Description/Abstract
This paper extends Pesaran's (2006) work on common correlated effects (CCE) estimators for large heterogeneous panels with a general multifactor error structure by allowing for unknown common structural breaks. Structural breaks due to new policy implementation or major technological shocks, are more likely to occur over a longer time span. Consequently, ignoring structural breaks may lead to inconsistent estimation and invalid inference. We propose a general framework that includes heterogeneous panel data models and structural break models as special cases. The least squares method proposed by Bai (1997a, 2010) is applied to estimate the common change points, and the consistency of the estimated change points is established. We find that the CCE estimator has the same asymptotic distribution as if the true change points were known. Additionally, Monte Carlo simulations are used to verify the main results of this paper.
Document Type
Working Paper
Date
Spring 3-2015
Keywords
Heterogeneous Panels, Cross-sectional Dependence, Structural Breaks, Common Correlated Effects
Language
English
Series
Working Papers Series
Disciplines
Econometrics | Economics | Longitudinal Data Analysis and Time Series | Mathematics
ISSN
1525-3066
Recommended Citation
Baltagi, Badi, "Estimation of Heterogeneous Panels with Structural Breaks" (2015). Center for Policy Research. 213.
https://surface.syr.edu/cpr/213
Source
Local input
Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.
Included in
Econometrics Commons, Longitudinal Data Analysis and Time Series Commons, Mathematics Commons
Additional Information
Working paper no. 179
The authors would like to thank the editor Han Hong, the associate editor and three anonymous referees for their constructive comments and suggestions.