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Catherine Doz

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.

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Catherine Doz & Domenico Giannone & Lucrezia Reichlin, 2012. "A Quasi–Maximum Likelihood Approach for Large, Approximate Dynamic Factor Models," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1014-1024, November.

    Mentioned in:

    1. Time-Varying Dynamic Factor Loadings
      by Francis Diebold in No Hesitations on 2016-01-20 23:32:00

RePEc Biblio mentions

As found on the RePEc Biblio, the curated bibliography of Economics:
  1. Catherine Doz & Domenico Giannone & Lucrezia Reichlin, 2012. "A Quasi–Maximum Likelihood Approach for Large, Approximate Dynamic Factor Models," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1014-1024, November.

    Mentioned in:

    1. > Econometrics > Time Series Models > Dynamic Factor Models

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Catherine Doz & Domenico Giannone & Lucrezia Reichlin, 2012. "A Quasi–Maximum Likelihood Approach for Large, Approximate Dynamic Factor Models," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1014-1024, November.

    Mentioned in:

    1. A Quasi–Maximum Likelihood Approach for Large, Approximate Dynamic Factor Models (REStat 2012) in ReplicationWiki ()

Working papers

  1. Reichlin, Lucrezia & Doz, Catherine & Giannone, Domenico, 2006. "A Quasi Maximum Likelihood Approach for Large Approximate Dynamic Factor Models," CEPR Discussion Papers 5724, C.E.P.R. Discussion Papers.

    Cited by:

