng Li & Marcel Scharth, 2022. "Leverage, Asymmetry, and Heavy Tails in the High-Dimensional Factor Stochastic Volatility Model," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 285-301, January.
  • Mengheng Li & Marcel Scharth, 2018. "Leverage, asymmetry and heavy tails in the high-dimensional factor stochastic volatility model," Working Paper Series 49, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
• Joshua D. Angrist & Brigham Frandsen, 2022. "Machine Labor," Journal of Labor Economics, University of Chicago Press, vol. 40(S1), pages 97-140.
  • Joshua Angrist & Brigham Frandsen, 2019. "Machine Labor," NBER Working Papers 26584, National Bureau of Economic Research, Inc.
• Tae-Hwy Lee & Ekaterina Seregina, 2022. "Combining Forecasts under Structural Breaks Using Graphical LASSO," Papers 2209.01697, arXiv.org, revised Sep 2023.
  • Tae-Hwy Lee & Ekaterina Seregina, 2022. "Combining Forecasts under Structural Breaks Using Graphical LASSO," Working Papers 202213, University of California at Riverside, Department of Economics.
  • Tae-Hwy Lee & Ekaterina Seregina, 2023. "Combining Forecasts under Structural Breaks Using Graphical LASSO," Working Papers 202310, University of California at Riverside, Department of Economics.
• Tetiana Yukhymenko, 2022. "The Role of the Media in the Inflation Expectation Formation Process," Visnyk of the National Bank of Ukraine, National Bank of Ukraine, issue 253, pages 4-26.
• Waweru David & Mose Naftaly, 2022. "Household Fuel Choice in Urban Kenya: A Multinomial Logit Analysis," Financial Internet Quarterly (formerly e-Finanse), Sciendo, vol. 18(2), pages 30-41, June.
• Kevin Moran & Dalibor Stevanovic & Adam Kader Touré, 2022. "Macroeconomic uncertainty and the COVID‐19 pandemic: Measure and impacts on the Canadian economy," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 55(S1), pages 379-405, February.
  • Kevin Moran & Dalibor Stevanovic & Adam Kader Toure, 2020. "Macroeconomic Uncertainty and the COVID-19 Pandemic: Measure and Impacts on the Canadian Economy," Working Papers 20-18, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Dec 2020.
  • Kevin Moran & Dalibor Stevanovic & Adam Abdel Kader Touré, 2020. "Macroeconomic Uncertainty and the COVID-19 Pandemic: Measure and Impacts on the Canadian Economy," CIRANO Working Papers 2020s-47, CIRANO.
• Michael P. Clements, 2022. "Individual forecaster perceptions of the persistence of shocks to GDP," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(3), pages 640-656, April.
  • Michael P. Clements, 2020. "Individual Forecaster Perceptions of the Persistence of Shocks to GDP," ICMA Centre Discussion Papers in Finance icma-dp2020-02, Henley Business School, University of Reading.
• Eleni Kalamara & Arthur Turrell & Chris Redl & George Kapetanios & Sujit Kapadia, 2022. "Making text count: Economic forecasting using newspaper text," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 896-919, August.
  • Kalamara, Eleni & Turrell, Arthur & Redl, Chris & Kapetanios, George & Kapadia, Sujit, 2020. "Making text count: economic forecasting using newspaper text," Bank of England working papers 865, Bank of England.
• Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2022. "How is machine learning useful for macroeconomic forecasting?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 920-964, August.
  • Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2019. "How is Machine Learning Useful for Macroeconomic Forecasting?," CIRANO Working Papers 2019s-22, CIRANO.
  • Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & St'ephane Surprenant, 2020. "How is Machine Learning Useful for Macroeconomic Forecasting?," Papers 2008.12477, arXiv.org.
  • Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stephane Surprenant, 2020. "How is Machine Learning Useful for Macroeconomic Forecasting?," Working Papers 20-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Aug 2020.
• Massimo Ferrari Minesso & Frederik Kurcz & Maria Sole Pagliari, 2022. "Do words hurt more than actions? The impact of trade tensions on financial markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(6), pages 1138-1159, September.
  • Ferrari Minesso, Massimo & Pagliari, Maria Sole & Kurcz, Frederik, 2020. "Do words hurt more than actions? The impact of trade tensions on financial markets," Working Paper Series 2490, European Central Bank.
  • Massimo Ferrari & Frederik Kurcz & Maria Sole Pagliari, 2021. "Do Words Hurt More Than Actions? The Impact of Trade Tensions on Financial Markets," Working papers 802, Banque de France.
• Yu Bai & Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022. "Macroeconomic forecasting in a multi‐country context," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(6), pages 1230-1255, September.
  • Yu Bai & Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022. "Macroeconomic Forecasting in a Multi-country Context," Working Papers 22-02, Federal Reserve Bank of Cleveland.
  • Bai, Yu & Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano, 2022. "Macroeconomic Forecasting in a Multi-country Context," CEPR Discussion Papers 16994, C.E.P.R. Discussion Papers.
• Caroline Jardet & Baptiste Meunier, 2022. "Nowcasting world GDP growth with high‐frequency data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1181-1200, September.
  • Jardet Caroline & Meunier Baptiste, 2020. "Nowcasting World GDP Growth with High-Frequency Data," Working papers 788, Banque de France.
  • Caroline Jardet & Baptiste Meunier, 2022. "Nowcasting world GDP growth with high‐frequency data," Post-Print hal-03647097, HAL.
• Saskia Ter Ellen & Vegard H. Larsen & Leif Anders Thorsrud, 2022. "Narrative Monetary Policy Surprises and the Media," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(5), pages 1525-1549, August.
  • Saskia ter Ellen & Vegard H. Larsen & Leif Anders Thorsrud, 2019. "Narrative monetary policy surprises and the media," Working Papers No 06/2019, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • ter Ellen, Saskia & Larsen, Vegard H. & Thorsrud, Leif Anders, 2019. "Narrative monetary policy surprises and the media," Working Paper 2019/19, Norges Bank.
• Joshua C. C. Chan, 2022. "Asymmetric conjugate priors for large Bayesian VARs," Quantitative Economics, Econometric Society, vol. 13(3), pages 1145-1169, July.
  • Joshua C. C. Chan, 2019. "Asymmetric conjugate priors for large Bayesian VARs," CAMA Working Papers 2019-51, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Joshua C. C. Chan, 2021. "Asymmetric Conjugate Priors for Large Bayesian VARs," Papers 2111.07170, arXiv.org.
• M. Hashem Pesaran & Yimeng Xie, 2021. "A Bias-Corrected CD Test for Error Cross-Sectional Dependence in Panel Data Models with Latent Factors," Papers 2109.00408, arXiv.org, revised Apr 2023.
  • M. Hashem Pesaran & Yimeng Xie, 2022. "A Bias-Corrected CD Test for Error Cross-Sectional Dependence in Panel Data Models with Latent Factors," Working Papers 2022-06-10, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
  • M. Hashem Pesaran & Yimeng Xie, 2021. "A Bias-Corrected CD Test for Error Cross-Sectional Dependence in Panel Data Models with Latent Factors," CESifo Working Paper Series 9234, CESifo.
  • Pesaran, M. H. & Xie, Y., 2021. "A Bias-Corrected CD Test for Error Cross-Sectional Dependence in Panel Data Models with Latent Factors," Cambridge Working Papers in Economics 2158, Faculty of Economics, University of Cambridge.
• Levy, Daniel & Mayer, Tamir & Raviv, Alon, 2022. "Economists in the 2008 financial crisis: Slow to see, fast to act," Journal of Financial Stability, Elsevier, vol. 60(C).
  • Levy, Daniel & Mayer, Tamir & Raviv, Alon, 2022. "Economists in the 2008 Financial Crisis: Slow to See, Fast to Act," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, issue Forthcomi.
  • Levy, Daniel & Mayer, Tamir & Raviv, Alon, 2022. "Economists in the 2008 Financial Crisis: Slow to See, Fast to Act," MPRA Paper 112008, University Library of Munich, Germany.
  • Daniel Levy & Tamir Mayer & Alon Raviv, 2022. "Economists in the 2008 Financial Crisis: Slow to See, Fast to Act," Working Papers 2022-01, Bar-Ilan University, Department of Economics.
  • Daniel Levy & Tamir Mayer & Alon Raviv, 2022. "Economists in the 2008 Financial Crisis: Slow to See, Fast to Act," Working Paper series 22-04, Rimini Centre for Economic Analysis.
• Hauber, Philipp, 2022. "Real-time nowcasting with sparse factor models," EconStor Preprints 251551, ZBW - Leibniz Information Centre for Economics.
• Porras-Arena, M. Sylvina & Martín-Román, Ángel L., 2023. "The heterogeneity of Okun's law: A metaregression analysis," Economic Modelling, Elsevier, vol. 128(C).
  • Porras, María Sylvina & Martín-Román, Ángel L., 2022. "The heterogeneity of Okun’s law: A metaregression analysis," MPRA Paper 112442, University Library of Munich, Germany.
  • Porras-Arena, M. Sylvina & Martín-Román, Ángel L., 2022. "The heterogeneity of Okun's law: A metaregression analysis," GLO Discussion Paper Series 1069, Global Labor Organization (GLO).
• Rossouw, Stephanié & Greyling, Talita, 2022. "Collective emotions and macro-level shocks: COVID-19 vs the Ukrainian war," GLO Discussion Paper Series 1210, Global Labor Organization (GLO).
• Benner, Niklas & Lange, Kai-Robin & Jentsch, Carsten, 2022. "Named entity narratives," Ruhr Economic Papers 962, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
• Lange, Kai-Robin & Reccius, Matthias & Schmidt, Tobias & Müller, Henrik & Roos, Michael W. M. & Jentsch, Carsten, 2022. "Towards extracting collective economic narratives from texts," Ruhr Economic Papers 963, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
• Shrub, Yuliya & Rieger, Jonas & Müller, Henrik & Jentsch, Carsten, 2022. "Text data rule - don't they? A study on the (additional) information of Handelsblatt data for nowcasting German GDP in comparison to established economic indicators," Ruhr Economic Papers 964, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.

2021

• Daniel Borup & David E. Rapach & Erik Christian Montes Schütte, 2021. "Now- and Backcasting Initial Claims with High-Dimensional Daily Internet Search-Volume Data," CREATES Research Papers 2021-02, Department of Economics and Business Economics, Aarhus University.
• Gonzalez Rivera, Gloria & Rodríguez Caballero, Carlos Vladimir, 2021. "Expecting the unexpected: economic growth under stress," DES - Working Papers. Statistics and Econometrics. WS 32148, Universidad Carlos III de Madrid. Departamento de Estadística.
  • Gloria González-Rivera & Carlos Vladimir Rodríguez-Caballero & Esther Ruiz Ortega, 2021. "Expecting the unexpected: economic growth under stress," CREATES Research Papers 2021-06, Department of Economics and Business Economics, Aarhus University.
  • Gloria Gonzalez-Rivera & Vladimir Rodriguez-Caballero & Esther Ruiz, 2021. "Expecting the unexpected: economic growth under stress," Working Papers 202106, University of California at Riverside, Department of Economics.
• Ofori, Isaac Kwesi, 2021. "Catching The Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," EconStor Preprints 235482, ZBW - Leibniz Information Centre for Economics.
  • Isaac K. Ofori, 2021. "Catching the Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," Research Africa Network Working Papers 21/044, Research Africa Network (RAN).
  • Isaac K. Ofori, 2021. "Catching the Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," Working Papers of the African Governance and Development Institute. 21/044, African Governance and Development Institute..
  • Ofori, Isaac K, 2021. "Catching The Drivers of Inclusive Growth In Sub-Saharan Africa: An Application of Machine Learning," MPRA Paper 108622, University Library of Munich, Germany.
  • Isaac K. Ofori, 2021. "Catching the Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," Working Papers 21/044, European Xtramile Centre of African Studies (EXCAS).
• Ofori, Isaac K. & Quaidoo, Christopher & Ofori, Pamela E., 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, issue forthcomi.
  • Isaac K. Ofori & Christopher Quaidoo & Pamela E. Ofori, 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," Working Papers 21/074, European Xtramile Centre of African Studies (EXCAS).
  • Isaac K. Ofori & Christopher Quaidoo & Pamela E. Ofori, 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," Research Africa Network Working Papers 21/074, Research Africa Network (RAN).
  • Isaac K. Ofori & Christopher Quaidoo & Pamela E. Ofori, 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," Working Papers of the African Governance and Development Institute. 21/074, African Governance and Development Institute..
• Sarthak Behera & Hyeongwoo Kim & Soohyon Kim, 2021. "Superior Predictability of American Factors of the Won/Dollar Real Exchange Rate," Auburn Economics Working Paper Series auwp2021-03, Department of Economics, Auburn University.
  • Sarthak Behera & Hyeongwoo Kim & Soohyon Kim, 2022. "Superior Predictability of American Factors of the Won/Dollar Real Exchange Rate," Auburn Economics Working Paper Series auwp2022-03, Department of Economics, Auburn University.
• Nigel E.N. Chitambo & Darren Lee & Sure Mataramvura, 2021. "A Hybrid Neural Network GARCH Approach to Forecasting Zimbabwean Inflation Volatility," The African Finance Journal, Africagrowth Institute, vol. 23(1), pages 56-73.
• Ofori, Isaac Kwesi, 2021. "Catching The Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," EconStor Preprints 235482, ZBW - Leibniz Information Centre for Economics.
  • Isaac K. Ofori, 2021. "Catching the Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," Working Papers of the African Governance and Development Institute. 21/044, African Governance and Development Institute..
  • Ofori, Isaac K, 2021. "Catching The Drivers of Inclusive Growth In Sub-Saharan Africa: An Application of Machine Learning," MPRA Paper 108622, University Library of Munich, Germany.
  • Isaac K. Ofori, 2021. "Catching the Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," Working Papers 21/044, European Xtramile Centre of African Studies (EXCAS).
  • Isaac K. Ofori, 2021. "Catching the Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," Research Africa Network Working Papers 21/044, Research Africa Network (RAN).
• Ofori, Isaac K. & Quaidoo, Christopher & Ofori, Pamela E., 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, issue forthcomi.
  • Isaac K. Ofori & Christopher Quaidoo & Pamela E. Ofori, 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," Working Papers 21/074, European Xtramile Centre of African Studies (EXCAS).
  • Isaac K. Ofori & Christopher Quaidoo & Pamela E. Ofori, 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," Working Papers of the African Governance and Development Institute. 21/074, African Governance and Development Institute..
  • Isaac K. Ofori & Christopher Quaidoo & Pamela E. Ofori, 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," Research Africa Network Working Papers 21/074, Research Africa Network (RAN).
• D.V. Firsov & T.C. Chernyshevа, 2021. "Review of Successful Practices of Applying Nowcasting in Socio-Economic Forecasting," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, vol. 20(2), pages 269-293.
• Lachlan O'Neill & Nandini Anantharama & Wray Buntine & Simon D Angus, 2021. "Quantitative Discourse Analysis at Scale - AI, NLP and the Transformer Revolution," SoDa Laboratories Working Paper Series 2021-12, Monash University, SoDa Laboratories.
• Nurdaulet Abilov & Aizhan Bolatbayeva, 2021. "Nowcasting GDP growth in Russia with an incomplete dataset: A factor model approach," NAC Analytica Working Paper 18, NAC Analytica, Nazarbayev University, revised Feb 2022.
• Mauricio Gallardo & María Emma Santos & Pablo Villatoro & Vicky Pizarro, 2021. "Measuring vulnerability to multidimensional poverty in Latin América," Asociación Argentina de Economía Política: Working Papers 4476, Asociación Argentina de Economía Política.
  • Mauricio Gallardo & María Emma Santos & Pablo Villatoro & Vicky Pizarro, 2021. "Measuring vulnerability to multidimensional poverty in Latin America," Working Papers 36, Red Nacional de Investigadores en Economía (RedNIE).
• Oscar Claveria & Enric Monte & Salvador Torra, 2021. ""Nowcasting and forecasting GDP growth with machine-learning sentiment indicators"," IREA Working Papers 202103, University of Barcelona, Research Institute of Applied Economics, revised Feb 2021.
  • Oscar Claveria & Enric Monte & Salvador Torra, 2021. "“Nowcasting and forecasting GDP growth with machine-learning sentiment indicators”," AQR Working Papers 202101, University of Barcelona, Regional Quantitative Analysis Group, revised Feb 2021.
• Goulet Coulombe, Philippe & Marcellino, Massimiliano & Stevanović, Dalibor, 2021. "Can Machine Learning Catch The Covid-19 Recession?," National Institute Economic Review, National Institute of Economic and Social Research, vol. 256, pages 71-109, May.
  • Marcellino, Massimiliano & Stevanovic, Dalibor & Goulet Coulombe, Philippe, 2021. "Can Machine Learning Catch the COVID-19 Recession?," CEPR Discussion Papers 15867, C.E.P.R. Discussion Papers.
  • Philippe Goulet Coulombe & Massimiliano Marcellino & Dalibor Stevanovic, 2021. "Can Machine Learning Catch the COVID-19 Recession?," Papers 2103.01201, arXiv.org.
  • Philippe Goulet Coulombe & Massimiliano Marcellino & Dalibor Stevanovic, 2021. "Can Machine Learning Catch the COVID-19 Recession?," Working Papers 21-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
  • Philippe Goulet Coulombe & Massimiliano Marcellino & Dalibor Stevanovic, 2021. "Can Machine Learning Catch the COVID-19 Recession?," CIRANO Working Papers 2021s-09, CIRANO.
• Caner, Mehmet, 2023. "Generalized linear models with structured sparsity estimators," Journal of Econometrics, Elsevier, vol. 236(2).
  • Mehmet Caner, 2021. "Generalized Linear Models with Structured Sparsity Estimators," Papers 2104.14371, arXiv.org.
• Francesca Micocci & Armando Rungi, 2021. "Predicting Exporters with Machine Learning," Working Papers 03/2021, IMT School for Advanced Studies Lucca, revised Jul 2021.
  • Francesca Micocci & Armando Rungi, 2021. "Predicting Exporters with Machine Learning," Papers 2107.02512, arXiv.org, revised Sep 2022.
• Pesaran, M. H. & Xie, Y., 2021. "How to Detect Network Dependence in Latent Factor Models? A Bias-Corrected CD Testy," Cambridge Working Papers in Economics 2158, Faculty of Economics, University of Cambridge.
  • M. Hashem Pesaran & Yimeng Xie, 2021. "How to Detect Network Dependence in Latent Factor Models? A Bias-Corrected CD Test," Papers 2109.00408, arXiv.org, revised Nov 2024.
• Joshua C. C. Chan, 2022. "Asymmetric conjugate priors for large Bayesian VARs," Quantitative Economics, Econometric Society, vol. 13(3), pages 1145-1169, July.
  • Joshua C. C. Chan, 2019. "Asymmetric conjugate priors for large Bayesian VARs," CAMA Working Papers 2019-51, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Joshua C. C. Chan, 2021. "Asymmetric Conjugate Priors for Large Bayesian VARs," Papers 2111.07170, arXiv.org.
• Minseog Oh & Donggyu Kim, 2024. "Effect of the U.S.–China Trade War on Stock Markets: A Financial Contagion Perspective," Journal of Financial Econometrics, Oxford University Press, vol. 22(4), pages 954-1005.
  • Minseog Oh & Donggyu Kim, 2021. "Effect of the U.S.--China Trade War on Stock Markets: A Financial Contagion Perspective," Papers 2111.09655, arXiv.org.
• Emilia VASILE & Danut Octavian SIMION, 2021. "Optimization Of Application Objects Used In The Economic Environments," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 61(1), pages 9-19, March.
• Danut Octavian SIMION & Emilia VASILE, 2021. "Implementing Different Types Of Data In Economic Application," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 62(2), pages 9-18, June.
• Emilia VASILE & Danut Octavian SIMION, 2021. "Methods For Storing And Finding Data In The Business Logic For Economic Applications," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 63(3), pages 9-18, September.
• Sabyasachi Kar & Amaani Bashir & Mayank Jain, 2021. "New Approaches to Forecasting Growth and Inflation: Big Data and Machine Learning," IEG Working Papers 446, Institute of Economic Growth.
• Goulet Coulombe, Philippe & Marcellino, Massimiliano & Stevanović, Dalibor, 2021. "Can Machine Learning Catch The Covid-19 Recession?," National Institute Economic Review, National Institute of Economic and Social Research, vol. 256, pages 71-109, May.
  • Marcellino, Massimiliano & Stevanovic, Dalibor & Goulet Coulombe, Philippe, 2021. "Can Machine Learning Catch the COVID-19 Recession?," CEPR Discussion Papers 15867, C.E.P.R. Discussion Papers.
  • Philippe Goulet Coulombe & Massimiliano Marcellino & Dalibor Stevanovic, 2021. "Can Machine Learning Catch the COVID-19 Recession?," Working Papers 21-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
  • Philippe Goulet Coulombe & Massimiliano Marcellino & Dalibor Stevanovic, 2021. "Can Machine Learning Catch the COVID-19 Recession?," CIRANO Working Papers 2021s-09, CIRANO.
  • Philippe Goulet Coulombe & Massimiliano Marcellino & Dalibor Stevanovic, 2021. "Can Machine Learning Catch the COVID-19 Recession?," Papers 2103.01201, arXiv.org.
• Ali Batuhan Barlas & Seda Guler Mert & Berk Orkun Isa & Alvaro Ortiz & Tomasa Rodrigo & Baris Soybilgen & Ege Yazgan, 2021. "Turquía | Big Data y Nowcasting: consumo e inversión de transacciones bancarias [Turkey | Big Data and Nowcasting: Consumption and Investment from Bank Transactions]," Working Papers 21/07, BBVA Bank, Economic Research Department.
• James Chapman & Ajit Desai, 2021. "Using Payments Data to Nowcast Macroeconomic Variables During the Onset of COVID-19," Staff Working Papers 21-2, Bank of Canada.
• Tatjana Dahlhaus & Angelika Welte, 2024. "Payment habits during Covid-19: Evidence from high-frequency transaction data," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Granular data: new horizons and challenges, volume 61, Bank for International Settlements.
  • Tatjana Dahlhaus & Angelika Welte, 2021. "Payment Habits During COVID-19: Evidence from High-Frequency Transaction Data," Staff Working Papers 21-43, Bank of Canada.
• Costa, Alexandre Bonnet R. & Ferreira, Pedro Cavalcanti G. & Gaglianone, Wagner P. & Guillén, Osmani Teixeira C. & Issler, João Victor & Lin, Yihao, 2021. "Machine learning and oil price point and density forecasting," Energy Economics, Elsevier, vol. 102(C).
  • Alexandre Bonnet R. Costa & Pedro Cavalcanti G. Ferreira & Wagner P. Gaglianone & Osmani Teixeira C. Guillén & João Victor Issler & Yihao Lin, 2021. "Machine Learning and Oil Price Point and Density Forecasting," Working Papers Series 544, Central Bank of Brazil, Research Department.
• Levent GUNTAY & Mehmet AKTUNA, 2021. "Scenario Based Anomaly Detection in Financial Institutions: A Study on the Turkish Factoring Sector," Journal of BRSA Banking and Financial Markets, Banking Regulation and Supervision Agency, vol. 15(1), pages 83-113.
• Christiane Baumeister & Danilo Leiva-León & Eric Sims, 2024. "Tracking Weekly State-Level Economic Conditions," The Review of Economics and Statistics, MIT Press, vol. 106(2), pages 483-504, March.
  • Christiane Baumeister & Danilo Leiva-León & Eric R. Sims, 2021. "Tracking Weekly State-Level Economic Conditions," NBER Working Papers 29003, National Bureau of Economic Research, Inc.
  • Christiane Baumeister & Danilo Leiva-León & Eric Sims, 2021. "Tracking weekly state-level economic conditions," Working Papers 2134, Banco de España.
  • Christiane Baumeister & Danilo Leiva-Leon & Eric Sims, 2021. "Tracking Weekly State-Level Economic Conditions," Working Papers 202151, University of Pretoria, Department of Economics.
  • Christiane Baumeister & Danilo Leiva-León & Eric R. Sims, 2021. "Tracking Weekly State-Level Economic Conditions," CESifo Working Paper Series 9165, CESifo.
  • Baumeister, Christiane & Leiva-León, Danilo & Sims, Eric, 2021. "Tracking Weekly State-Level Economic Conditions," CEPR Discussion Papers 16317, C.E.P.R. Discussion Papers.
  • Christiane Baumeister & Danilo Leiva-León & Eric Sims, 2021. "Tracking weekly state-level economic conditions," CAMA Working Papers 2021-55, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Angelico, Cristina & Marcucci, Juri & Miccoli, Marcello & Quarta, Filippo, 2022. "Can we measure inflation expectations using Twitter?," Journal of Econometrics, Elsevier, vol. 228(2), pages 259-277.
  • Cristina Angelico & Juri Marcucci & Marcello Miccoli & Filippo Quarta, 2021. "Can we measure inflation expectations using Twitter?," Temi di discussione (Economic working papers) 1318, Bank of Italy, Economic Research and International Relations Area.
• Aprigliano, Valentina & Emiliozzi, Simone & Guaitoli, Gabriele & Luciani, Andrea & Marcucci, Juri & Monteforte, Libero, 2023. "The power of text-based indicators in forecasting Italian economic activity," International Journal of Forecasting, Elsevier, vol. 39(2), pages 791-808.
  • Valentina Aprigliano & Simone Emiliozzi & Gabriele Guaitoli & Andrea Luciani & Juri Marcucci & Libero Monteforte, 2021. "The power of text-based indicators in forecasting the Italian economic activity," Temi di discussione (Economic working papers) 1321, Bank of Italy, Economic Research and International Relations Area.
• Rangel González Erick & Llamosas-Rosas Irving, 2021. "Observing the Evolution of the Informal Sector from Space: A Municipal Approach 2013-2020," Working Papers 2021-18, Banco de México.
• Massimo Ferrari Minesso & Frederik Kurcz & Maria Sole Pagliari, 2022. "Do words hurt more than actions? The impact of trade tensions on financial markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(6), pages 1138-1159, September.
  • Ferrari Minesso, Massimo & Pagliari, Maria Sole & Kurcz, Frederik, 2020. "Do words hurt more than actions? The impact of trade tensions on financial markets," Working Paper Series 2490, European Central Bank.
  • Massimo Ferrari & Frederik Kurcz & Maria Sole Pagliari, 2021. "Do Words Hurt More Than Actions? The Impact of Trade Tensions on Financial Markets," Working papers 802, Banque de France.
• Henri Fraisse & Matthias Laporte, 2021. "Return on Investment on AI: The Case of Capital Requirement," Working papers 809, Banque de France.
• Gambacorta, Leonardo & Amstad, Marlene & He, Chao & XIA, Fan Dora, 2021. "Trade sentiment and the stock market: new evidence based on big data textual analysis of Chinese media," CEPR Discussion Papers 15682, C.E.P.R. Discussion Papers.
  • Marlene Amstad & Leonardo Gambacorta & Chao He & Dora Xia, 2021. "Trade sentiment and the stock market: new evidence based on big data textual analysis of Chinese media," BIS Working Papers 917, Bank for International Settlements.
• Vrigazova Borislava, 2021. "The Proportion for Splitting Data into Training and Test Set for the Bootstrap in Classification Problems," Business Systems Research, Sciendo, vol. 12(1), pages 228-242, May.
• Ksenia Mayorova & Nikita Fokin, 2021. "Nowcasting Growth Rates of Russia's Export and Import by Commodity Group," Russian Journal of Money and Finance, Bank of Russia, vol. 80(3), pages 34-48, September.
• Alexander Plum & Gail Pacheco & Kabir Dasgupta, 2021. "When There is No Way Up: Reconsidering Low‐paid Jobs as Stepping‐stones," The Economic Record, The Economic Society of Australia, vol. 97(318), pages 387-409, September.
  • Gail Pacheco & Alexander Plum, 2020. "When there is no way up: Reconsidering low-paid jobs as stepping stones," Working Papers 2020-08, Auckland University of Technology, Department of Economics.
• Joseph, Andreas & Kalamara, Eleni & Kapetanios, George & Potjagailo, Galina & Chakraborty, Chiranjit, 2021. "Forecasting UK inflation bottom up," Bank of England working papers 915, Bank of England, revised 27 Sep 2022.
• Anesti, Nikoleta & Kalamara, Eleni & Kapetanios, George, 2021. "Forecasting UK GDP growth with large survey panels," Bank of England working papers 923, Bank of England.
• Marcus Buckmann & Andy Haldane & Anne-Caroline Hüser, 2021. "Comparing minds and machines: implications for financial stability," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 37(3), pages 479-508.
  • Buckmann, Marcus & Haldane, Andy & Hüser, Anne-Caroline, 2021. "Comparing minds and machines: implications for financial stability," Bank of England working papers 937, Bank of England.
• Munday, Tim & Brookes, James, 2021. "Mark my words: the transmission of central bank communication to the general public via the print media," Bank of England working papers 944, Bank of England.
• Jonathan Benchimol & Sophia Kazinnik & Yossi Saadon, 2021. "Federal Reserve Communication and the COVID-19 Pandemic," Bank of Israel Working Papers 2021.15, Bank of Israel.
• Jouchi Nakajima & Hiroaki Yamagata & Tatsushi Okuda & Shinnosuke Katsuki & Takeshi Shinohara, 2021. "Extracting Firms' Short-Term Inflation Expectations from the Economy Watchers Survey Using Text Analysis," Bank of Japan Working Paper Series 21-E-12, Bank of Japan.
• Reif Magnus, 2021. "Macroeconomic uncertainty and forecasting macroeconomic aggregates," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(2), pages 1-20, April.
  • Magnus Reif, 2018. "Macroeconomic Uncertainty and Forecasting Macroeconomic Aggregates," ifo Working Paper Series 265, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
• Agudze, Komla M. & Billio, Monica & Casarin, Roberto & Ravazzolo, Francesco, 2022. "Markov switching panel with endogenous synchronization effects," Journal of Econometrics, Elsevier, vol. 230(2), pages 281-298.
  • Komla M. Agudze & Monica Billio & Roberto Casarin & Francesco Ravazzolo, 2021. "Markov Switching Panel with Endogenous Synchronization Effects," BEMPS - Bozen Economics & Management Paper Series BEMPS82, Faculty of Economics and Management at the Free University of Bozen.
• Hannes Mueller & Christopher Rauh, 2022. "The Hard Problem of Prediction for Conflict Prevention," Journal of the European Economic Association, European Economic Association, vol. 20(6), pages 2440-2467.
  • Hannes Mueller & Christopher Rauh, 2019. "The hard problem of prediction for conflict prevention," Cahiers de recherche 2019-02, Universite de Montreal, Departement de sciences economiques.
  • Mueller, H. & Rauh, C., 2021. "The Hard Problem of Prediction for Conflict Prevention," Cambridge Working Papers in Economics 2103, Faculty of Economics, University of Cambridge.
  • Hannes Mueller & Christopher Rauh, 2021. "The Hard Problem of Prediction for Conflict Prevention," Working Papers 1244, Barcelona School of Economics.
  • Mueller, H. & Rauh, C., 2020. "The Hard Problem of Prediction for Conflict Prevention," Cambridge Working Papers in Economics 2015, Faculty of Economics, University of Cambridge.
  • Hannes Mueller & Christopher Rauh, 2019. "The Hard Problem of Prediction for Conflict Prevention," Cahiers de recherche 02-2019, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
  • Mueller, Hannes & Rauh, Christopher, 2019. "The Hard Problem of Prediction for Conflict Prevention," CEPR Discussion Papers 13748, C.E.P.R. Discussion Papers.
• Kang, Jieyi & Reiner, David M., 2022. "What is the effect of weather on household electricity consumption? Empirical evidence from Ireland," Energy Economics, Elsevier, vol. 111(C).
  • Jieyi Kang & David Reiner, 2021. "What is the effect of weather on household electricity consumption? Empirical evidence from Ireland," Working Papers EPRG2112, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
  • Kang, J. & Reiner, D., 2021. "What is the effect of weather on household electricity consumption? Empirical evidence from Ireland," Cambridge Working Papers in Economics 2141, Faculty of Economics, University of Cambridge.
• Jieyi Kang & David Reiner, 2021. "Machine Learning on residential electricity consumption: Which households are more responsive to weather?," Working Papers EPRG2113, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
  • Kang, J. & Reiner, D., 2021. "Machine Learning on residential electricity consumption: Which households are more responsive to weather?," Cambridge Working Papers in Economics 2142, Faculty of Economics, University of Cambridge.
• Jieyi Kang & David Reiner, 2021. "Identifying residential consumption patterns using data-mining techniques: A large-scale study of smart meter data in Chengdu, China," Working Papers EPRG2114, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
  • Kang, J. & Reiner, D., 2021. "Identifying residential consumption patterns using data-mining techniques: A large-scale study of smart meter data in Chengdu, China," Cambridge Working Papers in Economics 2143, Faculty of Economics, University of Cambridge.
• M. Hashem Pesaran & Yimeng Xie, 2021. "A Bias-Corrected CD Test for Error Cross-Sectional Dependence in Panel Data Models with Latent Factors," CESifo Working Paper Series 9234, CESifo.
  • Pesaran, M. H. & Xie, Y., 2021. "How to Detect Network Dependence in Latent Factor Models? A Bias-Corrected CD Testy," Cambridge Working Papers in Economics 2158, Faculty of Economics, University of Cambridge.
  • M. Hashem Pesaran & Yimeng Xie, 2022. "A Bias-Corrected CD Test for Error Cross-Sectional Dependence in Panel Data Models with Latent Factors," Working Papers 2022-06-10, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
• Ba Chu & Shafiullah Qureshi, 2023. "Comparing Out-of-Sample Performance of Machine Learning Methods to Forecast U.S. GDP Growth," Computational Economics, Springer;Society for Computational Economics, vol. 62(4), pages 1567-1609, December.
  • Ba Chu & Shafiullah Qureshi, 2021. "Comparing Out-of-Sample Performance of Machine Learning Methods to Forecast U.S. GDP Growth," Carleton Economic Papers 21-12, Carleton University, Department of Economics.
• Parle, Conor, 2022. "The financial market impact of ECB monetary policy press conferences — A text based approach," European Journal of Political Economy, Elsevier, vol. 74(C).
  • Parle, Conor, 2021. "The financial market impact of ECB monetary policy press conferences - a text based approach," Research Technical Papers 4/RT/21, Central Bank of Ireland.
• Bernadette Power & Gavin C Reid, 2021. "The Impact of Intellectual Property Types on the Performance of Business Start-ups in the USA," Working Papers wp523, Centre for Business Research, University of Cambridge.
• Stanislav Anatolyev & Vladimir Pyrlik, 2021. "Shrinkage for Gaussian and t Copulas in Ultra-High Dimensions," CERGE-EI Working Papers wp699, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
• Amberg, Niklas & Jansson, Thomas & Klein, Mathias & Rogantini Picco, Anna, 2021. "Five Facts about the Distributional Income Effects of Monetary Policy," Working Paper Series 403, Sveriges Riksbank (Central Bank of Sweden).
  • Niklas Amberg & Thomas Jansson & Mathias Klein & Anna Rogantini Picco, 2021. "Five Facts about the Distributional Income Effects of Monetary Policy," CESifo Working Paper Series 9062, CESifo.
• Christiane Baumeister & Danilo Leiva-León & Eric Sims, 2024. "Tracking Weekly State-Level Economic Conditions," The Review of Economics and Statistics, MIT Press, vol. 106(2), pages 483-504, March.
  • Christiane Baumeister & Danilo Leiva-León & Eric R. Sims, 2021. "Tracking Weekly State-Level Economic Conditions," NBER Working Papers 29003, National Bureau of Economic Research, Inc.
  • Christiane Baumeister & Danilo Leiva-León & Eric R. Sims, 2021. "Tracking Weekly State-Level Economic Conditions," CESifo Working Paper Series 9165, CESifo.
  • Christiane Baumeister & Danilo Leiva-Leon & Eric Sims, 2021. "Tracking Weekly State-Level Economic Conditions," Working Papers 202151, University of Pretoria, Department of Economics.
  • Baumeister, Christiane & Leiva-León, Danilo & Sims, Eric, 2021. "Tracking Weekly State-Level Economic Conditions," CEPR Discussion Papers 16317, C.E.P.R. Discussion Papers.
  • Christiane Baumeister & Danilo Leiva-León & Eric Sims, 2021. "Tracking weekly state-level economic conditions," Working Papers 2134, Banco de España.
  • Christiane Baumeister & Danilo Leiva-León & Eric Sims, 2021. "Tracking weekly state-level economic conditions," CAMA Working Papers 2021-55, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• M. Hashem Pesaran & Yimeng Xie, 2021. "A Bias-Corrected CD Test for Error Cross-Sectional Dependence in Panel Data Models with Latent Factors," CESifo Working Paper Series 9234, CESifo.
  • M. Hashem Pesaran & Yimeng Xie, 2022. "A Bias-Corrected CD Test for Error Cross-Sectional Dependence in Panel Data Models with Latent Factors," Working Papers 2022-06-10, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
• Els Bekaert & Amelie F. Constant & Killian Foubert & Ilse Ruyssen, 2021. "Longing for Which Home: Evidence from Global Aspirations to Stay, Return or Migrate Onwards," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 21/1028, Ghent University, Faculty of Economics and Business Administration.
  • Els Bekaert & Amelie F. Constant & Killian Foubert & Ilse Ruyssen, 2021. "Longing for Which Home: Evidence from Global Aspirations to Stay, Return or Migrate Onwards," CESifo Working Paper Series 9301, CESifo.
  • Bekaert, Els & Constant, Amelie F. & Foubert, Killian & Ruyssen, Ilse, 2021. "Longing for Which Home: Evidence from Global Aspirations to Stay, Return or Migrate Onwards," GLO Discussion Paper Series 930, Global Labor Organization (GLO).
  • Bekaert, Els & Constant, Amelie F. & Foubert, Killian & Ruyssen, Ilse, 2021. "Longing for which home: Evidence from global aspirations to stay, return or migrate onwards," MERIT Working Papers 2021-035, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
• Bakalli, Gaetan & Guerrier, Stéphane & Scaillet, Olivier, 2023. "A penalized two-pass regression to predict stock returns with time-varying risk premia," Journal of Econometrics, Elsevier, vol. 237(2).
  • Gaetan Bakalli & Stéphane Guerrier & Olivier Scaillet, 2021. "A penalized two-pass regression to predict stock returns with time-varying risk premia," Swiss Finance Institute Research Paper Series 21-09, Swiss Finance Institute.
  • Gaetan Bakalli & Stéphane Guerrier & Olivier Scaillet, 2023. "A penalized two-pass regression to predict stock returns with time-varying risk premia," Post-Print hal-04325655, HAL.
  • Gaetan Bakalli & St'ephane Guerrier & Olivier Scaillet, 2022. "A penalized two-pass regression to predict stock returns with time-varying risk premia," Papers 2208.00972, arXiv.org.
• Alexis Marchal, 2021. "Risk & Returns around Fomc Press Conferences: A Novel Perspective from Computer Vision," Swiss Finance Institute Research Paper Series 21-18, Swiss Finance Institute.
• Michael Mayer & Steven C. Bourassa & Martin Hoesli & Donato Scognamiglio, 2021. "Structured Additive Regression and Tree Boosting," Swiss Finance Institute Research Paper Series 21-83, Swiss Finance Institute.
• Hugo Couture & Dalibor Stevanovic, 2021. "Analyse du marché du travail à l’aide des données de Google Trends," CIRANO Project Reports 2021rp-15, CIRANO.
• Goulet Coulombe, Philippe & Marcellino, Massimiliano & Stevanović, Dalibor, 2021. "Can Machine Learning Catch The Covid-19 Recession?," National Institute Economic Review, National Institute of Economic and Social Research, vol. 256, pages 71-109, May.
  • Marcellino, Massimiliano & Stevanovic, Dalibor & Goulet Coulombe, Philippe, 2021. "Can Machine Learning Catch the COVID-19 Recession?," CEPR Discussion Papers 15867, C.E.P.R. Discussion Papers.
  • Philippe Goulet Coulombe & Massimiliano Marcellino & Dalibor Stevanovic, 2021. "Can Machine Learning Catch the COVID-19 Recession?," CIRANO Working Papers 2021s-09, CIRANO.
  • Philippe Goulet Coulombe & Massimiliano Marcellino & Dalibor Stevanovic, 2021. "Can Machine Learning Catch the COVID-19 Recession?," Working Papers 21-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
  • Philippe Goulet Coulombe & Massimiliano Marcellino & Dalibor Stevanovic, 2021. "Can Machine Learning Catch the COVID-19 Recession?," Papers 2103.01201, arXiv.org.
• Jorge Rojas-Vallejos & Carmen Gloria Jiménez Bucarey & Marcela Espinoza & Luis Araya-Castillo, 2021. "The short-term impact of urban air pollution on student achievement," Revista Desarrollo y Sociedad, Universidad de los Andes,Facultad de Economía, CEDE, vol. 87(2), March.
• Susana Martínez-Restrepo & Lina Tafur & Juan G. Ocio & Caroline Brethenoux & Patrick Furey & Orlando Rivera, 2021. "Análisis de narrativas en línea sobre el empoderamiento de las mujeres sobrevivientes de las violencias basadas en género en Colombia con procesamiento de lenguaje natural," Informes de Investigación 19664, Fedesarrollo.
• Marlene Amstad & Leonardo Gambacorta & Chao He & Dora Xia, 2021. "Trade sentiment and the stock market: new evidence based on big data textual analysis of Chinese media," BIS Working Papers 917, Bank for International Settlements.
  • Gambacorta, Leonardo & Amstad, Marlene & He, Chao & XIA, Fan Dora, 2021. "Trade sentiment and the stock market: new evidence based on big data textual analysis of Chinese media," CEPR Discussion Papers 15682, C.E.P.R. Discussion Papers.
• Goulet Coulombe, Philippe & Marcellino, Massimiliano & Stevanović, Dalibor, 2021. "Can Machine Learning Catch The Covid-19 Recession?," National Institute Economic Review, National Institute of Economic and Social Research, vol. 256, pages 71-109, May.
  • Philippe Goulet Coulombe & Massimiliano Marcellino & Dalibor Stevanovic, 2021. "Can Machine Learning Catch the COVID-19 Recession?," Papers 2103.01201, arXiv.org.
  • Marcellino, Massimiliano & Stevanovic, Dalibor & Goulet Coulombe, Philippe, 2021. "Can Machine Learning Catch the COVID-19 Recession?," CEPR Discussion Papers 15867, C.E.P.R. Discussion Papers.
  • Philippe Goulet Coulombe & Massimiliano Marcellino & Dalibor Stevanovic, 2021. "Can Machine Learning Catch the COVID-19 Recession?," Working Papers 21-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
  • Philippe Goulet Coulombe & Massimiliano Marcellino & Dalibor Stevanovic, 2021. "Can Machine Learning Catch the COVID-19 Recession?," CIRANO Working Papers 2021s-09, CIRANO.
• Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2020. "Measuring Uncertainty and Its Effects in the COVID-19 Era," Working Papers 20-32R, Federal Reserve Bank of Cleveland, revised 05 Jan 2022.
  • Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd & Mertens, Elmar, 2021. "Measuring Uncertainty and Its Effects in the COVID-19 Era," CEPR Discussion Papers 15965, C.E.P.R. Discussion Papers.
• Moench, Emanuel & Soofi-Siavash, Soroosh, 2022. "What moves treasury yields?," Journal of Financial Economics, Elsevier, vol. 146(3), pages 1016-1043.
  • Soroosh Soofi-Siavash & Emanuel Moench, 2021. "What Moves Treasury Yields?," Bank of Lithuania Working Paper Series 88, Bank of Lithuania.
  • Moench, Emanuel & Soofi Siavash, Soroosh, 2022. "What Moves Treasury Yields?," CEPR Discussion Papers 15978, C.E.P.R. Discussion Papers.
• Taylor, Mark & Filippou, Ilias & Wang, Zigan, 2021. "Media Sentiment and Currency Reversals," CEPR Discussion Papers 16049, C.E.P.R. Discussion Papers.
• Roshen Fernando & Weifeng Liu & Warwick J McKibbin, 2021. "Global economic impacts of climate shocks, climate policy and changes in climate risk assessment," CAMA Working Papers 2021-37, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Mckibbin, Warwick & Fernando, Roshen & Liu, Weifeng, 2021. "Global Economic Impacts of Climate Shocks, Climate Policy and Changes in Climate Risk Assessment," CEPR Discussion Papers 16154, C.E.P.R. Discussion Papers.
• Rao, Justin, 2021. "Demand for Online News under Government Control: Evidence from Russia," CEPR Discussion Papers 16233, C.E.P.R. Discussion Papers.
• Hector F. Calvo-Pardo & Tullio Mancini & Jose Olmo, 2022. "Machine Learning the Carbon Footprint of Bitcoin Mining," JRFM, MDPI, vol. 15(2), pages 1-30, February.
  • Calvo Pardo, Héctor & Olmo, Jose & Mancini, Tullio, 2021. "Machine Learning the Carbon Footprint of Bitcoin Mining," CEPR Discussion Papers 16267, C.E.P.R. Discussion Papers.
• Christiane Baumeister & Danilo Leiva-León & Eric Sims, 2024. "Tracking Weekly State-Level Economic Conditions," The Review of Economics and Statistics, MIT Press, vol. 106(2), pages 483-504, March.
  • Christiane Baumeister & Danilo Leiva-León & Eric R. Sims, 2021. "Tracking Weekly State-Level Economic Conditions," NBER Working Papers 29003, National Bureau of Economic Research, Inc.
  • Baumeister, Christiane & Leiva-León, Danilo & Sims, Eric, 2021. "Tracking Weekly State-Level Economic Conditions," CEPR Discussion Papers 16317, C.E.P.R. Discussion Papers.
  • Christiane Baumeister & Danilo Leiva-Leon & Eric Sims, 2021. "Tracking Weekly State-Level Economic Conditions," Working Papers 202151, University of Pretoria, Department of Economics.
  • Christiane Baumeister & Danilo Leiva-León & Eric R. Sims, 2021. "Tracking Weekly State-Level Economic Conditions," CESifo Working Paper Series 9165, CESifo.
  • Christiane Baumeister & Danilo Leiva-León & Eric Sims, 2021. "Tracking weekly state-level economic conditions," Working Papers 2134, Banco de España.
  • Christiane Baumeister & Danilo Leiva-León & Eric Sims, 2021. "Tracking weekly state-level economic conditions," CAMA Working Papers 2021-55, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Emily Aiken & Suzanne Bellue & Dean Karlan & Christopher R. Udry & Joshua Blumenstock, 2021. "Machine Learning and Mobile Phone Data Can Improve the Targeting of Humanitarian Assistance," NBER Working Papers 29070, National Bureau of Economic Research, Inc.
  • Blumenstock, Joshua & Aiken, Emily & Bellue, Suzanne & Udry, Christopher & Karlan, Dean, 2021. "Machine Learning and Mobile Phone Data Can Improve the Targeting of Humanitarian Assistance," CEPR Discussion Papers 16385, C.E.P.R. Discussion Papers.
• Ms. Florence Jaumotte & Weifeng Liu & Warwick J. McKibbin, 2021. "Mitigating Climate Change: Growth-Friendly Policies to Achieve Net Zero Emissions by 2050," IMF Working Papers 2021/195, International Monetary Fund.
  • Mckibbin, Warwick & Jaumotte, Florence & Liu, Weifeng, 2021. "Mitigating Climate Change: Growth-Friendly Policies to Achieve Net Zero Emissions by 2050," CEPR Discussion Papers 16553, C.E.P.R. Discussion Papers.
  • Florence Jaumotte & Weifeng Liu & Warwick J. McKibbin, 2021. "Mitigating climate change: Growth-friendly policies to achieve net zero emissions by 2050," CAMA Working Papers 2021-75, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Iaria, Alessandro & Wang, Ao, 2021. "An Empirical Model of Quantity Discounts with Large Choice Sets," CEPR Discussion Papers 16666, C.E.P.R. Discussion Papers.
• Gloria Gonzalez-Rivera & Vladimir Rodriguez-Caballero & Esther Ruiz, 2021. "Expecting the unexpected: economic growth under stress," Working Papers 202106, University of California at Riverside, Department of Economics.
  • Gonzalez Rivera, Gloria & Rodríguez Caballero, Carlos Vladimir, 2021. "Expecting the unexpected: economic growth under stress," DES - Working Papers. Statistics and Econometrics. WS 32148, Universidad Carlos III de Madrid. Departamento de Estadística.
  • Gloria González-Rivera & Carlos Vladimir Rodríguez-Caballero & Esther Ruiz Ortega, 2021. "Expecting the unexpected: economic growth under stress," CREATES Research Papers 2021-06, Department of Economics and Business Economics, Aarhus University.
• Chao, Shih-Kang & Härdle, Wolfgang K. & Yuan, Ming, 2021. "Factorisable Multitask Quantile Regression," Econometric Theory, Cambridge University Press, vol. 37(4), pages 794-816, August.
  • Chao, Shih-Kang & Härdle, Wolfgang Karl & Yuan, Ming, 2016. "Factorisable multi-task quantile regression," SFB 649 Discussion Papers 2016-057, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
  • Chao, Shih-Kang & Härdle, Wolfgang Karl & Yuan, Ming, 2020. "Factorisable Multitask Quantile Regression," IRTG 1792 Discussion Papers 2020-004, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
• Goulet Coulombe, Philippe & Marcellino, Massimiliano & Stevanović, Dalibor, 2021. "Can Machine Learning Catch The Covid-19 Recession?," National Institute Economic Review, National Institute of Economic and Social Research, vol. 256, pages 71-109, May.
  • Marcellino, Massimiliano & Stevanovic, Dalibor & Goulet Coulombe, Philippe, 2021. "Can Machine Learning Catch the COVID-19 Recession?," CEPR Discussion Papers 15867, C.E.P.R. Discussion Papers.
  • Philippe Goulet Coulombe & Massimiliano Marcellino & Dalibor Stevanovic, 2021. "Can Machine Learning Catch the COVID-19 Recession?," CIRANO Working Papers 2021s-09, CIRANO.
  • Philippe Goulet Coulombe & Massimiliano Marcellino & Dalibor Stevanovic, 2021. "Can Machine Learning Catch the COVID-19 Recession?," Working Papers 21-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
  • Philippe Goulet Coulombe & Massimiliano Marcellino & Dalibor Stevanovic, 2021. "Can Machine Learning Catch the COVID-19 Recession?," Papers 2103.01201, arXiv.org.
• Shan Huang & Michael Allan Ribers & Hannes Ullrich, 2021. "Der gesellschaftliche Mehrwert verknüpfter Daten: Algorithmen als Entscheidungshilfen bei Antibiotikaverschreibungen," DIW Wochenbericht, DIW Berlin, German Institute for Economic Research, vol. 88(13/14), pages 239-246.
• Shan Huang & Michael Allan Ribers & Hannes Ullrich, 2021. "The Value of Data for Prediction Policy Problems: Evidence from Antibiotic Prescribing," Discussion Papers of DIW Berlin 1939, DIW Berlin, German Institute for Economic Research.
• Dugast, Jerome & Foucault, Thierry, 2021. "Equilibrium Data Mining and Data Abundance," HEC Research Papers Series 1393, HEC Paris.
• Hurlin, Christophe & Pérignon, Christophe & Saurin, Sébastien, 2021. "The Fairness of Credit Scoring Models," HEC Research Papers Series 1411, HEC Paris.
• Hirschbühl, Dominik & Onorante, Luca & Saiz, Lorena, 2021. "Using machine learning and big data to analyse the business cycle," Economic Bulletin Articles, European Central Bank, vol. 5.
• Alogoskoufis, Spyros & Dunz, Nepomuk & Emambakhsh, Tina & Hennig, Tristan & Kaijser, Michiel & Kouratzoglou, Charalampos & Muñoz, Manuel A. & Parisi, Laura & Salleo, Carmelo, 2021. "ECB’s economy-wide climate stress test," Occasional Paper Series 281, European Central Bank.
• Alina Bobasu & Lucia Quaglietti & Martino Ricci, 2024. "Tracking Global Economic Uncertainty: Implications for the Euro Area," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 72(2), pages 820-857, June.
  • Bobasu, Alina & Geis, André & Quaglietti, Lucia & Ricci, Martino, 2021. "Tracking global economic uncertainty: implications for the euro area," Working Paper Series 2541, European Central Bank.
• Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2021. "Economic Predictions With Big Data: The Illusion of Sparsity," Econometrica, Econometric Society, vol. 89(5), pages 2409-2437, September.
  • Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio, 2017. "Economic Predictions with Big Data: The Illusion Of Sparsity," CEPR Discussion Papers 12256, C.E.P.R. Discussion Papers.
  • Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio E., 2021. "Economic predictions with big data: the illusion of sparsity," Working Paper Series 2542, European Central Bank.
  • Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2018. "Economic Predictions with Big Data: The Illusion of Sparsity," Liberty Street Economics 20180521, Federal Reserve Bank of New York.
  • Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2018. "Economic predictions with big data: the illusion of sparsity," Staff Reports 847, Federal Reserve Bank of New York.
• Korobilis, Dimitris & Landau, Bettina & Musso, Alberto & Phella, Anthoulla, 2021. "The time-varying evolution of inflation risks," Working Paper Series 2600, European Central Bank.
• Saiz, Lorena & Ashwin, Julian & Kalamara, Eleni, 2021. "Nowcasting euro area GDP with news sentiment: a tale of two crises," Working Paper Series 2616, European Central Bank.
• Santiago Gall n & Jorge Barrientos, 2021. "Forecasting the Colombian Electricity Spot Price under a Functional Approach," International Journal of Energy Economics and Policy, Econjournals, vol. 11(2), pages 67-74.
• Bharat Kumar Meher & Iqbal Thonse Hawaldar & Mathew Thomas Gil & Deebom Zorle Dum, 2021. "Measuring Leverage Effect of Covid 19 on Stock Price Volatility of Energy Companies Using High Frequency Data," International Journal of Energy Economics and Policy, Econjournals, vol. 11(6), pages 489-502.
• Nakamura, Nobuyuki & Suzuki, Aya, 2021. "COVID-19 and the intentions to migrate from developing countries: Evidence from online search activities in Southeast Asia," Journal of Asian Economics, Elsevier, vol. 76(C).
• Camacho, Maximo & Romeu, Andres & Ruiz-Marin, Manuel, 2021. "Symbolic transfer entropy test for causality in longitudinal data," Economic Modelling, Elsevier, vol. 94(C), pages 649-661.
• Lourenço, Nuno & Gouveia, Carlos Melo & Rua, António, 2021. "Forecasting tourism with targeted predictors in a data-rich environment," Economic Modelling, Elsevier, vol. 96(C), pages 445-454.
• Bastianin, Andrea & Manera, Matteo, 2021. "A test of symmetry based on L-moments with an application to the business cycles of the G7 economies," Economics Letters, Elsevier, vol. 198(C).
• Lyu, Yifei & Nie, Jun & Yang, Shu-Kuei X., 2021. "Forecasting US economic growth in downturns using cross-country data," Economics Letters, Elsevier, vol. 198(C).
  • , 2020. "Forecasting U.S. Economic Growth in Downturns Using Cross-Country Data," Research Working Paper RWP 20-09, Federal Reserve Bank of Kansas City.
• Biewen, Martin & Kugler, Philipp, 2021. "Two-stage least squares random forests with an application to Angrist and Evans (1998)," Economics Letters, Elsevier, vol. 204(C).
  • Biewen, Martin & Kugler, Philipp, 2020. "Two-Stage Least Squares Random Forests with an Application to Angrist and Evans (1998)," IZA Discussion Papers 13613, Institute of Labor Economics (IZA).
• Smeekes, Stephan & Wijler, Etienne, 2021. "An automated approach towards sparse single-equation cointegration modelling," Journal of Econometrics, Elsevier, vol. 221(1), pages 247-276.
  • Stephan Smeekes & Etienne Wijler, 2018. "An Automated Approach Towards Sparse Single-Equation Cointegration Modelling," Papers 1809.08889, arXiv.org, revised Jul 2020.
• Yang, Xinxin & Zheng, Xinghua & Chen, Jiaqi, 2021. "Testing high-dimensional covariance matrices under the elliptical distribution and beyond," Journal of Econometrics, Elsevier, vol. 221(2), pages 409-423.
• Kapetanios, G. & Pesaran, M.H. & Reese, S., 2021. "Detection of units with pervasive effects in large panel data models," Journal of Econometrics, Elsevier, vol. 221(2), pages 510-541.
• Ding, Yi & Li, Yingying & Zheng, Xinghua, 2021. "High dimensional minimum variance portfolio estimation under statistical factor models," Journal of Econometrics, Elsevier, vol. 222(1), pages 502-515.
• Jin, Sainan & Miao, Ke & Su, Liangjun, 2021. "On factor models with random missing: EM estimation, inference, and cross validation," Journal of Econometrics, Elsevier, vol. 222(1), pages 745-777.
  • Su, Liangjun & Miao, Ke & Jin, Sainan, 2019. "On Factor Models with Random Missing: EM Estimation, Inference, and Cross Validation," Economics and Statistics Working Papers 4-2019, Singapore Management University, School of Economics.
• Guðmundsson, Guðmundur Stefán & Brownlees, Christian, 2021. "Detecting groups in large vector autoregressions," Journal of Econometrics, Elsevier, vol. 225(1), pages 2-26.
• Di Iorio, Francesca & Fachin, Stefano, 2021. "Evaluating restricted common factor models for non-stationary data," Econometrics and Statistics, Elsevier, vol. 17(C), pages 64-75.
  • Francesca Di Iorio & Stefano Fachin, 2017. "Evaluating Restricted Common Factor models for non-stationary data," DSS Empirical Economics and Econometrics Working Papers Series 2017/2, Centre for Empirical Economics and Econometrics, Department of Statistics, "Sapienza" University of Rome.
• Cavallari, Lilia & Romano, Simone & Naticchioni, Paolo, 2021. "The original sin: Firms’ dynamics and the life-cycle consequences of economic conditions at birth," European Economic Review, Elsevier, vol. 138(C).
• Giovannelli, Alessandro & Massacci, Daniele & Soccorsi, Stefano, 2021. "Forecasting stock returns with large dimensional factor models," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 252-269.
  • Alessandro Giovannelli & Daniele Massacci & Stefano Soccorsi, 2020. "Forecasting Stock Returns with Large Dimensional Factor Models," Working Papers 305661169, Lancaster University Management School, Economics Department.
• Costa, Alexandre Bonnet R. & Ferreira, Pedro Cavalcanti G. & Gaglianone, Wagner P. & Guillén, Osmani Teixeira C. & Issler, João Victor & Lin, Yihao, 2021. "Machine learning and oil price point and density forecasting," Energy Economics, Elsevier, vol. 102(C).
  • Alexandre Bonnet R. Costa & Pedro Cavalcanti G. Ferreira & Wagner P. Gaglianone & Osmani Teixeira C. Guillén & João Victor Issler & Yihao Lin, 2021. "Machine Learning and Oil Price Point and Density Forecasting," Working Papers Series 544, Central Bank of Brazil, Research Department.
• Bennedsen, Mikkel & Hillebrand, Eric & Koopman, Siem Jan, 2021. "Modeling, forecasting, and nowcasting U.S. CO2 emissions using many macroeconomic predictors," Energy Economics, Elsevier, vol. 96(C).
  • Mikkel Bennedsen & Eric Hillebrand & Siem Jan Koopman, 2019. "Modeling, Forecasting, and Nowcasting U.S. CO2 Emissions Using Many Macroeconomic Predictors," CREATES Research Papers 2019-21, Department of Economics and Business Economics, Aarhus University.
• Nam, Kyungsik, 2021. "Investigating the effect of climate uncertainty on global commodity markets," Energy Economics, Elsevier, vol. 96(C).
• Strauss, Ilan & Yang, Jangho, 2021. "Slowing investment rates in developing economies: Evidence from a Bayesian hierarchical model," International Review of Financial Analysis, Elsevier, vol. 77(C).
• Shynkevich, Andrei, 2021. "Bitcoin arbitrage," Finance Research Letters, Elsevier, vol. 40(C).
• Joo, Young C. & Park, Sung Y., 2021. "Optimal portfolio selection using a simple double-shrinkage selection rule," Finance Research Letters, Elsevier, vol. 43(C).
• Avanzi, Benjamin & Taylor, Greg & Wang, Melantha & Wong, Bernard, 2021. "SynthETIC: An individual insurance claim simulator with feature control," Insurance: Mathematics and Economics, Elsevier, vol. 100(C), pages 296-308.
• Avanzi, Benjamin & Taylor, Greg & Wong, Bernard & Yang, Xinda, 2021. "On the modelling of multivariate counts with Cox processes and dependent shot noise intensities," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 9-24.
• Gallego, Jorge & Rivero, Gonzalo & Martínez, Juan, 2021. "Preventing rather than punishing: An early warning model of malfeasance in public procurement," International Journal of Forecasting, Elsevier, vol. 37(1), pages 360-377.
  • Gallego, J & Rivero, G & Martínez, J.D., 2018. "Preventing rather than Punishing: An Early Warning Model of Malfeasance in Public Procurement," Documentos de Trabajo 16724, Universidad del Rosario.
• Richardson, Adam & van Florenstein Mulder, Thomas & Vehbi, Tuğrul, 2021. "Nowcasting GDP using machine-learning algorithms: A real-time assessment," International Journal of Forecasting, Elsevier, vol. 37(2), pages 941-948.
  • Adam Richardson & Thomas van Florenstein Mulder & Tugrul Vehbi, 2019. "Nowcasting New Zealand GDP using machine learning algorithms," IFC Bulletins chapters, in: Bank for International Settlements (ed.), The use of big data analytics and artificial intelligence in central banking, volume 50, Bank for International Settlements.
  • Adam Richardson & Thomas van Florenstein Mulder & Tugrul Vehbi, 2018. "Nowcasting New Zealand GDP using machine learning algorithms," CAMA Working Papers 2018-47, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Adam Richardson & Thomas van Florenstein Mulder & Tugrul Vehbi, 2019. "Nowcasting GDP using machine learning algorithms: A real-time assessment," Reserve Bank of New Zealand Discussion Paper Series DP2019/03, Reserve Bank of New Zealand.
• Chan, Joshua C.C., 2021. "Minnesota-type adaptive hierarchical priors for large Bayesian VARs," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1212-1226.
  • Joshua C. C. Chan, 2019. "Minnesota-type adaptive hierarchical priors for large Bayesian VARs," CAMA Working Papers 2019-61, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Goulet Coulombe, Philippe & Leroux, Maxime & Stevanovic, Dalibor & Surprenant, Stéphane, 2021. "Macroeconomic data transformations matter," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1338-1354.
  • Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stephane Surprenant, 2020. "Macroeconomic Data Transformations Matter," Working Papers 20-17, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Mar 2021.
  • Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & St'ephane Surprenant, 2020. "Macroeconomic Data Transformations Matter," Papers 2008.01714, arXiv.org, revised Mar 2021.
  • Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2020. "Macroeconomic Data Transformations Matter," CIRANO Working Papers 2020s-42, CIRANO.
• Hillen, Judith & Fedoseeva, Svetlana, 2021. "E-commerce and the end of price rigidity?," Journal of Business Research, Elsevier, vol. 125(C), pages 63-73.
• Brettschneider, Julia & Burro, Giovanni & Henderson, Vicky, 2021. "Wide framing disposition effect: An empirical study," Journal of Economic Behavior & Organization, Elsevier, vol. 185(C), pages 330-347.
• Painter, Marcus & Qiu, Tian, 2021. "Political beliefs affect compliance with government mandates," Journal of Economic Behavior & Organization, Elsevier, vol. 185(C), pages 688-701.
• Godzinski, Alexandre & Suarez Castillo, Milena, 2021. "Disentangling the effects of air pollutants with many instruments," Journal of Environmental Economics and Management, Elsevier, vol. 109(C).
• Hirche, Martin & Farris, Paul W. & Greenacre, Luke & Quan, Yiran & Wei, Susan, 2021. "Predicting Under- and Overperforming SKUs within the Distribution–Market Share Relationship," Journal of Retailing, Elsevier, vol. 97(4), pages 697-714.
• Martins, Pedro S., 2021. "Working to get fired? Unemployment benefits and employment duration," Journal of Policy Modeling, Elsevier, vol. 43(5), pages 1016-1030.
• Turrell, Arthur & Speigner, Bradley & Copple, David & Djumalieva, Jyldyz & Thurgood, James, 2021. "Is the UK’s productivity puzzle mostly driven by occupational mismatch? An analysis using big data on job vacancies," Labour Economics, Elsevier, vol. 71(C).
• Brownlees, Christian & Hans, Christina & Nualart, Eulalia, 2021. "Bank credit risk networks: Evidence from the Eurozone," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 585-599.
• Tissaoui, Kais & Zaghdoudi, Taha, 2021. "Dynamic connectedness between the U.S. financial market and Euro-Asian financial markets: Testing transmission of uncertainty through spatial regressions models," The Quarterly Review of Economics and Finance, Elsevier, vol. 81(C), pages 481-492.
• Garciga, Christian & Verbrugge, Randal, 2021. "Robust covariance matrix estimation and identification of unusual data points: New tools," Research in Economics, Elsevier, vol. 75(2), pages 176-202.
• Mckibbin, Warwick & Fernando, Roshen & Liu, Weifeng, 2021. "Global Economic Impacts of Climate Shocks, Climate Policy and Changes in Climate Risk Assessment," CEPR Discussion Papers 16154, C.E.P.R. Discussion Papers.
  • Roshen Fernando & Weifeng Liu & Warwick J McKibbin, 2021. "Global economic impacts of climate shocks, climate policy and changes in climate risk assessment," CAMA Working Papers 2021-37, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Christiane Baumeister & Danilo Leiva-León & Eric Sims, 2024. "Tracking Weekly State-Level Economic Conditions," The Review of Economics and Statistics, MIT Press, vol. 106(2), pages 483-504, March.
  • Christiane Baumeister & Danilo Leiva-León & Eric R. Sims, 2021. "Tracking Weekly State-Level Economic Conditions," NBER Working Papers 29003, National Bureau of Economic Research, Inc.
  • Christiane Baumeister & Danilo Leiva-León & Eric Sims, 2021. "Tracking weekly state-level economic conditions," CAMA Working Papers 2021-55, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Christiane Baumeister & Danilo Leiva-Leon & Eric Sims, 2021. "Tracking Weekly State-Level Economic Conditions," Working Papers 202151, University of Pretoria, Department of Economics.
  • Baumeister, Christiane & Leiva-León, Danilo & Sims, Eric, 2021. "Tracking Weekly State-Level Economic Conditions," CEPR Discussion Papers 16317, C.E.P.R. Discussion Papers.
  • Christiane Baumeister & Danilo Leiva-León & Eric R. Sims, 2021. "Tracking Weekly State-Level Economic Conditions," CESifo Working Paper Series 9165, CESifo.
  • Christiane Baumeister & Danilo Leiva-León & Eric Sims, 2021. "Tracking weekly state-level economic conditions," Working Papers 2134, Banco de España.
• Hanol Lee & Jong-Wha Lee, 2021. "Why East Asian students perform better in mathematics than their peers: An investigation using a machine learning approach," CAMA Working Papers 2021-66, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Mckibbin, Warwick & Jaumotte, Florence & Liu, Weifeng, 2021. "Mitigating Climate Change: Growth-Friendly Policies to Achieve Net Zero Emissions by 2050," CEPR Discussion Papers 16553, C.E.P.R. Discussion Papers.
  • Florence Jaumotte & Weifeng Liu & Warwick J. McKibbin, 2021. "Mitigating climate change: Growth-friendly policies to achieve net zero emissions by 2050," CAMA Working Papers 2021-75, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Ms. Florence Jaumotte & Weifeng Liu & Warwick J. McKibbin, 2021. "Mitigating Climate Change: Growth-Friendly Policies to Achieve Net Zero Emissions by 2050," IMF Working Papers 2021/195, International Monetary Fund.
• Kang, Jieyi & Reiner, David M., 2022. "What is the effect of weather on household electricity consumption? Empirical evidence from Ireland," Energy Economics, Elsevier, vol. 111(C).
  • Kang, J. & Reiner, D., 2021. "What is the effect of weather on household electricity consumption? Empirical evidence from Ireland," Cambridge Working Papers in Economics 2141, Faculty of Economics, University of Cambridge.
  • Jieyi Kang & David Reiner, 2021. "What is the effect of weather on household electricity consumption? Empirical evidence from Ireland," Working Papers EPRG2112, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
• Kang, J. & Reiner, D., 2021. "Machine Learning on residential electricity consumption: Which households are more responsive to weather?," Cambridge Working Papers in Economics 2142, Faculty of Economics, University of Cambridge.
  • Jieyi Kang & David Reiner, 2021. "Machine Learning on residential electricity consumption: Which households are more responsive to weather?," Working Papers EPRG2113, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
• Kang, J. & Reiner, D., 2021. "Identifying residential consumption patterns using data-mining techniques: A large-scale study of smart meter data in Chengdu, China," Cambridge Working Papers in Economics 2143, Faculty of Economics, University of Cambridge.
  • Jieyi Kang & David Reiner, 2021. "Identifying residential consumption patterns using data-mining techniques: A large-scale study of smart meter data in Chengdu, China," Working Papers EPRG2114, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
• Krzysztof Marcjan & Lucjan Gucma & Kotkowska Diana, 2021. "The Collision Risk Management Method for Ships Navigating on Coastal Waters Based on Ship Domain and Near-Miss Concept," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 127-146.
• Ofori, Isaac K. & Quaidoo, Christopher & Ofori, Pamela E., 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, issue forthcomi.
  • Isaac K. Ofori & Christopher Quaidoo & Pamela E. Ofori, 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," Working Papers of the African Governance and Development Institute. 21/074, African Governance and Development Institute..
  • Isaac K. Ofori & Christopher Quaidoo & Pamela E. Ofori, 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," Working Papers 21/074, European Xtramile Centre of African Studies (EXCAS).
  • Isaac K. Ofori & Christopher Quaidoo & Pamela E. Ofori, 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," Research Africa Network Working Papers 21/074, Research Africa Network (RAN).
• Lenka Nechvatalova, 2024. "Multi-Horizon Equity Returns Predictability via Machine Learning," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 74(2), pages 142-190, May.
  • Lenka Nechvatalova, 2021. "Multi-Horizon Equity Returns Predictability via Machine Learning," Working Papers IES 2021/02, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Feb 2021.
• Yu Bai & Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022. "Macroeconomic forecasting in a multi‐country context," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(6), pages 1230-1255, September.
  • Bai, Yu & Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano, 2022. "Macroeconomic Forecasting in a Multi-country Context," CEPR Discussion Papers 16994, C.E.P.R. Discussion Papers.
  • Yu Bai & Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022. "Macroeconomic Forecasting in a Multi-country Context," Working Papers 22-02, Federal Reserve Bank of Cleveland.
• Hie Joo Ahn & Matteo Luciani, 2021. "Relative prices and pure inflation since the mid-1990s," Finance and Economics Discussion Series 2021-069, Board of Governors of the Federal Reserve System (U.S.).
• Freyaldenhoven, Simon, 2022. "Factor models with local factors — Determining the number of relevant factors," Journal of Econometrics, Elsevier, vol. 229(1), pages 80-102.
  • Simon Freyaldenhoven, 2021. "Factor Models with Local Factors—Determining the Number of Relevant Factors," Working Papers 21-15, Federal Reserve Bank of Philadelphia.
• Massimo Franchi & Paolo Paruolo, 2021. "Cointegration, Root Functions and Minimal Bases," Econometrics, MDPI, vol. 9(3), pages 1-27, August.
  • Massimo Franchi & Paolo Paruolo, 2019. "Cointegration, root functions and minimal bases," DSS Empirical Economics and Econometrics Working Papers Series 2019/2, Centre for Empirical Economics and Econometrics, Department of Statistics, "Sapienza" University of Rome.
• Dean Fantazzini & Julia Pushchelenko & Alexey Mironenkov & Alexey Kurbatskii, 2021. "Forecasting Internal Migration in Russia Using Google Trends: Evidence from Moscow and Saint Petersburg," Forecasting, MDPI, vol. 3(4), pages 1-30, October.
  • Fantazzini, Dean & Pushchelenko, Julia & Mironenkov, Alexey & Kurbatskii, Alexey, 2021. "Forecasting internal migration in Russia using Google Trends: Evidence from Moscow and Saint Petersburg," MPRA Paper 110452, University Library of Munich, Germany.
• Hager Ben Romdhane, 2021. "Nowcasting in Tunisia using large datasets and mixed frequency models," IHEID Working Papers 11-2021, Economics Section, The Graduate Institute of International Studies.
• Tetiana Yukhymenko, 2021. "Role of the Media in the Inflation Expectation Formation Process," IHEID Working Papers 13-2021, Economics Section, The Graduate Institute of International Studies.
• Hansson, Magnus, 2021. "Evolution of topics in central bank speech communication," Working Papers in Economics 811, University of Gothenburg, Department of Economics.
• Niklas Amberg & Thomas Jansson & Mathias Klein & Anna Rogantini Picco, 2021. "Five Facts about the Distributional Income Effects of Monetary Policy," CESifo Working Paper Series 9062, CESifo.
  • Amberg, Niklas & Jansson, Thomas & Klein, Mathias & Rogantini Picco, Anna, 2021. "Five Facts about the Distributional Income Effects of Monetary Policy," Working Paper Series 403, Sveriges Riksbank (Central Bank of Sweden).
• Camino González Vasco & María Jesús Delgado Rodríguez & Sonia de Lucas Santos, 2021. "Segmentation of Potential Fraud Taxpayers and Characterization in Personal Income Tax Using Data Mining Techniques," Hacienda Pública Española / Review of Public Economics, IEF, vol. 239(4), pages 127-157, November.
• Hartl, Tobias & Hutter, Christian & Weber, Enzo, 2021. "Matching for three: big data evidence on search activity of workers, firms, and employment service," IAB-Discussion Paper 202101, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
• Christian Hutter, 2021. "Cyclicality of labour market search: a new big data approach," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 55(1), pages 1-16, December.
  • Hutter, Christian, 2021. "Cyclicality of labour market search: a new big data Approach," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 55(55), pages 1-.1.
• Christian Hutter, 2021. "Cyclicality of labour market search: a new big data approach," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 55(1), pages 1-16, December.
  • Hutter, Christian, 2021. "Cyclicality of labour market search: a new big data Approach," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 55, pages 1-1.
• Francesca Micocci & Armando Rungi, 2021. "Predicting Exporters with Machine Learning," Papers 2107.02512, arXiv.org, revised Sep 2022.
  • Francesca Micocci & Armando Rungi, 2021. "Predicting Exporters with Machine Learning," Working Papers 03/2021, IMT School for Advanced Studies Lucca, revised Jul 2021.
• Mckibbin, Warwick & Jaumotte, Florence & Liu, Weifeng, 2021. "Mitigating Climate Change: Growth-Friendly Policies to Achieve Net Zero Emissions by 2050," CEPR Discussion Papers 16553, C.E.P.R. Discussion Papers.
  • Ms. Florence Jaumotte & Weifeng Liu & Warwick J. McKibbin, 2021. "Mitigating Climate Change: Growth-Friendly Policies to Achieve Net Zero Emissions by 2050," IMF Working Papers 2021/195, International Monetary Fund.
  • Florence Jaumotte & Weifeng Liu & Warwick J. McKibbin, 2021. "Mitigating climate change: Growth-friendly policies to achieve net zero emissions by 2050," CAMA Working Papers 2021-75, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Narges Ahani & Tommy Andersson & Alessandro Martinello & Alexander Teytelboym & Andrew C. Trapp, 2021. "Placement Optimization in Refugee Resettlement," Operations Research, INFORMS, vol. 69(5), pages 1468-1486, September.
  • Trapp, Andrew C. & Teytelboym, Alexander & Martinello, Alessandro & Andersson, Tommy & Ahani, Narges, 2018. "Placement Optimization in Refugee Resettlement," Working Papers 2018:23, Lund University, Department of Economics, revised 20 Mar 2020.
• Oscar Claveria & Enric Monte & Salvador Torra, 2021. "“Nowcasting and forecasting GDP growth with machine-learning sentiment indicators”," AQR Working Papers 202101, University of Barcelona, Regional Quantitative Analysis Group, revised Feb 2021.
  • Oscar Claveria & Enric Monte & Salvador Torra, 2021. ""Nowcasting and forecasting GDP growth with machine-learning sentiment indicators"," IREA Working Papers 202103, University of Barcelona, Research Institute of Applied Economics, revised Feb 2021.
• Sarracino, Francesco & Greyling, Talita & O'Connor , Kelsey & Peroni, Chiara & Rossouw, Stephanie, 2021. "A year of pandemic: levels, changes and validity of well-being data from Twitter. Evidence from ten countries," GLO Discussion Paper Series 831, Global Labor Organization (GLO).
  • Sarracino, Francesco & Greyling, Talita & O'Connor, Kelsey J. & Peroni, Chiara & Rossouw, Stephanié, 2021. "A Year of Pandemic: Levels, Changes and Validity of Well-Being Data from Twitter. Evidence from Ten Countries," IZA Discussion Papers 14903, Institute of Labor Economics (IZA).
• Kadriye Hilal Topal, 2021. "Variable selection via the adaptive elastic net- mathematics success of the students in Singapore and Turkey," Journal of Applied Microeconometrics, Holistence Publications, vol. 1(1), pages 41-55, June.
• Luiz Renato Lima & Lucas Lúcio Godeiro & Mohammed Mohsin, 2021. "Time-Varying Dictionary and the Predictive Power of FED Minutes," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 149-181, January.
• Zhan Gao & Zhentao Shi, 2021. "Implementing Convex Optimization in R: Two Econometric Examples," Computational Economics, Springer;Society for Computational Economics, vol. 58(4), pages 1127-1135, December.
  • Zhan Gao & Zhentao Shi, 2018. "Implementing Convex Optimization in R: Two Econometric Examples," Papers 1806.10423, arXiv.org, revised Aug 2019.
• Dani Arribas-Bel & Mark Green & Francisco Rowe & Alex Singleton, 2021. "Open data products-A framework for creating valuable analysis ready data," Journal of Geographical Systems, Springer, vol. 23(4), pages 497-514, October.
• Robert Donnelly & Francisco J.R. Ruiz & David Blei & Susan Athey, 2021. "Counterfactual inference for consumer choice across many product categories," Quantitative Marketing and Economics (QME), Springer, vol. 19(3), pages 369-407, December.
  • Rob Donnelly & Francisco R. Ruiz & David Blei & Susan Athey, 2019. "Counterfactual Inference for Consumer Choice Across Many Product Categories," Papers 1906.02635, arXiv.org, revised Aug 2023.
• Pradeep K. Chintagunta, 2021. "Comments on “Counterfactual Inference for Consumer Choice Across Many Product Categories”," Quantitative Marketing and Economics (QME), Springer, vol. 19(3), pages 411-415, December.
• Timothy Holt & Mitsuru Igami & Simon Scheidegger, 2021. "Detecting Edgeworth Cycles," Cahiers de Recherches Economiques du Département d'économie 21.16, Université de Lausanne, Faculté des HEC, Département d’économie.
• Moench, Emanuel & Soofi-Siavash, Soroosh, 2022. "What moves treasury yields?," Journal of Financial Economics, Elsevier, vol. 146(3), pages 1016-1043.
  • Soroosh Soofi-Siavash & Emanuel Moench, 2021. "What Moves Treasury Yields?," Bank of Lithuania Working Paper Series 88, Bank of Lithuania.
  • Moench, Emanuel & Soofi Siavash, Soroosh, 2022. "What Moves Treasury Yields?," CEPR Discussion Papers 15978, C.E.P.R. Discussion Papers.
• François Gardes, 2021. "Biases on variances estimated on large data-sets," Documents de travail du Centre d'Economie de la Sorbonne 21022, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
• François Gardes, 2021. "Endogenous Prices in a Riemannian Geometry Framework," Documents de travail du Centre d'Economie de la Sorbonne 21026, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
• George Athanasopoulos & Nikolaos Kourentzes, 2021. "On the Evaluation of Hierarchical Forecasts," Monash Econometrics and Business Statistics Working Papers 10/21, Monash University, Department of Econometrics and Business Statistics.
• Sevvandi Kandanaarachchi & Rob J Hyndman, 2021. "Leave-one-out Kernel Density Estimates for Outlier Detection," Monash Econometrics and Business Statistics Working Papers 2/21, Monash University, Department of Econometrics and Business Statistics.
• Sayani Gupta & Rob J Hyndman & Dianne Cook, 2021. "Detecting Distributional Differences between Temporal Granularities for Exploratory Time Series Analysis," Monash Econometrics and Business Statistics Working Papers 20/21, Monash University, Department of Econometrics and Business Statistics.
• Fan Cheng & Rob J Hyndman & Anastasios Panagiotelis, 2021. "Manifold Learning with Approximate Nearest Neighbors," Monash Econometrics and Business Statistics Working Papers 3/21, Monash University, Department of Econometrics and Business Statistics.
• Algaba, Andres & Borms, Samuel & Boudt, Kris & Verbeken, Brecht, 2023. "Daily news sentiment and monthly surveys: A mixed-frequency dynamic factor model for nowcasting consumer confidence," International Journal of Forecasting, Elsevier, vol. 39(1), pages 266-278.
  • Andres Algaba & Samuel Borms & Kris Boudt & Brecht Verbeken, 2021. "Daily news sentiment and monthly surveys: A mixed–frequency dynamic factor model for nowcasting consumer confidence," Working Paper Research 396, National Bank of Belgium.
• Stefano Giglio & Yuan Liao & Dacheng Xiu & Wei Jiang, 2021. "Thousands of Alpha Tests [The performance of hedge funds: Risk, return, and incentives]," The Review of Financial Studies, Society for Financial Studies, vol. 34(7), pages 3456-3496.
  • Stefano Giglio & Yuan Liao & Dacheng Xiu, 2021. "Thousands of Alpha Tests," NBER Chapters, in: Big Data: Long-Term Implications for Financial Markets and Firms, pages 3456, National Bureau of Economic Research, Inc.
• Mark Braverman & Sylvain Chassang, 2021. "Data-Driven Incentive Alignment in Capitation Schemes," NBER Working Papers 28429, National Bureau of Economic Research, Inc.
• Gabriel E. Kreindler & Yuhei Miyauchi, 2021. "Measuring Commuting and Economic Activity inside Cities with Cell Phone Records," NBER Working Papers 28516, National Bureau of Economic Research, Inc.
• Christiane Baumeister & Danilo Leiva-León & Eric Sims, 2024. "Tracking Weekly State-Level Economic Conditions," The Review of Economics and Statistics, MIT Press, vol. 106(2), pages 483-504, March.
  • Christiane Baumeister & Danilo Leiva-León & Eric Sims, 2021. "Tracking weekly state-level economic conditions," CAMA Working Papers 2021-55, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Christiane Baumeister & Danilo Leiva-León & Eric R. Sims, 2021. "Tracking Weekly State-Level Economic Conditions," NBER Working Papers 29003, National Bureau of Economic Research, Inc.
  • Christiane Baumeister & Danilo Leiva-Leon & Eric Sims, 2021. "Tracking Weekly State-Level Economic Conditions," Working Papers 202151, University of Pretoria, Department of Economics.
  • Baumeister, Christiane & Leiva-León, Danilo & Sims, Eric, 2021. "Tracking Weekly State-Level Economic Conditions," CEPR Discussion Papers 16317, C.E.P.R. Discussion Papers.
  • Christiane Baumeister & Danilo Leiva-León & Eric R. Sims, 2021. "Tracking Weekly State-Level Economic Conditions," CESifo Working Paper Series 9165, CESifo.
  • Christiane Baumeister & Danilo Leiva-León & Eric Sims, 2021. "Tracking weekly state-level economic conditions," Working Papers 2134, Banco de España.
• Allen Hu & Song Ma, 2021. "Persuading Investors: A Video-Based Study," NBER Working Papers 29048, National Bureau of Economic Research, Inc.
• Blumenstock, Joshua & Aiken, Emily & Bellue, Suzanne & Udry, Christopher & Karlan, Dean, 2021. "Machine Learning and Mobile Phone Data Can Improve the Targeting of Humanitarian Assistance," CEPR Discussion Papers 16385, C.E.P.R. Discussion Papers.
  • Emily Aiken & Suzanne Bellue & Dean Karlan & Christopher R. Udry & Joshua Blumenstock, 2021. "Machine Learning and Mobile Phone Data Can Improve the Targeting of Humanitarian Assistance," NBER Working Papers 29070, National Bureau of Economic Research, Inc.
• Jens Ludwig & Sendhil Mullainathan, 2021. "Fragile Algorithms and Fallible Decision-Makers: Lessons from the Justice System," Journal of Economic Perspectives, American Economic Association, vol. 35(4), pages 71-96, Fall.
  • Jens Ludwig & Sendhil Mullainathan, 2021. "Fragile Algorithms and Fallible Decision-Makers: Lessons from the Justice System," NBER Working Papers 29267, National Bureau of Economic Research, Inc.
• Galina Manahilova, 2021. "Identifying Surrogation Using Business Analysis," Economics and Management, Faculty of Economics, SOUTH-WEST UNIVERSITY "NEOFIT RILSKI", BLAGOEVGRAD, vol. 18(1), pages 90-95.
• J. Boussard & R. Lee, 2020. "Competition, Profit Share and Concentration," Documents de Travail de l'Insee - INSEE Working Papers g2020-04, Institut National de la Statistique et des Etudes Economiques.
• A. Godzinski & M. Suarez Castillo, 2021. "Disentangling the effects of air pollutants with many instruments," Documents de Travail de l'Insee - INSEE Working Papers g2021-04, Institut National de la Statistique et des Etudes Economiques.
• Vasil Marchev, 2021. "Self-Perfecting Model for Managing Individualized Investment Portfolios," Ikonomiceski i Sotsialni Alternativi, University of National and World Economy, Sofia, Bulgaria, issue 4, pages 86-97, December.
• Julie Lassébie & Luca Marcolin & Marieke Vandeweyer & Benjamin Vignal, 2021. "Speaking the same language: A machine learning approach to classify skills in Burning Glass Technologies data," OECD Social, Employment and Migration Working Papers 263, OECD Publishing.
• Şeuleanu Dragoş, 2021. "The Communication Dimension of the Business Model Applied to the ELI-NP Project," Revista OEconomica, Romanian Society for Economic Science, Revista OEconomica, issue 02, June.
• Torben Andersen & Ilya Archakov & Leon Grund & Nikolaus Hautsch & Yifan Li & Sergey Nasekin & Ingmar Nolte & Manh Cuong Pham & Stephen Taylor & Viktor Todorov, 2021. "A Descriptive Study of High-Frequency Trade and Quote Option Data [Stealth Trading in Options Markets]," Journal of Financial Econometrics, Oxford University Press, vol. 19(1), pages 128-177.
• Apaar Sadhwani & Kay Giesecke & Justin Sirignano, 2021. "Deep Learning for Mortgage Risk [The Subprime Virus]," Journal of Financial Econometrics, Oxford University Press, vol. 19(2), pages 313-368.
• P Gagliardini & C Gourieroux & M Rubin, 2021. "Positional Portfolio Management," Journal of Financial Econometrics, Oxford University Press, vol. 19(4), pages 650-706.
• Giorgio Calzolari & Roxana Halbleib & Aygul Zagidullina, 2021. "A Latent Factor Model for Forecasting Realized Variances [Stock Returns and Volatility: Pricing the Short-Run and Long-Run Components of Market Risk]," Journal of Financial Econometrics, Oxford University Press, vol. 19(5), pages 860-909.
• Marcus Buckmann & Andy Haldane & Anne-Caroline Hüser, 2021. "Comparing minds and machines: implications for financial stability," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 37(3), pages 479-508.
  • Buckmann, Marcus & Haldane, Andy & Hüser, Anne-Caroline, 2021. "Comparing minds and machines: implications for financial stability," Bank of England working papers 937, Bank of England.
• Stefano Giglio & Yuan Liao & Dacheng Xiu, 2021. "Thousands of Alpha Tests," NBER Chapters, in: Big Data: Long-Term Implications for Financial Markets and Firms, pages 3456, National Bureau of Economic Research, Inc.
  • Stefano Giglio & Yuan Liao & Dacheng Xiu & Wei Jiang, 2021. "Thousands of Alpha Tests [The performance of hedge funds: Risk, return, and incentives]," The Review of Financial Studies, Society for Financial Studies, vol. 34(7), pages 3456-3496.
• Claudiu-Catalin Munteanu & Adina Cristea, 2021. "A Methodological Approach for the Journey through Real-Time Marketing: From Customer Journey Analytics to Personalization Engines," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(2), pages 849-855, December.
• Alessandro Bitetto & Paola Cerchiello & Charilaos Mertzanis, 2021. "A data-driven approach to measuring epidemiological susceptibility risk around the world," DEM Working Papers Series 200, University of Pavia, Department of Economics and Management.
• Coronado, Hilary & Lahura, Erick & Vega, Marco, 2021. "¿Qué tan rígidos son los precios en línea? Evidencia para el Perú usando Big Data," Revista Moneda, Banco Central de Reserva del Perú, issue 188, pages 30-33.
  • Coronado, Hilary & Lahura, Erick & Vega, Marco, 2020. "¿Qué tan rígidos son los precios en línea? Evidencia para Perú usando Big Data," Working Papers 2020-018, Banco Central de Reserva del Perú.
  • Marco Vega & Erick Lahura & Hilary Coronado, 2021. "¿Qué tan rígidos son los precios en línea? Evidencia para Perú usando Big Data," Documentos de Trabajo / Working Papers 2021-497, Departamento de Economía - Pontificia Universidad Católica del Perú.
• Hinz, Julian & Stammann, Amrei & Wanner, Joschka, 2019. "Persistent zeros: The extensive margin of trade," Kiel Working Papers 2139, Kiel Institute for the World Economy (IfW Kiel).
  • Julian Hinz & Amrei Stammann & Joschka Wanner, 2021. "State Dependence and Unobserved Heterogeneity in the Extensive Margin of Trade," CEPA Discussion Papers 36, Center for Economic Policy Analysis.
  • Julian Hinz & Amrei Stammann & Joschka Wanner, 2020. "State Dependence and Unobserved Heterogeneity in the Extensive Margin of Trade," Papers 2004.12655, arXiv.org, revised Jul 2021.
• Kollár, Aladár, 2021. "Betting models using AI: a review on ANN, SVM, and Markov chain," MPRA Paper 106821, University Library of Munich, Germany.
• Ofori, Isaac Kwesi, 2021. "Catching The Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," EconStor Preprints 235482, ZBW - Leibniz Information Centre for Economics.
  • Ofori, Isaac K, 2021. "Catching The Drivers of Inclusive Growth In Sub-Saharan Africa: An Application of Machine Learning," MPRA Paper 108622, University Library of Munich, Germany.
  • Isaac K. Ofori, 2021. "Catching the Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," Research Africa Network Working Papers 21/044, Research Africa Network (RAN).
  • Isaac K. Ofori, 2021. "Catching the Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," Working Papers of the African Governance and Development Institute. 21/044, African Governance and Development Institute..
  • Isaac K. Ofori, 2021. "Catching the Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," Working Papers 21/044, European Xtramile Centre of African Studies (EXCAS).
• Dean Fantazzini & Julia Pushchelenko & Alexey Mironenkov & Alexey Kurbatskii, 2021. "Forecasting Internal Migration in Russia Using Google Trends: Evidence from Moscow and Saint Petersburg," Forecasting, MDPI, vol. 3(4), pages 1-30, October.
  • Fantazzini, Dean & Pushchelenko, Julia & Mironenkov, Alexey & Kurbatskii, Alexey, 2021. "Forecasting internal migration in Russia using Google Trends: Evidence from Moscow and Saint Petersburg," MPRA Paper 110452, University Library of Munich, Germany.
• Ando, Tomohiro & Bai, Jushan, 2021. "Large-scale generalized linear longitudinal data models with grouped patterns of unobserved heterogeneity," MPRA Paper 111431, University Library of Munich, Germany.
• Dimitris Korobilis & Kenichi Shimizu, 2022. "Bayesian Approaches to Shrinkage and Sparse Estimation," Foundations and Trends(R) in Econometrics, now publishers, vol. 11(4), pages 230-354, June.
  • Dimitris Korobilis & Kenichi Shimizu, 2021. "Bayesian Approaches to Shrinkage and Sparse Estimation," Working Papers 2021_19, Business School - Economics, University of Glasgow.
  • Korobilis, Dimitris & Shimizu, Kenichi, 2021. "Bayesian Approaches to Shrinkage and Sparse Estimation," MPRA Paper 111631, University Library of Munich, Germany.
  • Dimitris Korobilis & Kenichi Shimizu, 2022. "Bayesian Approaches to Shrinkage and Sparse Estimation," Working Paper series 22-02, Rimini Centre for Economic Analysis.
  • Dimitris Korobilis & Kenichi Shimizu, 2021. "Bayesian Approaches to Shrinkage and Sparse Estimation," Papers 2112.11751, arXiv.org.
• Kombarov, Sayan, 2021. "Action in Economics: Mathematical Derivation of Laws of Economics from the Principle of Least Action in Physics," MPRA Paper 112474, University Library of Munich, Germany.
• Bradrania, Reza & Pirayesh Neghab, Davood, 2021. "State-dependent asset allocation using neural networks," MPRA Paper 115254, University Library of Munich, Germany.
• Christiane Baumeister & Danilo Leiva-León & Eric Sims, 2024. "Tracking Weekly State-Level Economic Conditions," The Review of Economics and Statistics, MIT Press, vol. 106(2), pages 483-504, March.
  • Christiane Baumeister & Danilo Leiva-León & Eric R. Sims, 2021. "Tracking Weekly State-Level Economic Conditions," NBER Working Papers 29003, National Bureau of Economic Research, Inc.
  • Christiane Baumeister & Danilo Leiva-Leon & Eric Sims, 2021. "Tracking Weekly State-Level Economic Conditions," Working Papers 202151, University of Pretoria, Department of Economics.
  • Baumeister, Christiane & Leiva-León, Danilo & Sims, Eric, 2021. "Tracking Weekly State-Level Economic Conditions," CEPR Discussion Papers 16317, C.E.P.R. Discussion Papers.
  • Christiane Baumeister & Danilo Leiva-León & Eric R. Sims, 2021. "Tracking Weekly State-Level Economic Conditions," CESifo Working Paper Series 9165, CESifo.
  • Christiane Baumeister & Danilo Leiva-León & Eric Sims, 2021. "Tracking weekly state-level economic conditions," Working Papers 2134, Banco de España.
  • Christiane Baumeister & Danilo Leiva-León & Eric Sims, 2021. "Tracking weekly state-level economic conditions," CAMA Working Papers 2021-55, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Mark Braverman & Sylvain Chassang, 2021. "Data-Driven Incentive Alignment in Capitation Schemes," Working Papers 282, Princeton University, Department of Economics, Center for Economic Policy Studies..
• Redding, Stephen & Miyauchi, Yuhei & Nakajima, Kentaro, 2021. "Consumption Access and Agglomeration: Evidence from Smartphone Data," CEPR Discussion Papers 15839, C.E.P.R. Discussion Papers.
  • Yuhei Miyauchi & Kentaro Nakajima & Stephen J. Redding, 2021. "Consumption Access and Agglomeration: Evidence from Smartphone Data," Working Papers 287, Princeton University, Department of Economics, Center for Economic Policy Studies..
  • Redding, Stephen & Nakajima, Kentaro & Miyauchi, Yuhei, 2021. "Consumption access and agglomeration: evidence from smartphone data," LSE Research Online Documents on Economics 114353, London School of Economics and Political Science, LSE Library.
  • Yuhei Miyauchi & Kentaro Nakajima & Stephen J. Redding, 2021. "Consumption access and agglomeration: evidence from smartphone data," CEP Discussion Papers dp1745, Centre for Economic Performance, LSE.
• Bhumjai Tangsawasdirat & Suranan Tanpoonkiat & Burasakorn Tangsatchanan, 2021. "Credit Risk Database: Credit Scoring Models for Thai SMEs," PIER Discussion Papers 168, Puey Ungphakorn Institute for Economic Research.
• Giulio Marini, 2021. "Joining the European Union as an advantage in science performativity. A quasi-experimental study," DoQSS Working Papers 21-09, Quantitative Social Science - UCL Social Research Institute, University College London.
• Luke Hartigan & Michelle Wright, 2021. "Financial Conditions and Downside Risk to Economic Activity in Australia," RBA Research Discussion Papers rdp2021-03, Reserve Bank of Australia.
• Coronado, Hilary & Lahura, Erick & Vega, Marco, 2021. "¿Qué tan rígidos son los precios en línea? Evidencia para el Perú usando Big Data," Revista Moneda, Banco Central de Reserva del Perú, issue 188, pages 30-33.
  • Coronado, Hilary & Lahura, Erick & Vega, Marco, 2020. "¿Qué tan rígidos son los precios en línea? Evidencia para Perú usando Big Data," Working Papers 2020-018, Banco Central de Reserva del Perú.
  • Marco Vega & Erick Lahura & Hilary Coronado, 2021. "¿Qué tan rígidos son los precios en línea? Evidencia para Perú usando Big Data," Documentos de Trabajo / Working Papers 2021-497, Departamento de Economía - Pontificia Universidad Católica del Perú.
• Karen Poghosyan & Ruben Poghosyan, 2021. "On the Applicability of Dynamic Factor Models for Forecasting Real GDP Growth in Armenia," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 71(1), pages 52-79, June.
  • Poghosyan, Karen & Poghosyan, Ruben, 2021. "On the applicability of dynamic factor models for forecasting real GDP growth in Armenia," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 61, pages 28-46.
• Denise Desjardins & Georges Dionne & Yang Lu, 2023. "Hierarchical random‐effects model for the insurance pricing of vehicles belonging to a fleet," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(2), pages 242-259, March.
  • Desjardins, Denise & Dionne, Georges & Lu, Yang, 2021. "Hierarchical random effects model for insurance pricing of vehicles belonging to a fleet," Working Papers 21-2, HEC Montreal, Canada Research Chair in Risk Management.
• Dimingo, Roselyn & Muteba Mwamba, John W. & Bonga-Bonga, Lumengo, 2021. "Prediction of Stock Market Direction: Application of Machine Learning Models," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, vol. 74(4), pages 499-536.
• Farag, Markos & Zaki, Chahir, 2021. "On the Determinants of Trade in Natural Gas: A Political Economy Approach," EWI Working Papers 2021-8, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
• Rao, Anitha & Wiendling, Mark & Ridgeway, Paul & Kennedy, Liz & Eyre, Harris A. & Pinho, Paulo, 2021. "Bridging the Gap Between Medicine and Insurance: How to Leverage Data, Artificial Intelligence, and Neuroinformatics for Insurance and Financial Risk Management," Journal of Financial Transformation, Capco Institute, vol. 54, pages 142-147.
• Chow, Hwee Kwan & Han, Daniel, 2021. "Forecast Pooling or Information Pooling During Crises? MIDAS Forecasting of GDP in a Small Open Economy," Economics and Statistics Working Papers 6-2021, Singapore Management University, School of Economics.
• Huaiwen ZHANG & Adnan Khurshid & Xinyu WANG & Alina Mirela BĂLTĂŢEANU, 2021. "Corporate Financial Risk Assessment and Role of Big Data; New Perspective Using Fuzzy Analytic Hierarchy Process," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 181-199, June.
• Bekaert, Els & Constant, Amelie F. & Foubert, Killian & Ruyssen, Ilse, 2021. "Longing for which home: Evidence from global aspirations to stay, return or migrate onwards," MERIT Working Papers 2021-035, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
  • Els Bekaert & Amelie F. Constant & Killian Foubert & Ilse Ruyssen, 2021. "Longing for Which Home: Evidence from Global Aspirations to Stay, Return or Migrate Onwards," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 21/1028, Ghent University, Faculty of Economics and Business Administration.
  • Bekaert, Els & Constant, Amelie F. & Foubert, Killian & Ruyssen, Ilse, 2021. "Longing for Which Home: Evidence from Global Aspirations to Stay, Return or Migrate Onwards," GLO Discussion Paper Series 930, Global Labor Organization (GLO).
  • Els Bekaert & Amelie F. Constant & Killian Foubert & Ilse Ruyssen, 2021. "Longing for Which Home: Evidence from Global Aspirations to Stay, Return or Migrate Onwards," CESifo Working Paper Series 9301, CESifo.
• Wojciech Charemza & Michal Lewandowski & Lukasz Wozny, 2021. "Efficiency in rewarding academic journal publications. The case of Poland," KAE Working Papers 2021-062, Warsaw School of Economics, Collegium of Economic Analysis.
• Paolo Nicola Barbieri & Beatrice Bonini, 2021. "Political orientation and adherence to social distancing during the COVID-19 pandemic in Italy," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 38(2), pages 483-504, July.
• Christopher Helm & Tim A. Herberger & Marcel Tyrell, 2021. "Demand dynamics across secondary German Book markets: an information aggregation and synthetization approach," Information Systems and e-Business Management, Springer, vol. 19(2), pages 567-596, June.
• Faustino Prieto & José María Sarabia & Enrique Calderín-Ojeda, 2021. "The nonlinear distribution of employment across municipalities," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 16(2), pages 287-307, April.
• Hutter, Christian, 2021. "Cyclicality of labour market search: a new big data Approach," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 55, pages 1-1.
  • Christian Hutter, 2021. "Cyclicality of labour market search: a new big data approach," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 55(1), pages 1-16, December.
• Roberto S. Mariano & Suleyman Ozmucur, 2021. "Predictive Performance of Mixed-Frequency Nowcasting and Forecasting Models (with Application to Philippine Inflation and GDP Growth)," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 383-400, December.
• Iasonas Papafotikas & Dimitrios Folinas, 2021. "Sentiment Analysis: Relationship Between Customer Sentiment and Online Customer Ratings for Price Comparison Engines. An Empirical Study," Springer Proceedings in Business and Economics, in: Alexandra Horobet & Lucian Belascu & Persefoni Polychronidou & Anastasios Karasavvoglou (ed.), Global, Regional and Local Perspectives on the Economies of Southeastern Europe, pages 257-272, Springer.
• Fu-Hsiang Kuo, 2021. "An Investigation of the Operational Efficiency of School Management through Innovative Teaching via Digital Mobile E-learning: DEA and Data mining Methodology," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 11(1), pages 1-1.
• Chris van Wyk, 2021. "Learner flow through patterns in the Western Cape using CEMIS datasets from 2007 to 2019: A longitudinal cohort analysis," Working Papers 01/2021, Stellenbosch University, Department of Economics.
• Hanjo Odendaal, 2021. "A machine learning approach to domain specific dictionary generation. An economic time series framework," Working Papers 06/2021, Stellenbosch University, Department of Economics.
• Antoine A. Djogbenou, 2021. "Model selection in factor-augmented regressions with estimated factors," Econometric Reviews, Taylor & Francis Journals, vol. 40(5), pages 470-503, April.
  • Antoine A. Djogbenou, 2017. "Model Selection In Factor-augmented Regressions With Estimated Factors," Working Paper 1391, Economics Department, Queen's University.
• Dimitris Korobilis, 2021. "High-Dimensional Macroeconomic Forecasting Using Message Passing Algorithms," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(2), pages 493-504, March.
  • Dimitris Korobilis, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," Working Papers 2019_07, Business School - Economics, University of Glasgow.
  • Dimitris Korobilis, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," Working Paper series 19-17, Rimini Centre for Economic Analysis.
  • Korobilis, Dimitris, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," MPRA Paper 96079, University Library of Munich, Germany.
  • Dimitris Korobilis, 2020. "High-dimensional macroeconomic forecasting using message passing algorithms," Papers 2004.11485, arXiv.org.
• Gonzalez Rivera, Gloria & Rodríguez Caballero, Carlos Vladimir, 2021. "Expecting the unexpected: economic growth under stress," DES - Working Papers. Statistics and Econometrics. WS 32148, Universidad Carlos III de Madrid. Departamento de Estadística.
  • Gloria Gonzalez-Rivera & Vladimir Rodriguez-Caballero & Esther Ruiz, 2021. "Expecting the unexpected: economic growth under stress," Working Papers 202106, University of California at Riverside, Department of Economics.
  • Gloria González-Rivera & Carlos Vladimir Rodríguez-Caballero & Esther Ruiz Ortega, 2021. "Expecting the unexpected: economic growth under stress," CREATES Research Papers 2021-06, Department of Economics and Business Economics, Aarhus University.
• Guillermo Cabanillas-Jiménez, 2021. "Testing the Permanent Income Hypothesis using the Spanish Christmas Lottery," Studies in Economics 2104, School of Economics, University of Kent.
• Dylan Brewer & Alyssa Carlson, 2024. "Addressing sample selection bias for machine learning methods," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(3), pages 383-400, April.
  • Dylan Brewer & Alyssa Carlson, 2021. "Addressing Sample Selection Bias for Machine Learning Methods," Working Papers 2114, Department of Economics, University of Missouri.
  • Dylan Brewer & Alyssa Carlson, 2023. "Addressing Sample Selection Bias for Machine Learning Methods," Working Papers 2302, Department of Economics, University of Missouri.
  • Dylan Brewer & Alyssa Carlson, 2023. "Addressing Sample Selection Bias for Machine Learning Methods," Working Papers 2310, Department of Economics, University of Missouri.
  • Dylan Brewer & Alyssa Carlson, 2021. "Addressing Sample Selection Bias for Machine Learning Methods," Working Papers 2102, Department of Economics, University of Missouri.
• Dylan Brewer & Alyssa Carlson, 2024. "Addressing sample selection bias for machine learning methods," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(3), pages 383-400, April.
  • Dylan Brewer & Alyssa Carlson, 2021. "Addressing Sample Selection Bias for Machine Learning Methods," Working Papers 2102, Department of Economics, University of Missouri.
  • Dylan Brewer & Alyssa Carlson, 2023. "Addressing Sample Selection Bias for Machine Learning Methods," Working Papers 2302, Department of Economics, University of Missouri.
  • Dylan Brewer & Alyssa Carlson, 2023. "Addressing Sample Selection Bias for Machine Learning Methods," Working Papers 2310, Department of Economics, University of Missouri.
  • Dylan Brewer & Alyssa Carlson, 2021. "Addressing Sample Selection Bias for Machine Learning Methods," Working Papers 2114, Department of Economics, University of Missouri.
• Els Bekaert & Amelie F. Constant & Killian Foubert & Ilse Ruyssen, 2021. "Longing for Which Home: Evidence from Global Aspirations to Stay, Return or Migrate Onwards," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 21/1028, Ghent University, Faculty of Economics and Business Administration.
  • Bekaert, Els & Constant, Amelie F. & Foubert, Killian & Ruyssen, Ilse, 2021. "Longing for which home: Evidence from global aspirations to stay, return or migrate onwards," MERIT Working Papers 2021-035, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
  • Bekaert, Els & Constant, Amelie F. & Foubert, Killian & Ruyssen, Ilse, 2021. "Longing for Which Home: Evidence from Global Aspirations to Stay, Return or Migrate Onwards," GLO Discussion Paper Series 930, Global Labor Organization (GLO).
  • Els Bekaert & Amelie F. Constant & Killian Foubert & Ilse Ruyssen, 2021. "Longing for Which Home: Evidence from Global Aspirations to Stay, Return or Migrate Onwards," CESifo Working Paper Series 9301, CESifo.
• Jankowiak Maciej, 2021. "The EU Member States’ national healthcare systems compared using the single synthetic index," Economics and Business Review, Sciendo, vol. 7(2), pages 37-49, June.
• Poláček Lukáš & Vavřina Jan & Polák Josef, 2021. "Current Challenges of Social Responsibility Best Practise in Foodstuff Production and Distribution Chain: Focus on Cee Countries," Management Theory and Studies for Rural Business and Infrastructure Development, Sciendo, vol. 43(4), pages 442-456, December.
• Poláček Lukáš & Vavřina Jan & Polák Josef, 2021. "Current Challenges of Social Responsibility Best Practise in Foodstuff Production and Distribution Chain: Focus on Cee Countries," Management Theory and Studies for Rural Business and Infrastructure Development, Sciendo, vol. 43(4), pages 442-456, December.
• Dawid Siwicki, 2021. "The Application of Machine Learning Algorithms for Spatial Analysis: Predicting of Real Estate Prices in Warsaw," Working Papers 2021-05, Faculty of Economic Sciences, University of Warsaw.
• Piotr Borowski & Marcin Chlebus, 2021. "Machine learning in the prediction of flat horse racing results in Poland," Working Papers 2021-13, Faculty of Economic Sciences, University of Warsaw.
• Maaz Khan & Faheem Aslam & Paulo Ferreira, 2021. "Extreme Value Theory and COVID-19 Pandemic: Evidence from India," Economic Research Guardian, Weissberg Publishing, vol. 11(1), pages 2-10, June.
• Mrestyal Khan & Maaz Khan, 2021. "Cryptomarket Volatility in Times of COVID-19 Pandemic: Application of GARCH Models," Economic Research Guardian, Weissberg Publishing, vol. 11(2), pages 170-181, December.
• Stefan Ederer & Stefan Humer & Stefan Jestl & Emanuel List, 2020. "Distributional National Accounts (DINA) with Household Survey Data: Methodology and Results for European Countries," wiiw Working Papers 180, The Vienna Institute for International Economic Studies, wiiw.
  • Stefan Ederer & Stefan Humer & Stefan Jestl & Emanuel List, 2020. "Distributional National Accounts (DINA) with Household Survey Data. Methodology and Results for European Countries," WIFO Working Papers 599, WIFO.
• Peter C. B. Phillips & Zhentao Shi, 2021. "Boosting: Why You Can Use The Hp Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 62(2), pages 521-570, May.
  • Peter C. B. Phillips & Zhentao Shi, 2019. "Boosting: Why You Can Use the HP Filter," Papers 1905.00175, arXiv.org, revised Nov 2020.
  • Peter C.B. Phillips & Zhentao Shi, 2019. "Boosting: Why you Can Use the HP Filter," Cowles Foundation Discussion Papers 2212, Cowles Foundation for Research in Economics, Yale University.
• Ricketts, Simon, 2021. "Do Political Actors Engage in Strategic Deception on Social Media?," Warwick-Monash Economics Student Papers 16, Warwick Monash Economics Student Papers.
• Hauber, Philipp & Schumacher, Christian, 2021. "Precision-based sampling with missing observations: A factor model application," Discussion Papers 11/2021, Deutsche Bundesbank.
• Arrigoni, Simone & Bobasu, Alina & Venditti, Fabrizio, 2020. "The simpler the better: measuring financial conditions for monetary policy and financial stability," Working Paper Series 2451, European Central Bank.
  • Arrigoni, Simone & Bobasu, Alina & Venditti, Fabrizio, 2021. "The simpler, the better: Measuring financial conditions for monetary policy and financial stability," EIB Working Papers 2021/10, European Investment Bank (EIB).
• Ofori, Isaac K. & Quaidoo, Christopher & Ofori, Pamela E., 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, issue forthcomi.
  • Isaac K. Ofori & Christopher Quaidoo & Pamela E. Ofori, 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," Working Papers 21/074, European Xtramile Centre of African Studies (EXCAS).
  • Isaac K. Ofori & Christopher Quaidoo & Pamela E. Ofori, 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," Working Papers of the African Governance and Development Institute. 21/074, African Governance and Development Institute..
  • Isaac K. Ofori & Christopher Quaidoo & Pamela E. Ofori, 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," Research Africa Network Working Papers 21/074, Research Africa Network (RAN).
• Isaac K. Ofori, 2021. "Catching the Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," Working Papers 21/044, European Xtramile Centre of African Studies (EXCAS).
  • Ofori, Isaac Kwesi, 2021. "Catching The Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," EconStor Preprints 235482, ZBW - Leibniz Information Centre for Economics.
  • Ofori, Isaac K, 2021. "Catching The Drivers of Inclusive Growth In Sub-Saharan Africa: An Application of Machine Learning," MPRA Paper 108622, University Library of Munich, Germany.
  • Isaac K. Ofori, 2021. "Catching the Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," Research Africa Network Working Papers 21/044, Research Africa Network (RAN).
  • Isaac K. Ofori, 2021. "Catching the Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," Working Papers of the African Governance and Development Institute. 21/044, African Governance and Development Institute..
• Hauber, Philipp, 2021. "How useful is external information from professional forecasters? Conditional forecasts in large factor models," EconStor Preprints 251469, ZBW - Leibniz Information Centre for Economics.
• Sarracino, Francesco & Greyling, Talita & O'Connor, Kelsey J. & Peroni, Chiara & Rossouw, Stephanié, 2021. "A Year of Pandemic: Levels, Changes and Validity of Well-Being Data from Twitter. Evidence from Ten Countries," IZA Discussion Papers 14903, Institute of Labor Economics (IZA).
  • Sarracino, Francesco & Greyling, Talita & O'Connor , Kelsey & Peroni, Chiara & Rossouw, Stephanie, 2021. "A year of pandemic: levels, changes and validity of well-being data from Twitter. Evidence from ten countries," GLO Discussion Paper Series 831, Global Labor Organization (GLO).
• Els Bekaert & Amelie F. Constant & Killian Foubert & Ilse Ruyssen, 2021. "Longing for Which Home: Evidence from Global Aspirations to Stay, Return or Migrate Onwards," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 21/1028, Ghent University, Faculty of Economics and Business Administration.
  • Bekaert, Els & Constant, Amelie F. & Foubert, Killian & Ruyssen, Ilse, 2021. "Longing for Which Home: Evidence from Global Aspirations to Stay, Return or Migrate Onwards," GLO Discussion Paper Series 930, Global Labor Organization (GLO).
  • Els Bekaert & Amelie F. Constant & Killian Foubert & Ilse Ruyssen, 2021. "Longing for Which Home: Evidence from Global Aspirations to Stay, Return or Migrate Onwards," CESifo Working Paper Series 9301, CESifo.
  • Bekaert, Els & Constant, Amelie F. & Foubert, Killian & Ruyssen, Ilse, 2021. "Longing for which home: Evidence from global aspirations to stay, return or migrate onwards," MERIT Working Papers 2021-035, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
• Greyling, Talita & Rossouw, Stephanié, 2021. "Anger, fear and everything else: attitudes towards the COVID-19 vaccines," GLO Discussion Paper Series 939, Global Labor Organization (GLO).
• Dörr, Julian Oliver & Kinne, Jan & Lenz, David & Licht, Georg & Winker, Peter, 2021. "An integrated data framework for policy guidance in times of dynamic economic shocks," ZEW Discussion Papers 21-062, ZEW - Leibniz Centre for European Economic Research.

