A two-step estimator for large approximate dynamic factor models based on Kalman filtering

Journal article: This paper shows consistency of a two step estimation of the factors in a dynamic approximate factor model when the panel of time series is large (n large). In the first step, the parameters of the model are estimated from an OLS on principal components. In the second step, the factors are estimated via the Kalman smoother. The analysis develops the theory for the estimator considered in Giannone, Reichlin, and Sala (2004) and Giannone, Reichlin, and Small (2008) and for the many empirical papers using this framework for nowcasting.

Author(s)

Catherine Doz, Domenico Giannone, Lucrezia Reichlin

Journal
  • Econometrics
Date of publication
  • 2011
Keywords JEL
C C32 C33 C51
Keywords
  • Factor Models
  • Kalman Filter
  • Principal Components
  • Large Cross-sections
Pages
  • 188-205
Version
  • 1
Volume
  • 164