IDEAS home Printed from https://ideas.repec.org/f/c/plu244.html
   My authors  Follow this author

Matteo Luciani

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

RePEc Biblio mentions

As found on the RePEc Biblio, the curated bibliography of Economics:
  1. Matteo Luciani, 2015. "Monetary Policy and the Housing Market: A Structural Factor Analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(2), pages 199-218, March.

    Mentioned in:

    1. > Econometrics > Time Series Models > Dynamic Factor Models > Structural Factor Models
  2. 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.).

    Mentioned in:

    1. > Econometrics > Forecasting > Nowcasting
  3. Matteo Luciani & Lorenzo Ricci, 2014. "Nowcasting Norway," International Journal of Central Banking, International Journal of Central Banking, vol. 10(4), pages 215-248, December.

    Mentioned in:

    1. > Econometrics > Forecasting > Nowcasting

Working papers

  1. Matteo Barigozzi & Marc Hallin & Matteo Luciani & Paolo Zaffaroni, 2021. "Inferential Theory for Generalized Dynamic Factor Models," Working Papers ECARES 2021-20, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Matteo Barigozzi & Marc Hallin, 2024. "The Dynamic, the Static, and the Weak factor models and the analysis of high-dimensional time series," Papers 2407.10653, arXiv.org.
    2. Philipp Gersing, 2024. "A Distributed Lag Approach to the Generalised Dynamic Factor Model (GDFM)," Papers 2410.20885, arXiv.org.
    3. Philipp Gersing, 2024. "On the Existence of One-Sided Representations in the Generalised Dynamic Factor Model," Papers 2410.18159, arXiv.org.

  2. Matteo Luciani, 2020. "Common and Idiosyncratic Inflation," Finance and Economics Discussion Series 2020-024, Board of Governors of the Federal Reserve System (U.S.).

    Cited by:

    1. Yunjong Eo & Luis Uzeda & Benjamin Wong, 2022. "Understanding trend inflation through the lens of the goods and services sectors," CAMA Working Papers 2022-28, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    2. Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Working Papers 22-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
    3. 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.).
    4. Matteo Barigozzi & Marc Hallin & Matteo Luciani & Paolo Zaffaroni, 2021. "Inferential Theory for Generalized Dynamic Factor Models," Working Papers ECARES 2021-20, ULB -- Universite Libre de Bruxelles.
    5. Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Papers 2202.04146, arXiv.org, revised Oct 2024.
    6. Cristina Conflitti, 2020. "Alternative measures of underlying inflation in the euro area," Questioni di Economia e Finanza (Occasional Papers) 593, Bank of Italy, Economic Research and International Relations Area.

  3. Matteo Barigozzi & Matteo Luciani, 2019. "Quasi Maximum Likelihood Estimation of Non-Stationary Large Approximate Dynamic Factor Models," Papers 1910.09841, arXiv.org.

    Cited by:

    1. Matteo Barigozzi & Daniele Massacci, 2022. "Modelling Large Dimensional Datasets with Markov Switching Factor Models," Papers 2210.09828, arXiv.org, revised Dec 2024.
    2. Paolo Andreini & Cosimo Izzo & Giovanni Ricco, 2020. "Deep Dynamic Factor Models," Papers 2007.11887, arXiv.org, revised May 2023.
    3. 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.).
    4. 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).
    5. 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.
    6. 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).
    7. Matteo Barigozzi, 2023. "Asymptotic equivalence of Principal Components and Quasi Maximum Likelihood estimators in Large Approximate Factor Models," Papers 2307.09864, arXiv.org, revised Jun 2024.
    8. 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.
    9. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
    10. Matteo Barigozzi, 2023. "Quasi Maximum Likelihood Estimation of High-Dimensional Factor Models: A Critical Review," Papers 2303.11777, arXiv.org, revised May 2024.
    11. 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.
    12. Matteo Barigozzi & Marc Hallin & Matteo Luciani & Paolo Zaffaroni, 2021. "Inferential Theory for Generalized Dynamic Factor Models," Working Papers ECARES 2021-20, ULB -- Universite Libre de Bruxelles.
    13. Jianqing Fan & Kunpeng Li & Yuan Liao, 2020. "Recent Developments on Factor Models and its Applications in Econometric Learning," Papers 2009.10103, arXiv.org.
    14. Serena Ng & Susannah Scanlan, 2023. "Constructing High Frequency Economic Indicators by Imputation," Papers 2303.01863, arXiv.org, revised Oct 2023.
    15. Matteo Barigozzi & Angelo Cuzzola & Marco Grazzi & Daniele Moschella, 2021. "Factoring in the micro: a transaction-level dynamic factor approach to the decomposition of export volatility," LEM Papers Series 2021/22, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.

  4. 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.

    Cited by:

    1. Danilo Cascaldi-Garcia & Matteo Luciani & Michele Modugno, 2023. "Lessons from Nowcasting GDP across the World," International Finance Discussion Papers 1385, Board of Governors of the Federal Reserve System (U.S.).
    2. 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.).
    3. 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.
    4. 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).
    5. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
    6. Junfan Mao & Zhigen Gao & Bing-Yi Jing & Jianhua Guo, 2024. "On the statistical analysis of high-dimensional factor models," Statistical Papers, Springer, vol. 65(8), pages 4991-5019, October.
    7. Filippo Pellegrino, 2021. "Factor-augmented tree ensembles," Papers 2111.14000, arXiv.org, revised Jun 2023.
    8. Diego Fresoli & Pilar Poncela & Esther Ruiz, 2024. "Dealing with idiosyncratic cross-correlation when constructing confidence regions for PC factors," Papers 2407.06883, arXiv.org.

  5. Matteo Luciani & Riccardo Trezzi, 2019. "Comparing Two Measures of Core Inflation: PCE Excluding Food & Energy vs. the Trimmed Mean PCE Index," FEDS Notes 2019-08-02-1, Board of Governors of the Federal Reserve System (U.S.).

    Cited by:

    1. Helen Lao & Ceciline Steyn, 2019. "A Comprehensive Evaluation of Measures of Core Inflation in Canada: An Update," Discussion Papers 2019-9, Bank of Canada.
    2. Carlomagno, Guillermo & Fornero, Jorge & Sansone, Andrés, 2023. "A proposal for constructing and evaluating core inflation measures," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 4(3).
    3. Guillermo Carlomagno & Jorge Fornero & Andrés Sansone, 2021. "Toward a general framework for constructing and evaluating core inflation measures," Working Papers Central Bank of Chile 913, Central Bank of Chile.
    4. Behailu Shiferaw Benti, 2021. "Was the Interest Rate Policy of the ECB too Loose? Insight from a Simple Taylor Rule," Eurasian Journal of Economics and Finance, Eurasian Publications, vol. 9(1), pages 19-28.
    5. Nakagawa, Kei & Sakemoto, Ryuta, 2023. "Do commodity factors work as inflation hedges and safe havens?," Finance Research Letters, Elsevier, vol. 58(PD).
    6. Dietrich, Alexander M., 2023. "Consumption categories, household attention, and inflation expectations: Implications for optimal monetary policy," University of Tübingen Working Papers in Business and Economics 157, University of Tuebingen, Faculty of Economics and Social Sciences, School of Business and Economics.
    7. Cristina Conflitti, 2020. "Alternative measures of underlying inflation in the euro area," Questioni di Economia e Finanza (Occasional Papers) 593, Bank of Italy, Economic Research and International Relations Area.
    8. Randal J. Verbrugge, 2021. "Is It Time to Reassess the Focal Role of Core PCE Inflation?," Working Papers 21-10, Federal Reserve Bank of Cleveland.

  6. Matteo Barigozzi & Matteo Luciani, 2018. "Do National Account Statistics Underestimate US Real Output Growth?," FEDS Notes 2018-01-09-1, Board of Governors of the Federal Reserve System (U.S.).

    Cited by:

    1. Kenneth E. Poole & Allison Forbes & Nichelle Williams, 2023. "Applied Regional Economic Research Can Improve Development Strategies and Drive Better Outcomes," Economic Development Quarterly, , vol. 37(1), pages 85-95, February.
    2. Zheng Liu & Mark M. Spiegel & Eric Tallman, 2018. "Is GDP Overstating Economic Activity?," FRBSF Economic Letter, Federal Reserve Bank of San Francisco.

  7. Cristina Conflitti & Matteo Luciani, 2017. "Oil price pass-through into core inflation," Questioni di Economia e Finanza (Occasional Papers) 405, Bank of Italy, Economic Research and International Relations Area.

    Cited by:

