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Estimating the causal effect of R&D subsidies in a pan-European program

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  • Hünermund, Paul
  • Czarnitzki, Dirk

Abstract

We investigate the effect of Europe's largest multilateral subsidy program for R&D-performing small and medium-sized enterprises. The program applied a specific budget allocation rule, referred to as Virtual Common Pot (VCP), which is designed to avoid cross-subsidization between participating countries. This rule creates exogenous variation in funding status and allows us to identify the causal effect of public R&D grants on firm growth. In addition, we compare the program's effect under the VCP rule with the standard situation of a Real Common Pot (RCP), in which program authorities allocate a single budget according to uniform project evaluation criteria. Our estimates suggest that R&D grants had no average effect on job creation and sales growth, but treatment effects were heterogeneous and positive for high-quality projects. Under an RCP the program would have created 53% more jobs and 48% higher sales.

Suggested Citation

  • Hünermund, Paul & Czarnitzki, Dirk, 2019. "Estimating the causal effect of R&D subsidies in a pan-European program," Research Policy, Elsevier, vol. 48(1), pages 115-124.
    • Handle: RePEc:eee:respol:v:48:y:2019:i:1:p:115-124
    DOI: 10.1016/j.respol.2018.08.001
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    1. Albert N. Link & John T. Scott, 2013. "Governments as entrepreneur: Evaluating the commercialization success of SBIR projects," Chapters, in: Public Support of Innovation in Entrepreneurial Firms, chapter 2, pages 25-38, Edward Elgar Publishing.
    2. Raffaello Bronzini & Eleonora Iachini, 2014. "Are Incentives for R&D Effective? Evidence from a Regression Discontinuity Approach," American Economic Journal: Economic Policy, American Economic Association, vol. 6(4), pages 100-134, November.
    3. Benavente, José Miguel & Crespi, Gustavo & Figal Garone, Lucas & Maffioli, Alessandro, 2012. "The impact of national research funds: A regression discontinuity approach to the Chilean FONDECYT," Research Policy, Elsevier, vol. 41(8), pages 1461-1475.
    4. José Ángel Zúñiga-Vicente & César Alonso-Borrego & Francisco J. Forcadell & José I. Galán, 2014. "Assessing The Effect Of Public Subsidies On Firm R&D Investment: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 28(1), pages 36-67, February.
    5. Nicholas Bloom & Mark Schankerman & John Van Reenen, 2013. "Identifying Technology Spillovers and Product Market Rivalry," Econometrica, Econometric Society, vol. 81(4), pages 1347-1393, July.
    6. Alberto Abadie & Guido W. Imbens, 2016. "Matching on the Estimated Propensity Score," Econometrica, Econometric Society, vol. 84, pages 781-807, March.
    7. Blanes, J. Vicente & Busom, Isabel, 2004. "Who participates in R&D subsidy programs?: The case of Spanish manufacturing firms," Research Policy, Elsevier, vol. 33(10), pages 1459-1476, December.
    8. Saul Lach, 2002. "Do R&D Subsidies Stimulate or Displace Private R&D? Evidence from Israel," Journal of Industrial Economics, Wiley Blackwell, vol. 50(4), pages 369-390, December.
    9. David, Paul A. & Hall, Bronwyn H. & Toole, Andrew A., 2000. "Is public R&D a complement or substitute for private R&D? A review of the econometric evidence," Research Policy, Elsevier, vol. 29(4-5), pages 497-529, April.
    10. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-475, March.
    11. Abadie, Alberto & Imbens, Guido W., 2011. "Bias-Corrected Matching Estimators for Average Treatment Effects," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 1-11.
    12. Katrin Hussinger, 2008. "R&D and subsidies at the firm level: an application of parametric and semiparametric two-step selection models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(6), pages 729-747.
    13. Aguiar, Luis & Gagnepain, Philippe, 2017. "European cooperative R&D and firm performance: Evidence based on funding differences in key actions," International Journal of Industrial Organization, Elsevier, vol. 53(C), pages 1-31.
    14. repec:zbw:bofrdp:2013_002 is not listed on IDEAS
    15. Markus Frölich & Michael Lechner, 2015. "Combining Matching and Nonparametric Instrumental Variable Estimation: Theory and An Application to the Evaluation of Active Labour Market Policies," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(5), pages 718-738, August.
    16. Guido W. Imbens, 2004. "Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 4-29, February.
    17. Almus, Matthias & Czarnitzki, Dirk, 2003. "The Effects of Public R&D Subsidies on Firms' Innovation Activities: The Case of Eastern Germany," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(2), pages 226-236, April.
    18. repec:bla:jindec:v:50:y:2002:i:4:p:369-90 is not listed on IDEAS
    19. Sabrina T. Howell, 2017. "Financing Innovation: Evidence from R&D Grants," American Economic Review, American Economic Association, vol. 107(4), pages 1136-1164, April.
    20. Patrick Royston & Douglas G. Altman, 1994. "Regression Using Fractional Polynomials of Continuous Covariates: Parsimonious Parametric Modelling," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 43(3), pages 429-453, September.
    21. Takalo, Tuomas & Tanayama, Tanja & Toivanen, Otto, 2013. "Market failures and the additionality effects of public support to private R&D: Theory and empirical implications," International Journal of Industrial Organization, Elsevier, vol. 31(5), pages 634-642.
    22. James J. Heckman & Hidehiko Ichimura & Petra Todd, 1998. "Matching As An Econometric Evaluation Estimator," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(2), pages 261-294.
    23. Elias Einiö, 2014. "R&D Subsidies and Company Performance: Evidence from Geographic Variation in Government Funding Based on the ERDF Population-Density Rule," The Review of Economics and Statistics, MIT Press, vol. 96(4), pages 710-728, October.
    24. Scott J. Wallsten, 2000. "The Effects of Government-Industry R&D Programs on Private R&D: The Case of the Small Business Innovation Research Program," RAND Journal of Economics, The RAND Corporation, vol. 31(1), pages 82-100, Spring.
    25. Alberto Abadie & Guido W. Imbens, 2006. "Large Sample Properties of Matching Estimators for Average Treatment Effects," Econometrica, Econometric Society, vol. 74(1), pages 235-267, January.
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    More about this item

    Keywords

    R&D policy; Causal inference; Virtual Common Pot; Joint Programming Initiative; European Research Area;
    All these keywords.

    JEL classification:

    • O38 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Government Policy
    • H25 - Public Economics - - Taxation, Subsidies, and Revenue - - - Business Taxes and Subsidies
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models

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