Authors/Contributors

Badi BaltagiFollow

Document Type

Working Paper

Date

Spring 3-2015

Keywords

Heterogeneous Panels, Cross-sectional Dependence, Structural Breaks, Common Correlated Effects

Language

English

Disciplines

Econometrics | Economics | Longitudinal Data Analysis and Time Series | Mathematics

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.

ISSN

1525-3066

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.

wp179.pdf (1415 kB)

Source

Local input

Creative Commons License

Creative Commons Attribution 3.0 License
This work is licensed under a Creative Commons Attribution 3.0 License.

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