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This paper is concerned with inference in the linear model with dyadic data.Dyadic data is data that is indexed by pairs of "units", for example trade databetween pairs of countries. Because of the potential for observations with aunit in common to be correlated, standard inference procedures may not performas expected. We establish a range of conditions under which a t-statistic withthe dyadic-robust variance estimator of Fafchamps and Gubert (2007) isasymptotically normal. Using our theoretical results as a guide, we perform asimulation exercise to study the validity of the normal approximation, as wellas the performance of a novel finite-sample correction. We conclude withguidelines for applied researchers wishing to use the dyadic-robust estimatorfor inference.

Inference with Dyadic Data: Asymptotic Behavior of the Dyadic-Robust t-Statistic