The weakness of common job contacts

This paper identifies an ignored driver of labor market outcomes in Calvó-Armengol (2004): the presence of overlapping neighborhoods in people’s social networks, a stylized fact of real world networks. We prove that short network cycles induce stochastic affiliation in diffusion processes channeled by networks, generating diffusion inefficiencies in the transmission of job information with persistent consequences on employment, wages, and inequality within and across networked societies. In particular, they organize employment probabilities in the sense of the first-order stochastic dominance: people in close-knit neighborhoods exhibit worse labor-market outcomes, even if they have the same number of information providers and compete with the same number of people for vacancies.Such a finding implies that the results in Calvó-Armengol (2004) are generally only valid for tree networks. Since dense, overlapping neighborhoods is one aspect of strong relationships, our findings uncover an alternative mechanism behind the strength of weak ties (Granovetter, 1973). Furthermore, short network cycles reinforce spatial and temporal correlations in employment status, shaping labor-market transition rates and amplifying aggregate employment fluctuations.