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Title:Robust inference with clustered data PDF Logo
Authors:Cameron, A. Colin
Miller, Douglas L.
Issue Date:2010
Series/Report no.:Working Papers, University of California, Department of Economics 10,6
Abstract:In this paper we survey methods to control for regression model error that is correlated within groups or clusters, but is uncorrelated across groups or clusters. Then failure to control for the clustering can lead to understatement of standard errors and overstatement of statistical significance, as emphasized most notably in empirical studies by Moulton (1990) and Bertrand, Duflo and Mullainathan (2004). We emphasize OLS estimation with statistical inference based on minimal assumptions regarding the error correlation process. Complications we consider include cluster-specific fixed effects, few clusters, multi-way clustering, more efficient feasible GLS estimation, and adaptation to nonlinear and instrumental variables estimators.
Subjects:cluster robust
random effects
fixed effects
differences in differences
cluster bootstrap
few clusters
multi-way clusters
JEL:C12
C21
C23
Document Type:Working Paper
Appears in Collections:Working Papers, Department of Economics, UC Davis

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