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Heteroskedasticity‐Robust Standard Errors for Dynamic Panel Data Models with Fixed Effects

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  • Chirok Han
  • Hyoungjong Kim

Abstract

For linear panel data models with fixed effects, cluster‐robust covariance estimation does not use variability over time. The extant heteroskedasticity‐robust methods available under strict exogeneity do not generalize to dynamic models. We propose novel robust covariance estimators under a strong version of serial uncorrelatedness, where serial uncorrelatedness is required to identify dynamic panel models. Asymptotics are established, and simulations verify theoretical findings. The estimator can apply to the popular dynamic IV‐GMM estimators and be a sharper alternative for cluster‐robust covariance estimators in panel data models with limited cross‐sectional information.

Suggested Citation

  • Chirok Han & Hyoungjong Kim, 2023. "Heteroskedasticity‐Robust Standard Errors for Dynamic Panel Data Models with Fixed Effects," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(5), pages 1135-1155, October.
    • Handle: RePEc:bla:obuest:v:85:y:2023:i:5:p:1135-1155
    DOI: 10.1111/obes.12554
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    References listed on IDEAS

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    7. Hansen, Christian B., 2007. "Asymptotic properties of a robust variance matrix estimator for panel data when T is large," Journal of Econometrics, Elsevier, vol. 141(2), pages 597-620, December.
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    More about this item

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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