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Explaining U-shape of the Referral Hiring Pattern in a Search Model with Heterogeneous Workers

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  • Zaharieva, Anna
  • Stupnytska, Yuliia

Abstract

This paper presents a search model with heterogeneous workers, social networks and endogenous search intensity. There are three job search channels available to the unemployed: costly formal applications and two costless informal channels - through family and professional networks. The gain from being employed is increasing in the productivity, so the lowest motivation for preparing formal applications is proved to be among the least productive worker types. We assume that professional contacts exhibit a strong degree of homophily, thus it is profitable for firms to direct their network search towards more productive incumbent employees. So the probability of a professional referral is increasing in the productivity of the worker, which mitigates the incentives to use the formal channel of search. Therefore, the model predicts that workers in the right (left) tail of the productivity distribution have the highest propensity of finding a job with a help of professional (family) contacts, whereas the formal channel of search is mostly utilized by workers in the middle range of the distribution. This explains the U-shaped referral hiring pattern in the model. Endogenous sorting of workers across channels also implies that professional (family) referrals are associated with wage premiums (penalties) compared to the formal channel of search.

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  • Zaharieva, Anna & Stupnytska, Yuliia, 2015. "Explaining U-shape of the Referral Hiring Pattern in a Search Model with Heterogeneous Workers," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112992, Verein für Socialpolitik / German Economic Association.
  • Handle: RePEc:zbw:vfsc15:112992
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    Cited by:

    1. Zaharieva, Anna, 2015. "On the Puzzle of Diversification in Social Networks with Occupational Mismatch," Center for Mathematical Economics Working Papers 547, Center for Mathematical Economics, Bielefeld University.
    2. Martina Rebien & Michael Stops & Anna Zaharieva, 2020. "Formal Search And Referrals From A Firm'S Perspective," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 61(4), pages 1679-1748, November.
    3. Moreno Galbis, Eva & Wolff, Francois-Charles & Herault, Arnaud, 2020. "How helpful are social networks in finding a job along the economic cycle? Evidence from immigrants in France," Economic Modelling, Elsevier, vol. 91(C), pages 12-32.
    4. Gergely Horváth, 2020. "The Impact of Social Segregation on the Labor Market Outcomes of Low‐Skilled Workers," Scandinavian Journal of Economics, Wiley Blackwell, vol. 122(1), pages 3-37, January.
    5. Stupnytska, Yuliia, 2015. "Asymmetric information in a search model with social contacts," Center for Mathematical Economics Working Papers 548, Center for Mathematical Economics, Bielefeld University.
    6. Damdinsuren, Erdenebulgan & Mitkova, Mariya & Zaharieva, Anna, 2024. "Parental networks, wage expectations, and the intergenerational educational mobility," Journal of Economic Behavior & Organization, Elsevier, vol. 218(C), pages 146-175.
    7. Zaharieva, Anna, 2018. "On the optimal diversification of social networks in frictional labour markets with occupational mismatch," Labour Economics, Elsevier, vol. 50(C), pages 112-127.
    8. Obbey Ahmed Elamin, 2018. "Impact of Informal Job-search on Wages for University Graduates in Egypt and Jordan," Working Papers 1272, Economic Research Forum, revised 19 Dec 2018.

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    JEL classification:

    • J23 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Demand
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • J64 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment: Models, Duration, Incidence, and Job Search

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