This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

A quasi maximum likelihood approach for large approximate dynamic factor models

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Catherine Doz () (Directrice de l'UFR Economie Gestion, University of Cergy-Pontoise - Department of Economics, 33 Boulevard du port, F-95011 Cergy-Pontoise Cedex, France.)
Domenico Giannone () (Free University of Brussels (VUB/ULB) - European Center for Advanced Research in Economics and Statistics (ECARES), Ave. Franklin D Roosevelt, 50 - C.P. 114, B-1050 Brussels, Belgium.)
Lucrezia Reichlin () (European Central Bank, Kaiserstrasse 29, 60311 Frankfurt am Main, Germany.)

Additional information is available for the following registered author(s):

Abstract

This paper considers quasi-maximum likelihood estimations of a dynamic approximate factor model when the panel of time series is large. Maximum likelihood is analyzed under different sources of misspecification: omitted serial correlation of the observations and cross-sectional correlation of the idiosyncratic components. It is shown that the effects of misspecification on the estimation of the common factors is negligible for large sample size (T) and the cross-sectional dimension (n). The estimator is feasible when n is large and easily implementable using the Kalman smoother and the EM algorithm as in traditional factor analysis. Simulation results illustrate what are the empirical conditions in which we can expect improvement with respect to simple principle components considered by Bai (2003), Bai and Ng (2002), Forni, Hallin, Lippi, and Reichlin (2000, 2005b), Stock and Watson (2002a,b). JEL Classification: C51, C32, C33.

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help file. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.ecb.europa.eu/pub/pdf/scpwps/ecbwp674.pdf
File Format: application/pdf
File Function:
Download Restriction: no

Publisher Info
Paper provided by European Central Bank in its series Working Paper Series with number 674.

Download reference. The following formats are available: HTML, plain text, BibTeX, RIS (EndNote), ReDIF
Length: 35 pages
Date of creation: Sep 2006
Date of revision:
Handle: RePEc:ecb:ecbwps:20060674

Contact details of provider:
Postal: Postfach 16 03 19, Frankfurt am Main, Germany
Phone: +49 69 1344 0
Fax: +49 69 1344 6000
Web page: http://www.ecb.europa.eu/home/html/index.en.html
More information through EDIRC

Order Information:
Postal: Press and Information Division, European Central Bank, Kaiserstrasse 29, 60311 Frankfurt am Main, Germany
Email:

For technical questions regarding this item, or to correct its listing, contact: (Official Publications).

Related research
Keywords: Factor Model large cross-sections Quasi Maximum Likelihood.

Other versions of this item:

This paper has been announced in the following NEP Reports: References listed on IDEAS
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. Domenico Giannone & Lucrezia Reichlin & Luca Sala, . "Monetary Policy in Real Time," Working Papers 284, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University. [Downloadable!]
    Other versions:
  2. Forni, Mario & Reichlin, Lucrezia, 2001. "Federal policies and local economies: Europe and the US," European Economic Review, Elsevier, vol. 45(1), pages 109-134, January. [Downloadable!] (restricted)
  3. M. Ayhan Kose & Christopher Otrok & Charles H. Whiteman, 2003. "International Business Cycles: World, Region, and Country-Specific Factors," American Economic Review, American Economic Association, vol. 93(4), pages 1216-1239, September. [Downloadable!] (restricted)
  4. Jean Boivin & Marc Giannoni, 2006. "DSGE Models in a Data-Rich Environment," NBER Working Papers 12772, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
    Other versions:
  5. Thomas J. Sargent & Christopher A. Sims, 1977. "Business cycle modeling without pretending to have too much a priori economic theory," Working Papers 55, Federal Reserve Bank of Minneapolis. [Downloadable!]
  6. Jushan Bai, 2003. "Inferential Theory for Factor Models of Large Dimensions," Econometrica, Econometric Society, vol. 71(1), pages 135-171, January. [Downloadable!] (restricted)
  7. 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!]
    Other versions:
  8. Connor, Gregory & Korajczyk, Robert A., 1986. "Performance measurement with the arbitrage pricing theory : A new framework for analysis," Journal of Financial Economics, Elsevier, vol. 15(3), pages 373-394, March. [Downloadable!] (restricted)
  9. 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)
  10. Giannone, Domenico & Reichlin, Lucrezia & Small, David, 2005. "Nowcasting GDP and Inflation: The Real Time Informational Content of Macroeconomic Data Releases," CEPR Discussion Papers 5178, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
    Other versions:
  11. Stock, J.H. & Watson, M.W., 1989. "New Indexes Of Coincident And Leading Economic Indicators," Papers 178d, Harvard - J.F. Kennedy School of Government.
    Other versions:
  12. Ben S. Bernanke & Ilian Mihov, 1995. "Measuring Monetary Policy," NBER Working Papers 5145, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
    Other versions:
  13. 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)
  14. Doz, Catherine & Giannone, Domenico & Reichlin, Lucrezia, 2007. "A Two-Step Estimator for Large Approximate Dynamic Factor Models Based on Kalman Filtering," CEPR Discussion Papers 6043, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
    Other versions:
  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)
    Other versions:
Full references

Cited by:
(explanations, 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. Massimiliano Marcellino & Christian Schumacher, . "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. [Downloadable!]
    Other versions:
  2. Matteo Ciccarelli & Benoît Mojon, 2007. "Global Inflation," Kiel Working Papers 1337, Kiel Institute for the World Economy. [Downloadable!]
    Other versions:
  3. Hendry, David F & Hubrich, Kirstin, 2006. "Forecasting Economic Aggregates by Disaggregates," CEPR Discussion Papers 5485, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
    Other versions:
  4. Domenico Giannone & Lucrezia Reichlin & David H Small, 2007. "Nowcasting GDP and Inflation: The Real-Time Informational Content of Macroeconomic Data Releases," Money Macro and Finance (MMF) Research Group Conference 2006 164, Money Macro and Finance Research Group. [Downloadable!]
    Other versions:
  5. Marta Banbura & Gerhard Rünstler, 2007. "A look into the factor model black box - publication lags and the role of hard and soft data in forecasting GDP," Working Paper Series 751, European Central Bank. [Downloadable!]
  6. Doz, Catherine & Giannone, Domenico & Reichlin, Lucrezia, 2007. "A Two-Step Estimator for Large Approximate Dynamic Factor Models Based on Kalman Filtering," CEPR Discussion Papers 6043, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
    Other versions:
  7. Borus Jungbacker & Siem Jan Koopman, 2008. "Likelihood-based Analysis for Dynamic Factor Models," Tinbergen Institute Discussion Papers 08-007/4, Tinbergen Institute. [Downloadable!]
  8. D'Agostino, A & Surico, P, 2007. "Does global liquidity help to forecast US inflation?," MPRA Paper 6283, University Library of Munich, Germany. [Downloadable!]
  9. Lucia Alessi & Matteo Barigozzi & Marco Capasso, 2006. "Dynamic Factor GARCH: Multivariate Volatility Forecast for a Large Number of Series," LEM Papers Series 2006/25, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy. [Downloadable!]
  10. Lucia Alessi & Matteo Barigozzi & Marco Capasso, 2007. "A Review of Nonfundamentalness and Identification in Structural VAR Models," LEM Papers Series 2007/22, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy. [Downloadable!]
Statistics
Access and download statistics

Did you know? It is the publishers that input data about their publications, as there is no staff at RePEc.

This page was last updated on 2008-8-15.

This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.