    1. Adam Hale Shapiro, "undated". "Decomposing Supply and Demand Driven Inflation," RBA Annual Conference Papers acp2023-03, Reserve Bank of Australia, revised Nov 2023.
    2. Tersoo Shimonkabir Shitile & Nuruddeen Usman, 2020. "Disaggregated Inflation and Asymmetric Oil Price Pass-Through in Nigeria," International Journal of Energy Economics and Policy, Econjournals, vol. 10(1), pages 255-264.
    3. Kilian, Lutz & Zhou, Xiaoqing, 2023. "Oil Price Shocks and Inflation," CEPR Discussion Papers 18416, C.E.P.R. Discussion Papers.
    4. Lee, Chien-Chiang & Olasehinde-Williams, Godwin & Özkan, Oktay, 2023. "Geopolitical oil price uncertainty transmission into core inflation: Evidence from two of the biggest global players," Energy Economics, Elsevier, vol. 126(C).
    5. 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.).
    6. Lutz Kilian & Xiaoqing Zhou, 2020. "Oil Prices, Gasoline Prices and Inflation Expectations: A New Model and New Facts," CESifo Working Paper Series 8516, CESifo.
    7. Hakan Yilmazkuday, 2021. "Oil Price Pass-Through into Consumer Prices: Evidence from U.S. Weekly Data," Working Papers 2118, Florida International University, Department of Economics.
    8. Barigozzi, Matteo & Lippi, Marco & Luciani, Matteo, 2021. "Large-dimensional Dynamic Factor Models: Estimation of Impulse–Response Functions with I(1) cointegrated factors," Journal of Econometrics, Elsevier, vol. 221(2), pages 455-482.
    9. Francesco Corsello & Alex Tagliabracci, 2023. "Assessing the pass-through of energy prices to inflation in the euro area," Questioni di Economia e Finanza (Occasional Papers) 745, Bank of Italy, Economic Research and International Relations Area.
    10. Massimiliano Pisani & Alex Tagliabracci, 2024. "What caused the post-pandemic inflation in Italy? An application of Bernanke and Blanchard (2023)," Questioni di Economia e Finanza (Occasional Papers) 851, Bank of Italy, Economic Research and International Relations Area.
    11. Piergiorgio Alessandri & Andrea Gazzani, 2023. "Natural gas and the macroeconomy: not all energy shocks are alike," Temi di discussione (Economic working papers) 1428, Bank of Italy, Economic Research and International Relations Area.
    12. de Mendonça, Helder Ferreira & Garcia, Pedro Mendes, 2023. "Effects of oil shocks and central bank credibility on price diffusion," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 304-317.
    13. Kilian, Lutz & Zhou, Xiaoqing, 2021. "The impact of rising oil prices on U.S. inflation and inflation expectations in 2020-23," CFS Working Paper Series 670, Center for Financial Studies (CFS).
    14. Kilian, Lutz & Zhou, Xiaoqing, 2023. "A broader perspective on the inflationary effects of energy price shocks," CFS Working Paper Series 686, Center for Financial Studies (CFS).
    15. Salem, Leila Ben & Nouira, Ridha & Rault, Christophe, 2024. "On the Impact of Oil Prices on Sectoral Inflation: Evidence from World's Top Oil Exporters and Importers," IZA Discussion Papers 16706, Institute of Labor Economics (IZA).
    16. Grzegorz Przekota & Anna Szczepańska-Przekota, 2022. "Pro-Inflationary Impact of the Oil Market—A Study for Poland," Energies, MDPI, vol. 15(9), pages 1-19, April.
    17. Ekaterina Pirozhkova & Jeffrey Rakgalakane & Luchelle Soobyah & Rudi Steinbach, 2023. "Enhancing the Quarterly Projection Model," Working Papers 11048, South African Reserve Bank.
    18. Salisu, Afees A. & Ogbonna, Ahamuefula E. & Vo, Xuan Vinh, 2023. "Oil tail risks and the realized variance of consumer prices in advanced economies," Resources Policy, Elsevier, vol. 83(C).
    19. Stefano Neri & Fabio Busetti & Cristina Conflitti & Francesco Corsello & Davide Delle Monache & Alex Tagliabracci, 2023. "Energy price shocks and inflation in the euro area," Questioni di Economia e Finanza (Occasional Papers) 792, Bank of Italy, Economic Research and International Relations Area.
    20. Ekaterina Pirozhkova & Jeffrey Rakgalakane & Luchelle Soobyah Rudi Steinbach, 2023. "EnhancingtheQuarterlyProjectionModel," Working Papers 11044, South African Reserve Bank.
    21. Ozgur, Onder & Aydin, Levent & Karagol, Erdal Tanas & Ozbugday, Fatih Cemil, 2021. "The fuel price pass-through in Turkey: The case study of motor fuel price subsidy system," Energy, Elsevier, vol. 226(C).
    22. Cristina Conflitti, 2020. "Alternative measures of underlying inflation in the euro area," Questioni di Economia e Finanza (Occasional Papers) 593, Bank of Italy, Economic Research and International Relations Area.
    23. Adam Hale Shapiro, 2022. "Decomposing Supply and Demand Driven Inflation," Working Paper Series 2022-18, Federal Reserve Bank of San Francisco.
    24. Gertjan Vlieghe, 2024. "Core Strength: International Evidence on the Impact of Energy Prices on Core Inflation," Discussion Papers 2407, Centre for Macroeconomics (CFM).
    25. Chung, Changwoo & Kim, Jinsoo, 2024. "Greenflation, a myth or fact? Empirical evidence from 26 OECD countries," Energy Economics, Elsevier, vol. 139(C).
    26. Csaba BÁLINT, 2022. "Sectorial Price Shock Propagation via Input-Output Linkages," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 21-40, December.
    27. Чернявский Денис // Chernyavskiy Denis & Сейдахметов Ансар // Seidakhmetov Ansar, 2023. "Влияние повышения цен на горюче-смазочные материалы (ГСМ) на инфляцию: опыт Казахстана. // The impact of the increase in prices for fuels and lubricants on inflation: the experience of Kazakhstan," Working Papers #2023-6, National Bank of Kazakhstan.

  8. 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.).

    Cited by:

    1. Francisco Corona & Pilar Poncela & Esther Ruiz, 2020. "Estimating Non-stationary Common Factors: Implications for Risk Sharing," Computational Economics, Springer;Society for Computational Economics, vol. 55(1), pages 37-60, January.

  9. Matteo Barigozzi & Marco Lippi & Matteo Luciani, 2016. "Non-Stationary Dynamic Factor Models for Large Datasets," Finance and Economics Discussion Series 2016-024, Board of Governors of the Federal Reserve System (U.S.).

    Cited by:

    1. Alessi, Lucia & Kerssenfischer, Mark, 2016. "The response of asset prices to monetary policy shocks: stronger than thought," Working Paper Series 1967, European Central Bank.
    2. Cristina Conflitti and Matteo Luciani, 2019. "Oil Price Pass-through into Core Inflation," The Energy Journal, International Association for Energy Economics, vol. 0(Number 6).
    3. Kose, M. Ayhan & Ha, Jongrim & Ohnsorge, Franziska, 2021. "One-Stop Source: A Global Database of Inflation," CEPR Discussion Papers 16327, C.E.P.R. Discussion Papers.
    4. Francisco Corona & Graciela González-Farías & Pedro Orraca, 2017. "A dynamic factor model for the Mexican economy: are common trends useful when predicting economic activity?," Latin American Economic Review, Springer;Centro de Investigaciòn y Docencia Económica (CIDE), vol. 26(1), pages 1-35, December.
    5. Panagiotidis, Theodore & Printzis, Panagiotis, 2020. "What is the investment loss due to uncertainty?," Global Finance Journal, Elsevier, vol. 45(C).
    6. 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.).
    7. Panagiotidis, Theodore & Printzis, Panagiotis, 2021. "Investment and uncertainty: Are large firms different from small ones?," Journal of Economic Behavior & Organization, Elsevier, vol. 184(C), pages 302-317.
    8. Hsiang-Hsi Liu & Chien-Kuo Tseng, 2022. "Common Components in Co-integrated System and Its Estimation and Application: Evidence from Five Stock Markets in Asia-Pacific Chinese Region," Bulletin of Applied Economics, Risk Market Journals, vol. 9(2), pages 101-121.
    9. 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.
    10. Lenza, Michele & Cimadomo, Jacopo & Giannone, Domenico & Monti, Francesca & Sokol, Andrej, 2021. "Nowcasting with Large Bayesian Vector Autoregressions," CEPR Discussion Papers 15854, C.E.P.R. Discussion Papers.
    11. Maxime Leroux & Rachidi Kotchoni & Dalibor Stevanovic, 2017. "Forecasting economic activity in data-rich environment," Working Papers hal-04141668, HAL.
    12. Francisco Corona & Pilar Poncela & Esther Ruiz, 2020. "Estimating Non-stationary Common Factors: Implications for Risk Sharing," Computational Economics, Springer;Society for Computational Economics, vol. 55(1), pages 37-60, January.
    13. Martina Hengge & Seton Leonard, 2017. "Factor Models for Non-Stationary Series: Estimates of Monthly U.S. GDP," IHEID Working Papers 13-2017, Economics Section, The Graduate Institute of International Studies.
    14. Smeekes, Stephan & Wijler, Etiënne, 2016. "Macroeconomic Forecasting Using Penalized Regression Methods," Research Memorandum 039, Maastricht University, Graduate School of Business and Economics (GSBE).
    15. Ergemen, Yunus Emre, 2023. "Parametric estimation of long memory in factor models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1483-1499.
    16. Matteo Barigozzi & Marco Lippi & Matteo Luciani, 2016. "Dynamic Factor Models, Cointegration, and Error Correction Mechanisms," Finance and Economics Discussion Series 2016-018, Board of Governors of the Federal Reserve System (U.S.).

  10. 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.).

    Cited by:

    1. Danilo Cascaldi-Garcia & Matteo Luciani & Michele Modugno, 2023. "Lessons from Nowcasting GDP across the World," International Finance Discussion Papers 1385, Board of Governors of the Federal Reserve System (U.S.).
    2. Yose Rizal Damuri & Prabaning Tyas & Haryo Aswicahyono & Lionel Priyadi & Stella Kusumawardhani & Ega Kurnia Yazid, 2021. "Tracking the Ups and Downs in Indonesia’s Economic Activity During COVID-19 Using Mobility Index: Evidence from Provinces in Java and Bali," Working Papers DP-2021-18, Economic Research Institute for ASEAN and East Asia (ERIA).
    3. Daniela Bragoli & Michele Modugno, 2016. "A Nowcasting Model for Canada: Do U.S. Variables Matter?," Finance and Economics Discussion Series 2016-036, Board of Governors of the Federal Reserve System (U.S.).
    4. Bragoli, Daniela, 2017. "Now-casting the Japanese economy," International Journal of Forecasting, Elsevier, vol. 33(2), pages 390-402.
    5. Bantis, Evripidis & Clements, Michael P. & Urquhart, Andrew, 2023. "Forecasting GDP growth rates in the United States and Brazil using Google Trends," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1909-1924.
    6. Tingguo Zheng & Xinyue Fan & Wei Jin & Kuangnan Fang, 2024. "Forecasting CPI with multisource data: The value of media and internet information," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(3), pages 702-753, April.
    7. Dahlhaus, Tatjana & Guénette, Justin-Damien & Vasishtha, Garima, 2017. "Nowcasting BRIC+M in real time," International Journal of Forecasting, Elsevier, vol. 33(4), pages 915-935.
    8. Tony Chernis & Rodrigo Sekkel, 2017. "A dynamic factor model for nowcasting Canadian GDP growth," Empirical Economics, Springer, vol. 53(1), pages 217-234, August.
    9. Soybilgen, Barış & Yazgan, Ege, 2018. "Evaluating nowcasts of bridge equations with advanced combination schemes for the Turkish unemployment rate," Economic Modelling, Elsevier, vol. 72(C), pages 99-108.
    10. Bhadury, Soumya & Ghosh, Saurabh & Kumar, Pankaj, 2019. "Nowcasting GDP Growth Using a Coincident Economic Indicator for India," MPRA Paper 96007, University Library of Munich, Germany.
    11. Modugno, Michele & Soybilgen, Barış & Yazgan, Ege, 2016. "Nowcasting Turkish GDP and news decomposition," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1369-1384.
    12. Oguzhan Cepni & I. Ethem Guney & Norman R. Swanson, 2020. "Forecasting and nowcasting emerging market GDP growth rates: The role of latent global economic policy uncertainty and macroeconomic data surprise factors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(1), pages 18-36, January.
    13. Caruso, Alberto, 2018. "Nowcasting with the help of foreign indicators: The case of Mexico," Economic Modelling, Elsevier, vol. 69(C), pages 160-168.
    14. Cepni, Oguzhan & Güney, I. Ethem & Swanson, Norman R., 2019. "Nowcasting and forecasting GDP in emerging markets using global financial and macroeconomic diffusion indexes," International Journal of Forecasting, Elsevier, vol. 35(2), pages 555-572.
    15. 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.
    16. González-Astudillo, Manuel & Baquero, Daniel, 2019. "A nowcasting model for Ecuador: Implementing a time-varying mean output growth," Economic Modelling, Elsevier, vol. 82(C), pages 250-263.

  11. Dungey, Mardi & Luciani, Matteo & Matei, Marius & Veredas, David, 2015. "Surfing through the GFC: systemic risk in Australia," Working Papers 2015-01, University of Tasmania, Tasmanian School of Business and Economics.

