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Multiple Treatment Effects in Panel-Heterogeneity and Aggregation

Essays in Honor of M. Hashem Pesaran: Panel Modeling, Micro Applications, and Econometric Methodology

ISBN: 978-1-80262-066-5, eISBN: 978-1-80262-065-8

Publication date: 18 January 2022

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.

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Acknowledgements

Acknowledgment

We wish to thank Allan Timmermann and a referee for helpful comments. Partial research support by China NSF #71631004 and #72033008 to Cheng Hsiao is gratefully acknowledged.

Citation

Hsiao, C., Shen, Y. and Zhou, Q. (2022), "Multiple Treatment Effects in Panel-Heterogeneity and Aggregation", Chudik, A., Hsiao, C. and Timmermann, A. (Ed.) Essays in Honor of M. Hashem Pesaran: Panel Modeling, Micro Applications, and Econometric Methodology (Advances in Econometrics, Vol. 43B), Emerald Publishing Limited, Leeds, pp. 81-101. https://doi.org/10.1108/S0731-90532021000043B005

Publisher

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Emerald Publishing Limited