    1. Maria A. Arias & Charles S. Gascon & David E. Rapach, 2014. "Metro Business Cycles," Working Papers 2014-46, Federal Reserve Bank of St. Louis.
    2. C. Vladimir Rodr'iguez-Caballero & Esther Ruiz, 2024. "Temperature in the Iberian Peninsula: Trend, seasonality, and heterogeneity," Papers 2406.14145, arXiv.org.
    3. Robert Lehmann, 2016. "Economic Growth and Business Cycle Forecasting at the Regional Level," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 65, March.
    4. 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.
    5. Pegoraro, F. & Siegel, A. F. & Tiozzo Pezzoli, L., 2014. "Specification Analysis of International Treasury Yield Curve Factors," Working papers 490, Banque de France.
    6. Aaron J. Amburgey & Michael W. McCracken, 2023. "On the real‐time predictive content of financial condition indices for growth," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(2), pages 137-163, March.
    7. Claudio Morana, 2010. "Heteroskedastic Factor Vector Autoregressive Estimation of Persistent and Non Persistent Processes Subject to Structural Breaks," ICER Working Papers - Applied Mathematics Series 36-2010, ICER - International Centre for Economic Research.
    8. Michele Modugno & Lucrezia Reichlin & Domenico Giannone & Marta Banbura, 2012. "Nowcasting with Daily Data," 2012 Meeting Papers 555, Society for Economic Dynamics.
    9. 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.).
    10. Caroline Jardet & Baptiste Meunier, 2022. "Nowcasting world GDP growth with high‐frequency data," Post-Print hal-03647097, HAL.
    11. Marcellino, Massimiliano & Sivec, Vasja, 2016. "Monetary, fiscal and oil shocks: Evidence based on mixed frequency structural FAVARs," Journal of Econometrics, Elsevier, vol. 193(2), pages 335-348.
    12. Claudio Morana, 2014. "Factor Vector Autoregressive Estimation of Heteroskedastic Persistent and Non Persistent Processes Subject to Structural Breaks," Working Papers 273, University of Milano-Bicocca, Department of Economics, revised May 2014.
    13. Borus Jungbacker & Siem Jan Koopman & Michel van der Wel, 2009. "Smooth Dynamic Factor Analysis with an Application to the U.S. Term Structure of Interest Rates," CREATES Research Papers 2009-39, Department of Economics and Business Economics, Aarhus University.
    14. Boyarchenko, Nina & Adrian, Tobias & Giannone, Domenico, 2020. "Multimodality in Macro-Financial Dynamics," CEPR Discussion Papers 15088, C.E.P.R. Discussion Papers.
    15. 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, revised Jan 2025.
    16. Matteo Barigozzi & Daniele Massacci, 2022. "Modelling Large Dimensional Datasets with Markov Switching Factor Models," Papers 2210.09828, arXiv.org, revised Dec 2024.
    17. Ar'anzazu de Juan & Pilar Poncela & Vladimir Rodr'iguez-Caballero & Esther Ruiz, 2022. "Economic activity and climate change," Papers 2206.03187, arXiv.org, revised Jun 2022.
    18. Nina Boyarchenko & Richard K. Crump & Anna Kovner & Or Shachar, 2021. "Corporate Bond Market Distress," Staff Reports 957, Federal Reserve Bank of New York.
    19. Hideaki Hirata & M. Ayhan Kose & Christopher Otrok, 2013. "Regionalization vs. globalization," Working Papers 2013-002, Federal Reserve Bank of St. Louis.
    20. 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.
    21. Luciana Juvenal & Ivan Petrella, 2012. "Speculation in the oil market," Economic Synopses, Federal Reserve Bank of St. Louis.
    22. Scott Brave & Hesna Genay, 2011. "Federal Reserve policies and financial market conditions during the crisis," Working Paper Series WP-2011-04, Federal Reserve Bank of Chicago.
    23. Scott Brave & R. Andrew Butters, 2010. "Gathering insights on the forest from the trees: a new metric for financial conditions," Working Paper Series WP-2010-07, Federal Reserve Bank of Chicago.
    24. Gabriele Fiorentini & Alessandro Galesi & Enrique Sentana, 2015. "Fast ML Estimation of Dynamic Bifactor Models: An Application to European Inflation," Working Papers wp2015_1502, CEMFI.
    25. 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.
    26. Ricardo Reis & Mark W. Watson, 2010. "Relative Goods' Prices, Pure Inflation, and the Phillips Correlation," American Economic Journal: Macroeconomics, American Economic Association, vol. 2(3), pages 128-157, July.
    27. Onatski, Alexei, 2012. "Asymptotics of the principal components estimator of large factor models with weakly influential factors," Journal of Econometrics, Elsevier, vol. 168(2), pages 244-258.
    28. Deicy J. Cristiano & Manuel D. Hernández & José David Pulido, 2012. "Pronósticos de corto plazo en tiempo real para la actividad económica colombiana," Borradores de Economia 9827, Banco de la Republica.
    29. Antonello D'Agostino & Paolo Surico, 2009. "Does Global Liquidity Help to Forecast U.S. Inflation?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(2-3), pages 479-489, March.
    30. Domenico Giannone & Lucrezia Reichlin & Saverio Simonelli, 2009. "Nowcasting Euro Area Economic Activity in Real-Time: The Role of Confidence Indicators," CSEF Working Papers 240, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    31. Gobillon, Laurent & Magnac, Thierry, 2013. "Regional Policy Evaluation:Interactive Fixed Effects and Synthetic Controls," TSE Working Papers 13-419, Toulouse School of Economics (TSE).
    32. Jan J. J. Groen & George Kapetanios, 2009. "Model selection criteria for factor-augmented regressions," Staff Reports 363, Federal Reserve Bank of New York.
    33. Gary Koop & Dimitris Korobilis & Davide Pettenuzzo, 2016. "Bayesian Compressed Vector Autoregressions," Working Papers 103, Brandeis University, Department of Economics and International Business School.
    34. Giannoni, Marc & Boivin, Jean & Stevanovic, Dalibor, 2013. "Dynamic Effects of Credit Shocks in a Data-Rich Environment," CEPR Discussion Papers 9470, C.E.P.R. Discussion Papers.
    35. 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.
    36. Reichlin, Lucrezia & Giannone, Domenico & Modugno, Michele & Banbura, Marta, 2012. "Now-casting and the real-time data flow," CEPR Discussion Papers 9112, C.E.P.R. Discussion Papers.
