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Title: Estimation of Heterogeneous Panels with Structural Breaks
Authors: Baltagi, Badi Hani
Feng, Q.
Kao, C.
First Published: 31-Oct-2015
Publisher: Elsevier
Citation: Journal of Econometrics 2016, 191, pp. 176–195
Abstract: This paper extends Pesaranís (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 have 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.
DOI Link: 10.1016/j.jeconom.2015.03.048
ISSN: 0304-4076
Version: Post-print
Status: Peer-reviewed
Type: Journal Article
Rights: © 2015, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Description: JEL Classification: C23, C33
The file associated with this record is under embargo until 24 months after publication, in accordance with the publisher's self-archiving policy. The full text may be available through the publisher links provided above.
Appears in Collections:Published Articles, Dept. of Economics

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