DP6043 A Two-Step Estimator for Large Approximate Dynamic Factor Models Based on Kalman Filtering

Author(s): Catherine Doz , Domenico Giannone , Lucrezia Reichlin

Publication Date: January 2007

Keyword(s): Factor Models , Kalman filter , large cross-sections , principal components

JEL(s): C32 , C33 , C51

Programme Areas: International Macroeconomics

Link to this Page: www.cepr.org/pubs/dps/DP6043.asp.asp

This paper shows consistency of a two step estimator of the parameters of a dynamic approximate factor model when the panel of time series is large (n large). In the first step, the parameters are first estimated from an OLS on principal components. In the second step, the factors are estimated via the Kalman smoother. This projection allows to consider dynamics in the factors and heteroskedasticity in the idiosyncratic variance. The analysis provides theoretical backing for the estimator considered in Giannone, Reichlin, and Sala (2004) and Giannone, Reichlin, and Small (2005).