A Practitioner's Guide to Cluster-Robust Inference
نویسندگان
چکیده
We consider statistical inference for regression when data are grouped into clusters, with regression model errors independent across clusters but correlated within clusters. Examples include data on individuals with clustering on village or region or other category such as industry, and state-year di erences-in-di erences studies with clustering on state. In such settings default standard errors can greatly overstate estimator precision. Instead, if the number of clusters is large, statistical inference after OLS should be based on cluster-robust standard errors. We outline the basic method as well as many complications that can arise in practice. These include cluster-speci c xed e ects, few clusters, multi-way clustering, and estimators other than OLS. JEL Classi cation: C12, C21, C23, C81.
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