Bias-Corrected Common Correlated Effects Pooled Estimation In Homogeneous Dynamic Panels

Ignace De Vos, Gerdie Everaert

Research output: Working paper/PreprintWorking paper

Abstract

This paper extends the Common Correlated Effects Pooled (CCEP) estimator to homogeneous dynamic panels. In this setting CCEP suffers from a large bias when the time series dimension (T) is fixed. We develop a bias-corrected estimator that is valid for a multi-factor error structure provided that a sufficient number of cross-sectional averages, and lags thereof, are added to the model. We show that the resulting CCEPbc estimator is consistent as the number of cross-sections (N) tends to infinity, both for T fixed or growing large. Monte Carlo experiments show that our correction offers strong improvements in terms of bias and variance.
Original languageEnglish
Place of PublicationGhent
Publication statusPublished - 2016
Externally publishedYes

Publication series

NameWorking Paper
PublisherGhent University, Faculty of Economics and Business Administration
No.2016/920

Subject classification (UKÄ)

  • Probability Theory and Statistics
  • Economics

Free keywords

  • Factor augmented regression
  • multi-factor error structure
  • dynamic panel bias

Fingerprint

Dive into the research topics of 'Bias-Corrected Common Correlated Effects Pooled Estimation In Homogeneous Dynamic Panels'. Together they form a unique fingerprint.

Cite this