Evaluating one-way and two-way cluster–robust covariance matrix estimates
AbstractAlthough cluster–robust standard errors are now recognized as essential in a panel-data context, official Stata only supports clusters that are nested within panels. This rules out the possibility of defining clusters in the time dimension, and modeling contemporaneous dependence of panel units’ error processes. We build upon recent analytical developments that define two-way (and conceptually, n-way) clustering, and the 2010 implementation of two-way clustering in the widely used ivreg2 and xtivreg2 packages. We present examples of the utility of one-way and two-way clustering using Monte Carlo techniques, a comparison with alternative approaches to modeling error dependence, and consider tests for clustering of errors.
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Bibliographic InfoPaper provided by Stata Users Group in its series German Stata Users' Group Meetings 2011 with number 02.
Date of creation: 23 Jul 2011
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- Christopher F Baum & Austin Nichols & Mark E Schaffer, 2010. "Evaluating one-way and two-way cluster-robust covariance matrix estimates," United Kingdom Stata Users' Group Meetings 2010 12, Stata Users Group.
- Christopher F Baum & Austin Nichols & Mark E Schaffer, 2010. "Evaluating one-way and two-way cluster-robust covariance matrix estimates," BOS10 Stata Conference 11, Stata Users Group.
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