2020

• Borup, Daniel & Christensen, Bent Jesper & Mühlbach, Nicolaj Søndergaard & Nielsen, Mikkel Slot, 2023. "Targeting predictors in random forest regression," International Journal of Forecasting, Elsevier, vol. 39(2), pages 841-868.
  • Daniel Borup & Bent Jesper Christensen & Nicolaj N{o}rgaard Muhlbach & Mikkel Slot Nielsen, 2020. "Targeting predictors in random forest regression," Papers 2004.01411, arXiv.org, revised Nov 2020.
  • Daniel Borup & Bent Jesper Christensen & Nicolaj N. Mühlbach & Mikkel S. Nielsen, 2020. "Targeting predictors in random forest regression," CREATES Research Papers 2020-03, Department of Economics and Business Economics, Aarhus University.
• Eric Hillebrand & Jakob Mikkelsen & Lars Spreng & Giovanni Urga, 2020. "Exchange Rates and Macroeconomic Fundamentals: Evidence of Instabilities from Time-Varying Factor Loadings," CREATES Research Papers 2020-19, Department of Economics and Business Economics, Aarhus University.
• Sarthak Behera & Hyeongwoo Kim & Soohyon Kim, 2020. "Forecasting the US Dollar-Korean Won Exchange Rate: A Factor-Augmented Model Approach," Auburn Economics Working Paper Series auwp2020-02, Department of Economics, Auburn University.
• Maryam Farboodi & Laura Veldkamp, 2020. "Long-Run Growth of Financial Data Technology," American Economic Review, American Economic Association, vol. 110(8), pages 2485-2523, August.
• Janet Currie & Henrik Kleven & Esmée Zwiers, 2020. "Technology and Big Data Are Changing Economics: Mining Text to Track Methods," AEA Papers and Proceedings, American Economic Association, vol. 110, pages 42-48, May.
  • Janet Currie & Henrik Kleven & Esmée Zwiers, 2020. "Technology and Big Data Are Changing Economics: Mining Text to Track Methods," NBER Working Papers 26715, National Bureau of Economic Research, Inc.
• Viorelia LUNGU, 2020. "Some Notes on the Geopolitics and Geo-economics of Russia’s Post-Soviet Neocolonialism in Central Asia," Eastern European Journal for Regional Studies (EEJRS), Center for Studies in European Integration (CSEI), Academy of Economic Studies of Moldova (ASEM), vol. 6(1), pages 87-101, June.
• Edson Zambon Monte & Felipe Fantin Almeida, 2020. "Interrelationships Between The Stock Returns Of Brazilian Companies That Make Up The Sãƒo Paulo Stock Exchange Index," Revista de Economia Mackenzie (REM), Mackenzie Presbyterian University, Social and Applied Sciences Center, vol. 17(1), pages 115-145, January-J.
• Olivier Cabrignac & Arthur Charpentier & Ewen Gallic, 2020. "Modeling Joint Lives within Families," Working Papers halshs-02871927, HAL.
  • Olivier Cabrignac & Arthur Charpentier & Ewen Gallic, 2020. "Modeling Joint Lives within Families," AMSE Working Papers 2021, Aix-Marseille School of Economics, France.
  • Olivier Cabrignac & Arthur Charpentier & Ewen Gallic, 2020. "Modeling Joint Lives within Families," Papers 2006.08446, arXiv.org.
• Klaus Ackermann & Alexey Chernikov & Nandini Anantharama & Miethy Zaman & Paul A Raschky, 2020. "Object Recognition for Economic Development from Daytime Satellite Imagery," Papers 2009.05455, arXiv.org.
  • Klaus Ackermann & Alexey Chernikov & Nandini Anantharama & Miethy Zaman & Paul A Raschky, 2020. "Object Recognition for Economic Development from Daytime Satellite Imagery," SoDa Laboratories Working Paper Series 2020-02, Monash University, SoDa Laboratories.
• Klaus Ackermann & Simon D Angus & Paul A Raschky, 2020. "Estimating Sleep and Work Hours from Alternative Data by Segmented Functional Classification Analysis, SFCA," SoDa Laboratories Working Paper Series 2020-04, Monash University, SoDa Laboratories.
• Oscar Claveria & Ivana Lolic & Enric Monte & Petar Soric, 2020. "Economic determinants of employment sentiment: A socio-demographic analysis for the euro area," IREA Working Papers 202001, University of Barcelona, Research Institute of Applied Economics, revised Jan 2020.
  • Oscar Claveria & Ivana Lolic & Enric Monte & Salvador Torra & Petar Soric, 2020. "“Economic determinants of employment sentiment: A socio-demographic analysis for the euro area”," AQR Working Papers 2012001, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2020.
• Borup, Daniel & Christensen, Bent Jesper & Mühlbach, Nicolaj Søndergaard & Nielsen, Mikkel Slot, 2023. "Targeting predictors in random forest regression," International Journal of Forecasting, Elsevier, vol. 39(2), pages 841-868.
  • Daniel Borup & Bent Jesper Christensen & Nicolaj N. Mühlbach & Mikkel S. Nielsen, 2020. "Targeting predictors in random forest regression," CREATES Research Papers 2020-03, Department of Economics and Business Economics, Aarhus University.
  • Daniel Borup & Bent Jesper Christensen & Nicolaj N{o}rgaard Muhlbach & Mikkel Slot Nielsen, 2020. "Targeting predictors in random forest regression," Papers 2004.01411, arXiv.org, revised Nov 2020.
• Dimitris Korobilis, 2021. "High-Dimensional Macroeconomic Forecasting Using Message Passing Algorithms," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(2), pages 493-504, March.
  • Dimitris Korobilis, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," Working Papers 2019_07, Business School - Economics, University of Glasgow.
  • Dimitris Korobilis, 2020. "High-dimensional macroeconomic forecasting using message passing algorithms," Papers 2004.11485, arXiv.org.
  • Dimitris Korobilis, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," Working Paper series 19-17, Rimini Centre for Economic Analysis.
  • Korobilis, Dimitris, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," MPRA Paper 96079, University Library of Munich, Germany.
• Hinz, Julian & Stammann, Amrei & Wanner, Joschka, 2019. "Persistent zeros: The extensive margin of trade," Kiel Working Papers 2139, Kiel Institute for the World Economy (IfW Kiel).
  • Julian Hinz & Amrei Stammann & Joschka Wanner, 2020. "State Dependence and Unobserved Heterogeneity in the Extensive Margin of Trade," Papers 2004.12655, arXiv.org, revised Jul 2021.
  • Julian Hinz & Amrei Stammann & Joschka Wanner, 2021. "State Dependence and Unobserved Heterogeneity in the Extensive Margin of Trade," CEPA Discussion Papers 36, Center for Economic Policy Analysis.
• Olivier Cabrignac & Arthur Charpentier & Ewen Gallic, 2020. "Modeling Joint Lives within Families," AMSE Working Papers 2021, Aix-Marseille School of Economics, France.
  • Olivier Cabrignac & Arthur Charpentier & Ewen Gallic, 2020. "Modeling Joint Lives within Families," Papers 2006.08446, arXiv.org.
  • Olivier Cabrignac & Arthur Charpentier & Ewen Gallic, 2020. "Modeling Joint Lives within Families," Working Papers halshs-02871927, HAL.
• Laurent Ferrara & Anna Simoni, 2023. "When are Google Data Useful to Nowcast GDP? An Approach via Preselection and Shrinkage," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(4), pages 1188-1202, October.
  • Laurent Ferrara & Anna Simoni, 2019. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working Papers 2019-04, Center for Research in Economics and Statistics.
  • Laurent Ferrara & Anna Simoni, 2023. "When are Google Data Useful to Nowcast GDP? An Approach via Preselection and Shrinkage," Post-Print hal-03919944, HAL.
  • Laurent Ferrara & Anna Simoni, 2020. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Papers 2007.00273, arXiv.org, revised Sep 2022.
  • Laurent Ferrara & Anna Simoni, 2019. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working papers 717, Banque de France.
  • Laurent Ferrara & Anna Simoni, 2020. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working Papers hal-04159714, HAL.
  • Laurent Ferrara & Anna Simoni, 2020. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," EconomiX Working Papers 2020-11, University of Paris Nanterre, EconomiX.
• Adamek, Robert & Smeekes, Stephan & Wilms, Ines, 2023. "Lasso inference for high-dimensional time series," Journal of Econometrics, Elsevier, vol. 235(2), pages 1114-1143.
  • Robert Adamek & Stephan Smeekes & Ines Wilms, 2020. "Lasso Inference for High-Dimensional Time Series," Papers 2007.10952, arXiv.org, revised Sep 2022.
• Paolo Andreini & Cosimo Izzo & Giovanni Ricco, 2020. "Deep Dynamic Factor Models," Papers 2007.11887, arXiv.org, revised May 2023.
  • Paolo Andreini & Cosimo Izzo & Giovanni Ricco, 2023. "Deep Dynamic Factor Models," Working Papers 2023-08, Center for Research in Economics and Statistics.
• Goulet Coulombe, Philippe & Leroux, Maxime & Stevanovic, Dalibor & Surprenant, Stéphane, 2021. "Macroeconomic data transformations matter," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1338-1354.
  • Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stephane Surprenant, 2020. "Macroeconomic Data Transformations Matter," Working Papers 20-17, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Mar 2021.
  • Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & St'ephane Surprenant, 2020. "Macroeconomic Data Transformations Matter," Papers 2008.01714, arXiv.org, revised Mar 2021.
  • Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2020. "Macroeconomic Data Transformations Matter," CIRANO Working Papers 2020s-42, CIRANO.
• Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2022. "How is machine learning useful for macroeconomic forecasting?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 920-964, August.
  • Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2019. "How is Machine Learning Useful for Macroeconomic Forecasting?," CIRANO Working Papers 2019s-22, CIRANO.
  • Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & St'ephane Surprenant, 2020. "How is Machine Learning Useful for Macroeconomic Forecasting?," Papers 2008.12477, arXiv.org.
  • Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stephane Surprenant, 2020. "How is Machine Learning Useful for Macroeconomic Forecasting?," Working Papers 20-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Aug 2020.
• Klaus Ackermann & Alexey Chernikov & Nandini Anantharama & Miethy Zaman & Paul A Raschky, 2020. "Object Recognition for Economic Development from Daytime Satellite Imagery," SoDa Laboratories Working Paper Series 2020-02, Monash University, SoDa Laboratories.
  • Klaus Ackermann & Alexey Chernikov & Nandini Anantharama & Miethy Zaman & Paul A Raschky, 2020. "Object Recognition for Economic Development from Daytime Satellite Imagery," Papers 2009.05455, arXiv.org.
• Tae-Hwy Lee & Ekaterina Seregina, 2024. "Optimal Portfolio Using Factor Graphical Lasso," Journal of Financial Econometrics, Oxford University Press, vol. 22(3), pages 670-695.
  • Tae-Hwy Lee & Ekaterina Seregina, 2020. "Optimal Portfolio Using Factor Graphical Lasso," Working Papers 202025, University of California at Riverside, Department of Economics.
  • Tae-Hwy Lee & Ekaterina Seregina, 2023. "Optimal Portfolio Using Factor Graphical Lasso," Working Papers 202302, University of California at Riverside, Department of Economics.
  • Tae-Hwy Lee & Ekaterina Seregina, 2020. "Optimal Portfolio Using Factor Graphical Lasso," Papers 2011.00435, arXiv.org, revised Apr 2023.
• David Kohns & Arnab Bhattacharjee, 2020. "Nowcasting Growth using Google Trends Data: A Bayesian Structural Time Series Model," Papers 2011.00938, arXiv.org, revised May 2022.
  • Bhattacharjee, Arnab & Kohns, David, 2022. "Nowcasting Growth using Google Trends Data: A Bayesian Structural Time Series Model," National Institute of Economic and Social Research (NIESR) Discussion Papers 538, National Institute of Economic and Social Research.
• Tae-Hwy Lee & Ekaterina Seregina, 2020. "Learning from Forecast Errors: A New Approach to Forecast Combination," Working Papers 202024, University of California at Riverside, Department of Economics.
  • Tae-Hwy Lee & Ekaterina Seregina, 2020. "Learning from Forecast Errors: A New Approach to Forecast Combinations," Papers 2011.02077, arXiv.org, revised May 2021.
• Michael Allan Ribers & Hannes Ullrich, 2020. "Machine Predictions and Human Decisions with Variation in Payoffs and Skill," CESifo Working Paper Series 8702, CESifo.
  • Michael Allan Ribers & Hannes Ullrich, 2020. "Machine Predictions and Human Decisions with Variation in Payoffs and Skill," Papers 2011.11017, arXiv.org.
  • Michael Allan Ribers & Hannes Ullrich, 2020. "Machine Predictions and Human Decisions with Variation in Payoffs and Skills," Discussion Papers of DIW Berlin 1911, DIW Berlin, German Institute for Economic Research.
• Catalin DUMITRESCU, 2020. "Financial Stability Of Economic Agencies In Conditions Of Economic Crisis," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 57(1), pages 22-33, March.
• Cătălin DUMITRESCU & Matei DUMITRESCU, 2020. "Virtual Currency And Global Business - The New Trend In The Net-Economy," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 58(2), pages 22-32, June.
• Robert HELLVIG & Cătălin DUMITRESCU & Matei DUMITRESCU, 2020. "Management Of Cybercrime In The Financial Field - Perspectives To Combat The Phenomenon," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 59(3), pages 23-33, September.
• DănuÅ£-Octavian SIMION & Emilia VASILE, 2020. "Models Of Classes For Economic Objects In Applications," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 59(3), pages 9-22, September.
• Emilia VASILE & DănuÅ£-Octavian SIMION, 2020. "Polymorphism Of Classes And Reference Of Instances Distribution For Economic Objects In Applications," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 60(4), pages 9-21, December.
• Alexander Plum & Gail Pacheco & Kabir Dasgupta, 2021. "When There is No Way Up: Reconsidering Low‐paid Jobs as Stepping‐stones," The Economic Record, The Economic Society of Australia, vol. 97(318), pages 387-409, September.
  • Gail Pacheco & Alexander Plum, 2020. "When there is no way up: Reconsidering low-paid jobs as stepping stones," Working Papers 2020-08, Auckland University of Technology, Department of Economics.
• Cristina Caprara & Daniele Vergari, 2020. "Credit risk analysis and lending decisions: new Machine Learning techniques," BANCARIA, Bancaria Editrice, vol. 1, pages 49-53, January.
• Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2022. "How is machine learning useful for macroeconomic forecasting?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 920-964, August.
  • Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2019. "How is Machine Learning Useful for Macroeconomic Forecasting?," CIRANO Working Papers 2019s-22, CIRANO.
  • Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stephane Surprenant, 2020. "How is Machine Learning Useful for Macroeconomic Forecasting?," Working Papers 20-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Aug 2020.
  • Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & St'ephane Surprenant, 2020. "How is Machine Learning Useful for Macroeconomic Forecasting?," Papers 2008.12477, arXiv.org.
• Goulet Coulombe, Philippe & Leroux, Maxime & Stevanovic, Dalibor & Surprenant, Stéphane, 2021. "Macroeconomic data transformations matter," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1338-1354.
  • Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & St'ephane Surprenant, 2020. "Macroeconomic Data Transformations Matter," Papers 2008.01714, arXiv.org, revised Mar 2021.
  • Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stephane Surprenant, 2020. "Macroeconomic Data Transformations Matter," Working Papers 20-17, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Mar 2021.
  • Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2020. "Macroeconomic Data Transformations Matter," CIRANO Working Papers 2020s-42, CIRANO.
• Kevin Moran & Dalibor Stevanovic & Adam Kader Touré, 2022. "Macroeconomic uncertainty and the COVID‐19 pandemic: Measure and impacts on the Canadian economy," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 55(S1), pages 379-405, February.
  • Kevin Moran & Dalibor Stevanovic & Adam Abdel Kader Touré, 2020. "Macroeconomic Uncertainty and the COVID-19 Pandemic: Measure and Impacts on the Canadian Economy," CIRANO Working Papers 2020s-47, CIRANO.
  • Kevin Moran & Dalibor Stevanovic & Adam Kader Toure, 2020. "Macroeconomic Uncertainty and the COVID-19 Pandemic: Measure and Impacts on the Canadian Economy," Working Papers 20-18, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Dec 2020.
• Luis Antonio Espinosa & Juan José Li Ng, 2020. "El riesgo del sargazo para la economía y turismo de Quintana Roo y México [The risk of sargassum to the economy and tourism of Quintana Roo and Mexico]," Working Papers 20/02, BBVA Bank, Economic Research Department.
• Ali Batuhan Barlas & Seda Guler Mert & Alvaro Ortiz & Tomasa Rodrigo, 2020. "Global | Inversión en tiempo real y alta definición: Un enfoque Big Data [Global | Investment in Real Time and High Definition: A Big Data Approach]," Working Papers 20/13, BBVA Bank, Economic Research Department.
• Eddie Gerba & Danilo Leiva-Leon, 2020. "Macro-financial interactions in a changing world," Working Papers 2018, Banco de España.
• Nélida Díaz Sobrino & Corinna Ghirelli & Samuel Hurtado & Javier J. Pérez & Alberto Urtasun, 2020. "The narrative about the economy as a shadow forecast: an analysis using Banco de España quarterly reports," Working Papers 2042, Banco de España.
• Bradley Shapiro & Günter J. Hitsch & Anna Tuchman, 2020. "Generalizable and Robust TV Advertising Effects," Working Papers 2020-111, Becker Friedman Institute for Research In Economics.
• Caroline Jardet & Baptiste Meunier, 2022. "Nowcasting world GDP growth with high‐frequency data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1181-1200, September.
  • Jardet Caroline & Meunier Baptiste, 2020. "Nowcasting World GDP Growth with High-Frequency Data," Working papers 788, Banque de France.
  • Caroline Jardet & Baptiste Meunier, 2022. "Nowcasting world GDP growth with high‐frequency data," Post-Print hal-03647097, HAL.
• Faryna, Oleksandr & Pham, Tho & Talavera, Oleksandr & Tsapin, Andriy, 2020. "Wage Setting and Unemployment: Evidence from Online Job Vacancy Data," GLO Discussion Paper Series 503, Global Labor Organization (GLO).
  • Oleksandr Faryna & Tho Pham & Oleksandr Talavera & Andriy Tsapin, 2020. "Wage Setting and Unemployment: Evidence from Online Job Vacancy Data," Discussion Papers 20-03, Department of Economics, University of Birmingham.
  • Oleksandr Faryna & Tho Pham & Oleksandr Talavera & Andriy Tsapin, 2020. "Wage Setting and Unemployment: Evidence from Online Job Vacancy Data," Economics Discussion Papers em-dp2020-02, Department of Economics, University of Reading.
• Daniel Levy & Tamir Mayer & Alon Raviv, 2020. "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," Working Papers hal-02488796, HAL.
  • Daniel Levy & Tamir Mayer & Alon Raviv, 2020. "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," Working Papers 2020-01, Bar-Ilan University, Department of Economics.
  • Levy, Daniel & Mayer, Tamir & Raviv, Alon, 2020. "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," MPRA Paper 98785, University Library of Munich, Germany.
  • Daniel Levy & Tamir Mayer & Alon Raviv, 2020. "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," Working Paper series 20-05, Rimini Centre for Economic Analysis.
  • Levy, Daniel & Mayer, Tamir & Raviv, Alon, 2020. "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," EconStor Preprints 214194, ZBW - Leibniz Information Centre for Economics.
• Filipp Ulyankin, 2020. "Forecasting Russian Macroeconomic Indicators Based on Information from News and Search Queries," Russian Journal of Money and Finance, Bank of Russia, vol. 79(4), pages 75-97, December.
• Guanhao Feng & Stefano Giglio & Dacheng Xiu, 2020. "Taming the Factor Zoo: A Test of New Factors," Journal of Finance, American Finance Association, vol. 75(3), pages 1327-1370, June.
  • Guanhao Feng & Stefano Giglio & Dacheng Xiu, 2019. "Taming the Factor Zoo: A Test of New Factors," NBER Working Papers 25481, National Bureau of Economic Research, Inc.
  • Giglio, Stefano & Feng, Guanhao & Xiu, Dacheng, 2020. "Taming the Factor Zoo: A Test of New Factors," CEPR Discussion Papers 14266, C.E.P.R. Discussion Papers.
• Hilde C. Bj⊘rnland & Leif Anders Thorsrud & Sepideh Khayati Zahiri, 2020. "Do Central Banks Respond Timely to Developments in the Global Economy?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(2), pages 285-310, April.
  • Hilde C. Bjørnland & Leif Anders Thorsrud & Sepideh Khayati Zahiri, 2016. "Do central banks respond timely to developments in the global economy?," Working Paper 2016/19, Norges Bank.
  • Hilde C. Bjornland & Leif Anders Thorsrud & Sepideh Khayati Zahiri, 2017. "Do central banks respond timely to developments in the global economy?," CAMA Working Papers 2017-20, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Jaqueson K. Galimberti, 2020. "Forecasting GDP Growth from Outer Space," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(4), pages 697-722, August.
  • Jaqueson K Galimberti, 2017. "Forecasting GDP growth from the outer space," KOF Working papers 17-427, KOF Swiss Economic Institute, ETH Zurich.
  • Jaqueson K. Galimberti, 2020. "Forecasting GDP growth from outer space," Working Papers 2020-02, Auckland University of Technology, Department of Economics.
• Hanjo Odendaal & Monique Reid & Johann F. Kirsten, 2020. "Media‐Based Sentiment Indices as an Alternative Measure of Consumer Confidence," South African Journal of Economics, Economic Society of South Africa, vol. 88(4), pages 409-434, December.
  • Nicolaas Johannes Odendaal & Monique Reid, 2018. "Media based sentiment indices as an alternative measure of consumer confidence," Working Papers 17/2018, Stellenbosch University, Department of Economics.
• Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "News Media vs. FRED-MD for Macroeconomic Forecasting," CESifo Working Paper Series 8639, CESifo.
  • Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "News media vs. FRED-MD for macroeconomic forecasting," Working Paper 2020/14, Norges Bank.
• Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "News Media vs. FRED-MD for Macroeconomic Forecasting," CESifo Working Paper Series 8639, CESifo.
  • Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "News media vs. FRED-MD for macroeconomic forecasting," Working Papers No 08/2020, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "News media vs. FRED-MD for macroeconomic forecasting," Working Paper 2020/14, Norges Bank.
• Eleni Kalamara & Arthur Turrell & Chris Redl & George Kapetanios & Sujit Kapadia, 2022. "Making text count: Economic forecasting using newspaper text," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 896-919, August.
  • Kalamara, Eleni & Turrell, Arthur & Redl, Chris & Kapetanios, George & Kapadia, Sujit, 2020. "Making text count: economic forecasting using newspaper text," Bank of England working papers 865, Bank of England.
• Hyeongwoo Kim & Soohyon Kim, 2020. "Common Factor Augmented Forecasting Models for the US Dollar-Korean Won Exchange Rate," Working Papers 2020-5, Economic Research Institute, Bank of Korea.
• Andreas Gulyas & Krzysztof Pytka, 2019. "Understanding the Sources of Earnings Losses After Job Displacement: A Machine-Learning Approach," CRC TR 224 Discussion Paper Series crctr224_2019_131, University of Bonn and University of Mannheim, Germany.
  • Pytka, Krzysztof & Gulyas, Andreas, 2021. "Understanding the Sources of Earnings Losses After Job Displacement: A Machine-Learning Approach," VfS Annual Conference 2021 (Virtual Conference): Climate Economics 242402, Verein für Socialpolitik / German Economic Association.
  • Andreas Gulyas & Krzysztof Pytka, 2020. "Understanding the Sources of Earnings Losses After Job Displacement: A Machine-Learning Approach," CRC TR 224 Discussion Paper Series crctr224_2020_131v2, University of Bonn and University of Mannheim, Germany.
• Cristea, R. G., 2020. "Can Alternative Data Improve the Accuracy of Dynamic Factor Model Nowcasts?," Cambridge Working Papers in Economics 20108, Faculty of Economics, University of Cambridge.
• Rashad Ahmed & M. Hashem Pesaran, 2020. "Regional Heterogeneity and U.S. Presidential Elections," CESifo Working Paper Series 8615, CESifo.
  • Ahmed, R. & Pesaran, M. H., 2020. "Regional Heterogeneity and U.S. Presidential Elections," Cambridge Working Papers in Economics 2092, Faculty of Economics, University of Cambridge.
• Markus Heinrich & Magnus Reif, 2020. "Real-Time Forecasting Using Mixed-Frequency VARS with Time-Varying Parameters," CESifo Working Paper Series 8054, CESifo.
• Jonas Klos & Tim Krieger & Sven Stöwhase, 2022. "Measuring intra-generational redistribution in PAYG pension schemes," Public Choice, Springer, vol. 190(1), pages 53-73, January.
  • Klos, Jonas & Krieger, Tim & Stöwhase, Sven, 2020. "Measuring intra-generational redistribution in PAYG pension schemes," Discussion Paper Series 2020-01, University of Freiburg, Wilfried Guth Endowed Chair for Constitutional Political Economy and Competition Policy.
  • Jonas Klos & Tim Krieger & Sven Stöwhase, 2020. "Measuring Intra-Generational Redistribution in PAYG Pension Schemes," CESifo Working Paper Series 8200, CESifo.
• Alexander Chudik & M. Hashem Pesaran & Mahrad Sharifvaghefi, 2020. "Variable Selection and Forecasting in High Dimensional Linear Regressions with Structural Breaks," CESifo Working Paper Series 8475, CESifo.
• Ahmed, R. & Pesaran, M. H., 2020. "Regional Heterogeneity and U.S. Presidential Elections," Cambridge Working Papers in Economics 2092, Faculty of Economics, University of Cambridge.
  • Rashad Ahmed & M. Hashem Pesaran, 2020. "Regional Heterogeneity and U.S. Presidential Elections," CESifo Working Paper Series 8615, CESifo.
• Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "News media vs. FRED-MD for macroeconomic forecasting," Working Paper 2020/14, Norges Bank.
  • Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "News Media vs. FRED-MD for Macroeconomic Forecasting," CESifo Working Paper Series 8639, CESifo.
  • Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "News media vs. FRED-MD for macroeconomic forecasting," Working Papers No 08/2020, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
• Michael Allan Ribers & Hannes Ullrich, 2020. "Machine Predictions and Human Decisions with Variation in Payoffs and Skill," Papers 2011.11017, arXiv.org.
  • Michael Allan Ribers & Hannes Ullrich, 2020. "Machine Predictions and Human Decisions with Variation in Payoffs and Skill," CESifo Working Paper Series 8702, CESifo.
  • Michael Allan Ribers & Hannes Ullrich, 2020. "Machine Predictions and Human Decisions with Variation in Payoffs and Skills," Discussion Papers of DIW Berlin 1911, DIW Berlin, German Institute for Economic Research.
• Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87.
• Roberto Molinari & Gaetan Bakalli & Stéphane Guerrier & Cesare Miglioli & Samuel Orso & O. Scaillet, 2020. "Swag: A Wrapper Method for Sparse Learning," Swiss Finance Institute Research Paper Series 20-49, Swiss Finance Institute.
• Ardia, David & Barras, Laurent & Gagliardini, Patrick & Scaillet, Olivier, 2024. "Is it alpha or beta? Decomposing hedge fund returns when models are misspecified," Journal of Financial Economics, Elsevier, vol. 154(C).
  • David Ardia & Laurent Barras & Patrick Gagliardini & Olivier Scaillet, 2020. "Is it Alpha or Beta? Decomposing Hedge Fund Returns When Models are Misspecified," Swiss Finance Institute Research Paper Series 20-82, Swiss Finance Institute, revised May 2023.
• Goulet Coulombe, Philippe & Leroux, Maxime & Stevanovic, Dalibor & Surprenant, Stéphane, 2021. "Macroeconomic data transformations matter," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1338-1354.
  • Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stephane Surprenant, 2020. "Macroeconomic Data Transformations Matter," Working Papers 20-17, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Mar 2021.
  • Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2020. "Macroeconomic Data Transformations Matter," CIRANO Working Papers 2020s-42, CIRANO.
  • Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & St'ephane Surprenant, 2020. "Macroeconomic Data Transformations Matter," Papers 2008.01714, arXiv.org, revised Mar 2021.
• Kevin Moran & Dalibor Stevanovic & Adam Kader Touré, 2022. "Macroeconomic uncertainty and the COVID‐19 pandemic: Measure and impacts on the Canadian economy," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 55(S1), pages 379-405, February.
  • Kevin Moran & Dalibor Stevanovic & Adam Kader Toure, 2020. "Macroeconomic Uncertainty and the COVID-19 Pandemic: Measure and Impacts on the Canadian Economy," Working Papers 20-18, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Dec 2020.
  • Kevin Moran & Dalibor Stevanovic & Adam Abdel Kader Touré, 2020. "Macroeconomic Uncertainty and the COVID-19 Pandemic: Measure and Impacts on the Canadian Economy," CIRANO Working Papers 2020s-47, CIRANO.
• Guanhao Feng & Stefano Giglio & Dacheng Xiu, 2020. "Taming the Factor Zoo: A Test of New Factors," Journal of Finance, American Finance Association, vol. 75(3), pages 1327-1370, June.
  • Guanhao Feng & Stefano Giglio & Dacheng Xiu, 2019. "Taming the Factor Zoo: A Test of New Factors," NBER Working Papers 25481, National Bureau of Economic Research, Inc.
  • Giglio, Stefano & Feng, Guanhao & Xiu, Dacheng, 2020. "Taming the Factor Zoo: A Test of New Factors," CEPR Discussion Papers 14266, C.E.P.R. Discussion Papers.
• Mark Trede & Michael Zimmermann, 2020. "Regional labour migration - Stylized facts for Germany," CQE Working Papers 9320, Center for Quantitative Economics (CQE), University of Muenster.
• Franchi, Massimo & Paruolo, Paolo, 2020. "Cointegration In Functional Autoregressive Processes," Econometric Theory, Cambridge University Press, vol. 36(5), pages 803-839, October.
  • Massimo Franchi & Paolo Paruolo, 2017. "Cointegration in functional autoregressive processes," Papers 1712.07522, arXiv.org, revised Oct 2018.
  • Massimo Franchi & Paolo Paruolo, 2017. "Cointegration in functional autoregressive processes," DSS Empirical Economics and Econometrics Working Papers Series 2017/5, Centre for Empirical Economics and Econometrics, Department of Statistics, "Sapienza" University of Rome.
• Antonia Grohmann & Steffen Herbold & Friederike Lenel, 2020. "Repayment under Flexible Loan Contracts: Evidence from Tanzania," Discussion Papers of DIW Berlin 1884, DIW Berlin, German Institute for Economic Research.
• Michael Allan Ribers & Hannes Ullrich, 2020. "Machine Predictions and Human Decisions with Variation in Payoffs and Skill," CESifo Working Paper Series 8702, CESifo.
  • Michael Allan Ribers & Hannes Ullrich, 2020. "Machine Predictions and Human Decisions with Variation in Payoffs and Skills," Discussion Papers of DIW Berlin 1911, DIW Berlin, German Institute for Economic Research.
  • Michael Allan Ribers & Hannes Ullrich, 2020. "Machine Predictions and Human Decisions with Variation in Payoffs and Skill," Papers 2011.11017, arXiv.org.
• Laurent Ferrara & Anna Simoni, 2023. "When are Google Data Useful to Nowcast GDP? An Approach via Preselection and Shrinkage," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(4), pages 1188-1202, October.
  • Laurent Ferrara & Anna Simoni, 2019. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working Papers 2019-04, Center for Research in Economics and Statistics.
  • Laurent Ferrara & Anna Simoni, 2023. "When are Google Data Useful to Nowcast GDP? An Approach via Preselection and Shrinkage," Post-Print hal-03919944, HAL.
  • Laurent Ferrara & Anna Simoni, 2020. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," EconomiX Working Papers 2020-11, University of Paris Nanterre, EconomiX.
  • Laurent Ferrara & Anna Simoni, 2019. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working papers 717, Banque de France.
  • Laurent Ferrara & Anna Simoni, 2020. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Papers 2007.00273, arXiv.org, revised Sep 2022.
  • Laurent Ferrara & Anna Simoni, 2020. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working Papers hal-04159714, HAL.
• Hansen, Stephen & McMahon, Michael & Tong, Matthew, 2019. "The long-run information effect of central bank communication," Journal of Monetary Economics, Elsevier, vol. 108(C), pages 185-202.
  • McMahon, Michael & , & Tong, Matthew, 2019. "The Long-Run Information Effect of Central Bank Communication," CEPR Discussion Papers 13438, C.E.P.R. Discussion Papers.
  • Hansen, Stephen & McMahon, Michael & Tong, Matthew, 2020. "The long-run information effect of central bank communication," Working Paper Series 2363, European Central Bank.
  • Hansen, Stephen & McMahon, Michael & Tong, Matthew, 2019. "The long-run information effect of central bank communication," Bank of England working papers 777, Bank of England.
• Arrigoni, Simone & Bobasu, Alina & Venditti, Fabrizio, 2020. "The simpler the better: measuring financial conditions for monetary policy and financial stability," Working Paper Series 2451, European Central Bank.
  • Arrigoni, Simone & Bobasu, Alina & Venditti, Fabrizio, 2021. "The simpler, the better: Measuring financial conditions for monetary policy and financial stability," EIB Working Papers 2021/10, European Investment Bank (EIB).
• Massimo Ferrari Minesso & Frederik Kurcz & Maria Sole Pagliari, 2022. "Do words hurt more than actions? The impact of trade tensions on financial markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(6), pages 1138-1159, September.
  • Ferrari Minesso, Massimo & Pagliari, Maria Sole & Kurcz, Frederik, 2020. "Do words hurt more than actions? The impact of trade tensions on financial markets," Working Paper Series 2490, European Central Bank.
  • Massimo Ferrari & Frederik Kurcz & Maria Sole Pagliari, 2021. "Do Words Hurt More Than Actions? The Impact of Trade Tensions on Financial Markets," Working papers 802, Banque de France.
• Schönheit, David & Weinhold, Richard & Dierstein, Constantin, 2020. "The impact of different strategies for generation shift keys (GSKs) on the flow-based market coupling domain: A model-based analysis of Central Western Europe," Applied Energy, Elsevier, vol. 258(C).
• Milusheva, Sveta, 2020. "Managing the spread of disease with mobile phone data," Journal of Development Economics, Elsevier, vol. 147(C).
• Schnaubelt, Matthias & Fischer, Thomas G. & Krauss, Christopher, 2020. "Separating the signal from the noise – Financial machine learning for Twitter," Journal of Economic Dynamics and Control, Elsevier, vol. 114(C).
• Pham, Manh Cuong & Anderson, Heather Margot & Duong, Huu Nhan & Lajbcygier, Paul, 2020. "The effects of trade size and market depth on immediate price impact in a limit order book market," Journal of Economic Dynamics and Control, Elsevier, vol. 120(C).
• Kim, Hyeongwoo & Ko, Kyunghwan, 2020. "Improving forecast accuracy of financial vulnerability: PLS factor model approach," Economic Modelling, Elsevier, vol. 88(C), pages 341-355.
  • Hyeongwoo Kim & Kyunghwan Ko, 2017. "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," Auburn Economics Working Paper Series auwp2017-03, Department of Economics, Auburn University.
  • Hyeongwoo Kim & Kyunghwan Ko, 2019. "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," Auburn Economics Working Paper Series auwp2019-03, Department of Economics, Auburn University.
  • Kim, Hyeongwoo & Ko, Kyunghwan, 2018. "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," MPRA Paper 89449, University Library of Munich, Germany.
• Arata, Linda & Fabrizi, Enrico & Sckokai, Paolo, 2020. "A worldwide analysis of trend in crop yields and yield variability: Evidence from FAO data," Economic Modelling, Elsevier, vol. 90(C), pages 190-208.
• Álvarez de Toledo, Pablo & Núñez, Fernando & Usabiaga, Carlos, 2020. "Matching in segmented labor markets: An analytical proposal based on high-dimensional contingency tables," Economic Modelling, Elsevier, vol. 93(C), pages 175-186.
• Claveria, Oscar & Monte, Enric & Torra, Salvador, 2020. "Economic forecasting with evolved confidence indicators," Economic Modelling, Elsevier, vol. 93(C), pages 576-585.
• Sant’Anna, Leonardo Riegel & Caldeira, João Frois & Filomena, Tiago Pascoal, 2020. "Lasso-based index tracking and statistical arbitrage long-short strategies," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
• Gupta, Rangan & Sun, Xiaojin, 2020. "Forecasting economic policy uncertainty of BRIC countries using Bayesian VARs," Economics Letters, Elsevier, vol. 186(C).
• Wei, Jie & Chen, Hui, 2020. "Determining the number of factors in approximate factor models by twice K-fold cross validation," Economics Letters, Elsevier, vol. 191(C).
• Wei, Jie & Zhang, Yonghui, 2020. "A time-varying diffusion index forecasting model," Economics Letters, Elsevier, vol. 193(C).
• Fan, Yanqin & Han, Fang & Li, Wei & Zhou, Xiao-Hua, 2020. "On rank estimators in increasing dimensions," Journal of Econometrics, Elsevier, vol. 214(2), pages 379-412.
• Cai, T. Tony & Hu, Jianchang & Li, Yingying & Zheng, Xinghua, 2020. "High-dimensional minimum variance portfolio estimation based on high-frequency data," Journal of Econometrics, Elsevier, vol. 214(2), pages 482-494.
• Li, Z. Merrick & Laeven, Roger J.A. & Vellekoop, Michel H., 2020. "Dependent microstructure noise and integrated volatility estimation from high-frequency data," Journal of Econometrics, Elsevier, vol. 215(2), pages 536-558.
  • Li, Z. M. & Laeven, R. J. A. & Vellekoop, M. H., 2019. "Dependent Microstructure Noise and Integrated Volatility: Estimation from High-Frequency Data," Cambridge Working Papers in Economics 1952, Faculty of Economics, University of Cambridge.
• Zhu, Xuening & Huang, Danyang & Pan, Rui & Wang, Hansheng, 2020. "Multivariate spatial autoregressive model for large scale social networks," Journal of Econometrics, Elsevier, vol. 215(2), pages 591-606.
• Huang, Danyang & Wang, Feifei & Zhu, Xuening & Wang, Hansheng, 2020. "Two-mode network autoregressive model for large-scale networks," Journal of Econometrics, Elsevier, vol. 216(1), pages 203-219.
• Chan, N.H. & Cheung, Simon K.C. & Wong, Samuel P.S., 2020. "Inference for the degree distributions of preferential attachment networks with zero-degree nodes," Journal of Econometrics, Elsevier, vol. 216(1), pages 220-234.
• Vogt, Michael & Linton, Oliver, 2020. "Multiscale clustering of nonparametric regression curves," Journal of Econometrics, Elsevier, vol. 216(1), pages 305-325.
  • Michael Vogt & Oliver Linton, 2018. "Multiscale clustering of nonparametric regression curves," CeMMAP working papers CWP08/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
• Aït-Sahalia, Yacine & Kalnina, Ilze & Xiu, Dacheng, 2020. "High-frequency factor models and regressions," Journal of Econometrics, Elsevier, vol. 216(1), pages 86-105.
• Hafner, Christian M. & Linton, Oliver B. & Tang, Haihan, 2020. "Estimation of a multiplicative correlation structure in the large dimensional case," Journal of Econometrics, Elsevier, vol. 217(2), pages 431-470.
  • Hafner, C. & Linton, O. & Tang, H., 2018. "Estimation of a Multiplicative Correlation Structure in the Large Dimensional Case," Cambridge Working Papers in Economics 1878, Faculty of Economics, University of Cambridge.
  • Hafner, Christian & Linton, Oliver & Tang, Haihan, 2020. "Estimation of a multiplicative correlation structure in the large dimensional case," LIDAM Reprints ISBA 2020028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
• Galbraith, John W. & Zinde-Walsh, Victoria, 2020. "Simple and reliable estimators of coefficients of interest in a model with high-dimensional confounding effects," Journal of Econometrics, Elsevier, vol. 218(2), pages 609-632.
• Breunig, Christoph & Mammen, Enno & Simoni, Anna, 2020. "Ill-posed estimation in high-dimensional models with instrumental variables," Journal of Econometrics, Elsevier, vol. 219(1), pages 171-200.
  • Christoph Breunig & Enno Mammen & Anna Simoni, 2018. "Ill-posed Estimation in High-Dimensional Models with Instrumental Variables," Papers 1806.00666, arXiv.org, revised Aug 2020.
  • Christoph Breunig & Enno Mammen & Anna Simoni, 2020. "Ill-posed estimation in high-dimensional models with instrumental variables," Post-Print hal-03089879, HAL.
• Nevrla, Matěj, 2020. "Systemic risk in European financial and energy sectors: Dynamic factor copula approach," Economic Systems, Elsevier, vol. 44(4).
• Reschenhofer, Erhard & Mangat, Manveer Kaur & Stark, Thomas, 2020. "Volatility forecasts, proxies and loss functions," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 133-153.
• Cepni, Oguzhan & Gul, Selcuk & Gupta, Rangan, 2020. "Local currency bond risk premia of emerging markets: The role of local and global factors," Finance Research Letters, Elsevier, vol. 33(C).
  • Oguzhan Cepni & Selcuk Gul & Rangan Gupta, 2019. "Local Currency Bond Risk Premia of Emerging Markets: The Role of Local and Global Factors," Working Papers 201901, University of Pretoria, Department of Economics.
• Batagelj, Vladimir & Maltseva, Daria, 2020. "Temporal bibliographic networks," Journal of Informetrics, Elsevier, vol. 14(1).
• Hüttner, Amelie & Scherer, Matthias & Gräler, Benedikt, 2020. "Geostatistical modeling of dependent credit spreads: Estimation of large covariance matrices and imputation of missing data," Journal of Banking & Finance, Elsevier, vol. 118(C).
• DePaula, Guilherme, 2020. "The distributional effect of climate change on agriculture: Evidence from a Ricardian quantile analysis of Brazilian census data," Journal of Environmental Economics and Management, Elsevier, vol. 104(C).
• Kala, Kaveri & Bolia, Nomesh B. & Sushil,, 2020. "Waste management communication policy for effective citizen awareness," Journal of Policy Modeling, Elsevier, vol. 42(3), pages 661-678.
• Samaratunge, Ramanie & Kumara, Ajantha Sisira & Abeysekera, Lakmal, 2020. "Breaking the Perverse Health-debt Cycle in Sri Lanka: Policy Options," Journal of Policy Modeling, Elsevier, vol. 42(3), pages 728-745.
• Indaco, Agustín, 2020. "From twitter to GDP: Estimating economic activity from social media," Regional Science and Urban Economics, Elsevier, vol. 85(C).
  • Indaco, Agustín, 2019. "From Twitter to GDP: Estimating Economic Activity From Social Media," MPRA Paper 95885, University Library of Munich, Germany.
• Chen, Wang & Ma, Feng & Wei, Yu & Liu, Jing, 2020. "Forecasting oil price volatility using high-frequency data: New evidence," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 1-12.
• Chan, Joshua C.C. & Yu, Xuewen, 2022. "Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
  • Joshua C.C. Chan & Xuewen Yu, 2020. "Fast and accurate variational inference for large Bayesian VARs with stochastic volatility," CAMA Working Papers 2020-108, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Joshua C. C. Chan & Xuewen Yu, 2022. "Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility," Papers 2206.08438, arXiv.org.
• Berger, Tino & Morley, James & Wong, Benjamin, 2023. "Nowcasting the output gap," Journal of Econometrics, Elsevier, vol. 232(1), pages 18-34.
  • Tino Berger & James Morley & Benjamin Wong, 2020. "Nowcasting the output gap," CAMA Working Papers 2020-78, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Bo Zhang & Bao H. Nguyen, 2020. "Real-time forecasting of the Australian macroeconomy using flexible Bayesian VARs," CAMA Working Papers 2020-91, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Yan Li & Lian Luo & Chao Liang & Feng Ma, 2020. "The role of model bias in predicting volatility: evidence from the US equity markets," China Finance Review International, Emerald Group Publishing Limited, vol. 13(1), pages 140-155, October.
• Yan Li & Lian Luo & Chao Liang & Feng Ma, 2020. "The role of model bias in predicting volatility: evidence from the US equity markets," China Finance Review International, Emerald Group Publishing Limited, vol. 13(1), pages 140-155, October.
• Nguyen Khanh Doanh & Linh Tuan Truong & Yoon Heo, 2020. "Impact of institutional and cultural distances on ASEAN's trade efficiency," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 49(1), pages 77-94, December.
• Luisa Mendonça & Alan De Genaro, 2020. "Detection and analysis of occurrences of spoofing in the Brazilian capital market," Journal of Financial Regulation and Compliance, Emerald Group Publishing Limited, vol. 28(3), pages 369-408, March.
• Baris Yalin Uzunlu & Syed Muzammil Hussain, 2020. "Employing Machine Learning Algorithms to build Trading Strategies with higher than Risk-Free Returns," International Econometric Review (IER), Econometric Research Association, vol. 12(2), pages 112-138, September.
• Barbora Malinska, 2020. "Time-Varying Pricing of Risk in Sovereign Bond Futures Returns," Working Papers IES 2020/7, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Mar 2020.
• Chiara Castelli & Angela Parenti, 2020. "Commuting in Europe: An Inter-regional Analysis on its Determinants and Spatial Effects," Working Papers 2020.19, Fondazione Eni Enrico Mattei.
• Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2020. "Measuring Uncertainty and Its Effects in the COVID-19 Era," Working Papers 20-32R, Federal Reserve Bank of Cleveland, revised 05 Jan 2022.
  • Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd & Mertens, Elmar, 2021. "Measuring Uncertainty and Its Effects in the COVID-19 Era," CEPR Discussion Papers 15965, C.E.P.R. Discussion Papers.
• Alexander Chudik & M. Hashem Pesaran & Mahrad Sharifvaghefi, 2020. "Variable Selection in High Dimensional Linear Regressions with Parameter Instability," Globalization Institute Working Papers 394, Federal Reserve Bank of Dallas, revised 05 Aug 2024.
  • Alexander Chudik & M. Hashem Pesaran & Mahrad Sharifvaghefi, 2023. "Variable Selection in High Dimensional Linear Regressions with Parameter Instability," Papers 2312.15494, arXiv.org, revised Jul 2024.
  • Alexander Chudik & M. Hashem Pesaran & Mahrad Sharifvaghefi, 2023. "Variable Selection in High Dimensional Linear Regressions with Parameter Instability," CESifo Working Paper Series 10223, CESifo.
• Matteo Luciani, 2020. "Common and Idiosyncratic Inflation," FEDS Notes 2020-03-05, Board of Governors of the Federal Reserve System (U.S.).
  • Matteo Luciani, 2020. "Common and Idiosyncratic Inflation," Finance and Economics Discussion Series 2020-024, Board of Governors of the Federal Reserve System (U.S.).
• Tomaz Cajner & Leland D. Crane & Ryan A. Decker & Adrian Hamins-Puertolas & Christopher J. Kurz, 2020. "Tracking Labor Market Developments during the COVID-19 Pandemic: A Preliminary Assessment," Finance and Economics Discussion Series 2020-030, Board of Governors of the Federal Reserve System (U.S.).
• Crane, Leland D. & Decker, Ryan A. & Flaaen, Aaron & Hamins-Puertolas, Adrian & Kurz, Christopher, 2022. "Business exit during the COVID-19 pandemic: Non-traditional measures in historical context," Journal of Macroeconomics, Elsevier, vol. 72(C).
  • Leland D. Crane & Ryan A. Decker & Aaron Flaaen & Adrian Hamins-Puertolas & Christopher J. Kurz, 2020. "Business Exit During the COVID-19 Pandemic: Non-Traditional Measures in Historical Context," Finance and Economics Discussion Series 2020-089r1, Board of Governors of the Federal Reserve System (U.S.), revised 15 Apr 2021.
• Michael T. Kiley, 2020. "Financial Conditions and Economic Activity: Insights from Machine Learning," Finance and Economics Discussion Series 2020-095, Board of Governors of the Federal Reserve System (U.S.).
• Matteo Luciani, 2020. "Common and Idiosyncratic Inflation," Finance and Economics Discussion Series 2020-024, Board of Governors of the Federal Reserve System (U.S.).
  • Matteo Luciani, 2020. "Common and Idiosyncratic Inflation," FEDS Notes 2020-03-05, Board of Governors of the Federal Reserve System (U.S.).
• Feras A. Batarseh & Munisamy Gopinath & Anderson Monken, 2020. "Artificial Intelligence Methods for Evaluating Global Trade Flows," International Finance Discussion Papers 1296, Board of Governors of the Federal Reserve System (U.S.).
• Scott A. Brave & R. Andrew Butters & Michael Fogarty, 2020. "The perils of working with Big Data and a SMALL framework you can use to avoid them," Working Paper Series WP-2020-35, Federal Reserve Bank of Chicago, revised 02 Mar 2020.
• Lyu, Yifei & Nie, Jun & Yang, Shu-Kuei X., 2021. "Forecasting US economic growth in downturns using cross-country data," Economics Letters, Elsevier, vol. 198(C).
  • , 2020. "Forecasting U.S. Economic Growth in Downturns Using Cross-Country Data," Research Working Paper RWP 20-09, Federal Reserve Bank of Kansas City.
• Jan J. J. Groen & Michael Nattinger, 2020. "Alternative Indicators for Chinese Economic Activity Using Sparse PLS Regression," Economic Policy Review, Federal Reserve Bank of New York, vol. 26(4), pages 39-68, October.
• Dean Croushore & Stephanie M. Wilshusen, 2020. "Forecasting Consumption Spending Using Credit Bureau Data," Working Papers 20-22, Federal Reserve Bank of Philadelphia.
• Simon Freyaldenhoven, 2020. "Identification Through Sparsity in Factor Models," Working Papers 20-25, Federal Reserve Bank of Philadelphia.
• Leonardo BARGIGLI & Giulio CIFARELLI, 2020. "Structural Interdependence of Price and Demand in a Model of the Foreign Exchange Market with Heterogeneous Speculators: Evidence from High-frequency Data," Working Papers - Economics wp2020_04.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
• Leonardo Bargigli & Giulio Cifarelli, 2020. "Endogenous and Exogenous Volatility in the Foreign Exchange Market," Working Papers - Economics wp2020_17.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
• Breunig, Christoph & Mammen, Enno & Simoni, Anna, 2020. "Ill-posed estimation in high-dimensional models with instrumental variables," Journal of Econometrics, Elsevier, vol. 219(1), pages 171-200.
  • Christoph Breunig & Enno Mammen & Anna Simoni, 2018. "Ill-posed Estimation in High-Dimensional Models with Instrumental Variables," Papers 1806.00666, arXiv.org, revised Aug 2020.
  • Christoph Breunig & Enno Mammen & Anna Simoni, 2020. "Ill-posed estimation in high-dimensional models with instrumental variables," Post-Print hal-03089879, HAL.
• Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers 2019-4, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.
  • Catherine Doz & Peter Fuleky, 2020. "Dynamic Factor Models," Post-Print halshs-02491811, HAL.
  • Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," PSE Working Papers halshs-02262202, HAL.
  • Catherine Doz & Peter Fuleky, 2020. "Dynamic Factor Models," PSE-Ecole d'économie de Paris (Postprint) halshs-02491811, HAL.
  • Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers halshs-02262202, HAL.
• Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers 2019-4, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.
  • Catherine Doz & Peter Fuleky, 2020. "Dynamic Factor Models," PSE-Ecole d'économie de Paris (Postprint) halshs-02491811, HAL.
  • Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," PSE Working Papers halshs-02262202, HAL.
  • Catherine Doz & Peter Fuleky, 2020. "Dynamic Factor Models," Post-Print halshs-02491811, HAL.
  • Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers halshs-02262202, HAL.
• Daniel Levy & Tamir Mayer & Alon Raviv, 2020. "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," Working Papers 2020-01, Bar-Ilan University, Department of Economics.
  • Daniel Levy & Tamir Mayer & Alon Raviv, 2020. "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," Working Papers hal-02488796, HAL.
  • Daniel Levy & Tamir Mayer & Alon Raviv, 2020. "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," Working Paper series 20-05, Rimini Centre for Economic Analysis.
  • Levy, Daniel & Mayer, Tamir & Raviv, Alon, 2020. "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," EconStor Preprints 214194, ZBW - Leibniz Information Centre for Economics.
  • Levy, Daniel & Mayer, Tamir & Raviv, Alon, 2020. "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," MPRA Paper 98785, University Library of Munich, Germany.
• Laurent Ferrara & Anna Simoni, 2023. "When are Google Data Useful to Nowcast GDP? An Approach via Preselection and Shrinkage," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(4), pages 1188-1202, October.
  • Laurent Ferrara & Anna Simoni, 2019. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working Papers 2019-04, Center for Research in Economics and Statistics.
  • Laurent Ferrara & Anna Simoni, 2023. "When are Google Data Useful to Nowcast GDP? An Approach via Preselection and Shrinkage," Post-Print hal-03919944, HAL.
  • Laurent Ferrara & Anna Simoni, 2020. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working Papers hal-04159714, HAL.
  • Laurent Ferrara & Anna Simoni, 2019. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working papers 717, Banque de France.
  • Laurent Ferrara & Anna Simoni, 2020. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Papers 2007.00273, arXiv.org, revised Sep 2022.
  • Laurent Ferrara & Anna Simoni, 2020. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," EconomiX Working Papers 2020-11, University of Paris Nanterre, EconomiX.
• Olivier Cabrignac & Arthur Charpentier & Ewen Gallic, 2020. "Modeling Joint Lives within Families," AMSE Working Papers 2021, Aix-Marseille School of Economics, France.
  • Olivier Cabrignac & Arthur Charpentier & Ewen Gallic, 2020. "Modeling Joint Lives within Families," Working Papers halshs-02871927, HAL.
  • Olivier Cabrignac & Arthur Charpentier & Ewen Gallic, 2020. "Modeling Joint Lives within Families," Papers 2006.08446, arXiv.org.
• Diaf, Sami & Döpke, Jörg & Fritsche, Ulrich & Rockenbach, Ida, 2020. "Sharks and minnows in a shoal of words: Measuring latent ideological positions of German economic research institutes based on text mining techniques," Working Papers 24, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
  • Sami Diaf & Jörg Döpke & Ulrich Fritsche & Ida Rockenbach, 2020. "Sharks and minnows in a shoal of words: Measuring latent ideological positions of German economic research institutes based on text mining techniques," Macroeconomics and Finance Series 202001, University of Hamburg, Department of Socioeconomics.
• von Essen, Emma & Jansson, Joakim, 2020. "Misogynistic and xenophobic hate language online: a matter of anonymity," Working Paper Series 7/2020, Stockholm University, Swedish Institute for Social Research.
  • von Essen, Emma & Jansson, Joakim, 2020. "Misogynistic and Xenophobic Hate Language Online: A Matter of Anonymity," Working Paper Series 1350, Research Institute of Industrial Economics.
• Alfelt, Gustav & Bodnar, Taras & Javed, Farrukh & Tyrcha, Joanna, 2020. "Singular conditional autoregressive Wishart model for realized covariance matrices," Working Papers 2021:1, Örebro University, School of Business.
• von Essen, Emma & Jansson, Joakim, 2020. "Misogynistic and Xenophobic Hate Language Online: A Matter of Anonymity," Working Paper Series 1350, Research Institute of Industrial Economics.
  • von Essen, Emma & Jansson, Joakim, 2020. "Misogynistic and xenophobic hate language online: a matter of anonymity," Working Paper Series 7/2020, Stockholm University, Swedish Institute for Social Research.
• Dauth, Wolfgang & Eppelsheimer, Johann, 2020. "Preparing the sample of integrated labour market biographies (SIAB) for scientific analysis," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 54(1), pages 1-10.
• Dauth, Wolfgang & Eppelsheimer, Johann, 2020. "Preparing the sample of integrated labour market biographies (SIAB) for scientific analysis," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 54(1), pages .10(1-10).
• Dauth, Wolfgang & Eppelsheimer, Johann, 2020. "Preparing the sample of integrated labour market biographies (SIAB) for scientific analysis," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 54(1), pages 1-10.
• Falco J. Bargagli-Dtoffi & Massimo Riccaboni & Armando Rungi, 2020. "Machine Learning for Zombie Hunting. Firms Failures and Financial Constraints," Working Papers 01/2020, IMT School for Advanced Studies Lucca, revised Jun 2020.
• Daisuke Miyakawa & Kohei Shintani, 2020. "Disagreement between Human and Machine Predictions," IMES Discussion Paper Series 20-E-11, Institute for Monetary and Economic Studies, Bank of Japan.
• Saha, Shree & Narayanan, Sudha, 2022. "A simplified measure of nutritional empowerment: Using machine learning to abbreviate the Women’s Empowerment in Nutrition Index (WENI)," World Development, Elsevier, vol. 154(C).
  • Shree Saha & Sudha Narayanan, 2020. "A Simplified measure of nutritional empowerment using machine learning to abbreviate the Women's Empowerment in Nutrition Index (WENI)," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2020-031, Indira Gandhi Institute of Development Research, Mumbai, India.
• Oscar Claveria & Ivana Lolic & Enric Monte & Salvador Torra & Petar Soric, 2020. "“Economic determinants of employment sentiment: A socio-demographic analysis for the euro area”," AQR Working Papers 2012001, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2020.
  • Oscar Claveria & Ivana Lolic & Enric Monte & Petar Soric, 2020. "Economic determinants of employment sentiment: A socio-demographic analysis for the euro area," IREA Working Papers 202001, University of Barcelona, Research Institute of Applied Economics, revised Jan 2020.
• Pacheco, Gail & Plum, Alexander T. & Sloane, Peter J., 2020. "Not Much Bounce in the Springboard: On the Mobility of Low Pay Workers," IZA Discussion Papers 12896, Institute of Labor Economics (IZA).
• Nicodemo, Catia & Satorra, Albert, 2020. "Exploratory Data Analysis on Large Data Sets: The Example of Salary Variation in Spanish Social Security Data," IZA Discussion Papers 13459, Institute of Labor Economics (IZA).
• Biewen, Martin & Kugler, Philipp, 2021. "Two-stage least squares random forests with an application to Angrist and Evans (1998)," Economics Letters, Elsevier, vol. 204(C).
  • Biewen, Martin & Kugler, Philipp, 2020. "Two-Stage Least Squares Random Forests with an Application to Angrist and Evans (1998)," IZA Discussion Papers 13613, Institute of Labor Economics (IZA).
• Kailing Shen & Bledi Taska, 2020. "Measuring the impacts of COVID-19 on job postings in Australia using a reweighting-estimation-transformation approach," Australian Journal of Labour Economics (AJLE), Bankwest Curtin Economics Centre (BCEC), Curtin Business School, vol. 23(2), pages 153-171.
  • Shen, Kailing & Taska, Bledi, 2020. "Measuring the Impacts of COVID-19 on Job Postings in Australia Using a Reweighting-Estimation-Transformation Approach," IZA Discussion Papers 13640, Institute of Labor Economics (IZA).
• Nicodemo, Catia & Barzin, Samira & Lasserson, Daniel S. & Moscone, Francesco & Redding, Stuart & Shaikh, Mujaheed & Cavalli, Nicolò, 2020. "Measuring Geographical Disparities in England at the Time of COVID-19: Results Using a Composite Indicator of Population Vulnerability," IZA Discussion Papers 13757, Institute of Labor Economics (IZA).
• Philip Hans Franses & Thomas Wiemann, 2020. "Intertemporal Similarity of Economic Time Series: An Application of Dynamic Time Warping," Computational Economics, Springer;Society for Computational Economics, vol. 56(1), pages 59-75, June.
• Rezwanul Hasan Rana & Khorshed Alam & Jeff Gow, 2020. "Health expenditure and gross domestic product: causality analysis by income level," International Journal of Health Economics and Management, Springer, vol. 20(1), pages 55-77, March.
• Lu Jinks & Thomas J. Kniesner & John Leeth & Anthony T. Lo Sasso, 2020. "Opting out of workers’ compensation: Non-subscription in Texas and its effects," Journal of Risk and Uncertainty, Springer, vol. 60(1), pages 53-76, February.
  • Jinks, Lu & Kniesner, Thomas J. & Leeth, John D. & Lo Sasso, Anthony T., 2019. "Opting out of Workers' Compensation: Non-Subscription in Texas and Its Effects," IZA Discussion Papers 12290, Institute of Labor Economics (IZA).
• Martin Obschonka & Neil Lee & Andrés Rodríguez-Pose & Johannes C. Eichstaedt & Tobias Ebert, 2020. "Big data methods, social media, and the psychology of entrepreneurial regions: capturing cross-county personality traits and their impact on entrepreneurship in the USA," Small Business Economics, Springer, vol. 55(3), pages 567-588, October.
• Jens Prüfer & Patricia Prüfer, 2020. "Data science for entrepreneurship research: studying demand dynamics for entrepreneurial skills in the Netherlands," Small Business Economics, Springer, vol. 55(3), pages 651-672, October.
  • Prüfer, Jens & Prüfer, Patricia, 2019. "Data Science for Entrepreneurship Research : Studying Demand Dynamics for Entrepreneurial Skills in the Netherlands," Discussion Paper 2019-005, Tilburg University, Center for Economic Research.
  • Prüfer, Jens & Prüfer, Patricia, 2019. "Data Science for Entrepreneurship Research : Studying Demand Dynamics for Entrepreneurial Skills in the Netherlands," Other publications TiSEM 83a4ca9e-c0cd-4786-ac8c-9, Tilburg University, School of Economics and Management.
• Jermain C. Kaminski & Christian Hopp, 2020. "Predicting outcomes in crowdfunding campaigns with textual, visual, and linguistic signals," Small Business Economics, Springer, vol. 55(3), pages 627-649, October.
• Giovannelli, Alessandro & Massacci, Daniele & Soccorsi, Stefano, 2021. "Forecasting stock returns with large dimensional factor models," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 252-269.
  • Alessandro Giovannelli & Daniele Massacci & Stefano Soccorsi, 2020. "Forecasting Stock Returns with Large Dimensional Factor Models," Working Papers 305661169, Lancaster University Management School, Economics Department.
• Delogu, Marco & Lagravinese, Raffaele & Paolini, Dimitri & Resce, Giuliano, 2024. "Predicting dropout from higher education: Evidence from Italy," Economic Modelling, Elsevier, vol. 130(C).
  • Marco Delogu & Raffaelle Lagravinese & Dimitri Paolini & Giuliano Resce, 2020. "Predicting dropout from higher education: Evidence from Italy," DEM Discussion Paper Series 22-06, Department of Economics at the University of Luxembourg.
• Bastianin, Andrea & Galeotti, Marzio & Manera, Matteo, 2014. "Forecasting the oil–gasoline price relationship: Do asymmetries help?," Energy Economics, Elsevier, vol. 46(S1), pages 44-56.
  • Bastianin, Andrea & Galeotti, Marzio & Manera, Matteo, 2014. "Forecasting the Oil-gasoline Price Relationship: Should We Care about the Rockets and the Feathers?," Climate Change and Sustainable Development 165791, Fondazione Eni Enrico Mattei (FEEM).
  • Andrea Bastianin & Matteo Manera, 2020. "A test of time reversibility based on Lmoments with an application to the business cycles of the G7 economies," Working Papers 445, University of Milano-Bicocca, Department of Economics, revised Jun 2020.
  • Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2014. "Forecasting the Oil-Gasoline Price Relationship: Should We Care About the Rockets and the Feathers?," IEFE Working Papers 62, IEFE, Center for Research on Energy and Environmental Economics and Policy, Universita' Bocconi, Milano, Italy.
  • Andrea BASTIANIN & Marzio GALEOTTI & Matteo MANERA, 2015. "Forecasting the Oil-Gasoline Price Relationship: Should We Care about the Rockets and the Feathers?," Departmental Working Papers 2015-23, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
  • Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2014. "Forecasting the Oil-gasoline Price Relationship: Should We Care about the Rockets and the Feathers?," Working Papers 2014.21, Fondazione Eni Enrico Mattei.
• Guowei Cui & Vasilis Sarafidis & Takashi Yamagata, 2020. "IV Estimation of Spatial Dynamic Panels with Interactive Effects: Large Sample Theory and an Application on Bank Attitude," Monash Econometrics and Business Statistics Working Papers 11/20, Monash University, Department of Econometrics and Business Statistics.
• Yi He & Sombut Jaidee & Jiti Gao, 2020. "Most Powerful Test against High Dimensional Free Alternatives," Monash Econometrics and Business Statistics Working Papers 13/20, Monash University, Department of Econometrics and Business Statistics.
• George Athanasopoulos & Nikolaos Kourentzes, 2020. "On the Evaluation of Hierarchical Forecasts," Monash Econometrics and Business Statistics Working Papers 2/20, Monash University, Department of Econometrics and Business Statistics.
• Leland Bybee & Bryan T. Kelly & Asaf Manela & Dacheng Xiu, 2020. "The Structure of Economic News," NBER Working Papers 26648, National Bureau of Economic Research, Inc.
• Evan M. Munro & Serena Ng, 2020. "Latent Dirichlet Analysis of Categorical Survey Expectations," NBER Working Papers 27182, National Bureau of Economic Research, Inc.
• Ammar Farooq & Adriana D. Kugler & Umberto Muratori, 2020. "Do Unemployment Insurance Benefits Improve Match and Employer Quality? Evidence from Recent U.S. Recessions," NBER Working Papers 27574, National Bureau of Economic Research, Inc.
• Bradley Shapiro & Günter J. Hitsch & Anna Tuchman, 2020. "Generalizable and Robust TV Advertising Effects," NBER Working Papers 27684, National Bureau of Economic Research, Inc.
• Marshall Burke & Anne Driscoll & David Lobell & Stefano Ermon, 2020. "Using Satellite Imagery to Understand and Promote Sustainable Development," NBER Working Papers 27879, National Bureau of Economic Research, Inc.
• Bryan S. Graham, 2020. "Sparse Network Asymptotics for Logistic Regression under Possible Misspecification," NBER Working Papers 27962, National Bureau of Economic Research, Inc.
• L. Galiana & B. Sakarovitch & F. Sémécurbe & Z. Smoreda, 2020. "Residential segregation, daytime segregation and spatial frictions : an analysis from mobile phone data," Documents de Travail de l'Insee - INSEE Working Papers g2020-12, Institut National de la Statistique et des Etudes Economiques.
• Paula Adamczyk & Ben Westmore, 2020. "Unpicking Portugal’s export performance: A microdata analysis," OECD Economics Department Working Papers 1618, OECD Publishing.
• Nicolas Woloszko, 2020. "Tracking activity in real time with Google Trends," OECD Economics Department Working Papers 1634, OECD Publishing.
• Al-Kasawnih Akad, 2020. "Money-Laundering Practices, Estimation, Regulation, and Commercial and Financial Cross-Border Flows," Revista OEconomica, Romanian Society for Economic Science, Revista OEconomica, issue 03-4.
• Pedro Carneiro & Sokbae Lee & Daniel Wilhelm, 2020. "Optimal data collection for randomized control trials," The Econometrics Journal, Royal Economic Society, vol. 23(1), pages 1-31.
  • Carneiro, Pedro & Lee, Sokbae & Wilhelm, Daniel, 2016. "Optimal Data Collection for Randomized Control Trials," IZA Discussion Papers 9908, Institute of Labor Economics (IZA).
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers 15/17, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers 45/17, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers CWP15/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2019. "Optimal Data Collection for Randomized Control Trials," CeMMAP working papers CWP21/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2016. "Optimal data collection for randomized control trials," CeMMAP working papers 15/16, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers CWP45/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae Lee & Daniel Wilhelm, 2016. "Optimal Data Collection for Randomized Control Trials," Papers 1603.03675, arXiv.org, revised Aug 2016.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2016. "Optimal data collection for randomized control trials," CeMMAP working papers CWP15/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
• Elena Andreou & Patrick Gagliardini & Eric Ghysels & Mirco Rubin, 2020. "Mixed-Frequency Macro–Finance Factor Models: Theory and Applications," Journal of Financial Econometrics, Oxford University Press, vol. 18(3), pages 585-628.
• Shihao Gu & Bryan Kelly & Dacheng Xiu, 2020. "Empirical Asset Pricing via Machine Learning," Review of Finance, European Finance Association, vol. 33(5), pages 2223-2273.
• Shihao Gu & Bryan Kelly & Dacheng Xiu, 2020. "Empirical Asset Pricing via Machine Learning," The Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2223-2273.
  • Shihao Gu & Bryan Kelly & Dacheng Xiu, 2018. "Empirical Asset Pricing via Machine Learning," NBER Working Papers 25398, National Bureau of Economic Research, Inc.
  • Shihao Gu & Bryan T. Kelly & Dacheng Xiu, 2018. "Empirical Asset Pricing via Machine Learning," Swiss Finance Institute Research Paper Series 18-71, Swiss Finance Institute.
• Kailing Shen & Bledi Taska, 2020. "Measuring the impacts of COVID-19 on job postings in Australia using a reweighting-estimation-transformation approach," Australian Journal of Labour Economics (AJLE), Bankwest Curtin Economics Centre (BCEC), Curtin Business School, vol. 23(2), pages 153-171.
  • Shen, Kailing & Taska, Bledi, 2020. "Measuring the Impacts of COVID-19 on Job Postings in Australia Using a Reweighting-Estimation-Transformation Approach," IZA Discussion Papers 13640, Institute of Labor Economics (IZA).
• Daniel Felix Ahelegbey & Luis Carvalho & Eric D. Kolaczyk, 2020. "A Bayesian Covariance Graph And Latent Position Model For Multivariate Financial Time Series," DEM Working Papers Series 181, University of Pavia, Department of Economics and Management.
• Daniel Felix Ahelegbey & Paolo Giudici, 2020. "Market Risk, Connectedness and Turbulence: A Comparison of 21st Century Financial Crises," DEM Working Papers Series 188, University of Pavia, Department of Economics and Management.
• Ahelegbey, Daniel Felix & Giudici, Paolo, 2022. "NetVIX — A network volatility index of financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 594(C).
  • Daniel Felix Ahelegbey & Paolo Giudici, 2020. "NetVIX - A Network Volatility Index of Financial Markets," DEM Working Papers Series 192, University of Pavia, Department of Economics and Management.
• Daniel Felix Ahelegbey, 2020. "A Statistical Measure of Global Equity Market Risk," DEM Working Papers Series 194, University of Pavia, Department of Economics and Management.
• Ahelegbey, Daniel Felix & Billio, Monica & Casarin, Roberto, 2024. "Modeling Turning Points in the Global Equity Market," Econometrics and Statistics, Elsevier, vol. 30(C), pages 60-75.
  • Daniel Felix Ahelegbey & Monica Billio & Roberto Casarin, 2020. "Modeling Turning Points In Global Equity Market," DEM Working Papers Series 195, University of Pavia, Department of Economics and Management.
• Roberto S. Mariano & Suleyman Ozmucur, 2020. "Predictive Performance of Mixed-Frequency Nowcasting and Forecasting Models (with Application to Philippine Inflation and GDP Growth)Abstract: We study how the separation of time and risk preferences ," PIER Working Paper Archive 20-029, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
• igescu, iulia, 2020. "Describing Location Shifts with One Class Support Vector Machines," MPRA Paper 100984, University Library of Munich, Germany.
• Glocker, Christian & Kaniovski, Serguei, 2020. "Structural modeling and forecasting using a cluster of dynamic factor models," MPRA Paper 101874, University Library of Munich, Germany.
• Van, Germinal, 2020. "The Effect of Economic Sectors on the National Income of West African Economies from 2010 to 2019: A Multiple Regression Analysis," MPRA Paper 102417, University Library of Munich, Germany.
• Gomez-Ruano, Gerardo, 2020. "Data Science: A Primer for Economists," MPRA Paper 102928, University Library of Munich, Germany.
• Pinto, Claudio, 2020. "Fuzzy DEA models for sports data analysis: The evaluation of the relative performances of professional (virtual) football teams," MPRA Paper 103129, University Library of Munich, Germany.
• Tamara, Novian & Dwi Muchisha, Nadya & Andriansyah, Andriansyah & Soleh, Agus M, 2020. "Nowcasting Indonesia’s GDP Growth Using Machine Learning Algorithms," MPRA Paper 105235, University Library of Munich, Germany.
• van der Plaat, Mark, 2020. "Loan sales and the tyranny of tistance in U.S. residential mortgage lending," MPRA Paper 107519, University Library of Munich, Germany, revised 20 Apr 2021.
• Maiorova, Ksenia & Fokin, Nikita, 2020. "Наукастинг Темпов Роста Стоимостных Объемов Экспорта И Импорта По Товарным Группам [Nowcasting the growth rates of the export and import by commodity groups]," MPRA Paper 109557, University Library of Munich, Germany.
• Fernandez, Julian, 2020. "Exchange Rate Uncertainty and the Interest Rate Parity," MPRA Paper 116010, University Library of Munich, Germany, revised 2022.
• Daniel Levy & Tamir Mayer & Alon Raviv, 2020. "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," Working Papers 2020-01, Bar-Ilan University, Department of Economics.
  • Levy, Daniel & Mayer, Tamir & Raviv, Alon, 2020. "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," MPRA Paper 98785, University Library of Munich, Germany.
  • Daniel Levy & Tamir Mayer & Alon Raviv, 2020. "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," Working Paper series 20-05, Rimini Centre for Economic Analysis.
  • Levy, Daniel & Mayer, Tamir & Raviv, Alon, 2020. "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," EconStor Preprints 214194, ZBW - Leibniz Information Centre for Economics.
  • Daniel Levy & Tamir Mayer & Alon Raviv, 2020. "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," Working Papers hal-02488796, HAL.
• Oyenyinka Sunday Omoshoro‐Jones & Lumengo Bonga‐Bonga, 2022. "Intra‐regional spillovers from Nigeria and South Africa to the rest of Africa: New evidence from a FAVAR model," The World Economy, Wiley Blackwell, vol. 45(1), pages 251-275, January.
  • Omoshoro-Jones, Oyeyinka Sunday & Bonga-Bonga, Lumengo, 2020. "Intra-regional spillovers from Nigeria and South Africa to the rest of Africa: New evidence from a FAVAR model," MPRA Paper 99514, University Library of Munich, Germany.
• Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna, 2020. "Point and Density Forecasting of Macroeconomic and Financial Uncertainties of the United States," Working Papers 202058, University of Pretoria, Department of Economics.
• Markus Brunnermeier & Rohit Lamba & Carlos Segura-Rodriguez, 2020. "Inverse Selection," Working Papers 2020-50, Princeton University. Economics Department..
• Mark Braverman & Sylvain Chassang, 2020. "Data-Driven Incentive Alignment in Capitation Schemes," Working Papers 2020-60, Princeton University. Economics Department..
• Damian Przekop, 2020. "Feature Engineering for Anti-Fraud Models Based on Anomaly Detection," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 12(3), pages 301-316, September.
• António Rua & Carlos Melo Gouveia & Nuno Lourenço, 2020. "Forecasting tourism with targeted predictors in a data-rich environment," Working Papers w202005, Banco de Portugal, Economics and Research Department.
• Castellares, Renzo & Cornejo, Gerson, 2020. "A Leading Indicator for Employment using Big Data," Working Papers 2020-009, Banco Central de Reserva del Perú.
• Coronado, Hilary & Lahura, Erick & Vega, Marco, 2021. "¿Qué tan rígidos son los precios en línea? Evidencia para el Perú usando Big Data," Revista Moneda, Banco Central de Reserva del Perú, issue 188, pages 30-33.
  • Coronado, Hilary & Lahura, Erick & Vega, Marco, 2020. "¿Qué tan rígidos son los precios en línea? Evidencia para Perú usando Big Data," Working Papers 2020-018, Banco Central de Reserva del Perú.
  • Marco Vega & Erick Lahura & Hilary Coronado, 2021. "¿Qué tan rígidos son los precios en línea? Evidencia para Perú usando Big Data," Documentos de Trabajo / Working Papers 2021-497, Departamento de Economía - Pontificia Universidad Católica del Perú.
• Faryna, Oleksandr & Pham, Tho & Talavera, Oleksandr & Tsapin, Andriy, 2020. "Wage Setting and Unemployment: Evidence from Online Job Vacancy Data," GLO Discussion Paper Series 503, Global Labor Organization (GLO).
  • Oleksandr Faryna & Tho Pham & Oleksandr Talavera & Andriy Tsapin, 2020. "Wage Setting and Unemployment: Evidence from Online Job Vacancy Data," Economics Discussion Papers em-dp2020-02, Department of Economics, University of Reading.
  • Oleksandr Faryna & Tho Pham & Oleksandr Talavera & Andriy Tsapin, 2020. "Wage Setting and Unemployment: Evidence from Online Job Vacancy Data," Discussion Papers 20-03, Department of Economics, University of Birmingham.
• Michael P. Clements, 2022. "Individual forecaster perceptions of the persistence of shocks to GDP," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(3), pages 640-656, April.
  • Michael P. Clements, 2020. "Individual Forecaster Perceptions of the Persistence of Shocks to GDP," ICMA Centre Discussion Papers in Finance icma-dp2020-02, Henley Business School, University of Reading.
• Fornaro, Paolo, 2020. "Nowcasting Industrial Production Using Uncoventional Data Sources," ETLA Working Papers 80, The Research Institute of the Finnish Economy.
• Maurizio Daniele & Winfried Pohlmeier & Aygul Zagidullina, 2018. "Sparse Approximate Factor Estimation for High-Dimensional Covariance Matrices," Working Paper Series of the Department of Economics, University of Konstanz 2018-07, Department of Economics, University of Konstanz.
  • Maurizio Daniele & Winfried Pohlmeier & Aygul Zagidullina, 2020. "Sparse Approximate Factor Estimation for High-Dimensional Covariance Matrices," Working Paper series 20-03, Rimini Centre for Economic Analysis.
  • Maurizio Daniele & Winfried Pohlmeier & Aygul Zagidullina, 2019. "Sparse Approximate Factor Estimation for High-Dimensional Covariance Matrices," Papers 1906.05545, arXiv.org.
• Daniel Levy & Tamir Mayer & Alon Raviv, 2020. "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," Working Papers 2020-01, Bar-Ilan University, Department of Economics.
  • Daniel Levy & Tamir Mayer & Alon Raviv, 2020. "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," Working Paper series 20-05, Rimini Centre for Economic Analysis.
  • Levy, Daniel & Mayer, Tamir & Raviv, Alon, 2020. "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," EconStor Preprints 214194, ZBW - Leibniz Information Centre for Economics.
  • Daniel Levy & Tamir Mayer & Alon Raviv, 2020. "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," Working Papers hal-02488796, HAL.
  • Levy, Daniel & Mayer, Tamir & Raviv, Alon, 2020. "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," MPRA Paper 98785, University Library of Munich, Germany.
• Kang, Minsung, 2020. "Big Data and Policy Directions for Korean Service Firms," Industrial Economic Review 20-11, Korea Institute for Industrial Economics and Trade.
• Marianna Brunetti & Roberta De Luca, 2023. "Pre-selection in cointegration-based pairs trading," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(5), pages 1611-1640, December.
  • Marianna Brunetti & Roberta De Luca, 2020. "Pre-selection in Cointegration-based Pairs Trading," CEIS Research Paper 500, Tor Vergata University, CEIS, revised 10 Mar 2021.
  • Marianna Brunetti & Roberta de Luca, 2022. "Pre-selection in cointegration-based pairs trading," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0089, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
• Francesca Di Iorio & Stefano Fachin, 2020. "Forecasting mortality rates and life expectancy in the year of Covid-19," DSS Empirical Economics and Econometrics Working Papers Series 2020/1, Centre for Empirical Economics and Econometrics, Department of Statistics, "Sapienza" University of Rome.
• Neeti Mathur & Himanshu Mathur, 2020. "Application of GARCH Models For Volatility Modelling of Stock Market Returns: Evidences From BSE India," Proceedings of Business and Management Conferences 10112533, International Institute of Social and Economic Sciences.
• Sandra Figueiredo & André Soares & Neuza Vieira & Miguel Devezas, 2020. "A psycholinguistic analysis of world leaders? discourses concerning the COVID-19 context: authenticity and emotional tone," International Journal of Social Sciences, International Institute of Social and Economic Sciences, vol. 9(2), pages 66-69, September.
• Sandra Figueiredo & André Soares & Neuza Vieira & Miguel Devezas, 2020. "A psycholinguistic analysis of world leaders? discourses concerning the COVID-19 context: authenticity and emotional tone," International Journal of Social Sciences, International Institute of Social and Economic Sciences, vol. 9(2), pages 66-81, September.
• Tomasz Piotr Kostyra & Michał Rubaszek, 2020. "Forecasting the Yield Curve for Poland," Econometric Research in Finance, SGH Warsaw School of Economics, Collegium of Economic Analysis, vol. 5(2), pages 103-117, December.
• Sinem Güler KANGALLI-UYAR, 2020. "The Matrix Exponential Spatial Specification Approach for Big Datasets: The Analysis of Istanbul Office Market," Sosyoekonomi Journal, Sosyoekonomi Society, issue 28(43).
• Fernando Moraes & Rodrigo De-Losso, 2020. "Risk Factor Centrality and the Cross-Section of Expected Returns," Working Papers, Department of Economics 2020_17, University of São Paulo (FEA-USP).
• Fernando Moraes & Rodrigo De-Losso, 2020. "Risk Factors’ CPDAG Roots and the Cross-Section of Expected Returns," Working Papers, Department of Economics 2020_18, University of São Paulo (FEA-USP).
• Sabine Zinn & Ariane Würbach & Hans Walter Steinhauer & Angelina Hammon, 2020. "Attrition and selectivity of the NEPS starting cohorts: an overview of the past 8 years [Ausfall und Selektivitäten in den NEPS Startkohorten: ein Überblick über die letzten 8 Jahre]," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 14(2), pages 163-206, July.
• Arianna Agosto & Paolo Giudici, 2020. "COVID-19 contagion and digital finance," Digital Finance, Springer, vol. 2(1), pages 159-167, September.
• Larisa Adamyan & Kirill Efimov & Cathy Y. Chen & Wolfgang K. Härdle, 2020. "Adaptive weights clustering of research papers," Digital Finance, Springer, vol. 2(3), pages 169-187, December.
  • Adamyan, Larisa & Efimov, Kirill & Chen, Cathy Yi-hsuan & Härdle, Wolfgang Karl, 2017. "Adaptive weights clustering of research papers," SFB 649 Discussion Papers 2017-013, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
• Chris Heaton & Natalia Ponomareva & Qin Zhang, 2020. "Forecasting models for the Chinese macroeconomy: the simpler the better?," Empirical Economics, Springer, vol. 58(1), pages 139-167, January.
• Paolo Fornaro & Henri Luomaranta, 2020. "Nowcasting Finnish real economic activity: a machine learning approach," Empirical Economics, Springer, vol. 58(1), pages 55-71, January.
• K. Benkovskis & B. Bluhm & E. Bobeica & C. Osbat & S. Zeugner, 2020. "What drives export market shares? It depends! An empirical analysis using Bayesian model averaging," Empirical Economics, Springer, vol. 59(2), pages 817-869, August.
  • Konstantins Benkovskis & Benjamin Bluhm & Elena Bobeica & Chiara Osbat & Stefan Zeugner, 2017. "What drives export market shares? It depends! An empirical analysis using Bayesian Model Averaging," Working Papers 2017/02, Latvijas Banka.
  • Osbat, Chiara & Benkovskis, Konstantins & Bluhm, Benjamin & Bobeica, Elena & Zeugner, Stefan, 2017. "What drives export market shares? It depends! An empirical analysis using Bayesian Model Averaging," Working Paper Series 2090, European Central Bank.
• Maximo Camacho & Angela Caro & German Lopez-Buenache, 2020. "The two-speed Europe in business cycle synchronization," Empirical Economics, Springer, vol. 59(3), pages 1069-1084, September.
• Yaohao Peng & Lucas Ferreira Mation, 2020. "The Challenge of Pairing Big Datasets: Probabilistic Record Linkage Methods and Diagnosis of Their Empirical Viability," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 16(1), pages 35-57, April.
• Yongchen Zhao, 2020. "Predicting U.S. Business Cycle Turning Points Using Real-Time Diffusion Indexes Based on a Large Data Set," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 16(2), pages 77-97, November.
  • Herman O. Stekler & Yongchen Zhao, 2016. "Predicting U.S. Business Cycle Turning Points Using Real-Time Diffusion Indexes Based on a Large Data Set," Working Papers 2016-006, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
  • Herman Stekler & Yongchen Zhao, 2016. "Predicting U.S. Business Cycle Turning Points Using Real-Time Diffusion Indexes Based on a Large Data Set," Working Papers 2016-15, Towson University, Department of Economics, revised Sep 2016.
• Wolfgang Dauth & Johann Eppelsheimer, 2020. "Preparing the sample of integrated labour market biographies (SIAB) for scientific analysis: a guide," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 54(1), pages 1-14, December.
• Vladimir Batagelj, 2020. "On fractional approach to analysis of linked networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(2), pages 621-633, May.
• Andrea Bastianin, 2020. "Robust measures of skewness and kurtosis for macroeconomic and financial time series," Applied Economics, Taylor & Francis Journals, vol. 52(7), pages 637-670, February.
  • Andrea Bastianin, 2019. "Robust measures of skewness and kurtosis for macroeconomic and financial time series," Working Papers 408, University of Milano-Bicocca, Department of Economics, revised 06 May 2019.
• Jean Boivin & Marc P. Giannoni & Dalibor Stevanović, 2020. "Dynamic Effects of Credit Shocks in a Data-Rich Environment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 272-284, April.
  • Jean Boivin & Marc Giannoni & Dalibor Stevanovic, 2013. "Dynamic effects of credit shocks in a data-rich environment," Staff Reports 615, Federal Reserve Bank of New York.
  • Jean Boivin & Marc P. Giannoni & Dalibor Stevanovic, 2016. "Dynamic Effects of Credit Shocks in a Data-Rich Environment," CIRANO Working Papers 2016s-55, CIRANO.
  • Jean Boivin & Marc P. Giannoni & Dalibor Stevanovic, 2013. "Dynamic Effects of Credit Shocks in a Data-Rich Environment," CIRANO Working Papers 2013s-11, CIRANO.
  • Jean Boivin & Marc P. Giannoni & Dalibor Stevanovic, 2013. "Dynamic Effects of Credit Shocks in a Data-Rich Environment," Cahiers de recherche 1324, CIRPEE.
  • Giannoni, Marc & Boivin, Jean & Stevanovic, Dalibor, 2013. "Dynamic Effects of Credit Shocks in a Data-Rich Environment," CEPR Discussion Papers 9470, C.E.P.R. Discussion Papers.
• Zhang, Bo & Nguyen, Bao H., 2020. "Real-time forecasting of the Australian macroeconomy using Bayesian VARs," Working Papers 2020-12, University of Tasmania, Tasmanian School of Business and Economics.
• Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2020. "lassopack: Model selection and prediction with regularized regression in Stata," Stata Journal, StataCorp LP, vol. 20(1), pages 176-235, March.
  • Ahrens, Achim & Hansen, Christian B. & Schaffer, Mark E, 2019. "lassopack: Model Selection and Prediction with Regularized Regression in Stata," IZA Discussion Papers 12081, Institute of Labor Economics (IZA).
  • Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2019. "lassopack: Model selection and prediction with regularized regression in Stata," Papers 1901.05397, arXiv.org.
• Laura Zieger & John Jerrim & Jake Anders & Nikki Shure, 2020. "Conditioning: How background variables can influence PISA scores," CEPEO Working Paper Series 20-09, UCL Centre for Education Policy and Equalising Opportunities, revised Apr 2020.
• Fiona Burlig & Christopher Knittel & David Rapson & Mar Reguant & Catherine Wolfram, 2020. "Machine Learning from Schools about Energy Efficiency," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 7(6), pages 1181-1217.
  • Fiona Burlig & Christopher Knittel & David Rapson & Mar Reguant & Catherine Wolfram, 2017. "Machine Learning from Schools about Energy Efficiency," NBER Working Papers 23908, National Bureau of Economic Research, Inc.
• Tae-Hwy Lee & Ekaterina Seregina, 2020. "Learning from Forecast Errors: A New Approach to Forecast Combinations," Papers 2011.02077, arXiv.org, revised May 2021.
  • Tae-Hwy Lee & Ekaterina Seregina, 2020. "Learning from Forecast Errors: A New Approach to Forecast Combination," Working Papers 202024, University of California at Riverside, Department of Economics.
• Tae-Hwy Lee & Ekaterina Seregina, 2024. "Optimal Portfolio Using Factor Graphical Lasso," Journal of Financial Econometrics, Oxford University Press, vol. 22(3), pages 670-695.
  • Tae-Hwy Lee & Ekaterina Seregina, 2020. "Optimal Portfolio Using Factor Graphical Lasso," Papers 2011.00435, arXiv.org, revised Apr 2023.
  • Tae-Hwy Lee & Ekaterina Seregina, 2023. "Optimal Portfolio Using Factor Graphical Lasso," Working Papers 202302, University of California at Riverside, Department of Economics.
  • Tae-Hwy Lee & Ekaterina Seregina, 2020. "Optimal Portfolio Using Factor Graphical Lasso," Working Papers 202025, University of California at Riverside, Department of Economics.
• Schubert, Torben & Jäger, Angela & Türkeli, Serdar & Visentin, Fabiana, 2020. "Addressing the productivity paradox with big data: A literature review and adaptation of the CDM econometric model," MERIT Working Papers 2020-050, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
• WEBER Matthias, & STRIAUKAS Jonas, & SCHUMACHER Martin, & HARALD Binder,, 2018. "Network constrained covariate coefficient and connection sign estimation," LIDAM Discussion Papers CORE 2018018, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  • Jonas Striaukas & Martin Schumacher & Harald Binder & Matthias Weber, 2020. "Network-Constrained Covariate Coefficient and Connection Sign Estimation," Working Papers on Finance 2001, University of St. Gallen, School of Finance.
  • Matthias Weber & Jonas Striaukas & Martin Schumacher & Harald Binder, 2018. "Network constrained covariate coefficient and connection sign estimation," Bank of Lithuania Discussion Paper Series 8, Bank of Lithuania.
• Arnerić Josip, 2020. "Realized density estimation using intraday prices," Croatian Review of Economic, Business and Social Statistics, Sciendo, vol. 6(1), pages 1-9, May.
• Wójcik Filip & Górnik Michał, 2020. "Improvement of E-Commerce Recommendation Systems with Deep Hybrid Collaborative Filtering with Content: A Case Study," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 24(3), pages 37-50, September.
• Urbańczyk Dominika M., 2020. "Competing Risks Models for an Enterprises Duration on the Market," Folia Oeconomica Stetinensia, Sciendo, vol. 20(1), pages 456-473, June.
• Szkutnik Tomasz, 2020. "Identification of Outliers in High Density Areas with the Use of a Quantile Regression Model," Folia Oeconomica Stetinensia, Sciendo, vol. 20(2), pages 375-391, December.
• Gružauskas Valentas & Kriščiūnas Andrius & Čalnerytė Dalia & Navickas Valentinas, 2020. "Analytical Method for Correction Coefficient Determination for Applying Comparative Method for Real Estate Valuation," Real Estate Management and Valuation, Sciendo, vol. 28(2), pages 52-62, June.
• Marek Stelmach & Marcin Chlebus, 2020. "Novel multilayer stacking framework with weighted ensemble approach for multiclass credit scoring problem application," Working Papers 2020-08, Faculty of Economic Sciences, University of Warsaw.
• Christian Glocker & Serguei Kaniovski, 2022. "Macroeconometric forecasting using a cluster of dynamic factor models," Empirical Economics, Springer, vol. 63(1), pages 43-91, July.
  • Christian Glocker & Serguei Kaniovski, 2020. "Macroeconometric Forecasting Using a Cluster of Dynamic Factor Models," WIFO Working Papers 614, WIFO.
• Stefan Jestl & Emanuel List, 2020. "Distributional National Accounts (DINA) for Austria, 2004-2016," wiiw Working Papers 175, The Vienna Institute for International Economic Studies, wiiw.
• Stefan Ederer & Stefan Humer & Stefan Jestl & Emanuel List, 2020. "Distributional National Accounts (DINA) with Household Survey Data. Methodology and Results for European Countries," WIFO Working Papers 599, WIFO.
  • Stefan Ederer & Stefan Humer & Stefan Jestl & Emanuel List, 2020. "Distributional National Accounts (DINA) with Household Survey Data: Methodology and Results for European Countries," wiiw Working Papers 180, The Vienna Institute for International Economic Studies, wiiw.
• Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2020. "Assessing international commonality in macroeconomic uncertainty and its effects," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(3), pages 273-293, April.
  • Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2018. "Assessing International Commonality in Macroeconomic Uncertainty and Its Effects," Working Papers (Old Series) 1803, Federal Reserve Bank of Cleveland.
  • Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2019. "Assessing International Commonality in Macroeconomic Uncertainty and Its Effects," Working Papers 18-03R, Federal Reserve Bank of Cleveland.
  • Marcellino, Massimiliano & Clark, Todd & Carriero, Andrea, 2019. "Assessing International Commonality in Macroeconomic Uncertainty and Its Effects," CEPR Discussion Papers 13970, C.E.P.R. Discussion Papers.
• Antoine A. Djogbenou, 2020. "Comovements in the real activity of developed and emerging economies: A test of global versus specific international factors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(3), pages 344-370, April.
  • Antoine A. Djogbenou, 2018. "Comovements In The Real Activity Of Developed And Emerging Economies: A Test Of Global Versus Specific International Factors," Working Paper 1392, Economics Department, Queen's University.
• Benedikt Maas, 2020. "Short‐term forecasting of the US unemployment rate," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 394-411, April.
  • Maas, Benedikt, 2019. "Short-term forecasting of the US unemployment rate," MPRA Paper 94066, University Library of Munich, Germany.
• Oguzhan Cepni & Rangan Gupta & I. Ethem Güney & M. Yilmaz, 2020. "Forecasting local currency bond risk premia of emerging markets: The role of cross‐country macrofinancial linkages," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 966-985, September.
  • Oguzhan Cepni & Rangan Gupta & I. Ethem Guney & M. Hasan Yilmaz, 2019. "Forecasting Local Currency Bond Risk Premia of Emerging Markets: The Role of Cross-Country Macro-Financial Linkages," Working Papers 201957, University of Pretoria, Department of Economics.
• 牛霖琳 & 夏红玉 & 许秀, 2020. "中国地方债务的省级风险度量和网络外溢风险," Working Papers 2020-11-12, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
• Matthias Raddant & Hiroshi Takahashi, 2022. "Corporate boards, interorganizational ties and profitability: the case of Japan," Empirical Economics, Springer, vol. 62(3), pages 1365-1406, March.
  • Raddant, Matthias & Takahashi, Hiroshi, 2020. "Corporate boards, interorganizational ties and profitability: The case of Japan," Economics Working Papers 2020-02, Christian-Albrechts-University of Kiel, Department of Economics.
• Vrigazova, Borislava, 2020. "Tenfold Bootstrap as Resampling Method in Classification Problems," Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference (2020), Virtual Conference, in: Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Virtual Conference, 10-12 September 2020, pages 74-83, IRENET - Society for Advancing Innovation and Research in Economy, Zagreb.
• Zinn, Sabine & Würbach, Ariane & Steinhauer, Hans Walter, 2020. "Attrition and Selectivity of the NEPS Starting Cohorts: An Overview of the Past 8 Years," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 14, pages 163-206.
• Daniel Levy & Tamir Mayer & Alon Raviv, 2020. "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," Working Papers 2020-01, Bar-Ilan University, Department of Economics.
  • Levy, Daniel & Mayer, Tamir & Raviv, Alon, 2020. "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," EconStor Preprints 214194, ZBW - Leibniz Information Centre for Economics.
  • Daniel Levy & Tamir Mayer & Alon Raviv, 2020. "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," Working Paper series 20-05, Rimini Centre for Economic Analysis.
  • Daniel Levy & Tamir Mayer & Alon Raviv, 2020. "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," Working Papers hal-02488796, HAL.
  • Levy, Daniel & Mayer, Tamir & Raviv, Alon, 2020. "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," MPRA Paper 98785, University Library of Munich, Germany.
• Martínez-Hernández, Catalina, 2020. "Disentangling the effects of multidimensional monetary policy on inflation and inflation expectations in the euro area," Discussion Papers 2020/18, Free University Berlin, School of Business & Economics.
• Oleksandr Faryna & Tho Pham & Oleksandr Talavera & Andriy Tsapin, 2020. "Wage Setting and Unemployment: Evidence from Online Job Vacancy Data," Economics Discussion Papers em-dp2020-02, Department of Economics, University of Reading.
  • Faryna, Oleksandr & Pham, Tho & Talavera, Oleksandr & Tsapin, Andriy, 2020. "Wage Setting and Unemployment: Evidence from Online Job Vacancy Data," GLO Discussion Paper Series 503, Global Labor Organization (GLO).
  • Oleksandr Faryna & Tho Pham & Oleksandr Talavera & Andriy Tsapin, 2020. "Wage Setting and Unemployment: Evidence from Online Job Vacancy Data," Discussion Papers 20-03, Department of Economics, University of Birmingham.
• Greyling, Talita & Rossouw, Stephanie & Adhikari, Tamanna, 2020. "Happiness-lost: Did Governments make the right decisions to combat Covid-19?," GLO Discussion Paper Series 556, Global Labor Organization (GLO).
• Rossouw, Stephanie & Greyling, Talita & Adhikari, Tamanna & Morrison, Phillip S., 2020. "Markov switching models for happiness during a pandemic: The New-Zealand experience," GLO Discussion Paper Series 573, Global Labor Organization (GLO).
• Greyling, Talita & Rossouw, Stephanie & Adhikari, Tamanna, 2020. "A tale of three countries: How did Covid-19 lockdown impact happiness?," GLO Discussion Paper Series 584, Global Labor Organization (GLO).
• Lucchetti, Riccardo & Venetis, Ioannis A., 2020. "A replication of "A quasi-maximum likelihood approach for large, approximate dynamic factor models" (Review of Economics and Statistics, 2012)," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 14, pages 1-14.
  • Lucchetti, Riccardo & Venetis, Ioannis A., 2020. "A replication of "A quasi-maximum likelihood approach for large, approximate dynamic factor models" (Review of Economics and Statistics, 2012)," Economics Discussion Papers 2020-5, Kiel Institute for the World Economy (IfW Kiel).
• Poncela, Pilar & Ruiz, Esther, 2020. "A comment on the dynamic factor model with dynamic factors," Economics Discussion Papers 2020-7, Kiel Institute for the World Economy (IfW Kiel).
• Lucchetti, Riccardo & Venetis, Ioannis A., 2020. "A replication of "A quasi-maximum likelihood approach for large, approximate dynamic factor models" (Review of Economics and Statistics, 2012)," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 14, pages 1-14.
  • Lucchetti, Riccardo & Venetis, Ioannis A., 2020. "A replication of "A quasi-maximum likelihood approach for large, approximate dynamic factor models" (Review of Economics and Statistics, 2012)," Economics Discussion Papers 2020-5, Kiel Institute for the World Economy (IfW Kiel).
• Sami Diaf & Jörg Döpke & Ulrich Fritsche & Ida Rockenbach, 2020. "Sharks and minnows in a shoal of words: Measuring latent ideological positions of German economic research institutes based on text mining techniques," Macroeconomics and Finance Series 202001, University of Hamburg, Department of Socioeconomics.
  • Diaf, Sami & Döpke, Jörg & Fritsche, Ulrich & Rockenbach, Ida, 2020. "Sharks and minnows in a shoal of words: Measuring latent ideological positions of German economic research institutes based on text mining techniques," Working Papers 24, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
• Bluhm, Benjamin & Cutura, Jannic, 2020. "Econometrics at scale: Spark up big data in economics," SAFE Working Paper Series 266, Leibniz Institute for Financial Research SAFE.
• Kugler, Philipp & Biewen, Martin, 2020. "Two-Stage Least Squares Random Forests with a Replication of Angrist and Evans (1998)," VfS Annual Conference 2020 (Virtual Conference): Gender Economics 224538, Verein für Socialpolitik / German Economic Association.
• Jonas Klos & Tim Krieger & Sven Stöwhase, 2022. "Measuring intra-generational redistribution in PAYG pension schemes," Public Choice, Springer, vol. 190(1), pages 53-73, January.
  • Jonas Klos & Tim Krieger & Sven Stöwhase, 2020. "Measuring Intra-Generational Redistribution in PAYG Pension Schemes," CESifo Working Paper Series 8200, CESifo.
  • Klos, Jonas & Krieger, Tim & Stöwhase, Sven, 2020. "Measuring intra-generational redistribution in PAYG pension schemes," Discussion Paper Series 2020-01, University of Freiburg, Wilfried Guth Endowed Chair for Constitutional Political Economy and Competition Policy.