    Cited by:

    1. Raisul Islam & Vladimir Volkov, 2022. "Contagion or interdependence? Comparing spillover indices," Empirical Economics, Springer, vol. 63(3), pages 1403-1455, September.
    2. Xin Yan & Min Chen & Mu-Yen Chen, 2019. "Coupling and Coordination Development of Australian Energy, Economy, and Ecological Environment Systems from 2007 to 2016," Sustainability, MDPI, vol. 11(23), pages 1-13, November.
    3. Baumöhl, Eduard & Bouri, Elie & Hoang, Thi-Hong-Van & Shahzad, Syed Jawad Hussain & Výrost, Tomáš, 2020. "Increasing systemic risk during the Covid-19 pandemic: A cross-quantilogram analysis of the banking sector," EconStor Preprints 222580, ZBW - Leibniz Information Centre for Economics.
    4. Baumöhl, Eduard & Bouri, Elie & Hoang, Thi-Hong-Van & Hussain Shahzad, Syed Jawad & Výrost, Tomáš, 2022. "Measuring systemic risk in the global banking sector: A cross-quantilogram network approach," Economic Modelling, Elsevier, vol. 109(C).
    5. Christina Bui, 2018. "Bank Regulation and Financial Stability," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 5-2018, January-A.
    6. Bui, Christina & Scheule, Harald & Wu, Eliza, 2017. "The value of bank capital buffers in maintaining financial system resilience," Journal of Financial Stability, Elsevier, vol. 33(C), pages 23-40.
    7. Fijorek, Kamil & Jurkowska, Aleksandra & Jonek-Kowalska, Izabela, 2021. "Financial contagion between the financial and the mining industries – Empirical evidence based on the symmetric and asymmetric CoVaR approach," Resources Policy, Elsevier, vol. 70(C).
    8. Anufriev, Mikhail & Panchenko, Valentyn, 2015. "Connecting the dots: Econometric methods for uncovering networks with an application to the Australian financial institutions," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 241-255.
    9. Dungey, Mardi & Luciani, Matteo & Veredas, David, 2018. "Systemic risk in the US: Interconnectedness as a circuit breaker," Economic Modelling, Elsevier, vol. 71(C), pages 305-315.
    10. Rahman, Md Lutfur & Troster, Victor & Uddin, Gazi Salah & Yahya, Muhammad, 2022. "Systemic risk contribution of banks and non-bank financial institutions across frequencies: The Australian experience," International Review of Financial Analysis, Elsevier, vol. 79(C).
    11. Islam, Raisul & Volkov, Vladimir, 2020. "Contagion or interdependence? Comparing signed and unsigned spillovers," Working Papers 2020-05, University of Tasmania, Tasmanian School of Business and Economics.
    12. Van Cauwenberge, Annelies & Vancauteren, Mark & Braekers, Roel & Vandemaele, Sigrid, 2019. "International trade, foreign direct investments, and firms’ systemic risk : Evidence from the Netherlands," Economic Modelling, Elsevier, vol. 81(C), pages 361-386.
    13. Rösch, Daniel & Scheule, Harald, 2016. "The role of loan portfolio losses and bank capital for Asian financial system resilience," Pacific-Basin Finance Journal, Elsevier, vol. 40(PB), pages 289-305.

  12. Matteo Barigozzi & Marco Lippi & Matteo Luciani, 2014. "Dynamic Factor Models, Cointegration and Error Correction Mechanisms," Working Papers ECARES ECARES 2014-14, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Soccorsi, Stefano, 2016. "Measuring nonfundamentalness for structural VARs," Journal of Economic Dynamics and Control, Elsevier, vol. 71(C), pages 86-101.
    2. 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.).
    3. Matteo Barigozzi & Marco Lippi & Matteo Luciani, 2016. "Non-Stationary Dynamic Factor Models for Large Datasets," Finance and Economics Discussion Series 2016-024, Board of Governors of the Federal Reserve System (U.S.).
    4. Francisco Corona & Pilar Poncela & Esther Ruiz, 2020. "Estimating Non-stationary Common Factors: Implications for Risk Sharing," Computational Economics, Springer;Society for Computational Economics, vol. 55(1), pages 37-60, January.
    5. Martina Hengge & Seton Leonard, 2017. "Factor Models for Non-Stationary Series: Estimates of Monthly U.S. GDP," IHEID Working Papers 13-2017, Economics Section, The Graduate Institute of International Studies.
    6. Carlo A. Favero & Alessandro Melone, 2019. "Asset Pricing vs Asset Expected Returning in Factor Models," Working Papers 651, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    7. Smeekes, Stephan & Wijler, Etiënne, 2016. "Macroeconomic Forecasting Using Penalized Regression Methods," Research Memorandum 039, Maastricht University, Graduate School of Business and Economics (GSBE).

  13. Matteo Luciani & Lorenzo Ricci, 2013. "Nowcasting Norway," Working Papers ECARES ECARES 2013-10, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Antonello D'Agostino & Domenico Giannone & Michele Lenza & Michele Modugno, 2015. "Nowcasting Business Cycles: a Bayesian Approach to Dynamic Heterogeneous Factor Models," Finance and Economics Discussion Series 2015-66, Board of Governors of the Federal Reserve System (U.S.).
    2. Christopher McDonald & Craig Thamotheram & Shaun P. Vahey & Elizabeth C. Wakerly, 2016. "Assessing the economic value of probabilistic forecasts in the presence of an inflation target," CAMA Working Papers 2016-40, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    3. Katja Drechsel & Rolf Scheufele, 2012. "Bottom-up or Direct? Forecasting German GDP in a Data-rich Environment," Working Papers 2012-16, Swiss National Bank.
    4. Daniela Bragoli & Michele Modugno, 2016. "A Nowcasting Model for Canada: Do U.S. Variables Matter?," Finance and Economics Discussion Series 2016-036, Board of Governors of the Federal Reserve System (U.S.).
    5. Nima Nonejad, 2021. "Crude oil price point forecasts of the Norwegian GDP growth rate," Empirical Economics, Springer, vol. 61(5), pages 2913-2930, November.
    6. Bragoli, Daniela, 2017. "Now-casting the Japanese economy," International Journal of Forecasting, Elsevier, vol. 33(2), pages 390-402.
    7. Knut Are Aastveit & Tuva Marie Fastbø & Eleonora Granziera & Kenneth Sæterhagen Paulsen & Kjersti Næss Torstensen, 2020. "Nowcasting Norwegian household consumption with debit card transaction data," Working Paper 2020/17, Norges Bank.
    8. 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.
    9. Simona Delle Chiaie & Laurent Ferrara & Domenico Giannone, 2022. "Common factors of commodity prices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(3), pages 461-476, April.
    10. 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.).
    11. Antolin-Diaz, Juan & Drechsel, Thomas & Petrella, Ivan, 2017. "Tracking the slowdown in long-run GDP growth," LSE Research Online Documents on Economics 81869, London School of Economics and Political Science, LSE Library.
    12. Luciani, Matteo & Pundit, Madhavi & Ramayandi, Arief & Veronese , Giovanni, 2015. "Nowcasting Indonesia," ADB Economics Working Paper Series 471, Asian Development Bank.
    13. Dahlhaus, Tatjana & Guénette, Justin-Damien & Vasishtha, Garima, 2017. "Nowcasting BRIC+M in real time," International Journal of Forecasting, Elsevier, vol. 33(4), pages 915-935.
    14. Tony Chernis & Rodrigo Sekkel, 2017. "A dynamic factor model for nowcasting Canadian GDP growth," Empirical Economics, Springer, vol. 53(1), pages 217-234, August.
    15. Petrella, Ivan & Drechsel, Thomas & Antolin-Diaz, Juan, 2014. "Following the Trend: Tracking GDP when Long-Run Growth is Uncertain," CEPR Discussion Papers 10272, C.E.P.R. Discussion Papers.
    16. Danilo Cascaldi-Garcia & Thiago Revil T. Ferreira & Domenico Giannone & Michele Modugno, 2021. "Back to the Present: Learning about the Euro Area through a Now-casting Model," International Finance Discussion Papers 1313, Board of Governors of the Federal Reserve System (U.S.).
    17. Daniel Kaufmann & Rolf Scheufele, 2015. "Business tendency surveys and macroeconomic fluctuations," KOF Working papers 15-378, KOF Swiss Economic Institute, ETH Zurich.
    18. Caruso, Alberto, 2018. "Nowcasting with the help of foreign indicators: The case of Mexico," Economic Modelling, Elsevier, vol. 69(C), pages 160-168.
    19. Alberto Caruso, 2015. "Nowcasting Mexican GDP," Working Papers ECARES ECARES 2015-40, ULB -- Universite Libre de Bruxelles.
    20. Cepni, Oguzhan & Güney, I. Ethem & Swanson, Norman R., 2019. "Nowcasting and forecasting GDP in emerging markets using global financial and macroeconomic diffusion indexes," International Journal of Forecasting, Elsevier, vol. 35(2), pages 555-572.
    21. 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.
    22. Camila Figueroa S. & Michael Pedersen, 2019. "Extracting information on economic activity from business and consumer surveys in an emerging economy (Chile)," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 22(3), pages 098-131, December.
    23. Jack Fosten & Daniel Gutknecht, 2021. "Horizon confidence sets," Empirical Economics, Springer, vol. 61(2), pages 667-692, August.
    24. 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.

  14. Matteo Barigozzi & Antonio M. Conti & Matteo Luciani, 2013. "Do euro area countries respond asymmetrically to the common monetary policy?," Temi di discussione (Economic working papers) 923, Bank of Italy, Economic Research and International Relations Area.

    Cited by:

