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Forecasting economic time series using targeted predictors
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Cited by:
- Özen, Kadir & Yıldırım, Dilem, 2021. "Application of bagging in day-ahead electricity price forecasting and factor augmentation," Energy Economics, Elsevier, vol. 103(C).
- Carstensen, Kai & Heinrich, Markus & Reif, Magnus & Wolters, Maik H., 2020.
"Predicting ordinary and severe recessions with a three-state Markov-switching dynamic factor model,"
International Journal of Forecasting, Elsevier, vol. 36(3), pages 829-850.
- Heinrich, Markus & Carstensen, Kai & Reif, Magnus & Wolters, Maik, 2017. "Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model. An Application to the German Business Cycle," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168206, Verein für Socialpolitik / German Economic Association.
- Kai Carstensen & Markus Heinrich & Magnus Reif & Maik H. Wolters, 2017. "Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model. An Application to the German Business Cycle," CESifo Working Paper Series 6457, CESifo.
- Kai Carstensen & Markus Heinrich & Magnus Reif & Maik H. Wolters, 2019. "Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model," Jena Economics Research Papers 2019-006, Friedrich-Schiller-University Jena.
- Carstensen, Kai & Bachmann, Rüdiger & Schneider, Martin & Lautenbacher, Stefan, 2018. "Uncertainty is Change," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181572, Verein für Socialpolitik / German Economic Association.
- Jens J. Krüger, 2021. "A Wavelet Evaluation of Some Leading Business Cycle Indicators for the German Economy," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(3), pages 293-319, December.
- Marie Bessec, 2013.
"Short‐Term Forecasts of French GDP: A Dynamic Factor Model with Targeted Predictors,"
Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(6), pages 500-511, September.
- Bessec, M., 2012. "Short-term forecasts of French GDP: a dynamic factor model with targeted predictors," Working papers 409, Banque de France.
- Marie Bessec, 2013. "Short-term forecasts of French GDP: A dynamic factor model with targeted predictors," Post-Print hal-01515605, HAL.
- Eric Hillebrand & Huiyu Huang & Tae-Hwy Lee & Canlin Li, 2018.
"Using the Entire Yield Curve in Forecasting Output and Inflation,"
Econometrics, MDPI, vol. 6(3), pages 1-27, August.
- Tae-Hwy Lee & Eric Hillebrand & Huiyu Huang & Canlin Li, 2018. "Using the Entire Yield Curve in Forecasting Output and Inflation," Working Papers 201903, University of California at Riverside, Department of 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.
- 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.
- Claudio Morana, 2014. "Factor Vector Autoregressive Estimation of Heteroskedastic Persistent and Non Persistent Processes Subject to Structural Breaks," Working Papers 273, University of Milano-Bicocca, Department of Economics, revised May 2014.
- Carlos Cesar Trucios-Maza & João H. G Mazzeu & Luis K. Hotta & Pedro L. Valls Pereira & Marc Hallin, 2019. "On the robustness of the general dynamic factor model with infinite-dimensional space: identification, estimation, and forecasting," Working Papers ECARES 2019-32, ULB -- Universite Libre de Bruxelles.
- Dai, Zhifeng & Zhang, Xiaotong & Li, Tingyu, 2023. "Forecasting stock return volatility in data-rich environment: A new powerful predictor," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
- Exterkate, Peter & Groenen, Patrick J.F. & Heij, Christiaan & van Dijk, Dick, 2016.
"Nonlinear forecasting with many predictors using kernel ridge regression,"
International Journal of Forecasting, Elsevier, vol. 32(3), pages 736-753.
- Peter Exterkate & Patrick J.F. Groenen & Christiaan Heij & Dick van Dijk, 2011. "Nonlinear Forecasting with Many Predictors using Kernel Ridge Regression," Tinbergen Institute Discussion Papers 11-007/4, Tinbergen Institute.
- Peter Exterkate & Patrick J.F. Groenen & Christiaan Heij & Dick van Dijk, 2013. "Nonlinear Forecasting With Many Predictors Using Kernel Ridge Regression," CREATES Research Papers 2013-16, Department of Economics and Business Economics, Aarhus University.
- Poncela, Pilar, 2012. "More is not always better : back to the Kalman filter in dynamic factor models," DES - Working Papers. Statistics and Econometrics. WS ws122317, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
- Chen, Qitong & Hong, Yongmiao & Li, Haiqi, 2024. "Time-varying forecast combination for factor-augmented regressions with smooth structural changes," Journal of Econometrics, Elsevier, vol. 240(1).
