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Trimmed Mean Group Estimation of Average Effects in Ultra Short T Panels under Correlated Heterogeneity

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  • M. Hashem Pesaran
  • Liying Yang

Abstract

The commonly used two-way fixed effects estimator is biased under correlated heterogeneity and can lead to misleading inference. This paper proposes a new trimmed mean group (TMG) estimator which is consistent at the irregular rate of n^{1/3} even if the time dimension of the panel is as small as the number of its regressors. Extensions to panels with time effects are provided, and a Hausman test of correlated heterogeneity is proposed. Small sample properties of the TMG estimator (with and without time effects) are investigated by Monte Carlo experiments and shown to be satisfactory and perform better than other trimmed estimators proposed in the literature. The proposed test of correlated heterogeneity is also shown to have the correct size and satisfactory power. The utility of the TMG approach is illustrated with an empirical application.

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  • M. Hashem Pesaran & Liying Yang, 2023. "Trimmed Mean Group Estimation of Average Effects in Ultra Short T Panels under Correlated Heterogeneity," Papers 2310.11680, arXiv.org, revised Jul 2024.
    • Handle: RePEc:arx:papers:2310.11680
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    1. Bryan S. Graham & James L. Powell, 2012. "Identification and Estimation of Average Partial Effects in “Irregular” Correlated Random Coefficient Panel Data Models," Econometrica, Econometric Society, vol. 80(5), pages 2105-2152, September.
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    Cited by:

    1. Liying Yang & Yi Qian & Hui Xie, 2024. "Handling Endogenous Marketing Mix Regressors in Correlated Heterogeneous Panels with Copula Augmented Mean Group Estimation," NBER Working Papers 33265, National Bureau of Economic Research, Inc.

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