    1. Kerssenfischer, Mark, 2017. "The effects of US monetary policy shocks: Applying external instrument identification to a dynamic factor model," Discussion Papers 08/2017, Deutsche Bundesbank.
    2. Jackson, Laura E. & Owyang, Michael T. & Zubairy, Sarah, 2018. "Debt and stabilization policy: Evidence from a Euro Area FAVAR," Journal of Economic Dynamics and Control, Elsevier, vol. 93(C), pages 67-91.
    3. Christophe Blot & Jérôme Creel & Bruno Ducoudre & Xavier Timbeau, 2015. "Back to fiscal consolidation in Europe and its dual tradeoff : now or later, through spending cuts or tax hikes ?," Working Papers hal-01143545, HAL.
    4. Mattia Guerini & Duc Thi Luu & Mauro Napoletano, 2019. "Synchronization Patterns in the European Union," GREDEG Working Papers 2019-30, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France.
    5. Akbari Dehbaghi, Simin & Arman, Seyed Aziz & Ahangari, Majid, 2020. "The Impact of Domestic and Foreign Monetary Policy on Iran\'s economy: Global Modeling," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 15(2), pages 151-180, April.
    6. Jung, Alexander & Carcel Villanova, Hector, 2020. "The empirical properties of euro area M3, 1980-2017," The Quarterly Review of Economics and Finance, Elsevier, vol. 77(C), pages 37-49.
    7. Andrea Colabella, 2019. "Do the ECB’s monetary policies benefit emerging market economies? A GVAR analysis on the crisis and post-crisis period," Temi di discussione (Economic working papers) 1207, Bank of Italy, Economic Research and International Relations Area.
    8. Marco Flaccadoro, 2022. "Exchange rate pass-through in small, open, commodity-exporting economies: lessons from Canada," Temi di discussione (Economic working papers) 1368, Bank of Italy, Economic Research and International Relations Area.
    9. Christophe Blot & Marion Cochard & Jérôme Creel & Bruno Ducoudré & Danielle Schweisguth & Xavier Timbeau, 2014. "Fiscal Consolidation, Public Debt and Output Dynamics in the Euro Area: lessons from a simple model with time-varying fiscal multipliers," Revue d'économie politique, Dalloz, vol. 124(6), pages 953-989.
    10. Potjagailo, Galina & Wolters, Maik H., 2019. "Global financial cycles since 1880," IMFS Working Paper Series 132, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
    11. von Borstel, Julia & Eickmeier, Sandra & Krippner, Leo, 2016. "The interest rate pass-through in the euro area during the sovereign debt crisis," Journal of International Money and Finance, Elsevier, vol. 68(C), pages 386-402.
    12. Potjagailo, Galina, 2017. "Spillover effects from Euro area monetary policy across Europe: A factor-augmented VAR approach," Journal of International Money and Finance, Elsevier, vol. 72(C), pages 127-147.
    13. Barigozzi, Matteo & Lippi, Marco & Luciani, Matteo, 2021. "Large-dimensional Dynamic Factor Models: Estimation of Impulse–Response Functions with I(1) cointegrated factors," Journal of Econometrics, Elsevier, vol. 221(2), pages 455-482.
    14. Christophe Blot & Jérôme Creel & Paul Hubert & Fabien Labondance, 2016. "The impact of ECB policies on Euro area investment," Working Papers hal-03459319, HAL.
    15. Matteo Farnè & Angelos T. Vouldis, 2021. "Banks’ business models in the euro area: a cluster analysis in high dimensions," Annals of Operations Research, Springer, vol. 305(1), pages 23-57, October.
    16. Matteo Barigozzi & Marco Lippi & Matteo Luciani, 2016. "Non-Stationary Dynamic Factor Models for Large Datasets," Finance and Economics Discussion Series 2016-024, Board of Governors of the Federal Reserve System (U.S.).
    17. Bagnai, Alberto & Granville, Brigitte & Mongeau Ospina, Christian A., 2017. "Withdrawal of Italy from the euro area: Stochastic simulations of a structural macroeconometric model," Economic Modelling, Elsevier, vol. 64(C), pages 524-538.
    18. Badinger, Harald & Schiman, Stefan, 2020. "Measuring Monetary Policy with Residual Sign Restrictions at Known Shock Dates," Department of Economics Working Paper Series 300, WU Vienna University of Economics and Business.
    19. Giancarlo Corsetti & Joao B. Duarte & Samuel Mann, 2018. "One Money, Many Markets," Discussion Papers 1805, Centre for Macroeconomics (CFM).
    20. Mario Forni & Luca Gambetti & marco Lippi & Luca Sala, 2020. "Common Components Structural VARs," Center for Economic Research (RECent) 147, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
    21. Matteo Barigozzi & Claudio Lissona & Lorenzo Tonni, 2024. "Large datasets for the Euro Area and its member countries and the dynamic effects of the common monetary policy," Papers 2410.05082, arXiv.org.
    22. Georgios Georgiadis & Martina Jancokova, 2017. "Financial Globalisation, Monetary Policy Spillovers and Macro-modelling: Tales from 1001 Shocks," Globalization Institute Working Papers 314, Federal Reserve Bank of Dallas.
    23. Mandler, Martin & Scharnagl, Michael & Volz, Ute, 2016. "Heterogeneity in euro-area monetary policy transmission: Results from a large multi-country BVAR model," Discussion Papers 03/2016, Deutsche Bundesbank.
    24. Sergio Destefanis & Matteo Fragetta & Emanuel Gasteiger, 2024. "Does one size fit all in the Euro Area? Some counterfactual evidence," Empirical Economics, Springer, vol. 67(4), pages 1615-1647, October.
    25. Norhana Endut & James Morley & Pao-Lin Tien, 2015. "The Changing Transmission Mechanism of U.S. Monetary Policy," Discussion Papers 2015-03, School of Economics, The University of New South Wales.
    26. Juho Koistinen & Bernd Funovits, 2022. "Estimation of Impulse-Response Functions with Dynamic Factor Models: A New Parametrization," Papers 2202.00310, arXiv.org, revised Feb 2022.
    27. Cavallo, Antonella & Ribba, Antonio, 2015. "Common macroeconomic shocks and business cycle fluctuations in Euro area countries," International Review of Economics & Finance, Elsevier, vol. 38(C), pages 377-392.
    28. Thomas Lux & Duc Thi Luu & Boyan Yanovski, 2020. "An analysis of systemic risk in worldwide economic sentiment indices," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 47(4), pages 909-928, November.
    29. Xing, Xiaoyun & Wang, Mingsong & Wang, Yougui & Stanley, H. Eugene, 2020. "Credit creation under multiple banking regulations: The impact of balance sheet diversity on money supply," Economic Modelling, Elsevier, vol. 91(C), pages 720-735.
    30. Simona Hašková & Marek Vochozka, 2018. "Duality in Cyclical Trends in European Union Confirmed," SAGE Open, , vol. 8(1), pages 21582440177, January.
    31. Hanisch, Max & Kempa, Bernd, 2017. "The international transmission channels of US supply and demand shocks: Evidence from a non-stationary dynamic factor model for the G7 countries," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 70-88.
    32. Petrovska Magdalena & Tonovska Jasna & Nikolov Miso & Sulejmani Artan, 2022. "Evaluating Monetary Policy Effectiveness in North Macedonia: Evidence from a Bayesian Favar Framework," South East European Journal of Economics and Business, Sciendo, vol. 17(2), pages 67-82, December.
    33. Corsetti, Giancarlo & Duarte, Joao B. & Mann, Samuel, 2018. "One money, many markets: a factor model approach to monetary policy in the Euro Area with high-frequency identification," LSE Research Online Documents on Economics 87182, London School of Economics and Political Science, LSE Library.
    34. Geiger, Martin & Gründler, Daniel & Scharler, Johann, 2023. "Monetary policy shocks and consumer expectations in the euro area," Journal of International Economics, Elsevier, vol. 140(C).
    35. Gabe de Bondt, 2017. "Confidence and monetary policy transmission," EcoMod2017 10197, EcoMod.
    36. Stefano Neri & Tiziano Ropele, 2015. "The macroeconomic effects of the sovereign debt crisis in the euro area," Temi di discussione (Economic working papers) 1007, Bank of Italy, Economic Research and International Relations Area.
    37. Roy, Ripon & Bashar, Omar H.N.M. & Bhattacharya, Prasad Sankar, 2023. "The cross-industry effects of monetary policy: New evidence from Bangladesh," Economic Modelling, Elsevier, vol. 127(C).
    38. Florian Huber & Michael Pfarrhofer & Philipp Piribauer, 2020. "A multi‐country dynamic factor model with stochastic volatility for euro area business cycle analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 911-926, September.
    39. Pestova, Anna, 2020. "“Credit view” on monetary policy in Russia," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 57, pages 72-88.
    40. Michael Pfarrhofer & Anna Stelzer, 2019. "High-frequency and heteroskedasticity identification in multicountry models: Revisiting spillovers of monetary shocks," Papers 1912.03158, arXiv.org, revised Dec 2024.
    41. Potjagailo, Galina, 2016. "Spillover effects from euro area monetary policy across the EU: A factor-augmented VAR approach," Kiel Working Papers 2033, Kiel Institute for the World Economy (IfW Kiel).
    42. Max Hanisch, 2017. "US Monetary Policy and the Euro Area," Discussion Papers of DIW Berlin 1701, DIW Berlin, German Institute for Economic Research.
    43. Hristov, Nikolay & Huelsewig, Oliver & Siemsen, Thomas & Wollmershaeuser, Timo, 2019. "Restoring euro area monetary transmission: Which role for government bond rates?," Munich Reprints in Economics 78269, University of Munich, Department of Economics.
    44. Zhu, Bing & Betzinger, Michael & Sebastian, Steffen, 2017. "Housing market stability, mortgage market structure, and monetary policy: Evidence from the euro area," Journal of Housing Economics, Elsevier, vol. 37(C), pages 1-21.
    45. Corsetti, Giancarlo & Duarte, Joao B. & Mann, Samuel, 2020. "One Money, Many Markets: Monetary Transmission and Housing Financing in the Euro Area," CEPR Discussion Papers 14968, C.E.P.R. Discussion Papers.
    46. Ayla OguÅŸ Binatli & Niloufer Sohrabji, 2019. "Monetary Policy Transmission in the Euro Zone," Athens Journal of Business & Economics, Athens Institute for Education and Research (ATINER), vol. 5(1), pages 79-92, January.
    47. Conti, Antonio M., 2021. "Resurrecting the Phillips Curve in Low-Inflation Times," Economic Modelling, Elsevier, vol. 96(C), pages 172-195.
    48. Hanisch, Max, 2019. "US monetary policy and the euro area," Journal of Banking & Finance, Elsevier, vol. 100(C), pages 77-96.
    49. Neri, Stefano & Nobili, Andrea & Conti, Antonio M., 2017. "Low inflation and monetary policy in the euro area," Working Paper Series 2005, European Central Bank.
    50. Krokida, Styliani-Iris & Makrychoriti, Panagiota & Spyrou, Spyros, 2020. "Monetary policy and herd behavior: International evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 170(C), pages 386-417.
    51. Andrea Colabella, 2021. "Do ECB's Monetary Policies Benefit EMEs? A GVAR Analysis on the Global Financial and Sovereign Debt Crises and Postcrises Period," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(2), pages 472-494, April.
    52. Matteo Barigozzi & Marco Lippi & Matteo Luciani, 2016. "Dynamic Factor Models, Cointegration, and Error Correction Mechanisms," Finance and Economics Discussion Series 2016-018, Board of Governors of the Federal Reserve System (U.S.).
    53. Matteo Barigozzi & Marco Lippi & Matteo Luciani, 2020. "Cointegration and Error Correction Mechanisms for Singular Stochastic Vectors," Econometrics, MDPI, vol. 8(1), pages 1-23, February.
    54. Karim Triki, 2016. "Expenditure-based Consolidation: Experiences and Outcomes – Workshop proceedings," European Economy - Discussion Papers 026, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    55. Alberto Caruso, 2016. "The Impact of Macroeconomic News on the Euro-Dollar Exchange Rate," Working Papers ECARES ECARES 2016-32, ULB -- Universite Libre de Bruxelles.
    56. Lukas Berend & Jan Pruser, 2024. "The Transmission of Monetary Policy via Common Cycles in the Euro Area," Papers 2410.05741, arXiv.org, revised Nov 2024.
    57. Theron Shumba & Sophia Mukorera, 2023. "Monetary Policy Implications on Macroeconomic Performance in the Common Monetary Area: A Panel-SVAR Framework," Economies, MDPI, vol. 11(5), pages 1-18, May.
    58. Emter, Lorenz & Setzer, Ralph & Zorell, Nico & Moura, Afonso S., 2024. "Monetary policy and growth-at-risk: the role of institutional quality," Working Paper Series 2989, European Central Bank.
    59. Hanisch, Max, 2017. "The effectiveness of conventional and unconventional monetary policy: Evidence from a structural dynamic factor model for Japan," Journal of International Money and Finance, Elsevier, vol. 70(C), pages 110-134.
    60. Ute Volz & Martin Mandler & Michael Scharnagl, 2016. "Heterogeneity in Euro Area Monetary Policy Transmission: Results from a large Multi-Country BVAR," EcoMod2016 9609, EcoMod.

  15. Matteo Luciani & Libero Monteforte, 2013. "Uncertainty and heterogeneity in factor models forecasting," Temi di discussione (Economic working papers) 930, Bank of Italy, Economic Research and International Relations Area.

    Cited by:

    1. M. Caivano & A. Harvey, 2013. "Two EGARCH models and one fat tail," Cambridge Working Papers in Economics 1326, Faculty of Economics, University of Cambridge.

