Heterogeneous Structural Breaks in Panel Data Models

53 Pages Posted: 8 Sep 2017 Last revised: 11 Oct 2019

See all articles by Ryo Okui

Ryo Okui

Seoul National University

Wendun Wang

Erasmus University Rotterdam (EUR) - Department of Econometrics

Date Written: April 1, 2019

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 pattern, structural break, grouped fixed effects, fused Lasso

JEL Classification: C23, C38, C51

Suggested Citation

Okui, Ryo and Wang, Wendun, Heterogeneous Structural Breaks in Panel Data Models (April 1, 2019). Available at SSRN: https://ssrn.com/abstract=3031689 or http://dx.doi.org/10.2139/ssrn.3031689

Ryo Okui (Contact Author)

Seoul National University ( email )

Seoul
Korea, Republic of (South Korea)

Wendun Wang

Erasmus University Rotterdam (EUR) - Department of Econometrics ( email )

P.O. Box 1738
3000 DR Rotterdam
Netherlands

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