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

Max Tabord-Meehan

Journal of Business & Economic Statistics, 2019, vol. 37, issue 4, 671-680

Abstract: This 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.

Date: 2019
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Citations: View citations in EconPapers (18)

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Persistent link: https://EconPapers.repec.org/RePEc:taf:jnlbes:v:37:y:2019:i:4:p:671-680

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DOI: 10.1080/07350015.2017.1409630

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