Robust Inference with Clustered Data
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.Download Info
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Paper provided by University of California, Davis, Department of Economics in its series Working Papers with number 106.Length: 28
Date of creation: 25 Mar 2010
Date of revision:
Handle: RePEc:cda:wpaper:10-6
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Related research
Keywords: Cluster robust; random eects; xed eects; dierences in dierences; cluster bootstrap; few clusters; multi-way clusters.;Other versions of this item:
- Colin Cameron, 2011. "Robust inference with clustered data," Mexican Stata Users' Group Meetings 2011 07, Stata Users Group.
- A. Colin Cameron & Douglas L. Miller, 2010. "Robust Inference with Clustered Data," Working Papers 107, University of California, Davis, Department of Economics.
- Cameron, A. Colin & Miller, Douglas L., 2010. "Robust Inference with Clustered Data," Working Papers 10-7, University of California at Davis, Department of Economics.
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
- C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Longitudinal Data; Spatial Time Series
References
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Citations
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