Jochmans, KoenIdRefORCIDORCID: https://orcid.org/0000-0002-3090-3003 (2026) Two-Way Clustering with Non-Exchangeable Data. TSE Working Paper, n. 26-1701, Toulouse

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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.

Item Type: Monograph (Working Paper)
Language: English
Date: January 2026
Place of Publication: Toulouse
Uncontrolled Keywords: bootstrap, clustering, dependence, dyadic data, inference, serial correlation
Subjects: B- ECONOMIE ET FINANCE
Divisions: TSE-R (Toulouse)
Institution: Université Toulouse Capitole
Site: UT1
Date Deposited: 22 Jan 2026 08:57
Last Modified: 22 Jan 2026 08:58
OAI Identifier: oai:tse-fr.eu:131300
URI: https://publications.ut-capitole.fr/id/eprint/51819
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