Cluster-robust inference: A guide to empirical practice - James G. MacKinnon; Morten Ørregaard Nielsen; Matthew Webb (Queen's University, Department of Economics, 2021)
Methods for cluster-robust inference are routinely used in economics and many other disciplines. However, it is only recently that theoretical foundations for the use of these methods in many empirically relevant situations have been developed. In this paper, we use these theoretical results to provide a guide to empirical practice. We do not attempt to present a comprehensive survey of the (very large) literature. Instead, we bridge theory and practice by providing a thorough guide on what to do and why, based on recently available econometric theory and simulation evidence. The paper includes an empirical analysis of the effects of the minimum wage on teenagers using individual data, in which we practice what we preach.
Keywords: C12; C15; C21; C23; 330; clustered data; grouped data; cluster-robust variance estimator; CRVE; robust inference; wild cluster bootstrap