Robust standard errors for panel regressions with cross-sectional dependence

Daniel Hoechle ()
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Daniel Hoechle: Department of Finance, University of Basel

Stata Journal, 2007, vol. 7, issue 3, 281-312

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.

Keywords: xtscc; robust standard errors; nonparametric covariance estimation (search for similar items in EconPapers)
Date: 2007
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Citations: View citations in EconPapers (969)

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