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A parametric estimation method for dynamic factor models of large dimensions

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George Kapetanios
Massimiliano Marcellino

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Abstract

The estimation of dynamic factor models for large sets of variables has attracted considerable attention recently, because of the increased availability of large data sets. In this article we propose a new parametric methodology for estimating factors from large data sets based on state-space models and discuss its theoretical properties. In particular, we show that it is possible to estimate consistently the factor space. We also conduct a set of simulation experiments that show that our approach compares well with existing alternatives. Copyright 2009 The Authors. Journal compilation 2009 Blackwell Publishing Ltd

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File URL: http://www.blackwell-synergy.com/doi/abs/10.1111/j.1467-9892.2009.00607.x
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Article provided by Blackwell Publishing in its journal Journal of Time Series Analysis.

Volume (Year): 30 (2009)
Issue (Month): 2 (03)
Pages: 208-238
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Handle: RePEc:bla:jtsera:v:30:y:2009:i:2:p:208-238

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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2003. "The Generalized Dynamic Factor Model. One-Sided Estimation and Forecasting," LEM Papers Series 2003/13, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy. [Downloadable!]
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  2. Forni, Mario & Reichlin, Lucrezia, 1997. "National Policies and Local Economies: Europe and the United States," CEPR Discussion Papers 1632, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
  3. Chamberlain, Gary & Rothschild, Michael, 1983. "Arbitrage, Factor Structure, and Mean-Variance Analysis on Large Asset Markets," Econometrica, Econometric Society, vol. 51(5), pages 1281-304, September. [Downloadable!] (restricted)
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  4. Forni, Mario & Reichlin, Lucrezia, 1995. "Let's Get Real: A Dynamic Factor Analytical Approach to Disaggregated Business Cycle," CEPR Discussion Papers 1244, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
  5. Forni, Mario & Reichlin, Lucrezia, 1996. "Dynamic Common Factors in Large Cross-Sections," Empirical Economics, Springer, vol. 21(1), pages 27-42.
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  6. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 2000. "Reference Cycles: The NBER Methodology Revisited," CEPR Discussion Papers 2400, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
  7. George Kapetanios & Massimiliano Marcellino, 2003. "A Comparison of Estimation Methods for Dynamic Factor Models of Large Dimensions," Working Papers 489, Queen Mary, University of London, Department of Economics. [Downloadable!]
  8. Carlo Ambrogio Favero & Massimilano Marcellino & Francesca Neglia, . "Principal components at work: The empirical analysis of monetary policy with large datasets," Working Papers 223, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University. [Downloadable!]
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  9. James H. Stock & Mark W. Watson, 1989. "New Indexes of Coincident and Leading Economic Indicators," NBER Chapters, in: NBER Macroeconomics Annual 1989, Volume 4, pages 351-409 National Bureau of Economic Research, Inc. [Downloadable!]
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  10. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-62, April.
  11. Danny Quah & Thomas J. Sargent, 1992. "A dynamic index model for large cross sections," Discussion Paper / Institute for Empirical Macroeconomics 77, Federal Reserve Bank of Minneapolis. [Downloadable!]
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  12. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 1999. "The Generalized Dynamic Factor Model: Identification and Estimation," CEPR Discussion Papers 2338, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
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  13. James H. Stock & Mark W. Watson, 1988. "A Probability Model of The Coincident Economic Indicators," NBER Working Papers 2772, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  14. Connor, Gregory & Korajczyk, Robert A, 1993. " A Test for the Number of Factors in an Approximate Factor Model," Journal of Finance, American Finance Association, vol. 48(4), pages 1263-91, September. [Downloadable!] (restricted)
  15. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January. [Downloadable!] (restricted)
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  1. Kuzin, Vladimir & Marcellino, Massimiliano & Schumacher, Christian, 2009. "Pooling versus model selection for nowcasting with many predictors: an application to German GDP," Discussion Paper Series 1: Economic Studies 2009,03, Deutsche Bundesbank, Research Centre. [Downloadable!]
    Other versions:
  2. Massimiliano Marcellino & Christian Schumacher, 2008. "Factor-MIDAS for Now- and Forecasting with Ragged-Edge Data: A Model Comparison for German GDP," Economics Working Papers ECO2008/16, European University Institute. [Downloadable!]
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  3. Boriss Siliverstovs & Konstantin A. Kholodilin, 2006. "On Selection of Components for a Diffusion Index Model: It's not the Size, It's How You Use It," Discussion Papers of DIW Berlin 598, DIW Berlin, German Institute for Economic Research. [Downloadable!]
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  4. Konstantin A. Kholodilin & Boriss Siliverstovs, 2005. "On the Forecasting Properties of the Alternative Leading Indicators for the German GDP: Recent Evidence," Discussion Papers of DIW Berlin 522, DIW Berlin, German Institute for Economic Research. [Downloadable!]
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  5. Eickmeier, Sandra, 2006. "Comovements and heterogeneity in the Comovements and heterogeneity in the dynamic factor model," Discussion Paper Series 1: Economic Studies 2006,31, Deutsche Bundesbank, Research Centre. [Downloadable!]
  6. Anindya Banerjee & Massimiliano Marcellino & Igor Masten, 2008. "Forecasting Macroeconomic Variables Using Diffusion Indexes in Short Samples with Structural Change," Economics Working Papers ECO2008/17, European University Institute. [Downloadable!]
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  7. Oliver Hülsewig & Johannes Mayr & Timo Wollmershäuser, 2008. "Forecasting Euro Area Real GDP: Optimal Pooling of Information," CESifo Working Paper Series CESifo Working Paper No. , CESifo Group Munich. [Downloadable!]
  8. Alain N. Kabundi & Francisco Nadal-De Simone, 2007. "France in the Global Economy: A Structural Approximate Dynamic Factor Model Analysis," IMF Working Papers 07/129, International Monetary Fund. [Downloadable!]
  9. Gonzalo Camba-Méndez & George Kapetanios, 2004. "Forecasting euro area inflation using dynamic factor measures of underlying inflation," Working Paper Series 402, European Central Bank. [Downloadable!]
  10. Filippo Altissimo & Riccardo Cristadoro & Mario Forni & Marco Lippi & Giovanni Veronese, 2007. "New Eurocoin: Tracking Economic Growth in Real Time," Temi di discussione (Economic working papers) 631, Bank of Italy, Economic Research Department. [Downloadable!]
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  11. Sandra Eickmeier & Joerg Breitung, 2006. "Business cycle transmission from the euro area to CEECs," Computing in Economics and Finance 2006 229, Society for Computational Economics. [Downloadable!]
  12. Heather Anderson & Fashid Vahid, 2005. "Forecasting the Volatility of Australian Stock Returns: Do Common Factors Help?," ANUCBE School of Economics Working Papers 2005-451, Australian National University, College of Business and Economics, School of Economics. [Downloadable!]
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