2019

• Bunjira Makond & Mayuening Eso, 2019. "Predictive Models for Classifying the Outcomes of Violence Case Study for Thailand's Deep South," Advances in Decision Sciences, Asia University, Taiwan, vol. 23(3), pages 56-92, September.
• Daniel Borup & Erik Christian Montes Schütte, 2022. "In Search of a Job: Forecasting Employment Growth Using Google Trends," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 186-200, January.
  • Daniel Borup & Erik Christian Montes Schütte, 2019. "In search of a job: Forecasting employment growth using Google Trends," CREATES Research Papers 2019-13, Department of Economics and Business Economics, Aarhus University.
• Bennedsen, Mikkel & Hillebrand, Eric & Koopman, Siem Jan, 2021. "Modeling, forecasting, and nowcasting U.S. CO2 emissions using many macroeconomic predictors," Energy Economics, Elsevier, vol. 96(C).
  • Mikkel Bennedsen & Eric Hillebrand & Siem Jan Koopman, 2019. "Modeling, Forecasting, and Nowcasting U.S. CO2 Emissions Using Many Macroeconomic Predictors," CREATES Research Papers 2019-21, Department of Economics and Business Economics, Aarhus University.
• Kim, Hyeongwoo & Ko, Kyunghwan, 2020. "Improving forecast accuracy of financial vulnerability: PLS factor model approach," Economic Modelling, Elsevier, vol. 88(C), pages 341-355.
  • Hyeongwoo Kim & Kyunghwan Ko, 2017. "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," Auburn Economics Working Paper Series auwp2017-03, Department of Economics, Auburn University.
  • Hyeongwoo Kim & Kyunghwan Ko, 2019. "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," Auburn Economics Working Paper Series auwp2019-03, Department of Economics, Auburn University.
  • Kim, Hyeongwoo & Ko, Kyunghwan, 2018. "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," MPRA Paper 89449, University Library of Munich, Germany.
• Sarthak Behera & Hyeongwoo Kim, 2019. "Forecasting Dollar Real Exchange Rates and the Role of Real Activity Factors," Auburn Economics Working Paper Series auwp2019-04, Department of Economics, Auburn University.
• Nadezhda Baryshnikova & Shannon Davidson & Dennis Wesselbaum, 2022. "Do you feel the heat around the corner? The effect of weather on crime," Empirical Economics, Springer, vol. 63(1), pages 179-199, July.
  • Nadezdha Baryshnikova & Shannon. F. Davidson & Dennis Wesselbaum, 2019. "Do you Feel the Heat Around the Corner? The Effect of Weather on Crime," School of Economics and Public Policy Working Papers 2019-07, University of Adelaide, School of Economics and Public Policy.
• Matthew Harding & Carlos Lamarche, 2019. "Penalized Estimation of a Quantile Count Model for Panel Data," Annals of Economics and Statistics, GENES, issue 134, pages 177-206.
• Patrick Bajari & Victor Chernozhukov & Ali Hortaçsu & Junichi Suzuki, 2019. "The Impact of Big Data on Firm Performance: An Empirical Investigation," AEA Papers and Proceedings, American Economic Association, vol. 109, pages 33-37, May.
  • Patrick Bajari & Victor Chernozhukov & Ali Hortaçsu & Junichi Suzuki, 2018. "The Impact of Big Data on Firm Performance: An Empirical Investigation," NBER Working Papers 24334, National Bureau of Economic Research, Inc.
• Dmitri K. Koustas, 2019. "What Do Big Data Tell Us about Why People Take Gig Economy Jobs?," AEA Papers and Proceedings, American Economic Association, vol. 109, pages 367-371, May.
• Maryam Farboodi & Roxana Mihet & Thomas Philippon & Laura Veldkamp, 2019. "Big Data and Firm Dynamics," AEA Papers and Proceedings, American Economic Association, vol. 109, pages 38-42, May.
  • Maryam Farboodi & Roxana Mihet & Thomas Philippon & Laura Veldkamp, 2019. "Big Data and Firm Dynamics," NBER Working Papers 25515, National Bureau of Economic Research, Inc.
  • Veldkamp, Laura & Farboodi, Maryam & Mihet, Roxana, 2019. "Big Data and Firm Dynamics," CEPR Discussion Papers 13489, C.E.P.R. Discussion Papers.
• Matthew Gentzkow & Bryan Kelly & Matt Taddy, 2019. "Text as Data," Journal of Economic Literature, American Economic Association, vol. 57(3), pages 535-574, September.
• Ellen Hughes-Cromwick & Julia Coronado, 2019. "The Value of US Government Data to US Business Decisions," Journal of Economic Perspectives, American Economic Association, vol. 33(1), pages 131-146, Winter.
• Bunjira Makond & Mayuening Eso, 2019. "Predictive Models for Classifying the Outcomes of Violence Case Study for Thailand’s Deep South," International Association of Decision Sciences, Asia University, Taiwan, vol. 23(3), pages 56-92, September.
• Hafner, Christian M. & Linton, Oliver B. & Tang, Haihan, 2020. "Estimation of a multiplicative correlation structure in the large dimensional case," Journal of Econometrics, Elsevier, vol. 217(2), pages 431-470.
  • Hafner, C. & Linton, O. & Tang, H., 2018. "Estimation of a Multiplicative Correlation Structure in the Large Dimensional Case," Cambridge Working Papers in Economics 1878, Faculty of Economics, University of Cambridge.
  • Hafner, Christian & Linton, Oliver & Tang, Haihan, 2020. "Estimation of a multiplicative correlation structure in the large dimensional case," LIDAM Reprints ISBA 2020028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
• Жузбаев А.М. // Zhuzbayev A.M. & Орлов К.В. // Orlov K.V., 2019. "Использование квартальной прогностической модели и сателлитных моделей в системе анализа и прогнозирования НБ РК // Use of the quarterly predictive model and satellite models in the analysis and forec," Economic Review(National Bank of Kazakhstan), National Bank of Kazakhstan, issue special, pages 3-14.
• Орлов Константин // Orlov Konstantin, 2019. "Оценка и анализ эффективности применения динамической факторной модели для оценивания и прогнозирования ВВП на примере Казахстан // Evaluation and analysis of the effectiveness of the use of a dynamic," Working Papers #2019-4, National Bank of Kazakhstan.
• Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2020. "lassopack: Model selection and prediction with regularized regression in Stata," Stata Journal, StataCorp LP, vol. 20(1), pages 176-235, March.
  • Ahrens, Achim & Hansen, Christian B. & Schaffer, Mark E, 2019. "lassopack: Model Selection and Prediction with Regularized Regression in Stata," IZA Discussion Papers 12081, Institute of Labor Economics (IZA).
  • Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2019. "lassopack: Model selection and prediction with regularized regression in Stata," Papers 1901.05397, arXiv.org.
• Alain Hecq & Luca Margaritella & Stephan Smeekes, 2023. "Granger Causality Testing in High-Dimensional VARs: A Post-Double-Selection Procedure," Journal of Financial Econometrics, Oxford University Press, vol. 21(3), pages 915-958.
  • Alain Hecq & Luca Margaritella & Stephan Smeekes, 2019. "Granger Causality Testing in High-Dimensional VARs: a Post-Double-Selection Procedure," Papers 1902.10991, arXiv.org, revised Dec 2020.
• Peter C. B. Phillips & Zhentao Shi, 2021. "Boosting: Why You Can Use The Hp Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 62(2), pages 521-570, May.
  • Peter C.B. Phillips & Zhentao Shi, 2019. "Boosting: Why you Can Use the HP Filter," Cowles Foundation Discussion Papers 2212, Cowles Foundation for Research in Economics, Yale University.
  • Peter C. B. Phillips & Zhentao Shi, 2019. "Boosting: Why You Can Use the HP Filter," Papers 1905.00175, arXiv.org, revised Nov 2020.
• Robert Donnelly & Francisco J.R. Ruiz & David Blei & Susan Athey, 2021. "Counterfactual inference for consumer choice across many product categories," Quantitative Marketing and Economics (QME), Springer, vol. 19(3), pages 369-407, December.
  • Rob Donnelly & Francisco R. Ruiz & David Blei & Susan Athey, 2019. "Counterfactual Inference for Consumer Choice Across Many Product Categories," Papers 1906.02635, arXiv.org, revised Aug 2023.
• Michael A. Ribers & Hannes Ullrich, 2019. "Battling Antibiotic Resistance: Can Machine Learning Improve Prescribing?," Discussion Papers of DIW Berlin 1803, DIW Berlin, German Institute for Economic Research.
  • Michael Allan Ribers & Hannes Ullrich, 2019. "Battling Antibiotic Resistance: Can Machine Learning Improve Prescribing?," Papers 1906.03044, arXiv.org.
  • Michael Allan Ribers & Hannes Ullrich, 2019. "Battling antibiotic resistance: can machine learning improve prescribing?," CESifo Working Paper Series 7654, CESifo.
• Maurizio Daniele & Winfried Pohlmeier & Aygul Zagidullina, 2018. "Sparse Approximate Factor Estimation for High-Dimensional Covariance Matrices," Working Paper Series of the Department of Economics, University of Konstanz 2018-07, Department of Economics, University of Konstanz.
  • Maurizio Daniele & Winfried Pohlmeier & Aygul Zagidullina, 2020. "Sparse Approximate Factor Estimation for High-Dimensional Covariance Matrices," Working Paper series 20-03, Rimini Centre for Economic Analysis.
  • Maurizio Daniele & Winfried Pohlmeier & Aygul Zagidullina, 2019. "Sparse Approximate Factor Estimation for High-Dimensional Covariance Matrices," Papers 1906.05545, arXiv.org.
• Pfarrhofer, Michael, 2023. "Measuring International Uncertainty Using Global Vector Autoregressions with Drifting Parameters," Macroeconomic Dynamics, Cambridge University Press, vol. 27(3), pages 770-793, April.
  • Pfarrhofer, Michael, 2019. "Measuring international uncertainty using global vector autoregressions with drifting parameters," Working Papers in Economics 2019-3, University of Salzburg.
  • Michael Pfarrhofer, 2019. "Measuring international uncertainty using global vector autoregressions with drifting parameters," Papers 1908.06325, arXiv.org, revised Dec 2019.
• Stefania Albanesi & Domonkos F. Vamossy, 2019. "Predicting Consumer Default: A Deep Learning Approach," NBER Working Papers 26165, National Bureau of Economic Research, Inc.
  • Stefania Albanesi & Domonkos F. Vamossy, 2019. "Predicting Consumer Default: A Deep Learning Approach," Papers 1908.11498, arXiv.org, revised Oct 2019.
  • Stefania Albanesi & Domonkos F. Vamossy, 2019. "Predicting Consumer Default: A Deep Learning Approach," Working Papers 2019-056, Human Capital and Economic Opportunity Working Group.
  • Albanesi, Stefania & Vamossy, Domonkos, 2019. "Predicting Consumer Default: A Deep Learning Approach," CEPR Discussion Papers 13914, C.E.P.R. Discussion Papers.
• Matteo Barigozzi & Matteo Luciani, 2019. "Quasi Maximum Likelihood Estimation and Inference of Large Approximate Dynamic Factor Models via the EM algorithm," Papers 1910.03821, arXiv.org, revised Sep 2024.
  • Matteo Barigozzi & Matteo Luciani, 2024. "Quasi Maximum Likelihood Estimation and Inference of Large Approximate Dynamic Factor Models via the EM algorithm," Finance and Economics Discussion Series 2024-086, Board of Governors of the Federal Reserve System (U.S.).
• Evan Munro & Serena Ng, 2022. "Latent Dirichlet Analysis of Categorical Survey Responses," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 256-271, January.
  • Evan Munro & Serena Ng, 2019. "Latent Dirichlet Analysis of Categorical Survey Responses," Papers 1910.04883, arXiv.org, revised Jul 2020.
• Xiong, Ruoxuan & Pelger, Markus, 2023. "Large dimensional latent factor modeling with missing observations and applications to causal inference," Journal of Econometrics, Elsevier, vol. 233(1), pages 271-301.
  • Ruoxuan Xiong & Markus Pelger, 2019. "Large Dimensional Latent Factor Modeling with Missing Observations and Applications to Causal Inference," Papers 1910.08273, arXiv.org, revised Jan 2022.
• Emilia VASILE & Danut-Octavian SIMION, 2019. "The Management Information Systems Reengineering Through Economic Applications," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 53(1), pages 9-22, March.
• Emilia VASILE & Danut-Octavian SIMION, 2019. "The Role Of Information Systems In Economic Organizations For The Strategic Management," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 54(2), pages 9-24, June.
• Emilia VASILE & Danut-Octavian SIMION, 2019. "Applications For Economic Organizations Built On Enterprise Javabeans Technologies," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 55(3), pages 9-23, September.
• Emilia VASILE & Danut-Octavian SIMION, 2019. "Implementations Of Classes And Objects In Applications For Economic Organizations," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 56(4), pages 9-20, December.
• Catalin DUMITRESCU, 2019. "Contributions To Modeling The Behavior Of Chaotic Systems With Applicability In Economic Systems," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 56(4), pages 98-107, December.
• Jaqueson K. Galimberti, 2020. "Forecasting GDP Growth from Outer Space," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(4), pages 697-722, August.
  • Jaqueson K Galimberti, 2017. "Forecasting GDP growth from the outer space," KOF Working papers 17-427, KOF Swiss Economic Institute, ETH Zurich.
  • Jaqueson K. Galimberti, 2020. "Forecasting GDP growth from outer space," Working Papers 2020-02, Auckland University of Technology, Department of Economics.
• Guillermo Jr. Cardenas Salgado & Luis Antonio Espinosa & Juan Jose Li Ng & Carlos Serrano, 2019. "México | La crisis por escasez de gasolina: un análisis de Big Data [Mexico | The gasoline shortage crisis: A Big Data analysis]," Working Papers 19/09, BBVA Bank, Economic Research Department.
• Diego Bodas & Juan R. García López & Tomasa Rodrigo López & Pep Ruiz de Aguirre & Camilo A. Ulloa & Juan Murillo Arias & Juan de Dios Romero Palop & Heribert Valero Lapaz & Matías J. Pacce, 2019. "Measuring retail trade using card transactional data," Working Papers 1921, Banco de España.
• Massimo Gallo & Sonia Soncin & Andrea Venturini, 2019. "Ven-ICE: a new indicator for the economy of the Veneto region," Questioni di Economia e Finanza (Occasional Papers) 498, Bank of Italy, Economic Research and International Relations Area.
• Guerino Ardizzi & Simone Emiliozzi & Juri Marcucci & Libero Monteforte, 2019. "News and consumer card payments," Temi di discussione (Economic working papers) 1233, Bank of Italy, Economic Research and International Relations Area.
• Mirko Moscatelli & Simone Narizzano & Fabio Parlapiano & Gianluca Viggiano, 2019. "Corporate default forecasting with machine learning," Temi di discussione (Economic working papers) 1256, Bank of Italy, Economic Research and International Relations Area.
• Laurent Ferrara & Anna Simoni, 2023. "When are Google Data Useful to Nowcast GDP? An Approach via Preselection and Shrinkage," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(4), pages 1188-1202, October.
  • Laurent Ferrara & Anna Simoni, 2019. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working Papers 2019-04, Center for Research in Economics and Statistics.
  • Laurent Ferrara & Anna Simoni, 2023. "When are Google Data Useful to Nowcast GDP? An Approach via Preselection and Shrinkage," Post-Print hal-03919944, HAL.
  • Laurent Ferrara & Anna Simoni, 2020. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," EconomiX Working Papers 2020-11, University of Paris Nanterre, EconomiX.
  • Laurent Ferrara & Anna Simoni, 2019. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working papers 717, Banque de France.
  • Laurent Ferrara & Anna Simoni, 2020. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Papers 2007.00273, arXiv.org, revised Sep 2022.
  • Laurent Ferrara & Anna Simoni, 2020. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working Papers hal-04159714, HAL.
• Bailliu, Jeannine & Han, Xinfen & Kruger, Mark & Liu, Yu-Hsien & Thanabalasingam, Sri, 2019. "Can media and text analytics provide insights into labour market conditions in China?," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1118-1130.
  • Jeannine Bailliu & Xinfen Han & Mark Kruger & Yu-Hsien Liu & Sri Thanabalasingam, 2019. "Can media and text analytics provide insights into labour market conditions in China?," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Are post-crisis statistical initiatives completed?, volume 49, Bank for International Settlements.
  • Bailliu, Jeannine & Han, Xinfen & Kruger, Mark & Liu, Yu-Hsien & Thanabalasingam, Sri, 2018. "Can media and text analytics provide insights into labour market conditions in China?," BOFIT Discussion Papers 9/2018, Bank of Finland Institute for Emerging Economies (BOFIT).
  • Jeannine Bailliu & Xinfen Han & Mark Kruger & Yu-Hsien Liu & Sri Thanabalasingam, 2018. "Can Media and Text Analytics Provide Insights into Labour Market Conditions in China?," Staff Working Papers 18-12, Bank of Canada.
• Richardson, Adam & van Florenstein Mulder, Thomas & Vehbi, Tuğrul, 2021. "Nowcasting GDP using machine-learning algorithms: A real-time assessment," International Journal of Forecasting, Elsevier, vol. 37(2), pages 941-948.
  • Adam Richardson & Thomas van Florenstein Mulder & Tugrul Vehbi, 2019. "Nowcasting New Zealand GDP using machine learning algorithms," IFC Bulletins chapters, in: Bank for International Settlements (ed.), The use of big data analytics and artificial intelligence in central banking, volume 50, Bank for International Settlements.
  • Adam Richardson & Thomas van Florenstein Mulder & Tugrul Vehbi, 2018. "Nowcasting New Zealand GDP using machine learning algorithms," CAMA Working Papers 2018-47, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Nikita Fokin & Andrey Polbin, 2019. "Forecasting Russia's Key Macroeconomic Indicators with the VAR-LASSO Model," Russian Journal of Money and Finance, Bank of Russia, vol. 78(2), pages 67-93, June.
• Qi Ge & Benjamin Ho, 2019. "Energy Use And Temperature Habituation: Evidence From High Frequency Thermostat Usage Data," Economic Inquiry, Western Economic Association International, vol. 57(2), pages 1196-1214, April.
• Heinisch Katja & Scheufele Rolf, 2019. "Should Forecasters Use Real-Time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence," German Economic Review, De Gruyter, vol. 20(4), pages 170-200, December.
  • Katja Heinisch & Rolf Scheufele, 2019. "Should Forecasters Use Real‐Time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence," German Economic Review, Verein für Socialpolitik, vol. 20(4), pages 170-200, November.
  • Heinisch, Katja & Scheufele, Rolf, 2017. "Should forecasters use real-time data to evaluate leading indicator models for GDP prediction? German evidence," IWH Discussion Papers 5/2017, Halle Institute for Economic Research (IWH).
• Dario Sansone, 2019. "Beyond Early Warning Indicators: High School Dropout and Machine Learning," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(2), pages 456-485, April.
  • Dario Sansone, 2017. "Beyond Early Warning Indicators: High School Dropout and Machine Learning," Working Papers gueconwpa~17-17-09, Georgetown University, Department of Economics.
• Hilde C. Bjørnland & Julia Zhulanova, 2019. "The shale oil boom and the US economy: Spillovers and time-varying effects," CAMA Working Papers 2019-59, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Hilde C. Bjørnland & Julia Zhulanova, 2019. "The shale oil boom and the U.S. economy: Spillovers and time-varying effects," Working Paper 2019/14, Norges Bank.
• Saskia Ter Ellen & Vegard H. Larsen & Leif Anders Thorsrud, 2022. "Narrative Monetary Policy Surprises and the Media," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(5), pages 1525-1549, August.
  • ter Ellen, Saskia & Larsen, Vegard H. & Thorsrud, Leif Anders, 2019. "Narrative monetary policy surprises and the media," Working Paper 2019/19, Norges Bank.
• Saskia Ter Ellen & Vegard H. Larsen & Leif Anders Thorsrud, 2022. "Narrative Monetary Policy Surprises and the Media," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(5), pages 1525-1549, August.
  • ter Ellen, Saskia & Larsen, Vegard H. & Thorsrud, Leif Anders, 2019. "Narrative monetary policy surprises and the media," Working Paper 2019/19, Norges Bank.
  • Saskia ter Ellen & Vegard H. Larsen & Leif Anders Thorsrud, 2019. "Narrative monetary policy surprises and the media," Working Papers No 06/2019, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
• Hansen, Stephen & McMahon, Michael & Tong, Matthew, 2019. "The long-run information effect of central bank communication," Journal of Monetary Economics, Elsevier, vol. 108(C), pages 185-202.
  • McMahon, Michael & , & Tong, Matthew, 2019. "The Long-Run Information Effect of Central Bank Communication," CEPR Discussion Papers 13438, C.E.P.R. Discussion Papers.
  • Hansen, Stephen & McMahon, Michael & Tong, Matthew, 2019. "The long-run information effect of central bank communication," Bank of England working papers 777, Bank of England.
  • Hansen, Stephen & McMahon, Michael & Tong, Matthew, 2020. "The long-run information effect of central bank communication," Working Paper Series 2363, European Central Bank.
• Meeks, Roland & Monti, Francesca, 2023. "Heterogeneous beliefs and the Phillips curve," Journal of Monetary Economics, Elsevier, vol. 139(C), pages 41-54.
  • Meeks, Roland & Monti, Francesca, 2019. "Heterogeneous beliefs and the Phillips curve," Bank of England working papers 807, Bank of England.
  • Roland Meeks & Francesca Monti, 2022. "Heterogeneous Beliefs and the Phillips Curve," CAMA Working Papers 2022-51, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Meeks, Roland & Monti, Francesca, 2022. "Heterogeneous beliefs and the Phillips curve," CEPR Discussion Papers 17537, C.E.P.R. Discussion Papers.
• Bracke, Philippe & Datta, Anupam & Jung, Carsten & Sen, Shayak, 2019. "Machine learning explainability in finance: an application to default risk analysis," Bank of England working papers 816, Bank of England.
• Yosuke Uno & Ko Adachi, 2019. ""Don't know" Tells: Calculating Non-Response Bias in Firms' Inflation Expectations Using Machine Learning Techniques," Bank of Japan Working Paper Series 19-E-17, Bank of Japan.
• Andreas Gulyas & Krzysztof Pytka, 2019. "Understanding the Sources of Earnings Losses After Job Displacement: A Machine-Learning Approach," CRC TR 224 Discussion Paper Series crctr224_2019_131, University of Bonn and University of Mannheim, Germany.
  • Pytka, Krzysztof & Gulyas, Andreas, 2021. "Understanding the Sources of Earnings Losses After Job Displacement: A Machine-Learning Approach," VfS Annual Conference 2021 (Virtual Conference): Climate Economics 242402, Verein für Socialpolitik / German Economic Association.
  • Andreas Gulyas & Krzysztof Pytka, 2020. "Understanding the Sources of Earnings Losses After Job Displacement: A Machine-Learning Approach," CRC TR 224 Discussion Paper Series crctr224_2020_131v2, University of Bonn and University of Mannheim, Germany.
• Jianjun Miao, 2019. "Multivariate LQG Control under Rational Inattention in Continuous Time," Boston University - Department of Economics - Working Papers Series WP2019-06, Boston University - Department of Economics.
• Gabriel E. Kreindler & Yuhei Miyauchi, 2019. "Measuring Commuting and Economic Activity inside Cities with Cell Phone Records," Boston University - Department of Economics - Working Papers Series WP2020-006, Boston University - Department of Economics, revised Apr 2020.
• Katja Heinisch & Rolf Scheufele, 2019. "Should Forecasters Use Real‐Time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence," German Economic Review, Verein für Socialpolitik, vol. 20(4), pages 170-200, November.
  • Heinisch Katja & Scheufele Rolf, 2019. "Should Forecasters Use Real-Time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence," German Economic Review, De Gruyter, vol. 20(4), pages 170-200, December.
  • Heinisch, Katja & Scheufele, Rolf, 2017. "Should forecasters use real-time data to evaluate leading indicator models for GDP prediction? German evidence," IWH Discussion Papers 5/2017, Halle Institute for Economic Research (IWH).
• Christophe Hurlin & Christophe Pérignon, 2019. "Machine learning et nouvelles sources de données pour le scoring de crédit," Revue d'économie financière, Association d'économie financière, vol. 0(3), pages 21-50.
  • Christophe Hurlin & Christophe Pérignon, 2019. "Machine Learning et nouvelles sources de données pour le scoring de crédit," Working Papers halshs-02377886, HAL.
  • Christophe HURLIN & Christophe PERIGNON, 2019. "Machine Learning et nouvelles sources de données pour le scoring de crédit," LEO Working Papers / DR LEO 2739, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
  • Christophe Hurlin & Christophe Pérignon, 2019. "Machine learning et nouvelles sources de données pour le scoring de crédit," Post-Print hal-03532418, HAL.
• Koen Jochmans & Martin Weidner, 2019. "Fixed‐Effect Regressions on Network Data," Econometrica, Econometric Society, vol. 87(5), pages 1543-1560, September.
  • Koen Jochmans & Martin Weidner, 2016. "Fixed-effect regressions on network data," CeMMAP working papers CWP32/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Jochmans, K. & Weidner, M., 2019. "Fixed-Effect Regressions on Network Data," Cambridge Working Papers in Economics 1938, Faculty of Economics, University of Cambridge.
  • Koen Jochmans & Martin Weidner, 2018. "Fixed-effect regressions on network data," CeMMAP working papers CWP44/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2017. "Fixed-effect regressions on network data," CeMMAP working papers 26/17, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2017. "Fixed-effect regressions on network data," CeMMAP working papers CWP26/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2016. "Fixed-Effect Regressions on Network Data," Papers 1608.01532, arXiv.org, revised Apr 2019.
  • Koen Jochmans & Martin Weidner, 2019. "Fixed-effect regressions on network data," CeMMAP working papers CWP16/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2016. "Fixed-effect regressions on network data," CeMMAP working papers 32/16, Institute for Fiscal Studies.
• Li, Z. Merrick & Laeven, Roger J.A. & Vellekoop, Michel H., 2020. "Dependent microstructure noise and integrated volatility estimation from high-frequency data," Journal of Econometrics, Elsevier, vol. 215(2), pages 536-558.
  • Li, Z. M. & Laeven, R. J. A. & Vellekoop, M. H., 2019. "Dependent Microstructure Noise and Integrated Volatility: Estimation from High-Frequency Data," Cambridge Working Papers in Economics 1952, Faculty of Economics, University of Cambridge.
• Max Nathan & Anna Rosso, 2017. "Innovative events," Development Working Papers 429, Centro Studi Luca d'Agliano, University of Milano, revised 08 Apr 2019.
  • Max Nathan & Anna Rosso, 2019. "Innovative events," CEP Discussion Papers dp1607, Centre for Economic Performance, LSE.
  • Nathan, Max & Rosso, Anna, 2019. "Innovative Events," IZA Discussion Papers 12213, Institute of Labor Economics (IZA).
  • Nathan, Max & Rosso, Anna, 2019. "Innovative events," LSE Research Online Documents on Economics 102626, London School of Economics and Political Science, LSE Library.
  • Nathan, Max & Rosso, Anna, 2019. "Innovative Events," SocArXiv t3jrq, Center for Open Science.
• Vegard H ghaug Larsen & Leif Anders Thorsrud, 2018. "Business cycle narratives," Working Papers No 6/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • Vegard H. Larsen & Leif Anders Thorsrud, 2019. "Business Cycle Narratives," CESifo Working Paper Series 7468, CESifo.
  • Vegard H. Larsen & Leif Anders Thorsrud, 2018. "Business cycle narratives," Working Paper 2018/3, Norges Bank.
• Michael A. Ribers & Hannes Ullrich, 2019. "Battling Antibiotic Resistance: Can Machine Learning Improve Prescribing?," Discussion Papers of DIW Berlin 1803, DIW Berlin, German Institute for Economic Research.
  • Michael Allan Ribers & Hannes Ullrich, 2019. "Battling antibiotic resistance: can machine learning improve prescribing?," CESifo Working Paper Series 7654, CESifo.
  • Michael Allan Ribers & Hannes Ullrich, 2019. "Battling Antibiotic Resistance: Can Machine Learning Improve Prescribing?," Papers 1906.03044, arXiv.org.
• Svatopluk Kapounek & Zuzana Kucerová, 2019. "Overfunding and Signaling Effects of Herding Behavior in Crowdfunding," CESifo Working Paper Series 7973, CESifo.
• Delatte, Anne-Laure & , & Imbs, Jean, 2019. "The transmission channels of unconventional monetary policy: Evidence from a change in collateral requirements in France," CEPR Discussion Papers 13693, C.E.P.R. Discussion Papers.
  • Anne-Laure Delatte & Pranav Garg & Jean Imbs, 2019. "The transmission channels of unconventional monetary policy: Evidence from a change in collateral requirements in France," Working Papers 2019-07, CEPII research center.
• Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2022. "How is machine learning useful for macroeconomic forecasting?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 920-964, August.
  • Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2019. "How is Machine Learning Useful for Macroeconomic Forecasting?," CIRANO Working Papers 2019s-22, CIRANO.
  • Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & St'ephane Surprenant, 2020. "How is Machine Learning Useful for Macroeconomic Forecasting?," Papers 2008.12477, arXiv.org.
  • Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stephane Surprenant, 2020. "How is Machine Learning Useful for Macroeconomic Forecasting?," Working Papers 20-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Aug 2020.
• Hansen, Stephen & McMahon, Michael & Tong, Matthew, 2019. "The long-run information effect of central bank communication," Journal of Monetary Economics, Elsevier, vol. 108(C), pages 185-202.
  • Hansen, Stephen & McMahon, Michael & Tong, Matthew, 2019. "The long-run information effect of central bank communication," Bank of England working papers 777, Bank of England.
  • McMahon, Michael & , & Tong, Matthew, 2019. "The Long-Run Information Effect of Central Bank Communication," CEPR Discussion Papers 13438, C.E.P.R. Discussion Papers.
  • Hansen, Stephen & McMahon, Michael & Tong, Matthew, 2020. "The long-run information effect of central bank communication," Working Paper Series 2363, European Central Bank.
• Simon Jäger & Benjamin Schoefer & Josef Zweimüller, 2023. "Marginal Jobs and Job Surplus: A Test of the Efficiency of Separations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 90(3), pages 1265-1303.
  • Simon Jäger & Benjamin Schoefer & Josef Zweimüller, 2018. "Marginal jobs and job surplus: a test of the efficiency of separations," ECON - Working Papers 314, Department of Economics - University of Zurich.
  • Zweimüller, Josef & Jäger, Simon & Schoefer, Benjamin, 2019. "Marginal Jobs and Job Surplus: A Test of the Efficiency of Separations," CEPR Discussion Papers 13473, C.E.P.R. Discussion Papers.
  • Simon Jäger & Benjamin Schoefer & Josef Zweimüller, 2019. "Marginal Jobs and Job Surplus: A Test of the Efficiency of Separations," NBER Working Papers 25492, National Bureau of Economic Research, Inc.
  • Jäger, Simon & Schoefer, Benjamin & Zweimüller, Josef, 2019. "Marginal Jobs and Job Surplus: A Test of the Efficiency of Separations," IZA Discussion Papers 12127, Institute of Labor Economics (IZA).
• Maryam Farboodi & Roxana Mihet & Thomas Philippon & Laura Veldkamp, 2019. "Big Data and Firm Dynamics," AEA Papers and Proceedings, American Economic Association, vol. 109, pages 38-42, May.
  • Maryam Farboodi & Roxana Mihet & Thomas Philippon & Laura Veldkamp, 2019. "Big Data and Firm Dynamics," NBER Working Papers 25515, National Bureau of Economic Research, Inc.
  • Veldkamp, Laura & Farboodi, Maryam & Mihet, Roxana, 2019. "Big Data and Firm Dynamics," CEPR Discussion Papers 13489, C.E.P.R. Discussion Papers.
• Blumenstock, Joshua & Chi, Guanghua & Tan, Xu, 2019. "Migration and the Value of Social Networks," CEPR Discussion Papers 13611, C.E.P.R. Discussion Papers.
• Anne-Laure Delatte & Pranav Garg & Jean Imbs, 2019. "The transmission channels of unconventional monetary policy: Evidence from a change in collateral requirements in France," Working Papers 2019-07, CEPII research center.
  • Delatte, Anne-Laure & , & Imbs, Jean, 2019. "The transmission channels of unconventional monetary policy: Evidence from a change in collateral requirements in France," CEPR Discussion Papers 13693, C.E.P.R. Discussion Papers.
• Hannes Mueller & Christopher Rauh, 2022. "The Hard Problem of Prediction for Conflict Prevention," Journal of the European Economic Association, European Economic Association, vol. 20(6), pages 2440-2467.
  • Hannes Mueller & Christopher Rauh, 2019. "The hard problem of prediction for conflict prevention," Cahiers de recherche 2019-02, Universite de Montreal, Departement de sciences economiques.
  • Mueller, Hannes & Rauh, Christopher, 2019. "The Hard Problem of Prediction for Conflict Prevention," CEPR Discussion Papers 13748, C.E.P.R. Discussion Papers.
  • Hannes Mueller & Christopher Rauh, 2021. "The Hard Problem of Prediction for Conflict Prevention," Working Papers 1244, Barcelona School of Economics.
  • Mueller, H. & Rauh, C., 2021. "The Hard Problem of Prediction for Conflict Prevention," Cambridge Working Papers in Economics 2103, Faculty of Economics, University of Cambridge.
  • Mueller, H. & Rauh, C., 2020. "The Hard Problem of Prediction for Conflict Prevention," Cambridge Working Papers in Economics 2015, Faculty of Economics, University of Cambridge.
  • Hannes Mueller & Christopher Rauh, 2019. "The Hard Problem of Prediction for Conflict Prevention," Cahiers de recherche 02-2019, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
• Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2020. "Assessing international commonality in macroeconomic uncertainty and its effects," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(3), pages 273-293, April.
  • Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2018. "Assessing International Commonality in Macroeconomic Uncertainty and Its Effects," Working Papers (Old Series) 1803, Federal Reserve Bank of Cleveland.
  • Marcellino, Massimiliano & Clark, Todd & Carriero, Andrea, 2019. "Assessing International Commonality in Macroeconomic Uncertainty and Its Effects," CEPR Discussion Papers 13970, C.E.P.R. Discussion Papers.
  • Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2019. "Assessing International Commonality in Macroeconomic Uncertainty and Its Effects," Working Papers 18-03R, Federal Reserve Bank of Cleveland.
• Laurent Ferrara & Anna Simoni, 2023. "When are Google Data Useful to Nowcast GDP? An Approach via Preselection and Shrinkage," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(4), pages 1188-1202, October.
  • Laurent Ferrara & Anna Simoni, 2019. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working papers 717, Banque de France.
  • Laurent Ferrara & Anna Simoni, 2023. "When are Google Data Useful to Nowcast GDP? An Approach via Preselection and Shrinkage," Post-Print hal-03919944, HAL.
  • Laurent Ferrara & Anna Simoni, 2020. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," EconomiX Working Papers 2020-11, University of Paris Nanterre, EconomiX.
  • Laurent Ferrara & Anna Simoni, 2019. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working Papers 2019-04, Center for Research in Economics and Statistics.
  • Laurent Ferrara & Anna Simoni, 2020. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Papers 2007.00273, arXiv.org, revised Sep 2022.
  • Laurent Ferrara & Anna Simoni, 2020. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working Papers hal-04159714, HAL.
• Christopoulos, Dimitris K. & McAdam, Peter, 2019. "Efficiency, Inefficiency, And The Mena Frontier," Macroeconomic Dynamics, Cambridge University Press, vol. 23(2), pages 489-521, March.
  • McAdam, Peter & Christopoulos, Dimitris, 2015. "Efficiency, Inefficiency and the MENA Frontier," Working Paper Series 1757, European Central Bank.
  • Cristiano Cantore & Peter Paul Levine & Giovanni Melina & Joseph Pearlman, 2015. "Optimal Fiscal and Monetary Policy, Debt and Crisis Management," School of Economics Discussion Papers 0515, School of Economics, University of Surrey.
• Peter C.B. Phillips & Zhentao Shi, 2019. "Boosting the Hodrick-Prescott Filter," Cowles Foundation Discussion Papers 2192, Cowles Foundation for Research in Economics, Yale University.
• Peter C. B. Phillips & Zhentao Shi, 2021. "Boosting: Why You Can Use The Hp Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 62(2), pages 521-570, May.
  • Peter C. B. Phillips & Zhentao Shi, 2019. "Boosting: Why You Can Use the HP Filter," Papers 1905.00175, arXiv.org, revised Nov 2020.
  • Peter C.B. Phillips & Zhentao Shi, 2019. "Boosting: Why you Can Use the HP Filter," Cowles Foundation Discussion Papers 2212, Cowles Foundation for Research in Economics, Yale University.
• Michael A. Ribers & Hannes Ullrich, 2019. "Artificial Intelligence and Big Data Can Help Contain Resistance to Antibiotics," DIW Weekly Report, DIW Berlin, German Institute for Economic Research, vol. 9(19), pages 169-175.
• Michael A. Ribers & Hannes Ullrich, 2019. "Künstliche Intelligenz und Daten können bei der Eindämmung von Antibiotikaresistenzen helfen," DIW Wochenbericht, DIW Berlin, German Institute for Economic Research, vol. 86(19), pages 335-341.
• Michael Allan Ribers & Hannes Ullrich, 2019. "Battling antibiotic resistance: can machine learning improve prescribing?," CESifo Working Paper Series 7654, CESifo.
  • Michael A. Ribers & Hannes Ullrich, 2019. "Battling Antibiotic Resistance: Can Machine Learning Improve Prescribing?," Discussion Papers of DIW Berlin 1803, DIW Berlin, German Institute for Economic Research.
  • Michael Allan Ribers & Hannes Ullrich, 2019. "Battling Antibiotic Resistance: Can Machine Learning Improve Prescribing?," Papers 1906.03044, arXiv.org.
• Eric M. Bosire, 2019. "Foreign Direct Investments into Eastern Africa Region: The Governance Paradox," International Journal of Economics and Financial Issues, Econjournals, vol. 9(1), pages 169-182.
• Bulat Mukhamediyev & Zhansaya Temerbulatova, 2019. "The Impact of Oil Prices on the Global Competitiveness of National Economies," International Journal of Energy Economics and Policy, Econjournals, vol. 9(6), pages 45-50.
• Kirchkamp, Oliver, 2019. "Importing z-Tree data into R," Journal of Behavioral and Experimental Finance, Elsevier, vol. 22(C), pages 1-2.
• Kolidakis, Stylianos & Botzoris, George & Profillidis, Vassilios & Lemonakis, Panagiotis, 2019. "Road traffic forecasting — A hybrid approach combining Artificial Neural Network with Singular Spectrum Analysis," Economic Analysis and Policy, Elsevier, vol. 64(C), pages 159-171.
• Lopez-Buenache, German, 2019. "The evolution of monetary policy effectiveness under macroeconomic instability," Economic Modelling, Elsevier, vol. 83(C), pages 221-233.
• Pelger, Markus, 2019. "Large-dimensional factor modeling based on high-frequency observations," Journal of Econometrics, Elsevier, vol. 208(1), pages 23-42.
• Dai, Chaoxing & Lu, Kun & Xiu, Dacheng, 2019. "Knowing factors or factor loadings, or neither? Evaluating estimators of large covariance matrices with noisy and asynchronous data," Journal of Econometrics, Elsevier, vol. 208(1), pages 43-79.
• Kim, Donggyu & Fan, Jianqing, 2019. "Factor GARCH-Itô models for high-frequency data with application to large volatility matrix prediction," Journal of Econometrics, Elsevier, vol. 208(2), pages 395-417.
• Fan, Jianqing & Kim, Donggyu, 2019. "Structured volatility matrix estimation for non-synchronized high-frequency financial data," Journal of Econometrics, Elsevier, vol. 209(1), pages 61-78.
• Boot, Tom & Nibbering, Didier, 2019. "Forecasting using random subspace methods," Journal of Econometrics, Elsevier, vol. 209(2), pages 391-406.
  • Tom Boot & Didier Nibbering, 2016. "Forecasting Using Random Subspace Methods," Tinbergen Institute Discussion Papers 16-073/III, Tinbergen Institute, revised 11 Aug 2017.
• Aït-Sahalia, Yacine & Xiu, Dacheng, 2019. "A Hausman test for the presence of market microstructure noise in high frequency data," Journal of Econometrics, Elsevier, vol. 211(1), pages 176-205.
• Harding, Matthew & Lamarche, Carlos, 2019. "A panel quantile approach to attrition bias in Big Data: Evidence from a randomized experiment," Journal of Econometrics, Elsevier, vol. 211(1), pages 61-82.
  • Matthew Harding & Carlos Lamarche, 2018. "A Panel Quantile Approach to Attrition Bias in Big Data: Evidence from a Randomized Experiment," Papers 1808.03364, arXiv.org.
• Chen, Jia & Li, Degui & Linton, Oliver, 2019. "A new semiparametric estimation approach for large dynamic covariance matrices with multiple conditioning variables," Journal of Econometrics, Elsevier, vol. 212(1), pages 155-176.
  • Jia Chen & Degui Li & Oliver Linton, 2018. "A New Semiparametric Estimation Approach for Large Dynamic Covariance Matrices with Multiple Conditioning Variables," Discussion Papers 18/14, Department of Economics, University of York.
  • Chen, J. & Li, D. & Linton, O., 2018. "A New Semiparametric Estimation Approach for Large Dynamic Covariance Matrices with Multiple Conditioning Variables," Cambridge Working Papers in Economics 1876, Faculty of Economics, University of Cambridge.
• Andreasen, Martin M. & Christensen, Jens H.E. & Rudebusch, Glenn D., 2019. "Term Structure Analysis with Big Data: One-Step Estimation Using Bond Prices," Journal of Econometrics, Elsevier, vol. 212(1), pages 26-46.
• Salish, Nazarii & Gleim, Alexander, 2019. "A moment-based notion of time dependence for functional time series," Journal of Econometrics, Elsevier, vol. 212(2), pages 377-392.
• Jongman, Willem M. & Jacobs, Jan P.A.M. & Klein Goldewijk, Geertje M., 2019. "Health and wealth in the Roman Empire," Economics & Human Biology, Elsevier, vol. 34(C), pages 138-150.
• Cepni, Oguzhan & Güney, I.Ethem, 2019. "Local currency bond risk premia: A panel evidence on emerging markets," Emerging Markets Review, Elsevier, vol. 38(C), pages 182-196.
• Trucíos, Carlos & Hotta, Luiz K. & Valls Pereira, Pedro L., 2019. "On the robustness of the principal volatility components," Journal of Empirical Finance, Elsevier, vol. 52(C), pages 201-219.
  • Trucíos Maza, Carlos César & Hotta, Luiz Koodi & Pereira, Pedro L. Valls, 2018. "On the robustness of the principal volatility components," Textos para discussão 474, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
• Barbry, Adrien & Anjos, Miguel F. & Delage, Erick & Schell, Kristen R., 2019. "Robust self-scheduling of a price-maker energy storage facility in the New York electricity market," Energy Economics, Elsevier, vol. 78(C), pages 629-646.
• Møller, Niels Framroze & Andersen, Laura Mørch & Hansen, Lars Gårn & Jensen, Carsten Lynge, 2019. "Can pecuniary and environmental incentives via SMS messaging make households adjust their electricity demand to a fluctuating production?," Energy Economics, Elsevier, vol. 80(C), pages 1050-1058.
• Liu, Jingzhen & Kemp, Alexander, 2019. "Forecasting the sign of U.S. oil and gas industry stock index excess returns employing macroeconomic variables," Energy Economics, Elsevier, vol. 81(C), pages 672-686.
• Chindarkar, Namrata & Goyal, Nihit, 2019. "One price doesn't fit all: An examination of heterogeneity in price elasticity of residential electricity in India," Energy Economics, Elsevier, vol. 81(C), pages 765-778.
• Antoszewski, Michał, 2019. "Wide-range estimation of various substitution elasticities for CES production functions at the sectoral level," Energy Economics, Elsevier, vol. 83(C), pages 272-289.
• Tissaoui, Kais, 2019. "Forecasting implied volatility risk indexes: International evidence using Hammerstein-ARX approach," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 232-249.
• Aslanidis, Nektarios & Christiansen, Charlotte & Cipollini, Andrea, 2019. "Predicting bond betas using macro-finance variables," Finance Research Letters, Elsevier, vol. 29(C), pages 193-199.
  • Nektarios Aslanidis & Charlotte Christiansen & Andrea Cipollini, 2017. "Predicting Bond Betas using Macro-Finance Variables," CREATES Research Papers 2017-01, Department of Economics and Business Economics, Aarhus University.
  • Aslanidis, Nektarios, & Christiansen, Charlotte & Cipollini, Andrea & Bons -- Models matemàtics, 2018. "Predicting Bond Betas using Macro-Finance Variables," Working Papers 2072/306546, Universitat Rovira i Virgili, Department of Economics.
• Demetrescu, Matei & Hacıoğlu Hoke, Sinem, 2019. "Predictive regressions under asymmetric loss: Factor augmentation and model selection," International Journal of Forecasting, Elsevier, vol. 35(1), pages 80-99.
  • Demetrescu, Matei & Hacioglu Hoke, Sinem, 2018. "Predictive regressions under asymmetric loss: factor augmentation and model selection," Bank of England working papers 723, Bank of England.
• Panagiotelis, Anastasios & Athanasopoulos, George & Hyndman, Rob J. & Jiang, Bin & Vahid, Farshid, 2019. "Macroeconomic forecasting for Australia using a large number of predictors," International Journal of Forecasting, Elsevier, vol. 35(2), pages 616-633.
  • Bin Jiang & George Athanasopoulos & Rob J Hyndman & Anastasios Panagiotelis & Farshid Vahid, 2017. "Macroeconomic forecasting for Australia using a large number of predictors," Monash Econometrics and Business Statistics Working Papers 2/17, Monash University, Department of Econometrics and Business Statistics.
• Szafranek, Karol, 2019. "Bagged neural networks for forecasting Polish (low) inflation," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1042-1059.
  • Karol Szafranek, 2017. "Bagged artificial neural networks in forecasting inflation: An extensive comparison with current modelling frameworks," NBP Working Papers 262, Narodowy Bank Polski.
• Jeannine Bailliu & Xinfen Han & Mark Kruger & Yu-Hsien Liu & Sri Thanabalasingam, 2019. "Can media and text analytics provide insights into labour market conditions in China?," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Are post-crisis statistical initiatives completed?, volume 49, Bank for International Settlements.
  • Bailliu, Jeannine & Han, Xinfen & Kruger, Mark & Liu, Yu-Hsien & Thanabalasingam, Sri, 2019. "Can media and text analytics provide insights into labour market conditions in China?," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1118-1130.
  • Bailliu, Jeannine & Han, Xinfen & Kruger, Mark & Liu, Yu-Hsien & Thanabalasingam, Sri, 2018. "Can media and text analytics provide insights into labour market conditions in China?," BOFIT Discussion Papers 9/2018, Bank of Finland Institute for Emerging Economies (BOFIT).
  • Jeannine Bailliu & Xinfen Han & Mark Kruger & Yu-Hsien Liu & Sri Thanabalasingam, 2018. "Can Media and Text Analytics Provide Insights into Labour Market Conditions in China?," Staff Working Papers 18-12, Bank of Canada.
• Spruk, Rok & Kovac, Mitja, 2019. "Replicating and extending Martin-Quinn scores," International Review of Law and Economics, Elsevier, vol. 60(C).
• Panayides, Marios A. & Shohfi, Thomas D. & Smith, Jared D., 2019. "Bulk volume classification and information detection," Journal of Banking & Finance, Elsevier, vol. 103(C), pages 113-129.
• Bulusu, Narayan & Guérin, Pierre, 2019. "What drives interbank loans? Evidence from Canada," Journal of Banking & Finance, Elsevier, vol. 106(C), pages 427-444.
  • Narayan Bulusu & Pierre Guérin, 2018. "What Drives Interbank Loans? Evidence from Canada," Staff Working Papers 18-5, Bank of Canada.
• Grajzl, Peter & Murrell, Peter, 2019. "Toward understanding 17th century English culture: A structural topic model of Francis Bacon's ideas," Journal of Comparative Economics, Elsevier, vol. 47(1), pages 111-135.
  • Peter Grajzl & Peter Murrell, 2017. "Toward Understanding 17th Century English Culture: A Structural Topic Model of Francis Bacon's Ideas," CESifo Working Paper Series 6443, CESifo.
• Crea, Giovanni & Galizzi, Matteo M. & Linnosmaa, Ismo & Miraldo, Marisa, 2019. "Physician altruism and moral hazard: (no) Evidence from Finnish national prescriptions data," Journal of Health Economics, Elsevier, vol. 65(C), pages 153-169.
  • Crea, Giovanni & Galizzi, Matteo M. & Linnosmaa, Ismo & Miraldo, Marisa, 2019. "Physician altruism and moral hazard: (no) evidence from Finnish national prescriptions data," LSE Research Online Documents on Economics 100301, London School of Economics and Political Science, LSE Library.
• Fiorelli, Cristiana & Meliciani, Valentina, 2019. "Economic growth in the era of unconventional monetary instruments: A FAVAR approach," Journal of Macroeconomics, Elsevier, vol. 62(C).
• Tran, Ngoc M. & Burdejová, Petra & Ospienko, Maria & Härdle, Wolfgang K., 2019. "Principal component analysis in an asymmetric norm," Journal of Multivariate Analysis, Elsevier, vol. 171(C), pages 1-21.
  • Tran, Ngoc Mai & Burdejová, Petra & Osipenko, Maria & Härdle, Wolfgang Karl, 2016. "Principal component analysis in an asymmetric norm," SFB 649 Discussion Papers 2016-040, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
• Sorić, Petar & Lolić, Ivana & Claveria, Oscar & Monte, Enric & Torra, Salvador, 2019. "Unemployment expectations: A socio-demographic analysis of the effect of news," Labour Economics, Elsevier, vol. 60(C), pages 64-74.
• Hansen, Stephen & McMahon, Michael & Tong, Matthew, 2019. "The long-run information effect of central bank communication," Journal of Monetary Economics, Elsevier, vol. 108(C), pages 185-202.
  • McMahon, Michael & , & Tong, Matthew, 2019. "The Long-Run Information Effect of Central Bank Communication," CEPR Discussion Papers 13438, C.E.P.R. Discussion Papers.
  • Hansen, Stephen & McMahon, Michael & Tong, Matthew, 2019. "The long-run information effect of central bank communication," Bank of England working papers 777, Bank of England.
  • Hansen, Stephen & McMahon, Michael & Tong, Matthew, 2020. "The long-run information effect of central bank communication," Working Paper Series 2363, European Central Bank.
• Brady, Ryan R. & Insler, Michael A., 2019. "Order of play advantage in sequential tournaments: Evidence from randomized settings in professional golf," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 79(C), pages 79-92.
  • Ryan Brady & Michael Insler, 2017. "Order of Play Advantage in Sequential Tournaments: Evidence from randomized settings in professional golf," Departmental Working Papers 54, United States Naval Academy Department of Economics.
• Christian Gross & Pierre L. Siklos, 2020. "Analyzing credit risk transmission to the nonfinancial sector in Europe: A network approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 61-81, January.
  • Christian Gross & Pierre L. Siklos, 2018. "Analyzing Credit Risk Transmission to the Non-Financial Sector in Europe: A Network Approach," CQE Working Papers 7218, Center for Quantitative Economics (CQE), University of Muenster.
  • Christian Gross & Pierre L. Siklos, 2019. "Analyzing credit risk transmission to the non-financial sector in Europe: A network approach," CAMA Working Papers 2019-43, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Gross, Christian & Siklos, Pierre, 2018. "Analyzing credit risk transmission to the non-financial sector in Europe: a network approach," ESRB Working Paper Series 78, European Systemic Risk Board.
  • Groß, Christian, 2019. "Analyzing credit risk transmission to the non-financial sector in Europe: a network approach," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203645, Verein für Socialpolitik / German Economic Association.
• Joshua C. C. Chan, 2022. "Asymmetric conjugate priors for large Bayesian VARs," Quantitative Economics, Econometric Society, vol. 13(3), pages 1145-1169, July.
  • Joshua C. C. Chan, 2019. "Asymmetric conjugate priors for large Bayesian VARs," CAMA Working Papers 2019-51, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Joshua C. C. Chan, 2021. "Asymmetric Conjugate Priors for Large Bayesian VARs," Papers 2111.07170, arXiv.org.
• Hilde C. Bjørnland & Julia Zhulanova, 2018. "The Shale Oil Boom and the U.S. Economy: Spillovers and Time-Varying Effects," Working Papers No 8/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • Hilde C. Bjørnland & Julia Zhulanova, 2019. "The shale oil boom and the US economy: Spillovers and time-varying effects," CAMA Working Papers 2019-59, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Hilde C. Bjørnland & Julia Zhulanova, 2019. "The shale oil boom and the U.S. economy: Spillovers and time-varying effects," Working Paper 2019/14, Norges Bank.
• Chan, Joshua C.C., 2021. "Minnesota-type adaptive hierarchical priors for large Bayesian VARs," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1212-1226.
  • Joshua C. C. Chan, 2019. "Minnesota-type adaptive hierarchical priors for large Bayesian VARs," CAMA Working Papers 2019-61, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Joshua C. C. Chan, 2023. "Large Hybrid Time-Varying Parameter VARs," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(3), pages 890-905, July.
  • Joshua C.C. Chan, 2019. "Large hybrid time-varying parameter VARs," CAMA Working Papers 2019-77, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Joshua C. C. Chan, 2022. "Large Hybrid Time-Varying Parameter VARs," Papers 2201.07303, arXiv.org, revised Jun 2022.
• Christopher S. Henry & Tamás Ilyés, 2019. "Effectiveness of Stratified Random Sampling for Payment Card Acceptance and Usage," Advances in Econometrics, in: The Econometrics of Complex Survey Data, volume 39, pages 35-57, Emerald Group Publishing Limited.
  • Christopher S. Henry & Tamás Ilyés, 2019. "Effectiveness of Stratified Random Sampling for Payment Card Acceptance and Usage," Post-Print hal-03182306, HAL.
• Jianghao Chu & Tae-Hwy Lee & Aman Ullah, 2019. "Variable Selection in Sparse Semiparametric Single Index Models," Advances in Econometrics, in: Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling: Part B, volume 40, pages 65-88, Emerald Group Publishing Limited.
  • Tae-Hwy Lee & Jianghao Chu & Aman Ullah, 2018. "Variable Selection in Sparse Semiparametric Single Index Models," Working Papers 201908, University of California at Riverside, Department of Economics.
• Ya Qian & Wolfgang Härdle & Cathy Yi-Hsuan Chen, 2019. "Modelling industry interdependency dynamics in a network context," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 37(1), pages 50-70, December.
• Imaduddin Sahabat & Tumpak Silalahi & Ratih Indrastuti & Marizsa Herlina, 2019. "The interbank payment network and financial system stability," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 37(1), pages 1-17, September.
• Adriana Ramírez Rocha & L. Arturo Bernal Ponce & Mauricio Cervantes Zepeda, 2019. "Differences in the interest rates of microfinance institutions in some emerging markets economies: An HLM approach/Diferencias en las tasas de interés entre instituciones financieras de algunas econo," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, vol. 34(2), pages 275-307.
• Eoghan O'Neill & Melvyn Weeks, 2019. "Causal Tree Estimation of Heterogeneous Household Response to Time-Of-Use Electricity Pricing Schemes," Working Papers EPRG 1906, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
• Garnov & A. & Zvyagin & L. & Sviridova & O., 2019. "System Data Analysis: Innovative Technologies, Methods and Techniques," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(Special 1), pages 26-39.
• Christopher L. Foote & Lara Loewenstein & Paul S. Willen, 2018. "Technological Innovation in Mortgage Underwriting and the Growth in Credit: 1985-2015," Working Papers (Old Series) 1816, Federal Reserve Bank of Cleveland.
  • Christopher L. Foote & Lara Loewenstein & Paul S. Willen, 2019. "Technological innovation in mortgage underwriting and the growth in credit, 1985–2015," Working Papers 19-11, Federal Reserve Bank of Boston.
• Charles B. Perkins & J. Christina Wang, 2019. "How Magic a Bullet Is Machine Learning for Credit Analysis? An Exploration with FinTech Lending Data," Working Papers 19-16, Federal Reserve Bank of Boston.
• Jack DeWaard & Janna Johnson & Stephan D. Whitaker, 2019. "Internal Migration in the United States: A Comprehensive Comparative Assessment of the Consumer Credit Panel," Working Papers 18-04R, Federal Reserve Bank of Cleveland.
• Aditya Aladangady & Shifrah Aron-Dine & Wendy Dunn & Laura Feiveson & Paul Lengermann & Claudia Sahm, 2021. "From Transaction Data to Economic Statistics: Constructing Real-Time, High-Frequency, Geographic Measures of Consumer Spending," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 115-145, National Bureau of Economic Research, Inc.
  • Aditya Aladangady & Shifrah Aron-Dine & Wendy Dunn & Laura Feiveson & Paul Lengermann & Claudia Sahm, 2019. "From Transactions Data to Economic Statistics: Constructing Real-time, High-frequency, Geographic Measures of Consumer Spending," NBER Working Papers 26253, National Bureau of Economic Research, Inc.
  • Aditya Aladangady & Shifrah Aron-Dine & Wendy E. Dunn & Laura Feiveson & Paul Lengermann & Claudia R. Sahm, 2019. "From Transactions Data to Economic Statistics: Constructing Real-time, High-frequency, Geographic Measures of Consumer Spending," Finance and Economics Discussion Series 2019-057, Board of Governors of the Federal Reserve System (U.S.).
• Tomaz Cajner & Leland D. Crane & Ryan A. Decker & Adrian Hamins-Puertolas & Christopher Kurz, 2019. "Improving the Accuracy of Economic Measurement with Multiple Data Sources: The Case of Payroll Employment Data," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 147-170, National Bureau of Economic Research, Inc.
  • Tomaz Cajner & Leland D. Crane & Ryan A. Decker & Adrian Hamins-Puertolas & Christopher Kurz, 2019. "Improving the Accuracy of Economic Measurement with Multiple Data Sources: The Case of Payroll Employment Data," NBER Working Papers 26033, National Bureau of Economic Research, Inc.
  • Tomaz Cajner & Leland D. Crane & Ryan A. Decker & Adrian Hamins-Puertolas & Christopher J. Kurz, 2019. "Improving the Accuracy of Economic Measurement with Multiple Data Sources: The Case of Payroll Employment Data," Finance and Economics Discussion Series 2019-065, Board of Governors of the Federal Reserve System (U.S.).
• Thomas R. Cook & Taeyoung Doh, 2019. "Assessing Macroeconomic Tail Risks in a Data-Rich Environment," Research Working Paper RWP 19-12, Federal Reserve Bank of Kansas City.
• Simon Freyaldenhoven, 2017. "A Generalized Factor Model with Local Factors," 2017 Papers pfr361, Job Market Papers.
  • Simon Freyaldenhoven, 2019. "A Generalized Factor Model with Local Factors," Working Papers 19-23, Federal Reserve Bank of Philadelphia.
• Korobilis, Dimitris, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," MPRA Paper 96079, University Library of Munich, Germany.
  • Dimitris Korobilis, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," Working Papers 2019-07, Business School - Economics, University of Glasgow.
  • Dimitris Korobilis, 2020. "High-dimensional macroeconomic forecasting using message passing algorithms," Papers 2004.11485, arXiv.org.
  • Dimitris Korobilis, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," Working Paper series 19-17, Rimini Centre for Economic Analysis.
• Dimitris Korobilis, 2021. "High-Dimensional Macroeconomic Forecasting Using Message Passing Algorithms," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(2), pages 493-504, March.
  • Korobilis, Dimitris, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," MPRA Paper 96079, University Library of Munich, Germany.
  • Dimitris Korobilis, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," Working Papers 2019_07, Business School - Economics, University of Glasgow.
  • Dimitris Korobilis, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," Working Paper series 19-17, Rimini Centre for Economic Analysis.
  • Dimitris Korobilis, 2020. "High-dimensional macroeconomic forecasting using message passing algorithms," Papers 2004.11485, arXiv.org.
• Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers halshs-02262202, HAL.
  • Catherine Doz & Peter Fuleky, 2020. "Dynamic Factor Models," Post-Print halshs-02491811, HAL.
  • Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers 2019-4, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.
  • Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," PSE Working Papers halshs-02262202, HAL.
  • Catherine Doz & Peter Fuleky, 2020. "Dynamic Factor Models," PSE-Ecole d'économie de Paris (Postprint) halshs-02491811, HAL.
