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Promotion through Connections: Favors or Information?

Author

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  • Yann Bramoullé

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

  • 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://halshs.archives-ouvertes.fr/halshs-01577251
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    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. Meta Brown & Elizabeth Setren & Giorgio Topa, 2016. "Do Informal Referrals Lead to Better Matches? Evidence from a Firm's Employee Referral System," Journal of Labor Economics, University of Chicago Press, vol. 34(1), pages 161-209.
    4. Bester, C. Alan & Hansen, Christian B., 2016. "Grouped effects estimators in fixed effects models," Journal of Econometrics, Elsevier, vol. 190(1), pages 197-208.
    5. Combes, Pierre-Philippe & Linnemer, Laurent & Visser, Michael, 2008. "Publish or peer-rich? The role of skills and networks in hiring economics professors," Labour Economics, Elsevier, vol. 15(3), pages 423-441, June.
    6. Davidson, Russell & MacKinnon, James G., 1984. "Convenient specification tests for logit and probit models," Journal of Econometrics, Elsevier, vol. 25(3), pages 241-262, July.
    7. David Neumark, 2012. "Detecting Discrimination in Audit and Correspondence Studies," Journal of Human Resources, University of Wisconsin Press, vol. 47(4), pages 1128-1157.
    8. Amanda Pallais & Emily Glassberg Sands, 2016. "Why the Referential Treatment? Evidence from Field Experiments on Referrals," Journal of Political Economy, University of Chicago Press, vol. 124(6), pages 1793-1828.
    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.
    11. Colussi, Tommaso, 2015. "Social Ties in Academia: A Friend is a Treasure," IZA Discussion Papers 9414, Institute of Labor Economics (IZA).
    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.
    14. Brogaard, Jonathan & Engelberg, Joseph & Parsons, Christopher A., 2014. "Networks and productivity: Causal evidence from editor rotations," Journal of Financial Economics, Elsevier, vol. 111(1), pages 251-270.
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    More about this item

    Keywords

    social networks; connections; promotion; favoritism; information;

    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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