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

Nestor Duch-Brown (), Jose Garcia-Quevedo and Daniel Montolio
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Nestor Duch-Brown: IEB, Universitat de Barcelona
Authors registered in the RePEc Author Service: Néstor Duch Brown

No XREAP2008-12, Working Papers from Xarxa de Referència en Economia Aplicada (XREAP)

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.

Keywords: Subsidies; R&D; DEA; Multi Criteria Decision Analysis; “peer review” (search for similar items in EconPapers)
JEL-codes: C61 H25 O32 (search for similar items in EconPapers)
Pages: 30 pages
Date: 2008-11, Revised 2008-11
New Economics Papers: this item is included in nep-ipr, nep-pr~, nep-pbe and nep-ppm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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http://www.xreap.cat/RePEc/xrp/pdf/XREAP2008-12.pdf First version, 2008 (application/pdf)
http://www.xreap.cat/RePEc/xrp/pdf/XREAP2008-12.pdf Revised version, 2008 (application/pdf)

Related works:
Working Paper: Assessing the assignation of public subsidies: Do the experts choose the most efficient R&D projects? (2008)
Working Paper: Assessing the assignation of public subsidies: Do the experts choose the most efficient R&D projects? (2008)
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