數量經濟學研討會      
      報告題目：Heterogenous structural breaks in panel data models          報告人：Ryo Okui          報告時間：2017年4月20日12:00-13:30          報告地點：明德主樓729          
         內容簡介：In many applications, there is a good reason to suspect that structural breaks occur at different time points across individual units and the sizes of the breaks dif- fer too. This paper provides a new model and a new estimation procedure for panel data that allow us to discern heterogenous structure breaks. We model individual heterogeneity to have a grouped pattern such that individuals within the group share the same regression coefficients. For each group, we allow common structure breaks in the coefficients, while the number of breaks and the break points can differ across groups. We develop a hybrid procedure of the grouped fixed effects and adaptive group fused Lasso (least absolute shrinkage and selection operator) to estimate the model. The grouped fixed effects approach is used to estimate the group structure and the adaptive group fused Lasso is used to detect the structural breaks and obtain coefficient estimates. We show that our method can consistently identify the latent group structure, detect structural breaks, and estimate the regression parameters. Monte Carlo results demonstrate good performance of the method in finite sample. We apply our method to two cross-country empirical studies and illustrate the im- portance of taking heterogenous structural breaks into account.          
         
         報告人簡介：Ryo Okui，上海紐約大學副教授，研究領域為微觀計量經濟學，研究論文曾發表于Econometrica, Review of Economic Studies以及其他頂級計量經濟學期刊。      
 
      數量經濟教研室          運籌學與數量經濟研究所          中國人民大學經濟學院          2017年04月          
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