    37. 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.
    38. Matteo Mogliani & Anna Simoni, 2020. "Bayesian MIDAS penalized regressions: Estimation, selection, and prediction," Post-Print hal-03089878, HAL.
    39. Davide Ferrari & Francesco Ravazzolo & Joaquin Vespignani, 2021. "Forecasting Energy Commodity Prices: A Large Global Dataset Sparse Approach," BEMPS - Bozen Economics & Management Paper Series BEMPS83, Faculty of Economics and Management at the Free University of Bozen.
    40. Monokroussos, George & Zhao, Yongchen, 2020. "Nowcasting in real time using popularity priors," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1173-1180.
    41. 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.
    42. Mirko Wiederholt & Emanuel Moench & Bartosz Maćkowiak, 2009. "Sectoral Price Data and Models of Price Setting," 2009 Meeting Papers 666, Society for Economic Dynamics.
    43. 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.
    44. Bastian Gribisch, 2018. "A latent dynamic factor approach to forecasting multivariate stock market volatility," Empirical Economics, Springer, vol. 55(2), pages 621-651, September.
    45. Patrick A. Adams & Tobias Adrian & Nina Boyarchenko & Domenico Giannone, 2020. "Forecasting Macroeconomic Risks," Staff Reports 914, Federal Reserve Bank of New York.
    46. Lasse Bork & Hans Dewachter & Romain Houssa, 2009. "Identification of Macroeconomic Factors in Large Panels," CREATES Research Papers 2009-43, Department of Economics and Business Economics, Aarhus University.
    47. Jie Wei & Yonghui Zhang, 2023. "Does Principal Component Analysis Preserve the Sparsity in Sparse Weak Factor Models?," Papers 2305.05934, arXiv.org, revised Nov 2024.
    48. Scott Brave & R. Andrew Butters, 2012. "Diagnosing the Financial System: Financial Conditions and Financial Stress," International Journal of Central Banking, International Journal of Central Banking, vol. 8(2), pages 191-239, June.
    49. Ciccarelli, Matteo & Mojon, Benoît, 2006. "Global Inflation," Kiel Working Papers 1337, Kiel Institute for the World Economy (IfW Kiel).
    50. Amélie Charles & Olivier Darné, 2022. "Backcasting world trade growth using data reduction methods," The World Economy, Wiley Blackwell, vol. 45(10), pages 3169-3191, October.
    51. 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).
    52. Francisco Serranito & Nicolas Himounet & Julien Vauday, 2023. "Uncertainty is bad for Business. Really?," Working Papers hal-04219283, HAL.
    53. 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.
    54. 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.).
    55. Branimir, Jovanovic & Magdalena, Petrovska, 2010. "Forecasting Macedonian GDP: Evaluation of different models for short-term forecasting," MPRA Paper 43162, University Library of Munich, Germany.
    56. Doz, Catherine & Giannone, Domenico & Reichlin, Lucrezia, 2011. "A two-step estimator for large approximate dynamic factor models based on Kalman filtering," Journal of Econometrics, Elsevier, vol. 164(1), pages 188-205, September.
    57. Zirogiannis, Nikolaos & Tripodis, Yorghos, 2013. "A Generalized Dynamic Factor Model for Panel Data: Estimation with a Two-Cycle Conditional Expectation-Maximization Algorithm," Working Paper Series 142752, University of Massachusetts, Amherst, Department of Resource Economics.
    58. Julieta Fuentes & Pilar Poncela & Julio Rodríguez, 2015. "Sparse Partial Least Squares in Time Series for Macroeconomic Forecasting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(4), pages 576-595, June.
    59. Laurent Ferrara & Dominique Guegan & Patrick Rakotomarolahy, 2010. "GDP nowcasting with ragged-edge data: a semi-parametric modeling," Post-Print halshs-00460461, HAL.
    60. Tobias Hartl & Roland Weigand, 2018. "Approximate State Space Modelling of Unobserved Fractional Components," Papers 1812.09142, arXiv.org, revised May 2020.
    61. Petrella, Ivan & Venditti, Fabrizio & Delle Monache, Davide, 2016. "Adaptive state space models with applications to the business cycle and financial stress," CEPR Discussion Papers 11599, C.E.P.R. Discussion Papers.
    62. 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.).
    63. Thomas Despois & Catherine Doz, 2021. "Identifying and interpreting the factors in factor models via sparsity: Different approaches," PSE Working Papers halshs-02235543, HAL.
    64. Luciani, Matteo & Pundit, Madhavi & Ramayandi, Arief & Veronese , Giovanni, 2015. "Nowcasting Indonesia," ADB Economics Working Paper Series 471, Asian Development Bank.
    65. Tóth, Peter, 2014. "Malý dynamický faktorový model na krátkodobé prognózovanie slovenského HDP [A Small Dynamic Factor Model for the Short-Term Forecasting of Slovak GDP]," MPRA Paper 63713, University Library of Munich, Germany.
    66. Lombardi, Marco J. & Maier, Philipp, 2011. "Forecasting economic growth in the euro area during the Great Moderation and the Great Recession," Working Paper Series 1379, European Central Bank.
    67. Scott Brave & R. Andrew Butters, 2014. "Nowcasting Using the Chicago Fed National Activity Index," Economic Perspectives, Federal Reserve Bank of Chicago, issue Q I, pages 19-37.
    68. Domenico Giannone & Lucrezia Reichlin & David H. Small, 2005. "Nowcasting GDP and inflation: the real-time informational content of macroeconomic data releases," Finance and Economics Discussion Series 2005-42, Board of Governors of the Federal Reserve System (U.S.).
    69. Hartigan, Luke & Morley, James, 2019. "A Factor Model Analysis of the Australian Economy and the Effects of Inflation Targeting," Working Papers 2019-10, University of Sydney, School of Economics, revised Nov 2019.
    70. 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.
    71. Carlos Perez Montes, 2015. "Estimation of Regulatory Credit Risk Models," Journal of Financial Services Research, Springer;Western Finance Association, vol. 48(2), pages 161-191, October.
    72. Gábor Pellényi, 2012. "The Sectoral Effects of Monetary Policy in Hungary: A Structural Factor Analysis," MNB Working Papers 2012/1, Magyar Nemzeti Bank (Central Bank of Hungary).
