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Robust inference with clustered data

  • Colin Cameron

    (University of California-Davis)

This talk considers robust inference for regression models where data are clustered, with correlation of observations in the same cluster (such as state) and independence across clusters. The talk will range from the simplest case of heteroskedastic-ro bust (one individual per cluster) through to complications such as a small number of clusters and two- clustering. The relevant Stata commands and Stata add-ons, where available, will be discussed.

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Paper provided by Stata Users Group in its series Mexican Stata Users' Group Meetings 2011 with number 07.

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Date of creation: 23 Jul 2011
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Handle: RePEc:boc:msug11:07
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  1. Greenwald, Bruce C., 1983. "A general analysis of bias in the estimated standard errors of least squares coefficients," Journal of Econometrics, Elsevier, vol. 22(3), pages 323-338, August.
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  9. Pepper, John V., 2002. "Robust inferences from random clustered samples: an application using data from the panel study of income dynamics," Economics Letters, Elsevier, vol. 75(3), pages 341-345, May.
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  13. Cameron,A. Colin & Trivedi,Pravin K., 2005. "Microeconometrics," Cambridge Books, Cambridge University Press, number 9780521848053, November.
  14. A. Colin Cameron & Jonah B. Gelbach & Douglas L. Miller & Doug Miller, 2009. "Robust Inference with Multi-way Clustering," Working Papers 98, University of California, Davis, Department of Economics.
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  24. Doug Miller & A. Colin Cameron & Jonah B. Gelbach, 2006. "Bootstrap-Based Improvements for Inference with Clustered Errors," Working Papers 621, University of California, Davis, Department of Economics.
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  29. Austin Nichols & Mark E Schaffer, 2007. "Clustered standard errors in Stata," United Kingdom Stata Users' Group Meetings 2007 07, Stata Users Group.
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