GMM and M Estimation under Network Dependence
Econometrics
2026-03-10 v3 Statistics Theory
Statistics Theory
Abstract
This paper presents GMM and M estimators and their asymptotic properties for network-dependent data. To this end, I build on Kojevnikov, Marmer, and Song (KMS, 2021) and develop a novel uniform law of large numbers (ULLN), which is essential to ensure desired asymptotic behaviors of nonlinear estimators (e.g., Newey and McFadden, 1994, Section 2). Using this ULLN, I establish the consistency and asymptotic normality of both GMM and M estimators. For practical convenience, complete estimation and inference procedures are also provided.
Keywords
Cite
@article{arxiv.2503.00290,
title = {GMM and M Estimation under Network Dependence},
author = {Yuya Sasaki},
journal= {arXiv preprint arXiv:2503.00290},
year = {2026}
}