  16. Matteo Luciani, 2012. "Monetary Policy and the Housing Market: A Structural Factor Analysis," Working Papers ECARES ECARES 2012-035, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Alessi, Lucia & Kerssenfischer, Mark, 2016. "The response of asset prices to monetary policy shocks: stronger than thought," Working Paper Series 1967, European Central Bank.
    2. Kerssenfischer, Mark, 2017. "The effects of US monetary policy shocks: Applying external instrument identification to a dynamic factor model," Discussion Papers 08/2017, Deutsche Bundesbank.
    3. Poncela, Pilar, 2021. "Dynamic factor models: does the specification matter?," DES - Working Papers. Statistics and Econometrics. WS 32210, Universidad Carlos III de Madrid. Departamento de Estadística.
    4. Cristina Conflitti and Matteo Luciani, 2019. "Oil Price Pass-through into Core Inflation," The Energy Journal, International Association for Energy Economics, vol. 0(Number 6).
    5. Daniel A. Dias & João B. Duarte, 2019. "Monetary policy, housing rents, and inflation dynamics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(5), pages 673-687, August.
    6. Bańbura, Marta & Giannone, Domenico & Lenza, Michele, 2015. "Conditional forecasts and scenario analysis with vector autoregressions for large cross-sections," International Journal of Forecasting, Elsevier, vol. 31(3), pages 739-756.
    7. Luciana Juvenal & Ivan Petrella, 2012. "Speculation in the oil market," Economic Synopses, Federal Reserve Bank of St. Louis.
    8. Barigozzi, Matteo & Conti, Antonio & Luciani, Matteo, 2012. "Do Euro area countries respond asymmetrically to the common monetary policy?," LSE Research Online Documents on Economics 43344, London School of Economics and Political Science, LSE Library.
    9. Guglielmo Maria Caporale & Luis Alberiko Gil-Alana & Pedro José Piqueras Martínez, 2024. "Dynamic Factor Models and Fractional Integration – With an Application to US Real Economic Activity," CESifo Working Paper Series 11486, CESifo.
    10. Orhan SANLI & Osman PEKER, 2023. "Effect of Inflation, Exchange Rate, Interest Rates and Income on House Sales: a Case of Turkiye," Journal of Economic Policy Researches, Istanbul University, Faculty of Economics, vol. 10(1), pages 37-60, January.
    11. Simona Delle Chiaie & Laurent Ferrara & Domenico Giannone, 2022. "Common factors of commodity prices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(3), pages 461-476, April.
    12. 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.
    13. Forni, Mario & Giovannelli, Alessandro & Lippi, Marco & Soccorsi, Stefano, 2016. "Dynamic Factor model with infinite dimensional factor space: forecasting," CEPR Discussion Papers 11161, C.E.P.R. Discussion Papers.
    14. Breitenfellner, Andreas & Crespo Cuaresma, Jesús & Mayer, Philipp, 2015. "Energy inflation and house price corrections," Energy Economics, Elsevier, vol. 48(C), pages 109-116.
    15. Yun Liu, 2022. "Housing and monetary policy: Fresh evidence from China," Financial Economics Letters, Anser Press, vol. 1(1), pages 1-12, December.
    16. Barigozzi, Matteo & Lippi, Marco & Luciani, Matteo, 2021. "Large-dimensional Dynamic Factor Models: Estimation of Impulse–Response Functions with I(1) cointegrated factors," Journal of Econometrics, Elsevier, vol. 221(2), pages 455-482.
    17. 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.).
    18. Yunus, Nafeesa, 2023. "Long-run and short-run impact of the U.S. economy on stock, bond and housing markets: An evaluation of U.S. and six major economies," The Quarterly Review of Economics and Finance, Elsevier, vol. 90(C), pages 211-232.
    19. 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.).
    20. Matteo Barigozzi & Marco Lippi & Matteo Luciani, 2016. "Non-Stationary Dynamic Factor Models for Large Datasets," Finance and Economics Discussion Series 2016-024, Board of Governors of the Federal Reserve System (U.S.).
    21. Monica Billio & Anna Petronevich, 2017. "Dynamical Interaction between Financial and Business Cycles," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01692239, HAL.
    22. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
    23. Matteo Barigozzi, 2023. "Quasi Maximum Likelihood Estimation of High-Dimensional Factor Models: A Critical Review," Papers 2303.11777, arXiv.org, revised May 2024.
    24. Mario Forni & Luca Gambetti & marco Lippi & Luca Sala, 2020. "Common Components Structural VARs," Center for Economic Research (RECent) 147, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
    25. Georgios Georgiadis & Martina Jancokova, 2017. "Financial Globalisation, Monetary Policy Spillovers and Macro-modelling: Tales from 1001 Shocks," Globalization Institute Working Papers 314, Federal Reserve Bank of Dallas.
    26. 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.
    27. Juho Koistinen & Bernd Funovits, 2022. "Estimation of Impulse-Response Functions with Dynamic Factor Models: A New Parametrization," Papers 2202.00310, arXiv.org, revised Feb 2022.
    28. CĂLIN, Adrian Cantemir, 2015. "The Effects Of The Federal Reserve’S Tapering Announcements On The Us Real Estate Market," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", vol. 19(3), pages 79-90.
    29. Hanisch, Max & Kempa, Bernd, 2017. "The international transmission channels of US supply and demand shocks: Evidence from a non-stationary dynamic factor model for the G7 countries," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 70-88.
    30. Christiane Baumeister & James D. Hamilton, 2020. "Drawing Conclusions from Structural Vector Autoregressions Identified on the Basis of Sign Restrictions," NBER Working Papers 26606, National Bureau of Economic Research, Inc.
    31. Caruso, Alberto, 2018. "Nowcasting with the help of foreign indicators: The case of Mexico," Economic Modelling, Elsevier, vol. 69(C), pages 160-168.
    32. Stefano Neri & Tiziano Ropele, 2015. "The macroeconomic effects of the sovereign debt crisis in the euro area," Temi di discussione (Economic working papers) 1007, Bank of Italy, Economic Research and International Relations Area.
    33. Pestova, Anna, 2020. "“Credit view” on monetary policy in Russia," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 57, pages 72-88.
    34. Max Hanisch, 2017. "US Monetary Policy and the Euro Area," Discussion Papers of DIW Berlin 1701, DIW Berlin, German Institute for Economic Research.
    35. André Binette & Tony Chernis & Daniel de Munnik, 2017. "Global Real Activity for Canadian Exports: GRACE," Discussion Papers 17-2, Bank of Canada.
    36. Hanisch, Max, 2019. "US monetary policy and the euro area," Journal of Banking & Finance, Elsevier, vol. 100(C), pages 77-96.
    37. Luke Mosley & Tak-Shing Chan & Alex Gibberd, 2023. "sparseDFM: An R Package to Estimate Dynamic Factor Models with Sparse Loadings," Papers 2303.14125, arXiv.org.
    38. Killins, Robert N. & Egly, Peter V. & Escobari, Diego, 2017. "The impact of oil shocks on the housing market: Evidence from Canada and U.S," Journal of Economics and Business, Elsevier, vol. 93(C), pages 15-28.
    39. Rüdiger Bachmann & Sebastian Rüth, 2017. "Systematic Monetary Policy And The Macroeconomic Effects Of Shifts In Loan-To-Value Ratios," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 17/934, Ghent University, Faculty of Economics and Business Administration.
    40. Pestova, Anna A. (Пестова, Анна) & Mamonov, Mikhail E. (Мамонов, Михаил) & Rostova, Natalia A. (Ростова, Наталья), 2019. "Monetary Policy Shocks in the Russian Economy and Their Macroeconomic Effects [Шоки Процентной Политики Банка России И Оценка Их Макроэкономических Эффектов]," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 4, pages 48-75, August.
    41. Matteo Barigozzi & Marco Lippi & Matteo Luciani, 2016. "Dynamic Factor Models, Cointegration, and Error Correction Mechanisms," Finance and Economics Discussion Series 2016-018, Board of Governors of the Federal Reserve System (U.S.).
    42. Matteo Barigozzi & Marco Lippi & Matteo Luciani, 2020. "Cointegration and Error Correction Mechanisms for Singular Stochastic Vectors," Econometrics, MDPI, vol. 8(1), pages 1-23, February.
    43. Torben Klarl, 2016. "The nexus between housing and GDP re-visited: A wavelet coherence view on housing and GDP for the U.S," Economics Bulletin, AccessEcon, vol. 36(2), pages 704-720.
    44. Baumeister, Christiane & Hamilton, James D., 2021. "Reprint: Drawing conclusions from structural vector autoregressions identified on the basis of sign restrictions," Journal of International Money and Finance, Elsevier, vol. 114(C).
    45. Sui, Jianli & Liu, Biying & Li, Zhigang & Zhang, Chengping, 2022. "Monetary and macroprudential policies, output, prices, and financial stability," International Review of Economics & Finance, Elsevier, vol. 78(C), pages 212-233.
    46. Hanisch, Max, 2017. "The effectiveness of conventional and unconventional monetary policy: Evidence from a structural dynamic factor model for Japan," Journal of International Money and Finance, Elsevier, vol. 70(C), pages 110-134.

  17. Matteo Luciani & David Veredas, 2012. "A model for vast panels of volatilities," Working Papers 1230, Banco de España.

    Cited by:

    1. Sayantan Bandhu Majumder & Ranjanendra Narayan Nag, 2018. "Shock and Volatility Spillovers Among Equity Sectors of the National Stock Exchange in India," Global Business Review, International Management Institute, vol. 19(1), pages 227-240, February.
    2. Fady Barsoum, 2013. "The Effects of Monetary Policy Shocks on a Panel of Stock Market Volatilities: A Factor-Augmented Bayesian VAR Approach," Working Paper Series of the Department of Economics, University of Konstanz 2013-15, Department of Economics, University of Konstanz.
    3. Dungey, Mardi & Luciani, Matteo & Veredas, David, 2012. "Ranking systemically important financial institutions," Working Papers 15473, University of Tasmania, Tasmanian School of Business and Economics, revised 21 Nov 2012.
    4. Adam Clements & Ayesha Scott & Annastiina Silvennoinen, 2013. "On the Benefits of Equicorrelation for Portfolio Allocation," NCER Working Paper Series 99, National Centre for Econometric Research.
    5. Bernard Herskovic & Bryan Kelly & Hanno Lustig & Stijn Van Nieuwerburgh, 2020. "Firm Volatility in Granular Networks," Journal of Political Economy, University of Chicago Press, vol. 128(11), pages 4097-4162.
    6. Stijn Van Nieuwerburgh & Hanno Lustig & Bryan Kelly & Bernard Herskovic, 2014. "The Common Factor in Idiosyncratic Volatility," 2014 Meeting Papers 810, Society for Economic Dynamics.
    7. Barigozzi, Matteo & Brownlees, Christian & Gallo, Giampiero M. & Veredas, David, 2014. "Disentangling systematic and idiosyncratic dynamics in panels of volatility measures," Journal of Econometrics, Elsevier, vol. 182(2), pages 364-384.
    8. Herskovic, Bernard & Kelly, Bryan & Lustig, Hanno & Van Nieuwerburgh, Stijn, 2016. "The common factor in idiosyncratic volatility: Quantitative asset pricing implications," Journal of Financial Economics, Elsevier, vol. 119(2), pages 249-283.
    9. KALNINA, Ilze & TEWOU, Kokouvi, 2015. "Cross-sectional dependence in idiosyncratic volatility," Cahiers de recherche 2015-04, Universite de Montreal, Departement de sciences economiques.
    10. Yunus Emre Ergemen, 2016. "Generalized Efficient Inference on Factor Models with Long-Range Dependence," CREATES Research Papers 2016-05, Department of Economics and Business Economics, Aarhus University.
    11. Adam E Clements & Ayesha Scott & Annastiina Silvennoinen, 2012. "Forecasting multivariate volatility in larger dimensions: some practical issues," NCER Working Paper Series 80, National Centre for Econometric Research.
    12. Ezzat, Hassan, 2012. "The Application of GARCH Methods in Modeling Volatility Using Sector Indices from the Egyptian Exchange," MPRA Paper 51584, University Library of Munich, Germany.

