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Trimmed Mean Group Estimation

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Abstract

This paper develops robust panel estimation in the form of trimmed mean group estimation for potentially heterogenous panel regression models. It trims outlying individuals of which the sample variances of regressors are either extremely small or large. The limiting distribution of the trimmed estimator can be obtained in a similar way to the standard mean group estimator, provided the random coefficients are conditionally homoskedastic. We consider two trimming methods. The first one is based on the order statistic of the sample variance of each regressor. The second one is based on the Mahalanobis depth of the sample variances of regressors. We apply them to the mean group estimation of the two-way fixed effects model with potentially heterogeneous slope parameters and to the common correlated effects regression, and we derive limiting distribution of each estimator. As an empirical illustration, we consider the effect of police on property crime rates using the U.S. state-level panel data.

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  • Yoonseok Lee & Donggyu Sul, 2021. "Trimmed Mean Group Estimation," Center for Policy Research Working Papers 237, Center for Policy Research, Maxwell School, Syracuse University.
    • Handle: RePEc:max:cprwps:237
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    File URL: https://surface.syr.edu/cpr/269/
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    1. Stéphane Bonhomme & Elena Manresa, 2015. "Grouped Patterns of Heterogeneity in Panel Data," Econometrica, Econometric Society, vol. 83(3), pages 1147-1184, May.
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    9. Maddala, G S, et al, 1997. "Estimation of Short-Run and Long-Run Elasticities of Energy Demand from Panel Data Using Shrinkage Estimators," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(1), pages 90-100, January.
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    11. Chudik, Alexander & Pesaran, M. Hashem, 2015. "Common correlated effects estimation of heterogeneous dynamic panel data models with weakly exogenous regressors," Journal of Econometrics, Elsevier, vol. 188(2), pages 393-420.
    12. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, July.
    13. Levitt, Steven D, 1997. "Using Electoral Cycles in Police Hiring to Estimate the Effect of Police on Crime," American Economic Review, American Economic Association, vol. 87(3), pages 270-290, June.
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    15. Ryan Greenaway‐McGrevy & Nelson C. Mark & Donggyu Sul & Jyh‐Lin Wu, 2018. "Identifying Exchange Rate Common Factors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 59(4), pages 2193-2218, November.
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    Cited by:

    1. Lee, Yoonseok & Sul, Donggyu, 2023. "Depth-weighted means of noisy data: An application to estimating the average effect in heterogeneous panels," Journal of Multivariate Analysis, Elsevier, vol. 196(C).

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    More about this item

    Keywords

    Trimmed Mean Group Estimator; Robust Estimator; Heterogeneous Panel; Random Coefficient; Two-Way Fixed Effects; Common Correlated Effects;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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