Bayesian estimation; endogenous network formation; geographical space; Social interactions; social space
Résumé :
[en] 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.
Disciplines :
Economie internationale
Auteur, co-auteur :
Patacchini, Eleonora; Cornell University
PICARD, Pierre M ; University of Luxembourg > Faculty of Law, Economics and Finance (FDEF) > Center for Research in Economic Analysis (CREA)
Zenou, Yves; Monash University > Department of Economics, Monash Business School
Langue du document :
Anglais
Titre :
Urban social structure, social capital and spatial proximity