This paper develops a new model and a new estimation procedure for panel data that allow us to identify heterogeneous structural breaks. In many applications, there are good reasons to suspect that structural breaks occur at different time points across individual units and the sizes of the breaks differ too. We model individual heterogeneity using a grouped pattern such that individuals within a given group share the same regression coefficients . For each group, we allow common structural breaks in the coefficients  , while the numberof breaks, the break points, and the size of breaks can differ across groups. To estimate the model, we develop a hybrid  procedure of the grouped fixed effects approach and adaptive group fused Lasso (least absolute shrinkage and selection operator) . We show that our method can consistently identify the latent group structure, detect structural breaks, and estimate the regression parameters. Monte Carlo results demonstrate a good performance of the proposed method in finite samples. We apply our method to two cross-country empirical studies and illustrate the importance of taking heterogeneous structural breaks into account .
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 .
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a new
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In many applications, there are good reasons to suspect that structural breaks occur at different time points across individual units and the sizes of the breaks differ too.
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such that individuals within a given group share the same regression coefficients
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. However, the number
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while the numberof breaks, the break points, and the size of
timing, and size of these
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To estimate the model, we
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estimation
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(least absolute shrinkage and selection operator)
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We apply our method to two cross-country empirical studies and illustrate
An empirical application to the relationship between income and democracy illustrates
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into account