A Quasi Maximum Likelihood Approach for Large Approximate Dynamic Factor Models

31 Pages Posted: 17 Aug 2006

See all articles by Lucrezia Reichlin

Lucrezia Reichlin

London Business School; Université Libre de Bruxelles (ULB) - European Center for Advanced Research in Economics and Statistics (ECARES); Centre for Economic Policy Research (CEPR); European Central Bank (ECB)

Catherine Doz

University of Cergy-Pontoise - Department of Economics

Domenico Giannone

Federal Reserve Banks - Federal Reserve Bank of New York; Centre for Economic Policy Research (CEPR)

Multiple version iconThere are 2 versions of this paper

Date Written: June 2006

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).

Keywords: Factor model, large cross-sections, Quasi Maximum Likelihood

JEL Classification: C32, C33, C51

Suggested Citation

Reichlin, Lucrezia and Doz, Catherine and Giannone, Domenico, A Quasi Maximum Likelihood Approach for Large Approximate Dynamic Factor Models (June 2006). CEPR Discussion Paper No. 5724. Available at SSRN: https://ssrn.com/abstract=924885

Lucrezia Reichlin (Contact Author)

London Business School ( email )

Sussex Place
Regent's Park
London, London NW1 4SA
United Kingdom

Université Libre de Bruxelles (ULB) - European Center for Advanced Research in Economics and Statistics (ECARES) ( email )

Ave. Franklin D Roosevelt, 50 - C.P. 114
Brussels, B-1050
Belgium
+32 2 650 4221 (Phone)
+32 2 650 4475 (Fax)

Centre for Economic Policy Research (CEPR)

London
United Kingdom

European Central Bank (ECB) ( email )

Sonnemannstrasse 22
Frankfurt am Main, 60314
Germany

Catherine Doz

University of Cergy-Pontoise - Department of Economics ( email )

Site des Chênes 1
33 boulevard du Port
Cergy-Pontoise, Cédex F-95011
France
+33 1 34 25 60 53 (Phone)
+33 1 34 25 60 52 (Fax)

Domenico Giannone

Federal Reserve Banks - Federal Reserve Bank of New York ( email )

33 Liberty Street
New York, NY 10045
United States

Centre for Economic Policy Research (CEPR)

London
United Kingdom

Register to save articles to
your library

Register

Paper statistics

Downloads
23
Abstract Views
722
PlumX Metrics