Social networks and labour match quality: a search approach

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Individuals often rely on their informal personal contacts - social networks - to findemployment or improve their labour market prospects. The general direction of thetheoretical literature predicts a positive effect of networks on the quality of the matchbetween workers and firms, and thus wages and turnover, because they reduce informationand search frictions. However, the empirical literature gives mixed and heterogenous results.My objective is to explore alternative channels of transmission from networks to matchquality. I will study the role of networks in wage bargaining as a determinant of the worker'soutside option, and as a social risk sharing mechanism against the incidence ofunemployment, to explain the differentials of the effect of networks on wages and turnoverby skill level. To address these issues, I will follow a structural approach to identify andquantify the economic mechanisms behind the relationship. For the theoretical part, I willformulate three models incorporating networks into a directed search framework, thatincludes wage renegotiation and learning about match quality. Using individual level datafrom the UK and Germany, I will empirically test the predictions of these models usingadvanced quantitative methods. This project will contribute to the strand of theoreticalliterature on social networks in search models, and the empirical literature that evaluatesthem using large individual level datasets. From a policy point of view, this project will beuseful when designing programs for employment agencies to fill the information gap forthose who have less access to job referrals.