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Connections in Scientific Committees and Applicants' Self-Selection: Evidence from a Natural Randomized Experiment

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Listed:
  • Bagues, Manuel

    (University of Warwick)

  • Sylos-Labini, Mauro

    (University of Pisa)

  • Zinovyeva, Natalia

    (University of Warwick)

Abstract

We examine how the presence of connections in scientific committees affects researchers' decision to apply and their chances of success. We exploit evidence from Italian academia, where in order to be promoted to an associate or full professorship, researchers are firstly required to qualify in a national evaluation process. Prospective candidates are significantly less likely to apply when the committee includes, through luck of the draw, a colleague or a co-author. This pattern is driven mainly by researchers with a weak research profile. At the same time, information from 300,000 individual evaluation reports shows that applicants tend to receive more favorable evaluations from connected evaluators. Overall, this evidence is consistent with both the existence of a bias in favor of connected candidates and with academic connections reducing information asymmetries. Our study shows that connections are an important determinant of application decisions in academia and, more generally, it highlights the relevance of self-selection for empirical studies on discrimination.

Suggested Citation

  • Bagues, Manuel & Sylos-Labini, Mauro & Zinovyeva, Natalia, 2015. "Connections in Scientific Committees and Applicants' Self-Selection: Evidence from a Natural Randomized Experiment," IZA Discussion Papers 9594, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp9594
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    Cited by:

    1. Bagues, Manuel & Sylos-Labini, Mauro & Zinovyeva, Natalia, 2019. "A walk on the wild side: ‘Predatory’ journals and information asymmetries in scientific evaluations," Research Policy, Elsevier, vol. 48(2), pages 462-477.
    2. Daniele Checchi & Silvia Poli & Enrico Rettore, 2018. "Does Random Selection of Selectors Improve the Quality of Selected Candidates? An Investigation in the Italian Academia," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 4(2), pages 211-247, July.
    3. Manuel Bagues & Mauro Sylos-Labini & Natalia Zinovyeva, 2017. "Does the Gender Composition of Scientific Committees Matter?," American Economic Review, American Economic Association, vol. 107(4), pages 1207-1238, April.
    4. Daniele Checchi & Silvia De Poli & Enrico Rettore, 2017. "Does random selection of commissioners improve the quality of selected candidates? An investigation in the Italian academia," FBK-IRVAPP Working Papers 2017-01, Research Institute for the Evaluation of Public Policies (IRVAPP), Bruno Kessler Foundation.
    5. Federica Bologna & Angelo Iorio & Silvio Peroni & Francesco Poggi, 2023. "Do open citations give insights on the qualitative peer-review evaluation in research assessments? An analysis of the Italian National Scientific Qualification," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(1), pages 19-53, January.
    6. Teplitskiy, Misha & Acuna, Daniel & Elamrani-Raoult, Aïda & Körding, Konrad & Evans, James, 2018. "The sociology of scientific validity: How professional networks shape judgement in peer review," Research Policy, Elsevier, vol. 47(9), pages 1825-1841.
    7. Bao, Zhengyang & Huang, Difang, 2024. "Gender-specific favoritism in science," Journal of Economic Behavior & Organization, Elsevier, vol. 221(C), pages 94-109.

    More about this item

    Keywords

    scientific evaluations; connections; self-selection;
    All these keywords.

    JEL classification:

    • 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
    • J45 - Labor and Demographic Economics - - Particular Labor Markets - - - Public Sector Labor Markets

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