• Christopher S. Henry & Tamás Ilyés, 2019. "Effectiveness of Stratified Random Sampling for Payment Card Acceptance and Usage," Advances in Econometrics, in: The Econometrics of Complex Survey Data, volume 39, pages 35-57, Emerald Group Publishing Limited.
  • Christopher S. Henry & Tamás Ilyés, 2019. "Effectiveness of Stratified Random Sampling for Payment Card Acceptance and Usage," Post-Print hal-03182306, HAL.
• Christophe Hurlin & Christophe Pérignon, 2019. "Machine learning et nouvelles sources de données pour le scoring de crédit," Revue d'économie financière, Association d'économie financière, vol. 0(3), pages 21-50.
  • Christophe Hurlin & Christophe Pérignon, 2019. "Machine Learning et nouvelles sources de données pour le scoring de crédit," Working Papers halshs-02377886, HAL.
  • Christophe Hurlin & Christophe Pérignon, 2019. "Machine learning et nouvelles sources de données pour le scoring de crédit," Post-Print hal-03532418, HAL.
  • Christophe HURLIN & Christophe PERIGNON, 2019. "Machine Learning et nouvelles sources de données pour le scoring de crédit," LEO Working Papers / DR LEO 2739, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
• Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers 2019-4, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.
  • Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," PSE Working Papers halshs-02262202, HAL.
  • Catherine Doz & Peter Fuleky, 2020. "Dynamic Factor Models," Post-Print halshs-02491811, HAL.
  • Catherine Doz & Peter Fuleky, 2020. "Dynamic Factor Models," PSE-Ecole d'économie de Paris (Postprint) halshs-02491811, HAL.
  • Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers halshs-02262202, HAL.
• Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers 2019-4, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.
  • Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers halshs-02262202, HAL.
  • Catherine Doz & Peter Fuleky, 2020. "Dynamic Factor Models," Post-Print halshs-02491811, HAL.
  • Catherine Doz & Peter Fuleky, 2020. "Dynamic Factor Models," PSE-Ecole d'économie de Paris (Postprint) halshs-02491811, HAL.
  • Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," PSE Working Papers halshs-02262202, HAL.
• Christophe Hurlin & Christophe Pérignon, 2019. "Machine learning et nouvelles sources de données pour le scoring de crédit," Revue d'économie financière, Association d'économie financière, vol. 0(3), pages 21-50.
  • Christophe Hurlin & Christophe Pérignon, 2019. "Machine learning et nouvelles sources de données pour le scoring de crédit," Post-Print hal-03532418, HAL.
  • Christophe Hurlin & Christophe Pérignon, 2019. "Machine Learning et nouvelles sources de données pour le scoring de crédit," Working Papers halshs-02377886, HAL.
  • Christophe HURLIN & Christophe PERIGNON, 2019. "Machine Learning et nouvelles sources de données pour le scoring de crédit," LEO Working Papers / DR LEO 2739, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
• Gunawan, David & Dang, Khue-Dung & Quiroz, Matias & Kohn, Robert & Tran, Minh-Ngoc, 2019. "Subsampling Sequential Monte Carlo for Static Bayesian Models," Working Paper Series 371, Sveriges Riksbank (Central Bank of Sweden).
• Dang, Khue-Dung & Quiroz, Matias & Kohn, Robert & Tran, Minh-Ngoc & Villani, Mattias, 2019. "Hamiltonian Monte Carlo with Energy Conserving Subsampling," Working Paper Series 372, Sveriges Riksbank (Central Bank of Sweden).
• Grodecka, Anna & Hull, Isaiah, 2019. "The Impact of Local Taxes and Public Services on Property Values," Working Paper Series 374, Sveriges Riksbank (Central Bank of Sweden).
• Koen Jochmans & Martin Weidner, 2019. "Fixed‐Effect Regressions on Network Data," Econometrica, Econometric Society, vol. 87(5), pages 1543-1560, September.
  • Koen Jochmans & Martin Weidner, 2016. "Fixed-effect regressions on network data," CeMMAP working papers CWP32/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2019. "Fixed-effect regressions on network data," CeMMAP working papers CWP16/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2018. "Fixed-effect regressions on network data," CeMMAP working papers CWP44/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2017. "Fixed-effect regressions on network data," CeMMAP working papers CWP26/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Jochmans, K. & Weidner, M., 2019. "Fixed-Effect Regressions on Network Data," Cambridge Working Papers in Economics 1938, Faculty of Economics, University of Cambridge.
  • Koen Jochmans & Martin Weidner, 2016. "Fixed-Effect Regressions on Network Data," Papers 1608.01532, arXiv.org, revised Apr 2019.
  • Koen Jochmans & Martin Weidner, 2017. "Fixed-effect regressions on network data," CeMMAP working papers 26/17, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2016. "Fixed-effect regressions on network data," CeMMAP working papers 32/16, Institute for Fiscal Studies.
• Pedro Carneiro & Sokbae Lee & Daniel Wilhelm, 2020. "Optimal data collection for randomized control trials," The Econometrics Journal, Royal Economic Society, vol. 23(1), pages 1-31.
  • Carneiro, Pedro & Lee, Sokbae & Wilhelm, Daniel, 2016. "Optimal Data Collection for Randomized Control Trials," IZA Discussion Papers 9908, Institute of Labor Economics (IZA).
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2019. "Optimal Data Collection for Randomized Control Trials," CeMMAP working papers CWP21/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers 15/17, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers 45/17, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers CWP15/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae Lee & Daniel Wilhelm, 2016. "Optimal Data Collection for Randomized Control Trials," Papers 1603.03675, arXiv.org, revised Aug 2016.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers CWP45/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2016. "Optimal data collection for randomized control trials," CeMMAP working papers 15/16, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2016. "Optimal data collection for randomized control trials," CeMMAP working papers CWP15/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
• Victor Chernozhukov & Jerry A. Hausman & Whitney K. Newey, 2019. "Demand Analysis with Many Prices," NBER Working Papers 26424, National Bureau of Economic Research, Inc.
  • Victor Chernozhukov & Jerry Hausman & Whitney K. Newey, 2019. "Demand analysis with many prices," CeMMAP working papers CWP59/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
• Clément Nestrigue & Laure Com-Ruelle & Damien Bricard, 2019. "Analyse séquentielle et déterminants des parcours de soins en phase post-aiguë d'un Accident vasculaire cérébral (AVC)," Working Papers DT82, IRDES institut for research and information in health economics, revised Oct 2019.
• Rui Evangelista & Esmeralda A. Ramalho & João Andrade e Silva, 2019. "On the use of Hedonic Regression Models to Measure the Effect of Energy Efficiency on Residential Property Transaction Prices: Evidence for Portugal and Selected Data Issues," Working Papers REM 2019/64, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
• Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2020. "lassopack: Model selection and prediction with regularized regression in Stata," Stata Journal, StataCorp LP, vol. 20(1), pages 176-235, March.
  • Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2019. "lassopack: Model selection and prediction with regularized regression in Stata," Papers 1901.05397, arXiv.org.
  • Ahrens, Achim & Hansen, Christian B. & Schaffer, Mark E, 2019. "lassopack: Model Selection and Prediction with Regularized Regression in Stata," IZA Discussion Papers 12081, Institute of Labor Economics (IZA).
• Simon Jäger & Benjamin Schoefer & Josef Zweimüller, 2023. "Marginal Jobs and Job Surplus: A Test of the Efficiency of Separations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 90(3), pages 1265-1303.
  • Simon Jäger & Benjamin Schoefer & Josef Zweimüller, 2018. "Marginal jobs and job surplus: a test of the efficiency of separations," ECON - Working Papers 314, Department of Economics - University of Zurich.
  • Jäger, Simon & Schoefer, Benjamin & Zweimüller, Josef, 2019. "Marginal Jobs and Job Surplus: A Test of the Efficiency of Separations," IZA Discussion Papers 12127, Institute of Labor Economics (IZA).
  • Simon Jäger & Benjamin Schoefer & Josef Zweimüller, 2019. "Marginal Jobs and Job Surplus: A Test of the Efficiency of Separations," NBER Working Papers 25492, National Bureau of Economic Research, Inc.
  • Zweimüller, Josef & Jäger, Simon & Schoefer, Benjamin, 2019. "Marginal Jobs and Job Surplus: A Test of the Efficiency of Separations," CEPR Discussion Papers 13473, C.E.P.R. Discussion Papers.
• Max Nathan & Anna Rosso, 2017. "Innovative events," Development Working Papers 429, Centro Studi Luca d'Agliano, University of Milano, revised 08 Apr 2019.
  • Nathan, Max & Rosso, Anna, 2019. "Innovative Events," IZA Discussion Papers 12213, Institute of Labor Economics (IZA).
  • Max Nathan & Anna Rosso, 2019. "Innovative events," CEP Discussion Papers dp1607, Centre for Economic Performance, LSE.
  • Nathan, Max & Rosso, Anna, 2019. "Innovative events," LSE Research Online Documents on Economics 102626, London School of Economics and Political Science, LSE Library.
  • Nathan, Max & Rosso, Anna, 2019. "Innovative Events," SocArXiv t3jrq, Center for Open Science.
• Lu Jinks & Thomas J. Kniesner & John Leeth & Anthony T. Lo Sasso, 2020. "Opting out of workers’ compensation: Non-subscription in Texas and its effects," Journal of Risk and Uncertainty, Springer, vol. 60(1), pages 53-76, February.
  • Jinks, Lu & Kniesner, Thomas J. & Leeth, John D. & Lo Sasso, Anthony T., 2019. "Opting out of Workers' Compensation: Non-Subscription in Texas and Its Effects," IZA Discussion Papers 12290, Institute of Labor Economics (IZA).
• Alacevich, Caterina & Nicodemo, Catia, 2019. "Immigration and Work-Related Injuries: Evidence from Italian Administrative Data," IZA Discussion Papers 12510, Institute of Labor Economics (IZA).
• Randolph Luca Bruno & Elodie Douarin & Julia Korosteleva & Slavo Radosevic, 2019. "Determinants of Productivity Gap in the European Union: A Multilevel Perspective," LEM Papers Series 2019/25, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  • Bruno, Randolph Luca & Douarin, Elodie & Korosteleva, Julia & Radosevic, Slavo, 2019. "Determinants of Productivity Gap in the European Union: A Multilevel Perspective," IZA Discussion Papers 12542, Institute of Labor Economics (IZA).
• Harold D. Chiang, 2018. "Many Average Partial Effects: with An Application to Text Regression," Papers 1812.09397, arXiv.org, revised Jan 2022.
  • Harold D. Chiang, 2019. "Many Average Partial Effects: with an Application to Text Regression," 2019 Papers pch1836, Job Market Papers.
• Rituparna Sen & Manavathi Subramaniam, 2019. "Stylized Facts of the Indian Stock Market," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 26(4), pages 479-493, December.
• Oscar Claveria & Enric Monte & Salvador Torra, 2019. "Empirical modelling of survey-based expectations for the design of economic indicators in five European regions," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 46(2), pages 205-227, May.
• Qing Luo & Daniel A. Griffith & Huayi Wu, 2019. "Spatial autocorrelation for massive spatial data: verification of efficiency and statistical power asymptotics," Journal of Geographical Systems, Springer, vol. 21(2), pages 237-269, June.
• Kim Kaivanto & Peng Zhang, 2019. "Popular Music, Sentiment, and Noise Trading," Working Papers 279326509, Lancaster University Management School, Economics Department.
• Christophe Hurlin & Christophe Pérignon, 2019. "Machine learning et nouvelles sources de données pour le scoring de crédit," Revue d'économie financière, Association d'économie financière, vol. 0(3), pages 21-50.
  • Christophe Hurlin & Christophe Pérignon, 2019. "Machine Learning et nouvelles sources de données pour le scoring de crédit," Working Papers halshs-02377886, HAL.
  • Christophe HURLIN & Christophe PERIGNON, 2019. "Machine Learning et nouvelles sources de données pour le scoring de crédit," LEO Working Papers / DR LEO 2739, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
  • Christophe Hurlin & Christophe Pérignon, 2019. "Machine learning et nouvelles sources de données pour le scoring de crédit," Post-Print hal-03532418, HAL.
• Andrea Bastianin, 2020. "Robust measures of skewness and kurtosis for macroeconomic and financial time series," Applied Economics, Taylor & Francis Journals, vol. 52(7), pages 637-670, February.
  • Andrea Bastianin, 2019. "Robust measures of skewness and kurtosis for macroeconomic and financial time series," Working Papers 408, University of Milano-Bicocca, Department of Economics, revised 06 May 2019.
• Tamás Sikos T. & Csaba József Kovács, 2019. "The Silver Generation as Potential Purchasing Power in Budapest: a Case Study," Theory Methodology Practice (TMP), Faculty of Economics, University of Miskolc, vol. 15(02), pages 53-63.
• Priyanga Dilini Talagala & Rob J Hyndman & Kate Smith-Miles, 2019. "Anomaly Detection in High Dimensional Data," Monash Econometrics and Business Statistics Working Papers 20/19, Monash University, Department of Econometrics and Business Statistics.
• Bo Zhang & Jiti Gao & Guangming Pan & Yanrong Yang, 2019. "Spiked Eigenvalues of High-Dimensional Separable Sample Covariance Matrices," Monash Econometrics and Business Statistics Working Papers 31/19, Monash University, Department of Econometrics and Business Statistics.
• Hannes Mueller & Christopher Rauh, 2022. "The Hard Problem of Prediction for Conflict Prevention," Journal of the European Economic Association, European Economic Association, vol. 20(6), pages 2440-2467.
  • Mueller, Hannes & Rauh, Christopher, 2019. "The Hard Problem of Prediction for Conflict Prevention," CEPR Discussion Papers 13748, C.E.P.R. Discussion Papers.
  • Hannes Mueller & Christopher Rauh, 2019. "The hard problem of prediction for conflict prevention," Cahiers de recherche 2019-02, Universite de Montreal, Departement de sciences economiques.
  • Hannes Mueller & Christopher Rauh, 2021. "The Hard Problem of Prediction for Conflict Prevention," Working Papers 1244, Barcelona School of Economics.
  • Mueller, H. & Rauh, C., 2021. "The Hard Problem of Prediction for Conflict Prevention," Cambridge Working Papers in Economics 2103, Faculty of Economics, University of Cambridge.
  • Mueller, H. & Rauh, C., 2020. "The Hard Problem of Prediction for Conflict Prevention," Cambridge Working Papers in Economics 2015, Faculty of Economics, University of Cambridge.
  • Hannes Mueller & Christopher Rauh, 2019. "The Hard Problem of Prediction for Conflict Prevention," Cahiers de recherche 02-2019, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
• Hannes Mueller & Christopher Rauh, 2022. "The Hard Problem of Prediction for Conflict Prevention," Journal of the European Economic Association, European Economic Association, vol. 20(6), pages 2440-2467.
  • Hannes Mueller & Christopher Rauh, 2019. "The hard problem of prediction for conflict prevention," Cahiers de recherche 2019-02, Universite de Montreal, Departement de sciences economiques.
  • Mueller, H. & Rauh, C., 2020. "The Hard Problem of Prediction for Conflict Prevention," Cambridge Working Papers in Economics 2015, Faculty of Economics, University of Cambridge.
  • Hannes Mueller & Christopher Rauh, 2019. "The Hard Problem of Prediction for Conflict Prevention," Cahiers de recherche 02-2019, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
  • Hannes Mueller & Christopher Rauh, 2021. "The Hard Problem of Prediction for Conflict Prevention," Working Papers 1244, Barcelona School of Economics.
  • Mueller, H. & Rauh, C., 2021. "The Hard Problem of Prediction for Conflict Prevention," Cambridge Working Papers in Economics 2103, Faculty of Economics, University of Cambridge.
  • Mueller, Hannes & Rauh, Christopher, 2019. "The Hard Problem of Prediction for Conflict Prevention," CEPR Discussion Papers 13748, C.E.P.R. Discussion Papers.
• Paweł Macias & Damian Stelmasiak, 2019. "Food inflation nowcasting with web scraped data," NBP Working Papers 302, Narodowy Bank Polski.
• Aditya Aladangady & Shifrah Aron-Dine & Wendy Dunn & Laura Feiveson & Paul Lengermann & Claudia Sahm, 2021. "From Transaction Data to Economic Statistics: Constructing Real-Time, High-Frequency, Geographic Measures of Consumer Spending," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 115-145, National Bureau of Economic Research, Inc.
  • Aditya Aladangady & Shifrah Aron-Dine & Wendy E. Dunn & Laura Feiveson & Paul Lengermann & Claudia R. Sahm, 2019. "From Transactions Data to Economic Statistics: Constructing Real-time, High-frequency, Geographic Measures of Consumer Spending," Finance and Economics Discussion Series 2019-057, Board of Governors of the Federal Reserve System (U.S.).
  • Aditya Aladangady & Shifrah Aron-Dine & Wendy Dunn & Laura Feiveson & Paul Lengermann & Claudia Sahm, 2019. "From Transactions Data to Economic Statistics: Constructing Real-time, High-frequency, Geographic Measures of Consumer Spending," NBER Working Papers 26253, National Bureau of Economic Research, Inc.
• Jeffrey C. Chen & Abe Dunn & Kyle Hood & Alexander Driessen & Andrea Batch, 2019. "Off to the Races: A Comparison of Machine Learning and Alternative Data for Predicting Economic Indicators," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 373-402, National Bureau of Economic Research, Inc.
• Rishab Guha & Serena Ng, 2019. "A Machine Learning Analysis of Seasonal and Cyclical Sales in Weekly Scanner Data," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 403-436, National Bureau of Economic Research, Inc.
  • Rishab Guha & Serena Ng, 2019. "A Machine Learning Analysis of Seasonal and Cyclical Sales in Weekly Scanner Data," NBER Working Papers 25899, National Bureau of Economic Research, Inc.
• Rebecca J. Hutchinson, 2019. "Improving Retail Trade Data Products Using Alternative Data Sources," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 99-114, National Bureau of Economic Research, Inc.
• Tomaz Cajner & Leland D. Crane & Ryan A. Decker & Adrian Hamins-Puertolas & Christopher Kurz, 2019. "Improving the Accuracy of Economic Measurement with Multiple Data Sources: The Case of Payroll Employment Data," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 147-170, National Bureau of Economic Research, Inc.
  • Tomaz Cajner & Leland D. Crane & Ryan A. Decker & Adrian Hamins-Puertolas & Christopher J. Kurz, 2019. "Improving the Accuracy of Economic Measurement with Multiple Data Sources: The Case of Payroll Employment Data," Finance and Economics Discussion Series 2019-065, Board of Governors of the Federal Reserve System (U.S.).
  • Tomaz Cajner & Leland D. Crane & Ryan A. Decker & Adrian Hamins-Puertolas & Christopher Kurz, 2019. "Improving the Accuracy of Economic Measurement with Multiple Data Sources: The Case of Payroll Employment Data," NBER Working Papers 26033, National Bureau of Economic Research, Inc.
• Arthur Turrell & Bradley Speigner & Jyldyz Djumalieva & David Copple & James Thurgood, 2019. "Transforming Naturally Occurring Text Data into Economic Statistics: The Case of Online Job Vacancy Postings," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 173-207, National Bureau of Economic Research, Inc.
  • Arthur Turrell & Bradley J. Speigner & Jyldyz Djumalieva & David Copple & James Thurgood, 2019. "Transforming Naturally Occurring Text Data Into Economic Statistics: The Case of Online Job Vacancy Postings," NBER Working Papers 25837, National Bureau of Economic Research, Inc.
• John Cuffe & Sudip Bhattacharjee & Ugochukwu Etudo & Justin C. Smith & Nevada Basdeo & Nathaniel Burbank & Shawn R. Roberts, 2019. "Using Public Data to Generate Industrial Classification Codes," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 229-246, National Bureau of Economic Research, Inc.
• Michela Giorcelli & Nicola Lacetera & Astrid Marinoni, 2022. "How does scientific progress affect cultural changes? A digital text analysis," Journal of Economic Growth, Springer, vol. 27(3), pages 415-452, September.
  • Michela Giorcelli & Nicola Lacetera & Astrid Marinoni, 2019. "How Does Scientific Progress Affect Cultural Changes? A Digital Text Analysis," NBER Working Papers 25429, National Bureau of Economic Research, Inc.
• Guanhao Feng & Stefano Giglio & Dacheng Xiu, 2020. "Taming the Factor Zoo: A Test of New Factors," Journal of Finance, American Finance Association, vol. 75(3), pages 1327-1370, June.
  • Guanhao Feng & Stefano Giglio & Dacheng Xiu, 2019. "Taming the Factor Zoo: A Test of New Factors," NBER Working Papers 25481, National Bureau of Economic Research, Inc.
  • Giglio, Stefano & Feng, Guanhao & Xiu, Dacheng, 2020. "Taming the Factor Zoo: A Test of New Factors," CEPR Discussion Papers 14266, C.E.P.R. Discussion Papers.
• Arthur Turrell & Bradley Speigner & Jyldyz Djumalieva & David Copple & James Thurgood, 2019. "Transforming Naturally Occurring Text Data into Economic Statistics: The Case of Online Job Vacancy Postings," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 173-207, National Bureau of Economic Research, Inc.
  • Arthur Turrell & Bradley J. Speigner & Jyldyz Djumalieva & David Copple & James Thurgood, 2019. "Transforming Naturally Occurring Text Data Into Economic Statistics: The Case of Online Job Vacancy Postings," NBER Working Papers 25837, National Bureau of Economic Research, Inc.
• Jon Kleinberg & Sendhil Mullainathan, 2019. "Simplicity Creates Inequity: Implications for Fairness, Stereotypes, and Interpretability," NBER Working Papers 25854, National Bureau of Economic Research, Inc.
• Rishab Guha & Serena Ng, 2019. "A Machine Learning Analysis of Seasonal and Cyclical Sales in Weekly Scanner Data," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 403-436, National Bureau of Economic Research, Inc.
  • Rishab Guha & Serena Ng, 2019. "A Machine Learning Analysis of Seasonal and Cyclical Sales in Weekly Scanner Data," NBER Working Papers 25899, National Bureau of Economic Research, Inc.
• Tomaz Cajner & Leland D. Crane & Ryan A. Decker & Adrian Hamins-Puertolas & Christopher Kurz, 2019. "Improving the Accuracy of Economic Measurement with Multiple Data Sources: The Case of Payroll Employment Data," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 147-170, National Bureau of Economic Research, Inc.
  • Tomaz Cajner & Leland D. Crane & Ryan A. Decker & Adrian Hamins-Puertolas & Christopher J. Kurz, 2019. "Improving the Accuracy of Economic Measurement with Multiple Data Sources: The Case of Payroll Employment Data," Finance and Economics Discussion Series 2019-065, Board of Governors of the Federal Reserve System (U.S.).
  • Tomaz Cajner & Leland D. Crane & Ryan A. Decker & Adrian Hamins-Puertolas & Christopher Kurz, 2019. "Improving the Accuracy of Economic Measurement with Multiple Data Sources: The Case of Payroll Employment Data," NBER Working Papers 26033, National Bureau of Economic Research, Inc.
• Stefania Albanesi & Domonkos F. Vamossy, 2019. "Predicting Consumer Default: A Deep Learning Approach," Working Papers 2019-056, Human Capital and Economic Opportunity Working Group.
  • Stefania Albanesi & Domonkos F. Vamossy, 2019. "Predicting Consumer Default: A Deep Learning Approach," NBER Working Papers 26165, National Bureau of Economic Research, Inc.
  • Albanesi, Stefania & Vamossy, Domonkos, 2019. "Predicting Consumer Default: A Deep Learning Approach," CEPR Discussion Papers 13914, C.E.P.R. Discussion Papers.
  • Stefania Albanesi & Domonkos F. Vamossy, 2019. "Predicting Consumer Default: A Deep Learning Approach," Papers 1908.11498, arXiv.org, revised Oct 2019.
• Sendhil Mullainathan & Ziad Obermeyer, 2023. "Diagnosing Physician Error: A Machine Learning Approach to Low-Value Health Care," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 137(2), pages 679-727.
  • Sendhil Mullainathan & Ziad Obermeyer, 2019. "Diagnosing Physician Error: A Machine Learning Approach to Low-Value Health Care," NBER Working Papers 26168, National Bureau of Economic Research, Inc.
• Zheng Tracy Ke & Bryan T. Kelly & Dacheng Xiu, 2019. "Predicting Returns With Text Data," NBER Working Papers 26186, National Bureau of Economic Research, Inc.
• Aditya Aladangady & Shifrah Aron-Dine & Wendy Dunn & Laura Feiveson & Paul Lengermann & Claudia Sahm, 2021. "From Transaction Data to Economic Statistics: Constructing Real-Time, High-Frequency, Geographic Measures of Consumer Spending," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 115-145, National Bureau of Economic Research, Inc.
  • Aditya Aladangady & Shifrah Aron-Dine & Wendy E. Dunn & Laura Feiveson & Paul Lengermann & Claudia R. Sahm, 2019. "From Transactions Data to Economic Statistics: Constructing Real-time, High-frequency, Geographic Measures of Consumer Spending," Finance and Economics Discussion Series 2019-057, Board of Governors of the Federal Reserve System (U.S.).
  • Aditya Aladangady & Shifrah Aron-Dine & Wendy Dunn & Laura Feiveson & Paul Lengermann & Claudia Sahm, 2019. "From Transactions Data to Economic Statistics: Constructing Real-time, High-frequency, Geographic Measures of Consumer Spending," NBER Working Papers 26253, National Bureau of Economic Research, Inc.
• Aragón, Fernando M. & Restuccia, Diego & Rud, Juan Pablo, 2022. "Are small farms really more productive than large farms?," Food Policy, Elsevier, vol. 106(C).
  • Fernando Aragon, Diego Restuccia, Juan Pablo Rud & Diego Restuccia & Juan Pablo Rud, 2019. "Are small farms really more productive than large farms?," Discussion Papers dp19-05, Department of Economics, Simon Fraser University.
  • Fernando M. Aragon Sanchez & Diego Restuccia & Juan Pablo Rud, 2019. "Are Small Farms Really more Productive than Large Farms?," NBER Working Papers 26331, National Bureau of Economic Research, Inc.
  • Fernando Aragon & Diego Restuccia & Juan Pablo Rud, 2019. "Are Small Farms Really more Productive than Large Farms?," Working Papers tecipa-647, University of Toronto, Department of Economics.
  • Fernando Aragon Sanchez & Diego Restuccia & Juan Pablo Rud, 2019. "Are Small Farms Really more Productive than Large Farms?," 2019 Meeting Papers 1230, Society for Economic Dynamics.
  • Fernando Aragon & Diego Restuccia & Juan Pablo Rud, 2021. "Are small farms really more productive than large farms?," Working Papers tecipa-708, University of Toronto, Department of Economics.
  • Fernando M. Aragón & Diego Restuccia & Juan Pablo Rud, 2021. "Are small farms really more productive than large farms?," IFS Working Papers W21/35, Institute for Fiscal Studies.
  • Fernando Aragon & Diego Restuccia & Juan Pablo Rud, 2020. "Are small farms really more productive than large farms?," Working Papers tecipa-675, University of Toronto, Department of Economics.
  • Fernando Aragon & Diego Restuccia & Juan Pablo Rud, 2021. "Are small farms really more productive than large farms?," Discussion Papers dp21-11, Department of Economics, Simon Fraser University.
  • Fernando Aragón & Diego Restuccia & Juan Pablo Rud, 2021. "Are small farms really more productive than large farms?," Working Papers 44, Red Nacional de Investigadores en Economía (RedNIE).
• Victor Chernozhukov & Jerry Hausman & Whitney K. Newey, 2019. "Demand analysis with many prices," CeMMAP working papers CWP59/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Victor Chernozhukov & Jerry A. Hausman & Whitney K. Newey, 2019. "Demand Analysis with Many Prices," NBER Working Papers 26424, National Bureau of Economic Research, Inc.
• Bryan T. Kelly & Asaf Manela & Alan Moreira, 2019. "Text Selection," NBER Working Papers 26517, National Bureau of Economic Research, Inc.
• Joshua D. Angrist & Brigham Frandsen, 2022. "Machine Labor," Journal of Labor Economics, University of Chicago Press, vol. 40(S1), pages 97-140.
  • Joshua Angrist & Brigham Frandsen, 2019. "Machine Labor," NBER Working Papers 26584, National Bureau of Economic Research, Inc.
• Ulrich K. Müller & James H. Stock & Mark W. Watson, 2019. "An Econometric Model of International Long-run Growth Dynamics," NBER Working Papers 26593, National Bureau of Economic Research, Inc.
• Jens Mehrhoff, 2019. "Introduction – The Value Chain of Scanner and Web Scraped Data," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 509, pages 5-11.
• Richardson, Adam & van Florenstein Mulder, Thomas & Vehbi, Tuğrul, 2021. "Nowcasting GDP using machine-learning algorithms: A real-time assessment," International Journal of Forecasting, Elsevier, vol. 37(2), pages 941-948.
  • Adam Richardson & Thomas van Florenstein Mulder & Tugrul Vehbi, 2019. "Nowcasting GDP using machine learning algorithms: A real-time assessment," Reserve Bank of New Zealand Discussion Paper Series DP2019/03, Reserve Bank of New Zealand.
• Seán Kennedy, 2019. "The potential of tax microdata for tax policy," OECD Taxation Working Papers 45, OECD Publishing.
• Arnaud Pincet & Shu Okabe & Martin Pawelczyk, 2019. "Linking Aid to the Sustainable Development Goals – a machine learning approach," OECD Development Co-operation Working Papers 52, OECD Publishing.
• Matteo Barigozzi & Marc Hallin & Stefano Soccorsi, 2019. "Identification of Global and Local Shocks in International Financial Markets via General Dynamic Factor Models," Journal of Financial Econometrics, Oxford University Press, vol. 17(3), pages 462-494.
  • Barigozzi, Matteo & Hallin, Marc & Soccorsi, Stefano, 2019. "Identification of global and local shocks in international financial markets via general dynamic factor models," LSE Research Online Documents on Economics 86932, London School of Economics and Political Science, LSE Library.
• Simona Vasilica Oprea & Adela Bâra, 2019. "Big Data Solutions for Efficient Operation of Microgrids," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(1), pages 266-271, August.
• Simona-Vasilica Oprea & Adela Bâra & Dan PreoÈ›escu, 2019. "NoSQL Data Storage and Clustering Large Volume of Data from Smart Metering Systems with Impact on Electricity Consumption Peak and Tariff Settings," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(2), pages 327-333, December.
• Mora Rodríguez, Jhon James & González Terán, Ángela María, 2019. "Progresos educativos intergeneracionales: un análisis para Colombia || Intergenerational educational progress: an analysis for Colombia," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 28(1), pages 143-159, December.
• Joanna Olbrys, 2019. "Intra-market commonality in liquidity: new evidence from the Polish stock exchange," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 14(2), pages 251-275, June.
• Dhruv Grover & Sebastian Bauhoff & Jed Friedman, 2019. "Using supervised learning to select audit targets in performance-based financing in health: An example from Zambia," PLOS ONE, Public Library of Science, vol. 14(1), pages 1-13, January.
  • Dhruv Grover & Sebastian Bauhoff & Jed Friedman, 2018. "Using Supervised Learning to Select Audit Targets in Performance-Based Financing in Health: An Example from Zambia," Working Papers 481, Center for Global Development.
• Alifatussaadah, Ardiana & Primariesty, Anindya Diva & Soleh, Agus Mohamad & Andriansyah, Andriansyah, 2019. "Nowcasting Indonesia's GDP Growth: Are Fiscal Data Useful?," MPRA Paper 105252, University Library of Munich, Germany.
• Yang, Bill Huajian, 2019. "Monotonic Estimation for the Survival Probability over a Risk-Rated Portfolio by Discrete-Time Hazard Rate Models," MPRA Paper 93398, University Library of Munich, Germany.
• Yang, Bill Huajian, 2019. "Monotonic Estimation for Probability Distribution and Multivariate Risk Scales by Constrained Minimum Generalized Cross-Entropy," MPRA Paper 93400, University Library of Munich, Germany.
• Benedikt Maas, 2020. "Short‐term forecasting of the US unemployment rate," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 394-411, April.
  • Maas, Benedikt, 2019. "Short-term forecasting of the US unemployment rate," MPRA Paper 94066, University Library of Munich, Germany.
• Genge, Ewa & Bartolucci, Francesco, 2019. "Are attitudes towards immigration changing in Europe? An analysis based on bidimensional latent class IRT models," MPRA Paper 94672, University Library of Munich, Germany.
• Loermann, Julius & Maas, Benedikt, 2019. "Nowcasting US GDP with artificial neural networks," MPRA Paper 95459, University Library of Munich, Germany.
• Indaco, Agustín, 2020. "From twitter to GDP: Estimating economic activity from social media," Regional Science and Urban Economics, Elsevier, vol. 85(C).
  • Indaco, Agustín, 2019. "From Twitter to GDP: Estimating Economic Activity From Social Media," MPRA Paper 95885, University Library of Munich, Germany.
• Dimitris Korobilis, 2021. "High-Dimensional Macroeconomic Forecasting Using Message Passing Algorithms," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(2), pages 493-504, March.
  • Korobilis, D, 2017. "Forecasting with many predictors using message passing algorithms," Essex Finance Centre Working Papers 19565, University of Essex, Essex Business School.
  • Korobilis, Dimitris, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," MPRA Paper 96079, University Library of Munich, Germany.
  • Dimitris Korobilis, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," Working Paper series 19-17, Rimini Centre for Economic Analysis.
  • Dimitris Korobilis, 2020. "High-dimensional macroeconomic forecasting using message passing algorithms," Papers 2004.11485, arXiv.org.
  • Dimitris Korobilis, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," Working Papers 2019_07, Business School - Economics, University of Glasgow.
• Maas, Benedikt, 2019. "Nowcasting and forecasting US recessions: Evidence from the Super Learner," MPRA Paper 96408, University Library of Munich, Germany.
• Mohammad Vesal & Amir Hossein Tavakoli & Mohammad H. Rahmati, 2022. "What do one hundred million transactions tell us about demand elasticity of gasoline?," Empirical Economics, Springer, vol. 62(6), pages 2693-2711, June.
  • Rahmati, Mohammad Hossein & Tavakoli, Amirhossein & Vesal, Mohammad, 2019. "What do one hundred million transactions tell us about demand elasticity of gasoline?," MPRA Paper 97858, University Library of Munich, Germany.
• Cepni, Oguzhan & Gul, Selcuk & Gupta, Rangan, 2020. "Local currency bond risk premia of emerging markets: The role of local and global factors," Finance Research Letters, Elsevier, vol. 33(C).
  • Oguzhan Cepni & Selcuk Gul & Rangan Gupta, 2019. "Local Currency Bond Risk Premia of Emerging Markets: The Role of Local and Global Factors," Working Papers 201901, University of Pretoria, Department of Economics.
• Oguzhan Cepni & Rangan Gupta & I. Ethem Güney & M. Yilmaz, 2020. "Forecasting local currency bond risk premia of emerging markets: The role of cross‐country macrofinancial linkages," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 966-985, September.
  • Oguzhan Cepni & Rangan Gupta & I. Ethem Guney & M. Hasan Yilmaz, 2019. "Forecasting Local Currency Bond Risk Premia of Emerging Markets: The Role of Cross-Country Macro-Financial Linkages," Working Papers 201957, University of Pretoria, Department of Economics.
• Rangan Gupta & Xiaojin Sun, 2019. "Forecasting Economic Policy Uncertainty of BRIC Countries Using Bayesian VARs," Working Papers 201961, University of Pretoria, Department of Economics.
• Paweł Lula & Anna Kovaleva & Renata Oczkowska & Małgorzata Tyrańska & Sylwia Wiśniewska, 2019. "Bipartite Competency Schemas on Polish Labor Market," Central European Business Review, Prague University of Economics and Business, vol. 2019(4), pages 1-25.
• Pavel Jasek & Lenka Vrana & Lucie Sperkova & Zdenek Smutny & Marek Kobulsky, 2019. "Predictive Performance of Customer Lifetime Value Models in E-Commerce and the Use of Non-Financial Data," Prague Economic Papers, Prague University of Economics and Business, vol. 2019(6), pages 648-669.
• Aragón, Fernando M. & Restuccia, Diego & Rud, Juan Pablo, 2022. "Are small farms really more productive than large farms?," Food Policy, Elsevier, vol. 106(C).
  • Fernando M. Aragon Sanchez & Diego Restuccia & Juan Pablo Rud, 2019. "Are Small Farms Really more Productive than Large Farms?," NBER Working Papers 26331, National Bureau of Economic Research, Inc.
  • Fernando Aragon Sanchez & Diego Restuccia & Juan Pablo Rud, 2019. "Are Small Farms Really more Productive than Large Farms?," 2019 Meeting Papers 1230, Society for Economic Dynamics.
  • Fernando Aragon & Diego Restuccia & Juan Pablo Rud, 2019. "Are Small Farms Really more Productive than Large Farms?," Working Papers tecipa-647, University of Toronto, Department of Economics.
  • Fernando Aragon, Diego Restuccia, Juan Pablo Rud & Diego Restuccia & Juan Pablo Rud, 2019. "Are small farms really more productive than large farms?," Discussion Papers dp19-05, Department of Economics, Simon Fraser University.
  • Fernando Aragon & Diego Restuccia & Juan Pablo Rud, 2021. "Are small farms really more productive than large farms?," Working Papers tecipa-708, University of Toronto, Department of Economics.
  • Fernando M. Aragón & Diego Restuccia & Juan Pablo Rud, 2021. "Are small farms really more productive than large farms?," IFS Working Papers W21/35, Institute for Fiscal Studies.
  • Fernando Aragon & Diego Restuccia & Juan Pablo Rud, 2020. "Are small farms really more productive than large farms?," Working Papers tecipa-675, University of Toronto, Department of Economics.
  • Fernando Aragon & Diego Restuccia & Juan Pablo Rud, 2021. "Are small farms really more productive than large farms?," Discussion Papers dp21-11, Department of Economics, Simon Fraser University.
  • Fernando Aragón & Diego Restuccia & Juan Pablo Rud, 2021. "Are small farms really more productive than large farms?," Working Papers 44, Red Nacional de Investigadores en Economía (RedNIE).
• Dimitris Korobilis, 2021. "High-Dimensional Macroeconomic Forecasting Using Message Passing Algorithms," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(2), pages 493-504, March.
  • Korobilis, D, 2017. "Forecasting with many predictors using message passing algorithms," Essex Finance Centre Working Papers 19565, University of Essex, Essex Business School.
  • Dimitris Korobilis, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," Working Paper series 19-17, Rimini Centre for Economic Analysis.
  • Korobilis, Dimitris, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," MPRA Paper 96079, University Library of Munich, Germany.
  • Dimitris Korobilis, 2020. "High-dimensional macroeconomic forecasting using message passing algorithms," Papers 2004.11485, arXiv.org.
  • Dimitris Korobilis, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," Working Papers 2019_07, Business School - Economics, University of Glasgow.
• Längst, Gerhard & Elsner, Jürgen & Berzhanin, Anastasia, 2019. "Data Quality Imperatives for Data Migration Initiatives: A Guide for Data Practicioners," Journal of Financial Transformation, Capco Institute, vol. 50, pages 118-125.
• Pfarrhofer, Michael, 2023. "Measuring International Uncertainty Using Global Vector Autoregressions with Drifting Parameters," Macroeconomic Dynamics, Cambridge University Press, vol. 27(3), pages 770-793, April.
  • Michael Pfarrhofer, 2019. "Measuring international uncertainty using global vector autoregressions with drifting parameters," Papers 1908.06325, arXiv.org, revised Dec 2019.
  • Pfarrhofer, Michael, 2019. "Measuring international uncertainty using global vector autoregressions with drifting parameters," Working Papers in Economics 2019-3, University of Salzburg.
• Jin, Sainan & Miao, Ke & Su, Liangjun, 2021. "On factor models with random missing: EM estimation, inference, and cross validation," Journal of Econometrics, Elsevier, vol. 222(1), pages 745-777.
  • Su, Liangjun & Miao, Ke & Jin, Sainan, 2019. "On Factor Models with Random Missing: EM Estimation, Inference, and Cross Validation," Economics and Statistics Working Papers 4-2019, Singapore Management University, School of Economics.
• Badruddoza, Syed & Amin, Modhurima & McCluskey, Jill, 2019. "Assessing the Importance of an Attribute in a Demand SystemStructural Model versus Machine Learning," Working Papers 2019-5, School of Economic Sciences, Washington State University.
• Paolo Andreini & Donato Ceci, 2019. "A Horse Race in High Dimensional Space," CEIS Research Paper 452, Tor Vergata University, CEIS, revised 14 Feb 2019.
• Massimo Franchi & Paolo Paruolo, 2021. "Cointegration, Root Functions and Minimal Bases," Econometrics, MDPI, vol. 9(3), pages 1-27, August.
  • Massimo Franchi & Paolo Paruolo, 2019. "Cointegration, root functions and minimal bases," DSS Empirical Economics and Econometrics Working Papers Series 2019/2, Centre for Empirical Economics and Econometrics, Department of Statistics, "Sapienza" University of Rome.
• Aragón, Fernando M. & Restuccia, Diego & Rud, Juan Pablo, 2022. "Are small farms really more productive than large farms?," Food Policy, Elsevier, vol. 106(C).
  • Fernando M. Aragon Sanchez & Diego Restuccia & Juan Pablo Rud, 2019. "Are Small Farms Really more Productive than Large Farms?," NBER Working Papers 26331, National Bureau of Economic Research, Inc.
  • Fernando Aragon, Diego Restuccia, Juan Pablo Rud & Diego Restuccia & Juan Pablo Rud, 2019. "Are small farms really more productive than large farms?," Discussion Papers dp19-05, Department of Economics, Simon Fraser University.
  • Fernando Aragon & Diego Restuccia & Juan Pablo Rud, 2019. "Are Small Farms Really more Productive than Large Farms?," Working Papers tecipa-647, University of Toronto, Department of Economics.
  • Fernando Aragon Sanchez & Diego Restuccia & Juan Pablo Rud, 2019. "Are Small Farms Really more Productive than Large Farms?," 2019 Meeting Papers 1230, Society for Economic Dynamics.
  • Fernando Aragon & Diego Restuccia & Juan Pablo Rud, 2021. "Are small farms really more productive than large farms?," Working Papers tecipa-708, University of Toronto, Department of Economics.
  • Fernando M. Aragón & Diego Restuccia & Juan Pablo Rud, 2021. "Are small farms really more productive than large farms?," IFS Working Papers W21/35, Institute for Fiscal Studies.
  • Fernando Aragon & Diego Restuccia & Juan Pablo Rud, 2020. "Are small farms really more productive than large farms?," Working Papers tecipa-675, University of Toronto, Department of Economics.
  • Fernando Aragon & Diego Restuccia & Juan Pablo Rud, 2021. "Are small farms really more productive than large farms?," Discussion Papers dp21-11, Department of Economics, Simon Fraser University.
  • Fernando Aragón & Diego Restuccia & Juan Pablo Rud, 2021. "Are small farms really more productive than large farms?," Working Papers 44, Red Nacional de Investigadores en Economía (RedNIE).
• Benjamin Anderegg & Didier Sornette & Florian Ulmann, 2019. "Quantification of feedback effects in FX options markets," Working Papers 2019-03, Swiss National Bank.
• Yoshiaki Ogura & Ryo Okui & Yukiko Umeno Saito, 2019. "Network-motivated Lending Decisions: A Rationale for Forbearance," Working Paper Series no127, Institute of Economic Research, Seoul National University.
• James P. LeSage & Daniel Hendrikz, 2019. "Large Bayesian vector autoregressive forecasting for regions: A comparison of methods based on alternative disturbance structures," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 62(3), pages 563-599, June.
• Petra Burdejová & Wolfgang K. Härdle, 2019. "Dynamic semi-parametric factor model for functional expectiles," Computational Statistics, Springer, vol. 34(2), pages 489-502, June.
  • Burdejová, Petra & Härdle, Wolfgang Karl, 2017. "Dynamic semi-parametric factor model for functional expectiles," SFB 649 Discussion Papers 2017-027, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
• Peter N. Posch & Daniel Ullmann & Dominik Wied, 2019. "Detecting structural changes in large portfolios," Empirical Economics, Springer, vol. 56(4), pages 1341-1357, April.
• Qing Wang & Dan Zhao, 2019. "Penalization methods with group-wise sparsity: econometric applications to eBay Motors online auctions," Empirical Economics, Springer, vol. 57(2), pages 683-704, August.
• Ard Reijer & Andreas Johansson, 2019. "Nowcasting Swedish GDP with a large and unbalanced data set," Empirical Economics, Springer, vol. 57(4), pages 1351-1373, October.
• Tomáš Gajdošík, 2019. "Big Data Analytics in Smart Tourism Destinations. A New Tool for Destination Management Organizations?," Springer Proceedings in Business and Economics, in: Vicky Katsoni & Marival Segarra-Oña (ed.), Smart Tourism as a Driver for Culture and Sustainability, chapter 0, pages 15-33, Springer.
• Athanasios Koutras & Ioannis A. Nikas & Alkiviadis Panagopoulos, 2019. "Towards Developing Smart Cities: Evidence from GIS Analysis on Tourists’ Behavior Using Social Network Data in the City of Athens," Springer Proceedings in Business and Economics, in: Vicky Katsoni & Marival Segarra-Oña (ed.), Smart Tourism as a Driver for Culture and Sustainability, chapter 0, pages 407-418, Springer.
• Daria Maltseva & Vladimir Batagelj, 2019. "Social network analysis as a field of invasions: bibliographic approach to study SNA development," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(2), pages 1085-1128, November.
• Buse, Rebekka & Schienle, Melanie & Urban, Jörg, 2019. "Effectiveness of policy and regulation in European sovereign credit risk markets: A network analysis," Working Paper Series in Economics 125, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
  • Buse, Rebekka & Schienle, Melanie & Urban, Jörg, 2019. "Effectiveness of policy and regulation in European sovereign credit risk markets: a network analysis," ESRB Working Paper Series 90, European Systemic Risk Board.
• Bruno, Randolph Luca & Douarin, Elodie & Korosteleva, Julia & Radosevic, Slavo, 2019. "Determinants of Productivity Gap in the European Union: A Multilevel Perspective," IZA Discussion Papers 12542, Institute of Labor Economics (IZA).
  • Randolph Luca Bruno & Elodie Douarin & Julia Korosteleva & Slavo Radosevic, 2019. "Determinants of Productivity Gap in the European Union: A Multilevel Perspective," LEM Papers Series 2019/25, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
• Rachida Ouysse, 2017. "Constrained principal components estimation of large approximate factor models," Discussion Papers 2017-12, School of Economics, The University of New South Wales.
  • Rachida Ouysse, 2019. "Constrained principal components estimation of large approximate factor models," Discussion Papers 2017-12a, School of Economics, The University of New South Wales.
• Chloé van Biljon & Cobus Burger, 2019. "The period effect: the effect of menstruation on absenteeism of school girls in Limpopo," Working Papers 20/2019, Stellenbosch University, Department of Economics.
• Simon Beyeler & Sylvia Kaufmann, 2016. "Factor augmented VAR revisited - A sparse dynamic factor model approach," Working Papers 16.08, Swiss National Bank, Study Center Gerzensee.
  • Simon Beyeler & Sylvia Kaufmann, 2019. "Factor augmented VAR revisited - A sparse dynamic factor model approach," Working Papers 16.08R, Swiss National Bank, Study Center Gerzensee.
  • Kaufmann, Sylvia & Beyeler, Simon, 2018. "Factor augmented VAR revisited - A sparse dynamic factor model approach," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181602, Verein für Socialpolitik / German Economic Association.
• Massimo Franchi & Paolo Paruolo, 2019. "A general inversion theorem for cointegration," Econometric Reviews, Taylor & Francis Journals, vol. 38(10), pages 1176-1201, November.
  • Massimo Franchi & Paolo Paruolo, 2017. "A general inversion theorem for cointegration," DSS Empirical Economics and Econometrics Working Papers Series 2017/3, Centre for Empirical Economics and Econometrics, Department of Statistics, "Sapienza" University of Rome.
• Yacine Aït-Sahalia & Dacheng Xiu, 2019. "Principal Component Analysis of High-Frequency Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 114(525), pages 287-303, January.
  • Yacine Aït-Sahalia & Dacheng Xiu, 2015. "Principal Component Analysis of High Frequency Data," NBER Working Papers 21584, National Bureau of Economic Research, Inc.
• Matias Quiroz & Robert Kohn & Mattias Villani & Minh-Ngoc Tran, 2019. "Speeding Up MCMC by Efficient Data Subsampling," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 114(526), pages 831-843, April.
  • Quiroz, Matias & Villani, Mattias & Kohn, Robert, 2015. "Speeding Up Mcmc By Efficient Data Subsampling," Working Paper Series 297, Sveriges Riksbank (Central Bank of Sweden).
  • Kohn, Robert & Quiroz, Matias & Tran, Minh-Ngoc & Villani, Mattias, 2016. "Speeding up MCMC by Efficient Data Subsampling," Working Papers 2123/16205, University of Sydney Business School, Discipline of Business Analytics.
• Alexander N. Bogin & William M. Doerner, 2019. "Property Renovations and Their Impact on House Price Index Construction," Journal of Real Estate Research, Taylor & Francis Journals, vol. 41(2), pages 249-284, April.
  • Alexander N. Bogin & William M. Doerner, 2017. "Property Renovations and Their Impact on House Price Index Construction," FHFA Staff Working Papers 17-02, Federal Housing Finance Agency.
• Jens Prüfer & Patricia Prüfer, 2020. "Data science for entrepreneurship research: studying demand dynamics for entrepreneurial skills in the Netherlands," Small Business Economics, Springer, vol. 55(3), pages 651-672, October.
  • Prüfer, Jens & Prüfer, Patricia, 2019. "Data Science for Entrepreneurship Research : Studying Demand Dynamics for Entrepreneurial Skills in the Netherlands," Other publications TiSEM 83a4ca9e-c0cd-4786-ac8c-9, Tilburg University, School of Economics and Management.
  • Prüfer, Jens & Prüfer, Patricia, 2019. "Data Science for Entrepreneurship Research : Studying Demand Dynamics for Entrepreneurial Skills in the Netherlands," Discussion Paper 2019-005, Tilburg University, Center for Economic Research.
• Jens Prüfer & Patricia Prüfer, 2020. "Data science for entrepreneurship research: studying demand dynamics for entrepreneurial skills in the Netherlands," Small Business Economics, Springer, vol. 55(3), pages 651-672, October.
  • Prüfer, Jens & Prüfer, Patricia, 2019. "Data Science for Entrepreneurship Research : Studying Demand Dynamics for Entrepreneurial Skills in the Netherlands," Discussion Paper 2019-005, Tilburg University, Center for Economic Research.
  • Prüfer, Jens & Prüfer, Patricia, 2019. "Data Science for Entrepreneurship Research : Studying Demand Dynamics for Entrepreneurial Skills in the Netherlands," Other publications TiSEM 83a4ca9e-c0cd-4786-ac8c-9, Tilburg University, School of Economics and Management.
• Aragón, Fernando M. & Restuccia, Diego & Rud, Juan Pablo, 2022. "Are small farms really more productive than large farms?," Food Policy, Elsevier, vol. 106(C).
  • Fernando M. Aragon Sanchez & Diego Restuccia & Juan Pablo Rud, 2019. "Are Small Farms Really more Productive than Large Farms?," NBER Working Papers 26331, National Bureau of Economic Research, Inc.
  • Fernando M. Aragón & Diego Restuccia & Juan Pablo Rud, 2021. "Are small farms really more productive than large farms?," IFS Working Papers W21/35, Institute for Fiscal Studies.
  • Fernando Aragon & Diego Restuccia & Juan Pablo Rud, 2019. "Are Small Farms Really more Productive than Large Farms?," Working Papers tecipa-647, University of Toronto, Department of Economics.
  • Fernando Aragon & Diego Restuccia & Juan Pablo Rud, 2020. "Are small farms really more productive than large farms?," Working Papers tecipa-675, University of Toronto, Department of Economics.
  • Fernando Aragon & Diego Restuccia & Juan Pablo Rud, 2021. "Are small farms really more productive than large farms?," Discussion Papers dp21-11, Department of Economics, Simon Fraser University.
  • Fernando Aragon Sanchez & Diego Restuccia & Juan Pablo Rud, 2019. "Are Small Farms Really more Productive than Large Farms?," 2019 Meeting Papers 1230, Society for Economic Dynamics.
  • Fernando Aragon, Diego Restuccia, Juan Pablo Rud & Diego Restuccia & Juan Pablo Rud, 2019. "Are small farms really more productive than large farms?," Discussion Papers dp19-05, Department of Economics, Simon Fraser University.
  • Fernando Aragon & Diego Restuccia & Juan Pablo Rud, 2021. "Are small farms really more productive than large farms?," Working Papers tecipa-708, University of Toronto, Department of Economics.
  • Fernando Aragón & Diego Restuccia & Juan Pablo Rud, 2021. "Are small farms really more productive than large farms?," Working Papers 44, Red Nacional de Investigadores en Economía (RedNIE).
• Gabriela Mordecki Corresponding author & Ronald Miranda, 2019. "Real Exchange Rate Volatility and Exports: A Study for Four Selected Commodity Exporting Countries," Panoeconomicus, Savez ekonomista Vojvodine, Novi Sad, Serbia, vol. 66(4), pages 411-437, September.
• Gabriela Mordecki & Ronald Miranda, 2019. "Real Exchange Rate Volatility and Exports: A Study for Four Selected Commodity Exporting Countries," Panoeconomicus, Savez ekonomista Vojvodine, Novi Sad, Serbia, vol. 66(4), pages 411-437.
• Chiara Elena Dalla & Menon Martina & Perali Federico, 2019. "An Integrated Database to Measure Living Standards," Journal of Official Statistics, Sciendo, vol. 35(3), pages 531-576, September.
  • Elena Dalla Chiara & Martina Menon & Federico Perali, 2015. "An Integrated Data Base to Measure Living Standards," Working Papers 28/2015, University of Verona, Department of Economics.
• Koen Jochmans & Martin Weidner, 2019. "Fixed‐Effect Regressions on Network Data," Econometrica, Econometric Society, vol. 87(5), pages 1543-1560, September.
  • Koen Jochmans & Martin Weidner, 2016. "Fixed-effect regressions on network data," CeMMAP working papers CWP32/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2018. "Fixed-effect regressions on network data," CeMMAP working papers CWP44/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Jochmans, K. & Weidner, M., 2019. "Fixed-Effect Regressions on Network Data," Cambridge Working Papers in Economics 1938, Faculty of Economics, University of Cambridge.
  • Koen Jochmans & Martin Weidner, 2017. "Fixed-effect regressions on network data," CeMMAP working papers 26/17, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2017. "Fixed-effect regressions on network data," CeMMAP working papers CWP26/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2019. "Fixed-effect regressions on network data," CeMMAP working papers CWP16/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2016. "Fixed-Effect Regressions on Network Data," Papers 1608.01532, arXiv.org, revised Apr 2019.
  • Koen Jochmans & Martin Weidner, 2016. "Fixed-effect regressions on network data," CeMMAP working papers 32/16, Institute for Fiscal Studies.
• Timo Bettendorf, 2019. "Spillover effects of credit default risk in the euro area and the effects on the Euro: A GVAR approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(1), pages 296-312, January.
  • Bettendorf, Timo, 2016. "Spillover effects of credit default risk in the euro area and the effects on the euro: A GVAR approach," Discussion Papers 42/2016, Deutsche Bundesbank.
• George Kapetanios & Massimiliano Marcellino & Fabrizio Venditti, 2019. "Large time‐varying parameter VARs: A nonparametric approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(7), pages 1027-1049, November.
  • Marcellino, Massimiliano & Kapetanios, George & Venditti, Fabrizio, 2016. "Large Time-Varying Parameter VARs: A Non-Parametric Approach," CEPR Discussion Papers 11560, C.E.P.R. Discussion Papers.
  • George Kapetanios & Massimiliano Marcellino & Fabrizio Venditti, 2017. "Large time-varying parameter VARs: a non-parametric approach," Temi di discussione (Economic working papers) 1122, Bank of Italy, Economic Research and International Relations Area.
• Hauber, Philipp & Schumacher, Christian & Zhang, Jiachun, 2019. "A flexible state-space model with lagged states and lagged dependent variables: Simulation smoothing," Discussion Papers 15/2019, Deutsche Bundesbank.
• Krstić, Živko & Seljan, Sanja & Zoroja, Jovana, 2019. "Visualization of Big Data Text Analytics in Financial Industry: A Case Study of Topic Extraction for Italian Banks," Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference (2019), Rovinj, Croatia, in: Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Rovinj, Croatia, 12-14 September 2019, pages 67-75, IRENET - Society for Advancing Innovation and Research in Economy, Zagreb.
• Dragotă, Victor & Pele, Daniel Traian & Yaseen, Hanaan, 2019. "Dividend payout ratio follows a Tweedie distribution: International evidence," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 13, pages 1-35.
  • Dragota, Victor & Pele, Daniel Traian & Yaseen, Hanaan, 2019. "Dividend payout ratio follows a Tweedie distribution: International evidence," Economics Discussion Papers 2019-41, Kiel Institute for the World Economy (IfW Kiel).
• Doanh Khanh Nguyen & Van Ngoc Thi Pham & Heo, Yoon, 2019. "Impact of institutional and cultural distance on ASEAN's trade efficiency," Economics Discussion Papers 2019-57, Kiel Institute for the World Economy (IfW Kiel).
• Dragotă, Victor & Pele, Daniel Traian & Yaseen, Hanaan, 2019. "Dividend payout ratio follows a Tweedie distribution: International evidence," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 13, pages 1-35.
  • Dragota, Victor & Pele, Daniel Traian & Yaseen, Hanaan, 2019. "Dividend payout ratio follows a Tweedie distribution: International evidence," Economics Discussion Papers 2019-41, Kiel Institute for the World Economy (IfW Kiel).
• Hinz, Julian & Stammann, Amrei & Wanner, Joschka, 2019. "Persistent zeros: The extensive margin of trade," Kiel Working Papers 2139, Kiel Institute for the World Economy (IfW Kiel).
  • Julian Hinz & Amrei Stammann & Joschka Wanner, 2020. "State Dependence and Unobserved Heterogeneity in the Extensive Margin of Trade," Papers 2004.12655, arXiv.org, revised Jul 2021.
  • Julian Hinz & Amrei Stammann & Joschka Wanner, 2021. "State Dependence and Unobserved Heterogeneity in the Extensive Margin of Trade," CEPA Discussion Papers 36, Center for Economic Policy Analysis.
• Härdle, Wolfgang Karl & Schulz, Rainer & Xie, Taojun, 2019. "Cooling Measures and Housing Wealth: Evidence from Singapore," IRTG 1792 Discussion Papers 2019-001, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
• Qian, Ya & Tu, Jun & Härdle, Wolfgang Karl, 2019. "Information Arrival, News Sentiment, Volatilities and Jumps of Intraday Returns," IRTG 1792 Discussion Papers 2019-002, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
• Buse, Rebekka & Schienle, Melanie & Urban, Jörg, 2019. "Effectiveness of policy and regulation in European sovereign credit risk markets: a network analysis," ESRB Working Paper Series 90, European Systemic Risk Board.
  • Buse, Rebekka & Schienle, Melanie & Urban, Jörg, 2019. "Effectiveness of policy and regulation in European sovereign credit risk markets: A network analysis," Working Paper Series in Economics 125, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
• Ralf Brüggemann & Christian Kascha, 2017. "Directed Graphs and Variable Selection in Large Vector Autoregressive Models," Working Paper Series of the Department of Economics, University of Konstanz 2017-06, Department of Economics, University of Konstanz.
  • Bertsche, Dominik & Brüggemann, Ralf & Kascha, Christian, 2019. "Directed Graph and Variable Selection in Large Vector Autoregressive Models," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203656, Verein für Socialpolitik / German Economic Association.
  • Dominik Bertsche & Ralf Brüggemann & Christian Kascha, 2018. "Directed Graphs and Variable Selection in Large Vector Autoregressive Models," Working Paper Series of the Department of Economics, University of Konstanz 2018-08, Department of Economics, University of Konstanz.