    73. 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.
    74. Tony Chernis & Calista Cheung & Gabriella Velasco, 2017. "A Three-Frequency Dynamic Factor Model for Nowcasting Canadian Provincial GDP Growth," Discussion Papers 17-8, Bank of Canada.
    75. Reis, Ricardo & Watson, Mark W., 2007. "Measuring changes in the value of the numeraire," Kiel Working Papers 1364, Kiel Institute for the World Economy (IfW Kiel).
    76. Kunpeng Li & Qi Li & Lina Lu, 2018. "Quasi Maximum Likelihood Analysis of High Dimensional Constrained Factor Models," Supervisory Research and Analysis Working Papers RPA 18-2, Federal Reserve Bank of Boston.
    77. Pellényi, Gábor, 2012. "A monetáris politika hatása a magyar gazdaságra. Elemzés strukturális, dinamikus faktormodellel [The sectoral effects of monetary policy in Hungary: a structural factor]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(3), pages 263-284.
    78. Luke Hartigan & James Morley, 2018. "A Factor Model Analysis of the Effects on Inflation Targeting on the Australian Economy," RBA Annual Conference Volume (Discontinued), in: John Simon & Maxwell Sutton (ed.),Central Bank Frameworks: Evolution or Revolution?, Reserve Bank of Australia.
    79. Tony Chernis & Rodrigo Sekkel, 2017. "A dynamic factor model for nowcasting Canadian GDP growth," Empirical Economics, Springer, vol. 53(1), pages 217-234, August.
    80. S. Boragan Aruoba & Francis X. Diebold, 2010. "Real-time macroeconomic monitoring: real activity, inflation, and interactions," Working Papers 10-5, Federal Reserve Bank of Philadelphia.
    81. Nimantha Manamperi, 2015. "A Comparative Analysis on US Financial Stress Indicators," International Journal of Economics and Financial Issues, Econjournals, vol. 5(2), pages 613-623.
    82. Angelini, Elena & Rünstler, Gerhard & Bańbura, Marta, 2008. "Estimating and forecasting the euro area monthly national accounts from a dynamic factor model," Working Paper Series 953, European Central Bank.
    83. Dias Francisco & Pinheiro Maximiano & Rua António, 2013. "Determining the number of global and country-specific factors in the euro area," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(5), pages 573-617, December.
    84. Noh-Sun Kwark & Changhyun Lee, 2020. "Asymmetric Effects of Financial Conditions on GDP Growth in Korea: A Quantile Regression Analysis," Working Papers 2005, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    85. 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.).
    86. Funke, Michael & Tsang, Andrew, 2019. "The direction and intensity of China's monetary policy conduct: A dynamic factor modelling approach," BOFIT Discussion Papers 8/2019, Bank of Finland Institute for Emerging Economies (BOFIT).
    87. Fausto Vieira & Fernando Chague, Marcelo Fernandes, 2016. "A dynamic Nelson-Siegel model with forward-looking indicators for the yield curve in the US," Working Papers, Department of Economics 2016_31, University of São Paulo (FEA-USP).
    88. Matteo Luciani & Lorenzo Ricci, 2014. "Nowcasting Norway," International Journal of Central Banking, International Journal of Central Banking, vol. 10(4), pages 215-248, December.
    89. Drew Creal & Bernd Schwaab & Siem Jan Koopman & Andre Lucas, 2011. "Observation Driven Mixed-Measurement Dynamic Factor Models with an Application to Credit Risk," Tinbergen Institute Discussion Papers 11-042/2/DSF16, Tinbergen Institute.
    90. Matteo Luciani, 2020. "Common and Idiosyncratic Inflation," Finance and Economics Discussion Series 2020-024, Board of Governors of the Federal Reserve System (U.S.).
    91. 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.
    92. Arrigoni, Simone & Bobasu, Alina & Venditti, Fabrizio, 2021. "The simpler, the better: Measuring financial conditions for monetary policy and financial stability," EIB Working Papers 2021/10, European Investment Bank (EIB).
    93. David de Antonio Liedo, 2014. "Nowcasting Belgium," Working Paper Research 256, National Bank of Belgium.
    94. Lucchetti, Riccardo & Venetis, Ioannis A., 2020. "A replication of "A quasi-maximum likelihood approach for large, approximate dynamic factor models" (Review of Economics and Statistics, 2012)," Economics Discussion Papers 2020-5, Kiel Institute for the World Economy (IfW Kiel).
    95. Giannone, Domenico & Monti, Francesca & Reichlin, Lucrezia, 2014. "Exploiting the monthly data-flow in structural forecasting," LSE Research Online Documents on Economics 57998, London School of Economics and Political Science, LSE Library.
    96. Nikolaou, Kleopatra & Modugno, Michele, 2009. "The forecasting power of internal yield curve linkages," Working Paper Series 1044, European Central Bank.
    97. Doemeland,Doerte & Estevão,Marcello & Jooste,Charl & Sampi Bravo,James Robert Ezequiel & Tsiropoulos,Vasileios, 2022. "Debt Vulnerability Analysis : A Multi-Angle Approach," Policy Research Working Paper Series 9929, The World Bank.
    98. Daniel Kaufmann & Rolf Scheufele, 2015. "Business tendency surveys and macroeconomic fluctuations," KOF Working papers 15-378, KOF Swiss Economic Institute, ETH Zurich.
    99. Eric Hillebrand & Jakob Guldbæk Mikkelsen & Lars Spreng & Giovanni Urga, 2023. "Exchange rates and macroeconomic fundamentals: Evidence of instabilities from time‐varying factor loadings," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(6), pages 857-877, September.
    100. 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.
    101. Nicolas Himounet, 2021. "Searching for the Nature of Uncertainty: Macroeconomic VS Financial," Working Papers 2021.05, International Network for Economic Research - INFER.
    102. Pappa, Evi & Molteni, Francesco, 2017. "The Combination of Monetary and Fiscal Policy Shocks: A TVP-FAVAR Approach," CEPR Discussion Papers 12541, C.E.P.R. Discussion Papers.
    103. Uluceviz, Erhan & Yilmaz, Kamil, 2021. "Measuring real–financial connectedness in the U.S. economy," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    104. Jianqing Fan & Yuan Liao & Han Liu, 2016. "An overview of the estimation of large covariance and precision matrices," Econometrics Journal, Royal Economic Society, vol. 19(1), pages 1-32, February.
