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Robust Standard Errors for Panel Regressions with Cross-Sectional Dependence

  • Hoechle, Daniel Department of Finance University of Basel Basel, Switzerland
  • 2007-9-1
Published in:
  • The Stata Journal: Promoting communications on statistics and Stata. - SAGE Publications. - 2007, vol. 7, no. 3, p. 281-312
Mathematics (miscellaneous)
English 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 Driscoll–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.
Language
  • English
Open access status
bronze
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Persistent URL
https://folia.unifr.ch/global/documents/194673
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