2018

• Ogerta Elezaj & Dhimitri Tole, 2018. "Big Data: Potential, Challenges, And Implications In Official Statistics," CBU International Conference Proceedings, ISE Research Institute, vol. 6(0), pages 95-99, September.
• Riccardo Borghi & Eric Hillebrand & Jakob Mikkelsen & Giovanni Urga, 2018. "The dynamics of factor loadings in the cross-section of returns," CREATES Research Papers 2018-38, Department of Economics and Business Economics, Aarhus University.
• Brito Rui Pedro & Sebastião Helder & Godinho Pedro, 2018. "On the Gains of Using High Frequency Data in Portfolio Selection," Scientific Annals of Economics and Business, Sciendo, vol. 65(4), pages 365-383, December.
  • Rui Pedro Brito & Helder Sebastião & Pedro Godinho, 2018. "On the Gains of Using High Frequency Data in Portfolio Selection," Scientific Annals of Economics and Business (continues Analele Stiintifice), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 65(4), pages 365-383, December.
• Chevillon, Guillaume & Hecq, Alain & Laurent, Sébastien, 2018. "Generating univariate fractional integration within a large VAR(1)," Journal of Econometrics, Elsevier, vol. 204(1), pages 54-65.
  • Guillaume Chevillon & Alain Hecq & Sébastien Laurent, 2018. "Generating Univariate Fractional Integration within a Large VAR(1)," Working Papers halshs-01944588, HAL.
  • Guillaume Chevillon & Alain Hecq & Sébastien Laurent, 2018. "Generating Univariate Fractional Integration within a Large VAR(1)," AMSE Working Papers 1844, Aix-Marseille School of Economics, France.
  • Guillaume Chevillon & Alain Hecq & Sébastien Laurent, 2018. "Generating univariate fractional integration within a large VAR(1)," Post-Print hal-01980783, HAL.
• Jan Vavřina & Lubor Lacina, 2018. "Profitability of foodstuff processing companies in V4 countries during the 2008-2012 economic crisis," Society and Economy, Akadémiai Kiadó, Hungary, vol. 40(2), pages 245-270, June.
• Brandyn Bok & Daniele Caratelli & Domenico Giannone & Argia M. Sbordone & Andrea Tambalotti, 2018. "Macroeconomic Nowcasting and Forecasting with Big Data," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 615-643, August.
  • Brandyn Bok & Daniele Caratelli & Domenico Giannone & Argia M. Sbordone & Andrea Tambalotti, 2017. "Macroeconomic nowcasting and forecasting with big data," Staff Reports 830, Federal Reserve Bank of New York.
  • Giannone, Domenico & Tambalotti, Andrea & Sbordone, Argia & Bok, Brandyn & Caratelli, Daniele, 2018. "Macroeconomic Nowcasting and Forecasting with Big Data," CEPR Discussion Papers 12589, C.E.P.R. Discussion Papers.
• Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“Tracking economic growth by evolving expectations via genetic programming: A two-step approach”," IREA Working Papers 201801, University of Barcelona, Research Institute of Applied Economics, revised Jan 2018.
  • Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“Tracking economic growth by evolving expectations via genetic programming: A two-step approach”," AQR Working Papers 201801, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2018.
  • Oscar Claveria & Enric Monte & Salvador Torra, 2018. "Tracking economic growth by evolving expectations via genetic programming: A two-step approach," Working Papers XREAP2018-4, Xarxa de Referència en Economia Aplicada (XREAP), revised Oct 2018.
• Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“A geometric approach to proxy economic uncertainty by a metric of disagreement among qualitative expectations”," IREA Working Papers 201806, University of Barcelona, Research Institute of Applied Economics, revised Mar 2018.
  • Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“A geometric approach to proxy economic uncertainty by a metric of disagreement among qualitative expectations”," AQR Working Papers 201803, University of Barcelona, Regional Quantitative Analysis Group, revised Jun 2018.
• Breunig, Christoph & Mammen, Enno & Simoni, Anna, 2020. "Ill-posed estimation in high-dimensional models with instrumental variables," Journal of Econometrics, Elsevier, vol. 219(1), pages 171-200.
  • Christoph Breunig & Enno Mammen & Anna Simoni, 2018. "Ill-posed Estimation in High-Dimensional Models with Instrumental Variables," Papers 1806.00666, arXiv.org, revised Aug 2020.
  • Christoph Breunig & Enno Mammen & Anna Simoni, 2020. "Ill-posed estimation in high-dimensional models with instrumental variables," Post-Print hal-03089879, HAL.
• Zhan Gao & Zhentao Shi, 2021. "Implementing Convex Optimization in R: Two Econometric Examples," Computational Economics, Springer;Society for Computational Economics, vol. 58(4), pages 1127-1135, December.
  • Zhan Gao & Zhentao Shi, 2018. "Implementing Convex Optimization in R: Two Econometric Examples," Papers 1806.10423, arXiv.org, revised Aug 2019.
• Harding, Matthew & Lamarche, Carlos, 2019. "A panel quantile approach to attrition bias in Big Data: Evidence from a randomized experiment," Journal of Econometrics, Elsevier, vol. 211(1), pages 61-82.
  • Matthew Harding & Carlos Lamarche, 2018. "A Panel Quantile Approach to Attrition Bias in Big Data: Evidence from a Randomized Experiment," Papers 1808.03364, arXiv.org.
• Smeekes, Stephan & Wijler, Etienne, 2021. "An automated approach towards sparse single-equation cointegration modelling," Journal of Econometrics, Elsevier, vol. 221(1), pages 247-276.
  • Stephan Smeekes & Etienne Wijler, 2018. "An Automated Approach Towards Sparse Single-Equation Cointegration Modelling," Papers 1809.08889, arXiv.org, revised Jul 2020.
• Harold D. Chiang, 2018. "Many Average Partial Effects: with An Application to Text Regression," Papers 1812.09397, arXiv.org, revised Jan 2022.
  • Harold D. Chiang, 2019. "Many Average Partial Effects: with an Application to Text Regression," 2019 Papers pch1836, Job Market Papers.
• Emilia VASILE & Danut-Octavian SIMION & George CALOTA, 2018. "Propositional calculation for expert systems in economics," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 50(2), pages 9-19, June.
• Danut-Octavian SIMION & Emilia VASILE, 2018. "Usage of informational systems in economic applications," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 51(3), pages 9-23, September.
• Emilia VASILE, 2018. "The Strategy Of Improving Informational Systems Through Economic Applications," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 52(4), pages 9-21, December.
• Dario Buono & George Kapetanios & Massimiliano Marcellino & Gianluigi Mazzi & Fotis Papailias, 2018. "Big Data Econometrics: Now Casting and Early Estimates," BAFFI CAREFIN Working Papers 1882, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
• Heather L.R. Tierney & Jiyoon Kim & Zafar Nazarov, 2018. "The Effects of Temporal Aggregation on Search Engine Data," Review of Economics & Finance, Better Advances Press, Canada, vol. 12, pages 57-71, May.
• Diego Bodas & Juan Ramon Garcia & Juan Murillo & Matias Pacce & Tomasa Rodrigo & Juan de Dios Romero & Pep Ruiz & Camilo Ulloa & Heribert Valero, 2018. "Measuring Retail Trade Using Card Transactional Data," Working Papers 18/03, BBVA Bank, Economic Research Department.
  • Diego Bodas & Juan R. García López & Tomasa Rodrigo López & Pep Ruiz de Aguirre & Camilo A. Ulloa & Juan Murillo Arias & Juan de Dios Romero Palop & Heribert Valero Lapaz & Matías J. Pacce, 2019. "Measuring retail trade using card transactional data," Working Papers 1921, Banco de España;Working Papers Homepage.
• Hicham Ganga & Javier Alonso & Vincenzo Spiezia & Jan Tscheke, 2018. "Patterns of domestic and cross-border e-commerce in Spain: A gravitational model approach," Working Papers 18/18, BBVA Bank, Economic Research Department.
• Jeannine Bailliu & Xinfen Han & Mark Kruger & Yu-Hsien Liu & Sri Thanabalasingam, 2019. "Can media and text analytics provide insights into labour market conditions in China?," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Are post-crisis statistical initiatives completed?, volume 49, Bank for International Settlements.
  • Bailliu, Jeannine & Han, Xinfen & Kruger, Mark & Liu, Yu-Hsien & Thanabalasingam, Sri, 2019. "Can media and text analytics provide insights into labour market conditions in China?," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1118-1130.
  • Bailliu, Jeannine & Han, Xinfen & Kruger, Mark & Liu, Yu-Hsien & Thanabalasingam, Sri, 2018. "Can media and text analytics provide insights into labour market conditions in China?," BOFIT Discussion Papers 9/2018, Bank of Finland Institute for Emerging Economies (BOFIT).
  • Jeannine Bailliu & Xinfen Han & Mark Kruger & Yu-Hsien Liu & Sri Thanabalasingam, 2018. "Can Media and Text Analytics Provide Insights into Labour Market Conditions in China?," Staff Working Papers 18-12, Bank of Canada.
• Bulusu, Narayan & Guérin, Pierre, 2019. "What drives interbank loans? Evidence from Canada," Journal of Banking & Finance, Elsevier, vol. 106(C), pages 427-444.
  • Narayan Bulusu & Pierre Guérin, 2018. "What Drives Interbank Loans? Evidence from Canada," Staff Working Papers 18-5, Bank of Canada.
• Sandra García-Uribe, 2018. "Multidimensional media slant: complementarities in news reporting by US newspapers," Working Papers 1817, Banco de España.
• Edward L. Glaeser & Scott Duke Kominers & Michael Luca & Nikhil Naik, 2018. "Big Data And Big Cities: The Promises And Limitations Of Improved Measures Of Urban Life," Economic Inquiry, Western Economic Association International, vol. 56(1), pages 114-137, January.
  • Edward L. Glaeser & Scott Duke Kominers & Michael Luca & Nikhil Naik, 2015. "Big Data and Big Cities: The Promises and Limitations of Improved Measures of Urban Life," NBER Working Papers 21778, National Bureau of Economic Research, Inc.
  • Edward L. Glaeser & Scott Duke Kominers & Michael Luca & Nikhil Naik, 2015. "Big Data and Big Cities: The Promises and Limitations of Improved Measures of Urban Life," Harvard Business School Working Papers 16-065, Harvard Business School.
  • Glaeser, Edward L. & Kominers, Scott Duke & Luca, Michael & Naik, Nikhil, 2015. "Big Data and Big Cities: The Promises and Limitations of Improved Measures for Urban Life," Working Paper Series 15-075, Harvard University, John F. Kennedy School of Government.
• José M. Cordero & Víctor Cristóbal & Daniel Santín, 2018. "Causal Inference On Education Policies: A Survey Of Empirical Studies Using Pisa, Timss And Pirls," Journal of Economic Surveys, Wiley Blackwell, vol. 32(3), pages 878-915, July.
  • Cordero, José Manuel & Cristobal, Victor & Santín, Daniel, 2017. "Causal Inference on Education Policies: A Survey of Empirical Studies Using PISA, TIMSS and PIRLS," MPRA Paper 76295, University Library of Munich, Germany.
• Vegard H. Larsen & Leif Anders Thorsrud, 2018. "Business cycle narratives," Working Paper 2018/3, Norges Bank.
  • Vegard H. Larsen & Leif Anders Thorsrud, 2019. "Business Cycle Narratives," CESifo Working Paper Series 7468, CESifo.
• Vegard H. Larsen & Leif Anders Thorsrud, 2018. "Business cycle narratives," Working Paper 2018/3, Norges Bank.
  • Vegard H ghaug Larsen & Leif Anders Thorsrud, 2018. "Business cycle narratives," Working Papers No 6/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • Vegard H. Larsen & Leif Anders Thorsrud, 2019. "Business Cycle Narratives," CESifo Working Paper Series 7468, CESifo.
• Hilde C. Bjørnland & Julia Zhulanova, 2018. "The Shale Oil Boom and the U.S. Economy: Spillovers and Time-Varying Effects," Working Papers No 8/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • Hilde C. Bjørnland & Julia Zhulanova, 2019. "The shale oil boom and the US economy: Spillovers and time-varying effects," CAMA Working Papers 2019-59, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Hilde C. Bjørnland & Julia Zhulanova, 2019. "The shale oil boom and the U.S. economy: Spillovers and time-varying effects," Working Paper 2019/14, Norges Bank.
• Shakeeb Khan & Denis Nekipelov & Justin Rao, 2018. "Measuring the Return to Online Advertising: Estimation and Inference of Endogenous Treatment Effects," Boston College Working Papers in Economics 946, Boston College Department of Economics.
• Demetrescu, Matei & Hacıoğlu Hoke, Sinem, 2019. "Predictive regressions under asymmetric loss: Factor augmentation and model selection," International Journal of Forecasting, Elsevier, vol. 35(1), pages 80-99.
  • Demetrescu, Matei & Hacioglu Hoke, Sinem, 2018. "Predictive regressions under asymmetric loss: factor augmentation and model selection," Bank of England working papers 723, Bank of England.
• Turrell, Arthur & Speigner, Bradley & Djumalieva, Jyldyz & Copple, David & Thurgood, James, 2018. "Using job vacancies to understand the effects of labour market mismatch on UK output and productivity," Bank of England working papers 737, Bank of England.
• Turrell, Arthur & Thurgood, James & Djumalieva, Jyldyz & Copple, David & Speigner, Bradley, 2018. "Using online job vacancies to understand the UK labour market from the bottom-up," Bank of England working papers 742, Bank of England.
• Lazarov, Vladimir & Hinterschweiger, Marc, 2018. "Determinants of distress in the UK owner-occupier and buy-to-let mortgage markets," Bank of England working papers 760, Bank of England.
• Nikoleta Anesti & Ana Beatriz Galvao & Silvia Miranda-Agrippino, 2018. "Uncertain Kingdom: Nowcasting GDP and its Revisions," Discussion Papers 1824, Centre for Macroeconomics (CFM).
  • Anesti, Nikoleta & Galvão, Ana & Miranda-Agrippino, Silvia, 2018. "Uncertain Kingdom: nowcasting GDP and its revisions," Bank of England working papers 764, Bank of England, revised 31 Jan 2020.
  • Anesti, Nikoleta & Galvao, Ana Beatriz & Miranda-Agrippino, Silvia, 2018. "Uncertain kingdom: nowcasting GDP and its revisions," LSE Research Online Documents on Economics 90382, London School of Economics and Political Science, LSE Library.
• Jeannine Bailliu & Xinfen Han & Mark Kruger & Yu-Hsien Liu & Sri Thanabalasingam, 2019. "Can media and text analytics provide insights into labour market conditions in China?," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Are post-crisis statistical initiatives completed?, volume 49, Bank for International Settlements.
  • Bailliu, Jeannine & Han, Xinfen & Kruger, Mark & Liu, Yu-Hsien & Thanabalasingam, Sri, 2019. "Can media and text analytics provide insights into labour market conditions in China?," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1118-1130.
  • Jeannine Bailliu & Xinfen Han & Mark Kruger & Yu-Hsien Liu & Sri Thanabalasingam, 2018. "Can Media and Text Analytics Provide Insights into Labour Market Conditions in China?," Staff Working Papers 18-12, Bank of Canada.
  • Bailliu, Jeannine & Han, Xinfen & Kruger, Mark & Liu, Yu-Hsien & Thanabalasingam, Sri, 2018. "Can media and text analytics provide insights into labour market conditions in China?," BOFIT Discussion Papers 9/2018, Bank of Finland, Institute for Economies in Transition.
• Wucherpfennig, Julian & Kachi, Aya & Bormann, Nils-Christian & Hunziker, Philipp, 2018. "Estimating Interdependence Across Space, Time and Outcomes in Binary Choice Models Using Pseudo Maximum Likelihood Estimators," Working papers 2018/11, Faculty of Business and Economics - University of Basel.
• Anna Gloria Billé & Leopoldo Catania, 2018. "Dynamic Spatial Autoregressive Models with Time-varying Spatial Weighting Matrices," BEMPS - Bozen Economics & Management Paper Series BEMPS55, Faculty of Economics and Management at the Free University of Bozen.
• Guo, P. & Lam, J. & Li, V., 2018. "A novel machine learning approach for identifying the drivers of domestic electricity users’ price responsiveness," Cambridge Working Papers in Economics 1844, Faculty of Economics, University of Cambridge.
• O'Neill, E. & Weeks, M., 2018. "Causal Tree Estimation of Heterogeneous Household Response to Time-Of-Use Electricity Pricing Schemes," Cambridge Working Papers in Economics 1865, Faculty of Economics, University of Cambridge.
• Hafner, Christian M. & Linton, Oliver B. & Tang, Haihan, 2020. "Estimation of a multiplicative correlation structure in the large dimensional case," Journal of Econometrics, Elsevier, vol. 217(2), pages 431-470.
  • Hafner, C. & Linton, O. & Tang, H., 2018. "Estimation of a Multiplicative Correlation Structure in the Large Dimensional Case," Cambridge Working Papers in Economics 1878, Faculty of Economics, University of Cambridge.
  • Hafner, Christian & Linton, Oliver & Tang, Haihan, 2020. "Estimation of a multiplicative correlation structure in the large dimensional case," LIDAM Reprints ISBA 2020028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
• George Kapetanios & M. Hashem Pesaran & Simon Reese, 2018. "A Residual-based Threshold Method for Detection of Units that are Too Big to Fail in Large Factor Models," CESifo Working Paper Series 7401, CESifo.
• Reif Magnus, 2021. "Macroeconomic uncertainty and forecasting macroeconomic aggregates," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(2), pages 1-20, April.
  • Magnus Reif, 2018. "Macroeconomic Uncertainty and Forecasting Macroeconomic Aggregates," ifo Working Paper Series 265, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
• Markus Heinrich & Magnus Reif, 2018. "Forecasting using mixed-frequency VARs with time-varying parameters," ifo Working Paper Series 273, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
• Anesti, Nikoleta & Galvão, Ana & Miranda-Agrippino, Silvia, 2018. "Uncertain Kingdom: nowcasting GDP and its revisions," Bank of England working papers 764, Bank of England, revised 31 Jan 2020.
  • Nikoleta Anesti & Ana Beatriz Galvao & Silvia Miranda-Agrippino, 2018. "Uncertain Kingdom: Nowcasting GDP and its Revisions," Discussion Papers 1824, Centre for Macroeconomics (CFM).
  • Anesti, Nikoleta & Galvao, Ana Beatriz & Miranda-Agrippino, Silvia, 2018. "Uncertain kingdom: nowcasting GDP and its revisions," LSE Research Online Documents on Economics 90382, London School of Economics and Political Science, LSE Library.
• Dhruv Grover & Sebastian Bauhoff & Jed Friedman, 2019. "Using supervised learning to select audit targets in performance-based financing in health: An example from Zambia," PLOS ONE, Public Library of Science, vol. 14(1), pages 1-13, January.
  • Dhruv Grover & Sebastian Bauhoff & Jed Friedman, 2018. "Using Supervised Learning to Select Audit Targets in Performance-Based Financing in Health: An Example from Zambia," Working Papers 481, Center for Global Development.
• J-C Gerlach & Guilherme Demos & Didier Sornette, 2018. "Dissection of Bitcoin's Multiscale Bubble History," Swiss Finance Institute Research Paper Series 18-30, Swiss Finance Institute.
• Shihao Gu & Bryan Kelly & Dacheng Xiu, 2020. "Empirical Asset Pricing via Machine Learning," The Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2223-2273.
  • Shihao Gu & Bryan Kelly & Dacheng Xiu, 2018. "Empirical Asset Pricing via Machine Learning," NBER Working Papers 25398, National Bureau of Economic Research, Inc.
  • Shihao Gu & Bryan T. Kelly & Dacheng Xiu, 2018. "Empirical Asset Pricing via Machine Learning," Swiss Finance Institute Research Paper Series 18-71, Swiss Finance Institute.
• Hausmann, Ricardo & Hinz, Julian & Yildirim, Muhammed A., 2018. "Measuring Venezuelan emigration with Twitter," Kiel Working Papers 2106, Kiel Institute for the World Economy (IfW Kiel).
  • Ricardo Hausmann & Julian Hinz & Muhammed A. Yildirim, 2018. "Measuring Venezuelan Emigration with Twitter," CID Working Papers 342, Center for International Development at Harvard University.
• Martin Gurtler, 2018. "What Influences Private Investment? The Case of the Czech Republic," Working Papers 2018/14, Czech National Bank.
• Gallego, Jorge & Rivero, Gonzalo & Martínez, Juan, 2021. "Preventing rather than punishing: An early warning model of malfeasance in public procurement," International Journal of Forecasting, Elsevier, vol. 37(1), pages 360-377.
  • Gallego, J & Rivero, G & Martínez, J.D., 2018. "Preventing rather than Punishing: An Early Warning Model of Malfeasance in Public Procurement," Documentos de Trabajo 16724, Universidad del Rosario.
• Eduardo Rosas Rojas & Mónica C. Mimbrera Delgado, 2018. "Inflación y volatilidad cambiaria en México (1969-2017)," Ensayos de Economía 17297, Universidad Nacional de Colombia Sede Medellín.
• Henry Sebastián Rangel Quinonez, & Gabriel Yáñez Canal, 2018. "Clasificación por capitales de una muestra de microempresarios del Área Metropolitana de Bucaramanga a partir del Análisis de Correspondencia Múltiple," Ensayos de Economía 17302, Universidad Nacional de Colombia Sede Medellín.
• Eduardo Rosas Rojas & Teresa López González, 2018. "Inflación e incertidumbre inflacionaria: la postura del Banco de México, 1969-2017," Revista Finanzas y Politica Economica, Universidad Católica de Colombia, vol. 10(2), pages 349-372, November.
• Matthias Weber & Jonas Striaukas & Martin Schumacher & Harald Binder, 2018. "Network constrained covariate coefficient and connection sign estimation," Bank of Lithuania Discussion Paper Series 8, Bank of Lithuania.
  • WEBER Matthias, & STRIAUKAS Jonas, & SCHUMACHER Martin, & HARALD Binder,, 2018. "Network constrained covariate coefficient and connection sign estimation," LIDAM Discussion Papers CORE 2018018, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  • Jonas Striaukas & Martin Schumacher & Harald Binder & Matthias Weber, 2020. "Network-Constrained Covariate Coefficient and Connection Sign Estimation," Working Papers on Finance 2001, University of St. Gallen, School of Finance.
• Brandyn Bok & Daniele Caratelli & Domenico Giannone & Argia M. Sbordone & Andrea Tambalotti, 2018. "Macroeconomic Nowcasting and Forecasting with Big Data," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 615-643, August.
  • Brandyn Bok & Daniele Caratelli & Domenico Giannone & Argia M. Sbordone & Andrea Tambalotti, 2017. "Macroeconomic nowcasting and forecasting with big data," Staff Reports 830, Federal Reserve Bank of New York.
  • Giannone, Domenico & Tambalotti, Andrea & Sbordone, Argia & Bok, Brandyn & Caratelli, Daniele, 2018. "Macroeconomic Nowcasting and Forecasting with Big Data," CEPR Discussion Papers 12589, C.E.P.R. Discussion Papers.
• Gonzalo Villa-Cox & Everardo Quezada & Joseph Aguilar-Bohorquez & Ivanna Valverde-Bajana & Paul Vera-Gilces, 2018. "Diseño experimental para la entrada de una firma en un mercado monopolístico con efectos de red: caso de estudio con estudiantes de pregrado en un rol empresarial," Cuadernos de Economía - Spanish Journal of Economics and Finance, Asociación Cuadernos de Economía, vol. 41(115), pages 130-139, Enero.
• Angers, Jean-François & Desjardins, Denise & Dionne, Georges & Guertin, François, 2018. "Modelling And Estimating Individual And Firm Effects With Count Panel Data," ASTIN Bulletin, Cambridge University Press, vol. 48(3), pages 1049-1078, September.
  • Jean-François Angers & Denise Desjardins & Georges Dionne & François Guertin, 2015. "Modelling and Estimating Individual and Firm Effects with Count Panel Data," Cahiers de recherche 1506, CIRPEE.
  • Angers, Jean-François & Desjardins, Denise & Dionne, Georges & Guertin, François, 2018. "Modelling and Estimating Individual and Firm Effects with Count Panel Data," Working Papers 15-2, HEC Montreal, Canada Research Chair in Risk Management.
• Bruce Headey & Gert G. Wagner, 2018. "Alternative Values-Based 'Recipes' for Life Satisfaction: German Results with an Australian Replication," CESifo Working Paper Series 7234, CESifo.
  • Bruce Headey & Gert G. Wagner, 2018. "Alternative Values-Based ‘Recipes’ for Life Satisfaction: German Results with an Australian Replication," SOEPpapers on Multidisciplinary Panel Data Research 982, DIW Berlin, The German Socio-Economic Panel (SOEP).
  • Headey, Bruce & Wagner, Gert G., 2018. "Alternative Values-Based 'Recipes' for Life Satisfaction: German Results with an Australian Replication," IZA Discussion Papers 11818, Institute of Labor Economics (IZA).
• Schaefer, Maximilian & Sapi, Geza & Lorincz, Szabolcs, 2018. "The effect of big data on recommendation quality: The example of internet search," DICE Discussion Papers 284, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
  • Maximilian Schäfer & Geza Sapi & Szabolcs Lorincz, 2018. "The Effect of Big Data on Recommendation Quality: The Example of Internet Search," Discussion Papers of DIW Berlin 1730, DIW Berlin, German Institute for Economic Research.
• Fornaro, Paolo & Luomaranta, Henri, 2018. "Aggregate fluctuations and the effect of large corporations: Evidence from Finnish monthly data," Economic Modelling, Elsevier, vol. 70(C), pages 245-258.
• Jones, Benjamin A., 2018. "Forest-attacking Invasive Species and Infant Health: Evidence From the Invasive Emerald Ash Borer," Ecological Economics, Elsevier, vol. 154(C), pages 282-293.
• Xiang, Jingjie & Li, Kunpeng & Cui, Guowei, 2018. "A note on the asymptotic properties of least squares estimation in high dimensional constrained factor models," Economics Letters, Elsevier, vol. 171(C), pages 144-148.
• Chevillon, Guillaume & Hecq, Alain & Laurent, Sébastien, 2018. "Generating univariate fractional integration within a large VAR(1)," Journal of Econometrics, Elsevier, vol. 204(1), pages 54-65.
  • Guillaume Chevillon & Alain Hecq & Sébastien Laurent, 2018. "Generating Univariate Fractional Integration within a Large VAR(1)," Working Papers halshs-01944588, HAL.
  • Guillaume Chevillon & Alain Hecq & Sébastien Laurent, 2018. "Generating univariate fractional integration within a large VAR(1)," Post-Print hal-01980783, HAL.
  • Guillaume Chevillon & Alain Hecq & Sébastien Laurent, 2018. "Generating Univariate Fractional Integration within a Large VAR(1)," AMSE Working Papers 1844, Aix-Marseille School of Economics, France.
• Corradi, Valentina & Silvapulle, Mervyn J. & Swanson, Norman R., 2018. "Testing for jumps and jump intensity path dependence," Journal of Econometrics, Elsevier, vol. 204(2), pages 248-267.
• Lam, Clifford & Feng, Phoenix, 2018. "A nonparametric eigenvalue-regularized integrated covariance matrix estimator for asset return data," Journal of Econometrics, Elsevier, vol. 206(1), pages 226-257.
• Chen, Le-Yu & Lee, Sokbae, 2018. "Best subset binary prediction," Journal of Econometrics, Elsevier, vol. 206(1), pages 39-56.
  • Le-Yu Chen & Sokbae Lee, 2016. "Best Subset Binary Prediction," Papers 1610.02738, arXiv.org, revised May 2018.
  • Le-Yu Chen & Sokbae (Simon) Lee, 2017. "Best subset binary prediction," CeMMAP working papers 50/17, Institute for Fiscal Studies.
  • Le-Yu Chen & Sokbae (Simon) Lee, 2017. "Best subset binary prediction," CeMMAP working papers CWP50/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
• Jåstad, Eirik Ogner & Mustapha, Walid Fayez & Bolkesjø, Torjus Folsland & Trømborg, Erik & Solberg, Birger, 2018. "Modelling of uncertainty in the economic development of the Norwegian forest sector," Journal of Forest Economics, Elsevier, vol. 32(C), pages 106-115.
• Hofmarcher, Paul & Crespo Cuaresma, Jesus & Grün, Bettina & Humer, Stefan & Moser, Mathias, 2018. "Bivariate jointness measures in Bayesian Model Averaging: Solving the conundrum," Journal of Macroeconomics, Elsevier, vol. 57(C), pages 150-165.
• Kareem, Olayinka Idowu, 2018. "The determinants of large-scale land investments in Africa," Land Use Policy, Elsevier, vol. 75(C), pages 180-190.
• Whitaker, Stephan D., 2018. "Big Data versus a survey," The Quarterly Review of Economics and Finance, Elsevier, vol. 67(C), pages 285-296.
  • Stephan D. Whitaker, 2015. "Big Data versus a Survey," Working Papers (Old Series) 1440, Federal Reserve Bank of Cleveland.
• Richardson, Adam & van Florenstein Mulder, Thomas & Vehbi, Tuğrul, 2021. "Nowcasting GDP using machine-learning algorithms: A real-time assessment," International Journal of Forecasting, Elsevier, vol. 37(2), pages 941-948.
  • Adam Richardson & Thomas van Florenstein Mulder & Tugrul Vehbi, 2019. "Nowcasting New Zealand GDP using machine learning algorithms," IFC Bulletins chapters, in: Bank for International Settlements (ed.), The use of big data analytics and artificial intelligence in central banking, volume 50, Bank for International Settlements.
  • Adam Richardson & Thomas van Florenstein Mulder & Tugrul Vehbi, 2018. "Nowcasting New Zealand GDP using machine learning algorithms," CAMA Working Papers 2018-47, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Brian Micallef, 2018. "Constructing an index to examine house price misalignment with fundamentals in Malta," International Journal of Housing Markets and Analysis, Emerald Group Publishing Limited, vol. 11(2), pages 315-334, January.
• Franses, Ph.H.B.F. & Wiemann, T., 2018. "Intertemporal Similarity of Economic Time Series," Econometric Institute Research Papers EI2018-30, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
• Peiyang Guo & Jacqueline CK Lam & Victor OK Li, 2018. "A novel machine learning approach for identifying the drivers of domestic electricity users' price responsiveness," Working Papers EPRG 1824, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
• Jan Janku & Zuzana Kucerova, 2018. "Successful Crowdfunding Campaigns: The Role of Project Specifics, Competition and Founders’ Experience," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 68(4), pages 351-373, September.
• Trucíos, Carlos & Hotta, Luiz K. & Valls Pereira, Pedro L., 2019. "On the robustness of the principal volatility components," Journal of Empirical Finance, Elsevier, vol. 52(C), pages 201-219.
  • Trucíos Maza, Carlos César & Hotta, Luiz Koodi & Pereira, Pedro L. Valls, 2018. "On the robustness of the principal volatility components," Textos para discussão 474, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
• Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2020. "Assessing international commonality in macroeconomic uncertainty and its effects," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(3), pages 273-293, April.
  • Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2018. "Assessing International Commonality in Macroeconomic Uncertainty and Its Effects," Working Papers (Old Series) 1803, Federal Reserve Bank of Cleveland.
  • Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2019. "Assessing International Commonality in Macroeconomic Uncertainty and Its Effects," Working Papers 18-03R, Federal Reserve Bank of Cleveland.
  • Marcellino, Massimiliano & Clark, Todd & Carriero, Andrea, 2019. "Assessing International Commonality in Macroeconomic Uncertainty and Its Effects," CEPR Discussion Papers 13970, C.E.P.R. Discussion Papers.
• Jack DeWaard & Janna Johnson & Stephan D. Whitaker, 2018. "Internal Migration in the United States: A Comparative Assessment of the Utility of the Consumer Credit Panel," Working Papers (Old Series) 1804, Federal Reserve Bank of Cleveland.
• Christopher L. Foote & Lara Loewenstein & Paul S. Willen, 2018. "Technological Innovation in Mortgage Underwriting and the Growth in Credit: 1985-2015," Working Papers (Old Series) 1816, Federal Reserve Bank of Cleveland.
  • Christopher L. Foote & Lara Loewenstein & Paul S. Willen, 2019. "Technological innovation in mortgage underwriting and the growth in credit, 1985–2015," Working Papers 19-11, Federal Reserve Bank of Boston.
• Tomaz Cajner & Leland D. Crane & Ryan A. Decker & Adrian Hamins-Puertolas & Christopher J. Kurz & Tyler Radler, 2018. "Using Payroll Processor Microdata to Measure Aggregate Labor Market Activity," Finance and Economics Discussion Series 2018-005, Board of Governors of the Federal Reserve System (U.S.).
• Gregory J. Cohen & Melanie Friedrichs & Kamran Gupta & William Hayes & Seung Jung Lee & W. Blake Marsh & Nathan Mislang & Maya Shaton & Martin Sicilian, 2018. "The U.S. Syndicated Loan Market: Matching Data," Research Working Paper RWP 18-9, Federal Reserve Bank of Kansas City.
  • Gregory J. Cohen & Melanie Friedrichs & Kamran Gupta & William Hayes & Seung Jung Lee & W. Blake Marsh & Nathan Mislang & Maya Shaton & Martin Sicilian, 2018. "The U.S. Syndicated Loan Market : Matching Data," Finance and Economics Discussion Series 2018-085, Board of Governors of the Federal Reserve System (U.S.).
• Gregory J. Cohen & Melanie Friedrichs & Kamran Gupta & William Hayes & Seung Jung Lee & W. Blake Marsh & Nathan Mislang & Maya Shaton & Martin Sicilian, 2018. "The U.S. Syndicated Loan Market : Matching Data," Finance and Economics Discussion Series 2018-085, Board of Governors of the Federal Reserve System (U.S.).
  • Gregory J. Cohen & Melanie Friedrichs & Kamran Gupta & William Hayes & Seung Jung Lee & W. Blake Marsh & Nathan Mislang & Maya Shaton & Martin Sicilian, 2018. "The U.S. Syndicated Loan Market: Matching Data," Research Working Paper RWP 18-9, Federal Reserve Bank of Kansas City.
• Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2021. "Economic Predictions With Big Data: The Illusion of Sparsity," Econometrica, Econometric Society, vol. 89(5), pages 2409-2437, September.
  • Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio, 2017. "Economic Predictions with Big Data: The Illusion Of Sparsity," CEPR Discussion Papers 12256, C.E.P.R. Discussion Papers.
  • Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2018. "Economic predictions with big data: the illusion of sparsity," Staff Reports 847, Federal Reserve Bank of New York.
  • Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio E., 2021. "Economic predictions with big data: the illusion of sparsity," Working Paper Series 2542, European Central Bank.
  • Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2018. "Economic Predictions with Big Data: The Illusion of Sparsity," Liberty Street Economics 20180521, Federal Reserve Bank of New York.
• Niels Framroze Møller & Laura Mørch Andersen & Lars Gårn Hansen & Carsten Lynge Jensen, 2018. "Can pecuniary and environmental incentives via SMS messaging make households adjust their intra-day electricity demand to a fluctuating production?," IFRO Working Paper 2018/06, University of Copenhagen, Department of Food and Resource Economics.
• Chevillon, Guillaume & Hecq, Alain & Laurent, Sébastien, 2018. "Generating univariate fractional integration within a large VAR(1)," Journal of Econometrics, Elsevier, vol. 204(1), pages 54-65.
  • Guillaume Chevillon & Alain Hecq & Sébastien Laurent, 2018. "Generating Univariate Fractional Integration within a Large VAR(1)," Working Papers halshs-01944588, HAL.
  • Guillaume Chevillon & Alain Hecq & Sébastien Laurent, 2018. "Generating univariate fractional integration within a large VAR(1)," Post-Print hal-01980783, HAL.
  • Guillaume Chevillon & Alain Hecq & Sébastien Laurent, 2018. "Generating Univariate Fractional Integration within a Large VAR(1)," AMSE Working Papers 1844, Aix-Marseille School of Economics, France.
• Arthur Charpentier & Emmanuel Flachaire & Antoine Ly, 2018. "Econometrics and Machine Learning," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 505-506, pages 147-169.
  • Arthur Charpentier & Emmanuel Flachaire & Antoine Ly, 2018. "Econometrics and Machine Learning," Post-Print hal-02163979, HAL.
• Chevillon, Guillaume & Hecq, Alain & Laurent, Sébastien, 2018. "Generating univariate fractional integration within a large VAR(1)," Journal of Econometrics, Elsevier, vol. 204(1), pages 54-65.
  • Guillaume Chevillon & Alain Hecq & Sébastien Laurent, 2018. "Generating univariate fractional integration within a large VAR(1)," Post-Print hal-01980783, HAL.
  • Guillaume Chevillon & Alain Hecq & Sébastien Laurent, 2018. "Generating Univariate Fractional Integration within a Large VAR(1)," Working Papers halshs-01944588, HAL.
  • Guillaume Chevillon & Alain Hecq & Sébastien Laurent, 2018. "Generating Univariate Fractional Integration within a Large VAR(1)," AMSE Working Papers 1844, Aix-Marseille School of Economics, France.
• Baum, Christopher F & Lööf, Hans & Perez, Luis & Stephan, Andreas, 2018. "Offshoring and Innovation Capabilities: Evidence from Swedish Manufacturing," Working Paper Series in Economics and Institutions of Innovation 469, Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies.
• Narges Ahani & Tommy Andersson & Alessandro Martinello & Alexander Teytelboym & Andrew C. Trapp, 2021. "Placement Optimization in Refugee Resettlement," Operations Research, INFORMS, vol. 69(5), pages 1468-1486, September.
  • Trapp, Andrew C. & Teytelboym, Alexander & Martinello, Alessandro & Andersson, Tommy & Ahani, Narges, 2018. "Placement Optimization in Refugee Resettlement," Working Papers 2018:23, Lund University, Department of Economics, revised 20 Mar 2020.
• Ilya Kuzminov & Pavel Bakhtin & Elena Khabirova & Maxim Kotsemir & Alina Lavrynenko, 2018. "Mapping the Radical Innovations in Food Industry: A Text Mining Study," HSE Working papers WP BRP 80/STI/2018, National Research University Higher School of Economics.
• Ilya Kuzminov & Pavel Bakhtin & Elena Khabirova & Irina V. Loginova, 2018. "Detecting and Validating Global Technology Trends Using Quantitative and Expert-Based Foresight Techniques," HSE Working papers WP BRP 82/STI/2018, National Research University Higher School of Economics.
• Ilya Kuzminov & Irina Loginova & Elena Khabirova, 2018. "Stress Scenario Development: Global Challenges For The Russian Agricultural Sector," HSE Working papers WP BRP 88/STI/2018, National Research University Higher School of Economics.
• Vogt, Michael & Linton, Oliver, 2020. "Multiscale clustering of nonparametric regression curves," Journal of Econometrics, Elsevier, vol. 216(1), pages 305-325.
  • Michael Vogt & Oliver Linton, 2018. "Multiscale clustering of nonparametric regression curves," CeMMAP working papers CWP08/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
• Koen Jochmans & Martin Weidner, 2019. "Fixed‐Effect Regressions on Network Data," Econometrica, Econometric Society, vol. 87(5), pages 1543-1560, September.
  • Koen Jochmans & Martin Weidner, 2016. "Fixed-effect regressions on network data," CeMMAP working papers CWP32/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2018. "Fixed-effect regressions on network data," CeMMAP working papers CWP44/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2017. "Fixed-effect regressions on network data," CeMMAP working papers CWP26/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Jochmans, K. & Weidner, M., 2019. "Fixed-Effect Regressions on Network Data," Cambridge Working Papers in Economics 1938, Faculty of Economics, University of Cambridge.
  • Koen Jochmans & Martin Weidner, 2016. "Fixed-Effect Regressions on Network Data," Papers 1608.01532, arXiv.org, revised Apr 2019.
  • Koen Jochmans & Martin Weidner, 2019. "Fixed-effect regressions on network data," CeMMAP working papers CWP16/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2017. "Fixed-effect regressions on network data," CeMMAP working papers 26/17, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2016. "Fixed-effect regressions on network data," CeMMAP working papers 32/16, Institute for Fiscal Studies.
• Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“A geometric approach to proxy economic uncertainty by a metric of disagreement among qualitative expectations”," AQR Working Papers 201803, University of Barcelona, Regional Quantitative Analysis Group, revised Jun 2018.
  • Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“A geometric approach to proxy economic uncertainty by a metric of disagreement among qualitative expectations”," IREA Working Papers 201806, University of Barcelona, Research Institute of Applied Economics, revised Mar 2018.
• Montserrat Guillen & Ana M. Pérez-Marín & Mercedes Ayuso & Jens Perch Nielsen, 2018. "“Exposure to risk increases the excess of zero accident claims frequency in automobile insurance”," IREA Working Papers 201810, University of Barcelona, Research Institute of Applied Economics, revised May 2018.
• Susana Santos & Tanya Araújo, 2018. "The network of inter-industry flows in a SAM framework," Working Papers REM 2018/40, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
• Bruce Headey & Gert G. Wagner, 2018. "Alternative Values-Based 'Recipes' for Life Satisfaction: German Results with an Australian Replication," CESifo Working Paper Series 7234, CESifo.
  • Headey, Bruce & Wagner, Gert G., 2018. "Alternative Values-Based 'Recipes' for Life Satisfaction: German Results with an Australian Replication," IZA Discussion Papers 11818, Institute of Labor Economics (IZA).
  • Bruce Headey & Gert G. Wagner, 2018. "Alternative Values-Based ‘Recipes’ for Life Satisfaction: German Results with an Australian Replication," SOEPpapers on Multidisciplinary Panel Data Research 982, DIW Berlin, The German Socio-Economic Panel (SOEP).
• Susan Dynarski & Brian Jacob & Daniel Kreisman, 2018. "How important are fixed effects and time trends in estimating returns to schooling? Evidence from a replication of Jacobson, Lalonde, and Sullivan, 2005," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 1098-1108, November.
  • Dynarski, Susan & Jacob, Brian A. & Kreisman, Daniel, 2018. "How Important Are Fixed Effects and Time Trends in Estimating Returns to Schooling? Evidence from a Replication of Jacobson, Lalonde and Sullivan, 2005," IZA Discussion Papers 11935, Institute of Labor Economics (IZA).
• Jonathan Hersh & Matthew Harding, 2018. "Big Data in economics," IZA World of Labor, Institute of Labor Economics (IZA), pages 451-451, September.
• Kevin Momanyi, 2018. "A Structural Model of The Demand For Telecare," 2018 Papers pmo1170, Job Market Papers.
• James Lo, 2018. "Dynamic ideal point estimation for the European Parliament, 1980–2009," Public Choice, Springer, vol. 176(1), pages 229-246, July.
• Maurizio Daniele & Winfried Pohlmeier & Aygul Zagidullina, 2018. "Sparse Approximate Factor Estimation for High-Dimensional Covariance Matrices," Working Paper Series of the Department of Economics, University of Konstanz 2018-07, Department of Economics, University of Konstanz.
  • Maurizio Daniele & Winfried Pohlmeier & Aygul Zagidullina, 2020. "Sparse Approximate Factor Estimation for High-Dimensional Covariance Matrices," Working Paper series 20-03, Rimini Centre for Economic Analysis.
  • Maurizio Daniele & Winfried Pohlmeier & Aygul Zagidullina, 2019. "Sparse Approximate Factor Estimation for High-Dimensional Covariance Matrices," Papers 1906.05545, arXiv.org.
• Ralf Brüggemann & Christian Kascha, 2017. "Directed Graphs and Variable Selection in Large Vector Autoregressive Models," Working Paper Series of the Department of Economics, University of Konstanz 2017-06, Department of Economics, University of Konstanz.
  • Bertsche, Dominik & Brüggemann, Ralf & Kascha, Christian, 2019. "Directed Graph and Variable Selection in Large Vector Autoregressive Models," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203656, Verein für Socialpolitik / German Economic Association.
  • Dominik Bertsche & Ralf Brüggemann & Christian Kascha, 2018. "Directed Graphs and Variable Selection in Large Vector Autoregressive Models," Working Paper Series of the Department of Economics, University of Konstanz 2018-08, Department of Economics, University of Konstanz.
• WEBER Matthias, & STRIAUKAS Jonas, & SCHUMACHER Martin, & HARALD Binder,, 2018. "Network constrained covariate coefficient and connection sign estimation," LIDAM Discussion Papers CORE 2018018, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  • Jonas Striaukas & Martin Schumacher & Harald Binder & Matthias Weber, 2020. "Network-Constrained Covariate Coefficient and Connection Sign Estimation," Working Papers on Finance 2001, University of St. Gallen, School of Finance.
  • Matthias Weber & Jonas Striaukas & Martin Schumacher & Harald Binder, 2018. "Network constrained covariate coefficient and connection sign estimation," Bank of Lithuania Discussion Paper Series 8, Bank of Lithuania.
• Montero, José-María, 2018. "Geostatistics: Unde venis et quo vadis? /Geoestadística:¿De dónde vienes y a dónde vas?," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 36, pages 81-106, Enero.
• Ian Borg & Germano Ruisi, 2018. "Forecasting using Bayesian VARs: A Benchmark for STREAM," CBM Working Papers WP/04/2018, Central Bank of Malta.
• Priyanga Dilini Talagala & Rob J Hyndman & Kate Smith-Miles & Sevvandi Kandanaarachchi & Mario A Munoz, 2018. "Anomaly detection in streaming nonstationary temporal data," Monash Econometrics and Business Statistics Working Papers 4/18, Monash University, Department of Econometrics and Business Statistics.
• Dominic Coey & Bradley Larsen & Kane Sweeney & Caio Waisman, 2018. "The Simple Empirics of Optimal Online Auctions," NBER Working Papers 24698, National Bureau of Economic Research, Inc.
• Steven F. Lehrer & Tian Xie, 2022. "The Bigger Picture: Combining Econometrics with Analytics Improves Forecasts of Movie Success," Management Science, INFORMS, vol. 68(1), pages 189-210, January.
  • Steven F. Lehrer & Tian Xie, 2018. "The Bigger Picture: Combining Econometrics with Analytics Improve Forecasts of Movie Success," NBER Working Papers 24755, National Bureau of Economic Research, Inc.
  • Steven Lehrer & Tian Xie, 2020. "The Bigger Picture: Combining Econometrics with Analytics Improve Forecasts of Movie Success," Working Paper 1449, Economics Department, Queen's University.
• Shihao Gu & Bryan Kelly & Dacheng Xiu, 2020. "Empirical Asset Pricing via Machine Learning," The Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2223-2273.
  • Shihao Gu & Bryan T. Kelly & Dacheng Xiu, 2018. "Empirical Asset Pricing via Machine Learning," Swiss Finance Institute Research Paper Series 18-71, Swiss Finance Institute.
  • Shihao Gu & Bryan Kelly & Dacheng Xiu, 2018. "Empirical Asset Pricing via Machine Learning," NBER Working Papers 25398, National Bureau of Economic Research, Inc.
• Benjamin Sakarovitch & Marie-Pierre de Bellefon & Pauline Givord & Maarten Vanhoof, 2018. "Estimating the Residential Population from Mobile Phone Data, an Initial Exploration," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 505-506, pages 109-132.
• Lorie Dudoignon & Fabienne Le Sager & Aurélie Vanheuverzwyn, 2018. "Big Data and Audience Measurement: A Marriage of Convenience?," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 505-506, pages 133-146.
• Arthur Charpentier & Emmanuel Flachaire & Antoine Ly, 2018. "Econometrics and Machine Learning," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 505-506, pages 147-169.
  • Arthur Charpentier & Emmanuel Flachaire & Antoine Ly, 2018. "Econometrics and Machine Learning," Post-Print hal-02163979, HAL.
• George Kapetanios & Fotis Papailias, 2018. "Big Data & Macroeconomic Nowcasting: Methodological Review," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-12, Economic Statistics Centre of Excellence (ESCoE).
• Paul Labonne & Martin Weale, 2018. "Temporal disaggregation of overlapping noisy quarterly data using state space models: Estimation of monthly business sector output from Value Added Tax data in the UK," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-18, Economic Statistics Centre of Excellence (ESCoE).
• Tommaso Proietti & Alessandro Giovannelli, 2018. "A Durbin–Levinson regularized estimator of high-dimensional autocovariance matrices," Biometrika, Biometrika Trust, vol. 105(4), pages 783-795.
  • Tommaso Proietti & Alessandro Giovannelli, 2017. "A Durbin-Levinson Regularized Estimator of High Dimensional Autocovariance Matrices," CREATES Research Papers 2017-20, Department of Economics and Business Economics, Aarhus University.
  • Tommaso Proietti & Alessandro Giovannelli, 2017. "A Durbin-Levinson Regularized Estimator of High Dimensional Autocovariance Matrices," CEIS Research Paper 410, Tor Vergata University, CEIS, revised 19 Jul 2017.
• Jon Kleinberg & Himabindu Lakkaraju & Jure Leskovec & Jens Ludwig & Sendhil Mullainathan, 2018. "Human Decisions and Machine Predictions," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 133(1), pages 237-293.
  • Jon Kleinberg & Himabindu Lakkaraju & Jure Leskovec & Jens Ludwig & Sendhil Mullainathan, 2017. "Human Decisions and Machine Predictions," NBER Working Papers 23180, National Bureau of Economic Research, Inc.
• Oprea Simona Vasilica & Bâra Adela & Elefterescu LuminiÈ›a, 2018. "Decision Support System Design for Photovoltaic Systems Operation and Maintenance by using Big Data Technologies," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(1), pages 104-110, July.
• Bâra Adela & Oprea Simona Vasilica & PreoÈ›escu Dan, 2018. "Data Management for Photovoltaic Power Plants Operation and Maintenance," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(1), pages 70-75, July.
• David Troncoso-Ponce, 2018. "Estimation of competing risks duration models with unobserved heterogeneity using hsmlogit," Working Papers 18.03, Universidad Pablo de Olavide, Department of Economics.
• Garanasvili, Antanina & Kazimierczak, Michal & Lazaridis, George, 2018. "The Use of Intellectual Property Right Bundles by Firms in Copyright Intensive Industries," MPRA Paper 109493, University Library of Munich, Germany, revised 2021.
• Tierney, Heather L.R. & Kim, Jiyoon (June) & Nazarov, Zafar, 2018. "The Effects of Temporal Aggregation on Search Engine Data," MPRA Paper 84474, University Library of Munich, Germany.
• Chakraborty, Lekha S & Singh, Yadawendra, 2018. "Fiscal Policy, as the “Employer of Last Resort”: Impact of Direct fiscal transfer (MGNREGA) on Labour Force Participation Rates in India," MPRA Paper 85225, University Library of Munich, Germany.
• Verstappen, Ksenia, 2018. "Economics of big data: review of best papers for January 2018," MPRA Paper 85520, University Library of Munich, Germany.
• Kim, Hyeongwoo & Ko, Kyunghwan, 2020. "Improving forecast accuracy of financial vulnerability: PLS factor model approach," Economic Modelling, Elsevier, vol. 88(C), pages 341-355.
  • Hyeongwoo Kim & Kyunghwan Ko, 2017. "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," Auburn Economics Working Paper Series auwp2017-03, Department of Economics, Auburn University.
  • Hyeongwoo Kim & Kyunghwan Ko, 2019. "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," Auburn Economics Working Paper Series auwp2019-03, Department of Economics, Auburn University.
  • Kim, Hyeongwoo & Ko, Kyunghwan, 2018. "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," MPRA Paper 89449, University Library of Munich, Germany.
• Asante Gyamerah, Samuel & Ngare, Philip & Ikpe, Dennis, 2018. "A Levy Regime-Switching Temperature Dynamics Model for Weather Derivatives," MPRA Paper 89680, University Library of Munich, Germany, revised 10 Jul 2018.
• bailek, Alexandra, 2018. "Economic Impact Analysis of Hospital Readmission Rate and Service Quality Using Machine Learning," MPRA Paper 89875, University Library of Munich, Germany.
• Ogunlesi, Ayodeji, 2018. "Agricultural Productivity, Fiscal and Trade Policies Nexus in Sub-Saharan Africa: A Panel Structural Vector Error Correction Model Analysis," MPRA Paper 90202, University Library of Munich, Germany.
• Aleksandra Halka & Grzegorz Szafranski, 2018. "What Common Factors are Driving Inflation in CEE Countries?," Prague Economic Papers, Prague University of Economics and Business, vol. 2018(2), pages 131-148.
  • Aleksandra Halka & Grzegorz Szafrański, 2014. "What common factors are driving inflation in CEE countries?," EcoMod2014 6977, EcoMod.
  • Aleksandra Hałka & Grzegorz Szafrański, 2015. "What common factors are driving inflation in CEE countries?," NBP Working Papers 225, Narodowy Bank Polski.
• Jan Hanousek & Štěpán Jurajda, 2018. "Názvy společností a jejich vliv na výkonnost firem [Corporate Names and Performance]," Politická ekonomie, Prague University of Economics and Business, vol. 2018(6), pages 671-688.
• Chantawit Tantasith & Nasha Ananchotikul & Chatlada Chotanakarn & Vorada Limjaroenrat & Runchana Pongsaparn, 2018. "The Impact of LTV policy on Bank Lending: Evidence from Disaggregate Housing Loan Data," PIER Discussion Papers 90, Puey Ungphakorn Institute for Economic Research.
• Anttonen, Jetro, 2018. "Nowcasting the Unemployment Rate in the EU with Seasonal BVAR and Google Search Data," ETLA Working Papers 62, The Research Institute of the Finnish Economy.
• SAIDI, Abdessamad & BENAZZI, Sara & EL OTHMANI, Jawad, 2018. "Capital humain au Maroc: Evaluation fondée sur le revenu de la vie entière," Document de travail 2018-1, Bank Al-Maghrib, Département de la Recherche.
• Angers, Jean-François & Desjardins, Denise & Dionne, Georges & Guertin, François, 2018. "Modelling And Estimating Individual And Firm Effects With Count Panel Data," ASTIN Bulletin, Cambridge University Press, vol. 48(3), pages 1049-1078, September.
  • Jean-François Angers & Denise Desjardins & Georges Dionne & François Guertin, 2015. "Modelling and Estimating Individual and Firm Effects with Count Panel Data," Cahiers de recherche 1506, CIRPEE.
  • Angers, Jean-François & Desjardins, Denise & Dionne, Georges & Guertin, François, 2018. "Modelling and Estimating Individual and Firm Effects with Count Panel Data," Working Papers 15-2, HEC Montreal, Canada Research Chair in Risk Management.
• Lee, Jin-Myon & Park, Kayoung, 2018. "Utilization and Development of Big Data for Official Statistics," Industrial Economic Review 18-1, Korea Institute for Industrial Economics and Trade.
• Sumana Chaudhuri & Shovan Ray & Ganesh-Kumar, 2018. "Integrated Model of Computable General Equilibrium and Social Cost Benefit Analysis of an Indian Oil Refinery: Future Projections and Macroeconomic Effects," Journal of Infrastructure Development, India Development Foundation, vol. 10(1-2), pages 96-125, June.
  • Shovan Ray & A. Ganesh Kumar & Sumana Chaudhuri, 2016. "Integrated model of computable general equilibrium and social cost benefit analysis of an Indian oil refinery: Future projections and macroeconomic effects," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2016-024, Indira Gandhi Institute of Development Research, Mumbai, India.
  • Shovan Ray & A. Ganesh-Kumar & Sumana Chaudhuri, 2016. "Integrated Model of Computable General Equilibrium and Social Cost Benefit Analysis of an Indian Oil Refinery: Future Projections and Macroeconomic Effects," Working Papers id:11381, eSocialSciences.
• Łukasz Lipiński & Michał Bernardelli, 2018. "Anonimowość w Internecie – identyfikacja płci użytkowników na podstawie historii odwiedzanych stron internetowych," Collegium of Economic Analysis Annals, Warsaw School of Economics, Collegium of Economic Analysis, issue 53, pages 147-162.
• Philipp Otto & Wolfgang Schmid, 2018. "Spatiotemporal analysis of German real-estate prices," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 60(1), pages 41-72, January.
• Milena Stróżyna & Gerd Eiden & Witold Abramowicz & Dominik Filipiak & Jacek Małyszko & Krzysztof Węcel, 2018. "A framework for the quality-based selection and retrieval of open data - a use case from the maritime domain," Electronic Markets, Springer;IIM University of St. Gallen, vol. 28(2), pages 219-233, May.
• Inske Pirschel & Maik H. Wolters, 2018. "Forecasting with large datasets: compressing information before, during or after the estimation?," Empirical Economics, Springer, vol. 55(2), pages 573-596, September.
• Grégoire Lagasnerie & Anne-Sophie Aguadé & Pierre Denis & Anne Fagot-Campagna & Christelle Gastaldi-Menager, 2018. "The economic burden of diabetes to French national health insurance: a new cost-of-illness method based on a combined medicalized and incremental approach," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 19(2), pages 189-201, March.
• Valerie Moran & Rowena Jacobs, 2018. "Investigating the relationship between costs and outcomes for English mental health providers: a bi-variate multi-level regression analysis," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 19(5), pages 709-718, June.
• Gordon H. Dash & Nina Kajiji & Domenic Vonella, 2018. "The role of supervised learning in the decision process to fair trade US municipal debt," EURO Journal on Decision Processes, Springer;EURO - The Association of European Operational Research Societies, vol. 6(1), pages 139-168, June.
• Raïsa Basselier & David Antonio Liedo & Geert Langenus, 2018. "Nowcasting Real Economic Activity in the Euro Area: Assessing the Impact of Qualitative Surveys," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(1), pages 1-46, April.
• Alain Galli, 2018. "Which Indicators Matter? Analyzing the Swiss Business Cycle Using a Large-Scale Mixed-Frequency Dynamic Factor Model," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(2), pages 179-218, November.
  • Dr. Alain Galli, 2017. "Which indicators matter? Analyzing the Swiss business cycle using a large-scale mixed-frequency dynamic factor model," Working Papers 2017-08, Swiss National Bank.
• Tanya Araújo & Elsa Fontainha, 2018. "Are scientific memes inherited differently from gendered authorship?," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(2), pages 953-972, November.
• Hanjo Odendaal & Monique Reid & Johann F. Kirsten, 2020. "Media‐Based Sentiment Indices as an Alternative Measure of Consumer Confidence," South African Journal of Economics, Economic Society of South Africa, vol. 88(4), pages 409-434, December.
  • Nicolaas Johannes Odendaal & Monique Reid, 2018. "Media based sentiment indices as an alternative measure of consumer confidence," Working Papers 17/2018, Stellenbosch University, Department of Economics.
• Jochen Lüdering, 2018. "Standing and ‘survival’ in the adult film industry," Applied Economics, Taylor & Francis Journals, vol. 50(16), pages 1812-1823, April.
  • Jochen Lüdering, 2016. "Standing and “Survival” in the Adult Film Industry," MAGKS Papers on Economics 201626, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
• Mahmut Gunay, 2018. "Forecasting industrial production and inflation in Turkey with factor models," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 18(4), pages 149-161.
  • Mahmut Gunay, 2018. "Forecasting Industrial Production and Inflation in Turkey with Factor Models," Working Papers 1805, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
• Mahmut Gunay, 2018. "Forecasting industrial production and inflation in Turkey with factor models," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 18(4), pages 149-161.
  • Mahmut Gunay, 2018. "Forecasting Industrial Production and Inflation in Turkey with Factor Models," Working Papers 1805, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
• Marta Banbura & Andries van Vlodrop, 2018. "Forecasting with Bayesian Vector Autoregressions with Time Variation in the Mean," Tinbergen Institute Discussion Papers 18-025/IV, Tinbergen Institute.
• Andries C. van Vlodrop & Andre (A.) Lucas, 2018. "Estimation Risk and Shrinkage in Vast-Dimensional Fundamental Factor Models," Tinbergen Institute Discussion Papers 18-099/III, Tinbergen Institute.
• Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2018. "Measuring Uncertainty and Its Impact on the Economy," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 799-815, December.
  • Andrea Carriero & Todd E. Clark & Marcellino Massimiliano, 2016. "Measuring Uncertainty and Its Impact on the Economy," Working Papers (Old Series) 1622, Federal Reserve Bank of Cleveland.
  • Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2016. "Measuring Uncertainty and Its Impact on the Economy," BAFFI CAREFIN Working Papers 1639, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
• Giacomo Caterini, 2018. "Classifying Firms with Text Mining," DEM Working Papers 2018/09, Department of Economics and Management.
• Jianghao Chu & Tae-Hwy Lee & Aman Ullah, 2019. "Variable Selection in Sparse Semiparametric Single Index Models," Advances in Econometrics, in: Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling: Part B, volume 40, pages 65-88, Emerald Group Publishing Limited.
  • Tae-Hwy Lee & Jianghao Chu & Aman Ullah, 2018. "Variable Selection in Sparse Semiparametric Single Index Models," Working Papers 201908, University of California at Riverside, Department of Economics.
• Tae-Hwy Lee & Yundong Tu, 2018. "Forecasting Using Supervised Factor Models," Working Papers 201909, University of California at Riverside, Department of Economics.
• Oleksandr Faryna & Oleksandr Talavera & Tetiana Yukhymenko, 2018. "What Drives the Difference between Online and Official Price Indexes?," Visnyk of the National Bank of Ukraine, National Bank of Ukraine, issue 243, pages 21-32.
• Aslanidis, Nektarios & Christiansen, Charlotte & Cipollini, Andrea, 2019. "Predicting bond betas using macro-finance variables," Finance Research Letters, Elsevier, vol. 29(C), pages 193-199.
  • Nektarios Aslanidis & Charlotte Christiansen & Andrea Cipollini, 2017. "Predicting Bond Betas using Macro-Finance Variables," CREATES Research Papers 2017-01, Department of Economics and Business Economics, Aarhus University.
  • Aslanidis, Nektarios, & Christiansen, Charlotte & Cipollini, Andrea & Bons -- Models matemàtics, 2018. "Predicting Bond Betas using Macro-Finance Variables," Working Papers 2072/306546, Universitat Rovira i Virgili, Department of Economics.
• Mengheng Li & Marcel Scharth, 2022. "Leverage, Asymmetry, and Heavy Tails in the High-Dimensional Factor Stochastic Volatility Model," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 285-301, January.
  • Mengheng Li & Marcel Scharth, 2018. "Leverage, asymmetry and heavy tails in the high-dimensional factor stochastic volatility model," Working Paper Series 49, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
• Peter Martey Addo & Dominique Guegan & Bertrand Hassani, 2018. "Credit Risk Analysis using Machine and Deep learning models," Working Papers 2018:08, Department of Economics, University of Venice "Ca' Foscari".
• Rui Pedro Brito & Helder Sebastião & Pedro Godinho, 2018. "On the Gains of Using High Frequency Data in Portfolio Selection," Scientific Annals of Economics and Business (continues Analele Stiintifice), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 65(4), pages 365-383, December.
  • Brito Rui Pedro & Sebastião Helder & Godinho Pedro, 2018. "On the Gains of Using High Frequency Data in Portfolio Selection," Scientific Annals of Economics and Business, Sciendo, vol. 65(4), pages 365-383, December.
• Zekić-Sušac Marijana & Scitovski Rudolf & Has Adela, 2018. "Cluster analysis and artificial neural networks in predicting energy efficiency of public buildings as a cost-saving approach," Croatian Review of Economic, Business and Social Statistics, Sciendo, vol. 4(2), pages 57-66, November.
• Oliver Reiter & Robert Stehrer, 2018. "Trade Policies and Integration of the Western Balkans," wiiw Working Papers 148, The Vienna Institute for International Economic Studies, wiiw.
• A. Chudik & G. Kapetanios & M. Hashem Pesaran, 2018. "A One Covariate at a Time, Multiple Testing Approach to Variable Selection in High‐Dimensional Linear Regression Models," Econometrica, Econometric Society, vol. 86(4), pages 1479-1512, July.
  • Alexander Chudik & George Kapetanios & M. Hashem Pesaran, 2016. "A one-covariate at a time, multiple testing approach to variable selection in high-dimensional linear regression models," Globalization Institute Working Papers 290, Federal Reserve Bank of Dallas.
  • Chudik, A. & Kapetanios, G. & Pesaran, Hashem, 2016. "A One-Covariate at a Time, Multiple Testing Approach to Variable Selection in High-Dimensional Linear Regression Models," Cambridge Working Papers in Economics 1677, Faculty of Economics, University of Cambridge.
• Susan Dynarski & Brian Jacob & Daniel Kreisman, 2018. "How important are fixed effects and time trends in estimating returns to schooling? Evidence from a replication of Jacobson, Lalonde, and Sullivan, 2005," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 1098-1108, November.
  • Dynarski, Susan & Jacob, Brian A. & Kreisman, Daniel, 2018. "How Important Are Fixed Effects and Time Trends in Estimating Returns to Schooling? Evidence from a Replication of Jacobson, Lalonde and Sullivan, 2005," IZA Discussion Papers 11935, Institute of Labor Economics (IZA).
• Carriero, Andrea & Galvao, Ana Beatriz & Marcellino, Massimiliano, 2018. "Credit Conditions and the Asymmetric Effects of Monetary Policy Shocks," EMF Research Papers 17, Economic Modelling and Forecasting Group.
• Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“Tracking economic growth by evolving expectations via genetic programming: A two-step approach”," IREA Working Papers 201801, University of Barcelona, Research Institute of Applied Economics, revised Jan 2018.
  • Oscar Claveria & Enric Monte & Salvador Torra, 2018. "Tracking economic growth by evolving expectations via genetic programming: A two-step approach," Working Papers XREAP2018-4, Xarxa de Referència en Economia Aplicada (XREAP), revised Oct 2018.
  • Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“Tracking economic growth by evolving expectations via genetic programming: A two-step approach”," AQR Working Papers 201801, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2018.
• Chen, Jia & Li, Degui & Linton, Oliver, 2019. "A new semiparametric estimation approach for large dynamic covariance matrices with multiple conditioning variables," Journal of Econometrics, Elsevier, vol. 212(1), pages 155-176.
  • Chen, J. & Li, D. & Linton, O., 2018. "A New Semiparametric Estimation Approach for Large Dynamic Covariance Matrices with Multiple Conditioning Variables," Cambridge Working Papers in Economics 1876, Faculty of Economics, University of Cambridge.
  • Jia Chen & Degui Li & Oliver Linton, 2018. "A New Semiparametric Estimation Approach for Large Dynamic Covariance Matrices with Multiple Conditioning Variables," Discussion Papers 18/14, Department of Economics, University of York.
• Jeannine Bailliu & Xinfen Han & Mark Kruger & Yu-Hsien Liu & Sri Thanabalasingam, 2019. "Can media and text analytics provide insights into labour market conditions in China?," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Are post-crisis statistical initiatives completed?, volume 49, Bank for International Settlements.
  • Bailliu, Jeannine & Han, Xinfen & Kruger, Mark & Liu, Yu-Hsien & Thanabalasingam, Sri, 2019. "Can media and text analytics provide insights into labour market conditions in China?," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1118-1130.
  • Jeannine Bailliu & Xinfen Han & Mark Kruger & Yu-Hsien Liu & Sri Thanabalasingam, 2018. "Can Media and Text Analytics Provide Insights into Labour Market Conditions in China?," Staff Working Papers 18-12, Bank of Canada.
  • Bailliu, Jeannine & Han, Xinfen & Kruger, Mark & Liu, Yu-Hsien & Thanabalasingam, Sri, 2018. "Can media and text analytics provide insights into labour market conditions in China?," BOFIT Discussion Papers 9/2018, Bank of Finland Institute for Emerging Economies (BOFIT).
• Maximilian Schäfer & Geza Sapi & Szabolcs Lorincz, 2018. "The Effect of Big Data on Recommendation Quality: The Example of Internet Search," Discussion Papers of DIW Berlin 1730, DIW Berlin, German Institute for Economic Research.
  • Schaefer, Maximilian & Sapi, Geza & Lorincz, Szabolcs, 2018. "The effect of big data on recommendation quality: The example of internet search," DICE Discussion Papers 284, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
• Ricardo Hausmann & Julian Hinz & Muhammed A. Yildirim, 2018. "Measuring Venezuelan Emigration with Twitter," Growth Lab Working Papers 113, Harvard's Growth Lab.
  • Hausmann, Ricardo & Hinz, Julian & Yildirim, Muhammed A., 2018. "Measuring Venezuelan emigration with Twitter," Kiel Working Papers 2106, Kiel Institute for the World Economy (IfW Kiel).
  • Ricardo Hausmann & Julian Hinz & Muhammed A. Yildirim, 2018. "Measuring Venezuelan Emigration with Twitter," CID Working Papers 342, Center for International Development at Harvard University.
• Daniel Volker & Neubert Magnus & Orban Agnes, 2018. "Fictional Expectations and the Global Media in the Greek Debt Crisis: A Topic Modeling Approach," Jahrbuch für Wirtschaftsgeschichte / Economic History Yearbook, De Gruyter, vol. 59(2), pages 525-566, May.
  • Daniel, Volker & Neubert, Magnus & Orban, Agnes, 2018. "Fictional expectations and the global media in the Greek debt crisis: A topic modeling approach," Working Papers 4, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
• Klos, Jonas & Krieger, Tim & Stöwhase, Sven, 2018. "A New Measure of Intra-generational Redistribution within PAYG Pension Schemes and its Application to German Micro-data," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181580, Verein für Socialpolitik / German Economic Association.
• Simon Beyeler & Sylvia Kaufmann, 2016. "Factor augmented VAR revisited - A sparse dynamic factor model approach," Working Papers 16.08, Swiss National Bank, Study Center Gerzensee.
  • Kaufmann, Sylvia & Beyeler, Simon, 2018. "Factor augmented VAR revisited - A sparse dynamic factor model approach," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181602, Verein für Socialpolitik / German Economic Association.
  • Simon Beyeler & Sylvia Kaufmann, 2019. "Factor augmented VAR revisited - A sparse dynamic factor model approach," Working Papers 16.08R, Swiss National Bank, Study Center Gerzensee.
• Simon Jäger & Benjamin Schoefer & Josef Zweimüller, 2023. "Marginal Jobs and Job Surplus: A Test of the Efficiency of Separations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 90(3), pages 1265-1303.
  • Simon Jäger & Benjamin Schoefer & Josef Zweimüller, 2018. "Marginal jobs and job surplus: a test of the efficiency of separations," ECON - Working Papers 314, Department of Economics - University of Zurich.
  • Simon Jäger & Benjamin Schoefer & Josef Zweimüller, 2019. "Marginal Jobs and Job Surplus: A Test of the Efficiency of Separations," NBER Working Papers 25492, National Bureau of Economic Research, Inc.
  • Jäger, Simon & Schoefer, Benjamin & Zweimüller, Josef, 2019. "Marginal Jobs and Job Surplus: A Test of the Efficiency of Separations," IZA Discussion Papers 12127, Institute of Labor Economics (IZA).
  • Zweimüller, Josef & Jäger, Simon & Schoefer, Benjamin, 2019. "Marginal Jobs and Job Surplus: A Test of the Efficiency of Separations," CEPR Discussion Papers 13473, C.E.P.R. Discussion Papers.

