Multiple Treatment Effects in Panel-Heterogeneity and Aggregation

Cheng Hsiao, Yan Shen and Qiankun Zhou

A chapter in Essays in Honor of M. Hashem Pesaran: Panel Modeling, Micro Applications, and Econometric Methodology, 2022, vol. 43B, pp 81-101 from Emerald Group Publishing Limited

Abstract: Panel data provide the possibilities of estimating individual treatment effects for multiple individuals. Two issues are considered: (1) differences in the estimated individual treatment effects are due to heterogeneity or a chance mechanism? (2) what is the best way to estimate the average treatment effects? Testing and aggregation methods are suggested. Monte Carlo simulations are also conducted to shed light on these two issues. An empirical analysis on the involvement of underground organization in China’s Peer-to-Peer (P2P) activities through the “anti-gang” campaign is also provided.

Keywords: Treatment effects; panel data analysis; interactive effects; aggregation; eigenvalue; eigenvector; C01; C21; C31; I18 (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:eme:aecozz:s0731-90532021000043b005

DOI: 10.1108/S0731-90532021000043B005

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