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The impact of the French policy mix on business R&D: How geography matters

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  • Montmartin, Benjamin
  • Herrera, Marcos
  • Massard, Nadine

Abstract

Based on a spatial extension of an R&D investment model, this paper measures the macroeconomic impact of the French R&D policy mix on business R&D using regional data. Our measure takes into account not only the direct effect of policies but also indirect effects generated by the existence of spatial interaction between regions. Using a unique database containing information on the levels of various R&D policy instruments received by firms in French NUTS3 regions over the period 2001–2011, our estimates of a spatial Durbin model with structural breaks and fixed effects reveal the existence of a negative spatial dependence among R&D investments in regions. In this context, while a-spatial estimates would conclude that all instruments have a crowding-in effect, we show that national subsidies are the only instrument that is able to generate significant crowding-in effects. On the contrary, it seems that the design, size and spatial allocation of funds from the other instruments (tax credits, local subsidies, European subsidies) lead them to act (in the French context) as beggar-thy-neighbor policies.

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  • Montmartin, Benjamin & Herrera, Marcos & Massard, Nadine, 2018. "The impact of the French policy mix on business R&D: How geography matters," Research Policy, Elsevier, vol. 47(10), pages 2010-2027.
    • Handle: RePEc:eee:respol:v:47:y:2018:i:10:p:2010-2027
    DOI: 10.1016/j.respol.2018.07.009
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    Cited by:

    1. Thomas H. W. Ziesemer, 2021. "The Effects of R&D Subsidies and Publicly Performed R&D on Business R&D: A Survey," Hacienda Pública Española / Review of Public Economics, IEF, vol. 236(1), pages 171-205, March.
    2. Caloffi, Annalisa & Freo, Marzia & Ghinoi, Stefano & Mariani, Marco & Rossi, Federica, 2022. "Assessing the effects of a deliberate policy mix: The case of technology and innovation advisory services and innovation vouchers," Research Policy, Elsevier, vol. 51(6).
    3. Shoulin Pang & Shiting Dou & Huan Li, 2020. "Synergy effect of science and technology policies on innovation: Evidence from China," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-19, October.
    4. Pierre Courtioux & François Métivier & Antoine Rebérioux, 2021. "The private return of R&D tax credit," Documents de travail du Centre d'Economie de la Sorbonne 21006, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    5. Paige Clayton & Maryann Feldman & Benjamin Montmartin, 2019. "Funding Emerging Ecosystems," GREDEG Working Papers 2019-25, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France.
    6. Michel Dumont, 2019. "Working Paper 04-19 - Tax incentives for business R&D in Belgium - Third evaluation," Working Papers 1904, Federal Planning Bureau, Belgium.

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    More about this item

    Keywords

    Policy mix evaluation; R&D investment; Spatial panel; French NUTS3 regions;
    All these keywords.

    JEL classification:

    • H25 - Public Economics - - Taxation, Subsidies, and Revenue - - - Business Taxes and Subsidies
    • 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
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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