Homogeneity pursuit in panel data models: Theory and application

This paper studies the estimation of a panel data model with latent structures where individuals can be classified into different groups with the slope parameters being homogeneous within the same group but heterogeneous across groups. To identify the unknown group structure of vector parameters, we...

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Main Authors: WANG, Wuyi, PHILLIPS, Peter C. B., SU, Liangjun
格式: text
語言:English
出版: Institutional Knowledge at Singapore Management University 2018
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在線閱讀:https://ink.library.smu.edu.sg/soe_research/2189
https://ink.library.smu.edu.sg/context/soe_research/article/3188/viewcontent/Homogeneity_pursuit_in_panel_data_models_2016_pp.pdf
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機構: Singapore Management University
語言: English
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總結:This paper studies the estimation of a panel data model with latent structures where individuals can be classified into different groups with the slope parameters being homogeneous within the same group but heterogeneous across groups. To identify the unknown group structure of vector parameters, we design an algorithm called Panel-CARDS. We show that it can identify the true group structure asymptotically and estimate the model parameters consistently at the same time. Simulations evaluate the performance and corroborate the asymptotic theory in several practical design settings. The empirical application reveals the heterogeneous grouping effect of income on democracy.