    105. Nikolaos Zirogiannis & Yorghos Tripodis, 2018. "Dynamic factor analysis for short panels: estimating performance trajectories for water utilities," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(1), pages 131-150, March.
    106. Tobias Adrian & Nina Boyarchenko & Domenico Giannone, 2019. "Vulnerable Growth," American Economic Review, American Economic Association, vol. 109(4), pages 1263-1289, April.
    107. Matteo Barigozzi & Marc Hallin, 2023. "Dynamic Factor Models: a Genealogy," Working Papers ECARES 2023-15, ULB -- Universite Libre de Bruxelles.
    108. Karim Barhoumi & Laurent Ferrara, 2015. "A World Trade Leading Index (WTLI)," IMF Working Papers 2015/020, International Monetary Fund.
    109. Catherine Doz & Anna Petronevich, 2015. "Dating Business Cycle Turning Points for the French Economy: a MS-DFM approach," Documents de travail du Centre d'Economie de la Sorbonne 15009, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    110. Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers 2019-4, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.
    111. Germán López, 2015. "Forecast Accuracy of Small and Large Scale Dynamic Factor Models in Developing Economies," Working Papers. Serie AD 2015-03, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    112. Heather D. Gibson & Stephen G. Hall & George S. Tavlas, 2020. "A Suggestion for a Dynamic Multi Factor Model (DMFM)," Working Papers 282, Bank of Greece.
    113. Raïsa Basselier & David Antonio Liedo & Geert Langenus, 2018. "Nowcasting Real Economic Activity in the Euro Area: Assessing the Impact of Qualitative Surveys," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(1), pages 1-46, April.
    114. In Choi & Jorg Breitung, 2011. "Factor models," Working Papers 1121, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy), revised Dec 2011.
    115. Massimiliano Marcellino & Christian Schumacher, 2008. "Factor-MIDAS for Now- and Forecasting with Ragged-Edge Data: A Model Comparison for German GDP1," Working Papers 333, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    116. Helmut Herwartz & Christian Ochsner & Hannes Rohloff, 2021. "The Credit Composition of Global Liquidity," MAGKS Papers on Economics 202115, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    117. Shinya Tanaka & Eiji Kurozumi, 2010. "Investigating Finite Sample Properties of Estimators for Approximate Factor Models When N Is Small," Global COE Hi-Stat Discussion Paper Series gd10-156, Institute of Economic Research, Hitotsubashi University.
    118. Marco Del Negro & Christopher Otrok, 2008. "Dynamic factor models with time-varying parameters: measuring changes in international business cycles," Staff Reports 326, Federal Reserve Bank of New York.
    119. Stock, James H. & Watson, Mark, 2011. "Dynamic Factor Models," Scholarly Articles 28469541, Harvard University Department of Economics.
    120. Beyer, Robert C.M. & Stemmer, Michael A., 2016. "Polarization or convergence? An analysis of regional unemployment disparities in Europe over time," Economic Modelling, Elsevier, vol. 55(C), pages 373-381.
    121. 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.
    122. André Nunes Maranhão & Nicole Rennó Castro, 2023. "Dissecting Brazilian agriculture business cycles in high-dimensional and time-irregular span contexts," Empirical Economics, Springer, vol. 65(4), pages 1543-1578, October.
    123. Fiorentini, Gabriele & Galesi, Alessandro & Sentana, Enrique, 2018. "A spectral EM algorithm for dynamic factor models," Journal of Econometrics, Elsevier, vol. 205(1), pages 249-279.
    124. 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.
    125. Bai, Jushan & Li, Kunpeng, 2012. "Maximum likelihood estimation and inference for approximate factor models of high dimension," MPRA Paper 42099, University Library of Munich, Germany, revised 19 Oct 2012.
    126. Lasse Bork, 2009. "Estimating US Monetary Policy Shocks Using a Factor-Augmented Vector Autoregression: An EM Algorithm Approach," CREATES Research Papers 2009-11, Department of Economics and Business Economics, Aarhus University.
    127. Amélie Charles & Olivier Darné & Fabien Tripier, 2017. "Uncertainty and the Macroeconomy," Post-Print hal-01549625, HAL.
    128. Gabriele Fiorentini & Enrique Sentana, 2013. "Dynamic Specification Tests for Dynamic Factor Models," Working Papers wp2013_1306, CEMFI.
    129. Evzen Kocenda & Karen Poghosyan, 2018. "Nowcasting real GDP growth with business tendency surveys data: A cross country analysis," KIER Working Papers 1002, Kyoto University, Institute of Economic Research.
    130. Poghosyan, Karen & Poghosyan, Ruben, 2021. "On the applicability of dynamic factor models for forecasting real GDP growth in Armenia," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 61, pages 28-46.
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    255. Konstantin Kuck & Karsten Schweikert, 2021. "Forecasting Baden‐Württemberg's GDP growth: MIDAS regressions versus dynamic mixed‐frequency factor models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 861-882, August.
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    262. Lucas P. Harlaar & Jacques J.F. Commandeur & Jan A. van den Brakel & Siem Jan Koopman & Niels Bos & Frits D. Bijleveld, 2024. "Statistical Early Warning Models with Applications," Tinbergen Institute Discussion Papers 24-037/III, Tinbergen Institute.
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    264. Julian Ashwin & Eleni Kalamara & Lorena Saiz, 2024. "Nowcasting Euro area GDP with news sentiment: A tale of two crises," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(5), pages 887-905, August.
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  3. Catherine Doz & Eric Renault, 2004. "Conditionally Heteroskedastic Factor Models: Identification and Instrumental Variables Estimation," CIRANO Working Papers 2004s-37, CIRANO.

