Working Paper: CEPR ID: DP10501
Authors: Eleonora Patacchini; Pierre M. Picard; Yves Zenou
Abstract: We develop a theoretical model where the existence and intensity of dyadic contacts depend on location. We show that agents tend to interact more with agents that are highly central in the network of social contacts and that are geographically closer. Using a unique geo-coded dataset of friendship networks in the United States, we find evidence consistent with this model. The main empirical challenge, which is the possible endogenous network formation, is tackled by employing a Bayesian methodology that allows to estimate simultaneously network formation and intensity of network contacts.
Keywords: Bayesian estimation; endogenous network formation; geographical space; social interactions; social space
JEL Codes: R1; R23; Z13
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Geographical distance (R12) | Intensity of social interactions (C92) |
| Social capital (Z13) | Intensity of social interactions (C92) |
| Lower travel costs (R41) | Social capital (Z13) |
| Spatial distribution of individuals (R12) | Social capital (Z13) |