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Referral-based Job Search Networks

  • Christian Dustmann

    ()

    (University College London)

  • Albrecht Glitz

    ()

    (Universitat Pompeu Fabra and Barcelona GSE)

  • Uta Schönberg

    ()

    (University College London and Institute for Employment Research (IAB))

This paper develops a model and derives novel testable implications of referral-based job search networks in which employees provide employers with information about potential job market candidates that they otherwise would not have. Using unique matched employeremployee data that cover the entire workforce in one large metropolitan labor market over a 20 year period, we find strong support for the predictions of our model. We first show that firms are more likely to hire minority workers from a particular group if the existing share of workers from that group employed in the firm is higher. We then provide evidence that workers earn higher wages, and are less likely to leave their firms, if they were hired by a firm with a larger share of minority workers from their own group and are therefore more likely to have obtained the job through a referral. The effects are particularly strong at the beginning of the employment relationship and decline with tenure in the firm. These findings have important implications in suggesting that job search networks help to reduce informational deficiencies in the labor market and lead to productivity gains for workers and firms.

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Paper provided by Centre for Research and Analysis of Migration (CReAM), Department of Economics, University College London in its series CReAM Discussion Paper Series with number 1114.

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Date of creation: Jun 2011
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Handle: RePEc:crm:wpaper:1114
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