    Cited by:

    1. Prosper Dovonon & Alastair Hall, 2018. "The Asymptotic Properties of GMM and Indirect Inference under Second-order Identification," CIRANO Working Papers 2018s-37, CIRANO.
    2. Weber, Enzo, 2013. "Decomposing U.S. Stock Market Comovement into spillovers and common factors," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 106-118.
    3. Anderson, Heather M. & Vahid, Farshid, 2007. "Forecasting the Volatility of Australian Stock Returns: Do Common Factors Help?," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 76-90, January.
    4. Prosper Dovonon & Alastair R. Hall, 2017. "The Asymptotic Properties of GMM and Indirect Inference Under Second-Order Identification," Economics Discussion Paper Series 1705, Economics, The University of Manchester.
    5. Dovonon, Prosper & Hall, Alastair R., 2018. "The asymptotic properties of GMM and indirect inference under second-order identification," Journal of Econometrics, Elsevier, vol. 205(1), pages 76-111.
    6. García-Ferrer, Antonio & González-Prieto, Ester & Peña, Daniel, 2012. "A conditionally heteroskedastic independent factor model with an application to financial stock returns," International Journal of Forecasting, Elsevier, vol. 28(1), pages 70-93.

  4. Doz, C. & Lenglart, F., 1998. "Analyse factorielle dynamique: test du nombre de facteurs, estimation, et application a l'enquete de conjoncture dans l'industrie," Papers 9831, Paris X - Nanterre, U.F.R. de Sc. Ec. Gest. Maths Infor..

