Social Contacts and Occupational Choice

Abstract

Social contacts help to find jobs, but not necessarily in the occupations where workers are most productive. Hence social contacts can generate mismatch between workers' occupational choices and their productive advantage. Accordingly, social networks can lead to low labour force quality, low returns to firms' investment and depressed aggregate productivity. We analyse surveys from both the US and Europe including information on job finding through contacts. Consistent with our predictions, contacts reduce unemployment duration by 1-3 months on average, but they are associated with wage discounts of at least 2.5%. We also find some evidence of negative externalities on aggregate productivity. Copyright (c) The London School of Economics and Political Science 2008.

With a little help from my friends? Quality of social networks, job finding and job match quality

“…However, if workers are heterogeneous in their skills, and jobs differ in the type of skills they require, mismatch may arise when employed contacts transmit opportunities about jobs which require different skills from the ones the unemployed possess (e.g. Bentolila et al, 2010). The degree of mismatch depends on the degree of homophily, which is the 1 Studies in which networks transmit information about the productivity of workers through referrals to current employers, or can inform workers and firms about the quality of the match, include Saloner (1985), Montgomery (1991), Simon and Warner 1992, Mortensen and Vishwanath, 1994, and more recently, Brown et al (2012, Dustmann et al (2011) andGalenianos (2014).…”

“…2 Previous empirical research on network effects in the labor market is based either on survey information on the use of informal search methods, such as friends and relatives, or on administrative records in which networks are defined indirectly using observable proxies, such as neighborhood, firm, or ethnicity. Studies on the use of informal search methods include Simon and Warner (1992), Pistaferri (1999), Marmaros and Sacerdote (2002), Loury (2006), Bentolila et al (2010) and Pellizzari (2010). 3 Studies defining networks indirectly using proxies include Topa (2001), Weinberg et al (2004), Bayer et al (2008), Hellerstein et al (2011) and Schmutte (2015), who use geographic proximity at the neighborhood level; Cingano and Rosolia (2012), who define networks at the firm level; Edin et al (2003), Munshi (2003) and Beaman (2012), who define networks based on immigrants' ethnic origin; and Dustmann et al (2011), who use information on both firms and ethnicity.…”

“…The effect of network quality on job match quality, however, depends on the degree of homophily, which is the tendency of individuals to befriend others who are similar to themselves (e.g. Bentolila et al 2010;Horvath, 2014).…”

Local social capital and geographical mobility

“…8 It is interesting to note that most works surveyed emphasize the positive role of social capital on labor market performance, while in this paper we tend to emphasize certain negative channels. Bentolila et al (2010) provides a counterexample, and looks more specifically at European countries, emphasizing the potential negative links between social capital and labor markets. In particular, they argue that jobs obtained through social networks have a wage discount, distorting choices towards inefficiency.…”

An Overview of Social Networks and Economic Applications

“…This sort of pattern is not specific to the textile industry, but is typical. There are some variations in the role of networks as a source of job information as we make comparisons across professions, locations, ethnicities of workers, and other attributes; but networks play a substantial role in essentially all of the labor markets that have been studied, regardless of the skill level, location, or population of workers (e.g., see Rees and Shultz (1970), Montgomery (1991), Pellizzari (2009), Corcoran, Datcher, and Duncan (1980), and Bentolila et al (2009)). 5 The fact that information about jobs is passed through a social network becomes interesting because of its implications for wage and employment dynamics and patterns.…”