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
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oai_lastmod: 2024-09-17T08:26:01Z
oai_set: tse
site: ut1
citation:   Diegert, Paul <https://www.idref.fr/280416512> and Jochmans, Koen <https://www.idref.fr/175871108>  (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