Oct

22

Tue
3:30 PM

When:
Tuesday, October 22, 2019

3:30 PM - 5:00 PM

Where: Kellogg Global Hub, 1410, 2211 Campus Drive, Evanston, IL 60208 map it

Audience: Faculty/Staff - Post Docs/Docs - Graduate Students

Contact:
Cindy Pingry
847.467.7263

Group: Department of Economics: Seminar in Econometrics

Category: Academic

Michael Leung (University of Southern California): "Normal Approximation in Large Network Models."

Abstract: We prove central limit theorems for models of network formation and network processes with homophilous agents. The results hold under large-network asymptotics, enabling inference in the typical setting where the sample consists of a small set of large networks. We first establish a general central limit theorem under high-level `stabilization' conditions that provide a useful formulation of weak dependence, particularly in models with strategic interactions. The result delivers a root-n rate of convergence and a closed-form expression for the asymptotic variance. Then using techniques in branching process theory, we derive primitive conditions for stabilization in the following applications: static and dynamic models of strategic network formation, network regressions, and treatment effects with network spillovers. Finally, we suggest some practical methods for inference.