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

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Author Info

  • Christopher F Baum

    ()
    (Boston College
    DIW Berlin)

  • Austin Nichols

    (Urban Institute)

  • Mark E Schaffer

    (Heriot-Watt University
    CEPR)

Abstract

In this presentation, I update Nichols and Schaffer's 2007 UK Stata Users Group talk on clustered standard errors. 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 requirement rules out the possibility of defining clusters in the time dimension and modeling contemporaneous dependence of panel units' error processes. I build upon recent analytical developments that define two-way (and conceptually, n-way) clustering and upon the 2010 implementation of two-way clustering in the widely used ivreg2 and xtivreg2 packages. I present examples of the utility of one-way and two-way clustering using Monte Carlo techniques, I present a comparison with alternative approaches to modeling error dependence, and I consider tests for clustering of errors.

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Bibliographic Info

Paper provided by Stata Users Group in its series United Kingdom Stata Users' Group Meetings 2010 with number 12.

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Date of creation: 17 Sep 2010
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Handle: RePEc:boc:usug10:12

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Web page: http://www.stata.com/meeting/uk10
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Cited by:
  1. 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.
  2. Abebe, Gumataw K. & Bijman, Jos & Kemp, Ron & Omta, Onno & Tsegaye, Admasu, 2013. "Contract farming configuration: Smallholders’ preferences for contract design attributes," Food Policy, Elsevier, vol. 40(C), pages 14-24.
  3. Guillermo Baquero & Malika Hamadi & Andréas Heinen, 2012. "Competition, loan rates and information dispersion in microcredit markets," ESMT Research Working Papers ESMT-12-02, ESMT European School of Management and Technology.

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