  18. Mardi Dungey & Matteo Luciani & David Veredas, 2012. "Ranking Systemically Important Financial Institutions," CAMA Working Papers 2012-47, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.

    Cited by:

    1. Matteo Barigozzi & Christian Brownlees, 2013. "Nets: Network Estimation for Time Series," Working Papers 723, Barcelona School of Economics.
    2. Dungey, Mardi & Luciani, Matteo & Veredas, David, 2012. "Ranking systemically important financial institutions," Working Papers 15473, University of Tasmania, Tasmanian School of Business and Economics, revised 21 Nov 2012.
    3. Mardi Dungey & Moses Kangogo & Vladimir Volkov, 2022. "Dynamic effects of network exposure on equity markets," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(4), pages 569-629, December.
    4. Dahlqvist, Carl-Henrik & Gnabo, Jean-Yves, 2018. "Effective network inference through multivariate information transfer estimation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 376-394.
    5. I�aki Aldasoro & Ignazio Angeloni, 2015. "Input-output-based measures of systemic importance," Quantitative Finance, Taylor & Francis Journals, vol. 15(4), pages 589-606, April.
    6. Dungey, Mardi & Matei, Marius & Treepongkaruna, Sirimon, 2014. "Identifying periods of financial stress in Asian currencies: the role of high frequency financial market data," Working Papers 2014-12, University of Tasmania, Tasmanian School of Business and Economics.
    7. Ahelegbey, Daniel Felix, 2015. "The Econometrics of Bayesian Graphical Models: A Review With Financial Application," MPRA Paper 92634, University Library of Munich, Germany, revised 25 Apr 2016.
    8. Vitali Alexeev & Mardi Dungey, 2015. "Equity portfolio diversification with high frequency data," Quantitative Finance, Taylor & Francis Journals, vol. 15(7), pages 1205-1215, July.
    9. Jerzy Korczak & Maria Sasin & Dorota Janiszewska, 2021. "Smart Logistics Infrastructure in Peripheral Region," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 4), pages 535-548.
    10. Masciantonio, Sergio, 2013. "Identifying, ranking and tracking systemically important financial institutions (SIFIs), from a global, EU and Eurozone perspective," MPRA Paper 46788, University Library of Munich, Germany.
    11. Stefano Gurciullo, 2014. "Stess-testing the system: Financial shock contagion in the realm of uncertainty," Papers 1412.1679, arXiv.org.
    12. Yun, Tae-Sub & Jeong, Deokjong & Park, Sunyoung, 2019. "“Too central to fail” systemic risk measure using PageRank algorithm," Journal of Economic Behavior & Organization, Elsevier, vol. 162(C), pages 251-272.
    13. Kleinow, Jacob & Moreira, Fernando, 2016. "Systemic risk among European banks: A copula approach," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 42(C), pages 27-42.
    14. Jacob Kleinow & Tobias Nell, 2015. "Determinants of systemically important banks: the case of Europe," Journal of Financial Economic Policy, Emerald Group Publishing Limited, vol. 7(4), pages 446-476, November.
    15. Yao, Wenying & Tian, Jing, 2015. "The role of intra-day volatility pattern in jump detection: empirical evidence on how financial markets respond to macroeconomic news announcements," Working Papers 2015-05, University of Tasmania, Tasmanian School of Business and Economics.
    16. Jacob Kleinow & Andreas Horsch & Mario Garcia-Molina, 2017. "Factors driving systemic risk of banks in Latin America," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 41(2), pages 211-234, April.
    17. Vitali Alexeev & Katja Ignatieva, 2021. "Biases in variance of decomposed portfolio returns," International Review of Finance, International Review of Finance Ltd., vol. 21(4), pages 1152-1178, December.
    18. Vitali Alexeev & Mardi Dungey & Wenying Yao, 2016. "Continuous and Jump Betas: Implications for Portfolio Diversification," Econometrics, MDPI, vol. 4(2), pages 1-15, June.
    19. Daniel Felix Ahelegbey, 2015. "The Econometrics of Networks: A Review," Working Papers 2015:13, Department of Economics, University of Venice "Ca' Foscari".

  19. Matteo Barigozzi & Antonio M. Conti & Matteo Luciani, 2011. "Measuring Euro Area Monetary Policy Transmission in a Structural Dynamic Factor Model," European Economy - Economic Papers 2008 - 2015 441, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.

    Cited by:

    1. Konstantins Benkovskis & Andrejs Bessonovs & Martin Feldkircher & Julia Wörz, 2011. "The Transmission of Euro Area Monetary Shocks to the Czech Republic, Poland and Hungary: Evidence from a FAVAR Model," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue 3, pages 8-36.
    2. Prettner, Catherine & Prettner, Klaus, 2012. "After Two Decades of Integration: How Interdependent are Eastern European Economies and the Euro Area?," Department of Economics Working Paper Series 138, WU Vienna University of Economics and Business.
    3. Prettner, Catherine & Prettner, Klaus, 2014. "How interdependent are Eastern European economies and the Euro area?," University of Göttingen Working Papers in Economics 187, University of Goettingen, Department of Economics.
    4. Efrem Castelnuovo, 2016. "Monetary policy shocks and Cholesky VARs: an assessment for the Euro area," Empirical Economics, Springer, vol. 50(2), pages 383-414, March.
    5. Bhattacharya, Rudrani & Tripathi, Shruti & Chowdhury, Sahana Roy, 2019. "Financial structure, institutional quality and monetary policy transmission: A Meta-Analysis," Working Papers 19/274, National Institute of Public Finance and Policy.

  20. Matteo Luciani, 2011. "Forecasting with Approximate Dynamic Factor Models: the Role of Non-Pervasive Shocks," Working Papers ECARES ECARES 2011‐022, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Danilo Cascaldi-Garcia & Matteo Luciani & Michele Modugno, 2023. "Lessons from Nowcasting GDP across the World," International Finance Discussion Papers 1385, Board of Governors of the Federal Reserve System (U.S.).
    2. Hindrayanto, Irma & Koopman, Siem Jan & de Winter, Jasper, 2016. "Forecasting and nowcasting economic growth in the euro area using factor models," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1284-1305.
    3. Daniela Bragoli & Michele Modugno, 2016. "A Nowcasting Model for Canada: Do U.S. Variables Matter?," Finance and Economics Discussion Series 2016-036, Board of Governors of the Federal Reserve System (U.S.).
    4. Bragoli, Daniela, 2017. "Now-casting the Japanese economy," International Journal of Forecasting, Elsevier, vol. 33(2), pages 390-402.
    5. Shaoxin Wang & Hu Yang & Chaoli Yao, 2019. "On the penalized maximum likelihood estimation of high-dimensional approximate factor model," Computational Statistics, Springer, vol. 34(2), pages 819-846, June.
    6. 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.
    7. Simona Delle Chiaie & Laurent Ferrara & Domenico Giannone, 2022. "Common factors of commodity prices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(3), pages 461-476, April.
    8. 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.
    9. Richard D. F. Harris & Anh T. H. Nguyen, 2017. "Dynamic factor long memory volatility," Quantitative Finance, Taylor & Francis Journals, vol. 17(8), pages 1205-1221, August.
    10. Barigozzi, Matteo & Lippi, Marco & Luciani, Matteo, 2021. "Large-dimensional Dynamic Factor Models: Estimation of Impulse–Response Functions with I(1) cointegrated factors," Journal of Econometrics, Elsevier, vol. 221(2), pages 455-482.
    11. 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.).
    12. Luciani, Matteo & Pundit, Madhavi & Ramayandi, Arief & Veronese , Giovanni, 2015. "Nowcasting Indonesia," ADB Economics Working Paper Series 471, Asian Development Bank.
    13. Matteo Barigozzi & Marco Lippi & Matteo Luciani, 2016. "Non-Stationary Dynamic Factor Models for Large Datasets," Finance and Economics Discussion Series 2016-024, Board of Governors of the Federal Reserve System (U.S.).
    14. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
    15. Dahlhaus, Tatjana & Guénette, Justin-Damien & Vasishtha, Garima, 2017. "Nowcasting BRIC+M in real time," International Journal of Forecasting, Elsevier, vol. 33(4), pages 915-935.
    16. Li, Jiahan & Chen, Weiye, 2014. "Forecasting macroeconomic time series: LASSO-based approaches and their forecast combinations with dynamic factor models," International Journal of Forecasting, Elsevier, vol. 30(4), pages 996-1015.
    17. Matteo Luciani & Lorenzo Ricci, 2014. "Nowcasting Norway," International Journal of Central Banking, International Journal of Central Banking, vol. 10(4), pages 215-248, December.
    18. Matteo Barigozzi & Marc Hallin & Matteo Luciani & Paolo Zaffaroni, 2021. "Inferential Theory for Generalized Dynamic Factor Models," Working Papers ECARES 2021-20, ULB -- Universite Libre de Bruxelles.
    19. David de Antonio Liedo, 2014. "Nowcasting Belgium," Working Paper Research 256, National Bank of Belgium.
    20. Barigozzi, Matteo & Hallin, Marc, 2017. "Generalized dynamic factor models and volatilities: estimation and forecasting," Journal of Econometrics, Elsevier, vol. 201(2), pages 307-321.
    21. Abberger, Klaus & Graff, Michael & Siliverstovs, Boriss & Sturm, Jan-Egbert, 2018. "Using rule-based updating procedures to improve the performance of composite indicators," Economic Modelling, Elsevier, vol. 68(C), pages 127-144.
    22. Jack Fosten, 2016. "Model selection with factors and variables," University of East Anglia School of Economics Working Paper Series 2016-07, School of Economics, University of East Anglia, Norwich, UK..
    23. Duarte, Pablo & Süßmuth, Bernd, 2018. "Implementing an approximate dynamic factor model to nowcast GDP using sensitivity analysis," Working Papers 152, University of Leipzig, Faculty of Economics and Management Science.
    24. Smeekes, Stephan & Wijler, Etiënne, 2016. "Macroeconomic Forecasting Using Penalized Regression Methods," Research Memorandum 039, Maastricht University, Graduate School of Business and Economics (GSBE).
    25. Kyle E. Binder & Mohsen Pourahmadi & James W. Mjelde, 2020. "The role of temporal dependence in factor selection and forecasting oil prices," Empirical Economics, Springer, vol. 58(3), pages 1185-1223, March.
    26. Karmous, Aida & Boubaker, Heni & Belkacem, Lotfi, 2019. "A dynamic factor model with stylized facts to forecast volatility for an optimal portfolio," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    27. Matteo Barigozzi & Marco Lippi & Matteo Luciani, 2016. "Dynamic Factor Models, Cointegration, and Error Correction Mechanisms," Finance and Economics Discussion Series 2016-018, Board of Governors of the Federal Reserve System (U.S.).
    28. Bai, Jushan & Liao, Yuan, 2016. "Efficient estimation of approximate factor models via penalized maximum likelihood," Journal of Econometrics, Elsevier, vol. 191(1), pages 1-18.
    29. Hyun Hak Kim, 2013. "Forecasting Macroeconomic Variables Using Data Dimension Reduction Methods: The Case of Korea," Working Papers 2013-26, Economic Research Institute, Bank of Korea.

