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Assessing the assignation of public subsidies: Do the experts choose the most efficient R&D projects?

Author

Listed:
  • Néstor Duch-Brown

    (IEB & Universitat de Barcelona)

  • José García-Quevedo

    (IEB & Universitat de Barcelona)

  • Daniel Montolio

    (IEB & Universitat de Barcelona)

Abstract
The implementation of public programs to support business R&D projects requires the establishment of a selection process. This selection process faces various difficulties, which include the measurement of the impact of the R&D projects as well as selection process optimization among projects with multiple, and sometimes incomparable, performance indicators. To this end, public agencies generally use the peer review method, which, while presenting some advantages, also demonstrates significant drawbacks. Private firms, on the other hand, tend toward more quantitative methods, such as Data Envelopment Analysis (DEA), in their pursuit of R&D investment optimization. In this paper, the performance of a public agency peer review method of project selection is compared with an alternative DEA method.

Suggested Citation

  • Néstor Duch-Brown & José García-Quevedo & Daniel Montolio, 2008. "Assessing the assignation of public subsidies: Do the experts choose the most efficient R&D projects?," Working Papers 2008/5, Institut d'Economia de Barcelona (IEB).
  • Handle: RePEc:ieb:wpaper:doc2008-5
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    References listed on IDEAS

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    3. Esther-Vayá & José-Ramón-García & Joaquim-Murillo & Javier-Romaní & Jordi-Suriñach, 2016. "“Economic Impact of Cruise Activity: The Port of Barcelona"," IREA Working Papers 201613, University of Barcelona, Research Institute of Applied Economics, revised Nov 2016.
    4. Simon Hirzel & Tim Hettesheimer & Peter Viebahn & Manfred Fischedick, 2018. "A Decision Support System for Public Funding of Experimental Development in Energy Research," Energies, MDPI, vol. 11(6), pages 1-18, May.
    5. Mercedes Ayuso & Montserrat Guillen & Jens Perch Nielsen, 2019. "Improving automobile insurance ratemaking using telematics: incorporating mileage and driver behaviour data," Transportation, Springer, vol. 46(3), pages 735-752, June.
    6. Antonio Manresa & Ferran Sancho, 2012. "Leontief versus Ghosh: two faces of the same coin," Working Papers XREAP2012-18, Xarxa de Referència en Economia Aplicada (XREAP), revised Oct 2012.
    7. Anna Castañer & Mª Mercè Claramunt & Alba Tadeo & Javier Varea, 2016. "Modelización de la dependencia del número de siniestros. Aplicación a Solvencia II," Working Papers XREAP2016-01, Xarxa de Referència en Economia Aplicada (XREAP), revised Sep 2016.
    8. Carlos José Miranda Victório & Helder Gomes Costa & Cristina Gomes de Souza, 2016. "Modeling selection criteria of R&D projects for awarding direct subsidies to the private sector," Science and Public Policy, Oxford University Press, vol. 43(2), pages 275-287.

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    More about this item

    Keywords

    Subsidies; R&D; DEA; Multi Criteria Decision Analysis; “peer review”;
    All these keywords.

    JEL classification:

    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • H25 - Public Economics - - Taxation, Subsidies, and Revenue - - - Business Taxes and Subsidies

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