2017

• Tommaso Proietti & Alessandro Giovannelli, 2018. "A Durbin–Levinson regularized estimator of high-dimensional autocovariance matrices," Biometrika, Biometrika Trust, vol. 105(4), pages 783-795.
  • Tommaso Proietti & Alessandro Giovannelli, 2017. "A Durbin-Levinson Regularized Estimator of High Dimensional Autocovariance Matrices," CEIS Research Paper 410, Tor Vergata University, CEIS, revised 19 Jul 2017.
  • Tommaso Proietti & Alessandro Giovannelli, 2017. "A Durbin-Levinson Regularized Estimator of High Dimensional Autocovariance Matrices," CREATES Research Papers 2017-20, Department of Economics and Business Economics, Aarhus University.
• Martin M. Andreasen & Jens H. E. Christensen & Glenn D. Rudebusch, 2017. "Term Structure Analysis with Big Data," Working Paper Series 2017-21, Federal Reserve Bank of San Francisco.
  • Martin M. Andreasen & Jens H.E. Christensen & Glenn D. Rudebusch, 2017. "Term Structure Analysis with Big Data," CREATES Research Papers 2017-31, Department of Economics and Business Economics, Aarhus University.
• Kim, Hyeongwoo & Ko, Kyunghwan, 2020. "Improving forecast accuracy of financial vulnerability: PLS factor model approach," Economic Modelling, Elsevier, vol. 88(C), pages 341-355.
  • Hyeongwoo Kim & Kyunghwan Ko, 2017. "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," Auburn Economics Working Paper Series auwp2017-03, Department of Economics, Auburn University.
  • Hyeongwoo Kim & Kyunghwan Ko, 2019. "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," Auburn Economics Working Paper Series auwp2019-03, Department of Economics, Auburn University.
  • Kim, Hyeongwoo & Ko, Kyunghwan, 2018. "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," MPRA Paper 89449, University Library of Munich, Germany.
• Christian Gouriéroux & Alain Monfort & Eric Renault, 2017. "Consistent Pseudo-Maximum Likelihood Estimators," Annals of Economics and Statistics, GENES, issue 125-126, pages 187-218.
  • Christian Gouriéroux & Alain Monfort & Eric Renault, 2016. "Consistent Pseudo-Maximum Likelihood Estimators," Working Papers 2016-33, Center for Research in Economics and Statistics.
  • Christian Gouriéroux & Alain Monfort & Eric Renault, 2017. "Consistent Pseudo-Maximum Likelihood Estimators," Working Papers 2017-10, Center for Research in Economics and Statistics.
• Luis Alejandro Lopez-Agudo & John Jerrim & Oscar David Marcenaro Gutierrez & Nikki Shure, 2017. "To weight or not to weight?: the case of PISA data," Investigaciones de Economía de la Educación volume 12, in: Juan Cándido Gómez Gallego & María Concepción Pérez Cárceles & Laura Nieto Torrejón (ed.), Investigaciones de Economía de la Educación 12, edition 1, volume 12, chapter 13, pages 285-302, Asociación de Economía de la Educación.
• Sorin Manole & Laura Panoiu & Adriana Paunescu, 2017. "Impact of Migration upon a Receiving Country’s Economic Development," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 19(46), pages 670-670, August.
• T. Tony Cai & Wenguang Sun, 2017. "Large-Scale Global and Simultaneous Inference: Estimation and Testing in Very High Dimensions," Annual Review of Economics, Annual Reviews, vol. 9(1), pages 411-439, September.
• Oscar Claveria & Enric Monte & Salvador Torra, 2017. "Let the data do the talking: Empirical modelling of survey-based expectations by means of genetic programming," IREA Working Papers 201711, University of Barcelona, Research Institute of Applied Economics, revised May 2017.
  • Oscar Claveria & Enric Monte & Salvador Torra, 2017. "“Let the data do the talking: Empirical modelling of survey-based expectations by means of genetic programming”," AQR Working Papers 201706, University of Barcelona, Regional Quantitative Analysis Group, revised May 2017.
• Franchi, Massimo & Paruolo, Paolo, 2020. "Cointegration In Functional Autoregressive Processes," Econometric Theory, Cambridge University Press, vol. 36(5), pages 803-839, October.
  • Massimo Franchi & Paolo Paruolo, 2017. "Cointegration in functional autoregressive processes," DSS Empirical Economics and Econometrics Working Papers Series 2017/5, Centre for Empirical Economics and Econometrics, Department of Statistics, "Sapienza" University of Rome.
  • Massimo Franchi & Paolo Paruolo, 2017. "Cointegration in functional autoregressive processes," Papers 1712.07522, arXiv.org, revised Oct 2018.
• Danut-Octavian SIMION & Emilia VASILE, 2017. "Applications For Businesses That Uses Relational Databases:," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 45(1), pages 61-72, March.
• Danut-Octavian SIMION, 2017. "Evaluation Of The Economic Activity Through Experts Systems," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 46(2), pages 63-75, June.
• Nelu BURCEA & Danut-Octavian SIMION, 2017. "The Management Of Software Products Through Economic Information Systems," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 47(3), pages 111-124, Supplemen.
• Emilia VASILE & Danut-Octavian SIMION, 2017. "Representation Of Knowledge And Algorithms For Economic Systems," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 48(4), pages 7-20, December.
• Pedro Carneiro & Sokbae Lee & Daniel Wilhelm, 2020. "Optimal data collection for randomized control trials," The Econometrics Journal, Royal Economic Society, vol. 23(1), pages 1-31.
  • Carneiro, Pedro & Lee, Sokbae & Wilhelm, Daniel, 2016. "Optimal Data Collection for Randomized Control Trials," IZA Discussion Papers 9908, Institute of Labor Economics (IZA).
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers 15/17, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2019. "Optimal Data Collection for Randomized Control Trials," CeMMAP working papers CWP21/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers 45/17, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers CWP15/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae Lee & Daniel Wilhelm, 2016. "Optimal Data Collection for Randomized Control Trials," Papers 1603.03675, arXiv.org, revised Aug 2016.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers CWP45/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2016. "Optimal data collection for randomized control trials," CeMMAP working papers 15/16, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2016. "Optimal data collection for randomized control trials," CeMMAP working papers CWP15/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
• Koen Jochmans & Martin Weidner, 2019. "Fixed‐Effect Regressions on Network Data," Econometrica, Econometric Society, vol. 87(5), pages 1543-1560, September.
  • Koen Jochmans & Martin Weidner, 2016. "Fixed-effect regressions on network data," CeMMAP working papers CWP32/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2017. "Fixed-effect regressions on network data," CeMMAP working papers 26/17, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2018. "Fixed-effect regressions on network data," CeMMAP working papers CWP44/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2017. "Fixed-effect regressions on network data," CeMMAP working papers CWP26/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Jochmans, K. & Weidner, M., 2019. "Fixed-Effect Regressions on Network Data," Cambridge Working Papers in Economics 1938, Faculty of Economics, University of Cambridge.
  • Koen Jochmans & Martin Weidner, 2016. "Fixed-Effect Regressions on Network Data," Papers 1608.01532, arXiv.org, revised Apr 2019.
  • Koen Jochmans & Martin Weidner, 2019. "Fixed-effect regressions on network data," CeMMAP working papers CWP16/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2016. "Fixed-effect regressions on network data," CeMMAP working papers 32/16, Institute for Fiscal Studies.
• Pedro Carneiro & Sokbae Lee & Daniel Wilhelm, 2020. "Optimal data collection for randomized control trials," The Econometrics Journal, Royal Economic Society, vol. 23(1), pages 1-31.
  • Carneiro, Pedro & Lee, Sokbae & Wilhelm, Daniel, 2016. "Optimal Data Collection for Randomized Control Trials," IZA Discussion Papers 9908, Institute of Labor Economics (IZA).
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers 45/17, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2019. "Optimal Data Collection for Randomized Control Trials," CeMMAP working papers CWP21/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers 15/17, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers CWP15/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae Lee & Daniel Wilhelm, 2016. "Optimal Data Collection for Randomized Control Trials," Papers 1603.03675, arXiv.org, revised Aug 2016.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers CWP45/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2016. "Optimal data collection for randomized control trials," CeMMAP working papers 15/16, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2016. "Optimal data collection for randomized control trials," CeMMAP working papers CWP15/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
• Chen, Le-Yu & Lee, Sokbae, 2018. "Best subset binary prediction," Journal of Econometrics, Elsevier, vol. 206(1), pages 39-56.
  • Le-Yu Chen & Sokbae Lee, 2016. "Best Subset Binary Prediction," Papers 1610.02738, arXiv.org, revised May 2018.
  • Le-Yu Chen & Sokbae (Simon) Lee, 2017. "Best subset binary prediction," CeMMAP working papers 50/17, Institute for Fiscal Studies.
  • Le-Yu Chen & Sokbae (Simon) Lee, 2017. "Best subset binary prediction," CeMMAP working papers CWP50/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
• Lidiya Guryanova & Tamara Klebanova & Tetiana Trunova, 2017. "Modeling the Financial Strategy of the Enterprise in an Unstable Environment," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 3, pages 91-109.
• Carlos Casanova & Alvaro Ortiz & Tomasa Rodrigo & Le Xia & Joaquín Iglesias, 2017. "Tracking chinese vulnerability in real time using Big Data," Working Papers 17/13, BBVA Bank, Economic Research Department.
• George Kapetanios & Massimiliano Marcellino & Fabrizio Venditti, 2019. "Large time‐varying parameter VARs: A nonparametric approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(7), pages 1027-1049, November.
  • Marcellino, Massimiliano & Kapetanios, George & Venditti, Fabrizio, 2016. "Large Time-Varying Parameter VARs: A Non-Parametric Approach," CEPR Discussion Papers 11560, C.E.P.R. Discussion Papers.
  • George Kapetanios & Massimiliano Marcellino & Fabrizio Venditti, 2017. "Large time-varying parameter VARs: a non-parametric approach," Temi di discussione (Economic working papers) 1122, Bank of Italy, Economic Research and International Relations Area.
• Dario Sansone, 2017. "Beyond Early Warning Indicators: High School Dropout and Machine Learning," Working Papers gueconwpa~17-17-09, Georgetown University, Department of Economics.
  • Dario Sansone, 2017. "Now You See Me: High School Dropout and Machine Learning," 2017 Stata Conference 5, Stata Users Group.
• Chakraborty, Chiranjit & Joseph, Andreas, 2017. "Machine learning at central banks," Bank of England working papers 674, Bank of England.
• Bholat, David & Brookes, James & Cai, Chris & Grundy, Katy & Lund, Jakob, 2017. "Sending firm messages: text mining letters from PRA supervisors to banks and building societies they regulate," Bank of England working papers 688, Bank of England.
• Hyeongwoo Kim & Kyunghwan Ko, 2017. "Improving Forecast Accuracy of Financial Vulnerability: Partial Least Squares Factor Model Approach," Working Papers 2017-14, Economic Research Institute, Bank of Korea.
• Berg Tim Oliver, 2017. "Forecast accuracy of a BVAR under alternative specifications of the zero lower bound," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(2), pages 1-29, April.
  • Tim Oliver Berg, 2015. "Forecast Accuracy of a BVAR under Alternative Specifications of the Zero Lower Bound," ifo Working Paper Series 203, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
• Oscar Claveria & Enric Monte & Salvador Torra, 2017. "Using Survey Data to Forecast Real Activity with Evolutionary Algorithms. a Cross-Country Analysis," Journal of Applied Economics, Taylor & Francis Journals, vol. 20(2), pages 329-349, November.
  • Oscar Claveria & Enric Monte & Salvador Torra, 2017. "Using survey data to forecast real activity with evolutionary algorithms. A cross-country analysis," Journal of Applied Economics, Universidad del CEMA, vol. 20, pages 329-349, November.
• Matthew Bursnall & Vahé Nafilyan & Stefan Speckesser, 2017. "An analysis of the duration and achievement of apprenticeships in England," CVER Briefing Notes 004, Centre for Vocational Education Research.
• Sophie Hedges & Vahé Nafilyan & Stefan Speckesser & Augustin de Coulon, 2017. "Young people in low level vocational education: characteristics, trajectories and labour market outcomes," CVER Research Papers 004, Centre for Vocational Education Research.
• Vahé Nafilyan & Stefan Speckesser, 2017. "The longer the better? The impact of the 2012 apprenticeship reform in England on achievement and other outcomes," CVER Research Papers 006, Centre for Vocational Education Research.
• Grajzl, Peter & Murrell, Peter, 2019. "Toward understanding 17th century English culture: A structural topic model of Francis Bacon's ideas," Journal of Comparative Economics, Elsevier, vol. 47(1), pages 111-135.
  • Peter Grajzl & Peter Murrell, 2017. "Toward Understanding 17th Century English Culture: A Structural Topic Model of Francis Bacon's Ideas," CESifo Working Paper Series 6443, CESifo.
• Maxime Leroux & Rachidi Kotchoni & Dalibor Stevanovic, 2017. "Forecasting economic activity in data-rich environment," EconomiX Working Papers 2017-5, University of Paris Nanterre, EconomiX.
  • Dalibor Stevanovic & Rachidi Kotchoni & Maxime Leroux, 2017. "Forecasting economic activity in data-rich environment," CIRANO Working Papers 2017s-05, CIRANO.
  • Maxime Leroux & Rachidi Kotchoni & Dalibor Stevanovic, 2017. "Forecasting economic activity in data-rich environment," Working Papers hal-04141668, HAL.
• Ariadne M. Checo & Salomé Pradel & Francisco A. Ramírez, 2017. "The Effects of USA Monetary Policy on Central America and the Dominican Republic," Investigación Conjunta-Joint Research, in: Ángel Estrada García & Alberto Ortiz Bolaños (ed.), International Spillovers of Monetary Policy, edition 1, chapter 7, pages 189-222, Centro de Estudios Monetarios Latinoamericanos, CEMLA.
• Ángel Estrada García & Alberto Ortiz Bolaños (ed.), 2017. "International Spillovers of Monetary Policy," Investigación Conjunta-Joint Research, Centro de Estudios Monetarios Latinoamericanos, CEMLA, edition 1, volume 1, number 3, December.
• Alvaro J. Riascos & Mauricio Romero & Natalia Serna, 2017. "Risk Adjustment Revisited using Machine Learning Techniques," Documentos CEDE 15601, Universidad de los Andes, Facultad de Economía, CEDE.
• Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2021. "Economic Predictions With Big Data: The Illusion of Sparsity," Econometrica, Econometric Society, vol. 89(5), pages 2409-2437, September.
  • Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio, 2017. "Economic Predictions with Big Data: The Illusion Of Sparsity," CEPR Discussion Papers 12256, C.E.P.R. Discussion Papers.
  • Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2018. "Economic Predictions with Big Data: The Illusion of Sparsity," Liberty Street Economics 20180521, Federal Reserve Bank of New York.
  • Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2018. "Economic predictions with big data: the illusion of sparsity," Staff Reports 847, Federal Reserve Bank of New York.
  • Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio E., 2021. "Economic predictions with big data: the illusion of sparsity," Working Paper Series 2542, European Central Bank.
• Christian Gouriéroux & Alain Monfort & Eric Renault, 2017. "Consistent Pseudo-Maximum Likelihood Estimators," Annals of Economics and Statistics, GENES, issue 125-126, pages 187-218.
  • Christian Gouriéroux & Alain Monfort & Eric Renault, 2016. "Consistent Pseudo-Maximum Likelihood Estimators," Working Papers 2016-33, Center for Research in Economics and Statistics.
  • Christian Gouriéroux & Alain Monfort & Eric Renault, 2017. "Consistent Pseudo-Maximum Likelihood Estimators," Working Papers 2017-10, Center for Research in Economics and Statistics.
• Max Nathan & Anna Rosso, 2017. "Innovative events," Development Working Papers 429, Centro Studi Luca d'Agliano, University of Milano, revised 08 Apr 2019.
  • Max Nathan & Anna Rosso, 2019. "Innovative events," CEP Discussion Papers dp1607, Centre for Economic Performance, LSE.
  • Nathan, Max & Rosso, Anna, 2019. "Innovative Events," IZA Discussion Papers 12213, Institute of Labor Economics (IZA).
  • Nathan, Max & Rosso, Anna, 2019. "Innovative events," LSE Research Online Documents on Economics 102626, London School of Economics and Political Science, LSE Library.
  • Nathan, Max & Rosso, Anna, 2019. "Innovative Events," SocArXiv t3jrq, Center for Open Science.
• Alvarez Iturri, Silvana Valeria, 2017. "Pricing the quality of an innovative idea," INDEM - Working Paper Business Economic Series 24183, Instituto para el Desarrollo Empresarial (INDEM).
• Alvarez Iturri, Silvana Valeria, 2017. "Pricing the quality of an innovative idea," IC3JM - Estudios = Working Papers 24183, Instituto Mixto Carlos III - Juan March de Ciencias Sociales (IC3JM).
• Benjamin David, 2017. "Model economic phenomena with CART and Random Forest algorithms," EconomiX Working Papers 2017-46, University of Paris Nanterre, EconomiX.
• Dalibor Stevanovic & Rachidi Kotchoni & Maxime Leroux, 2017. "Forecasting economic activity in data-rich environment," CIRANO Working Papers 2017s-05, CIRANO.
  • Maxime Leroux & Rachidi Kotchoni & Dalibor Stevanovic, 2017. "Forecasting economic activity in data-rich environment," EconomiX Working Papers 2017-5, University of Paris Nanterre, EconomiX.
  • Maxime Leroux & Rachidi Kotchoni & Dalibor Stevanovic, 2017. "Forecasting economic activity in data-rich environment," Working Papers hal-04141668, HAL.
• Ciccarelli, Matteo & García, Juan Angel & Montes-Galdón, Carlos, 2017. "Unconventional monetary policy and the anchoring of inflation expectations," Working Paper Series 1995, European Central Bank.
• K. Benkovskis & B. Bluhm & E. Bobeica & C. Osbat & S. Zeugner, 2020. "What drives export market shares? It depends! An empirical analysis using Bayesian model averaging," Empirical Economics, Springer, vol. 59(2), pages 817-869, August.
  • Konstantins Benkovskis & Benjamin Bluhm & Elena Bobeica & Chiara Osbat & Stefan Zeugner, 2017. "What drives export market shares? It depends! An empirical analysis using Bayesian Model Averaging," Working Papers 2017/02, Latvijas Banka.
  • Osbat, Chiara & Benkovskis, Konstantins & Bluhm, Benjamin & Bobeica, Elena & Zeugner, Stefan, 2017. "What drives export market shares? It depends! An empirical analysis using Bayesian Model Averaging," Working Paper Series 2090, European Central Bank.
• Md. Shakib Hossain & Md. Ziaur Rahman, 2017. "Does Governance Facilitate Foreign Direct Investment in Developing Countries?," International Journal of Economics and Financial Issues, Econjournals, vol. 7(1), pages 164-177.
• Bee, Marco & Riccaboni, Massimo & Trapin, Luca, 2017. "An extreme value analysis of the last century crises across industries in the U.S. economy," Journal of Economic Dynamics and Control, Elsevier, vol. 81(C), pages 65-78.
  • Marco Bee & Massimo Riccaboni & Luca Trapin, 2016. "An extreme value analysis of the last century crises across industries in the U.S. economy," Working Papers 02/2016, IMT School for Advanced Studies Lucca, revised Feb 2016.
• Wongboonsin, Kua & Phiromswad, Piyachart, 2017. "Searching for empirical linkages between demographic structure and economic growth," Economic Modelling, Elsevier, vol. 60(C), pages 364-379.
• Liu, Jing & Wei, Yu & Ma, Feng & Wahab, M.I.M., 2017. "Forecasting the realized range-based volatility using dynamic model averaging approach," Economic Modelling, Elsevier, vol. 61(C), pages 12-26.
• Ma, Feng & Liu, Jing & Huang, Dengshi & Chen, Wang, 2017. "Forecasting the oil futures price volatility: A new approach," Economic Modelling, Elsevier, vol. 64(C), pages 560-566.
• Jerrim, John & Lopez-Agudo, Luis Alejandro & Marcenaro-Gutierrez, Oscar D. & Shure, Nikki, 2017. "What happens when econometrics and psychometrics collide? An example using the PISA data," Economics of Education Review, Elsevier, vol. 61(C), pages 51-58.
  • Jerrim, John & Lopez-Agudo, Luis Alejandro & Marcenaro Gutierrez, Oscar & Shure, Nikki, 2017. "What Happens When Econometrics and Psychometrics Collide? An Example Using the PISA Data," IZA Discussion Papers 10847, Institute of Labor Economics (IZA).
  • John Jerrim & Luis Alejandro Lopez-Agudo & Oscar D. Marcenaro-Gutierrez & Nikki Shure, 2017. "What Happens When Econometrics and Psychometrics Collide? An Example Using PISA Data," DoQSS Working Papers 17-04, Quantitative Social Science - UCL Social Research Institute, University College London.
• Fosten, Jack, 2017. "Confidence intervals in regressions with estimated factors and idiosyncratic components," Economics Letters, Elsevier, vol. 157(C), pages 71-74.
• Gagliardini, Patrick & Gouriéroux, Christian, 2017. "Double instrumental variable estimation of interaction models with big data," Journal of Econometrics, Elsevier, vol. 201(2), pages 176-197.
• Aït-Sahalia, Yacine & Xiu, Dacheng, 2017. "Using principal component analysis to estimate a high dimensional factor model with high-frequency data," Journal of Econometrics, Elsevier, vol. 201(2), pages 384-399.
• Shang, Han Lin, 2017. "Functional time series forecasting with dynamic updating: An application to intraday particulate matter concentration," Econometrics and Statistics, Elsevier, vol. 1(C), pages 184-200.
• Gupta, Rangan & Wohar, Mark, 2017. "Forecasting oil and stock returns with a Qual VAR using over 150years off data," Energy Economics, Elsevier, vol. 62(C), pages 181-186.
  • Rangan Gupta & Mark E. Wohar, 2015. "Forecasting Oil and Stock Returns with a Qual VAR using over 150 Years of Data," Working Papers 201589, University of Pretoria, Department of Economics.
• Bjørnland, Hilde C. & Ravazzolo, Francesco & Thorsrud, Leif Anders, 2017. "Forecasting GDP with global components: This time is different," International Journal of Forecasting, Elsevier, vol. 33(1), pages 153-173.
  • Hilde C. Bjørnland & Francesco Ravazzolo & Leif Anders Thorsrud, 2015. "Forecasting GDP with global components. This time is different," Working Paper 2015/05, Norges Bank.
  • Hilde C. Bjornland & Francesco Ravazzolo & Leif Anders Thorsrud, 2016. "Forecasting GDP with global components. This time is different," CAMA Working Papers 2016-26, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Kang, Yanfei & Hyndman, Rob J. & Smith-Miles, Kate, 2017. "Visualising forecasting algorithm performance using time series instance spaces," International Journal of Forecasting, Elsevier, vol. 33(2), pages 345-358.
  • Yanfei Kang & Rob J. Hyndman & Kate Smith-Miles, 2016. "Visualising forecasting Algorithm Performance using Time Series Instance Spaces," Monash Econometrics and Business Statistics Working Papers 10/16, Monash University, Department of Econometrics and Business Statistics.
• Hännikäinen, Jari, 2017. "When does the yield curve contain predictive power? Evidence from a data-rich environment," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1044-1064.
  • Hännikäinen, Jari, 2016. "When does the yield curve contain predictive power? Evidence from a data-rich environment," MPRA Paper 70489, University Library of Munich, Germany.
  • Jari Hännikäinen, 2016. "When does the yield curve contain predictive power? Evidence from a data-rich environment," Working Papers 1603, Tampere University, Faculty of Management and Business, Economics.
• Davis, Morris A. & Oliner, Stephen D. & Pinto, Edward J. & Bokka, Sankar, 2017. "Residential land values in the Washington, DC metro area: New insights from big data," Regional Science and Urban Economics, Elsevier, vol. 66(C), pages 224-246.
  • Edward J. Pinto & Stephen D. Oliner & Morris A. Davis & Sankar Bokka, 2016. "Residential land values in the Washington, DC metro area: New insights from big data," AEI Economics Working Papers 872547, American Enterprise Institute.
• Timur Behlul & Anastasios Panagiotelis & George Athanasopoulos & Rob J Hyndman & Farshid Vahid, 2017. "The Australian Macro Database: An online resource for macroeconomic research in Australia," Monash Econometrics and Business Statistics Working Papers 1/17, Monash University, Department of Econometrics and Business Statistics.
  • Timur Behlul & Anastasios Panagiotelis & George Athanasopoulos & Rob J Hyndman & Farshid Vahid, 2017. "The Australian Macro Database: An online resource for macroeconomic research in Australia," CAMA Working Papers 2017-15, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Hilde C. Bj⊘rnland & Leif Anders Thorsrud & Sepideh Khayati Zahiri, 2020. "Do Central Banks Respond Timely to Developments in the Global Economy?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(2), pages 285-310, April.
  • Hilde C. Bjørnland & Leif Anders Thorsrud & Sepideh K. Zahiri, 2016. "Do central banks respond timely to developments in the global economy?," Working Papers No 8/2016, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • Hilde C. Bjornland & Leif Anders Thorsrud & Sepideh Khayati Zahiri, 2017. "Do central banks respond timely to developments in the global economy?," CAMA Working Papers 2017-20, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Hilde C. Bjørnland & Leif Anders Thorsrud & Sepideh Khayati Zahiri, 2016. "Do central banks respond timely to developments in the global economy?," Working Paper 2016/19, Norges Bank.
• Antoszewski, Michal, 2017. "Panel estimation of sectoral substitution elasticities for CES production functions," MF Working Papers 28, Ministry of Finance in Poland.
  • Michal Antoszewski, 2017. "Panel estimation of sectoral substitution elasticities for CES production functions," EcoMod2017 10160, EcoMod.
• Nathalie Picard & Kamel Gadouche, 2017. "L’accès aux données très détaillées pour la recherche scientifique," THEMA Working Papers 2017-06, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
• Yolanda F. Rebollo-Sanz, 2017. "Decomposing the structure of wages into firm and worker effects," International Journal of Manpower, Emerald Group Publishing Limited, vol. 38(5), pages 765-787, August.
• Yolanda F. Rebollo-Sanz, 2017. "Decomposing the structure of wages into firm and worker effects," International Journal of Manpower, Emerald Group Publishing Limited, vol. 38(5), pages 765-787, August.
• Korobilis, D, 2017. "Forecasting with many predictors using message passing algorithms," Essex Finance Centre Working Papers 19565, University of Essex, Essex Business School.
  • Dimitris Korobilis, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," Working Paper series 19-17, Rimini Centre for Economic Analysis.
  • Korobilis, Dimitris, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," MPRA Paper 96079, University Library of Munich, Germany.
• Matej Nevrla, 2017. "Systemic Risk in the European Financial and Energy Sector: Dynamic Factor Copula Approach," Working Papers IES 2017/11, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised May 2017.
• Michelle L. Barnes & Giovanni P. Olivei, 2017. "Financial variables and macroeconomic forecast errors," Working Papers 17-17, Federal Reserve Bank of Boston.
• Martin M. Andreasen & Jens H.E. Christensen & Glenn D. Rudebusch, 2017. "Term Structure Analysis with Big Data," CREATES Research Papers 2017-31, Department of Economics and Business Economics, Aarhus University.
  • Martin M. Andreasen & Jens H. E. Christensen & Glenn D. Rudebusch, 2017. "Term Structure Analysis with Big Data," Working Paper Series 2017-21, Federal Reserve Bank of San Francisco.
• Alessandro Barbarino & Efstathia Bura, 2017. "A Unified Framework for Dimension Reduction in Forecasting," Finance and Economics Discussion Series 2017-004, Board of Governors of the Federal Reserve System (U.S.).
• Matteo Barigozzi & Matteo Luciani, 2017. "Common Factors, Trends, and Cycles in Large Datasets," Finance and Economics Discussion Series 2017-111, Board of Governors of the Federal Reserve System (U.S.).
• Marlene Amstad & Simon M. Potter & Robert W. Rich, 2017. "The New York Fed Staff Underlying Inflation Gauge (UIG)," Economic Policy Review, Federal Reserve Bank of New York, issue 23-2, pages 1-32.
• Brandyn Bok & Daniele Caratelli & Domenico Giannone & Argia M. Sbordone & Andrea Tambalotti, 2018. "Macroeconomic Nowcasting and Forecasting with Big Data," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 615-643, August.
  • Brandyn Bok & Daniele Caratelli & Domenico Giannone & Argia M. Sbordone & Andrea Tambalotti, 2017. "Macroeconomic nowcasting and forecasting with big data," Staff Reports 830, Federal Reserve Bank of New York.
  • Giannone, Domenico & Tambalotti, Andrea & Sbordone, Argia & Bok, Brandyn & Caratelli, Daniele, 2018. "Macroeconomic Nowcasting and Forecasting with Big Data," CEPR Discussion Papers 12589, C.E.P.R. Discussion Papers.
• Bige KÜÇÜKEFE, Dündar Murat DEMİRÖZ, 2017. "FAVAR (Factor-Augmented Vector Autoregression) Modeli Literatür Taraması," Fiscaoeconomia, Tubitak Ulakbim JournalPark (Dergipark), issue 2.
• Rossella Bardazzi & Leonardo Ghezzi, 2017. "International competitiveness and investment: simulations with a bilateral trade model," Working Papers - Economics wp2017_01.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
• Rui Pedro Brito & Hélder Sebastião & Pedro Godinho, 2017. "On the gains of using high frequency data and higher moments in Portfolio Selection," CeBER Working Papers 2017-02, Centre for Business and Economics Research (CeBER), University of Coimbra.
• Dalibor Stevanovic & Rachidi Kotchoni & Maxime Leroux, 2017. "Forecasting economic activity in data-rich environment," CIRANO Working Papers 2017s-05, CIRANO.
  • Maxime Leroux & Rachidi Kotchoni & Dalibor Stevanovic, 2017. "Forecasting economic activity in data-rich environment," Working Papers hal-04141668, HAL.
  • Maxime Leroux & Rachidi Kotchoni & Dalibor Stevanovic, 2017. "Forecasting economic activity in data-rich environment," EconomiX Working Papers 2017-5, University of Paris Nanterre, EconomiX.
• Alexander N. Bogin & William M. Doerner, 2019. "Property Renovations and Their Impact on House Price Index Construction," Journal of Real Estate Research, Taylor & Francis Journals, vol. 41(2), pages 249-284, April.
  • Alexander N. Bogin & William M. Doerner, 2017. "Property Renovations and Their Impact on House Price Index Construction," FHFA Staff Working Papers 17-02, Federal Housing Finance Agency.
• Leonid Gokhberg & Ilya Kuzminov & Pavel Bakhtin & Elena Tochilina & Alexander Chulok & Anton Timofeev & Alina Lavrinenko, 2017. "Big-Data-Augmented Approach to Emerging Technologies Identification: Case of Agriculture and Food Sector," HSE Working papers WP BRP 76/STI/2017, National Research University Higher School of Economics.
• Wolfgang Karl Härdle & Cathy Yi-Hsuan Chen, 2017. "Data Science & Digital Society," SFB 649 Discussion Papers SFB649DP2017-010, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
• Ya Qian & Wolfgang Karl Härdle & Cathy Yi-Hsuan Chen, 2017. "Industry Interdependency Dynamics in a Network Context," SFB 649 Discussion Papers SFB649DP2017-012, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
• Petra Burdejová & Wolfgang K. Härdle, 2019. "Dynamic semi-parametric factor model for functional expectiles," Computational Statistics, Springer, vol. 34(2), pages 489-502, June.
  • Petra Burdejová & Wolfgang K. Härdle, 2017. "Dynamic semi-parametric factor model for functional expectiles," SFB 649 Discussion Papers SFB649DP2017-027, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
• Alona Zharova & Wolfgang K. Härdle & Stefan Lessmann, 2017. "Is Scientific Performance a Function of Funds?," SFB 649 Discussion Papers SFB649DP2017-028, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
• Pedro Carneiro & Sokbae Lee & Daniel Wilhelm, 2020. "Optimal data collection for randomized control trials," The Econometrics Journal, Royal Economic Society, vol. 23(1), pages 1-31.
  • Carneiro, Pedro & Lee, Sokbae & Wilhelm, Daniel, 2016. "Optimal Data Collection for Randomized Control Trials," IZA Discussion Papers 9908, Institute of Labor Economics (IZA).
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers CWP15/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers 15/17, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2019. "Optimal Data Collection for Randomized Control Trials," CeMMAP working papers CWP21/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers 45/17, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae Lee & Daniel Wilhelm, 2016. "Optimal Data Collection for Randomized Control Trials," Papers 1603.03675, arXiv.org, revised Aug 2016.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers CWP45/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2016. "Optimal data collection for randomized control trials," CeMMAP working papers 15/16, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2016. "Optimal data collection for randomized control trials," CeMMAP working papers CWP15/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
• Koen Jochmans & Martin Weidner, 2019. "Fixed‐Effect Regressions on Network Data," Econometrica, Econometric Society, vol. 87(5), pages 1543-1560, September.
  • Koen Jochmans & Martin Weidner, 2016. "Fixed-effect regressions on network data," CeMMAP working papers CWP32/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2017. "Fixed-effect regressions on network data," CeMMAP working papers CWP26/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2018. "Fixed-effect regressions on network data," CeMMAP working papers CWP44/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Jochmans, K. & Weidner, M., 2019. "Fixed-Effect Regressions on Network Data," Cambridge Working Papers in Economics 1938, Faculty of Economics, University of Cambridge.
  • Koen Jochmans & Martin Weidner, 2016. "Fixed-Effect Regressions on Network Data," Papers 1608.01532, arXiv.org, revised Apr 2019.
  • Koen Jochmans & Martin Weidner, 2019. "Fixed-effect regressions on network data," CeMMAP working papers CWP16/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2017. "Fixed-effect regressions on network data," CeMMAP working papers 26/17, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2016. "Fixed-effect regressions on network data," CeMMAP working papers 32/16, Institute for Fiscal Studies.
• Pedro Carneiro & Sokbae Lee & Daniel Wilhelm, 2020. "Optimal data collection for randomized control trials," The Econometrics Journal, Royal Economic Society, vol. 23(1), pages 1-31.
  • Carneiro, Pedro & Lee, Sokbae & Wilhelm, Daniel, 2016. "Optimal Data Collection for Randomized Control Trials," IZA Discussion Papers 9908, Institute of Labor Economics (IZA).
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers CWP45/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers 15/17, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2019. "Optimal Data Collection for Randomized Control Trials," CeMMAP working papers CWP21/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers 45/17, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers CWP15/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae Lee & Daniel Wilhelm, 2016. "Optimal Data Collection for Randomized Control Trials," Papers 1603.03675, arXiv.org, revised Aug 2016.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2016. "Optimal data collection for randomized control trials," CeMMAP working papers 15/16, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2016. "Optimal data collection for randomized control trials," CeMMAP working papers CWP15/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
• Chen, Le-Yu & Lee, Sokbae, 2018. "Best subset binary prediction," Journal of Econometrics, Elsevier, vol. 206(1), pages 39-56.
  • Le-Yu Chen & Sokbae Lee, 2016. "Best Subset Binary Prediction," Papers 1610.02738, arXiv.org, revised May 2018.
  • Le-Yu Chen & Sokbae (Simon) Lee, 2017. "Best subset binary prediction," CeMMAP working papers CWP50/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Le-Yu Chen & Sokbae (Simon) Lee, 2017. "Best subset binary prediction," CeMMAP working papers 50/17, Institute for Fiscal Studies.
• Oscar Claveria & Enric Monte & Salvador Torra, 2017. "“Let the data do the talking: Empirical modelling of survey-based expectations by means of genetic programming”," AQR Working Papers 201706, University of Barcelona, Regional Quantitative Analysis Group, revised May 2017.
  • Oscar Claveria & Enric Monte & Salvador Torra, 2017. "Let the data do the talking: Empirical modelling of survey-based expectations by means of genetic programming," IREA Working Papers 201711, University of Barcelona, Research Institute of Applied Economics, revised May 2017.
• Jerrim, John & Lopez-Agudo, Luis Alejandro & Marcenaro-Gutierrez, Oscar D. & Shure, Nikki, 2017. "What happens when econometrics and psychometrics collide? An example using the PISA data," Economics of Education Review, Elsevier, vol. 61(C), pages 51-58.
  • John Jerrim & Luis Alejandro Lopez-Agudo & Oscar D. Marcenaro-Gutierrez & Nikki Shure, 2017. "What Happens When Econometrics and Psychometrics Collide? An Example Using PISA Data," DoQSS Working Papers 17-04, Quantitative Social Science - UCL Social Research Institute, University College London.
  • Jerrim, John & Lopez-Agudo, Luis Alejandro & Marcenaro Gutierrez, Oscar & Shure, Nikki, 2017. "What Happens When Econometrics and Psychometrics Collide? An Example Using the PISA Data," IZA Discussion Papers 10847, Institute of Labor Economics (IZA).
• Simon Freyaldenhoven, 2017. "A Generalized Factor Model with Local Factors," 2017 Papers pfr361, Job Market Papers.
  • Simon Freyaldenhoven, 2019. "A Generalized Factor Model with Local Factors," Working Papers 19-23, Federal Reserve Bank of Philadelphia.
• David Wuepper & Marc Patry, 2017. "The World Heritage list: Which sites promote the brand? A big data spatial econometrics approach," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 41(1), pages 1-21, February.
• Iulian Lolea, 2017. "Where did the GARCH Models Perform Best in Terms of Volatility Forecasting? Equity vs. Commodities Markets," Academic Journal of Economic Studies, Faculty of Finance, Banking and Accountancy Bucharest,"Dimitrie Cantemir" Christian University Bucharest, vol. 3(3), pages 79-86, September.
• Ralf Brüggemann & Christian Kascha, 2017. "Directed Graphs and Variable Selection in Large Vector Autoregressive Models," Working Paper Series of the Department of Economics, University of Konstanz 2017-06, Department of Economics, University of Konstanz.
  • Dominik Bertsche & Ralf Brüggemann & Christian Kascha, 2018. "Directed Graphs and Variable Selection in Large Vector Autoregressive Models," Working Paper Series of the Department of Economics, University of Konstanz 2018-08, Department of Economics, University of Konstanz.
  • Bertsche, Dominik & Brüggemann, Ralf & Kascha, Christian, 2019. "Directed Graph and Variable Selection in Large Vector Autoregressive Models," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203656, Verein für Socialpolitik / German Economic Association.
• Jaqueson K. Galimberti, 2020. "Forecasting GDP Growth from Outer Space," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(4), pages 697-722, August.
  • Jaqueson K Galimberti, 2017. "Forecasting GDP growth from the outer space," KOF Working papers 17-427, KOF Swiss Economic Institute, ETH Zurich.
  • Jaqueson K. Galimberti, 2020. "Forecasting GDP growth from outer space," Working Papers 2020-02, Auckland University of Technology, Department of Economics.
• Narongdech Keeratipranon & Phatcharasak Phawanaphinyo, 2017. "Optimal Active Energy Loss with Feeder Routing and Renewable Energy for Smart Grid Distribution," Journal of Reviews on Global Economics, Lifescience Global, vol. 6, pages 269-278.
• K. Benkovskis & B. Bluhm & E. Bobeica & C. Osbat & S. Zeugner, 2020. "What drives export market shares? It depends! An empirical analysis using Bayesian model averaging," Empirical Economics, Springer, vol. 59(2), pages 817-869, August.
  • Osbat, Chiara & Benkovskis, Konstantins & Bluhm, Benjamin & Bobeica, Elena & Zeugner, Stefan, 2017. "What drives export market shares? It depends! An empirical analysis using Bayesian Model Averaging," Working Paper Series 2090, European Central Bank.
  • Konstantins Benkovskis & Benjamin Bluhm & Elena Bobeica & Chiara Osbat & Stefan Zeugner, 2017. "What drives export market shares? It depends! An empirical analysis using Bayesian Model Averaging," Working Papers 2017/02, Latvijas Banka.
• Schumann, Martin & Severini, Thomas A. & Tripathi, Gautam, 2021. "Integrated likelihood based inference for nonlinear panel data models with unobserved effects," Journal of Econometrics, Elsevier, vol. 223(1), pages 73-95.
  • Martin Schumann & Thomas A. Severini & Gautam Tripathi, 2017. "Integrated Likelihood Based Inference for Nonlinear Panel Data Models with Unobserved Effects," DEM Discussion Paper Series 17-01, Department of Economics at the University of Luxembourg.
• Martin Boyer & Philippe De Donder & Claude Fluet & Marie-Louise Leroux & Pierre-Carl Michaud, 2017. "Long-Term Care Insurance: Knowledge Barriers, Risk Perception and Adverse Selection," NBER Working Papers 23918, National Bureau of Economic Research, Inc.
  • Martin Boyer & Philippe De Donder & Claude Fluet & Marie-Louise Leroux & Pierre-Carl Michaud, 2017. "Long-term Care Insurance: Knowledge Barriers, Risk Perception and Adverse Selection," Cahiers de recherche 1701, Chaire de recherche Industrielle Alliance sur les enjeux économiques des changements démographiques.
  • Martin Boyer & Philippe De Donder & Claude Fluet & Marie-Louise Leroux & Pierre-Carl Michaud, 2017. "Long-Term Care Insurance: Knowledge Barriers, Risk Perception and Adverse Selection," CESifo Working Paper Series 6698, CESifo.
  • M. Martin Boyer & Philippe De Donder & Claude Denys Fluet & Marie-Louise Leroux & Pierre-Carl Michaud, 2017. "Long-Term Care Insurance: Knowledge Barriers, Risk Perception and Adverse Selection," CIRANO Working Papers 2017s-17, CIRANO.
  • Martin Boyer & Philippe De Donder & Claude-Denys Fluet & Marie-Louise Leroux & Pierre-Carl Michaud, 2017. "Long-Term Care Insurance: Knowledge Barriers, Risk Perception and Adverse Selection," Cahiers de recherche 1711, Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques.
• Damien Échevin & Qing Li & Marc-André Morin, 2017. "Hospital Readmission is Highly Predictable from Deep Learning," Cahiers de recherche 1705, Chaire de recherche Industrielle Alliance sur les enjeux économiques des changements démographiques.
• Gabriele, Mazzolini & Laura, Pagani & Alessandro, Santoro, 2017. "The deterrence effect of real-world operational tax audits," Working Papers 359, University of Milano-Bicocca, Department of Economics, revised 03 Feb 2017.
• Carlo, Fiorio & Alessandro, Santoro, 2017. "Evidence-based threat-of-audit letters: do taxpayers respond strategically in a complex environment?," Working Papers 372, University of Milano-Bicocca, Department of Economics, revised 26 Sep 2017.
• François Gardes, 2017. "Angus Deaton, prix à la mémoire d'Alfred Nobel 2015 : un maître de l'économie appliquée," Documents de travail du Centre d'Economie de la Sorbonne 17025, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
• Dominique Guegan & Bertrand Hassani, 2017. "Regulatory Learning: how to supervise machine learning models? An application to credit scoring," Documents de travail du Centre d'Economie de la Sorbonne 17034, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
• Dominique Guegan & Bertrand Hassani, 2017. "Regulatory Learning: how to supervise machine learning models? An application to credit scoring," Documents de travail du Centre d'Economie de la Sorbonne 17034r, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Sep 2017.
• Okay Gunes, 2017. "Hedonic Recommendations: An Econometric Application on Big Data," Documents de travail du Centre d'Economie de la Sorbonne 17061, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
• Timur Behlul & Anastasios Panagiotelis & George Athanasopoulos & Rob J Hyndman & Farshid Vahid, 2017. "The Australian Macro Database: An online resource for macroeconomic research in Australia," CAMA Working Papers 2017-15, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Timur Behlul & Anastasios Panagiotelis & George Athanasopoulos & Rob J Hyndman & Farshid Vahid, 2017. "The Australian Macro Database: An online resource for macroeconomic research in Australia," Monash Econometrics and Business Statistics Working Papers 1/17, Monash University, Department of Econometrics and Business Statistics.
• Panagiotelis, Anastasios & Athanasopoulos, George & Hyndman, Rob J. & Jiang, Bin & Vahid, Farshid, 2019. "Macroeconomic forecasting for Australia using a large number of predictors," International Journal of Forecasting, Elsevier, vol. 35(2), pages 616-633.
  • Bin Jiang & George Athanasopoulos & Rob J Hyndman & Anastasios Panagiotelis & Farshid Vahid, 2017. "Macroeconomic forecasting for Australia using a large number of predictors," Monash Econometrics and Business Statistics Working Papers 2/17, Monash University, Department of Econometrics and Business Statistics.
• Raïsa Basselier & David de Antonio Liedo & Geert Langenus,, 2017. "Nowcasting real economic activity in the euro area : Assessing the impact of qualitative surveys," Working Paper Research 331, National Bank of Belgium.
• Szafranek, Karol, 2019. "Bagged neural networks for forecasting Polish (low) inflation," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1042-1059.
  • Karol Szafranek, 2017. "Bagged artificial neural networks in forecasting inflation: An extensive comparison with current modelling frameworks," NBP Working Papers 262, Narodowy Bank Polski.
• Jon Kleinberg & Himabindu Lakkaraju & Jure Leskovec & Jens Ludwig & Sendhil Mullainathan, 2018. "Human Decisions and Machine Predictions," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 133(1), pages 237-293.
  • Jon Kleinberg & Himabindu Lakkaraju & Jure Leskovec & Jens Ludwig & Sendhil Mullainathan, 2017. "Human Decisions and Machine Predictions," NBER Working Papers 23180, National Bureau of Economic Research, Inc.
• Stefano Giglio & Dacheng Xiu, 2017. "Inference on Risk Premia in the Presence of Omitted Factors," NBER Working Papers 23527, National Bureau of Economic Research, Inc.
• Andrés F. Barrientos & Alexander Bolton & Tom Balmat & Jerome P. Reiter & John M. de Figueiredo & Ashwin Machanavajjhala & Yan Chen & Charles Kneifel & Mark DeLong, 2017. "A Framework for Sharing Confidential Research Data, Applied to Investigating Differential Pay by Race in the U. S. Government," NBER Working Papers 23534, National Bureau of Economic Research, Inc.
• Alexander M. Chinco & Mao Ye, 2017. "Investment-Horizon Spillovers," NBER Working Papers 23650, National Bureau of Economic Research, Inc.
• Serena Ng, 2017. "Opportunities and Challenges: Lessons from Analyzing Terabytes of Scanner Data," NBER Working Papers 23673, National Bureau of Economic Research, Inc.
• Jean-Pierre Dubé & Sanjog Misra, 2017. "Personalized Pricing and Consumer Welfare," NBER Working Papers 23775, National Bureau of Economic Research, Inc.
• Fiona Burlig & Christopher Knittel & David Rapson & Mar Reguant & Catherine Wolfram, 2020. "Machine Learning from Schools about Energy Efficiency," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 7(6), pages 1181-1217.
  • Fiona Burlig & Christopher Knittel & David Rapson & Mar Reguant & Catherine Wolfram, 2017. "Machine Learning from Schools about Energy Efficiency," NBER Working Papers 23908, National Bureau of Economic Research, Inc.
• Alexander M. Chinco & Adam D. Clark-Joseph & Mao Ye, 2017. "Sparse Signals in the Cross-Section of Returns," NBER Working Papers 23933, National Bureau of Economic Research, Inc.
• Jacob Assa, 2017. "Leveraged Growth: Endogenous Money and Speculative Credit in a Stock-flow Consistent Measure of Output," Working Papers 1727, New School for Social Research, Department of Economics.
• O. Borzykh., 2017. "The impact of banks’ capital adequacy ratio on bank lending channel of monetary transmission in Russia," VOPROSY ECONOMIKI, N.P. Redaktsiya zhurnala "Voprosy Economiki", vol. 7.
• Pierre-Alain Pionnier & María Belén Zinni & Kéa Baret, 2023. "Sensitivity of capital and MFP measurement to asset depreciation patterns and initial capital stock estimates," OECD Statistics Working Papers -en, OECD Publishing.
• Thilo Klein & Stefaan Verhulst, 2017. "Access to new data sources for statistics: Business models and incentives for the corporate sector," OECD Statistics Working Papers 2017/6, OECD Publishing.
• Jayson L. Lusk, 2017. "Consumer Research with Big Data: Applications from the Food Demand Survey (FooDS)," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 99(2), pages 303-320.
• Marisa Hidalgo-Hidalgo & Iñigo Iturbe-Ormaetxe, 2018. "Long-run effects of public expenditure on poverty," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 16(1), pages 1-22, March.
  • Marisa Hidalgo-Hidalgo & Iñigo Iturbe-Ormaetxe, 2018. "Long-run effects of public expenditure on poverty," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 16(1), pages 1-22, March.
  • Marisa Hidalgo-Hidalgo & Iñigo Iturbe-Ormaetxe, 2017. "Long-run Effects of Public Expenditure on Poverty," Working Papers 17.09, Universidad Pablo de Olavide, Department of Economics.
• Yolanda F. Rebollo-Sanz, 2017. "Decomposing the structure of wages into firm and worker effects: some insights from a high unemployment economy," Working Papers 17.10, Universidad Pablo de Olavide, Department of Economics.
• Annette O. Balaoing-Pelkmans, 2017. "A new look at Philippine export performance-a firm-level view," Philippine Review of Economics, University of the Philippines School of Economics and Philippine Economic Society, vol. 54(1), pages 1-31, June.
• José M. Cordero & Víctor Cristóbal & Daniel Santín, 2018. "Causal Inference On Education Policies: A Survey Of Empirical Studies Using Pisa, Timss And Pirls," Journal of Economic Surveys, Wiley Blackwell, vol. 32(3), pages 878-915, July.
  • Cordero, José Manuel & Cristobal, Victor & Santín, Daniel, 2017. "Causal Inference on Education Policies: A Survey of Empirical Studies Using PISA, TIMSS and PIRLS," MPRA Paper 76295, University Library of Munich, Germany.
• Chu, Ba, 2017. "Composite Quasi-Maximum Likelihood Estimation of Dynamic Panels with Group-Specific Heterogeneity and Spatially Dependent Errors," MPRA Paper 79709, University Library of Munich, Germany.
• Tagiew, Rustam & Ignatov, Dmitry I., 2017. "Behavior Mining in h-index Ranking Game," MPRA Paper 82795, University Library of Munich, Germany.
• Antoine A. Djogbenou, 2021. "Model selection in factor-augmented regressions with estimated factors," Econometric Reviews, Taylor & Francis Journals, vol. 40(5), pages 470-503, April.
  • Antoine A. Djogbenou, 2017. "Model Selection In Factor-augmented Regressions With Estimated Factors," Working Paper 1391, Economics Department, Queen's University.
• Antoine A. Djogbenou, 2020. "Comovements in the real activity of developed and emerging economies: A test of global versus specific international factors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(3), pages 344-370, April.
  • Antoine A. Djogbenou, 2018. "Comovements In The Real Activity Of Developed And Emerging Economies: A Test Of Global Versus Specific International Factors," Working Paper 1392, Economics Department, Queen's University.
• Jerrim, John & Lopez-Agudo, Luis Alejandro & Marcenaro-Gutierrez, Oscar D. & Shure, Nikki, 2017. "What happens when econometrics and psychometrics collide? An example using the PISA data," Economics of Education Review, Elsevier, vol. 61(C), pages 51-58.
  • Jerrim, John & Lopez-Agudo, Luis Alejandro & Marcenaro Gutierrez, Oscar & Shure, Nikki, 2017. "What Happens When Econometrics and Psychometrics Collide? An Example Using the PISA Data," IZA Discussion Papers 10847, Institute of Labor Economics (IZA).
  • John Jerrim & Luis Alejandro Lopez-Agudo & Oscar D. Marcenaro-Gutierrez & Nikki Shure, 2017. "What Happens When Econometrics and Psychometrics Collide? An Example Using PISA Data," DoQSS Working Papers 17-04, Quantitative Social Science - UCL Social Research Institute, University College London.
• Fornaro, Paolo & Luomaranta, Henri & Saarinen, Lauri, 2017. "Nowcasting Finnish Turnover Indexes Using Firm-Level Data," ETLA Working Papers 46, The Research Institute of the Finnish Economy.
• Frieling, Julius & Madlener, Reinhard, 2017. "The Turning Tide: How Energy has Driven the Transformation of the British Economy Since the Industrial Revolution," FCN Working Papers 7/2017, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
• Michal Antoszewski, 2017. "Panel estimation of sectoral substitution elasticities for CES production functions," EcoMod2017 10160, EcoMod.
  • Antoszewski, Michal, 2017. "Panel estimation of sectoral substitution elasticities for CES production functions," MF Working Papers 28, Ministry of Finance in Poland.
• Andreea – Cristina PETRICA & Stelian STANCU, 2017. "Empirical Results of Modeling EUR/RON Exchange Rate using ARCH, GARCH, EGARCH, TARCH and PARCH models," Romanian Statistical Review, Romanian Statistical Review, vol. 65(1), pages 57-72, March.
• Tommaso Proietti & Alessandro Giovannelli, 2018. "A Durbin–Levinson regularized estimator of high-dimensional autocovariance matrices," Biometrika, Biometrika Trust, vol. 105(4), pages 783-795.
  • Tommaso Proietti & Alessandro Giovannelli, 2017. "A Durbin-Levinson Regularized Estimator of High Dimensional Autocovariance Matrices," CREATES Research Papers 2017-20, Department of Economics and Business Economics, Aarhus University.
  • Tommaso Proietti & Alessandro Giovannelli, 2017. "A Durbin-Levinson Regularized Estimator of High Dimensional Autocovariance Matrices," CEIS Research Paper 410, Tor Vergata University, CEIS, revised 19 Jul 2017.
• Di Iorio, Francesca & Fachin, Stefano, 2021. "Evaluating restricted common factor models for non-stationary data," Econometrics and Statistics, Elsevier, vol. 17(C), pages 64-75.
  • Francesca Di Iorio & Stefano Fachin, 2017. "Evaluating Restricted Common Factor models for non-stationary data," DSS Empirical Economics and Econometrics Working Papers Series 2017/2, Centre for Empirical Economics and Econometrics, Department of Statistics, "Sapienza" University of Rome.
• Massimo Franchi & Paolo Paruolo, 2019. "A general inversion theorem for cointegration," Econometric Reviews, Taylor & Francis Journals, vol. 38(10), pages 1176-1201, November.
  • Massimo Franchi & Paolo Paruolo, 2017. "A general inversion theorem for cointegration," DSS Empirical Economics and Econometrics Working Papers Series 2017/3, Centre for Empirical Economics and Econometrics, Department of Statistics, "Sapienza" University of Rome.
• Franchi, Massimo & Paruolo, Paolo, 2020. "Cointegration In Functional Autoregressive Processes," Econometric Theory, Cambridge University Press, vol. 36(5), pages 803-839, October.
  • Massimo Franchi & Paolo Paruolo, 2017. "Cointegration in functional autoregressive processes," Papers 1712.07522, arXiv.org, revised Oct 2018.
  • Massimo Franchi & Paolo Paruolo, 2017. "Cointegration in functional autoregressive processes," DSS Empirical Economics and Econometrics Working Papers Series 2017/5, Centre for Empirical Economics and Econometrics, Department of Statistics, "Sapienza" University of Rome.
• Emilia Vasile & Danut Octavian Simion, 2017. "The Management of Businesses through Information Systems," Working papers Globalization - Economic, Social and Moral Implications, April 2017 20, Research Association for Interdisciplinary Studies.
• Alain Galli, 2018. "Which Indicators Matter? Analyzing the Swiss Business Cycle Using a Large-Scale Mixed-Frequency Dynamic Factor Model," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(2), pages 179-218, November.
  • Dr. Alain Galli, 2017. "Which indicators matter? Analyzing the Swiss business cycle using a large-scale mixed-frequency dynamic factor model," Working Papers 2017-08, Swiss National Bank.
• Júlia Gallego Ziero Uhr & André Luis Squarize Chagas, Daniel de Abreu Pereira Uhr, Renan Porn Peres, 2017. "A study on environmental infractions for Brazilian municipalities: a spatial dynamic panel approach," Working Papers, Department of Economics 2017_13, University of São Paulo (FEA-USP).
• Hocine Mokhtar-Kharroubi, 2017. "Convex and convex-like optimization over a range inclusion problem and first applications," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 40(1), pages 277-299, November.
• Ricardo Buettner, 2017. "Predicting user behavior in electronic markets based on personality-mining in large online social networks," Electronic Markets, Springer;IIM University of St. Gallen, vol. 27(3), pages 247-265, August.
• Eric. W. K. See-To & Yang Yang, 2017. "Market sentiment dispersion and its effects on stock return and volatility," Electronic Markets, Springer;IIM University of St. Gallen, vol. 27(3), pages 283-296, August.
• Júlia Varga, 2017. "Out-migration and attrition of physicians and dentists before and after EU accession (2003 and 2011): the case of Hungary," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 18(9), pages 1079-1093, December.
  • Júlia Varga, 2016. "Out-migration and attrition of physicians and dentists before and after EU accession (2003 and 2011). The case of Hungary," Budapest Working Papers on the Labour Market 1604, Institute of Economics, Centre for Economic and Regional Studies.
• Thomas Reutterer & Kurt Hornik & Nicolas March & Kathrin Gruber, 2017. "A data mining framework for targeted category promotions," Journal of Business Economics, Springer, vol. 87(3), pages 337-358, April.
• Sebastian Voigt & Oliver Hinz, 2017. "Assessing the economic effects of server launches in free-to-play MMO games," Journal of Business Economics, Springer, vol. 87(4), pages 421-464, May.
  • Voigt, Sebastian & Hinz, Oliver, 2016. "Assessing the Economic Effects of Server Launches in Free-to-Play MMO Games," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 84846, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
• R. P. Brito & H. Sebastião & P. Godinho, 2017. "Portfolio choice with high frequency data: CRRA preferences and the liquidity effect," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 16(2), pages 65-86, August.
• Oscar Claveria & Enric Monte & Salvador Torra, 2017. "A new approach for the quantification of qualitative measures of economic expectations," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(6), pages 2685-2706, November.
• Jessica Petersen & Fabian Hattke & Rick Vogel, 2017. "Editorial governance and journal impact: a study of management and business journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(3), pages 1593-1614, September.
• Scott French, 2017. "A Gravity-Based Revealed Comparative Advantage Estimator," Discussion Papers 2017-05, School of Economics, The University of New South Wales.
• Rachida Ouysse, 2017. "Constrained principal components estimation of large approximate factor models," Discussion Papers 2017-12, School of Economics, The University of New South Wales.
  • Rachida Ouysse, 2019. "Constrained principal components estimation of large approximate factor models," Discussion Papers 2017-12a, School of Economics, The University of New South Wales.
• Chris van Wyk & Anderson Gondwe & Pierre de Villiers, 2017. "Learner flow through patterns in the Western Cape using CEMIS datasets from 2007 to 2014: A longitudinal cohort analysis," Working Papers 02/2017, Stellenbosch University, Department of Economics.
• Oscar Claveria & Enric Monte & Salvador Torra, 2017. "Using survey data to forecast real activity with evolutionary algorithms. A cross-country analysis," Journal of Applied Economics, Universidad del CEMA, vol. 20, pages 329-349, November.
  • Oscar Claveria & Enric Monte & Salvador Torra, 2017. "Using Survey Data to Forecast Real Activity with Evolutionary Algorithms. a Cross-Country Analysis," Journal of Applied Economics, Taylor & Francis Journals, vol. 20(2), pages 329-349, November.
• Michael Greenacre, 2017. "Towards a pragmatic approach to compositional data analysis," Economics Working Papers 1554, Department of Economics and Business, Universitat Pompeu Fabra.
• Michael Greenacre, 2017. "Data reporting and visualization in ecology," Economics Working Papers 1558, Department of Economics and Business, Universitat Pompeu Fabra.
• Brady, Ryan R. & Insler, Michael A., 2019. "Order of play advantage in sequential tournaments: Evidence from randomized settings in professional golf," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 79(C), pages 79-92.
  • Ryan Brady & Michael Insler, 2017. "Order of Play Advantage in Sequential Tournaments: Evidence from randomized settings in professional golf," Departmental Working Papers 54, United States Naval Academy Department of Economics.
• Kjosev Sasho & Novkovska Blagica, 2017. "Developing Social Accounting Matrix for Macedonia: a challenge ahead," Croatian Review of Economic, Business and Social Statistics, Sciendo, vol. 3(2), pages 10-19, December.
• Eryk Kopczyński & Dorota Celińska, 2017. "Hyperbolic grids and discrete random graphs," Working Papers 2017-20, Faculty of Economic Sciences, University of Warsaw.
• Rangan Gupta & Eric Olson & Mark E. Wohar, 2017. "Forecasting key US macroeconomic variables with a factor‐augmented Qual VAR," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(6), pages 640-650, September.
  • Rangan Gupta & Eric Olson & Mark E. Wohar, 2015. "Forecasting Key US Macroeconomic Variables with a Factor-Augmented Qual VAR," Working Papers 201585, University of Pretoria, Department of Economics.
• Foos, Daniel & Lütkebohmert, Eva & Markovych, Mariia & Pliszka, Kamil, 2017. "Euro area banks' interest rate risk exposure to level, slope and curvature swings in the yield curve," Discussion Papers 24/2017, Deutsche Bundesbank.
• Momanyi, Kevin, 2017. "An Econometric Analysis of The Impact of Telecare on The Length of Stay in Hospital," EconStor Preprints 168559, ZBW - Leibniz Information Centre for Economics, revised 2017.
• Katja Heinisch & Rolf Scheufele, 2019. "Should Forecasters Use Real‐Time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence," German Economic Review, Verein für Socialpolitik, vol. 20(4), pages 170-200, November.
  • Heinisch Katja & Scheufele Rolf, 2019. "Should Forecasters Use Real-Time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence," German Economic Review, De Gruyter, vol. 20(4), pages 170-200, December.
  • Heinisch, Katja & Scheufele, Rolf, 2017. "Should forecasters use real-time data to evaluate leading indicator models for GDP prediction? German evidence," IWH Discussion Papers 5/2017, Halle Institute for Economic Research (IWH).
• Haskamp, Ulrich, 2017. "Improving the forecasts of European regional banks' profitability with machine learning algorithms," Ruhr Economic Papers 705, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
• Qian, Ya & Härdle, Wolfgang Karl & Chen, Cathy Yi-Hsuan, 2017. "Industry Interdependency Dynamics in a Network Context," SFB 649 Discussion Papers 2017-012, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
• Larisa Adamyan & Kirill Efimov & Cathy Y. Chen & Wolfgang K. Härdle, 2020. "Adaptive weights clustering of research papers," Digital Finance, Springer, vol. 2(3), pages 169-187, December.
  • Adamyan, Larisa & Efimov, Kirill & Chen, Cathy Yi-hsuan & Härdle, Wolfgang Karl, 2017. "Adaptive weights clustering of research papers," SFB 649 Discussion Papers 2017-013, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
• Petra Burdejová & Wolfgang K. Härdle, 2019. "Dynamic semi-parametric factor model for functional expectiles," Computational Statistics, Springer, vol. 34(2), pages 489-502, June.
  • Burdejová, Petra & Härdle, Wolfgang Karl, 2017. "Dynamic semi-parametric factor model for functional expectiles," SFB 649 Discussion Papers 2017-027, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
• Zharova, Alona & Härdle, Wolfgang Karl & Lessmann, Stefan, 2017. "Is scientific performance a function of funds?," SFB 649 Discussion Papers 2017-028, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

