Event Date
Speaker: Bulat Gafarov, Associate Professor, Agricultural and Resource Economics, UC Davis
Title: "Refined Cluster Robust Inference"
Abstract: It has become standard for empirical studies to conduct inference robust to cluster dependence and heterogeneity. With a small number of clusters, the normal approximation for the t-statistics of regression coefficients may be poor. This paper tackles this problem using a critical value based on the conditional Cramér-Edgeworth expansion for the t-statistics. The proposed critical value guarantees third-order refinement, and it does not require resampling because it is a closed-form function of the estimated score skewness and kurtosis. Simulations show that our proposal can make a difference in size control with as few as 10 clusters. Joint work with Takuya Ura.
Website (UCD)