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

Listed author(s):
  • Chirok Han


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

  • Hyoungjong Kim

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

Registered author(s):

    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.

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    Paper provided by Institute of Economic Research, Korea University in its series Discussion Paper Series with number 1703.

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    Date of creation: 2017
    Handle: RePEc:iek:wpaper:1703
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