Bagging the Network
Ming Li,
Zhentao Shi and
Yapeng Zheng
Papers from arXiv.org
Abstract:
This paper studies parametric estimation and inference in a dyadic network formation model with nontransferable utilities, incorporating observed covariates and unobservable individual fixed effects. We address both theoretical and computational challenges of maximum likelihood estimation in this complex network model by proposing a new bootstrap aggregating (bagging) estimator, which is asymptotically normal, unbiased, and efficient. We extend the approach to estimating average partial effects and analyzing link function misspecification. Simulations demonstrate strong finite-sample performance. Two empirical applications to Nyakatoke risk-sharing networks and Indian microfinance data find insignificant roles of wealth differences in link formation and the strong influence of caste in Indian villages, respectively.
Date: 2024-10, Revised 2025-09
New Economics Papers: this item is included in nep-dcm, nep-ecm, nep-inv and nep-net
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://arxiv.org/pdf/2410.23852 Latest version (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2410.23852
Access Statistics for this paper
More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().