Estimation of panel group structure models with structural breaks in group memberships and coefficients
研究了面板数据中潜在分组结构和系数在断点处同时发生变化的模型，提出最小二乘法联合估计断点、分组和系数，并证明估计量的一致性。
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.