- Arabinda Basistha, 2023. "Estimation of short‐run predictive factor for US growth using state employment data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(1), pages 34-50, January.
- 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).
- repec:dau:papers:123456789/10079 is not listed on IDEAS
- Klaus Abberger & Michael Graff & Boriss Siliverstovs & Jan-Egbert Sturm, 2014. "The KOF Economic Barometer, Version 2014," KOF Working papers 14-353, KOF Swiss Economic Institute, ETH Zurich.
- Stig Vinther Møller & Thomas Pedersen & Erik Christian Montes Schütte & Allan Timmermann, 2024.
"Search and Predictability of Prices in the Housing Market,"
Management Science, INFORMS, vol. 70(1), pages 415-438, January.
- Timmermann, Allan & Møller, Stig & Pedersen, Thomas & Schütte, Erik Christian Montes, 2021. "Search and Predictability of Prices in the Housing Market," CEPR Discussion Papers 15875, C.E.P.R. Discussion Papers.
- Valentina Aprigliano & Claudia Foroni & Massimiliano Marcellino & Gianluigi Mazzi & Fabrizio Venditti, 2017.
"A daily indicator of economic growth for the euro area,"
International Journal of Computational Economics and Econometrics, Inderscience Enterprises Ltd, vol. 7(1/2), pages 43-63.
- Valentina Aprigliano & Claudia Foroni & Massimiliano Marcellino & Gianluigi Mazzi & Fabrizio Venditti, 2016. "A daily indicator of economic growth for the euro area," Working Papers 570, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
- Ard Reijer, 2013. "Forecasting Dutch GDP and inflation using alternative factor model specifications based on large and small datasets," Empirical Economics, Springer, vol. 44(2), pages 435-453, April.
- 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.
- Bouaddi, Mohammed & Taamouti, Abderrahim, 2013. "Portfolio selection in a data-rich environment," Journal of Economic Dynamics and Control, Elsevier, vol. 37(12), pages 2943-2962.
- 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.
- Alessandro Giovannelli, 2012. "Nonlinear Forecasting Using Large Datasets: Evidences on US and Euro Area Economies," CEIS Research Paper 255, Tor Vergata University, CEIS, revised 08 Nov 2012.
- Tommaso Proietti, 2016.
"On the Selection of Common Factors for Macroeconomic Forecasting,"
Advances in Econometrics, in: Dynamic Factor Models, volume 35, pages 593-628,
Emerald Group Publishing Limited.
- Giovannelli, Alessandro & Proietti, Tommaso, 2014. "On the Selection of Common Factors for Macroeconomic Forecasting," MPRA Paper 60673, University Library of Munich, Germany.
- Alessandro Giovannelli & Tommaso Proietti, 2014. "On the Selection of Common Factors for Macroeconomic Forecasting," CREATES Research Papers 2014-46, Department of Economics and Business Economics, Aarhus University.
- Alessandro Giovannelli & Tommaso Proietti, 2015. "On the Selection of Common Factors for Macroeconomic Forecasting," CEIS Research Paper 332, Tor Vergata University, CEIS, revised 12 Mar 2015.
- 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.
- Vortelinos, Dimitrios I., 2017. "Forecasting realized volatility: HAR against Principal Components Combining, neural networks and GARCH," Research in International Business and Finance, Elsevier, vol. 39(PB), pages 824-839.
- Lima, Luiz Renato & Meng, Fanning & Godeiro, Lucas, 2020. "Quantile forecasting with mixed-frequency data," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1149-1162.
- Kim, Hyun Hak & Swanson, Norman R., 2018. "Mining big data using parsimonious factor, machine learning, variable selection and shrinkage methods," International Journal of Forecasting, Elsevier, vol. 34(2), pages 339-354.
- repec:zbw:bofitp:urn:nbn:fi:bof-201506091268 is not listed on IDEAS
- 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.
- Jo~ao B. Assunc{c}~ao & Pedro Afonso Fernandes, 2022. "Nowcasting the Portuguese GDP with Monthly Data," Papers 2206.06823, arXiv.org.
- Bańbura, Marta & Giannone, Domenico & Modugno, Michele & Reichlin, Lucrezia, 2013.
"Now-Casting and the Real-Time Data Flow,"
Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 195-237,
Elsevier.
