eprintid: 49703 rev_number: 6 eprint_status: archive userid: 1482 importid: 105 dir: disk0/00/04/97/03 datestamp: 2024-09-20 09:15:40 lastmod: 2024-09-20 09:15:40 status_changed: 2024-09-20 09:15:40 type: monograph metadata_visibility: show creators_name: Diegert, Paul creators_name: Jochmans, Koen creators_idrefppn: 280416512 creators_idrefppn: 175871108 creators_affiliation: Toulouse School of Economics creators_affiliation: Toulouse School of Economics creators_halaffid: 1002422 creators_halaffid: 1002422 title: Nonparametric Identification of Models for Dyadic Data ispublished: pub subjects: subjects_ECO abstract: Consider dyadic random variables on units from a given population. It is common to assume that these variables are jointly exchangeable and dissociated. In this case they admit a non-separable specification with two-way unobserved heterogeneity. The analysis of this type of structure is of considerable interest but little is known about their nonparametric identifiability, especially when the unobserved heterogeneity is continuous. We provide conditions under which both the distribution of the observed random variables conditional on the unit-specific heterogeneity and the distribution of the unit-specific heterogeneity itself are uniquely recoverable from knowledge of the joint marginal distribution of the observable random variables alone without imposing parametric restrictions. date: 2024-07 date_type: published publisher: TSE Working Paper official_url: http://tse-fr.eu/pub/129722 faculty: tse divisions: tse keywords: Exchangeability keywords: conditional independence keywords: dyadic data keywords: network keywords: two-way keywords: heterogeneity language: en has_fulltext: TRUE view_date_year: 2024 full_text_status: public monograph_type: working_paper series: TSE Working Paper volume: 24-1574 place_of_pub: Toulouse pages: 13 institution: Université Toulouse Capitole department: Toulouse School of Economics book_title: TSE Working Paper oai_identifier: oai:tse-fr.eu:129722 harvester_local_overwrite: department harvester_local_overwrite: pending harvester_local_overwrite: creators_idrefppn harvester_local_overwrite: creators_halaffid harvester_local_overwrite: institution harvester_local_overwrite: place_of_pub harvester_local_overwrite: title harvester_local_overwrite: pages oai_lastmod: 2024-09-17T08:26:01Z oai_set: tse site: ut1 citation: Diegert, Paul and Jochmans, Koen (2024) Nonparametric Identification of Models for Dyadic Data. TSE Working Paper, n. 24-1574, Toulouse document_url: https://publications.ut-capitole.fr/id/eprint/49703/1/wp_tse_1574.pdf