  21. Matteo Luciani, 2010. "Monetary Policy, the Housing Market, and the 2008 Recession: A Structural Factor Analysis," Working Papers 7, Doctoral School of Economics, Sapienza University of Rome, revised 2010.

    Cited by:

    1. Breitenfellner, Andreas & Crespo Cuaresma, Jesús & Mayer, Philipp, 2015. "Energy inflation and house price corrections," Energy Economics, Elsevier, vol. 48(C), pages 109-116.

Articles

  1. Barigozzi, Matteo & Lippi, Marco & Luciani, Matteo, 2021. "Large-dimensional Dynamic Factor Models: Estimation of Impulse–Response Functions with I(1) cointegrated factors," Journal of Econometrics, Elsevier, vol. 221(2), pages 455-482.

    Cited by:

    1. Chiara Casoli & Riccardo (Jack) Lucchetti, 2022. "Permanent-Transitory decomposition of cointegrated time series via dynamic factor models, with an application to commodity prices [Commodity-price comovement and global economic activity]," The Econometrics Journal, Royal Economic Society, vol. 25(2), pages 494-514.
    2. Donato Ceci & Andrea Silvestrini, 2023. "Nowcasting the state of the Italian economy: The role of financial markets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1569-1593, November.
    3. Gianluca Cubadda & Marco Mazzali, 2024. "The vector error correction index model: representation, estimation and identification," The Econometrics Journal, Royal Economic Society, vol. 27(1), pages 126-150.
    4. Davide Brignone & Alessandro Franconi & Marco Mazzali, 2023. "Robust Impulse Responses using External Instruments: the Role of Information," Papers 2307.06145, arXiv.org.
    5. 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.).
    6. Theo Drossidis & Haroon Mumtaz & Angeliki Theophilopoulou, 2024. "The Distributional Effects of Oil Supply New Shocks," Working Papers 975, Queen Mary University of London, School of Economics and Finance.
    7. 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.
    8. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
    9. Haroon Mumtaz & Roman Sustek, 2023. "Global house prices since 1950," Discussion Papers 2307, Centre for Macroeconomics (CFM).
    10. Juho Koistinen & Bernd Funovits, 2022. "Estimation of Impulse-Response Functions with Dynamic Factor Models: A New Parametrization," Papers 2202.00310, arXiv.org, revised Feb 2022.
    11. Matteo Barigozzi & Marc Hallin, 2023. "Dynamic Factor Models: a Genealogy," Papers 2310.17278, arXiv.org, revised Jan 2024.
    12. Shahriyar Aliyev & Evžen Kočenda, 2023. "ECB monetary policy and commodity prices," Review of International Economics, Wiley Blackwell, vol. 31(1), pages 274-304, February.
    13. Mirela Sorina Miescu & Giorgio Motta & Dario Pontiggia & Raffaele Rossi, 2023. "The Expansionary Effects Of Housing Credit Supply Shocks," Working Papers 399832231, Lancaster University Management School, Economics Department.
    14. Cantore, Cristiano & Ferroni, Filippo & Mumtaz, Hroon & Theophilopoulou, Angeliki, 2022. "A tail of labour supply and a tale of monetary policy," Bank of England working papers 989, Bank of England.
    15. Ergemen, Yunus Emre, 2023. "Parametric estimation of long memory in factor models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1483-1499.
    16. Gianluca Cubadda, 2024. "VAR models with an index structure: A survey with new results," Papers 2412.11278, arXiv.org.
    17. Gabriele Mingoli, 2024. "Modeling Common Bubbles: A Mixed Causal Non-Causal Dynamic Factor Model," Tinbergen Institute Discussion Papers 24-072/III, Tinbergen Institute.
    18. Takumah, Wisdom, 2023. "Fiscal Policy and Asset Prices in a Dynamic Factor Model with Cointegrated Factors," MPRA Paper 117897, University Library of Munich, Germany, revised 10 Jul 2023.

  2. Matteo Barigozzi & Marco Lippi & Matteo Luciani, 2020. "Cointegration and Error Correction Mechanisms for Singular Stochastic Vectors," Econometrics, MDPI, vol. 8(1), pages 1-23, February.

    Cited by:

    1. Chiara Casoli & Riccardo (Jack) Lucchetti, 2022. "Permanent-Transitory decomposition of cointegrated time series via dynamic factor models, with an application to commodity prices [Commodity-price comovement and global economic activity]," The Econometrics Journal, Royal Economic Society, vol. 25(2), pages 494-514.
    2. Sergej Gričar & Štefan Bojnec, 2021. "Technical Analysis of Tourism Price Process in the Eurozone," JRFM, MDPI, vol. 14(11), pages 1-25, October.
    3. Donato Ceci & Andrea Silvestrini, 2023. "Nowcasting the state of the Italian economy: The role of financial markets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1569-1593, November.
    4. Barigozzi, Matteo & Lippi, Marco & Luciani, Matteo, 2021. "Large-dimensional Dynamic Factor Models: Estimation of Impulse–Response Functions with I(1) cointegrated factors," Journal of Econometrics, Elsevier, vol. 221(2), pages 455-482.
    5. Feng, Zongbao & Chen, Weiya & Liu, Yang & Chen, Hongyu & Skibniewski, Mirosław J., 2023. "Long-term equilibrium relationship analysis and energy-saving measures of metro energy consumption and its influencing factors based on cointegration theory and an ARDL model," Energy, Elsevier, vol. 263(PD).
    6. 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.
    7. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
    8. Juho Koistinen & Bernd Funovits, 2022. "Estimation of Impulse-Response Functions with Dynamic Factor Models: A New Parametrization," Papers 2202.00310, arXiv.org, revised Feb 2022.
    9. Matteo Barigozzi & Marc Hallin, 2023. "Dynamic Factor Models: a Genealogy," Papers 2310.17278, arXiv.org, revised Jan 2024.
    10. Tibor Szendrei & Katalin Varga, 2020. "FISS - A Factor-based Index of Systemic Stress in the Financial System," Russian Journal of Money and Finance, Bank of Russia, vol. 79(1), pages 3-34, March.
    11. Gianluca Cubadda, 2024. "VAR models with an index structure: A survey with new results," Papers 2412.11278, arXiv.org.
    12. Gabriele Mingoli, 2024. "Modeling Common Bubbles: A Mixed Causal Non-Causal Dynamic Factor Model," Tinbergen Institute Discussion Papers 24-072/III, Tinbergen Institute.

  3. Cristina Conflitti and Matteo Luciani, 2019. "Oil Price Pass-through into Core Inflation," The Energy Journal, International Association for Energy Economics, vol. 0(Number 6).
    See citations under working paper version above.
  4. Dungey, Mardi & Luciani, Matteo & Veredas, David, 2018. "Systemic risk in the US: Interconnectedness as a circuit breaker," Economic Modelling, Elsevier, vol. 71(C), pages 305-315.

    Cited by:

    1. Dungey, Mardi & Flavin, Thomas & O'Connor, Thomas & Wosser, Michael, 2022. "Non-financial corporations and systemic risk," Journal of Corporate Finance, Elsevier, vol. 72(C).
    2. Dinesh Gajurel & Mardi Dungey & Wenying Yao & Nagaratnam Jeyasreedharan, 2020. "Jump Risk in the US Financial Sector," The Economic Record, The Economic Society of Australia, vol. 96(314), pages 331-349, September.
    3. Chowdhury, Biplob & Dungey, Mardi & Kangogo, Moses & Sayeed, Mohammad Abu & Volkov, Vladimir, 2019. "The changing network of financial market linkages: The Asian experience," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 71-92.
    4. Dungey, Mardi & Flavin, Thomas J. & Lagoa-Varela, Dolores, 2020. "Are banking shocks contagious? Evidence from the eurozone," Journal of Banking & Finance, Elsevier, vol. 112(C).
    5. Kevin Lee & Kian Ong & Kalvinder K. Shields, 2020. "Making Fiscal Adjustments Using Event Probability Forecasts in OECD Countries," The Economic Record, The Economic Society of Australia, vol. 96(314), pages 294-313, September.
    6. Cucinelli, Doriana & Soana, Maria Gaia, 2023. "Systemic risk in non financial companies: Does governance matter?," International Review of Financial Analysis, Elsevier, vol. 87(C).
    7. Kolari, James W. & López-Iturriaga, Félix J. & Sanz, Ivan Pastor, 2020. "Measuring systemic risk in the U.S. Banking system," Economic Modelling, Elsevier, vol. 91(C), pages 646-658.
    8. Grilli, Ruggero & Giri, Federico & Gallegati, Mauro, 2020. "Collateral rehypothecation, safe asset scarcity, and unconventional monetary policy," Economic Modelling, Elsevier, vol. 91(C), pages 633-645.
    9. Geraci, Marco Valerio & Gnabo, Jean-Yves, 2018. "Measuring Interconnectedness between Financial Institutions with Bayesian Time-Varying Vector Autoregressions," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 53(3), pages 1371-1390, June.
    10. Dungey, Mardi & Harvey, John & Siklos, Pierre & Volkov, Vladimir, 2017. "Signed spillover effects building on historical decompositions," Working Papers 2017-11, University of Tasmania, Tasmanian School of Business and Economics.
    11. Saidane, Dhafer & Sène, Babacar & Désiré Kanga, Kouamé, 2021. "Pan-African banks, banking interconnectivity: A new systemic risk measure in the WAEMU," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    12. Kanga, Désiré & Soumaré, Issouf & Amenounvé, Edoh, 2023. "Can corporate financing through the stock market create systemic risk? Evidence from the BRVM securities market," Emerging Markets Review, Elsevier, vol. 55(C).
    13. Wang, Xiaoting & Hou, Siyuan & Shen, Jie, 2021. "Default clustering of the nonfinancial sector and systemic risk: Evidence from China," Economic Modelling, Elsevier, vol. 96(C), pages 196-208.

  5. Matteo Luciani & Madhavi Pundit & Arief Ramayandi & Giovanni Veronese, 2018. "Nowcasting Indonesia," Empirical Economics, Springer, vol. 55(2), pages 597-619, September.
    See citations under working paper version above.
  6. Mardi Dungey & Marius Matei & Matteo Luciani & David Veredas, 2017. "Surfing through the GFC: Systemic Risk in Australia," The Economic Record, The Economic Society of Australia, vol. 93(300), pages 1-19, March.
    See citations under working paper version above.
  7. Matteo Luciani, 2015. "Monetary Policy and the Housing Market: A Structural Factor Analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(2), pages 199-218, March.
    See citations under working paper version above.
  8. Matteo Luciani & David Veredas, 2015. "Estimating and Forecasting Large Panels of Volatilities with Approximate Dynamic Factor Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(3), pages 163-176, April.