- Martha Banbura & Domenico Giannone & Michèle Modugno & Lucrezia Reichlin, 2012. "Now-Casting and the Real-Time Data Flow," Working Papers ECARES ECARES 2012-026, ULB -- Universite Libre de Bruxelles.
- Reichlin, Lucrezia & Giannone, Domenico & Modugno, Michele & Banbura, Marta, 2012. "Now-casting and the real-time data flow," CEPR Discussion Papers 9112, C.E.P.R. Discussion Papers.
- Giannone, Domenico & Reichlin, Lucrezia & Bańbura, Marta & Modugno, Michele, 2013. "Now-casting and the real-time data flow," Working Paper Series 1564, European Central Bank.
- Philippe Goulet Coulombe, 2020. "The Macroeconomy as a Random Forest," Papers 2006.12724, arXiv.org, revised Mar 2021.
- Haase, Felix & Neuenkirch, Matthias, 2023.
"Predictability of bull and bear markets: A new look at forecasting stock market regimes (and returns) in the US,"
International Journal of Forecasting, Elsevier, vol. 39(2), pages 587-605.
- Felix Haase & Matthias Neuenkirch, 2020. "Predictability of Bull and Bear Markets: A New Look at Forecasting Stock Market Regimes (and Returns) in the US," Working Paper Series 2020-03, University of Trier, Research Group Quantitative Finance and Risk Analysis.
- Felix Haase & Matthias Neuenkirch, 2021. "Predictability of Bull and Bear Markets: A New Look at Forecasting Stock Market Regimes (and Returns) in the US," CESifo Working Paper Series 8828, CESifo.
- Felix Haase & Matthias Neuenkirch, 2020. "Predictability of Bull and Bear Markets: A New Look at Forecasting Stock Market Regimes (and Returns) in the US," Research Papers in Economics 2020-01, University of Trier, Department of Economics.
- Alessandro Girardi & Roberto Golinelli & Carmine Pappalardo, 2017.
"The role of indicator selection in nowcasting euro-area GDP in pseudo-real time,"
Empirical Economics, Springer, vol. 53(1), pages 79-99, August.
- A. Girardi & R. Golinelli & C. Pappalardo, 2014. "The Role of Indicator Selection in Nowcasting Euro Area GDP in Pseudo Real Time," Working Papers wp919, Dipartimento Scienze Economiche, Universita' di Bologna.
- Mogliani, Matteo & Simoni, Anna, 2021.
"Bayesian MIDAS penalized regressions: Estimation, selection, and prediction,"
Journal of Econometrics, Elsevier, vol. 222(1), pages 833-860.
- Matteo Mogliani & Anna Simoni, 2019. "Bayesian MIDAS Penalized Regressions: Estimation, Selection, and Prediction," Papers 1903.08025, arXiv.org, revised Jun 2020.
- Matteo Mogliani & Anna Simoni, 2020. "Bayesian MIDAS penalized regressions: Estimation, selection, and prediction," Post-Print hal-03089878, HAL.
- Matteo Mogliani, 2019. "Bayesian MIDAS penalized regressions: estimation, selection, and prediction," Working papers 713, Banque de France.
- Andrejs Bessonovs, 2015. "Suite of Latvia's GDP forecasting models," Working Papers 2015/01, Latvijas Banka.
- David Havrlant & Peter Tóth & Julia Wörz, 2016. "On the optimal number of indicators – nowcasting GDP growth in CESEE," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue 4, pages 54-72.
- Diaz, Elena Maria & Pérez Quirós, Gabriel, 2020.
"Daily tracker of global economic activity: a close-up of the COVID-19 pandemic,"
Working Paper Series
2505, European Central Bank.
- Pérez-Quirós, Gabriel & Diaz, Elena, 2020. "Daily Tracker of Global Economic Activity. A Close-Up of the Covid-19 Pandemic," CEPR Discussion Papers 15451, C.E.P.R. Discussion Papers.
- Chuliá, Helena & Garrón, Ignacio & Uribe, Jorge M., 2024.
"Daily growth at risk: Financial or real drivers? The answer is not always the same,"
International Journal of Forecasting, Elsevier, vol. 40(2), pages 762-776.
- Helena Chuliá & Ignacio Garrón & Jorge M. Uribe, 2022. ""Daily Growth at Risk: financial or real drivers? The answer is not always the same"," IREA Working Papers 202208, University of Barcelona, Research Institute of Applied Economics, revised Jun 2022.
