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Evaluating one-way and two-way cluster–robust covariance matrix estimates

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Listed:
  • Christopher F Baum

    () (Boston College
    DIW Berlin)

  • Austin Nichols

    (Urban Institute)

  • Mark E Schaffer

    (IZA
    Heriot-Watt University
    CEPR)

Abstract

Although 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.

Suggested Citation

  • Christopher F Baum & Austin Nichols & Mark E Schaffer, 2011. "Evaluating one-way and two-way cluster–robust covariance matrix estimates," German Stata Users' Group Meetings 2011 02, Stata Users Group.
  • Handle: RePEc:boc:dsug11:02
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    File URL: http://fmwww.bc.edu/repec/dsug2011/desug11_schaffer.pdf
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    5. Cuffe, Harold E. & Waddell, Glen R. & Bignell, Wesley, 2014. "Too Busy for School? The Effect of Athletic Participation on Absenteeism," IZA Discussion Papers 8426, Institute for the Study of Labor (IZA).
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    7. Silvia Sacchetti & Ermanno C. Tortia, 2012. "A �Human Growth� Perspective on Organizational Resources and Firm Performance," Department of Economics Working Papers 1209, Department of Economics, University of Trento, Italia.

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