eprintid: 49492
rev_number: 8
eprint_status: archive
userid: 1482
importid: 105
dir: disk0/00/04/94/92
datestamp: 2024-08-19 07:18:17
lastmod: 2024-08-19 09:00:39
status_changed: 2024-08-19 07:18:17
type: article
metadata_visibility: show
creators_name: Jochmans, Koen
creators_idrefppn: 175871108
creators_affiliation: Toulouse School of Economics
creators_halaffid: 1002422
title: Nonparametric identification and estimation of stochastic block models from many small networks
ispublished: pub
subjects: subjects_ECO
abstract: This paper concerns the analysis of network data when unobserved node-specific heterogeneity is present. We postulate a weighted version of the classic stochastic block model, where nodes belong to one of a finite number of latent communities and the placement of edges between them and any weight assigned to these depend on the communities to which the nodes belong. A simple rank condition is presented under which we establish that the number of latent communities, their distribution, and the conditional distribution of edges and weights given community membership are all nonparametrically identified from knowledge of the joint (marginal) distribution of edges and weights in graphs of a fixed size. The identification argument is constructive and we present a computationally-attractive nonparametric estimator based on it. Limit theory is derived under asymptotics where we observe a growing number of independent networks of a fixed size. The results of a series of numerical experiments are reported on.
date: 2024-06
date_type: published
publisher: Elsevier
id_number: 10.1016/j.jeconom.2024.105805
official_url: http://tse-fr.eu/pub/129432
faculty: tse
divisions: tse
keywords: Heterogeneity
keywords: Network
keywords: Random graph
keywords: Sorting
keywords: Stochastic block model
language: en
has_fulltext: TRUE
doi: 10.1016/j.jeconom.2024.105805
view_date_year: 2024
full_text_status: public
publication: Journal of Econometrics
volume: vol.242
number: n°2
place_of_pub: Amsterdam
refereed: TRUE
issn: 0304-4076
oai_identifier: oai:tse-fr.eu:129432
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oai_lastmod: 2024-07-26T09:23:15Z
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site: ut1
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hal_id: hal-04672521
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hal_version: 1
hal_url: https://hal.science/hal-04672521
citation:   Jochmans, Koen <https://www.idref.fr/175871108>  (2024) Nonparametric identification and estimation of stochastic block models from many small networks.    Journal of Econometrics, vol.242 (n°2).        
document_url: https://publications.ut-capitole.fr/id/eprint/49492/1/wp_tse_1514.pdf