- José R. Maria & Sara Serra, 2008. "Forecasting investment: A fishing contest using survey data," Working Papers w200818, Banco de Portugal, Economics and Research Department.
- Vasilios Plakandaras & Periklis Gogas & Theophilos Papadimitriou & Rangan Gupta, 2017.
"The Informational Content of the Term Spread in Forecasting the US Inflation Rate: A Nonlinear Approach,"
Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(2), pages 109-121, March.
- Periklis Gogas & Theophilos Papadimitriou & Vasilios Plakandaras & Rangan Gupta, 2015. "The Informational Content of the Term-Spread in Forecasting the U.S. Inflation Rate: A Nonlinear Approach," Working Papers 201548, University of Pretoria, Department of Economics.
- Gogas, Periklis & Papadimitriou, Theophilos & Plakandaras, Vasilios & Gupta, Rangan, 2019. "The Informational Content of the Term-Spread in Forecasting the U.S. Inflation Rate: A Nonlinear Approach," DUTH Research Papers in Economics 3-2016, Democritus University of Thrace, Department of Economics.
- 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.
- Zhang, Yaojie & Wang, Yudong, 2023. "Forecasting crude oil futures market returns: A principal component analysis combination approach," International Journal of Forecasting, Elsevier, vol. 39(2), pages 659-673.
- Rachida Ouysse, 2013. "Forecasting using a large number of predictors: Bayesian model averaging versus principal components regression," Discussion Papers 2013-04, School of Economics, The University of New South Wales.
- Ivan Savin & Peter Winker, 2012. "Lasso-type and Heuristic Strategies in Model Selection and Forecasting," Jena Economics Research Papers 2012-055, Friedrich-Schiller-University Jena.
- Ziwei Mei & Zhentao Shi, 2022. "On LASSO for High Dimensional Predictive Regression," Papers 2212.07052, arXiv.org, revised Jan 2024.
- Gupta, Rangan & Hammoudeh, Shawkat & Modise, Mampho P. & Nguyen, Duc Khuong, 2014.
"Can economic uncertainty, financial stress and consumer sentiments predict U.S. equity premium?,"
Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 33(C), pages 367-378.
- Rangan Gupta & Shawkat Hammoudeh & Mampho P. Modise & Duc Khuong Nguyen, 2013. "Can Economic Uncertainty, Financial Stress and Consumer Sentiments Predict U.S. Equity Premium?," Working Papers 2013-20, Department of Research, Ipag Business School.
- Rangan Gupta & Shawkat Hammoudeh & Mampho P. Modise & Duc Khuong Nguyen, 2013. "Can Economic Uncertainty, Financial Stress and Consumer Sentiments Predict U.S. Equity Premium?," Working Papers 201351, University of Pretoria, Department of Economics.
- Rangan Gupta & Shawkat Hammoudeh & Mampho P. Modise & Duc Khuong Nguyen, 2014. "Can Economic Uncertainty, Financial Stress and Consumer Senti-ments Predict U.S. Equity Premium?," Working Papers 2014-436, Department of Research, Ipag Business School.
- Marie Bessec & Othman Bouabdallah, 2015.
"Forecasting GDP over the Business Cycle in a Multi-Frequency and Data-Rich Environment,"
Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(3), pages 360-384, June.
- Bessec, M. & Bouabdallah, O., 2012. "Forecasting GDP over the business cycle in a multi-frequency and data-rich environment," Working papers 384, Banque de France.
- Marie Bessec & Othman Bouabdallah, 2015. "Forecasting GDP over the business cycle in a multi-frequency and data-rich environment," Post-Print hal-01275760, HAL.
- Jamie L. Cross & Bao H. Nguyen & Trung Duc Tran, 2022.
"The role of precautionary and speculative demand in the global market for crude oil,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 882-895, August.
- Jamie L. Cross & Bao H. Nguyen & Trung Duc Tran, 2020. "The role of precautionary and speculative demand in the global market for crude oil," CAMA Working Papers 2020-34, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Jamie L. Cross & Bao H. Nguyen & Trung Duc Tran, 2021. "The Role of Precautionary and Speculative Demand in the Global Market for Crude Oil," Working Papers No 06/2021, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
- Niu, Linlin & Xu, Xiu & Chen, Ying, 2017.
"An adaptive approach to forecasting three key macroeconomic variables for transitional China,"
Economic Modelling, Elsevier, vol. 66(C), pages 201-213.
