IDEAS home Printed from https://ideas.repec.org/p/hal/journl/halshs-03564238.html

What Makes a Productive Ph.D. Student?

Author

Listed:
  • Alberto Corsini

    (GREDEG - Groupe de Recherche en Droit, Economie et Gestion - UNS - Université Nice Sophia Antipolis (1965 - 2019) - CNRS - Centre National de la Recherche Scientifique - UniCA - Université Côte d'Azur)

  • Michele Pezzoni

    (GREDEG - Groupe de Recherche en Droit, Economie et Gestion - UNS - Université Nice Sophia Antipolis (1965 - 2019) - CNRS - Centre National de la Recherche Scientifique - UniCA - Université Côte d'Azur)

  • Fabiana Visentin

Abstract

This paper investigates how the social environment to which a Ph.D. student is exposed during her training relates to her scientific productivity. We investigate how supervisor and peers' characteristics are associated with the student's publication quantity, quality, and co-authorship network size. Unique to our study, we cover the entire Ph.D. student population of a European country for all the STEM fields analyzing 77,143 students who graduated in France between 2000 and 2014. We find that having a productive, mid-career, low-experienced, female supervisor who benefits from a national grant is positively associated with the student's productivity. Furthermore, we find that having few productive freshman peers and at least one female peer is positively associated with the student's productivity. Interestingly, we find heterogeneity in our results when breaking down the student population by field of research.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Alberto Corsini & Michele Pezzoni & Fabiana Visentin, 2021. "What Makes a Productive Ph.D. Student?," Post-Print halshs-03564238, HAL.
    • Handle: RePEc:hal:journl:halshs-03564238
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Danielle Lee, 2024. "Exploring the determinants of research performance for early-career researchers: a literature review," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(1), pages 181-235, January.
    2. Plantec, Quentin & Cabanes, Benjamin & le Masson, Pascal & Weil, Benoit, 2023. "Early-career academic engagement in university–industry collaborative PhDs: Research orientation and project performance," Research Policy, Elsevier, vol. 52(9).
    3. Chen, Kaihua & Ding, Yi & Zhao, Binbin & Guo, Rui & Ning, Lutao, 2025. "Benefits beyond the local network: Does indirect international collaboration ties contribute to research performance for young scientists?," Research Policy, Elsevier, vol. 54(5).
    4. Changhong Teng & Chunmei Yang & Guanghao Wu, 2025. "Are female students less satisfied with doctoral candidacy experiences? Evidence from 108 countries," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 12(1), pages 1-13, December.
    5. Keloharju, Matti & Knüpfer, Samuli & Müller, Dagmar & Tåg, Joacim, 2024. "PhD studies hurt mental health, but less than previously feared," Research Policy, Elsevier, vol. 53(8).
    6. Sofia Patsali & Michele Pezzoni & Fabiana Visentin, 2021. "The Impact of Research Independence on PhD Students’ Careers: Large-Scale Evidence from France," Post-Print hal-03564708, HAL.
    7. Marjan Cugmas & Franc Mali & Luka Kronegger, 2024. "Longitudinal patterns of scientific collaboration in doctoral studies," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(2), pages 1055-1077, February.
    8. Lindahl, Jonas & Danell, Rickard & Litson, Kaylee & Feldon, David F., 2025. "Sex differences in research productivity among doctoral students in Sweden: A quantile regression approach," Journal of Informetrics, Elsevier, vol. 19(3).

    More about this item

    JEL classification:

    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General

    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:hal:journl:halshs-03564238. See general information about how to correct material in RePEc.

    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.

    We have no bibliographic references for this item. You can help adding them by using 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.