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


  • Nestor Duch-Brown
  • Jose Garcia-Quevedo
  • Daniel Montolio

    (Universitat de Barcelona)


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

  • Nestor Duch-Brown & Jose Garcia-Quevedo & Daniel Montolio, 2008. "Assessing the assignation of public subsidies: Do the experts choose the most efficient R&D projects?," Working Papers in Economics 207, Universitat de Barcelona. Espai de Recerca en Economia.
  • Handle: RePEc:bar:bedcje:2008207

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    References listed on IDEAS

    1. Adam B. Jaffe, 2002. "Building Programme Evaluation into the Design of Public Research-Support Programmes," Oxford Review of Economic Policy, Oxford University Press, vol. 18(1), pages 22-34, Spring.
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    2. 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.
    3. Catalina Bolancé & Zuhair Bahraoui & Ramon Alemany, 2015. "Estimating extreme value cumulative distribution functions using bias-corrected kernel approaches," Working Papers XREAP2015-01, Xarxa de Referència en Economia Aplicada (XREAP), revised Jan 2015.
    4. Anna Castañer & Mª Mercè Claramunt, 2014. "Optimal stop-loss reinsurance: a dependence analysis," Working Papers XREAP2014-04, Xarxa de Referència en Economia Aplicada (XREAP), revised Apr 2014.
    5. Mercedes Ayuso & Montserrat Guillén & Jens Perch Nielsen, 2016. "Improving automobile insurance ratemaking using telematics: incorporating mileage and driver behaviour data," Working Papers XREAP2016-08, Xarxa de Referència en Economia Aplicada (XREAP), revised Dec 2016.
    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.

    More about this item

    JEL classification:

    • H25 - Public Economics - - Taxation, Subsidies, and Revenue - - - Business Taxes and Subsidies
    • 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

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