Applied Micro Seminar : Every Tuesday
Time: 12:15 pm – 13:30 pm
Date: May, 5th
Room : 3001

Maximilian KASY  “Causal Inference for Social Network Formation”

Abstract : 

This paper develops a framework for identification, estimation, and infer-ence on the causal mechanisms driving endogenous social network formation. Identification is challenging because of unobserved confounders and reverse causality; inference is complicated by questions of equilibrium and sampling. We leverage repeated observations of a network over time and random variation in initial ties to address challenges to causal identification. Our design-based approach sidesteps questions of sampling and asymptotics by treating both the set of nodes (individuals) and potential outcomes as non-random.We apply our approach to data from a large professional services firm, where new hires are randomly assigned to project teams within offices. We estimate the causal effect on tie formation of indirect ties, network degree, and local network density. Indirect ties have a strong and significant positive effect ontie formation, while the effects of degree and density are smaller and less robust.

Paper is here: https://maxkasy.github.io/home/files/papers/network_formation.pdf

Organizers:
Benoît SCHMUTZ (Pôle économie du CREST)
Clément MALGOUYRES (Pôle économie du CREST)

Sponsors:
CREST