IDEAS home Printed from
   My bibliography  Save this article

A robust nonparametric approach to the analysis of scientific productivity


  • Andrea Bonaccorsi
  • Cinzia Daraio


Data on scientific productivity at institutes of the French INSERM and at biomedical research institutes of the Italian CNR for 1997 were analysed. Available data on human capital input and geographical agglomeration allowed the estimation and comparison of efficiency measures. Nonparametric envelopment techniques were used, and robust nonparametric techniques were applied in this work for the first time for evaluating scientific productivity. They are shown to be useful tools to compute scientific productivity indicators and make institutional comparative analyses. Taking into account a large number of methodological problems, a meaningful and rigorous indirect comparison is made possible. Several possible explanations of the observed differences in productivity are commented on. Copyright , Beech Tree Publishing.

Suggested Citation

  • Andrea Bonaccorsi & Cinzia Daraio, 2003. "A robust nonparametric approach to the analysis of scientific productivity," Research Evaluation, Oxford University Press, vol. 12(1), pages 47-69, April.
  • Handle: RePEc:oup:rseval:v:12:y:2003:i:1:p:47-69

    Download full text from publisher

    File URL:
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    1. Saragossi, Sarina & van Pottelsberghe de la Potterie, Bruno, 2003. "What Patent Data Reveal about Universities: The Case of Belgium," The Journal of Technology Transfer, Springer, vol. 28(1), pages 47-51, January.
    2. Saul Lach & Mark Schankerman, 2008. "Incentives and invention in universities," RAND Journal of Economics, RAND Corporation, vol. 39(2), pages 403-433.
    3. Rebecca Henderson & Adam B. Jaffe & Manuel Trajtenberg, 1998. "Universities As A Source Of Commercial Technology: A Detailed Analysis Of University Patenting, 1965-1988," The Review of Economics and Statistics, MIT Press, vol. 80(1), pages 119-127, February.
    4. Goldfarb, Brent & Henrekson, Magnus, 2003. "Bottom-up versus top-down policies towards the commercialization of university intellectual property," Research Policy, Elsevier, vol. 32(4), pages 639-658, April.
    5. Geuna, Aldo & Nesta, Lionel J.J., 2006. "University patenting and its effects on academic research: The emerging European evidence," Research Policy, Elsevier, vol. 35(6), pages 790-807, July.
    Full references (including those not matched with items on IDEAS)


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

    Cited by:

    1. repec:spr:scient:v:81:y:2009:i:3:d:10.1007_s11192-008-2210-9 is not listed on IDEAS
    2. Daraio, Cinzia & Bonaccorsi, Andrea & Simar, Léopold, 2015. "Efficiency and economies of scale and specialization in European universities: A directional distance approach," Journal of Informetrics, Elsevier, vol. 9(3), pages 430-448.
    3. Chen, Ping-Chuan & Hung, Shiu-Wan, 2016. "An actor-network perspective on evaluating the R&D linking efficiency of innovation ecosystems," Technological Forecasting and Social Change, Elsevier, vol. 112(C), pages 303-312.
    4. Abramo, Giovanni & Cicero, Tindaro & D’Angelo, Ciriaco Andrea, 2011. "A field-standardized application of DEA to national-scale research assessment of universities," Journal of Informetrics, Elsevier, vol. 5(4), pages 618-628.
    5. Bronwyn Hall & Jacques Mairesse & Laure Turner, 2007. "Identifying Age, Cohort, And Period Effects In Scientific Research Productivity: Discussion And Illustration Using Simulated And Actual Data On French Physicists," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 16(2), pages 159-177.
    6. repec:eee:jomega:v:74:y:2018:i:c:p:103-114 is not listed on IDEAS
    7. Amy Apon & Linh Ngo & Michael Payne & Paul Wilson, 2015. "Assessing the effect of high performance computing capabilities on academic research output," Empirical Economics, Springer, vol. 48(1), pages 283-312, February.
    8. Ortega, Francisco J. & Gavilan, Jose M., 2013. "The measurement of production efficiency in scientific journals through stochastic frontier analysis models: Application to quantitative economics journals," Journal of Informetrics, Elsevier, vol. 7(4), pages 959-965.
    9. Chen Kaihua & Kou Mingting, 2014. "Staged efficiency and its determinants of regional innovation systems: a two-step analytical procedure," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 52(2), pages 627-657, March.
    10. Daniel Chudnovsky & Andrés López & Martín Rossi & Diego Ubfal, 2006. "Evaluating a Program of Public Funding of Scientific Activity: A Case Study of FONCYT in Argentina," IDB Publications (Working Papers) 2831, Inter-American Development Bank.
    11. Gustavo Crespi & Aldo Geuna, 2005. "Modelling and Measuring Scientific Production: Results for a Panel of OECD Countries," SPRU Working Paper Series 133, SPRU - Science and Technology Policy Research, University of Sussex.
    12. Crespi, Gustavo A. & Geuna, Aldo, 2008. "An empirical study of scientific production: A cross country analysis, 1981-2002," Research Policy, Elsevier, vol. 37(4), pages 565-579, May.
    13. Mehdi Rhaiem, 2017. "Measurement and determinants of academic research efficiency: a systematic review of the evidence," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(2), pages 581-615, February.
    14. Lee, Seonghee & Lee, Hakyeon, 2015. "Measuring and comparing the R&D performance of government research institutes: A bottom-up data envelopment analysis approach," Journal of Informetrics, Elsevier, vol. 9(4), pages 942-953.
    15. repec:gam:jsusta:v:9:y:2017:i:12:p:2297-:d:122520 is not listed on IDEAS
    16. repec:spr:scient:v:76:y:2008:i:2:d:10.1007_s11192-007-1942-2 is not listed on IDEAS
    17. repec:spr:scient:v:98:y:2014:i:2:d:10.1007_s11192-013-1088-3 is not listed on IDEAS

    More about this item


    Access and download statistics


    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:oup:rseval:v:12:y:2003:i:1:p:47-69. 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: (Oxford University Press) or (Christopher F. Baum). General contact details of provider: .

    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 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.

    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.