Inference with dependent data using cluster covariance estimators

Alan Bester (), Timothy Conley and Christian Hansen

Journal of Econometrics, 2011, vol. 165, issue 2, 137-151

Abstract: This paper presents an inference approach for dependent data in time series, spatial, and panel data applications. The method involves constructing t and Wald statistics using a cluster covariance matrix estimator (CCE). We use an approximation that takes the number of clusters/groups as fixed and the number of observations per group to be large. The resulting limiting distributions of the t and Wald statistics are standard t and F distributions where the number of groups plays the role of sample size. Using a small number of groups is analogous to ‘fixed-b’ asymptotics of Kiefer and Vogelsang (2002, 2005) (KV) for heteroskedasticity and autocorrelation consistent inference. We provide simulation evidence that demonstrates that the procedure substantially outperforms conventional inference procedures.

Keywords: HAC; Panel; Robust; Spatial (search for similar items in EconPapers)
JEL-codes: C12 C21 C22 C23 (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (197)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:165:y:2011:i:2:p:137-151

DOI: 10.1016/j.jeconom.2011.01.007

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