GMM and M Estimation under Network Dependence

Yuya Sasaki

Papers from arXiv.org

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.

Date: 2025-02, Revised 2025-08
New Economics Papers: this item is included in nep-ecm and nep-net
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