- Niu, Linlin & Xu, Xiu & Chen, Ying, 2015. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," SFB 649 Discussion Papers 2015-023, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
- Niu, Linlin & Xu, Xiu & Chen, Ying, 2015. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," BOFIT Discussion Papers 12/2015, Bank of Finland Institute for Emerging Economies (BOFIT).
- Juan, Aranzazu de & Poncela, Maria Pilar, 2023. "Economic activity and C02 emissions in Spain," DES - Working Papers. Statistics and Econometrics. WS 37975, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
- Siliverstovs Boriss & Kholodilin Konstantin A., 2012.
"Assessing the Real-Time Informational Content of Macroeconomic Data Releases for Now-/Forecasting GDP: Evidence for Switzerland,"
Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 232(4), pages 429-444, August.
- Boriss Siliverstovs & Konstantin A. Kholodilin, 2010. "Assessing the Real-Time Informational Content of Macroeconomic Data Releases for Now-/Forecasting GDP: Evidence for Switzerland," Discussion Papers of DIW Berlin 970, DIW Berlin, German Institute for Economic Research.
- Akgun, Oguzhan & Pirotte, Alain & Urga, Giovanni, 2020.
"Forecasting using heterogeneous panels with cross-sectional dependence,"
International Journal of Forecasting, Elsevier, vol. 36(4), pages 1211-1227.
- Oguzhan Akgun & Alain Pirotte & Giovanni Urga, 2020. "Forecasting using heterogeneous panels with cross-sectional dependence," Post-Print hal-04120413, HAL.
- Matteo Luciani & Madhavi Pundit & Arief Ramayandi & Giovanni Veronese, 2018.
"Nowcasting Indonesia,"
Empirical Economics, Springer, vol. 55(2), pages 597-619, September.
- Matteo Luciani & Madhavi Pundit & Arief Ramayandi & Giovanni Veronese, 2015. "Nowcasting Indonesia," Finance and Economics Discussion Series 2015-100, Board of Governors of the Federal Reserve System (U.S.).
- Luciani, Matteo & Pundit, Madhavi & Ramayandi, Arief & Veronese , Giovanni, 2015. "Nowcasting Indonesia," ADB Economics Working Paper Series 471, Asian Development Bank.
- Ouyang, Ruolan & Pei, Tiancheng & Fang, Yi & Zhao, Yang, 2024. "Commodity systemic risk and macroeconomic predictions," Energy Economics, Elsevier, vol. 138(C).
- Julius Stakenas, 2012. "Generating short-term forecasts of the Lithuanian GDP using factor models," Bank of Lithuania Working Paper Series 13, Bank of Lithuania.
- Michael W. McCracken & Serena Ng, 2016.
"FRED-MD: A Monthly Database for Macroeconomic Research,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 574-589, October.
- Michael W. McCracken & Serena Ng, 2015. "FRED-MD: A Monthly Database for Macroeconomic Research," Working Papers 2015-12, Federal Reserve Bank of St. Louis.
- Kozyrev, Boris, 2024. "Forecast combination and interpretability using random subspace," IWH Discussion Papers 21/2024, Halle Institute for Economic Research (IWH).
- Christian Glocker & Philipp Wegmueller, 2020.
"Business cycle dating and forecasting with real-time Swiss GDP data,"
Empirical Economics, Springer, vol. 58(1), pages 73-105, January.
- Christian Glocker & Philipp Wegmüller, 2017. "Business Cycle Dating and Forecasting with Real-time Swiss GDP Data," WIFO Working Papers 542, WIFO.
- Norman R. Swanson & Weiqi Xiong, 2018.
"Big data analytics in economics: What have we learned so far, and where should we go from here?,"
Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 51(3), pages 695-746, August.
- Norman R. Swanson & Weiqi Xiong, 2018. "Big data analytics in economics: What have we learned so far, and where should we go from here?," Canadian Journal of Economics, Canadian Economics Association, vol. 51(3), pages 695-746, August.
- Shu, Lei & Lu, Feiyang & Chen, Yu, 2023. "Robust forecasting with scaled independent component analysis," Finance Research Letters, Elsevier, vol. 51(C).
- Diaz, Elena Maria & Perez-Quiros, Gabriel, 2021. "GEA tracker: A daily indicator of global economic activity," Journal of International Money and Finance, Elsevier, vol. 115(C).
- A. Belloni & D. Chen & V. Chernozhukov & C. Hansen, 2012.
"Sparse Models and Methods for Optimal Instruments With an Application to Eminent Domain,"
Econometrica, Econometric Society, vol. 80(6), pages 2369-2429, November.