2016

• Daniel Felix Ahelegbey & Monica Billio & Roberto Casarin, 2016. "Sparse Graphical Vector Autoregression: A Bayesian Approach," Annals of Economics and Statistics, GENES, issue 123-124, pages 333-361.
  • Roberto Casarin & Daniel Felix Ahelegbey & Monica Billio, 2014. "Sparse Graphical Vector Autoregression: A Bayesian Approach," Working Papers 2014:29, Department of Economics, University of Venice "Ca' Foscari".
• Nicholas Bloom & Renata Lemos & Raffaella Sadun & Daniela Scur & John Van Reenen, 2016. "International Data on Measuring Management Practices," American Economic Review, American Economic Association, vol. 106(5), pages 152-156, May.
  • Bloom, Nicholas & Lemos, Renata & Sadun, Raffaella & Scur, Daniela & Van Reenen, John, 2016. "International data on measuring management practices," LSE Research Online Documents on Economics 67379, London School of Economics and Political Science, LSE Library.
  • Nicholas Bloom & Renata Lemos & Raffaella Sadun & Daniela Scur & John Van Reenen, 2016. "International Data on Measuring Management Practices," CEP Occasional Papers 46, Centre for Economic Performance, LSE.
• Liran Einav & Amy Finkelstein & Raymond Kluender & Paul Schrimpf, 2016. "Beyond Statistics: The Economic Content of Risk Scores," American Economic Journal: Applied Economics, American Economic Association, vol. 8(2), pages 195-224, April.
  • Liran Einav & Amy Finkelstein & Raymond Kluender & Paul Schrimpf, "undated". "Beyond Statistics: The Economic Content of Risk Scores," Discussion Papers 15-024, Stanford Institute for Economic Policy Research.
  • Liran Einav & Amy Finkelstein & Raymond Kluender & Paul Schrimpf, 2015. "Beyond Statistics: The Economic Content of Risk Scores," NBER Working Papers 21304, National Bureau of Economic Research, Inc.
• Alberto Cavallo & Roberto Rigobon, 2016. "The Billion Prices Project: Using Online Prices for Measurement and Research," Journal of Economic Perspectives, American Economic Association, vol. 30(2), pages 151-178, Spring.
  • Alberto Cavallo & Roberto Rigobon, 2016. "The Billion Prices Project: Using Online Prices for Measurement and Research," NBER Working Papers 22111, National Bureau of Economic Research, Inc.
• Emmanuel Olusegun STOBER, 2016. "Crude Oil Price Shocks And Macroeconomic Behavior In Nigeria," Journal of Social and Economic Statistics, Bucharest University of Economic Studies, vol. 5(1), pages 56-66, JULY.
• Ufuk Çelik & Eyüp Akçetin & Abdulkadir Yaldır, 2016. "Analysis of Volvo IT's Closed Problem Management Processes By Using Process Mining Software ProM and Disco," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 4(2), pages 171-182, December.
• Gordon Rausser & David A. Bessler, 2016. "Information Recovery and Causality: A Tribute to George Judge," Annual Review of Resource Economics, Annual Reviews, vol. 8(1), pages 7-23, October.
• Jushan Bai & Peng Wang, 2016. "Econometric Analysis of Large Factor Models," Annual Review of Economics, Annual Reviews, vol. 8(1), pages 53-80, October.
• Pedro Carneiro & Sokbae Lee & Daniel Wilhelm, 2020. "Optimal data collection for randomized control trials," The Econometrics Journal, Royal Economic Society, vol. 23(1), pages 1-31.
  • Carneiro, Pedro & Lee, Sokbae & Wilhelm, Daniel, 2016. "Optimal Data Collection for Randomized Control Trials," IZA Discussion Papers 9908, Institute of Labor Economics (IZA).
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers 15/17, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers 45/17, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2019. "Optimal Data Collection for Randomized Control Trials," CeMMAP working papers CWP21/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers CWP15/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae Lee & Daniel Wilhelm, 2016. "Optimal Data Collection for Randomized Control Trials," Papers 1603.03675, arXiv.org, revised Aug 2016.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers CWP45/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2016. "Optimal data collection for randomized control trials," CeMMAP working papers 15/16, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2016. "Optimal data collection for randomized control trials," CeMMAP working papers CWP15/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
• Xu, Ning & Hong, Jian & Fisher, Timothy, 2016. "Model selection consistency from the perspective of generalization ability and VC theory with an application to Lasso," MPRA Paper 71670, University Library of Munich, Germany.
  • Ning Xu & Jian Hong & Timothy C. G. Fisher, 2016. "Model selection consistency from the perspective of generalization ability and VC theory with an application to Lasso," Papers 1606.00142, arXiv.org.
• Koen Jochmans & Martin Weidner, 2019. "Fixed‐Effect Regressions on Network Data," Econometrica, Econometric Society, vol. 87(5), pages 1543-1560, September.
  • Koen Jochmans & Martin Weidner, 2016. "Fixed-effect regressions on network data," CeMMAP working papers CWP32/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2018. "Fixed-effect regressions on network data," CeMMAP working papers CWP44/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2017. "Fixed-effect regressions on network data," CeMMAP working papers CWP26/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Jochmans, K. & Weidner, M., 2019. "Fixed-Effect Regressions on Network Data," Cambridge Working Papers in Economics 1938, Faculty of Economics, University of Cambridge.
  • Koen Jochmans & Martin Weidner, 2016. "Fixed-Effect Regressions on Network Data," Papers 1608.01532, arXiv.org, revised Apr 2019.
  • Koen Jochmans & Martin Weidner, 2019. "Fixed-effect regressions on network data," CeMMAP working papers CWP16/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2017. "Fixed-effect regressions on network data," CeMMAP working papers 26/17, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2016. "Fixed-effect regressions on network data," CeMMAP working papers 32/16, Institute for Fiscal Studies.
• Xu, Ning & Hong, Jian & Fisher, Timothy, 2016. "Finite-sample and asymptotic analysis of generalization ability with an application to penalized regression," MPRA Paper 73622, University Library of Munich, Germany.
  • Ning Xu & Jian Hong & Timothy C. G. Fisher, 2016. "Finite-sample and asymptotic analysis of generalization ability with an application to penalized regression," Papers 1609.03344, arXiv.org, revised Sep 2016.
• M. Raddant & F. Wagner, 2022. "Multivariate GARCH with dynamic beta," The European Journal of Finance, Taylor & Francis Journals, vol. 28(13-15), pages 1324-1343, October.
  • Matthias Raddant & Friedrich Wagner, 2016. "Multivariate Garch with dynamic beta," Papers 1609.07051, arXiv.org, revised Nov 2019.
• Chen, Le-Yu & Lee, Sokbae, 2018. "Best subset binary prediction," Journal of Econometrics, Elsevier, vol. 206(1), pages 39-56.
  • Le-Yu Chen & Sokbae Lee, 2016. "Best Subset Binary Prediction," Papers 1610.02738, arXiv.org, revised May 2018.
  • Le-Yu Chen & Sokbae (Simon) Lee, 2017. "Best subset binary prediction," CeMMAP working papers CWP50/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Le-Yu Chen & Sokbae (Simon) Lee, 2017. "Best subset binary prediction," CeMMAP working papers 50/17, Institute for Fiscal Studies.
• Pedro Carneiro & Sokbae Lee & Daniel Wilhelm, 2020. "Optimal data collection for randomized control trials," The Econometrics Journal, Royal Economic Society, vol. 23(1), pages 1-31.
  • Carneiro, Pedro & Lee, Sokbae & Wilhelm, Daniel, 2016. "Optimal Data Collection for Randomized Control Trials," IZA Discussion Papers 9908, Institute of Labor Economics (IZA).
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers 15/17, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers 45/17, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2019. "Optimal Data Collection for Randomized Control Trials," CeMMAP working papers CWP21/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers CWP15/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2016. "Optimal data collection for randomized control trials," CeMMAP working papers 15/16, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers CWP45/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae Lee & Daniel Wilhelm, 2016. "Optimal Data Collection for Randomized Control Trials," Papers 1603.03675, arXiv.org, revised Aug 2016.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2016. "Optimal data collection for randomized control trials," CeMMAP working papers CWP15/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
• Koen Jochmans & Martin Weidner, 2019. "Fixed‐Effect Regressions on Network Data," Econometrica, Econometric Society, vol. 87(5), pages 1543-1560, September.
  • Koen Jochmans & Martin Weidner, 2016. "Fixed-effect regressions on network data," CeMMAP working papers CWP32/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2016. "Fixed-effect regressions on network data," CeMMAP working papers 32/16, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2018. "Fixed-effect regressions on network data," CeMMAP working papers CWP44/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2017. "Fixed-effect regressions on network data," CeMMAP working papers CWP26/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Jochmans, K. & Weidner, M., 2019. "Fixed-Effect Regressions on Network Data," Cambridge Working Papers in Economics 1938, Faculty of Economics, University of Cambridge.
  • Koen Jochmans & Martin Weidner, 2019. "Fixed-effect regressions on network data," CeMMAP working papers CWP16/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2017. "Fixed-effect regressions on network data," CeMMAP working papers 26/17, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2016. "Fixed-Effect Regressions on Network Data," Papers 1608.01532, arXiv.org, revised Apr 2019.
• Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Valid Post-Selection and Post-Regularization Inference: An Elementary, General Approach," Annual Review of Economics, Annual Reviews, vol. 7(1), pages 649-688, August.
  • Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Valid Post-Selection and Post-Regularization Inference: An Elementary, General Approach," Papers 1501.03430, arXiv.org, revised Aug 2015.
  • Victor Chernozhukov & Christian Hansen & Martin Spindler, 2016. "Valid post-selection and post-regularization inference: An elementary, general approach," CeMMAP working papers 36/16, Institute for Fiscal Studies.
  • Victor Chernozhukov & Christian Hansen & Martin Spindler, 2016. "Valid post-selection and post-regularization inference: An elementary, general approach," CeMMAP working papers CWP36/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
• Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2018. "Measuring Uncertainty and Its Impact on the Economy," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 799-815, December.
  • Andrea Carriero & Todd E. Clark & Marcellino Massimiliano, 2016. "Measuring Uncertainty and Its Impact on the Economy," Working Papers (Old Series) 1622, Federal Reserve Bank of Cleveland.
  • Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2016. "Measuring Uncertainty and Its Impact on the Economy," BAFFI CAREFIN Working Papers 1639, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
• Kan Chen & Mario Crucini, 2016. "Trends & Cycles in Small Open Economies:Making the Case for a General Equilibrium Approach," Working Papers 16/12, BBVA Bank, Economic Research Department.
• Burdeau, E. & Potier, L., 2016. "Crédits à l’habitat : taux d’intérêt, durée des crédits et profil des emprunteurs," Bulletin de la Banque de France, Banque de France, issue 206, pages 5-18.
• Tor Korneliussen & Michael Greenacre, 2016. "Information sources used by European tourists: A cross-cultural study," Economics Working Papers 1527, Department of Economics and Business, Universitat Pompeu Fabra.
  • Tor Korneliussen & Michael Greenacre, 2016. "Information Sources Used by European Tourists: A Cross-Cultural Study," Working Papers 915, Barcelona School of Economics.
• Bilandžić Ana & Marina Jeger & Šarlija Nataša, 2016. "Dealing with Interpretability Issues in Predicting Firm Growth: Factor Analysis Approach," Business Systems Research, Sciendo, vol. 7(2), pages 23-34, September.
• Hilde C. Bj⊘rnland & Leif Anders Thorsrud & Sepideh Khayati Zahiri, 2020. "Do Central Banks Respond Timely to Developments in the Global Economy?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(2), pages 285-310, April.
  • Hilde C. Bjørnland & Leif Anders Thorsrud & Sepideh Khayati Zahiri, 2016. "Do central banks respond timely to developments in the global economy?," Working Paper 2016/19, Norges Bank.
  • Hilde C. Bjornland & Leif Anders Thorsrud & Sepideh Khayati Zahiri, 2017. "Do central banks respond timely to developments in the global economy?," CAMA Working Papers 2017-20, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Hilde C. Bj⊘rnland & Leif Anders Thorsrud & Sepideh Khayati Zahiri, 2020. "Do Central Banks Respond Timely to Developments in the Global Economy?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(2), pages 285-310, April.
  • Hilde C. Bjørnland & Leif Anders Thorsrud & Sepideh Khayati Zahiri, 2016. "Do central banks respond timely to developments in the global economy?," Working Paper 2016/19, Norges Bank.
  • Hilde C. Bjornland & Leif Anders Thorsrud & Sepideh Khayati Zahiri, 2017. "Do central banks respond timely to developments in the global economy?," CAMA Working Papers 2017-20, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Hilde C. Bjørnland & Leif Anders Thorsrud & Sepideh K. Zahiri, 2016. "Do central banks respond timely to developments in the global economy?," Working Papers No 8/2016, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
• Hacioglu, Sinem & Tuzcuoglu, Kerem, 2016. "Interpreting the latent dynamic factors by threshold FAVAR model," Bank of England working papers 622, Bank of England.
• François-Xavier Meunier & Célia Zyla, 2016. "Firm growth and knowledge flows: comparative analysis between defence and civil areas," Journal of Innovation Economics, De Boeck Université, vol. 0(2), pages 89-108.
• Étienne Chamayou & Ronan Le Saout, 2016. "Changement d’enseigne sur le marché français des carburants : effets sur la concurrence locale d’une baisse des prix," Revue économique, Presses de Sciences-Po, vol. 67(5), pages 1085-1105.
• Alexander Chudik & George Kapetanios & M. Hashem Pesaran, 2016. "Big Data Analytics: A New Perspective," CESifo Working Paper Series 5824, CESifo.
  • A. Chudik & G. Kapetanios & M. Hashem Pesaran, 2016. "Big Data Analytics: A New Perspective," Cambridge Working Papers in Economics 1611, Faculty of Economics, University of Cambridge.
  • Alexander Chudik & George Kapetanios & M. Hashem Pesaran, 2016. "Big data analytics: a new perspective," Globalization Institute Working Papers 268, Federal Reserve Bank of Dallas.
• HAFNER, Christian & LINTON, Oliver B. & TANG, Haihan, 2016. "Estimation of a Multiplicative Covariance Structure in the Large Dimensional Case," LIDAM Discussion Papers CORE 2016044, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  • Hafner, C. M. & Linton, O., 2016. "Estimation of a Multiplicative Covariance Structure in the Large Dimensional Case," Cambridge Working Papers in Economics 1664, Faculty of Economics, University of Cambridge.
  • Christian M. Hafner & Oliver Linton & Haihan Tang, 2016. "Estimation of a multiplicative covariance structure in the large dimensional case," CeMMAP working papers CWP52/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
• A. Chudik & G. Kapetanios & M. Hashem Pesaran, 2018. "A One Covariate at a Time, Multiple Testing Approach to Variable Selection in High‐Dimensional Linear Regression Models," Econometrica, Econometric Society, vol. 86(4), pages 1479-1512, July.
  • Alexander Chudik & George Kapetanios & M. Hashem Pesaran, 2016. "A one-covariate at a time, multiple testing approach to variable selection in high-dimensional linear regression models," Globalization Institute Working Papers 290, Federal Reserve Bank of Dallas.
  • Chudik, A. & Kapetanios, G. & Pesaran, Hashem, 2016. "A One-Covariate at a Time, Multiple Testing Approach to Variable Selection in High-Dimensional Linear Regression Models," Cambridge Working Papers in Economics 1677, Faculty of Economics, University of Cambridge.
• Nicholas Bloom & Renata Lemos & Raffaella Sadun & Daniela Scur & John Van Reenen, 2016. "International Data on Measuring Management Practices," American Economic Review, American Economic Association, vol. 106(5), pages 152-156, May.
  • Bloom, Nicholas & Lemos, Renata & Sadun, Raffaella & Scur, Daniela & Van Reenen, John, 2016. "International data on measuring management practices," LSE Research Online Documents on Economics 67379, London School of Economics and Political Science, LSE Library.
  • Nicholas Bloom & Renata Lemos & Raffaella Sadun & Daniela Scur & John Van Reenen, 2016. "International Data on Measuring Management Practices," CEP Occasional Papers 46, Centre for Economic Performance, LSE.
• Alexander Chudik & George Kapetanios & M. Hashem Pesaran, 2016. "Big data analytics: a new perspective," Globalization Institute Working Papers 268, Federal Reserve Bank of Dallas.
  • Alexander Chudik & George Kapetanios & M. Hashem Pesaran, 2016. "Big Data Analytics: A New Perspective," CESifo Working Paper Series 5824, CESifo.
  • A. Chudik & G. Kapetanios & M. Hashem Pesaran, 2016. "Big Data Analytics: A New Perspective," Cambridge Working Papers in Economics 1611, Faculty of Economics, University of Cambridge.
• Dalibor Stevanovic & Rachidi Kotchoni, 2016. "Prévision de l’activité économique au Québec," CIRANO Project Reports 2016rp-08, CIRANO.
• Jean Boivin & Marc P. Giannoni & Dalibor Stevanović, 2020. "Dynamic Effects of Credit Shocks in a Data-Rich Environment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 272-284, April.
  • Jean Boivin & Marc Giannoni & Dalibor Stevanovic, 2013. "Dynamic effects of credit shocks in a data-rich environment," Staff Reports 615, Federal Reserve Bank of New York.
  • Jean Boivin & Marc P. Giannoni & Dalibor Stevanovic, 2016. "Dynamic Effects of Credit Shocks in a Data-Rich Environment," CIRANO Working Papers 2016s-55, CIRANO.
  • Jean Boivin & Marc P. Giannoni & Dalibor Stevanovic, 2013. "Dynamic Effects of Credit Shocks in a Data-Rich Environment," Cahiers de recherche 1324, CIRPEE.
  • Jean Boivin & Marc P. Giannoni & Dalibor Stevanovic, 2013. "Dynamic Effects of Credit Shocks in a Data-Rich Environment," CIRANO Working Papers 2013s-11, CIRANO.
  • Giannoni, Marc & Boivin, Jean & Stevanovic, Dalibor, 2013. "Dynamic Effects of Credit Shocks in a Data-Rich Environment," CEPR Discussion Papers 9470, C.E.P.R. Discussion Papers.
• Luis Arturo Bárcenas & Lorena Barreiro & Carolina Pagliacci, 2016. "What Is the Role of Size in Latin American Banks’ Performancein Response to External Shocks?," Monetaria, Centro de Estudios Monetarios Latinoamericanos, CEMLA, vol. 0(2), pages 233-273, july-dece.
• Luis Arturo Bárcenas & Lorena Barreiro & Carolina Pagliacci, 2016. "¿Cuál es el papel del tamaño de los bancos en su desempeño en América Latina ante choques externos?," Monetaria, Centro de Estudios Monetarios Latinoamericanos, CEMLA, vol. 0(2), pages 251-296, julio-dic.
• Oxana Babecka Kucharcukova & Jan Bruha, 2016. "Nowcasting the Czech Trade Balance," Working Papers 2016/11, Czech National Bank.
• Gustavo Peralta, 2016. "The Nature of Volatility Spillovers across the International Capital Markets," CNMV Working Papers CNMV Working Papers no. 6, CNMV- Spanish Securities Markets Commission - Research and Statistics Department.
• Hafner, C. M. & Linton, O., 2016. "Estimation of a Multiplicative Covariance Structure in the Large Dimensional Case," Cambridge Working Papers in Economics 1664, Faculty of Economics, University of Cambridge.
  • HAFNER, Christian & LINTON, Oliver B. & TANG, Haihan, 2016. "Estimation of a Multiplicative Covariance Structure in the Large Dimensional Case," LIDAM Discussion Papers CORE 2016044, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  • Christian M. Hafner & Oliver Linton & Haihan Tang, 2016. "Estimation of a multiplicative covariance structure in the large dimensional case," CeMMAP working papers CWP52/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
• George Kapetanios & Massimiliano Marcellino & Fabrizio Venditti, 2019. "Large time‐varying parameter VARs: A nonparametric approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(7), pages 1027-1049, November.
  • Marcellino, Massimiliano & Kapetanios, George & Venditti, Fabrizio, 2016. "Large Time-Varying Parameter VARs: A Non-Parametric Approach," CEPR Discussion Papers 11560, C.E.P.R. Discussion Papers.
  • George Kapetanios & Massimiliano Marcellino & Fabrizio Venditti, 2017. "Large time-varying parameter VARs: a non-parametric approach," Temi di discussione (Economic working papers) 1122, Bank of Italy, Economic Research and International Relations Area.
• Jérémy L'Hour, 2016. "Distinguishing the Confounding Factors: Policy Evaluation, High-Dimension and Variable Selection," Working Papers 2016-23, Center for Research in Economics and Statistics.
• Christian Gouriéroux & Alain Monfort & Eric Renault, 2017. "Consistent Pseudo-Maximum Likelihood Estimators," Annals of Economics and Statistics, GENES, issue 125-126, pages 187-218.
  • Christian Gouriéroux & Alain Monfort & Eric Renault, 2016. "Consistent Pseudo-Maximum Likelihood Estimators," Working Papers 2016-33, Center for Research in Economics and Statistics.
  • Christian Gouriéroux & Alain Monfort & Eric Renault, 2017. "Consistent Pseudo-Maximum Likelihood Estimators," Working Papers 2017-10, Center for Research in Economics and Statistics.
• Sebastian Voigt & Oliver Hinz, 2017. "Assessing the economic effects of server launches in free-to-play MMO games," Journal of Business Economics, Springer, vol. 87(4), pages 421-464, May.
  • Voigt, Sebastian & Hinz, Oliver, 2016. "Assessing the Economic Effects of Server Launches in Free-to-Play MMO Games," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 84846, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
• Garcí­a, Juan Angel & Werner, Sebastian E. V., 2016. "Bond risk premia, macroeconomic factors and financial crisis in the euro area," Working Paper Series 1938, European Central Bank.
• Hyndman, Rob J. & Lee, Alan J. & Wang, Earo, 2016. "Fast computation of reconciled forecasts for hierarchical and grouped time series," Computational Statistics & Data Analysis, Elsevier, vol. 97(C), pages 16-32.
  • Rob J Hyndman & Alan Lee & Earo Wang, 2014. "Fast computation of reconciled forecasts for hierarchical and grouped time series," Monash Econometrics and Business Statistics Working Papers 17/14, Monash University, Department of Econometrics and Business Statistics.
• Chen, Kan & Crucini, Mario J., 2016. "Trends and cycles in small open economies: making the case for a general equilibrium approach," Journal of Economic Dynamics and Control, Elsevier, vol. 72(C), pages 159-168.
  • Kan Chen & Mario J. Crucini, 2014. "Trends and Cycles in Small Open Economies: Making The Case For A General Equilibrium Approach," CAMA Working Papers 2014-76, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Kan Chen & Mario J. Crucini, 2016. "Trends and cycles in small open economies: making the case for a general equilibrium approach," Globalization Institute Working Papers 279, Federal Reserve Bank of Dallas.
  • Kan Chen & Mario J. Crucini, 2014. "Trends and cycles in small open economies: making the case for a general equilibrium approach," Globalization Institute Working Papers 217, Federal Reserve Bank of Dallas.
  • Kan Chen & Mario Crucini, 2016. "Trends and Cycles in Small Open Economies: Making The Case For A General Equilibrium Approach," NBER Working Papers 22460, National Bureau of Economic Research, Inc.
  • Kan Chen & Mario Crucini, 2016. "Trends and cycles in small open economies: Making the case for a general equilibrium approach," CAMA Working Papers 2016-50, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Shi, Zhentao, 2016. "Econometric estimation with high-dimensional moment equalities," Journal of Econometrics, Elsevier, vol. 195(1), pages 104-119.
• Byun, Sung Je, 2016. "The usefulness of cross-sectional dispersion for forecasting aggregate stock price volatility," Journal of Empirical Finance, Elsevier, vol. 36(C), pages 162-180.
• Bernstein, Paul & Tuladhar, Sugandha D. & Yuan, Mei, 2016. "Economics of U.S. natural gas exports: Should regulators limit U.S. LNG exports?," Energy Economics, Elsevier, vol. 60(C), pages 427-437.
• Avanzi, Benjamin & Wong, Bernard & Yang, Xinda, 2016. "A micro-level claim count model with overdispersion and reporting delays," Insurance: Mathematics and Economics, Elsevier, vol. 71(C), pages 1-14.
• Butaru, Florentin & Chen, Qingqing & Clark, Brian & Das, Sanmay & Lo, Andrew W. & Siddique, Akhtar, 2016. "Risk and risk management in the credit card industry," Journal of Banking & Finance, Elsevier, vol. 72(C), pages 218-239.
  • Florentin Butaru & QingQing Chen & Brian Clark & Sanmay Das & Andrew W. Lo & Akhtar Siddique, 2015. "Risk and Risk Management in the Credit Card Industry," NBER Working Papers 21305, National Bureau of Economic Research, Inc.
• Bodnar, Taras & Reiß, Markus, 2016. "Exact and asymptotic tests on a factor model in low and large dimensions with applications," Journal of Multivariate Analysis, Elsevier, vol. 150(C), pages 125-151.
• Stock, J.H. & Watson, M.W., 2016. "Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 415-525, Elsevier.
• Galanti, Sébastien, 2016. "Archival data of financial analysts' earnings forecasts in the euro zone: Problems with euro conversions," Research in International Business and Finance, Elsevier, vol. 38(C), pages 466-473.
  • Sébastien GALANTI, 2016. "Archival data of financial analysts' earnings forecasts in the Euro zone: problems with euro conversions," LEO Working Papers / DR LEO 2413, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
  • Sébastien Galanti, 2016. "Archival data of financial analysts' earnings forecasts in the Euro zone: problems with euro conversions," Post-Print hal-01724241, HAL.
  • Sébastien Galanti, 2016. "Archival data of financial analysts' earnings forecasts in the Euro zone: problems with euro conversions," Working Papers hal-01392253, HAL.
• Bjørnland, Hilde C. & Ravazzolo, Francesco & Thorsrud, Leif Anders, 2017. "Forecasting GDP with global components: This time is different," International Journal of Forecasting, Elsevier, vol. 33(1), pages 153-173.
  • Hilde C. Bjørnland & Francesco Ravazzolo & Leif Anders Thorsrud, 2015. "Forecasting GDP with global components. This time is different," Working Papers No 1/2015, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • Hilde C. Bjornland & Francesco Ravazzolo & Leif Anders Thorsrud, 2016. "Forecasting GDP with global components. This time is different," CAMA Working Papers 2016-26, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Hilde C. Bjørnland & Francesco Ravazzolo & Leif Anders Thorsrud, 2015. "Forecasting GDP with global components. This time is different," Working Paper 2015/05, Norges Bank.
• Chen, Kan & Crucini, Mario J., 2016. "Trends and cycles in small open economies: making the case for a general equilibrium approach," Journal of Economic Dynamics and Control, Elsevier, vol. 72(C), pages 159-168.
  • Kan Chen & Mario J. Crucini, 2014. "Trends and cycles in small open economies: making the case for a general equilibrium approach," Globalization Institute Working Papers 217, Federal Reserve Bank of Dallas.
  • Kan Chen & Mario Crucini, 2016. "Trends and cycles in small open economies: Making the case for a general equilibrium approach," CAMA Working Papers 2016-50, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Kan Chen & Mario Crucini, 2016. "Trends and Cycles in Small Open Economies: Making The Case For A General Equilibrium Approach," NBER Working Papers 22460, National Bureau of Economic Research, Inc.
  • Kan Chen & Mario J. Crucini, 2016. "Trends and cycles in small open economies: making the case for a general equilibrium approach," Globalization Institute Working Papers 279, Federal Reserve Bank of Dallas.
  • Kan Chen & Mario J. Crucini, 2014. "Trends and Cycles in Small Open Economies: Making The Case For A General Equilibrium Approach," CAMA Working Papers 2014-76, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Kurt Unger & Fernando Varela, 2016. "Complejidad, competitividad e innovación en los estados mexicanos: La urgencia de una Política Industrial integral y diferenciada," Working Papers DTE 605, CIDE, División de Economía.
• Breitung Jörg & Eickmeier Sandra, 2016. "Analyzing International Business and Financial Cycles using Multi-Level Factor Models: A Comparison of Alternative Approaches," Advances in Econometrics, in: Dynamic Factor Models, volume 35, pages 177-214, Emerald Group Publishing Limited.
• Catherine Doz & Anna Petronevich, 2016. "Dating Business Cycle Turning Points for the French Economy: An MS-DFM approach," Advances in Econometrics, in: Dynamic Factor Models, volume 35, pages 481-538, Emerald Group Publishing Limited.
  • Catherine Doz & Anna Petronevich, 2015. "Dating Business Cycle Turning Points for the French Economy: a MS-DFM approach," Post-Print hal-01159200, HAL.
  • Catherine Doz & Anna Petronevich, 2015. "Dating Business Cycle Turning Points for the French Economy: a MS-DFM approach," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01159200, HAL.
  • Catherine Doz & Anna Petronevich, 2015. "Dating Business Cycle Turning Points for the French Economy: a MS-DFM approach," Documents de travail du Centre d'Economie de la Sorbonne 15009, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
• R. Kelley Pace & James P. LeSage, 2016. "Fast Simulated Maximum Likelihood Estimation of the Spatial Probit Model Capable of Handling Large Samples," Advances in Econometrics, in: Spatial Econometrics: Qualitative and Limited Dependent Variables, volume 37, pages 3-34, Emerald Group Publishing Limited.
• Sumana Chaudhuri & Shovan Ray & Ganesh-Kumar, 2018. "Integrated Model of Computable General Equilibrium and Social Cost Benefit Analysis of an Indian Oil Refinery: Future Projections and Macroeconomic Effects," Journal of Infrastructure Development, India Development Foundation, vol. 10(1-2), pages 96-125, June.
  • Shovan Ray & A. Ganesh Kumar & Sumana Chaudhuri, 2016. "Integrated model of computable general equilibrium and social cost benefit analysis of an Indian oil refinery: Future projections and macroeconomic effects," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2016-024, Indira Gandhi Institute of Development Research, Mumbai, India.
  • Shovan Ray & A. Ganesh-Kumar & Sumana Chaudhuri, 2016. "Integrated Model of Computable General Equilibrium and Social Cost Benefit Analysis of an Indian Oil Refinery: Future Projections and Macroeconomic Effects," Working Papers id:11381, eSocialSciences.
• Jushan Bai & Xu Han, 2016. "Structural Changes in High Dimensional Factor Models," Frontiers of Economics in China-Selected Publications from Chinese Universities, Higher Education Press, vol. 11(1), pages 9-39, March.
• Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2018. "Measuring Uncertainty and Its Impact on the Economy," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 799-815, December.
  • Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2016. "Measuring Uncertainty and Its Impact on the Economy," BAFFI CAREFIN Working Papers 1639, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
  • Andrea Carriero & Todd E. Clark & Marcellino Massimiliano, 2016. "Measuring Uncertainty and Its Impact on the Economy," Working Papers (Old Series) 1622, Federal Reserve Bank of Cleveland.
• Alexander Chudik & George Kapetanios & M. Hashem Pesaran, 2016. "Big Data Analytics: A New Perspective," CESifo Working Paper Series 5824, CESifo.
  • Alexander Chudik & George Kapetanios & M. Hashem Pesaran, 2016. "Big data analytics: a new perspective," Globalization Institute Working Papers 268, Federal Reserve Bank of Dallas.
  • A. Chudik & G. Kapetanios & M. Hashem Pesaran, 2016. "Big Data Analytics: A New Perspective," Cambridge Working Papers in Economics 1611, Faculty of Economics, University of Cambridge.
• Chen, Kan & Crucini, Mario J., 2016. "Trends and cycles in small open economies: making the case for a general equilibrium approach," Journal of Economic Dynamics and Control, Elsevier, vol. 72(C), pages 159-168.
  • Kan Chen & Mario J. Crucini, 2014. "Trends and cycles in small open economies: making the case for a general equilibrium approach," Globalization Institute Working Papers 217, Federal Reserve Bank of Dallas.
  • Kan Chen & Mario J. Crucini, 2016. "Trends and cycles in small open economies: making the case for a general equilibrium approach," Globalization Institute Working Papers 279, Federal Reserve Bank of Dallas.
  • Kan Chen & Mario Crucini, 2016. "Trends and Cycles in Small Open Economies: Making The Case For A General Equilibrium Approach," NBER Working Papers 22460, National Bureau of Economic Research, Inc.
  • Kan Chen & Mario Crucini, 2016. "Trends and cycles in small open economies: Making the case for a general equilibrium approach," CAMA Working Papers 2016-50, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Kan Chen & Mario J. Crucini, 2014. "Trends and Cycles in Small Open Economies: Making The Case For A General Equilibrium Approach," CAMA Working Papers 2014-76, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• A. Chudik & G. Kapetanios & M. Hashem Pesaran, 2018. "A One Covariate at a Time, Multiple Testing Approach to Variable Selection in High‐Dimensional Linear Regression Models," Econometrica, Econometric Society, vol. 86(4), pages 1479-1512, July.
  • Chudik, A. & Kapetanios, G. & Pesaran, Hashem, 2016. "A One-Covariate at a Time, Multiple Testing Approach to Variable Selection in High-Dimensional Linear Regression Models," Cambridge Working Papers in Economics 1677, Faculty of Economics, University of Cambridge.
  • Alexander Chudik & George Kapetanios & M. Hashem Pesaran, 2016. "A one-covariate at a time, multiple testing approach to variable selection in high-dimensional linear regression models," Globalization Institute Working Papers 290, Federal Reserve Bank of Dallas.
• Rui Pedro Brito & Hélder Sebastião & Pedro Godinho, 2016. "Portfolio Choice with High Frequency Data: CRRA Preferences and the Liquidity Effect," GEMF Working Papers 2016-13, GEMF, Faculty of Economics, University of Coimbra.
• R. P. Brito & H. Sebastião & P. Godinho, 2017. "Portfolio choice with high frequency data: CRRA preferences and the liquidity effect," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 16(2), pages 65-86, August.
  • Rui Pedro Brito & Hélder Sebastião & Pedro Godinho, 2016. "Portfolio Choice with High Frequency Data: CRRA Preferences and the Liquidity Effect," GEMF Working Papers 2016-13, GEMF, Faculty of Economics, University of Coimbra.
• Yongchen Zhao, 2020. "Predicting U.S. Business Cycle Turning Points Using Real-Time Diffusion Indexes Based on a Large Data Set," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 16(2), pages 77-97, November.
  • Herman Stekler & Yongchen Zhao, 2016. "Predicting U.S. Business Cycle Turning Points Using Real-Time Diffusion Indexes Based on a Large Data Set," Working Papers 2016-15, Towson University, Department of Economics, revised Sep 2016.
  • Herman O. Stekler & Yongchen Zhao, 2016. "Predicting U.S. Business Cycle Turning Points Using Real-Time Diffusion Indexes Based on a Large Data Set," Working Papers 2016-006, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
• Alexander N. Bogin & William M. Doerner & William D. Larson, 2016. "Missing the Mark: House Price Index Accuracy and Mortgage Credit Modeling," FHFA Staff Working Papers 16-04, Federal Housing Finance Agency.
  • Alexander N. Bogin & William M. Doerner & William D. Larson, 2016. "Missing the Mark: House Price Index Accuracy and Mortgage Credit Modeling," Working Papers 2016-010, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
• Galanti, Sébastien, 2016. "Archival data of financial analysts' earnings forecasts in the euro zone: Problems with euro conversions," Research in International Business and Finance, Elsevier, vol. 38(C), pages 466-473.
  • Sébastien GALANTI, 2016. "Archival data of financial analysts' earnings forecasts in the Euro zone: problems with euro conversions," LEO Working Papers / DR LEO 2413, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
  • Sébastien Galanti, 2016. "Archival data of financial analysts' earnings forecasts in the Euro zone: problems with euro conversions," Post-Print hal-01724241, HAL.
  • Sébastien Galanti, 2016. "Archival data of financial analysts' earnings forecasts in the Euro zone: problems with euro conversions," Working Papers hal-01392253, HAL.
• Galanti, Sébastien, 2016. "Archival data of financial analysts' earnings forecasts in the euro zone: Problems with euro conversions," Research in International Business and Finance, Elsevier, vol. 38(C), pages 466-473.
  • Sébastien GALANTI, 2016. "Archival data of financial analysts' earnings forecasts in the Euro zone: problems with euro conversions," LEO Working Papers / DR LEO 2413, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
  • Sébastien Galanti, 2016. "Archival data of financial analysts' earnings forecasts in the Euro zone: problems with euro conversions," Working Papers hal-01392253, HAL.
  • Sébastien Galanti, 2016. "Archival data of financial analysts' earnings forecasts in the Euro zone: problems with euro conversions," Post-Print hal-01724241, HAL.
• Júlia Varga, 2017. "Out-migration and attrition of physicians and dentists before and after EU accession (2003 and 2011): the case of Hungary," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 18(9), pages 1079-1093, December.
  • Júlia Varga, 2016. "Out-migration and attrition of physicians and dentists before and after EU accession (2003 and 2011). The case of Hungary," Budapest Working Papers on the Labour Market 1604, Institute of Economics, Centre for Economic and Regional Studies.
• Alexander N. Bogin & William M. Doerner & William D. Larson, 2016. "Missing the Mark: House Price Index Accuracy and Mortgage Credit Modeling," Working Papers 2016-010, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
  • Alexander N. Bogin & William M. Doerner & William D. Larson, 2016. "Missing the Mark: House Price Index Accuracy and Mortgage Credit Modeling," FHFA Staff Working Papers 16-04, Federal Housing Finance Agency.
• Wolfgang K. Härdle & Chen Huang & Shih-Kang Chao, 2016. "Calculating Joint Confidence Bands for Impulse Response Functions using Highest Density Regions," SFB 649 Discussion Papers SFB649DP2016-018, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
• Tran, Ngoc M. & Burdejová, Petra & Ospienko, Maria & Härdle, Wolfgang K., 2019. "Principal component analysis in an asymmetric norm," Journal of Multivariate Analysis, Elsevier, vol. 171(C), pages 1-21.
  • Ngoc M. Tran & Petra Burdejová & Maria Osipenko & Wolfgang K. Härdle, 2016. "Principal Component Analysis in an Asymmetric Norm," SFB 649 Discussion Papers SFB649DP2016-040, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
• Chao, Shih-Kang & Härdle, Wolfgang K. & Yuan, Ming, 2021. "Factorisable Multitask Quantile Regression," Econometric Theory, Cambridge University Press, vol. 37(4), pages 794-816, August.
  • Shih-Kang Chao & Wolfgang K. Härdle & Ming Yuan, 2016. "Factorisable Multi-Task Quantile Regression," SFB 649 Discussion Papers SFB649DP2016-057, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  • Chao, Shih-Kang & Härdle, Wolfgang Karl & Yuan, Ming, 2020. "Factorisable Multitask Quantile Regression," IRTG 1792 Discussion Papers 2020-004, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
• Grazia Biorci & Antonella Emina & Michelangelo Puliga & Lisa Sella & Gianna Vivaldo, 2016. "Tweet-tales: moods of socio-economic crisis?," Working Papers 04/2016, IMT School for Advanced Studies Lucca, revised Jul 2016.
• Pedro Carneiro & Sokbae Lee & Daniel Wilhelm, 2020. "Optimal data collection for randomized control trials," The Econometrics Journal, Royal Economic Society, vol. 23(1), pages 1-31.
  • Carneiro, Pedro & Lee, Sokbae & Wilhelm, Daniel, 2016. "Optimal Data Collection for Randomized Control Trials," IZA Discussion Papers 9908, Institute of Labor Economics (IZA).
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers 15/17, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers 45/17, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2019. "Optimal Data Collection for Randomized Control Trials," CeMMAP working papers CWP21/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers CWP15/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2016. "Optimal data collection for randomized control trials," CeMMAP working papers CWP15/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae Lee & Daniel Wilhelm, 2016. "Optimal Data Collection for Randomized Control Trials," Papers 1603.03675, arXiv.org, revised Aug 2016.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers CWP45/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2016. "Optimal data collection for randomized control trials," CeMMAP working papers 15/16, Institute for Fiscal Studies.
• Koen Jochmans & Martin Weidner, 2019. "Fixed‐Effect Regressions on Network Data," Econometrica, Econometric Society, vol. 87(5), pages 1543-1560, September.
  • Koen Jochmans & Martin Weidner, 2016. "Fixed-effect regressions on network data," CeMMAP working papers 32/16, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2016. "Fixed-effect regressions on network data," CeMMAP working papers CWP32/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2018. "Fixed-effect regressions on network data," CeMMAP working papers CWP44/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2017. "Fixed-effect regressions on network data," CeMMAP working papers CWP26/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Jochmans, K. & Weidner, M., 2019. "Fixed-Effect Regressions on Network Data," Cambridge Working Papers in Economics 1938, Faculty of Economics, University of Cambridge.
  • Koen Jochmans & Martin Weidner, 2016. "Fixed-Effect Regressions on Network Data," Papers 1608.01532, arXiv.org, revised Apr 2019.
  • Koen Jochmans & Martin Weidner, 2019. "Fixed-effect regressions on network data," CeMMAP working papers CWP16/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2017. "Fixed-effect regressions on network data," CeMMAP working papers 26/17, Institute for Fiscal Studies.
• Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Valid Post-Selection and Post-Regularization Inference: An Elementary, General Approach," Annual Review of Economics, Annual Reviews, vol. 7(1), pages 649-688, August.
  • Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Valid Post-Selection and Post-Regularization Inference: An Elementary, General Approach," Papers 1501.03430, arXiv.org, revised Aug 2015.
  • Victor Chernozhukov & Christian Hansen & Martin Spindler, 2016. "Valid post-selection and post-regularization inference: An elementary, general approach," CeMMAP working papers CWP36/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Victor Chernozhukov & Christian Hansen & Martin Spindler, 2016. "Valid post-selection and post-regularization inference: An elementary, general approach," CeMMAP working papers 36/16, Institute for Fiscal Studies.
• HAFNER, Christian & LINTON, Oliver B. & TANG, Haihan, 2016. "Estimation of a Multiplicative Covariance Structure in the Large Dimensional Case," LIDAM Discussion Papers CORE 2016044, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  • Christian M. Hafner & Oliver Linton & Haihan Tang, 2016. "Estimation of a multiplicative covariance structure in the large dimensional case," CeMMAP working papers CWP52/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Hafner, C. M. & Linton, O., 2016. "Estimation of a Multiplicative Covariance Structure in the Large Dimensional Case," Cambridge Working Papers in Economics 1664, Faculty of Economics, University of Cambridge.
• Sumana Chaudhuri & Shovan Ray & Ganesh-Kumar, 2018. "Integrated Model of Computable General Equilibrium and Social Cost Benefit Analysis of an Indian Oil Refinery: Future Projections and Macroeconomic Effects," Journal of Infrastructure Development, India Development Foundation, vol. 10(1-2), pages 96-125, June.
  • Shovan Ray & A. Ganesh-Kumar & Sumana Chaudhuri, 2016. "Integrated Model of Computable General Equilibrium and Social Cost Benefit Analysis of an Indian Oil Refinery: Future Projections and Macroeconomic Effects," Working Papers id:11381, eSocialSciences.
  • Shovan Ray & A. Ganesh Kumar & Sumana Chaudhuri, 2016. "Integrated model of computable general equilibrium and social cost benefit analysis of an Indian oil refinery: Future projections and macroeconomic effects," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2016-024, Indira Gandhi Institute of Development Research, Mumbai, India.
• Marco Di Zio & Ugo Guarnera & Roberta Varriale, 2016. "Estimation of the main variables of the economic account of small and medium enterprises based on administrative sources," Rivista di statistica ufficiale, ISTAT - Italian National Institute of Statistics - (Rome, ITALY), vol. 18(1), pages 71-81.
• Paolo Righi, 2016. "Estimation procedure and inference for component totals of the economic aggregates in the “Frame SBS”," Rivista di statistica ufficiale, ISTAT - Italian National Institute of Statistics - (Rome, ITALY), vol. 18(1), pages 83-97.
• Pedro S. Martins, 2015. "Working to get fired? Regression discontinuity effects of unemployment benefit eligibility on prior employment duration," Working Papers 61, Queen Mary, University of London, School of Business and Management, Centre for Globalisation Research.
  • Martins, Pedro S., 2016. "Working to Get Fired? Regression Discontinuity Effects of Unemployment Benefit Eligibility on Prior Employment Duration," IZA Discussion Papers 10262, Institute of Labor Economics (IZA).
• Pedro Carneiro & Sokbae Lee & Daniel Wilhelm, 2020. "Optimal data collection for randomized control trials," The Econometrics Journal, Royal Economic Society, vol. 23(1), pages 1-31.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2016. "Optimal data collection for randomized control trials," CeMMAP working papers CWP15/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers 15/17, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers 45/17, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers CWP15/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Carneiro, Pedro & Lee, Sokbae & Wilhelm, Daniel, 2016. "Optimal Data Collection for Randomized Control Trials," IZA Discussion Papers 9908, Institute of Labor Economics (IZA).
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2019. "Optimal Data Collection for Randomized Control Trials," CeMMAP working papers CWP21/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2016. "Optimal data collection for randomized control trials," CeMMAP working papers 15/16, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers CWP45/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae Lee & Daniel Wilhelm, 2016. "Optimal Data Collection for Randomized Control Trials," Papers 1603.03675, arXiv.org, revised Aug 2016.
• Nikolaos Askitas, 2016. "Big Data is a big deal but how much data do we need? [Big Data gut und schön. Aber wie viel Data brauchen wir?]," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 10(2), pages 113-125, October.
  • Askitas, Nikos, 2016. "Big Data Is a Big Deal But How Much Data Do We Need?," IZA Discussion Papers 9988, Institute of Labor Economics (IZA).
• Varga, Júlia, 2016. "Hova lettek az orvosok?. Az orvosok külföldre vándorlása és pályaelhagyása Magyarországon, 2003-2011 [Where have all the doctors gone?. Migration and attrition of physicians and dentists in Hungary," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(1), pages 1-26.
• Galanti, Sébastien, 2016. "Archival data of financial analysts' earnings forecasts in the euro zone: Problems with euro conversions," Research in International Business and Finance, Elsevier, vol. 38(C), pages 466-473.
  • Sébastien Galanti, 2016. "Archival data of financial analysts' earnings forecasts in the Euro zone: problems with euro conversions," Working Papers hal-01392253, HAL.
  • Sébastien GALANTI, 2016. "Archival data of financial analysts' earnings forecasts in the Euro zone: problems with euro conversions," LEO Working Papers / DR LEO 2413, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
  • Sébastien Galanti, 2016. "Archival data of financial analysts' earnings forecasts in the Euro zone: problems with euro conversions," Post-Print hal-01724241, HAL.
• Jochen Lüdering, 2018. "Standing and ‘survival’ in the adult film industry," Applied Economics, Taylor & Francis Journals, vol. 50(16), pages 1812-1823, April.
  • Jochen Lüdering, 2016. "Standing and “Survival” in the Adult Film Industry," MAGKS Papers on Economics 201626, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
• Markus Engler & Vahidin Jeleskovic, 2016. "Intraday volatility, trading volume and trading intensity in the interbank market e-MID," MAGKS Papers on Economics 201648, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
• György Inzelt & Gábor Szappanos & Zsolt Armai, 2016. "Supervision by robust risk monitoring – a cycle-independent Hungarian corporate credit rating system," Financial and Economic Review, Magyar Nemzeti Bank (Central Bank of Hungary), vol. 15(3), pages 51-78.
• Kang, Yanfei & Hyndman, Rob J. & Smith-Miles, Kate, 2017. "Visualising forecasting algorithm performance using time series instance spaces," International Journal of Forecasting, Elsevier, vol. 33(2), pages 345-358.
  • Yanfei Kang & Rob J. Hyndman & Kate Smith-Miles, 2016. "Visualising forecasting Algorithm Performance using Time Series Instance Spaces," Monash Econometrics and Business Statistics Working Papers 10/16, Monash University, Department of Econometrics and Business Statistics.
• Chen, Kan & Crucini, Mario J., 2016. "Trends and cycles in small open economies: making the case for a general equilibrium approach," Journal of Economic Dynamics and Control, Elsevier, vol. 72(C), pages 159-168.
  • Kan Chen & Mario J. Crucini, 2014. "Trends and cycles in small open economies: making the case for a general equilibrium approach," Globalization Institute Working Papers 217, Federal Reserve Bank of Dallas.
  • Kan Chen & Mario Crucini, 2016. "Trends and Cycles in Small Open Economies: Making The Case For A General Equilibrium Approach," NBER Working Papers 22460, National Bureau of Economic Research, Inc.
  • Kan Chen & Mario Crucini, 2016. "Trends and cycles in small open economies: Making the case for a general equilibrium approach," CAMA Working Papers 2016-50, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Kan Chen & Mario J. Crucini, 2016. "Trends and cycles in small open economies: making the case for a general equilibrium approach," Globalization Institute Working Papers 279, Federal Reserve Bank of Dallas.
  • Kan Chen & Mario J. Crucini, 2014. "Trends and Cycles in Small Open Economies: Making The Case For A General Equilibrium Approach," CAMA Working Papers 2014-76, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Radoslav Tusan, 2016. "Using Benford'S Law To The Detection Of Misrepresentation Of Financial Statements Data," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(1), pages 737-745, July.
• Vipul Kumar Singh, 2016. "Pricing and hedging competitiveness of the tree option pricing models: Evidence from India," Journal of Asset Management, Palgrave Macmillan, vol. 17(6), pages 453-475, October.
• Daniel Kaimann & Nadja Maraun & Joe Cox, 2016. "Identifying the preferences and heterogeneity of consumer groups in multiplayer video games," Working Papers CIE 94, Paderborn University, CIE Center for International Economics.
• Hännikäinen, Jari, 2017. "When does the yield curve contain predictive power? Evidence from a data-rich environment," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1044-1064.
  • Jari Hännikäinen, 2016. "When does the yield curve contain predictive power? Evidence from a data-rich environment," Working Papers 1603, Tampere University, Faculty of Management and Business, Economics.
  • Hännikäinen, Jari, 2016. "When does the yield curve contain predictive power? Evidence from a data-rich environment," MPRA Paper 70489, University Library of Munich, Germany.
• Ning Xu & Jian Hong & Timothy C. G. Fisher, 2016. "Model selection consistency from the perspective of generalization ability and VC theory with an application to Lasso," Papers 1606.00142, arXiv.org.
  • Xu, Ning & Hong, Jian & Fisher, Timothy, 2016. "Model selection consistency from the perspective of generalization ability and VC theory with an application to Lasso," MPRA Paper 71670, University Library of Munich, Germany.
• Einian, Majid & Nili, Masoud, 2016. "Consumption Smoothing and Borrowing Constraints: Evidence from Household Surveys of Iran," MPRA Paper 72461, University Library of Munich, Germany.
• Ning Xu & Jian Hong & Timothy C. G. Fisher, 2016. "Finite-sample and asymptotic analysis of generalization ability with an application to penalized regression," Papers 1609.03344, arXiv.org, revised Sep 2016.
  • Xu, Ning & Hong, Jian & Fisher, Timothy, 2016. "Finite-sample and asymptotic analysis of generalization ability with an application to penalized regression," MPRA Paper 73622, University Library of Munich, Germany.
• Cordero, José Manuel & Gil, María & Pedraja Chaparro, Francisco, 2016. "Exploring the effect of financial literacy courses on student achievement: a cross-country approach using PISA 2012 data," MPRA Paper 75474, University Library of Munich, Germany.
• Bonga-Bonga, Lumengo & Mabe, Queen Magadi, 2020. "How financially integrated are trading blocs in Africa?," The Quarterly Review of Economics and Finance, Elsevier, vol. 75(C), pages 84-94.
  • Bonga-Bonga, Lumengo & Mabe, Queen Magadi, 2016. "How financially integrated are trading blocs in Africa?," MPRA Paper 75716, University Library of Munich, Germany.
  • Lumengo Bonga-Bonga, 2017. "How financially integrated are trading blocs in Africa?," EcoMod2017 10580, EcoMod.
• Nikitinsky, Nikita & Shashev, Sergey & Kachurina, Polina & Bespalov, Aleksander, 2016. "Big Data and Machine Learning in Government Projects: Expert Evaluation Case," MPRA Paper 82865, University Library of Munich, Germany.
• Mitrofanova, Ekaterina S. & Artamonova, Alyona V., 2016. "Studying Family Formation Trajectories’ Deinstitutionalization in Russia Using Sequence Analysis," MPRA Paper 82877, University Library of Munich, Germany.
• Trabelsi, Mohamed Ali, 2016. "Analyse des données : Résumé de cours avec exercices d’application [Data analysis: course summary with case studies]," MPRA Paper 82947, University Library of Munich, Germany, revised 03 May 2016.
• Pallara, Kevin, 2016. "The dynamic effects of government spending: a FAVAR approach," MPRA Paper 92283, University Library of Munich, Germany.
• Roman Huptas, 2016. "The UHF-GARCH-Type Model in the Analysis of Intraday Volatility and Price Durations – the Bayesian Approach," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 8(1), pages 1-20, March.
• Tuhkuri, Joonas, 2016. "ETLAnow: A Model for Forecasting with Big Data – Forecasting Unemployment with Google Searches in Europe," ETLA Reports 54, The Research Institute of the Finnish Economy.
• Tuhkuri, Joonas, 2016. "Forecasting Unemployment with Google Searches," ETLA Working Papers 35, The Research Institute of the Finnish Economy.
• Borzykh, Olga, 2016. "Bank lending channel in Russia: A TVP-FAVAR approach," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 43, pages 96-117.
• Rebouças, Sílvia & Oliveira, Daniele & Soares, Rômulo & Ferreira, Eugénia & Gouveia, Maria José, 2016. "Classification Of The Financial Sustainability Of Health Insurance Beneficiaries Through Data Mining Techniques," Journal of Tourism, Sustainability and Well-being, Cinturs - Research Centre for Tourism, Sustainability and Well-being, University of Algarve, vol. 4(3), pages 229-242.
• Vincenzo Atella & Federico Belotti & Valentina Conti & Claudio Cricelli & Joanna Kopinska & Andrea Piano Mortari, 2016. "Modeling public health care expenditure using patient level data: Empirical evidence from Italy," CEIS Research Paper 367, Tor Vergata University, CEIS, revised 10 Feb 2016.
• Michał Bernardelli, 2016. "Econometric modeling of panel data using parallel computing with Apache Spark," Collegium of Economic Analysis Annals, Warsaw School of Economics, Collegium of Economic Analysis, issue 41, pages 189-202.
• Pietro Battiston, 2016. "Constrained Network Formation," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 2(3), pages 347-362, November.
• Kajal Lahiri & Yongchen Zhao, 2016. "Determinants of Consumer Sentiment Over Business Cycles: Evidence from the US Surveys of Consumers," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(2), pages 187-215, December.
  • Kajal Lahiri & Yongchen Zhao, 2016. "Determinants of Consumer Sentiment over Business Cycles: Evidence from the U.S. Surveys of Consumers," Working Papers 2016-14, Towson University, Department of Economics, revised Jul 2016.
• Matias Quiroz & Robert Kohn & Mattias Villani & Minh-Ngoc Tran, 2019. "Speeding Up MCMC by Efficient Data Subsampling," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 114(526), pages 831-843, April.
  • Quiroz, Matias & Villani, Mattias & Kohn, Robert, 2015. "Speeding Up Mcmc By Efficient Data Subsampling," Working Paper Series 297, Sveriges Riksbank (Central Bank of Sweden).
  • Kohn, Robert & Quiroz, Matias & Tran, Minh-Ngoc & Villani, Mattias, 2016. "Speeding up MCMC by Efficient Data Subsampling," Working Papers 2123/16205, University of Sydney Business School, Discipline of Business Analytics.
• Simon Beyeler & Sylvia Kaufmann, 2016. "Factor augmented VAR revisited - A sparse dynamic factor model approach," Working Papers 16.08, Swiss National Bank, Study Center Gerzensee.
  • Kaufmann, Sylvia & Beyeler, Simon, 2018. "Factor augmented VAR revisited - A sparse dynamic factor model approach," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181602, Verein für Socialpolitik / German Economic Association.
  • Simon Beyeler & Sylvia Kaufmann, 2019. "Factor augmented VAR revisited - A sparse dynamic factor model approach," Working Papers 16.08R, Swiss National Bank, Study Center Gerzensee.
• Hännikäinen, Jari, 2017. "When does the yield curve contain predictive power? Evidence from a data-rich environment," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1044-1064.
  • Hännikäinen, Jari, 2016. "When does the yield curve contain predictive power? Evidence from a data-rich environment," MPRA Paper 70489, University Library of Munich, Germany.
  • Jari Hännikäinen, 2016. "When does the yield curve contain predictive power? Evidence from a data-rich environment," Working Papers 1603, Tampere University, Faculty of Management and Business, Economics.
• Boot, Tom & Nibbering, Didier, 2019. "Forecasting using random subspace methods," Journal of Econometrics, Elsevier, vol. 209(2), pages 391-406.
  • Tom Boot & Didier Nibbering, 2016. "Forecasting Using Random Subspace Methods," Tinbergen Institute Discussion Papers 16-073/III, Tinbergen Institute, revised 11 Aug 2017.
• Kajal Lahiri & Yongchen Zhao, 2016. "Determinants of Consumer Sentiment Over Business Cycles: Evidence from the US Surveys of Consumers," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(2), pages 187-215, December.
  • Kajal Lahiri & Yongchen Zhao, 2016. "Determinants of Consumer Sentiment over Business Cycles: Evidence from the U.S. Surveys of Consumers," Working Papers 2016-14, Towson University, Department of Economics, revised Jul 2016.
• Yongchen Zhao, 2020. "Predicting U.S. Business Cycle Turning Points Using Real-Time Diffusion Indexes Based on a Large Data Set," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 16(2), pages 77-97, November.
  • Herman O. Stekler & Yongchen Zhao, 2016. "Predicting U.S. Business Cycle Turning Points Using Real-Time Diffusion Indexes Based on a Large Data Set," Working Papers 2016-006, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
  • Herman Stekler & Yongchen Zhao, 2016. "Predicting U.S. Business Cycle Turning Points Using Real-Time Diffusion Indexes Based on a Large Data Set," Working Papers 2016-15, Towson University, Department of Economics, revised Sep 2016.
• Jushan Bai & Kunpeng Li, 2016. "Maximum Likelihood Estimation and Inference for Approximate Factor Models of High Dimension," The Review of Economics and Statistics, MIT Press, vol. 98(2), pages 298-309, May.
  • Bai, Jushan & Li, Kunpeng, 2012. "Maximum likelihood estimation and inference for approximate factor models of high dimension," MPRA Paper 42099, University Library of Munich, Germany, revised 19 Oct 2012.
• Zhong, Sheng, 2016. "The dynamics of vehicle energy efficiency: Evidence from the Massachusetts Vehicle Census," MERIT Working Papers 2016-014, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
• Tor Korneliussen & Michael Greenacre, 2016. "Information Sources Used by European Tourists: A Cross-Cultural Study," Working Papers 915, Barcelona School of Economics.
  • Tor Korneliussen & Michael Greenacre, 2016. "Information sources used by European tourists: A cross-cultural study," Economics Working Papers 1527, Department of Economics and Business, Universitat Pompeu Fabra.
• Ritchie, Felix & Veliziotis, Michail & Drew, Hilary & Whittard, Damian, 2017. "Measuring compliance with minimum wages," Journal of Economic and Social Measurement, IOS Press, issue 3-4, pages 249-270.
  • Felix Ritchie & Michail Veliziotis & Hilary Drew & Damian Whittard, 2016. "Measuring compliance with minimum wages," Working Papers 20161608, Department of Accounting, Economics and Finance, Bristol Business School, University of the West of England, Bristol.
• Tim Oliver Berg, 2016. "Multivariate Forecasting with BVARs and DSGE Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(8), pages 718-740, December.
  • Berg, Tim Oliver, 2015. "Multivariate Forecasting with BVARs and DSGE Models," MPRA Paper 62405, University Library of Munich, Germany.
• Timo Bettendorf, 2019. "Spillover effects of credit default risk in the euro area and the effects on the Euro: A GVAR approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(1), pages 296-312, January.
  • Bettendorf, Timo, 2016. "Spillover effects of credit default risk in the euro area and the effects on the euro: A GVAR approach," Discussion Papers 42/2016, Deutsche Bundesbank.
• Raddant, Matthias & Wagner, Friedrich, 2016. "Multivariate GARCH for a large number of stocks," Kiel Working Papers 2049, Kiel Institute for the World Economy (IfW Kiel).
• Kaeding, Matthias, 2016. "Fast, approximate MCMC for Bayesian analysis of large data sets: A design based approach," Ruhr Economic Papers 660, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
• Härdle, Wolfgang Karl & Huang, Chen & Chao, Shih-Kang, 2016. "Factorisable sparse tail event curves with expectiles," SFB 649 Discussion Papers 2016-018, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
• Tran, Ngoc M. & Burdejová, Petra & Ospienko, Maria & Härdle, Wolfgang K., 2019. "Principal component analysis in an asymmetric norm," Journal of Multivariate Analysis, Elsevier, vol. 171(C), pages 1-21.
  • Tran, Ngoc Mai & Osipenko, Maria & Härdle, Wolfgang Karl, 2014. "Principal component analysis in an asymmetric norm," SFB 649 Discussion Papers 2014-001, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
  • Tran, Ngoc Mai & Burdejová, Petra & Osipenko, Maria & Härdle, Wolfgang Karl, 2016. "Principal component analysis in an asymmetric norm," SFB 649 Discussion Papers 2016-040, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
• Chao, Shih-Kang & Härdle, Wolfgang K. & Yuan, Ming, 2021. "Factorisable Multitask Quantile Regression," Econometric Theory, Cambridge University Press, vol. 37(4), pages 794-816, August.
  • Chao, Shih-Kang & Härdle, Wolfgang Karl & Yuan, Ming, 2016. "Factorisable multi-task quantile regression," SFB 649 Discussion Papers 2016-057, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
  • Chao, Shih-Kang & Härdle, Wolfgang Karl & Yuan, Ming, 2020. "Factorisable Multitask Quantile Regression," IRTG 1792 Discussion Papers 2020-004, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
• Chao, Shih-Kang & Härdle, Wolfgang Karl & Huang, Chen, 2016. "Multivariate factorisable sparse asymmetric least squares regression," SFB 649 Discussion Papers 2016-058, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
• Christian Hansen & Damian Kozbur & Sanjog Misra, 2016. "Targeted undersmoothing," ECON - Working Papers 282, Department of Economics - University of Zurich, revised Apr 2018.

