Estimation of panel group structure models with structural breaks in group memberships and coefficients

This paper considers linear panel data models with a grouped pattern of heterogeneity when the latent group membership structure and/or the values of slope coefficients change at a break point. We propose a least squares approach to jointly estimate the break point, group membership structure, and c...

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Bibliographic Details
Published in:Journal of econometrics 2023-03, Vol.233 (1), p.45-65
Main Authors: Lumsdaine, Robin L., Okui, Ryo, Wang, Wendun
Format: Article
Language:English
Subjects:
Group membership change
Grouped patterns
Panel data
Structural breaks
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Summary:This paper considers linear panel data models with a grouped pattern of heterogeneity when the latent group membership structure and/or the values of slope coefficients change at a break point. We propose a least squares approach to jointly estimate the break point, group membership structure, and coefficients. The proposed estimators are consistent, and the asymptotic distribution of the coefficient estimators is identical to that under known break point and group structure even when the cross-sectional sample size is much larger than the length of time series. Monte Carlo simulations and an empirical example illustrate the use of the approach and associated inference.
ISSN:0304-4076
1872-6895
DOI:10.1016/j.jeconom.2022.01.001