    Cited by:

    1. Thomas A. Knetsch, 2004. "Evaluating the German Inventory Cycle – Using Data from the Ifo Business Survey," CESifo Working Paper Series 1202, CESifo.

Articles

  1. Catherine Doz & Domenico Giannone & Lucrezia Reichlin, 2012. "A Quasi–Maximum Likelihood Approach for Large, Approximate Dynamic Factor Models," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1014-1024, November.
    See citations under working paper version above.
  2. Doz, Catherine & Giannone, Domenico & Reichlin, Lucrezia, 2011. "A two-step estimator for large approximate dynamic factor models based on Kalman filtering," Journal of Econometrics, Elsevier, vol. 164(1), pages 188-205, September.
    See citations under working paper version above.
  3. Catherine Doz & Eric Renault, 2006. "Factor Stochastic Volatility in Mean Models: A GMM Approach," Econometric Reviews, Taylor & Francis Journals, vol. 25(2-3), pages 275-309.

    Cited by:

    1. Sentana, Enrique & Calzolari, Giorgio & Fiorentini, Gabriele, 2008. "Indirect estimation of large conditionally heteroskedastic factor models, with an application to the Dow 30 stocks," Journal of Econometrics, Elsevier, vol. 146(1), pages 10-25, September.
    2. Anders Johansson, 2009. "Stochastic volatility and time-varying country risk in emerging markets," The European Journal of Finance, Taylor & Francis Journals, vol. 15(3), pages 337-363.
    3. Bastian Gribisch, 2016. "Multivariate Wishart stochastic volatility and changes in regime," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 100(4), pages 443-473, October.
    4. Dovonon, Prosper & Renault, Eric, 2011. "Testing for Common GARCH Factors," MPRA Paper 40224, University Library of Munich, Germany.
    5. Mike K. P. So & C. Y. Choi, 2009. "A threshold factor multivariate stochastic volatility model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(8), pages 712-735.
    6. Dovonon, Prosper & Gonçalves, Sílvia, 2017. "Bootstrapping the GMM overidentification test under first-order underidentification," Journal of Econometrics, Elsevier, vol. 201(1), pages 43-71.
    7. Dovonon, Prosper & Hall, Alastair R., 2018. "The asymptotic properties of GMM and indirect inference under second-order identification," Journal of Econometrics, Elsevier, vol. 205(1), pages 76-111.
    8. M. Hashem Pesaran & Paolo Zaffaroni, 2009. "Optimality and Diversifiability of Mean Variance and Arbitrage Pricing Portfolios," CESifo Working Paper Series 2857, CESifo.
    9. Kuruppuarachchi, Duminda & Premachandra, I.M., 2016. "Information spillover dynamics of the energy futures market sector: A novel common factor approach," Energy Economics, Elsevier, vol. 57(C), pages 277-294.
    10. Peter Boswijk, H. & van der Weide, Roy, 2011. "Method of moments estimation of GO-GARCH models," Journal of Econometrics, Elsevier, vol. 163(1), pages 118-126, July.
    11. Serda S. Öztürk & Thanasis Stengos, 2017. "A Multivariate Stochastic Volatility Model Applied to a Panel of S&P500 Stocks in Different Industries," International Review of Finance, International Review of Finance Ltd., vol. 17(3), pages 479-490, September.
    12. Mardi Dungey & Eric Renault, 2018. "Identifying contagion," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(2), pages 227-250, March.
    13. Dovonon, Prosper & Hall, Alastair R. & Kleibergen, Frank, 2020. "Inference in second-order identified models," Journal of Econometrics, Elsevier, vol. 218(2), pages 346-372.
    14. Zhou, Xiaocong & Nakajima, Jouchi & West, Mike, 2014. "Bayesian forecasting and portfolio decisions using dynamic dependent sparse factor models," International Journal of Forecasting, Elsevier, vol. 30(4), pages 963-980.

