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Good value for public money? The case of R&D policy

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  • Aiello, Francesco
  • Albanese, Giuseppe
  • Piselli, Paolo

Abstract

This paper evaluates the role of public R&D support on Italian manufacturing SMEs’ innovation activities, focusing on innovation output rather than innovation input. Combining information from EPO records and the Capitalia survey, the new data set enables a counterfactual assessment of R&D policy from 2001 to 2003 (2009 is the final year of the post-treatment period). We find that publicly supported firms have higher R&D expenditure regardless of their characteristics, confirming a strong additionality effect of public policies on innovation inputs. However, this additional spending does not increase firms’ probability of patenting or the number of patents in comparison with privately financed R&D.

Suggested Citation

  • Aiello, Francesco & Albanese, Giuseppe & Piselli, Paolo, 2019. "Good value for public money? The case of R&D policy," Journal of Policy Modeling, Elsevier, vol. 41(6), pages 1057-1076.
  • Handle: RePEc:eee:jpolmo:v:41:y:2019:i:6:p:1057-1076
    DOI: 10.1016/j.jpolmod.2019.02.006
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    References listed on IDEAS

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    Cited by:

    1. Aalto, Eero & Gustafsson, Robin, 2020. "Innovation Promotion Rationales and Impacts – A Review," ETLA Reports 99, The Research Institute of the Finnish Economy.

    More about this item

    Keywords

    Patents; R&D support; Policy evaluation; SMEs;

    JEL classification:

    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O38 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Government Policy
    • L1 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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