    Cited by:

    1. Bastian Gribisch, 2018. "A latent dynamic factor approach to forecasting multivariate stock market volatility," Empirical Economics, Springer, vol. 55(2), pages 621-651, September.
    2. Tobias Hartl & Roland Jucknewitz, 2022. "Approximate state space modelling of unobserved fractional components," Econometric Reviews, Taylor & Francis Journals, vol. 41(1), pages 75-98, January.
    3. Manabu Asai & Michael McAleer, 2014. "Forecasting Co-Volatilities via Factor Models with Asymmetry and Long Memory in Realized Covariance," Working Papers in Economics 14/10, University of Canterbury, Department of Economics and Finance.
    4. Tobias Hartl & Roland Weigand, 2018. "Multivariate Fractional Components Analysis," Papers 1812.09149, arXiv.org, revised Jan 2019.
    5. Harry Vander Elst, 2015. "FloGARCH : Realizing long memory and asymmetries in returns volatility," Working Paper Research 280, National Bank of Belgium.
    6. Ergemen, Yunus Emre & Rodríguez-Caballero, C. Vladimir, 2023. "Estimation of a dynamic multi-level factor model with possible long-range dependence," International Journal of Forecasting, Elsevier, vol. 39(1), pages 405-430.
    7. Matteo Barigozzi & Marc Hallin, 2016. "Generalized dynamic factor models and volatilities: recovering the market volatility shocks," Econometrics Journal, Royal Economic Society, vol. 19(1), pages 33-60, February.
    8. Barigozzi, Matteo & Hallin, Marc, 2017. "Generalized dynamic factor models and volatilities: estimation and forecasting," Journal of Econometrics, Elsevier, vol. 201(2), pages 307-321.
    9. Dungey, Mardi & Luciani, Matteo & Matei, Marius & Veredas, David, 2015. "Surfing through the GFC: systemic risk in Australia," Working Papers 2015-01, University of Tasmania, Tasmanian School of Business and Economics.
    10. Herskovic, Bernard & Kelly, Bryan & Lustig, Hanno & Van Nieuwerburgh, Stijn, 2016. "The common factor in idiosyncratic volatility: Quantitative asset pricing implications," Journal of Financial Economics, Elsevier, vol. 119(2), pages 249-283.
    11. Kris Boudt & Dries Cornilly & Tim Verdonck, 2019. "Nearest Comoment Estimation With Unobserved Factors," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 19/970, Ghent University, Faculty of Economics and Business Administration.
    12. Chang, Ya-Ting & Gau, Yin-Feng & Hsu, Chih-Chiang, 2017. "Liquidity Commonality in Foreign Exchange Markets During the Global Financial Crisis and the Sovereign Debt Crisis: Effects of Macroeconomic and Quantitative Easing Announcements," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 172-192.
    13. Ergemen, Yunus Emre, 2023. "Parametric estimation of long memory in factor models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1483-1499.
    14. Cipollini, Fabrizio & Gallo, Giampiero M., 2019. "Modeling Euro STOXX 50 volatility with common and market-specific components," Econometrics and Statistics, Elsevier, vol. 11(C), pages 22-42.
    15. Yunus Emre Ergemen, 2022. "Parametric Estimation of Long Memory in Factor Models," CREATES Research Papers 2022-10, Department of Economics and Business Economics, Aarhus University.
    16. Tobias Hartl, 2020. "Macroeconomic Forecasting with Fractional Factor Models," Papers 2005.04897, arXiv.org.
    17. Matteo Barigozzi & Marc Hallin & Stefano Soccorsi, 2017. "Identification of Global and National Shocks in International Financial Markets via General Dynamic Factor Models," Working Papers ECARES ECARES 2017-10, ULB -- Universite Libre de Bruxelles.

  9. Matteo Barigozzi & Antonio M. Conti & Matteo Luciani, 2014. "Do Euro Area Countries Respond Asymmetrically to the Common Monetary Policy?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(5), pages 693-714, October.
    See citations under working paper version above.
  10. Matteo Luciani & Lorenzo Ricci, 2014. "Nowcasting Norway," International Journal of Central Banking, International Journal of Central Banking, vol. 10(4), pages 215-248, December.
    See citations under working paper version above.
  11. Luciani, Matteo, 2014. "Forecasting with approximate dynamic factor models: The role of non-pervasive shocks," International Journal of Forecasting, Elsevier, vol. 30(1), pages 20-29.
    See citations under working paper version above.
  12. P. Guerrieri & M. Luciani & V. Meliciani, 2011. "The determinants of investment in information and communication technologies," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 20(4), pages 387-403.

    Cited by:

    1. Jimmy Lopez & Jacques Mairesse & Cette Gilbert, 2018. "Labour Market Regulations and Capital Intensity," Post-Print hal-02197392, HAL.
    2. Fabio Bacchini & Maria Elena Bontempi & Roberto Golinelli & Cecilia Jona-Lasinio, 2014. "ICT and Non-ICT investments: short and long run macro dynamics," Working Papers LuissLab 14113, Dipartimento di Economia e Finanza, LUISS Guido Carli.
    3. Gilbert Cette & Christian Clerc & Lea Bresson, 2015. "Contribution of ICT Diffusion to Labour Productivity Growth: The United States, Canada, the Eurozone, and the United Kingdom, 1970-2013," Post-Print hal-01456123, HAL.
    4. Kariem Soliman, 2021. "Are Industrial Robots a new GPT? A Panel Study of Nine European Countries with Capital and Quality-adjusted Industrial Robots as Drivers of Labour Productivity Growth," EIIW Discussion paper disbei307, Universitätsbibliothek Wuppertal, University Library.
    5. Gilbert Cette & Jimmy Lopez & Jacques Mairesse, 2018. "Employment Protection Legislation Impacts on Capital and Skills Composition," Post-Print hal-01981426, HAL.
    6. Gilbert Cette & John Fernald & Benoît Mojon, 2016. "The pre-Great Recession slowdown in productivity," Post-Print hal-01725475, HAL.
    7. G. Cette & J. Lopez & J. Mairesse, 2016. "Labour market regulations and capital labour substitution," Working papers 604, Banque de France.
    8. Fabio Bacchini & Maria Elena Bontempi & Roberto Golinelli & Cecilia Jona-Lasinio, 2018. "Short- and long-run heterogeneous investment dynamics," Empirical Economics, Springer, vol. 54(2), pages 343-378, March.
    9. Anupam Das & Murshed Chowdhury & Sariah Seaborn, 2018. "ICT Diffusion, Financial Development and Economic Growth: New Evidence from Low and Lower Middle-Income Countries," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 9(3), pages 928-947, September.
    10. Mr. Luc Eyraud & Ms. Changchang Zhang & Mr. Abdoul A Wane & Mr. Benedict J. Clements, 2011. "Who's Going Green and Why? Trends and Determinants of Green Investment," IMF Working Papers 2011/296, International Monetary Fund.
    11. Krüger, Jens J. & Rhiel, Mathias, 2016. "Determinants of ICT infrastructure: A cross-country statistical analysis," Darmstadt Discussion Papers in Economics 228, Darmstadt University of Technology, Department of Law and Economics.
    12. Gilbert Cette & Christian Clerc & Lea Bresson, 2016. "Contribution of information and communication technologies (ICT) to growth," Post-Print hal-03565112, HAL.
    13. Maté Fodor, 2016. "Essays on Education, Wages and Technology," ULB Institutional Repository 2013/239691, ULB -- Universite Libre de Bruxelles.
    14. Olimpia Neagu, 2011. "How The Investment In R&D Is Related To The Human Capital Accumulation? The Case Of Romania," Annales Universitatis Apulensis Series Oeconomica, Faculty of Sciences, "1 Decembrie 1918" University, Alba Iulia, vol. 2(13), pages 1-35.
    15. Laudien, Sven M. & Reuter, Ute & Sendra Garcia, Francisco Javier & Botella-Carrubi, Dolores, 2024. "Digital advancement and its effect on business model design: Qualitative-empirical insights," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    16. Marianna Belloc & Paolo Guerrieri, 2015. "Impact of ICT diffusion and adoption on sectoral industrial performance: evidence from a panel of European countries," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 32(1), pages 67-84, April.
    17. G. Cette & R. Lecat & C. Ly-Marin, 2017. "Long-term growth and productivity projections in advanced countries," Working papers 617, Banque de France.
    18. Gilbert Cette & Aurélien Devillard & Vincenzo Spiezia, 2020. "Growth factors in developed countries: A 1960-2019 growth accounting decomposition," AMSE Working Papers 2033, Aix-Marseille School of Economics, France.
    19. Gilbert CETTE, 2015. "Which Role for ICTs as a Productivity Driver Over the Last Years and the Next Future?," Communications & Strategies, IDATE, Com&Strat dept., vol. 1(100), pages 65-83, 4th quart.
    20. Bahar Bayraktar Sağlam, 2018. "ICT Diffusion, R&D Intensity, and Economic Growth: a Dynamic Panel Data Approach," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 9(2), pages 636-648, June.
    21. Cristiano, Antonelli, 2019. "The creative response and international trade11The comments of the anonymous referees and the editor are gratefully acknowledged. The funding of my Department are acknowledged," Structural Change and Economic Dynamics, Elsevier, vol. 51(C), pages 445-452.
    22. Cristina Fernández & Juan Benavides, 2020. "Las plataformas digitales, la productividad y el empleo en Colombia," Informes de Investigación 18276, Fedesarrollo.
    23. Cette, G. & Clerc, C. & Bresson, L., 2015. "Diffusion et contribution à la croissance des TIC aux États-Unis, dans la zone euro et au Royaume-Uni," Bulletin de la Banque de France, Banque de France, issue 200, pages 83-90.
    24. Gilbert Cette & Jimmy Lopez & Giorgio Presidente & Vincenzo Spiezia, 2018. "Measuring “Indirect” Investments in ICT in OECD Countries," Working papers 686, Banque de France.
    25. Hyuk Chung, 2021. "Adoption and Development of the Fourth Industrial Revolution Technology: Features and Determinants," Sustainability, MDPI, vol. 13(2), pages 1-16, January.
    26. Eyraud, Luc & Clements, Benedict & Wane, Abdoul, 2013. "Green investment: Trends and determinants," Energy Policy, Elsevier, vol. 60(C), pages 852-865.
    27. Sadaf Bashir & Bert Sadowski, 2014. "General Purpose Technologies: A Survey, a Critique and Future Research Directions," Working Papers 14-02, Eindhoven Center for Innovation Studies, revised Feb 2014.
    28. Nicoletti, Giuseppe & von Rueden, Christina & Andrews, Dan, 2020. "Digital technology diffusion: A matter of capabilities, incentives or both?," European Economic Review, Elsevier, vol. 128(C).
    29. Rammer, Christian & Köhler, Christian, 2012. "Innovationen, Anlageinvestitionen und immaterielle Investitionen," ZEW Discussion Papers 12-085, ZEW - Leibniz Centre for European Economic Research.
    30. Ebeling Antoine, 2022. "European investment Bank loan appraisal, the EU climate bank ?," Working Papers of BETA 2022-10, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    31. Kren, Janez & O'Toole, Conor, 2024. "What drives SME investment in digitalisation? Micro-data evidence for Ireland," Papers WP777, Economic and Social Research Institute (ESRI).

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.