Heterogeneous structural breaks in panel data models

Ryo Okui and Wendun Wang

Journal of Econometrics, 2021, vol. 220, issue 2, 447-473

Abstract: This paper develops a new model and estimation procedure for panel data that allows us to identify heterogeneous structural breaks. We model individual heterogeneity using a grouped pattern. For each group, we allow common structural breaks in the coefficients. However, the number, timing, and size of these breaks can differ across groups. We develop a hybrid estimation procedure of the grouped fixed effects approach and adaptive group fused Lasso. We show that our method can consistently identify the latent group structure, detect structural breaks, and estimate the regression parameters. Monte Carlo results demonstrate the good performance of the proposed method in finite samples. An empirical application to the relationship between income and democracy illustrates the importance of considering heterogeneous structural breaks.

Keywords: Panel data; Grouped patterns; Structural breaks; Grouped fixed effects; Fused Lasso (search for similar items in EconPapers)
JEL-codes: C23 C38 C51 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (24)

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Working Paper: Heterogeneous structural breaks in panel data models (2018)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:220:y:2021:i:2:p:447-473

DOI: 10.1016/j.jeconom.2020.04.009

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