Social Networks and the Dynamics of Labour Market Outcomes: Evidence from Refugees Resettled in the U.S.

Abstract

Recent theoretical work suggests that social networks may play an important role in the dynamics of employment and wages across groups of individuals. This paper provides empirical evidence of job information flows within social networks and the non-linear relationship between social network size and labor market outcomes. An extended version of the model developed by Calvo-Armengol and Jackson (2004) shows that competition can exist between network members for job referrals and investigates the dynamics between the size of a social network, the tenure of network members and labor market outcomes. The predictions of the model are tested empirically using a unique data-set of refugees resettled in the U.S. from 2001-2005. The empirical strategy exploits the special institutional environment of refugee resettlement. I find that a one standard deviation increase in the number of network members who have arrived in the U.S. one year ago lowers the probability of employment by 4.9% and the average hourly wage by $.70. Conversely, as predicted by the model, more tenured network members improve labor market outcomes for recently arrived refugees.