Two-Way Clustering with Non-Exchangeable Data

Koen Jochmans
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Koen Jochmans: TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement

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Abstract: Inference procedures for dyadic data based on two-way clustering rely on the data being exchangeable and dissociated. In particular, observations must be independent if they have no index in common. In an effort to relax this we consider, instead, data where Yij and Ypq can be dependent for all index pairs, with the dependence vanishing as the distance between the indices grows large. We establish limit theory for the sample mean and propose analytical and bootstrap procedures to perform inference.

Keywords: bootstrap; clustering; dependence; dyadic data; inference; serial correlation (search for similar items in EconPapers)
Date: 2026-01-22
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