Information Flow in Networks of Former Coworkers

In this paper, we provide a comprehensive assessment of the role of coworker-based networks in the labor market. Using Danish register data, we first analyse how such social networks shape workers' inter-firm mobility patterns, considering both job-to-job and unemployment-to-job movements. We then assess which dimensions of worker-pair-specific social capital are the main drivers of individual mobility choices and estimate semi-parametrically how getting a job through the network affects wage profiles and job stability. Preliminary results show, first, that 34.5% of workers start a new job in a firm in which a former coworker is already present. This is 4-times more than expected under random matching of workers to firms. Second, starting a new job in a firm with a former coworker already present increases starting wages by 2.0% and reduces subsequent wage growth by 0.1 percentage points per year. Third, starting a new job in a firm with a former coworker already present reduces initial turnover by 4.3 percentage points and leads to a 0.8 percentage point relative annual increase in subsequent job turnover probability. Finally, higher social capital levels magnify both the initial effects on wages and turnover and the effects determining subsequent convergence rates. Overall, the empirical results strongly suggest that referrals serve as providers of information about match-specific productivity.