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

Author

Listed:
  • Chirok Han

    () (Department of Economics, Korea University, Seoul, Republic of Korea)

  • Hyoungjong Kim

    (Department of Economics, Korea University, Seoul, Republic of Korea)

Abstract

For linear dynamic panel data models with fixed effects, practitioners often use clustered covariance estimators for inference in the presence of cross-sectional or temporal heteroskedasticity in idiosyncratic errors. The performance of a clustered estimator heavily depends on the magnitude of the cross-sectional dimension(n). When n is small, inferences using clustered estimators are compromised. A paper by Stock and Watson (2008) provides a solution under strict exogeneity if the idiosyncratic errors are possibly heteroskedastic but serially uncorrelated. Their method, however, is not generalizable to dynamic panel data models, although heteroskedasticity-robust inferences have natural relevance to dynamic models due to the requirement of serial uncorrelatedness for model identification. In the present paper, we provide a solution for instrumental variables and generalized method of moments estimators using predetermined instruments, including popular estimators for dynamic panel models. Asymptotics are established, and the findings are verified by simulations.

Suggested Citation

  • Chirok Han & Hyoungjong Kim, 2017. "Heteroskedasticity-Robust Standard Errors for Dynamic Panel Data Models with Fixed Effects," Discussion Paper Series 1703, Institute of Economic Research, Korea University.
    • Handle: RePEc:iek:wpaper:1703
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    File URL: http://econ.korea.ac.kr/~ri/WorkingPapers/w1703.pdf
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    References listed on IDEAS

    as
    1. Stock, James H. & Watson, Mark, 2008. "Heteroskedasticity-Robust Standard Errors for Fixed Effects Panel Data Regression," Scholarly Articles 28461843, Harvard University Department of Economics.
    2. Love, Inessa & Zicchino, Lea, 2006. "Financial development and dynamic investment behavior: Evidence from panel VAR," The Quarterly Review of Economics and Finance, Elsevier, vol. 46(2), pages 190-210, May.
    3. Han, Chirok & Kim, Hyoungjong, 2014. "The role of constant instruments in dynamic panel estimation," Economics Letters, Elsevier, vol. 124(3), pages 500-503.
    4. 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.
    5. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
    6. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Oxford University Press, vol. 58(2), pages 277-297.
    7. James H. Stock & Mark W. Watson, 2008. "Heteroskedasticity-Robust Standard Errors for Fixed Effects Panel Data Regression," Econometrica, Econometric Society, vol. 76(1), pages 155-174, January.
    8. Windmeijer, Frank, 2005. "A finite sample correction for the variance of linear efficient two-step GMM estimators," Journal of Econometrics, Elsevier, vol. 126(1), pages 25-51, May.
    9. Ahn, Seung C. & Schmidt, Peter, 1995. "Efficient estimation of models for dynamic panel data," Journal of Econometrics, Elsevier, vol. 68(1), pages 5-27, July.
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    More about this item

    Keywords

    Heteroskedasticity-robust covariance estimation; Dynamic panel data; Cluster co- variance estimator; Instrumental variable estimation;

    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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