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Referrals and Search Efficiency: Who Learns What and When?

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  • Tavis Barr
  • Raicho Bojilov
  • Lalith Munasinghe

Abstract

Referrals can improve screening and self-selection of applicants during the hiring process. We model and estimate how referral information affects the selection of employees through job offers, acceptances, and turnover. Using data from a call center company, we show that referrals help employers attract applicants of superior performance. Yet performance differences between referred and nonreferred workers diminish with tenure through selective turnover. Our estimates reveal that referrals allow employers to screen on hard-to-observe but performance-relevant attributes for employees of high performance and high propensity to stay. Thus, referred applicants complete much of the sorting during the hiring process.

Suggested Citation

  • Tavis Barr & Raicho Bojilov & Lalith Munasinghe, 2019. "Referrals and Search Efficiency: Who Learns What and When?," Journal of Labor Economics, University of Chicago Press, vol. 37(4), pages 1267-1300.
    • Handle: RePEc:ucp:jlabec:doi:10.1086/703163
    DOI: 10.1086/703163
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    Cited by:

    1. Emre Ekinci, 2022. "Monetary rewards in employee referral programs," Manchester School, University of Manchester, vol. 90(1), pages 35-58, January.
    2. Dariel, Aurelie & Riedl, Arno & Siegenthaler, Simon, 2021. "Referral hiring and wage formation in a market with adverse selection," Games and Economic Behavior, Elsevier, vol. 130(C), pages 109-130.
    3. María Paz Espinosa & Jaromír Kovárík & Sofía Ruíz-Palazuelos, 2021. "Are close-knit networks good for employment?," Working Papers 21.06, Universidad Pablo de Olavide, Department of Economics.

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