IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1708.07723.html
   My bibliography  Save this paper

Promotion through Connections: Favors or Information?

Author

Listed:
  • Yann Bramoull'e
  • Kenan Huremovi'c

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 Bramoull'e & Kenan Huremovi'c, 2017. "Promotion through Connections: Favors or Information?," Papers 1708.07723, arXiv.org.
  • Handle: RePEc:arx:papers:1708.07723
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1708.07723
    File Function: Latest version
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. James J. Heckman, 1998. "Detecting Discrimination," Journal of Economic Perspectives, American Economic Association, vol. 12(2), pages 101-116, Spring.
    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. 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.
    10. 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.
    11. Bester, C. Alan & Hansen, Christian B., 2016. "Grouped effects estimators in fixed effects models," Journal of Econometrics, Elsevier, vol. 190(1), pages 197-208.
    12. 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.
    13. 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.
    14. Colussi, Tommaso, 2015. "Social Ties in Academia: A Friend is a Treasure," IZA Discussion Papers 9414, Institute of Labor Economics (IZA).
    Full references (including those not matched with items on IDEAS)

    More about this item

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:1708.07723. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (arXiv administrators). General contact details of provider: http://arxiv.org/ .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.