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

A-Tier
Journal: Journal of Econometrics
Year: 2011
Volume: 164
Issue: 1
Pages: 188-205

Score contribution per author:

1.341 = (α=2.01 / 3 authors) × 2.0x A-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

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 et al. (2004) and Giannone et al. (2008) and for the many empirical papers using this framework for nowcasting.

Technical Details

RePEc Handle
repec:eee:econom:v:164:y:2011:i:1:p:188-205
Journal Field
Econometrics
Author Count
3
Added to Database
2026-01-25