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Who gets Horizon 2020 research grants? Propensity to apply and probability to succeed in a two-step analysis

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  • Simen G. Enger

    (University of Oslo
    Norwegian Ministry of Education and Research)

  • Fulvio Castellacci

    (University of Oslo)

Abstract

This paper presents a timely analysis of participation in the 8th European Framework Programme for Research and Innovation (EU FP) Horizon 2020. Our dataset comprises the entire population of research organizations in Norway, enabling us to distinguish between non-applicants, non-successful applicants, and successful participants. We find it important to distinguish two stages of the participation process: the self-selection stage in which organizations decide whether they wish to apply for EU funding, and the second stage in which the European Commission selects the best applications for funding. Our econometric results indicate that the propensity to apply is enhanced by prior participation in EU FPs and the existence of complementary national funding schemes; further, that the probability of succeeding is strengthened by prior participation as well as the scientific reputation of the applicant organization.

Suggested Citation

  • Simen G. Enger & Fulvio Castellacci, 2016. "Who gets Horizon 2020 research grants? Propensity to apply and probability to succeed in a two-step analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 1611-1638, December.
    • Handle: RePEc:spr:scient:v:109:y:2016:i:3:d:10.1007_s11192-016-2145-5
    DOI: 10.1007/s11192-016-2145-5
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    Cited by:

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    2. Balázs Győrffy & Andrea Magda Nagy & Péter Herman & Ádám Török, 2018. "Factors influencing the scientific performance of Momentum grant holders: an evaluation of the first 117 research groups," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(1), pages 409-426, October.
    3. Bertoni, Marco & Brunello, Giorgio & Checchi, Daniele & Rocco, Lorenzo, 2021. "Where do I stand? Assessing researchers’ beliefs about their productivity," Journal of Economic Behavior & Organization, Elsevier, vol. 185(C), pages 61-80.
    4. Giuseppe Calignano & Rune Dahl Fitjar & Nina Hjertvikrem, 2018. "Innovation networks and green restructuring: Which path development can EU Framework Programmes stimulate in Norway?," PEGIS geo-disc-2018_05, Institute for Economic Geography and GIScience, Department of Socioeconomics, Vienna University of Economics and Business.
    5. Bertoni, Marco & Brunello, Giorgio & Checchi, Daniele & Rocco, Lorenzo, 2020. "Where Do I Stand? Assessing Researchers' Beliefs about Their Relative Productivity," IZA Discussion Papers 13637, Institute of Labor Economics (IZA).
    6. Giuseppe Calignano, 2022. "Not all peripheries are the same: The importance of relative regional innovativeness in transnational innovation networks," Growth and Change, Wiley Blackwell, vol. 53(1), pages 276-312, March.
    7. Kevin W. Boyack & Caleb Smith & Richard Klavans, 2018. "Toward predicting research proposal success," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(2), pages 449-461, February.
    8. Seeber, Marco & Alon, Ilan & Pina, David G. & Piro, Fredrik Niclas & Seeber, Michele, 2022. "Predictors of applying for and winning an ERC Proof-of-Concept grant: An automated machine learning model," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    9. Walker, James & Brewster, Chris & Fontinha, Rita & Haak-Saheem, Washika & Benigni, Stefano & Lamperti, Fabio & Ribaudo, Dalila, 2022. "The unintended consequences of the pandemic on non-pandemic research activities," Research Policy, Elsevier, vol. 51(1).

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