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Robust standard errors for panel regressions with cross-sectional dependence

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  • Daniel Hoechle

    () (Department of Finance, University of Basel)

Abstract

I present a new Stata program, xtscc, that estimates pooled ordinary least-squares/weighted least-squares regression and fixed-effects (within) regression models with Driscoll and Kraay (Review of Economics and Statistics 80: 549–560) standard errors. By running Monte Carlo simulations, I compare the finite-sample properties of the cross-sectional dependence-consistent Driscoll-Kraay estimator with the properties of other, more commonly used covariance matrix estimators that do not account for cross-sectional dependence. The results indicate that Driscol-Kraay standard errors are well calibrated when cross-sectional dependence is present. However, erroneously ignoring cross-sectional correlation in the estimation of panel models can lead to severely biased statistical results. I illustrate the xtscc program by considering an application from empirical finance. Thereby, I also propose a Hausman-type test for fixed effects that is robust to general forms of cross-sectional and temporal dependence. Copyright 2007 by StataCorp LP.

Suggested Citation

  • Daniel Hoechle, 2007. "Robust standard errors for panel regressions with cross-sectional dependence," Stata Journal, StataCorp LP, vol. 7(3), pages 281-312, September.
  • Handle: RePEc:tsj:stataj:v:7:y:2007:i:3:p:281-312
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    References listed on IDEAS

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