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Promotion through Connections: Favors or Information?

Author

Listed:
  • Yann Bramoullé

    (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique)

  • Kenan Huremovic

    (IMT - School for Advanced Studies Lucca)

Abstract
Connections appear to be helpful in many contexts such as obtaining a job, a promotion, a grant, a loan or publishing a paper. This may be due to favoritism or to information conveyed by connections. Attempts at identifying both effects have relied on measures of true quality, generally built from data collected long after promotion. This empirical strategy faces important limitations. Building on earlier work on discrimination, we propose a new method to identify favors and information from classical data collected at time of promotion. Under natural assumptions, we show that promotion decisions look more random for connected candidates, due to the information channel. We obtain new identification results and show how probit models with heteroscedasticity can be used to estimate the strength of the two effects. We apply our method to the data on academic promotions in Spain studied in Zinovyeva & Bagues (2015). We find evidence of both favors and information effects at work. Empirical results are consistent with evidence obtained from quality measures collected five years after promotion.

Suggested Citation

  • Yann Bramoullé & Kenan Huremovic, 2017. "Promotion through Connections: Favors or Information?," Working Papers halshs-01577251, HAL.
    • Handle: RePEc:hal:wpaper:halshs-01577251
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-01577251
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    References listed on IDEAS

    as
    1. Lori Beaman & Jeremy Magruder, 2012. "Who Gets the Job Referral? Evidence from a Social Networks Experiment," American Economic Review, American Economic Association, vol. 102(7), pages 3574-3593, December.
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    4. Natalia Zinovyeva & Manuel Bagues, 2015. "The Role of Connections in Academic Promotions," American Economic Journal: Applied Economics, American Economic Association, vol. 7(2), pages 264-292, April.
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    9. Marianne Bertrand & Sendhil Mullainathan, 2004. "Are Emily and Greg More Employable Than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination," American Economic Review, American Economic Association, vol. 94(4), pages 991-1013, September.
    10. Danielle Li, 2017. "Expertise versus Bias in Evaluation: Evidence from the NIH," American Economic Journal: Applied Economics, American Economic Association, vol. 9(2), pages 60-92, April.
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    12. James J. Heckman, 1998. "Detecting Discrimination," Journal of Economic Perspectives, American Economic Association, vol. 12(2), pages 101-116, Spring.
    13. Laband, David N & Piette, Michael J, 1994. "Favoritism versus Search for Good Papers: Empirical Evidence Regarding the Behavior of Journal Editors," Journal of Political Economy, University of Chicago Press, vol. 102(1), pages 194-203, February.
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    More about this item

    Keywords

    promotion; connections; social networks; favoritism; information;
    All these keywords.

    JEL classification:

    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
    • M51 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Personnel Economics - - - Firm Employment Decisions; Promotions

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