A Quasi Maximum Likelihood Approach for Large Approximate Dynamic Factor Models

Lucrezia Reichlin, Catherine Doz and Domenico Giannone

No 5724, CEPR Discussion Papers from C.E.P.R. Discussion Papers

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 (search for similar items in EconPapers)
JEL-codes: C32 C33 C51 (search for similar items in EconPapers)
Date: 2006-06
New Economics Papers: this item is included in nep-ecm and nep-ets
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Citations: View citations in EconPapers (121)

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Related works:
Journal Article: A Quasi–Maximum Likelihood Approach for Large, Approximate Dynamic Factor Models (2012)
Working Paper: A Quasi Maximum Likelihood Approach for Large, Approximate Dynamic Factor Models (2012)
Working Paper: A Quasi Maximum Likelihood Approach for Large, Approximate Dynamic Factor Models (2012)
Working Paper: A Quasi Maximum Likelihood Approach for Large, Approximate Dynamic Factor Models (2012)
Working Paper: A Quasi Maximum Likelihood Approach for Large Approximate Dynamic Factor Models (2008)
Working Paper: A quasi maximum likelihood approach for large approximate dynamic factor models (2006)
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