  4. Catherine Doz & Guillaume Rabault & Nicolas Sobczak, 1995. "Décomposition tendance-cycle : estimations par des méthodes statistiques univariées," Économie et Prévision, Programme National Persée, vol. 120(4), pages 73-93.

    Cited by:

    1. Hervé Le Bihan, 2004. "Tests de ruptures : une application au PIB tendanciel français," Économie et Prévision, Programme National Persée, vol. 163(2), pages 133-154.

  5. Catherine Doz, 1993. "Note sur les tests de rationalité des prévisions," Économie et Prévision, Programme National Persée, vol. 108(2), pages 129-133.

    Cited by:

    1. Thomas Jobert & Lionel Persyn, 2012. "Quelques constats sur les prévisions conjoncturelles de la croissance française," Revue d'économie politique, Dalloz, vol. 122(6), pages 833-849.
    2. Karine Bouthevillain & Alexandre Mathis, 1995. "Prévisions : mesures, erreurs et principaux résultats," Économie et Statistique, Programme National Persée, vol. 285(1), pages 89-100.

  6. Catherine Doz & Pierre Malgrange, 1992. "Modèles VAR et prévisions à court terme," Économie et Prévision, Programme National Persée, vol. 106(5), pages 109-122.

    Cited by:

    1. Gossé, Jean-Baptiste & Guillaumin, Cyriac, 2013. "L’apport de la représentation VAR de Christopher A. Sims à la science économique," L'Actualité Economique, Société Canadienne de Science Economique, vol. 89(4), pages 309-319, Décembre.
    2. Karine Bouthevillain & Alexandre Mathis, 1995. "Prévisions : mesures, erreurs et principaux résultats," Économie et Statistique, Programme National Persée, vol. 285(1), pages 89-100.
    3. Karine Bouthevillain, 1993. "La prévision macro-économique : précision relative et consensus," Économie et Prévision, Programme National Persée, vol. 108(2), pages 97-126.
    4. Alexandre Mathis & Andrew Brociner, 1994. "Retour vers le futur. Une analyse rétrospective des prévisions de MOSAÏQUE," Revue de l'OFCE, Programme National Persée, vol. 49(1), pages 207-228.

  7. Didier Borowski & Carine Bouthevillain & Catherine Doz & Pierre Malgrange & Pierre Morin, 1991. "Vingt ans de prévisions macro-économiques : une évaluation sur données françaises," Économie et Prévision, Programme National Persée, vol. 99(3), pages 43-65.

    Cited by:

    1. Karine Bouthevillain & Alexandre Mathis, 1995. "Prévisions : mesures, erreurs et principaux résultats," Économie et Statistique, Programme National Persée, vol. 285(1), pages 89-100.
    2. Peaucelle, Irina, 1996. "Prévisions de court terme pour analyser les réformes en Russie (les)," CEPREMAP Working Papers (Couverture Orange) 9610, CEPREMAP.
    3. Karine Bouthevillain, 1993. "La prévision macro-économique : précision relative et consensus," Économie et Prévision, Programme National Persée, vol. 108(2), pages 97-126.
    4. Alexandre Mathis & Andrew Brociner, 1994. "Retour vers le futur. Une analyse rétrospective des prévisions de MOSAÏQUE," Revue de l'OFCE, Programme National Persée, vol. 49(1), pages 207-228.
    5. Pierre Malgrange & Silvia Mira d'Ercole, 1993. "Erreurs de prévision ex ante et ex post," Économie et Prévision, Programme National Persée, vol. 108(2), pages 135-138.
    6. Catherine Doz & Pierre Malgrange, 1992. "Modèles VAR et prévisions à court terme," Économie et Prévision, Programme National Persée, vol. 106(5), pages 109-122.

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