2015

• Lorenzo Boldrini & Eric Hillebrand, 2015. "Supervision in Factor Models Using a Large Number of Predictors," CREATES Research Papers 2015-38, Department of Economics and Business Economics, Aarhus University.
• Jakob Guldbæk Mikkelsen & Eric Hillebrand & Giovanni Urga, 2015. "Maximum Likelihood Estimation of Time-Varying Loadings in High-Dimensional Factor Models," CREATES Research Papers 2015-61, Department of Economics and Business Economics, Aarhus University.
• Patrick Bajari & Denis Nekipelov & Stephen P. Ryan & Miaoyu Yang, 2015. "Machine Learning Methods for Demand Estimation," American Economic Review, American Economic Association, vol. 105(5), pages 481-485, May.
• Burns, Christopher & Prager, Daniel & Ghosh, Sujit & Goodwin, Barry, 2015. "Imputing for Missing Data in the ARMS Household Section: A Multivariate Imputation Approach," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205291, Agricultural and Applied Economics Association.
• Louhichi, Kamel & Ciaian, Pavel & Espinosa, Maria & Colen, Liesbeth & Perni, Angel & Gomez y Paloma, Sergio, 2015. "Farm-level economic impacts of EU-CAP greening measures," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205309, Agricultural and Applied Economics Association.
• Ferto, Imre & Bojnec, Stefan, 2015. "Quality upgrading in the European-Union agri-food exports," 89th Annual Conference, April 13-15, 2015, Warwick University, Coventry, UK 204225, Agricultural Economics Society.
• Witajewski-Baltvilks, Jan & Verdolini, Elena & Tavoni, Massimo, 2015. "Bending the learning curve," Energy Economics, Elsevier, vol. 52(S1), pages 86-99.
  • Jan Witajewski-Baltvilks & Elena Verdolini & Massimo Tavoni, 2015. "Bending The Learning Curve," Working Papers 2015.65, Fondazione Eni Enrico Mattei.
  • Witajewski-Baltvilks, Jan & Verdolini, Elena & Tavoni, Massimo, 2015. "Bending The Learning Curve," Climate Change and Sustainable Development 206836, Fondazione Eni Enrico Mattei (FEEM).
• Hristov, Jordan, 2015. "An exploratory analysis of the impact of climate change on Macedonian agriculture," 2015 Conference, August 9-14, 2015, Milan, Italy 211747, International Association of Agricultural Economists.
• Louhichi, Kamel & Ciaian, Pavel & Espinosa, Maria & Colen, Liesbeth & Perni, Angel & Gomez y Paloma, Sergio, 2015. "EU-wide individual Farm Model for CAP Analysis (IFM-CAP): Application to Crop Diversification Policy," 2015 Conference, August 9-14, 2015, Milan, Italy 212155, International Association of Agricultural Economists.
• Martinez, Pilar & Blanco, Maria & Van Doorslaer, Benjamin & Ramos, Fabien & Stanca, Lucian, 2015. "What role does climate change play in agricultural market uncertainty? An integrated assessment taking into account market-driven adjustments," 2015 Conference, August 9-14, 2015, Milan, Italy 212230, International Association of Agricultural Economists.
• Ibrahim Onur Oz & Tezer Yelkenci, 2015. "The Generalizability of Financial Distress Prediction Models: Evidence from Turkey," Journal of Accounting and Management Information Systems, Faculty of Accounting and Management Information Systems, The Bucharest University of Economic Studies, vol. 14(4), pages 685-703, December.
• Aysun Kapucugil İkiz & Güzin Özdağoğlu, 2015. "Text Mining as a Supporting Process for VoC Clarification," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 3(1), pages 25-40, June.
• Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Valid Post-Selection and Post-Regularization Inference: An Elementary, General Approach," Annual Review of Economics, Annual Reviews, vol. 7(1), pages 649-688, August.
  • Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Valid Post-Selection and Post-Regularization Inference: An Elementary, General Approach," Papers 1501.03430, arXiv.org, revised Aug 2015.
  • Victor Chernozhukov & Christian Hansen & Martin Spindler, 2016. "Valid post-selection and post-regularization inference: An elementary, general approach," CeMMAP working papers 36/16, Institute for Fiscal Studies.
  • Victor Chernozhukov & Christian Hansen & Martin Spindler, 2016. "Valid post-selection and post-regularization inference: An elementary, general approach," CeMMAP working papers CWP36/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
• Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Valid Post-Selection and Post-Regularization Inference: An Elementary, General Approach," Annual Review of Economics, Annual Reviews, vol. 7(1), pages 649-688, August.
  • Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Valid Post-Selection and Post-Regularization Inference: An Elementary, General Approach," Papers 1501.03430, arXiv.org, revised Aug 2015.
  • Victor Chernozhukov & Christian Hansen & Martin Spindler, 2016. "Valid post-selection and post-regularization inference: An elementary, general approach," CeMMAP working papers 36/16, Institute for Fiscal Studies.
  • Victor Chernozhukov & Christian Hansen & Martin Spindler, 2016. "Valid post-selection and post-regularization inference: An elementary, general approach," CeMMAP working papers CWP36/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
• Raphael Douady & Antoine Kornprobst, 2018. "An Empirical Approach To Financial Crisis Indicators Based On Random Matrices," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 21(03), pages 1-22, May.
  • Antoine Kornprobst & Raphael Douady, 2015. "An Empirical Approach to Financial Crisis Indicators Based on Random Matrices," Papers 1506.00806, arXiv.org, revised Sep 2017.
  • Raphaël Douady & Antoine Kornprobst, 2018. "An empirical approach to financial crisis indicators based on random matrices," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-03265045, HAL.
  • Raphaël Douady & Antoine Kornprobst, 2018. "An empirical approach to financial crisis indicators based on random matrices," Post-Print hal-03265045, HAL.
• Mumtaz Hussain Shah & Anum Gul Afridi, 2015. "Significance of Good Governance for FDI Inflows in SAARC Countries," Business & Economic Review, Institute of Management Sciences, Peshawar, Pakistan, vol. 7(2), pages 31-52, October.
• Charles Rahal, 2015. "Housing Market Forecasting with Factor Combinations," Discussion Papers 15-05, Department of Economics, University of Birmingham.
• Charles Rahal, 2015. "Housing Market Forecasting with Factor Combinations," Discussion Papers 15-05r, Department of Economics, University of Birmingham.
• Bjørnland, Hilde C. & Ravazzolo, Francesco & Thorsrud, Leif Anders, 2017. "Forecasting GDP with global components: This time is different," International Journal of Forecasting, Elsevier, vol. 33(1), pages 153-173.
  • Hilde C. Bjørnland & Francesco Ravazzolo & Leif Anders Thorsrud, 2015. "Forecasting GDP with global components. This time is different," Working Paper 2015/05, Norges Bank.
  • Hilde C. Bjornland & Francesco Ravazzolo & Leif Anders Thorsrud, 2016. "Forecasting GDP with global components. This time is different," CAMA Working Papers 2016-26, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Claudia Foroni & Francesco Ravazzolo & Pinho J. Ribeiro, 2015. "Forecasting commodity currencies: the role of fundamentals with short-lived predictive content," Working Paper 2015/14, Norges Bank.
• Bjørnland, Hilde C. & Ravazzolo, Francesco & Thorsrud, Leif Anders, 2017. "Forecasting GDP with global components: This time is different," International Journal of Forecasting, Elsevier, vol. 33(1), pages 153-173.
  • Hilde C. Bjørnland & Francesco Ravazzolo & Leif Anders Thorsrud, 2015. "Forecasting GDP with global components. This time is different," Working Paper 2015/05, Norges Bank.
  • Hilde C. Bjørnland & Francesco Ravazzolo & Leif Anders Thorsrud, 2015. "Forecasting GDP with global components. This time is different," Working Papers No 1/2015, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • Hilde C. Bjornland & Francesco Ravazzolo & Leif Anders Thorsrud, 2016. "Forecasting GDP with global components. This time is different," CAMA Working Papers 2016-26, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• David Bholat & Stephen Hans & Pedro Santos & Cheryl Schonhardt-Bailey, 2015. "Text mining for central banks," Handbooks, Centre for Central Banking Studies, Bank of England, number 33, April.
• Jeremiah Dittmar & Skipper Seabold, 2015. "Media, Markets and Institutional Change: Evidence from the Protestant Reformation," CEP Discussion Papers dp1367, Centre for Economic Performance, LSE.
• Dong, Zhengbin & Wu, Wenjie, 2015. "Exploring the geography of China's airport networks: a hybrid complex-network approach," LSE Research Online Documents on Economics 64508, London School of Economics and Political Science, LSE Library.
  • Zhengbin Dong & Wenjie Wu, 2015. "Exploring the Geography of China's Airport Networks: A Hybrid Complex-Network Approach," SERC Discussion Papers 0173, Centre for Economic Performance, LSE.
• Berg Tim Oliver, 2017. "Forecast accuracy of a BVAR under alternative specifications of the zero lower bound," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(2), pages 1-29, April.
  • Tim Oliver Berg, 2015. "Forecast Accuracy of a BVAR under Alternative Specifications of the Zero Lower Bound," ifo Working Paper Series 203, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
• Pedro S. Martins, 2015. "Working to get fired? Regression discontinuity effects of unemployment benefit eligibility on prior employment duration," Working Papers 61, Queen Mary, University of London, School of Business and Management, Centre for Globalisation Research.
  • Martins, Pedro S., 2016. "Working to Get Fired? Regression Discontinuity Effects of Unemployment Benefit Eligibility on Prior Employment Duration," IZA Discussion Papers 10262, Institute of Labor Economics (IZA).
• Gheorghe MILITARU & Massimo POLLIFRONI & Alexandra IOANID, 2015. "Big Data In Supply Chain Management: An Exploratory Study," Network Intelligence Studies, Romanian Foundation for Business Intelligence, Editorial Department, issue 6, pages 103-108, December.
• Gustavo Nicolás Páez, 2015. "Prediciendo decisiones de agentes económicos: ¿Cómo determina el Banco de la República de Colombia la tasa de interés?," Documentos CEDE 12567, Universidad de los Andes, Facultad de Economía, CEDE.
• Christian Hutter & Joachim Möller & Marion Penninger, 2015. "Reducing the Need for Heuristic Rules - An Iterative Algorithm for Imputing the Education Variable in SIAB," Schmollers Jahrbuch : Journal of Applied Social Science Studies / Zeitschrift für Wirtschafts- und Sozialwissenschaften, Duncker & Humblot, Berlin, vol. 135(3), pages 355-388.
• Kutluk Kaðan SÜMER, 2015. "Effectiveness of technical analysis indicators over stock return: A Panel Data Approach," Eurasian Eononometrics, Statistics and Emprical Economics Journal, Eurasian Academy Of Sciences, vol. 1(1), pages 43-56, April.
• Christopoulos, Dimitris K. & McAdam, Peter, 2019. "Efficiency, Inefficiency, And The Mena Frontier," Macroeconomic Dynamics, Cambridge University Press, vol. 23(2), pages 489-521, March.
  • Cristiano Cantore & Peter Paul Levine & Giovanni Melina & Joseph Pearlman, 2015. "Optimal Fiscal and Monetary Policy, Debt and Crisis Management," School of Economics Discussion Papers 0515, School of Economics, University of Surrey.
  • McAdam, Peter & Christopoulos, Dimitris, 2015. "Efficiency, Inefficiency and the MENA Frontier," Working Paper Series 1757, European Central Bank.
• Edward L. Glaeser & Scott Duke Kominers & Michael Luca & Nikhil Naik, 2018. "Big Data And Big Cities: The Promises And Limitations Of Improved Measures Of Urban Life," Economic Inquiry, Western Economic Association International, vol. 56(1), pages 114-137, January.
  • Edward L. Glaeser & Scott Duke Kominers & Michael Luca & Nikhil Naik, 2015. "Big Data and Big Cities: The Promises and Limitations of Improved Measures of Urban Life," NBER Working Papers 21778, National Bureau of Economic Research, Inc.
  • Glaeser, Edward L. & Kominers, Scott Duke & Luca, Michael & Naik, Nikhil, 2015. "Big Data and Big Cities: The Promises and Limitations of Improved Measures for Urban Life," Working Paper Series 15-075, Harvard University, John F. Kennedy School of Government.
  • Edward L. Glaeser & Scott Duke Kominers & Michael Luca & Nikhil Naik, 2015. "Big Data and Big Cities: The Promises and Limitations of Improved Measures of Urban Life," Harvard Business School Working Papers 16-065, Harvard Business School.
• Breitung, Jörg & Eickmeier, Sandra, 2015. "Analyzing business cycle asymmetries in a multi-level factor model," Economics Letters, Elsevier, vol. 127(C), pages 31-34.
• Chang, Chia-Lin & McAleer, Michael, 2015. "Econometric analysis of financial derivatives: An overview," Journal of Econometrics, Elsevier, vol. 187(2), pages 403-407.
  • Chia-Lin Chang & Michael McAleer, 2014. "Econometric Analysis of Financial Derivatives: An Overview," Tinbergen Institute Discussion Papers 14-153/III, Tinbergen Institute.
  • Chia-Lin Chang & Michael McAleer, 2014. "Econometric Analysis of Financial Derivatives: An Overview," Documentos de Trabajo del ICAE 2014-31, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
  • Chia-Lin Chang & Michael McAleer, 2014. "Econometric Analysis of Financial Derivatives: An Overview," Working Papers in Economics 14/29, University of Canterbury, Department of Economics and Finance.
• Castelli, Mauro & Vanneschi, Leonardo & De Felice, Matteo, 2015. "Forecasting short-term electricity consumption using a semantics-based genetic programming framework: The South Italy case," Energy Economics, Elsevier, vol. 47(C), pages 37-41.
• Witajewski-Baltvilks, Jan & Verdolini, Elena & Tavoni, Massimo, 2015. "Bending the learning curve," Energy Economics, Elsevier, vol. 52(S1), pages 86-99.
  • Jan Witajewski-Baltvilks & Elena Verdolini & Massimo Tavoni, 2015. "Bending The Learning Curve," Working Papers 2015.65, Fondazione Eni Enrico Mattei.
  • Witajewski-Baltvilks, Jan & Verdolini, Elena & Tavoni, Massimo, 2015. "Bending The Learning Curve," Climate Change and Sustainable Development 206836, Fondazione Eni Enrico Mattei (FEEM).
• Mittnik, Stefan & Robinzonov, Nikolay & Spindler, Martin, 2015. "Stock market volatility: Identifying major drivers and the nature of their impact," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 1-14.
• Nathan, Max & Rosso, Anna, 2015. "Mapping digital businesses with big data: Some early findings from the UK," Research Policy, Elsevier, vol. 44(9), pages 1714-1733.
  • Nathan, Max & Rosso, Anna, 2015. "Mapping digital businesses with big data: some early findings from the UK," LSE Research Online Documents on Economics 65211, London School of Economics and Political Science, LSE Library.
• Chia-Lin Chang & Michael McAleer, 2015. "Research Ideas for the Journal of Health & Medical Economics: Opinion," Documentos de Trabajo del ICAE 2015-12, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
  • Chang, C-L. & McAleer, M.J., 2015. "Research Ideas for the Journal of Health & Medical Economics: Opinion," Econometric Institute Research Papers EI2015-25, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
• Michael McAleer, 2015. "Research Ideas for the Journal of Informatics and Data Mining: Opinion," Documentos de Trabajo del ICAE 2015-13, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
  • McAleer, M.J., 2015. "Research Ideas for the Journal of Informatics and Data Mining: Opinion," Econometric Institute Research Papers EI2015-26, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
• Ogura, Yoshiaki & Okui, Ryo & Saito, Yukiko Umeno, 2015. "Network-Motivated Lending Decisions," HIT-REFINED Working Paper Series 29, Institute of Economic Research, Hitotsubashi University.
  • OGURA Yoshiaki & OKUI Ryo & SAITO Yukiko, 2015. "Network-motivated Lending Decisions," Discussion papers 15057, Research Institute of Economy, Trade and Industry (RIETI).
• Witajewski-Baltvilks, Jan & Verdolini, Elena & Tavoni, Massimo, 2015. "Bending the learning curve," Energy Economics, Elsevier, vol. 52(S1), pages 86-99.
  • Witajewski-Baltvilks, Jan & Verdolini, Elena & Tavoni, Massimo, 2015. "Bending The Learning Curve," Climate Change and Sustainable Development 206836, Fondazione Eni Enrico Mattei (FEEM).
  • Jan Witajewski-Baltvilks & Elena Verdolini & Massimo Tavoni, 2015. "Bending The Learning Curve," Working Papers 2015.65, Fondazione Eni Enrico Mattei.
• Whitaker, Stephan D., 2018. "Big Data versus a survey," The Quarterly Review of Economics and Finance, Elsevier, vol. 67(C), pages 285-296.
  • Stephan D. Whitaker, 2015. "Big Data versus a Survey," Working Papers (Old Series) 1440, Federal Reserve Bank of Cleveland.
• Alessandro Barbarino & Efstathia Bura, 2015. "Forecasting with Sufficient Dimension Reductions," Finance and Economics Discussion Series 2015-74, Board of Governors of the Federal Reserve System (U.S.).
• Stephanie M. Wilshusen, 2015. "Exploring the use of anonymized consumer credit information to estimate economic conditions: an application of big data," Consumer Finance Institute discussion papers 15-5, Federal Reserve Bank of Philadelphia.
• António Alberto Santos, 2015. "The evolution of the Volatility in Financial Returns: Realized Volatility vs Stochastic Volatility Measures," GEMF Working Papers 2015-10, GEMF, Faculty of Economics, University of Coimbra.
• António Alberto Santos, 2015. "The evolution of the Volatility in Financial Returns: Realized Volatility vs Stochastic Volatility Measures," GEMF Working Papers 2015-10, GEMF, Faculty of Economics, University of Coimbra.
• António A. F. Santos, 2015. "On the Forecasting of Financial Volatility Using Ultra-High Frequency Data," GEMF Working Papers 2015-17, GEMF, Faculty of Economics, University of Coimbra.
• António A. F. Santos, 2015. "On the Forecasting of Financial Volatility Using Ultra-High Frequency Data," GEMF Working Papers 2015-17, GEMF, Faculty of Economics, University of Coimbra.
• Catherine Doz & Anna Petronevich, 2016. "Dating Business Cycle Turning Points for the French Economy: An MS-DFM approach," Advances in Econometrics, in: Dynamic Factor Models, volume 35, pages 481-538, Emerald Group Publishing Limited.
  • Catherine Doz & Anna Petronevich, 2015. "Dating Business Cycle Turning Points for the French Economy: a MS-DFM approach," Post-Print hal-01159200, HAL.
  • Catherine Doz & Anna Petronevich, 2015. "Dating Business Cycle Turning Points for the French Economy: a MS-DFM approach," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01159200, HAL.
  • Catherine Doz & Anna Petronevich, 2015. "Dating Business Cycle Turning Points for the French Economy: a MS-DFM approach," Documents de travail du Centre d'Economie de la Sorbonne 15009, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
• Antoine Kornprobst & Raphaël Douady, 2015. "A Pratical Approach to Financial Crisis Indicators Based on Random Matrices," Post-Print halshs-01169307, HAL.
  • Antoine Kornprobst & Raphaël Douady, 2015. "A Pratical Approach to Financial Crisis Indicators Based on Random Matrices," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01169307, HAL.
  • Antoine Kornprobst & Raphael Douady, 2015. "A Practical Approach to Financial Crisis Indicators Based on Random Matrices," Documents de travail du Centre d'Economie de la Sorbonne 15049, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
• Catherine Doz & Anna Petronevich, 2016. "Dating Business Cycle Turning Points for the French Economy: An MS-DFM approach," Advances in Econometrics, in: Dynamic Factor Models, volume 35, pages 481-538, Emerald Group Publishing Limited.
  • Catherine Doz & Anna Petronevich, 2015. "Dating Business Cycle Turning Points for the French Economy: a MS-DFM approach," Documents de travail du Centre d'Economie de la Sorbonne 15009, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
  • Catherine Doz & Anna Petronevich, 2015. "Dating Business Cycle Turning Points for the French Economy: a MS-DFM approach," Post-Print hal-01159200, HAL.
  • Catherine Doz & Anna Petronevich, 2015. "Dating Business Cycle Turning Points for the French Economy: a MS-DFM approach," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01159200, HAL.
• Antoine Kornprobst & Raphaël Douady, 2015. "A Pratical Approach to Financial Crisis Indicators Based on Random Matrices," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01169307, HAL.
  • Antoine Kornprobst & Raphaël Douady, 2015. "A Pratical Approach to Financial Crisis Indicators Based on Random Matrices," Post-Print halshs-01169307, HAL.
  • Antoine Kornprobst & Raphael Douady, 2015. "A Practical Approach to Financial Crisis Indicators Based on Random Matrices," Documents de travail du Centre d'Economie de la Sorbonne 15049, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
• Edward L. Glaeser & Scott Duke Kominers & Michael Luca & Nikhil Naik, 2018. "Big Data And Big Cities: The Promises And Limitations Of Improved Measures Of Urban Life," Economic Inquiry, Western Economic Association International, vol. 56(1), pages 114-137, January.
  • Edward L. Glaeser & Scott Duke Kominers & Michael Luca & Nikhil Naik, 2015. "Big Data and Big Cities: The Promises and Limitations of Improved Measures of Urban Life," NBER Working Papers 21778, National Bureau of Economic Research, Inc.
  • Edward L. Glaeser & Scott Duke Kominers & Michael Luca & Nikhil Naik, 2015. "Big Data and Big Cities: The Promises and Limitations of Improved Measures of Urban Life," Harvard Business School Working Papers 16-065, Harvard Business School.
  • Glaeser, Edward L. & Kominers, Scott Duke & Luca, Michael & Naik, Nikhil, 2015. "Big Data and Big Cities: The Promises and Limitations of Improved Measures for Urban Life," Working Paper Series 15-075, Harvard University, John F. Kennedy School of Government.
• Matias Quiroz & Robert Kohn & Mattias Villani & Minh-Ngoc Tran, 2019. "Speeding Up MCMC by Efficient Data Subsampling," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 114(526), pages 831-843, April.
  • Quiroz, Matias & Villani, Mattias & Kohn, Robert, 2015. "Speeding Up Mcmc By Efficient Data Subsampling," Working Paper Series 297, Sveriges Riksbank (Central Bank of Sweden).
  • Kohn, Robert & Quiroz, Matias & Tran, Minh-Ngoc & Villani, Mattias, 2016. "Speeding up MCMC by Efficient Data Subsampling," Working Papers 2123/16205, University of Sydney Business School, Discipline of Business Analytics.
• Quiroz, Matias & Villani, Mattias & Kohn, Robert, 2015. "Scalable Mcmc For Large Data Problems Using Data Subsampling And The Difference Estimator," Working Paper Series 306, Sveriges Riksbank (Central Bank of Sweden).
• Quiroz, Matias, 2015. "Speeding Up Mcmc By Delayed Acceptance And Data Subsampling," Working Paper Series 307, Sveriges Riksbank (Central Bank of Sweden).
• OGURA Yoshiaki & OKUI Ryo & SAITO Yukiko, 2015. "Network-motivated Lending Decisions," Discussion papers 15057, Research Institute of Economy, Trade and Industry (RIETI).
  • Ogura, Yoshiaki & Okui, Ryo & Saito, Yukiko Umeno, 2015. "Network-Motivated Lending Decisions," HIT-REFINED Working Paper Series 29, Institute of Economic Research, Hitotsubashi University.
• Hoxby, Caroline M. & Bulman, George B., 2016. "The effects of the tax deduction for postsecondary tuition: Implications for structuring tax-based aid," Economics of Education Review, Elsevier, vol. 51(C), pages 23-60.
  • Caroline M. Hoxby & George B. Bulman, 2015. "The Effects of the Tax Deduction for Postsecondary Tuition: Implications for Structuring Tax-Based Aid," NBER Working Papers 21554, National Bureau of Economic Research, Inc.
  • Caroline M. Hoxby & George B. Bulman, 2015. "The Effects of the Tax Deduction for Postsecondary Tuition: Implications for Structuring Tax-Based Aid," Economics Working Papers 15114, Hoover Institution, Stanford University.
• Shih-Kang Chao & Wolfgang K. Härdle & Ming Yuan, 2015. "Factorisable Sparse Tail Event Curves," SFB 649 Discussion Papers SFB649DP2015-034, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
• Koomen, Miriam & Backes-Gellner, Uschi, 2022. "Occupational tasks and wage inequality in West Germany: A decomposition analysis," Labour Economics, Elsevier, vol. 79(C).
  • Rinawi, Miriam & Backes-Gellner, Uschi, 2015. "Occupational Skills and the Evolution of Wages," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112801, Verein für Socialpolitik / German Economic Association.
  • Miriam Koomen & Uschi Backes-Gellner, 2015. "Occupational Tasks and Wage Inequality in West Germany: A Decomposition Analysis," Economics of Education Working Paper Series 0112, University of Zurich, Department of Business Administration (IBW), revised Oct 2022.
• John P. Robinson & Elena Tracy & Yoonjoo Lee, 2015. "Cruising through the millennium - 2003-13 changes in American Daily life," electronic International Journal of Time Use Research, Research Institute on Professions (Forschungsinstitut Freie Berufe (FFB)) and The International Association for Time Use Research (IATUR), vol. 12(1), pages 133-152, December.
• Montero, José-María & Fernández-Avilés, Gema, 2015. "Functional Kriging Prediction of Pollution Series: The Geostatistical Alternative for Spatially-fixed Data/Predicción de series de contaminación mediante kriging funcional. La alternativa geoestadísti," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 33, pages 145-179, Enero.
• Angers, Jean-François & Desjardins, Denise & Dionne, Georges & Guertin, François, 2018. "Modelling And Estimating Individual And Firm Effects With Count Panel Data," ASTIN Bulletin, Cambridge University Press, vol. 48(3), pages 1049-1078, September.
  • Jean-François Angers & Denise Desjardins & Georges Dionne & François Guertin, 2015. "Modelling and Estimating Individual and Firm Effects with Count Panel Data," Cahiers de recherche 1506, CIRPEE.
  • Angers, Jean-François & Desjardins, Denise & Dionne, Georges & Guertin, François, 2018. "Modelling and Estimating Individual and Firm Effects with Count Panel Data," Working Papers 15-2, HEC Montreal, Canada Research Chair in Risk Management.
• Catherine Doz & Anna Petronevich, 2016. "Dating Business Cycle Turning Points for the French Economy: An MS-DFM approach," Advances in Econometrics, in: Dynamic Factor Models, volume 35, pages 481-538, Emerald Group Publishing Limited.
  • Catherine Doz & Anna Petronevich, 2015. "Dating Business Cycle Turning Points for the French Economy: a MS-DFM approach," Post-Print hal-01159200, HAL.
  • Catherine Doz & Anna Petronevich, 2015. "Dating Business Cycle Turning Points for the French Economy: a MS-DFM approach," Documents de travail du Centre d'Economie de la Sorbonne 15009, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
  • Catherine Doz & Anna Petronevich, 2015. "Dating Business Cycle Turning Points for the French Economy: a MS-DFM approach," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01159200, HAL.
• Antoine Kornprobst & Raphaël Douady, 2015. "A Pratical Approach to Financial Crisis Indicators Based on Random Matrices," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01169307, HAL.
  • Antoine Kornprobst & Raphael Douady, 2015. "A Practical Approach to Financial Crisis Indicators Based on Random Matrices," Documents de travail du Centre d'Economie de la Sorbonne 15049, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
  • Antoine Kornprobst & Raphaël Douady, 2015. "A Pratical Approach to Financial Crisis Indicators Based on Random Matrices," Post-Print halshs-01169307, HAL.
• Aleksandra Halka & Grzegorz Szafranski, 2018. "What Common Factors are Driving Inflation in CEE Countries?," Prague Economic Papers, Prague University of Economics and Business, vol. 2018(2), pages 131-148.
  • Aleksandra Halka & Grzegorz Szafrański, 2014. "What common factors are driving inflation in CEE countries?," EcoMod2014 6977, EcoMod.
  • Aleksandra Hałka & Grzegorz Szafrański, 2015. "What common factors are driving inflation in CEE countries?," NBP Working Papers 225, Narodowy Bank Polski.
• Patrick Bajari & Denis Nekipelov & Stephen P. Ryan & Miaoyu Yang, 2015. "Demand Estimation with Machine Learning and Model Combination," NBER Working Papers 20955, National Bureau of Economic Research, Inc.
• Carlos A. Manzanares & Ying Jiang & Patrick Bajari, 2015. "Improving Policy Functions in High-Dimensional Dynamic Games," NBER Working Papers 21124, National Bureau of Economic Research, Inc.
• Hoxby, Caroline M. & Bulman, George B., 2016. "The effects of the tax deduction for postsecondary tuition: Implications for structuring tax-based aid," Economics of Education Review, Elsevier, vol. 51(C), pages 23-60.
  • Caroline M. Hoxby & George B. Bulman, 2015. "The Effects of the Tax Deduction for Postsecondary Tuition: Implications for Structuring Tax-Based Aid," Economics Working Papers 15114, Hoover Institution, Stanford University.
  • Caroline M. Hoxby & George B. Bulman, 2015. "The Effects of the Tax Deduction for Postsecondary Tuition: Implications for Structuring Tax-Based Aid," NBER Working Papers 21554, National Bureau of Economic Research, Inc.
• Yacine Aït-Sahalia & Dacheng Xiu, 2019. "Principal Component Analysis of High-Frequency Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 114(525), pages 287-303, January.
  • Yacine Aït-Sahalia & Dacheng Xiu, 2015. "Principal Component Analysis of High Frequency Data," NBER Working Papers 21584, National Bureau of Economic Research, Inc.
• Edward L. Glaeser & Scott Duke Kominers & Michael Luca & Nikhil Naik, 2018. "Big Data And Big Cities: The Promises And Limitations Of Improved Measures Of Urban Life," Economic Inquiry, Western Economic Association International, vol. 56(1), pages 114-137, January.
  • Edward L. Glaeser & Scott Duke Kominers & Michael Luca & Nikhil Naik, 2015. "Big Data and Big Cities: The Promises and Limitations of Improved Measures of Urban Life," Harvard Business School Working Papers 16-065, Harvard Business School.
  • Edward L. Glaeser & Scott Duke Kominers & Michael Luca & Nikhil Naik, 2015. "Big Data and Big Cities: The Promises and Limitations of Improved Measures of Urban Life," NBER Working Papers 21778, National Bureau of Economic Research, Inc.
  • Glaeser, Edward L. & Kominers, Scott Duke & Luca, Michael & Naik, Nikhil, 2015. "Big Data and Big Cities: The Promises and Limitations of Improved Measures for Urban Life," Working Paper Series 15-075, Harvard University, John F. Kennedy School of Government.
• Lenarčič, Črt & Damjanović, Milan, 2015. "Slovene Residential Property Prices Misalignment with Fundamentals," MPRA Paper 101198, University Library of Munich, Germany.
• Byambasuren, Tsenguunjav & Gochoo, Munkh-Erdene, 2015. "Optimizing the Structure of Mongolian Foreign Trade and the Alternative Policy of Successful Transition," MPRA Paper 61803, University Library of Munich, Germany.
• Tim Oliver Berg, 2016. "Multivariate Forecasting with BVARs and DSGE Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(8), pages 718-740, December.
  • Berg, Tim Oliver, 2015. "Multivariate Forecasting with BVARs and DSGE Models," MPRA Paper 62405, University Library of Munich, Germany.
• Situngkir, Hokky, 2015. "Indonesia embraces the Data Science," MPRA Paper 66048, University Library of Munich, Germany.
• Ben Jebli, Mehdi, 2015. "The Impact of Combustible Renewables and Waste Consumption and Transport on the Environmental Degradation: The Case of Tunisia," MPRA Paper 68038, University Library of Munich, Germany.
• Kausik Gangopadhyay & Abhishek Jangir & Rudra Sensarma, 2014. "Forecasting the price of gold: An error correction approach," Working papers 155, Indian Institute of Management Kozhikode.
  • Gangopadhyay, Kausik & Jangir, Abhishek & Sensarma, Rudra, 2015. "Forecasting the price of gold: An error correction approach," MPRA Paper 81066, University Library of Munich, Germany.
• Braaksma, Barteld & Zeelenberg, Kees, 2015. "“Re-make/Re-model”: Should big data change the modelling paradigm in official statistics?," MPRA Paper 87741, University Library of Munich, Germany.
• Rangan Gupta & Eric Olson & Mark E. Wohar, 2017. "Forecasting key US macroeconomic variables with a factor‐augmented Qual VAR," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(6), pages 640-650, September.
  • Rangan Gupta & Eric Olson & Mark E. Wohar, 2015. "Forecasting Key US Macroeconomic Variables with a Factor-Augmented Qual VAR," Working Papers 201585, University of Pretoria, Department of Economics.
• Gupta, Rangan & Wohar, Mark, 2017. "Forecasting oil and stock returns with a Qual VAR using over 150years off data," Energy Economics, Elsevier, vol. 62(C), pages 181-186.
  • Rangan Gupta & Mark E. Wohar, 2015. "Forecasting Oil and Stock Returns with a Qual VAR using over 150 Years of Data," Working Papers 201589, University of Pretoria, Department of Economics.
• Chris Godfrey & Chris Brooks, 2015. "The Negative Credit Risk Premium Puzzle: A Limits to Arbitrage Story," ICMA Centre Discussion Papers in Finance icma-dp2015-07, Henley Business School, University of Reading.
• Mao Takongmo, Charles Olivier & Stevanovic, Dalibor, 2015. "Selection Of The Number Of Factors In Presence Of Structural Instability: A Monte Carlo Study," L'Actualité Economique, Société Canadienne de Science Economique, vol. 91(1-2), pages 177-233, Mars-Juin.
  • Dalibor Stevanovic & Charles Olivier Mao Takongmo, 2014. "Selection of the number of factors in presence of structural instability: a Monte Carlo study," CIRANO Working Papers 2014s-44, CIRANO.
• Francesco Lautizi, 2015. "Large Scale Covariance Estimates for Portfolio Selection," CEIS Research Paper 353, Tor Vergata University, CEIS, revised 07 Aug 2015.
• Ülle Säälik, 2015. "Reading performance, learning strategies, gender and school language as related issues ? PISA 2009 findings in Finland and Estonia," Proceedings of International Academic Conferences 1003055, International Institute of Social and Economic Sciences.
• Ülle Säälik, 2015. "Reading performance, learning strategies, gender and school language as related issues ? PISA 2009 findings in Finland and Estonia," International Journal of Teaching and Education, International Institute of Social and Economic Sciences, vol. 3(2), pages 17-30, June.
• Michał Bernardelli, 2015. "Cheater detection in Real Time Bidding system – panel approach," Collegium of Economic Analysis Annals, Warsaw School of Economics, Collegium of Economic Analysis, issue 39, pages 11-24.
• Luke Hartigan, 2015. "Changes in the Factor Structure of the U.S. Economy: Permanent Breaks or Business Cycle Regimes?," Discussion Papers 2015-17, School of Economics, The University of New South Wales.
• Thomas Peeters & Steven Salaga & Matthew Juravich, 2015. "Matching and Winning? The Impact of Upper and Middle Managers on Team Performance in Major League Baseball," Tinbergen Institute Discussion Papers 15-115/VII, Tinbergen Institute, revised 03 Mar 2020.
• Chang, C-L. & McAleer, M.J., 2015. "Research Ideas for the Journal of Health & Medical Economics: Opinion," Econometric Institute Research Papers EI2015-25, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  • Chia-Lin Chang & Michael McAleer, 2015. "Research Ideas for the Journal of Health & Medical Economics: Opinion," Documentos de Trabajo del ICAE 2015-12, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
• McAleer, M.J., 2015. "Research Ideas for the Journal of Informatics and Data Mining: Opinion," Econometric Institute Research Papers EI2015-26, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  • Michael McAleer, 2015. "Research Ideas for the Journal of Informatics and Data Mining: Opinion," Documentos de Trabajo del ICAE 2015-13, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
• Sylvain Barde, 2015. "A fast algorithm for finding the confidence set of large collections of models," Studies in Economics 1519, School of Economics, University of Kent.
• Ronald Miranda & Gabriela Mordecki, 2015. "Real exchange rate volatility impact on exports: A comparative study 1990-2013," Documentos de Trabajo (working papers) 15-18, Instituto de Economía - IECON.
• Chiara Elena Dalla & Menon Martina & Perali Federico, 2019. "An Integrated Database to Measure Living Standards," Journal of Official Statistics, Sciendo, vol. 35(3), pages 531-576, September.
  • Elena Dalla Chiara & Martina Menon & Federico Perali, 2015. "An Integrated Data Base to Measure Living Standards," Working Papers 28/2015, University of Verona, Department of Economics.
• Taro Takimoto & Kazuya Sakata & Kazunori Nakajima & Masaki Narukawa & Naoki Sakamoto, 2015. "Disparity in emergency medical services across Japan," ERSA conference papers ersa15p526, European Regional Science Association.
• Wenjie Wu & Jianghao Wang, 2015. "Exploring city social interaction ties in the big data era: Evidence based on location-based social media data from China," ERSA conference papers ersa15p798, European Regional Science Association.
• Crespo Cuaresma, Jesus & Grün, Bettina & Hofmarcher, Paul & Humer, Stefan & Moser, Mathias, 2015. "A Comprehensive Approach to Posterior Jointness Analysis in Bayesian Model Averaging Applications," Department of Economics Working Paper Series 193, WU Vienna University of Economics and Business.
  • Jesus Crespo Cuaresma & Bettina Grün & Paul Hofmarcher & Stefan Humer & Mathias Moser, 2015. "A Comprehensive Approach to Posterior Jointness Analysis in Bayesian Model Averaging Applications," Department of Economics Working Papers wuwp193, Vienna University of Economics and Business, Department of Economics.
• Jesus Crespo Cuaresma & Bettina Grün & Paul Hofmarcher & Stefan Humer & Mathias Moser, 2015. "A Comprehensive Approach to Posterior Jointness Analysis in Bayesian Model Averaging Applications," Department of Economics Working Papers wuwp193, Vienna University of Economics and Business, Department of Economics.
  • Crespo Cuaresma, Jesus & Grün, Bettina & Hofmarcher, Paul & Humer, Stefan & Moser, Mathias, 2015. "A Comprehensive Approach to Posterior Jointness Analysis in Bayesian Model Averaging Applications," Department of Economics Working Paper Series 193, WU Vienna University of Economics and Business.
• Adam Nowak & Patrick Smith, 2015. "Textual Analysis in Real Estate," Working Papers 15-34, Department of Economics, West Virginia University.
• Chao, Shih-Kang & Härdle, Wolfgang Karl & Yuan, Ming, 2015. "Factorisable sparse tail event curves," SFB 649 Discussion Papers 2015-034, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
• Köhler, Ekkehard, 2015. "Fiscal Sustainability in Cross-Dependent Panels: Evidence from the German L nder," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113104, Verein für Socialpolitik / German Economic Association.
• Damian Kozbur, 2017. "Testing-Based Forward Model Selection," American Economic Review, American Economic Association, vol. 107(5), pages 266-269, May.
  • Damian Kozbur, 2015. "Testing-Based Forward Model Selection," ECON - Working Papers 283, Department of Economics - University of Zurich, revised Apr 2018.

2014

• Anders Bredahl Kock & Haihan Tang, 2014. "Inference in High-dimensional Dynamic Panel Data Models," CREATES Research Papers 2014-58, Department of Economics and Business Economics, Aarhus University.
• Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2014. "High-Dimensional Methods and Inference on Structural and Treatment Effects," Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 29-50, Spring.
  • Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2013. "High dimensional methods and inference on structural and treatment effects," CeMMAP working papers CWP59/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2013. "High dimensional methods and inference on structural and treatment effects," CeMMAP working papers 59/13, Institute for Fiscal Studies.
• Hal R. Varian, 2014. "Big Data: New Tricks for Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 3-28, Spring.
• David W. Nickerson & Todd Rogers, 2014. "Political Campaigns and Big Data," Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 51-74, Spring.
• Ori Heffetz & Katrina Ligett, 2014. "Privacy and Data-Based Research," Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 75-98, Spring.
  • Ori Heffetz & Katrina Ligett, 2013. "Privacy and Data-Based Research," NBER Working Papers 19433, National Bureau of Economic Research, Inc.
• Cooper, Joseph & Delbecq, Benoît, 2014. "A multi-region approach to assessing fiscal and farm level consequences of government support for farm risk management," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), vol. 3(3), pages 1-23, December.
  • Cooper, Joseph & Delbecq, Benoit, 2014. "A Multi-Region Approach to Assessing Fiscal and Farm Level Consequences of Government Support for Farm Risk Management," 2014 Third Congress, June 25-27, 2014, Alghero, Italy 173108, Italian Association of Agricultural and Applied Economics (AIEAA).
• Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2014. "Forecasting the Oil-gasoline Price Relationship: Should We Care about the Rockets and the Feathers?," Working Papers 2014.21, Fondazione Eni Enrico Mattei.
  • Bastianin, Andrea & Galeotti, Marzio & Manera, Matteo, 2014. "Forecasting the Oil-gasoline Price Relationship: Should We Care about the Rockets and the Feathers?," Climate Change and Sustainable Development 165791, Fondazione Eni Enrico Mattei (FEEM).
  • Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2014. "Forecasting the Oil-Gasoline Price Relationship: Should We Care About the Rockets and the Feathers?," IEFE Working Papers 62, IEFE, Center for Research on Energy and Environmental Economics and Policy, Universita' Bocconi, Milano, Italy.
  • Andrea BASTIANIN & Marzio GALEOTTI & Matteo MANERA, 2015. "Forecasting the Oil-Gasoline Price Relationship: Should We Care about the Rockets and the Feathers?," Departmental Working Papers 2015-23, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
  • Andrea Bastianin & Matteo Manera, 2020. "A test of time reversibility based on Lmoments with an application to the business cycles of the G7 economies," Working Papers 445, University of Milano-Bicocca, Department of Economics, revised Jun 2020.
• Zekić-Sušac Marijana & Pfeifer Sanja & Šarlija Nataša, 2014. "A Comparison of Machine Learning Methods in a High-Dimensional Classification Problem," Business Systems Research, Sciendo, vol. 5(3), pages 82-96, September.
• McAleer, M.J., 2014. "Discussion of “Principal Volatility Component Analysis” by Yu-Pin Hu and Ruey Tsay," Econometric Institute Research Papers EI 2014-06, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  • Michael McAleer, 2014. "Discussion of “Principal Volatility Component Analysis” by Yu-Pin Hu and Ruey Tsay," Working Papers in Economics 14/09, University of Canterbury, Department of Economics and Finance.
  • Michael McAleer, 2014. "Discussion of “Principal Volatility Component Analysis” by Yu-Pin Hu and Ruey Tsay," Documentos de Trabajo del ICAE 2014-18, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
  • Michael McAleer, 2014. "Discussion of “Principal Volatility Component Analysis” by Yu-Pin Hu and Ruey Tsay," Tinbergen Institute Discussion Papers 14-025/III, Tinbergen Institute.
• Chang, Chia-Lin & McAleer, Michael, 2015. "Econometric analysis of financial derivatives: An overview," Journal of Econometrics, Elsevier, vol. 187(2), pages 403-407.
  • Chia-Lin Chang & Michael McAleer, 2014. "Econometric Analysis of Financial Derivatives: An Overview," Documentos de Trabajo del ICAE 2014-31, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
  • Chia-Lin Chang & Michael McAleer, 2014. "Econometric Analysis of Financial Derivatives: An Overview," Working Papers in Economics 14/29, University of Canterbury, Department of Economics and Finance.
  • Chia-Lin Chang & Michael McAleer, 2014. "Econometric Analysis of Financial Derivatives: An Overview," Tinbergen Institute Discussion Papers 14-153/III, Tinbergen Institute.
• Nathan, Max & Rosso, Anna, 2014. "Mapping information economy businesses with big data: findings from the UK," LSE Research Online Documents on Economics 60615, London School of Economics and Political Science, LSE Library.
  • Max Nathan & Anna Rosso, 2014. "Mapping Information Economy Businesses with Big Data: Findings for the UK," CEP Occasional Papers 44, Centre for Economic Performance, LSE.
  • Nathan, Max & Rosso, Anna & Bouet, Francois, 2014. "Mapping 'Information Economy' Businesses with Big Data: Findings for the UK," IZA Discussion Papers 8662, Institute of Labor Economics (IZA).
• Mao Takongmo, Charles Olivier & Stevanovic, Dalibor, 2015. "Selection Of The Number Of Factors In Presence Of Structural Instability: A Monte Carlo Study," L'Actualité Economique, Société Canadienne de Science Economique, vol. 91(1-2), pages 177-233, Mars-Juin.
  • Dalibor Stevanovic & Charles Olivier Mao Takongmo, 2014. "Selection of the number of factors in presence of structural instability: a Monte Carlo study," CIRANO Working Papers 2014s-44, CIRANO.
• Dante Amengual & Luca Repetto, 2014. "Testing a Large Number of Hypotheses in Approximate Factor Models," Working Papers wp2014_1410, CEMFI.
• Daas, Piet J.H. & Puts, Marco J.H., 2014. "Social media sentiment and consumer confidence," Statistics Paper Series 5, European Central Bank.
• Gillen, Benjamin J., 2014. "An empirical Bayesian approach to stein-optimal covariance matrix estimation," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 402-420.
• Breitung, Jörg & Eickmeier, Sandra, 2014. "Analyzing business and financial cycles using multi-level factor models," Discussion Papers 11/2014, Deutsche Bundesbank.
  • Jörg Breitung & Sandra Eickmeier, 2014. "Analyzing business and financial cycles using multi-level factor models," CAMA Working Papers 2014-43, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Chen, Kan & Crucini, Mario J., 2016. "Trends and cycles in small open economies: making the case for a general equilibrium approach," Journal of Economic Dynamics and Control, Elsevier, vol. 72(C), pages 159-168.
  • Kan Chen & Mario J. Crucini, 2014. "Trends and cycles in small open economies: making the case for a general equilibrium approach," Globalization Institute Working Papers 217, Federal Reserve Bank of Dallas.
  • Kan Chen & Mario Crucini, 2016. "Trends and Cycles in Small Open Economies: Making The Case For A General Equilibrium Approach," NBER Working Papers 22460, National Bureau of Economic Research, Inc.
  • Kan Chen & Mario Crucini, 2016. "Trends and cycles in small open economies: Making the case for a general equilibrium approach," CAMA Working Papers 2016-50, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Kan Chen & Mario J. Crucini, 2016. "Trends and cycles in small open economies: making the case for a general equilibrium approach," Globalization Institute Working Papers 279, Federal Reserve Bank of Dallas.
  • Kan Chen & Mario J. Crucini, 2014. "Trends and Cycles in Small Open Economies: Making The Case For A General Equilibrium Approach," CAMA Working Papers 2014-76, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Aleksandra Halka & Grzegorz Szafranski, 2018. "What Common Factors are Driving Inflation in CEE Countries?," Prague Economic Papers, Prague University of Economics and Business, vol. 2018(2), pages 131-148.
  • Aleksandra Halka & Grzegorz Szafrański, 2014. "What common factors are driving inflation in CEE countries?," EcoMod2014 6977, EcoMod.
  • Aleksandra Hałka & Grzegorz Szafrański, 2015. "What common factors are driving inflation in CEE countries?," NBP Working Papers 225, Narodowy Bank Polski.
• Benjamin J. Gillen & Matthew Shum & Hyungsik Roger Moon, 2014. "Demand Estimation with High-Dimensional Product Characteristics," Advances in Econometrics, in: Bayesian Model Comparison, volume 34, pages 301-323, Emerald Group Publishing Limited.
• Michael McAleer, 2014. "Discussion of “Principal Volatility Component Analysis” by Yu-Pin Hu and Ruey Tsay," Tinbergen Institute Discussion Papers 14-025/III, Tinbergen Institute.
  • McAleer, M.J., 2014. "Discussion of “Principal Volatility Component Analysis” by Yu-Pin Hu and Ruey Tsay," Econometric Institute Research Papers EI 2014-06, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  • Michael McAleer, 2014. "Discussion of “Principal Volatility Component Analysis” by Yu-Pin Hu and Ruey Tsay," Working Papers in Economics 14/09, University of Canterbury, Department of Economics and Finance.
  • Michael McAleer, 2014. "Discussion of “Principal Volatility Component Analysis” by Yu-Pin Hu and Ruey Tsay," Documentos de Trabajo del ICAE 2014-18, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
• Chang, C-L. & McAleer, M.J., 2014. "Econometric Analysis of Financial Derivatives," Econometric Institute Research Papers EI 2015-02, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
• Joseph P. Byrne & Dimitris Korobilis & Pinho J. Ribeiro, 2018. "On The Sources Of Uncertainty In Exchange Rate Predictability," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 59(1), pages 329-357, February.
  • Byrne, Joseph P & Korobilis, Dimitris & Ribeiro, Pinho J, 2014. "On the Sources of Uncertainty in Exchange Rate Predictability," MPRA Paper 58956, University Library of Munich, Germany.
  • Joseph P. Byrne & Dimitris Korobilis & Pinho J. Ribeiro, 2014. "On the Sources of Uncertainty in Exchange Rate Predictability," Working Papers 2014_16, Business School - Economics, University of Glasgow.
  • Byrne, Joseph P. & Korobilis, Dimitris & Ribeiro, Pinho J., 2014. "On the Sources of Uncertainty in Exchange Rate Predictability," SIRE Discussion Papers 2015-24, Scottish Institute for Research in Economics (SIRE).
• Davor Kunovac & Borna Špalat, 2014. "Nowcasting GDP Using Available Monthly Indicators," Working Papers 39, The Croatian National Bank, Croatia.
• Kausik Gangopadhyay & Abhishek Jangir & Rudra Sensarma, 2014. "Forecasting the price of gold: An error correction approach," Working papers 155, Indian Institute of Management Kozhikode.
  • Gangopadhyay, Kausik & Jangir, Abhishek & Sensarma, Rudra, 2015. "Forecasting the price of gold: An error correction approach," MPRA Paper 81066, University Library of Munich, Germany.
• Cathal O'Donoghue & Karyn Morrissey & John Lennon, 2014. "Spatial Microsimulation Modelling: a Review of Applications and Methodological Choices," International Journal of Microsimulation, International Microsimulation Association, vol. 7(1), pages 26-75.
• Max Nathan & Anna Rosso, 2014. "Mapping Information Economy Businesses with Big Data: Findings for the UK," CEP Occasional Papers 44, Centre for Economic Performance, LSE.
  • Nathan, Max & Rosso, Anna & Bouet, Francois, 2014. "Mapping 'Information Economy' Businesses with Big Data: Findings for the UK," IZA Discussion Papers 8662, Institute of Labor Economics (IZA).
  • Nathan, Max & Rosso, Anna, 2014. "Mapping information economy businesses with big data: findings from the UK," LSE Research Online Documents on Economics 60615, London School of Economics and Political Science, LSE Library.
• Inske Pirschel & Maik Wolters, 2014. "Forecasting German Key Macroeconomic Variables Using Large Dataset Methods," Kiel Working Papers 1925, Kiel Institute for the World Economy.
• Reinhold Decker, 2014. "Real-Time Analysis of Online Product Reviews by Means of Multi-Layer Feed-Forward Neural Networks," International Journal of Business and Social Research, LAR Center Press, vol. 4(11), pages 60-70, November.
• Reinhold Decker, 2014. "Real-Time Analysis of Online Product Reviews by Means of Multi-Layer Feed-Forward Neural Networks," International Journal of Business and Social Research, MIR Center for Socio-Economic Research, vol. 4(11), pages 60-70, November.
• Hyndman, Rob J. & Lee, Alan J. & Wang, Earo, 2016. "Fast computation of reconciled forecasts for hierarchical and grouped time series," Computational Statistics & Data Analysis, Elsevier, vol. 97(C), pages 16-32.
  • Rob J Hyndman & Alan Lee & Earo Wang, 2014. "Fast computation of reconciled forecasts for hierarchical and grouped time series," Monash Econometrics and Business Statistics Working Papers 17/14, Monash University, Department of Econometrics and Business Statistics.
• Nathan, Max & Rosso, Anna, 2014. "Mapping information economy businesses with big data: findings from the UK," LSE Research Online Documents on Economics 60615, London School of Economics and Political Science, LSE Library.
  • Max Nathan & Anna Rosso, 2014. "Mapping Information Economy Business with Big Data: Findings from the UK," National Institute of Economic and Social Research (NIESR) Discussion Papers 442, National Institute of Economic and Social Research.
• Popovici Alexandru, 2014. "Philosophy of the Multilevel Reality. Applications in Economics (I) [Filozofia realitǎţii multinivel. Aplicaţii în economie (I)]," Revista OEconomica, Romanian Society for Economic Science, Revista OEconomica, issue 03, September.
• Popovici Alexandru, 2014. "Philosophy of the Multilevel Reality. Applications in Economics (II) [Filozofia realitǎţii multinivel. Aplicaţii în economie (II)]," Revista OEconomica, Romanian Society for Economic Science, Revista OEconomica, issue 04, December.
• Cezary A. Kapuscinski & Kyle Thomson, 2014. "Experiment Estimates of Indigenous Employment from Administrative Data," Australian Journal of Labour Economics (AJLE), Bankwest Curtin Economics Centre (BCEC), Curtin Business School, vol. 17(2), pages 139-161.
• Estrada, Fernando, 2014. "El capital en el siglo XXI de Thomas Piketty [Thomas Piketty’s Capital in the 21st century]," MPRA Paper 60662, University Library of Munich, Germany.
• Gerunov, Anton, 2014. "Big Data Approaches to Modeling the Labor Market," MPRA Paper 68798, University Library of Munich, Germany.
• Carbajal De Nova, Carolina, 2014. "Synthetic data: an endogeneity simulation," MPRA Paper 79158, University Library of Munich, Germany, revised 11 May 2017.
  • Carbajal De Nova, Carolina, 2014. "Synthetic data: an endogeneity simulation," MPRA Paper 79067, University Library of Munich, Germany, revised 10 May 2017.
• Ramadas, Sendhil & Palanisamy, Ramasundaram & Kuruvila, Anil & Chandrasekaran, Sundaramoorthy & Singh, Randhir & Sharma, Indu, 2014. "Food Price Volatility in India – Drivers, Impact and Policy Response," MPRA Paper 91131, University Library of Munich, Germany.
• Michael Toedt, 2014. "The Development of a Response-Function for Customer Relationship Marketing," Proceedings of International Academic Conferences 0100789, International Institute of Social and Economic Sciences.
• Mehmet Fedai KAYA & Muslu Kaz?m KÖREZ & Süleyman DÜNDAR, 2014. "Estimation of the Distribution of Remaning Life Time of the People in Turkey," Proceedings of International Academic Conferences 0201556, International Institute of Social and Economic Sciences.
• Duo Qin & Sophie van H¸llen & Qing-Chao Wang, 2014. "What Happens to Wage Elasticities When We Strip Playometrics? Revisiting Married Women Labour Supply Model," Working Papers 190, Department of Economics, SOAS University of London, UK.
• McAleer, M.J., 2014. "Discussion of “Principal Volatility Component Analysis” by Yu-Pin Hu and Ruey Tsay," Econometric Institute Research Papers EI 2014-06, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  • Michael McAleer, 2014. "Discussion of “Principal Volatility Component Analysis” by Yu-Pin Hu and Ruey Tsay," Tinbergen Institute Discussion Papers 14-025/III, Tinbergen Institute.
  • Michael McAleer, 2014. "Discussion of “Principal Volatility Component Analysis” by Yu-Pin Hu and Ruey Tsay," Documentos de Trabajo del ICAE 2014-18, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
  • Michael McAleer, 2014. "Discussion of “Principal Volatility Component Analysis” by Yu-Pin Hu and Ruey Tsay," Working Papers in Economics 14/09, University of Canterbury, Department of Economics and Finance.
• Matthias Weber & Martin Schumacher & Harald Binder, 2014. "Regularized Regression Incorporating Network Information: Simultaneous Estimation of Covariate Coefficients and Connection Signs," Tinbergen Institute Discussion Papers 14-089/I, Tinbergen Institute.
• Chang, Chia-Lin & McAleer, Michael, 2015. "Econometric analysis of financial derivatives: An overview," Journal of Econometrics, Elsevier, vol. 187(2), pages 403-407.
  • Chia-Lin Chang & Michael McAleer, 2014. "Econometric Analysis of Financial Derivatives: An Overview," Working Papers in Economics 14/29, University of Canterbury, Department of Economics and Finance.
  • Chia-Lin Chang & Michael McAleer, 2014. "Econometric Analysis of Financial Derivatives: An Overview," Tinbergen Institute Discussion Papers 14-153/III, Tinbergen Institute.
  • Chia-Lin Chang & Michael McAleer, 2014. "Econometric Analysis of Financial Derivatives: An Overview," Documentos de Trabajo del ICAE 2014-31, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
• McAleer, M.J., 2014. "Discussion of “Principal Volatility Component Analysis” by Yu-Pin Hu and Ruey Tsay," Econometric Institute Research Papers EI 2014-06, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  • Michael McAleer, 2014. "Discussion of “Principal Volatility Component Analysis” by Yu-Pin Hu and Ruey Tsay," Documentos de Trabajo del ICAE 2014-18, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
  • Michael McAleer, 2014. "Discussion of “Principal Volatility Component Analysis” by Yu-Pin Hu and Ruey Tsay," Working Papers in Economics 14/09, University of Canterbury, Department of Economics and Finance.
  • Michael McAleer, 2014. "Discussion of “Principal Volatility Component Analysis” by Yu-Pin Hu and Ruey Tsay," Tinbergen Institute Discussion Papers 14-025/III, Tinbergen Institute.
• Chang, Chia-Lin & McAleer, Michael, 2015. "Econometric analysis of financial derivatives: An overview," Journal of Econometrics, Elsevier, vol. 187(2), pages 403-407.
  • Chia-Lin Chang & Michael McAleer, 2014. "Econometric Analysis of Financial Derivatives: An Overview," Tinbergen Institute Discussion Papers 14-153/III, Tinbergen Institute.
  • Chia-Lin Chang & Michael McAleer, 2014. "Econometric Analysis of Financial Derivatives: An Overview," Documentos de Trabajo del ICAE 2014-31, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
  • Chia-Lin Chang & Michael McAleer, 2014. "Econometric Analysis of Financial Derivatives: An Overview," Working Papers in Economics 14/29, University of Canterbury, Department of Economics and Finance.
• Daniel Felix Ahelegbey & Monica Billio & Roberto Casarin, 2016. "Sparse Graphical Vector Autoregression: A Bayesian Approach," Annals of Economics and Statistics, GENES, issue 123-124, pages 333-361.
  • Roberto Casarin & Daniel Felix Ahelegbey & Monica Billio, 2014. "Sparse Graphical Vector Autoregression: A Bayesian Approach," Working Papers 2014:29, Department of Economics, University of Venice "Ca' Foscari".
• Jörg Breitung & Sandra Eickmeier, 2014. "Analyzing business and financial cycles using multi-level factor models," CAMA Working Papers 2014-43, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Breitung, Jörg & Eickmeier, Sandra, 2014. "Analyzing business and financial cycles using multi-level factor models," Discussion Papers 11/2014, Deutsche Bundesbank.
• Pirschel, Inske & Wolters, Maik, 2014. "Forecasting German key macroeconomic variables using large dataset methods," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100587, Verein für Socialpolitik / German Economic Association.
  • Pirschel, Inske & Wolters, Maik H., 2014. "Forecasting German key macroeconomic variables using large dataset methods," Kiel Working Papers 1925, Kiel Institute for the World Economy (IfW Kiel).

2013

• Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2014. "High-Dimensional Methods and Inference on Structural and Treatment Effects," Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 29-50, Spring.
  • Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2013. "High dimensional methods and inference on structural and treatment effects," CeMMAP working papers CWP59/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2013. "High dimensional methods and inference on structural and treatment effects," CeMMAP working papers 59/13, Institute for Fiscal Studies.
• Mota, Rui Pedro & Domingos, Tiago, 2013. "Assessment of the theory of comprehensive national accounting with data for Portugal," Ecological Economics, Elsevier, vol. 95(C), pages 188-196.
• Jean Boivin & Marc P. Giannoni & Dalibor Stevanović, 2020. "Dynamic Effects of Credit Shocks in a Data-Rich Environment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 272-284, April.
  • Giannoni, Marc & Boivin, Jean & Stevanovic, Dalibor, 2013. "Dynamic Effects of Credit Shocks in a Data-Rich Environment," CEPR Discussion Papers 9470, C.E.P.R. Discussion Papers.
  • Jean Boivin & Marc Giannoni & Dalibor Stevanovic, 2013. "Dynamic effects of credit shocks in a data-rich environment," Staff Reports 615, Federal Reserve Bank of New York.
  • Jean Boivin & Marc P. Giannoni & Dalibor Stevanovic, 2016. "Dynamic Effects of Credit Shocks in a Data-Rich Environment," CIRANO Working Papers 2016s-55, CIRANO.
  • Jean Boivin & Marc P. Giannoni & Dalibor Stevanovic, 2013. "Dynamic Effects of Credit Shocks in a Data-Rich Environment," CIRANO Working Papers 2013s-11, CIRANO.
  • Jean Boivin & Marc P. Giannoni & Dalibor Stevanovic, 2013. "Dynamic Effects of Credit Shocks in a Data-Rich Environment," Cahiers de recherche 1324, CIRPEE.
• Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2014. "High-Dimensional Methods and Inference on Structural and Treatment Effects," Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 29-50, Spring.
  • Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2013. "High dimensional methods and inference on structural and treatment effects," CeMMAP working papers 59/13, Institute for Fiscal Studies.
  • Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2013. "High dimensional methods and inference on structural and treatment effects," CeMMAP working papers CWP59/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
• Anna Gloria Billé, 2013. "Computational Issues in the Estimation of the Spatial Probit Model: A Comparison of Various Estimators," The Review of Regional Studies, Southern Regional Science Association, vol. 43(2,3), pages 131-154, Winter.

2012

• Steffen Andersen & James C. Cox & Glenn W. Harrison & Morten Lau & Elisabet E. Rutstroem & Vjollca Sadiraj, 2011. "Asset Integration and Attitudes to Risk: Theory and Evidence," Working Papers 2011_10, Durham University Business School.
  • Steffen Andersen & James C. Cox & Glenn W. Harrison & Morten Lau & E. Elisabet Rutström & Vjollca Sadiraj, 2012. "Asset Integration and Attitudes to Risk: Theory and Evidence," Experimental Economics Center Working Paper Series 2012-12, Experimental Economics Center, Andrew Young School of Policy Studies, Georgia State University, revised Oct 2017.
• Prof. Dr. Bernd Meyer, 2012. "Macroeconomic Modelling of Sustainable Development and the Links between the Economy and the Environment," GWS Research Report Series 12-1, GWS - Institute of Economic Structures Research.
• Thomas von Brasch & Johan Byström & Lars Petter Lystad, 2012. "Optimal control and the Fibonacci sequence," Discussion Papers 674, Statistics Norway, Research Department.

2011

• Steffen Andersen & James C. Cox & Glenn W. Harrison & Morten Lau & Elisabet E. Rutstroem & Vjollca Sadiraj, 2011. "Asset Integration and Attitudes to Risk: Theory and Evidence," Working Papers 2011_10, Durham University Business School.
  • Steffen Andersen & James C. Cox & Glenn W. Harrison & Morten Lau & E. Elisabet Rutström & Vjollca Sadiraj, 2012. "Asset Integration and Attitudes to Risk: Theory and Evidence," Experimental Economics Center Working Paper Series 2012-12, Experimental Economics Center, Andrew Young School of Policy Studies, Georgia State University, revised Oct 2017.
• Soshichi Kinoshita (ed.), 2011. "Econometric Modeling of Japan and Asia-Pacific Economies," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 8276, February.

2009

• Mell T & Wartenburger I & Marschner A & Villringer A & Reischies FM & Heekeren, 2009. "Altered Function of Ventral Striatum during Reward-Based Decision Making in Old Age," SFB 649 Discussion Papers SFB649DP2009-064, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
• Bakshi, Sanjeev & Pathak, Prasanta, 2009. "Health at Old Ages in India: Statistical Exposition of Its Socio-Cultural and Gender Dimensions," MPRA Paper 60690, University Library of Munich, Germany.
• Mell, Thomas & Wartenburger, Isabell & Marschner, Alexander & Villringer, Arno & Reischies, Friedel M. & Heekeren, Hauke R., 2009. "Altered Function of Ventral Striatum during Reward-Based Decision Making in Old Age," SFB 649 Discussion Papers 2009-064, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

2008

• Shigenobu Ohara & Takayuki Asada (ed.), 2008. "Japanese Project Management:KPM — Innovation, Development and Improvement," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 6657, August.
• Shigenobu Ohara, 2008. "Framework of Contemporary Japanese Project Management (1): Project Management Paradigm — Interpretation, Application and Evolution to KPM," World Scientific Book Chapters, in: Shigenobu Ohara & Takayuki Asada (ed.), Japanese Project Management KPM — Innovation, Development and Improvement, chapter 1, pages 5-23, World Scientific Publishing Co. Pte. Ltd..
• Shigenobu Ohara, 2008. "Framework of Contemporary Japanese Project Management (2): Kakusin-Innovation Program Management (IPM) — Organizational Acceptance and Dynamic Intellectual Cycle," World Scientific Book Chapters, in: Shigenobu Ohara & Takayuki Asada (ed.), Japanese Project Management KPM — Innovation, Development and Improvement, chapter 2, pages 25-43, World Scientific Publishing Co. Pte. Ltd..
• Tametsugu Taketomi, 2008. "Adjusting Function and Office Design in Japanese-Style Project Management Organizations — Applying the Idea of KPM," World Scientific Book Chapters, in: Shigenobu Ohara & Takayuki Asada (ed.), Japanese Project Management KPM — Innovation, Development and Improvement, chapter 3, pages 45-59, World Scientific Publishing Co. Pte. Ltd..
• Tadamasa Imaguchi, 2008. "Innovative Strategy and Project Organization," World Scientific Book Chapters, in: Shigenobu Ohara & Takayuki Asada (ed.), Japanese Project Management KPM — Innovation, Development and Improvement, chapter 4, pages 61-69, World Scientific Publishing Co. Pte. Ltd..
• Emi Yunokawa, 2008. "The Practice Examples of KPM Knowledge Platform," World Scientific Book Chapters, in: Shigenobu Ohara & Takayuki Asada (ed.), Japanese Project Management KPM — Innovation, Development and Improvement, chapter 5, pages 71-81, World Scientific Publishing Co. Pte. Ltd..
• Toshihiko Kinoshita, 2008. "Changes of Japanese Corporate Business Model under Global Pressure: Evidence Justifying KPM," World Scientific Book Chapters, in: Shigenobu Ohara & Takayuki Asada (ed.), Japanese Project Management KPM — Innovation, Development and Improvement, chapter 6, pages 83-104, World Scientific Publishing Co. Pte. Ltd..
• Tametsugu Taketomi, 2008. "Toward Establishing Project Governance," World Scientific Book Chapters, in: Shigenobu Ohara & Takayuki Asada (ed.), Japanese Project Management KPM — Innovation, Development and Improvement, chapter 7, pages 111-128, World Scientific Publishing Co. Pte. Ltd..
• Shoei Komatsu, 2008. "Management Model of Information Development Program — Adaptive Multiple Spiral-Up Management," World Scientific Book Chapters, in: Shigenobu Ohara & Takayuki Asada (ed.), Japanese Project Management KPM — Innovation, Development and Improvement, chapter 8, pages 129-141, World Scientific Publishing Co. Pte. Ltd..
• Hideo Yamamoto, 2008. "Information Sharing for an ICT System for Strategic Program Management," World Scientific Book Chapters, in: Shigenobu Ohara & Takayuki Asada (ed.), Japanese Project Management KPM — Innovation, Development and Improvement, chapter 9, pages 143-153, World Scientific Publishing Co. Pte. Ltd..
• Naokoto Kogo & Atsushi Miyagawa, 2008. "Project Management from the Viewpoint of Projection Technologies," World Scientific Book Chapters, in: Shigenobu Ohara & Takayuki Asada (ed.), Japanese Project Management KPM — Innovation, Development and Improvement, chapter 10, pages 155-166, World Scientific Publishing Co. Pte. Ltd..
• Takashi Katayama & Takayuki Asada, 2008. "An Evaluation Theory for Practical Use of RFID under Supply Chain Project Management," World Scientific Book Chapters, in: Shigenobu Ohara & Takayuki Asada (ed.), Japanese Project Management KPM — Innovation, Development and Improvement, chapter 11, pages 167-180, World Scientific Publishing Co. Pte. Ltd..
• Takayuki Asada, 2008. "A Study of Multiple Value Measures Applied into Strategic Project Management," World Scientific Book Chapters, in: Shigenobu Ohara & Takayuki Asada (ed.), Japanese Project Management KPM — Innovation, Development and Improvement, chapter 12, pages 187-201, World Scientific Publishing Co. Pte. Ltd..
• Fumihiko Isada, 2008. "Business Architecture for Program and Project Management," World Scientific Book Chapters, in: Shigenobu Ohara & Takayuki Asada (ed.), Japanese Project Management KPM — Innovation, Development and Improvement, chapter 13, pages 203-212, World Scientific Publishing Co. Pte. Ltd..
• Hiroshi Sasaki, 2008. "Business Portfolio Strategies for IT Services Companies in Japan: IS Strategy, Governance and Management," World Scientific Book Chapters, in: Shigenobu Ohara & Takayuki Asada (ed.), Japanese Project Management KPM — Innovation, Development and Improvement, chapter 14, pages 213-224, World Scientific Publishing Co. Pte. Ltd..
• Kenichi Suzuki, 2008. "Project & Program Balanced Scorecard for Executing Strategy in a Hotel Corporation," World Scientific Book Chapters, in: Shigenobu Ohara & Takayuki Asada (ed.), Japanese Project Management KPM — Innovation, Development and Improvement, chapter 15, pages 225-233, World Scientific Publishing Co. Pte. Ltd..
• Kazuo Tanaka & Masaru Tamaki, 2008. "Development of a Service Model for the Japanese Construction Industry — Application to Business Innovation and Improvement Activities for Building Renewal," World Scientific Book Chapters, in: Shigenobu Ohara & Takayuki Asada (ed.), Japanese Project Management KPM — Innovation, Development and Improvement, chapter 16, pages 235-245, World Scientific Publishing Co. Pte. Ltd..
• Ellie Okada, 2008. "Strategic Knowledge/Intellectual Property Management and Compound Project Management: Theory and Practice," World Scientific Book Chapters, in: Shigenobu Ohara & Takayuki Asada (ed.), Japanese Project Management KPM — Innovation, Development and Improvement, chapter 17, pages 253-264, World Scientific Publishing Co. Pte. Ltd..
• Shiro Okazaki & Yousuke Manabe, 2008. "Strategic R&D Management at NEDO (Japanese Public R&D Management Organization)," World Scientific Book Chapters, in: Shigenobu Ohara & Takayuki Asada (ed.), Japanese Project Management KPM — Innovation, Development and Improvement, chapter 18, pages 265-279, World Scientific Publishing Co. Pte. Ltd..
• Koji Iwasaki, 2008. "Pharmaceutical Development as Case Study with High-Risk, High-Return Project Management," World Scientific Book Chapters, in: Shigenobu Ohara & Takayuki Asada (ed.), Japanese Project Management KPM — Innovation, Development and Improvement, chapter 19, pages 281-293, World Scientific Publishing Co. Pte. Ltd..
• Ninako Makino, 2008. "The Product Development Project Aiming at the “Sociality” of Commodities," World Scientific Book Chapters, in: Shigenobu Ohara & Takayuki Asada (ed.), Japanese Project Management KPM — Innovation, Development and Improvement, chapter 20, pages 295-308, World Scientific Publishing Co. Pte. Ltd..
• Christophe N Bredillet, 2008. "Shikumizukuri vs. One Best (No) Way! Project and Program Management for Enterprise Innovation (P2M): Towards a New Paradigm of KPM?," World Scientific Book Chapters, in: Shigenobu Ohara & Takayuki Asada (ed.), Japanese Project Management KPM — Innovation, Development and Improvement, chapter 21, pages 313-337, World Scientific Publishing Co. Pte. Ltd..
• Toshinori Nemoto & Yuki Misui, 2008. "Pricing Public Projects with Complexity — Highway Management and Capacity Optimization by Mile-Based Pricing," World Scientific Book Chapters, in: Shigenobu Ohara & Takayuki Asada (ed.), Japanese Project Management KPM — Innovation, Development and Improvement, chapter 22, pages 339-360, World Scientific Publishing Co. Pte. Ltd..
• Hajime Kita & Mikihiko Mori, 2008. "Projects of Participatory Production and Their Management: Practice in Industrial Accumulation in Suwa," World Scientific Book Chapters, in: Shigenobu Ohara & Takayuki Asada (ed.), Japanese Project Management KPM — Innovation, Development and Improvement, chapter 23, pages 361-373, World Scientific Publishing Co. Pte. Ltd..
• Lynn Crawford, 2008. "World PM Trends and the Position of P2M in the Global Community," World Scientific Book Chapters, in: Shigenobu Ohara & Takayuki Asada (ed.), Japanese Project Management KPM — Innovation, Development and Improvement, chapter 24, pages 381-402, World Scientific Publishing Co. Pte. Ltd..
• Toshihiko Kinoshita, 2008. "Examples of Changes of Japanese Corporate Business Model: Why is KPM Essentially Important Now?," World Scientific Book Chapters, in: Shigenobu Ohara & Takayuki Asada (ed.), Japanese Project Management KPM — Innovation, Development and Improvement, chapter 25, pages 403-423, World Scientific Publishing Co. Pte. Ltd..
• Masaaki Horiguchi, 2008. "Knowledge of Project Management and Finance in Japan," World Scientific Book Chapters, in: Shigenobu Ohara & Takayuki Asada (ed.), Japanese Project Management KPM — Innovation, Development and Improvement, chapter 26, pages 425-433, World Scientific Publishing Co. Pte. Ltd..
• Emiko Magoshi & Akio Yamamoto, 2008. "Transcultural Management: Cultural Relevance in Different Industries," World Scientific Book Chapters, in: Shigenobu Ohara & Takayuki Asada (ed.), Japanese Project Management KPM — Innovation, Development and Improvement, chapter 27, pages 435-449, World Scientific Publishing Co. Pte. Ltd..
• Masatoshi Nishio, 2008. "Educational Effectiveness and Implementation of KPM in the Cultivation of Human Resource," World Scientific Book Chapters, in: Shigenobu Ohara & Takayuki Asada (ed.), Japanese Project Management KPM — Innovation, Development and Improvement, chapter 28, pages 451-465, World Scientific Publishing Co. Pte. Ltd..

2005

• Angers, Jean-François & Desjardins, Denise & Dionne, Georges & Guertin, François, 2005. "Modélisation et estimation des effets individuels et d’entreprise avec des données de panel : une application aux flottes de véhicules," Working Papers 05-7, HEC Montreal, Canada Research Chair in Risk Management.

2004

• Ryo Nagata, 2004. "Theory of Regular Economies," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 5543, August.
• Ryo Nagata, 2004. "What Is a Regular Economy?," World Scientific Book Chapters, in: Theory Of Regular Economies, chapter 1, pages 3-16, World Scientific Publishing Co. Pte. Ltd..
• Ryo Nagata, 2004. "Regular Economies and Genericity," World Scientific Book Chapters, in: Theory Of Regular Economies, chapter 2, pages 17-27, World Scientific Publishing Co. Pte. Ltd..
• Ryo Nagata, 2004. "Formalization of Regular Economies," World Scientific Book Chapters, in: Theory Of Regular Economies, chapter 3, pages 29-40, World Scientific Publishing Co. Pte. Ltd..
• Ryo Nagata, 2004. "The Number of Equilibria in Regular Economies," World Scientific Book Chapters, in: Theory Of Regular Economies, chapter 4, pages 41-57, World Scientific Publishing Co. Pte. Ltd..
• Ryo Nagata, 2004. "Stability of Equilibria in Regular Economies," World Scientific Book Chapters, in: Theory Of Regular Economies, chapter 5, pages 59-82, World Scientific Publishing Co. Pte. Ltd..
• Ryo Nagata, 2004. "Space of Utility Functions," World Scientific Book Chapters, in: Theory Of Regular Economies, chapter 6, pages 85-98, World Scientific Publishing Co. Pte. Ltd..
• Ryo Nagata, 2004. "Transversality and Regular Economies," World Scientific Book Chapters, in: Theory Of Regular Economies, chapter 7, pages 99-107, World Scientific Publishing Co. Pte. Ltd..
• Ryo Nagata, 2004. "Transversality Theorems and Regular Economies," World Scientific Book Chapters, in: Theory Of Regular Economies, chapter 8, pages 109-124, World Scientific Publishing Co. Pte. Ltd..
• Ryo Nagata, 2004. "The Number of Extended Equilibria in Regular Economies," World Scientific Book Chapters, in: Theory Of Regular Economies, chapter 9, pages 125-137, World Scientific Publishing Co. Pte. Ltd..
• Ryo Nagata, 2004. "Production Economy with Linear Activities," World Scientific Book Chapters, in: Theory Of Regular Economies, chapter 10, pages 141-160, World Scientific Publishing Co. Pte. Ltd..
• Ryo Nagata, 2004. "Incomplete Markets I," World Scientific Book Chapters, in: Theory Of Regular Economies, chapter 11, pages 161-185, World Scientific Publishing Co. Pte. Ltd..
• Ryo Nagata, 2004. "Incomplete Markets II," World Scientific Book Chapters, in: Theory Of Regular Economies, chapter 12, pages 187-204, World Scientific Publishing Co. Pte. Ltd..

2000

• Cornelis A. Los, 2000. "A Scientific Perspective," World Scientific Book Chapters, in: Computational Finance A Scientific Perspective, chapter 1, pages 19-33, World Scientific Publishing Co. Pte. Ltd..
• Cornelis A. Los, 2000. "Capital Budgeting And Analytic Formulas," World Scientific Book Chapters, in: Computational Finance A Scientific Perspective, chapter 2, pages 35-49, World Scientific Publishing Co. Pte. Ltd..
• Cornelis A. Los, 2000. "Fundamental Security Valuation," World Scientific Book Chapters, in: Computational Finance A Scientific Perspective, chapter 3, pages 51-56, World Scientific Publishing Co. Pte. Ltd..
• Cornelis A. Los, 2000. "Analysis Of Exact Data I," World Scientific Book Chapters, in: Computational Finance A Scientific Perspective, chapter 4, pages 57-73, World Scientific Publishing Co. Pte. Ltd..
• Cornelis A. Los, 2000. "Analysis Of Inexact Data Ii," World Scientific Book Chapters, in: Computational Finance A Scientific Perspective, chapter 5, pages 75-98, World Scientific Publishing Co. Pte. Ltd..
• Cornelis A. Los, 2000. "Optimal Portfolio Formation," World Scientific Book Chapters, in: Computational Finance A Scientific Perspective, chapter 6, pages 99-111, World Scientific Publishing Co. Pte. Ltd..
• Cornelis A. Los, 2000. "Systematic Financial Risk Analysis," World Scientific Book Chapters, in: Computational Finance A Scientific Perspective, chapter 7, pages 113-134, World Scientific Publishing Co. Pte. Ltd..
• Cornelis A. Los, 2000. "Complete Valuation And Dynamic Risk Theory," World Scientific Book Chapters, in: Computational Finance A Scientific Perspective, chapter 8, pages 135-161, World Scientific Publishing Co. Pte. Ltd..
• Cornelis A. Los, 2000. "Option Pricing Ii," World Scientific Book Chapters, in: Computational Finance A Scientific Perspective, chapter 10, pages 183-200, World Scientific Publishing Co. Pte. Ltd..
  • Cornelis A. Los, 2000. "Option Pricing I," World Scientific Book Chapters, in: Computational Finance A Scientific Perspective, chapter 9, pages 163-182, World Scientific Publishing Co. Pte. Ltd..
• Cornelis A. Los, 2000. "Option Pricing I," World Scientific Book Chapters, in: Computational Finance A Scientific Perspective, chapter 9, pages 163-182, World Scientific Publishing Co. Pte. Ltd..
  • Cornelis A. Los, 2000. "Option Pricing Ii," World Scientific Book Chapters, in: Computational Finance A Scientific Perspective, chapter 10, pages 183-200, World Scientific Publishing Co. Pte. Ltd..
• Cornelis A. Los, 2000. "Bond Portfolio Valuation And Management," World Scientific Book Chapters, in: Computational Finance A Scientific Perspective, chapter 11, pages 201-221, World Scientific Publishing Co. Pte. Ltd..
• Cornelis A. Los, 2000. "Forwards And Futures," World Scientific Book Chapters, in: Computational Finance A Scientific Perspective, chapter 12, pages 223-235, World Scientific Publishing Co. Pte. Ltd..
• Cornelis A. Los, 2000. "Swaps," World Scientific Book Chapters, in: Computational Finance A Scientific Perspective, chapter 13, pages 237-252, World Scientific Publishing Co. Pte. Ltd..
• Cornelis A. Los, 2000. "Multi-Currency Investments And Exact Performance Attribution," World Scientific Book Chapters, in: Computational Finance A Scientific Perspective, chapter 14, pages 253-281, World Scientific Publishing Co. Pte. Ltd..

1992

• Albert, Pierre & Ghassan, Hassan B. & Huiban, Jean Pierre & Martin, Michel, 1992. "L'Industrie Laitière Française: Modèles d'Entreprises et Formes de Concurrence/Coordination Inter-Firmes [French Dairy Industry: Enterprise models and Inter-Firms Competition/Coordination Forms]," MPRA Paper 60457, University Library of Munich, Germany.

1982

• Anderson, Tn & Kida, Te, 1982. "The Cross-Lagged Research Approach - Description And Illustration," Journal of Accounting Research, Wiley Blackwell, vol. 20(2), pages 403-414.

0

• Cooper, Joseph & Delbecq, Benoît, 2014. "A multi-region approach to assessing fiscal and farm level consequences of government support for farm risk management," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), vol. 3(3), pages 1-23, December.
  • Cooper, Joseph & Delbecq, Benoit, 2014. "A Multi-Region Approach to Assessing Fiscal and Farm Level Consequences of Government Support for Farm Risk Management," 2014 Third Congress, June 25-27, 2014, Alghero, Italy 173108, Italian Association of Agricultural and Applied Economics (AIEAA).
• Antón Sarabia Arturo & Bazdresch Santiago & Lelo-de-Larrea Alejandra, 2023. "The Influence of Central Bank's Projections and Economic Narrative on Professional Forecasters' Expectations: Evidence from Mexico," Working Papers 2023-21, Banco de México.
• Leonardo Gambacorta & Byeungchun Kwon & Taejin Park & Pietro Patelli & Sonya Zhu, "undated". "CB-LMs: language models for central banking," BIS Working Papers 1215, Bank for International Settlements.
• Michele Tertilt & Matthias Doepke & Anne Hannusch & Laura Montenbruck, "undated". "The Economics of Woman's Rights The Mary Paley and Alfred Marshall Lecture," CRC TR 224 Discussion Paper Series crctr22401_2018, University of Bonn and University of Mannheim, Germany.
• Patrick GAGLIARDINI & Christian GOURIEROUX & Mirco RUBIN, 2014. "Are Behavioral Biases Stable Across Markets and Prevalent Across Individuals? Evidence from Individual Betting Choices," Swiss Finance Institute Research Paper Series 14-20, Swiss Finance Institute.
• Barbora Malinska, 2019. "Realized Moments and Bond Pricing," Working Papers IES 2019/11, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised May 2019.
• Dario Sansone, 2019. "Beyond Early Warning Indicators: High School Dropout and Machine Learning," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(2), pages 456-485, April.
  • Dario Sansone, 2017. "Now You See Me: High School Dropout and Machine Learning," 2017 Stata Conference 5, Stata Users Group.
  • Dario Sansone, 2017. "Beyond Early Warning Indicators: High School Dropout and Machine Learning," Working Papers gueconwpa~17-17-09, Georgetown University, Department of Economics.
• Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“Tracking economic growth by evolving expectations via genetic programming: A two-step approach”," AQR Working Papers 201801, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2018.
  • Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“Tracking economic growth by evolving expectations via genetic programming: A two-step approach”," IREA Working Papers 201801, University of Barcelona, Research Institute of Applied Economics, revised Jan 2018.
  • Oscar Claveria & Enric Monte & Salvador Torra, 2018. "Tracking economic growth by evolving expectations via genetic programming: A two-step approach," Working Papers XREAP2018-4, Xarxa de Referència en Economia Aplicada (XREAP), revised Oct 2018.
• Philip Hans Franses & Thomas Wiemann, 0. "Intertemporal Similarity of Economic Time Series: An Application of Dynamic Time Warping," Computational Economics, Springer;Society for Computational Economics, vol. 0, pages 1-17.
• Zhan Gao & Zhentao Shi, 0. "Implementing Convex Optimization in R: Two Econometric Examples," Computational Economics, Springer;Society for Computational Economics, vol. 0, pages 1-9.
• Martin Obschonka & Neil Lee & Andrés Rodríguez-Pose & Johannes C. Eichstaedt & Tobias Ebert, 0. "Big data methods, social media, and the psychology of entrepreneurial regions: capturing cross-county personality traits and their impact on entrepreneurship in the USA," Small Business Economics, Springer, vol. 0, pages 1-22.
• Jens Prüfer & Patricia Prüfer, 0. "Data science for entrepreneurship research: studying demand dynamics for entrepreneurial skills in the Netherlands," Small Business Economics, Springer, vol. 0, pages 1-22.
  • Prüfer, Jens & Prüfer, Patricia, 2019. "Data Science for Entrepreneurship Research : Studying Demand Dynamics for Entrepreneurial Skills in the Netherlands," Discussion Paper 2019-005, Tilburg University, Center for Economic Research.
• Jermain C. Kaminski & Christian Hopp, 0. "Predicting outcomes in crowdfunding campaigns with textual, visual, and linguistic signals," Small Business Economics, Springer, vol. 0, pages 1-23.
• Yasuhiro Hara, "undated". "Dynamic Relationship between Information Dissemination by Local Governors and Mobility during the COVID-19 Pandemic," Discussion papers ron373, Policy Research Institute, Ministry of Finance Japan.
• Elena Andreou & Patrick Gagliardini & Eric Ghysels & Mirco Rubin, 0. "Mixed-Frequency Macro–Finance Factor Models: Theory and Applications," Journal of Financial Econometrics, Oxford University Press, vol. 18(3), pages 585-628.
• Roberto S. Mariano & Suleyman Ozmucur, "undated". "Lawrence R. Klein’s Principles in Modeling and Contributions in Nowcasting, Real-Time Forecasting, and Machine Learning," PIER Working Paper Archive 20-034, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
• Sandra Figueiredo, 2020. "A psycholinguistic analysis of presidential? discourses concerning the COVID-19 context: authenticity and emotional tone," Proceedings of International Academic Conferences 10613009, International Institute of Social and Economic Sciences.
• Ivana Lolić & Petar Sorić & Marija Logarušić, 2022. "Economic Policy Uncertainty Index Meets Ensemble Learning," Computational Economics, Springer;Society for Computational Economics, vol. 60(2), pages 401-437, August.
  • Ivana Loli? & Petar Sori? & Marija Logaru?i?, 0000. "Economic Policy Uncertainty index meets ensemble learning," Proceedings of International Academic Conferences 11313180, International Institute of Social and Economic Sciences.
• Arianna Agosto & Paolo Giudici, 0. "COVID-19 contagion and digital finance," Digital Finance, Springer, vol. 0, pages 1-9.
• Ricardo Buettner, 0. "Predicting user behavior in electronic markets based on personality-mining in large online social networks," Electronic Markets, Springer;IIM University of St. Gallen, vol. 0, pages 1-19.
• Maximo Camacho & Angela Caro & German Lopez-Buenache, 0. "The two-speed Europe in business cycle synchronization," Empirical Economics, Springer, vol. 0, pages 1-16.
• Yongchen Zhao, 0. "Predicting U.S. Business Cycle Turning Points Using Real-Time Diffusion Indexes Based on a Large Data Set," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 0, pages 1-21.
  • Herman O. Stekler & Yongchen Zhao, 2016. "Predicting U.S. Business Cycle Turning Points Using Real-Time Diffusion Indexes Based on a Large Data Set," Working Papers 2016-006, The George Washington University, Department of Economics, Research Program on Forecasting.
  • Herman Stekler & Yongchen Zhao, 2016. "Predicting U.S. Business Cycle Turning Points Using Real-Time Diffusion Indexes Based on a Large Data Set," Working Papers 2016-15, Towson University, Department of Economics, revised Sep 2016.
• Sharada Davidson & Chenghan Hou & Gary Koop, "undated". "Investigating Economic Uncertainty Using Stochastic Volatility in Mean VARs: The Importance of Model Size, Order-Invariance and Classification," Working Papers 2306, University of Strathclyde Business School, Department of Economics.
• Andries C. van Vlodrop & Andre (A.) Lucas, "undated". "Estimation Risk and Shrinkage in Vast-Dimensional Fundamental Factor Models," Tinbergen Institute Discussion Papers 2018-12-22, Tinbergen Institute.