- Alexandre Belloni & D. Chen & Victor Chernozhukov & Christian Hansen, 2010. "Sparse models and methods for optimal instruments with an application to eminent domain," CeMMAP working papers CWP31/10, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Alexandre Belloni & Daniel Chen & Victor Chernozhukov & Christian Hansen, 2010. "Sparse Models and Methods for Optimal Instruments with an Application to Eminent Domain," Papers 1010.4345, arXiv.org, revised Apr 2015.
- 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.
- Адилханова Зарина // Adilkhanova Zarina & Ержан Ислам // Yerzhan Islam, 2024. "Система селективно - комбинированного прогноза инфляции (SSCIF)// Selective-Combined Inflation Forecasting System," Working Papers #2024-13, National Bank of Kazakhstan.
- Chernis, Tony & Cheung, Calista & Velasco, Gabriella, 2020.
"A three-frequency dynamic factor model for nowcasting Canadian provincial GDP growth,"
International Journal of Forecasting, Elsevier, vol. 36(3), pages 851-872.
- Tony Chernis & Calista Cheung & Gabriella Velasco, 2017. "A Three-Frequency Dynamic Factor Model for Nowcasting Canadian Provincial GDP Growth," Discussion Papers 17-8, Bank of Canada.
- Dashan Huang & Fuwei Jiang & Kunpeng Li & Guoshi Tong & Guofu Zhou, 2022.
"Scaled PCA: A New Approach to Dimension Reduction,"
Management Science, INFORMS, vol. 68(3), pages 1678-1695, March.
- Dashan Huang & Fuwei Jiang & Kunpeng Li & Guoshi Tong & Guofu Zhou, 2022. "Scaled PCA: A New Approach to Dimension Reduction," CEMA Working Papers 678, China Economics and Management Academy, Central University of Finance and Economics.
- Marijn A Bolhuis & Judd N L Cramer & Lawrence H Summers, 2022.
"The Coming Rise in Residential Inflation [The repeat rent index],"
Review of Finance, European Finance Association, vol. 26(5), pages 1051-1072.
- Marijn A. Bolhuis & Judd N. L. Cramer & Lawrence H. Summers, 2022. "The Coming Rise in Residential Inflation," NBER Working Papers 29795, National Bureau of Economic Research, Inc.
- Ballarin, Giovanni & Dellaportas, Petros & Grigoryeva, Lyudmila & Hirt, Marcel & van Huellen, Sophie & Ortega, Juan-Pablo, 2024.
"Reservoir computing for macroeconomic forecasting with mixed-frequency data,"
International Journal of Forecasting, Elsevier, vol. 40(3), pages 1206-1237.
- Giovanni Ballarin & Petros Dellaportas & Lyudmila Grigoryeva & Marcel Hirt & Sophie van Huellen & Juan-Pablo Ortega, 2022. "Reservoir Computing for Macroeconomic Forecasting with Mixed Frequency Data," Papers 2211.00363, arXiv.org, revised Jan 2024.
- Zhang, Yaojie & Wahab, M.I.M. & Wang, Yudong, 2023. "Forecasting crude oil market volatility using variable selection and common factor," International Journal of Forecasting, Elsevier, vol. 39(1), pages 486-502.
- Marine Carrasco & Barbara Rossi, 2016.
"In-Sample Inference and Forecasting in Misspecified Factor Models,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(3), pages 313-338, July.
- Marine Carrasco & Barbara Rossi, 2016. "In-sample inference and forecasting in misspecified factor models," Economics Working Papers 1530, Department of Economics and Business, Universitat Pompeu Fabra.
- Rossi, Barbara & Carrasco, Marine, 2016. "In-sample Inference and Forecasting in Misspecified Factor Models," CEPR Discussion Papers 11388, C.E.P.R. Discussion Papers.
- Ciner, Cetin, 2019. "Do industry returns predict the stock market? A reprise using the random forest," The Quarterly Review of Economics and Finance, Elsevier, vol. 72(C), pages 152-158.
- Jonas E. Arias & Minchul Shin, 2020. "Tracking U.S. Real GDP Growth During the Pandemic," Economic Insights, Federal Reserve Bank of Philadelphia, vol. 5(3), pages 9-14, September.
- Simon Beyeler & Sylvia Kaufmann, 2021. "Reduced‐form factor augmented VAR—Exploiting sparsity to include meaningful factors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(7), pages 989-1012, November.
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