Inference With Dyadic Data: Asymptotic Behavior of the Dyadic-Robust t-Statistic |
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Authors: | Max Tabord-Meehan |
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Affiliation: | Department of Economics, Northwestern University, Evanston, IL 60208 (mtabordmeehan@u.northwestern.edu) |
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Abstract: | ABSTRACTThis article is concerned with inference in the linear model with dyadic data. Dyadic data are indexed by pairs of “units;” for example, trade data between pairs of countries. Because of the potential for observations with a unit in common to be correlated, standard inference procedures may not perform as expected. We establish a range of conditions under which a t-statistic with the dyadic-robust variance estimator of Fafchamps and Gubert is asymptotically normal. Using our theoretical results as a guide, we perform a simulation exercise to study the validity of the normal approximation, as well as the performance of a novel finite-sample correction. We conclude with guidelines for applied researchers wishing to use the dyadic-robust estimator for inference. |
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Keywords: | Degrees of freedom correction Dependence Dyadic data Regression Robust variance estimators t-test. |
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