Coworkers, Networks, and Job-Search Outcomes among Displaced Workers

Abstract

This article examines the mechanisms by which social networks affect the labor market outcomes of displaced workers. The authors draw on administrative records for the universe of private-sector employment in Austria to identify work-related networks among former coworkers. They analyze the importance of social networks for both job seekers and hiring firms. For job seekers, results indicate that having a high share of former coworkers who are currently employed in expanding firms improves job-finding success. For firms seeking to hire new employees, the authors find that a firm is twice as likely to hire a displaced worker with a former-coworker link to one of their current employees than to hire a worker displaced from the same closing firm but without a link. These results suggest that information about job opportunities and demand-side conditions is transmitted in work-related networks between workers and firms.

Learning through coworker referrals

“…Presumably, the usefulness of coworkers as providers of referrals (as in Montgomery, 1991, Simon and Warner, 1992, Galenianos, 2013 or sources of information about available job opportunities (as in Calvó- Armengol and Jackson, 2004, Wahba and Zenou, 2005, Boucher and Goussé, 2019 is due to the fact that, by having worked together in the past, coworkers tend to possess better knowledge about their social contacts' respective skills and are more aware of suitable job openings than other types of social contacts such as former classmates, friends or neighbours, who often lack the professional interaction on the job and the attachment to the relevant labor market segment (see Antoninis, 2006). 2 In recent years, a number of studies have therefore analyzed in more detail this type of social connection and its role for labor market outcomes (see, for instance, Cingano and Rosolia, 2012, Hensvik and Skans, 2016, Glitz, 2017, Saygin et al, 2019.…”

“…Contrary to much of this literature, which has focused on the role of coworker-based networks in increasing job offer arrival rates (Cingano and Rosolia, 2012, Glitz, 2017, Saygin et al, 2019, we study the role of coworker-based referrals in reducing information frictions in the hiring process. Our empirical work is guided by a Jovanovic-type learning model, initially adapted to the referral context by Simon and Warner (1992) and then substantially extended by Dustmann et al (2016), in which initial uncertainty coupled with subsequent learning about match-specific productivity is generating distinct patterns of wages and job turnover as a function of tenure.…”

Do neighbors help finding a job? Social networks and labor market outcomes after plant closures

“…Similar analyses can be found in Edin et al (2003) for Sweden or in Damm (2009) for Denmark. Social networks, dened not as the neighborhood but as a set of former coworkers, form the starting point for the research of Cingano and Rosolia (2012), Glitz (2013), andSaygin et al (2014). Here, the idea is that information on vacancies may come from other workers with whom the displaced worker worked for at least a limited period of time at the rm that closed.…”

“…The study by Cingano and Rosolia (2012) is based on Italian data, Glitz (2013) on German data, and Saygin et al (2014) on Austrian data. All of these studies nd signicant eects of the employment rate among former co-workers on the job-nding probability of the displaced worker.…”

Information, Mobile Communication, and Referral Effects

“…In the existing literature researchers have proposed several proxies for social networks, such as former fellow workers(Cingano and Rosolia 2012;Giltz 2017;Saygin et al 2018), family ties(Kramarz and Skans 2014), individuals who belong to the same immigrant community or ethnic group(Edin et al 2003 ;Munshi and Rosenzweig 2013;Beaman 2012;Dustmann et al 2016;Aslund et al 2014), residential neighbors(Bayer et al 2008;Hellerstein et al 2011;Hellerstein et al 2014;Schumutte 2015), and Facebook friends(Gee et al 2017) …”