https://macropaperwarehouse.com/authors/michael-p-leung/Michael P LeungHugo -- gohugo.ioen-ushttps://macropaperwarehouse.com/papers/normal-approximation-in-large-network-models/https://macropaperwarehouse.com/papers/normal-approximation-in-large-network-models/<p>This paper proves a central limit theorem (CLT) for network formation models with strategic interactions and homophilous agents, addressing a foundational inferential gap in the econometrics of large networks. The setting is one where the econometrician observes a single large network — the asymptotic framework sends network size n to infinity — which is the empirically relevant case for most network datasets. The network moments of interest are averages of node-level statistics (1/n) Σ ψ_i, where ψ_i can capture degree, clustering coefficients, or subnetwork counts (triangles, k-stars) that have been used for structural inference in network formation games.</p>