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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.

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  • 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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    Cited by:

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    6. Czarnitzki, Dirk & Hünermund, Paul & Moshgbar, Nima, 2020. "Public Procurement of Innovation: Evidence from a German Legislative Reform," International Journal of Industrial Organization, Elsevier, vol. 71(C).
    7. Rainer Widmann, 2023. "The Behavioral Additionality of Government Research Grants," Rationality and Competition Discussion Paper Series 417, CRC TRR 190 Rationality and Competition.
    8. Giebel, Marek & Kraft, Kornelius, 2021. "Subsidies and innovation in the recent financial crisis," ZEW Discussion Papers 21-097, ZEW - Leibniz Centre for European Economic Research.
    9. Kristof Van Criekingen & Mark Freel & Dirk Czarnitzki, 2021. "Open innovation deficiency: Evidence on project abandonment and delay," Working Papers of Department of Management, Strategy and Innovation, Leuven 668283, KU Leuven, Faculty of Economics and Business (FEB), Department of Management, Strategy and Innovation, Leuven.
    10. Bettina Becker, 2020. "The Impact of Innovation Policy on Firm Innovation and Performance: A Review of Recent Research Developments," ifo DICE Report, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 17(04), pages 10-15, January.
    11. Chandranath Amarasekara & Bernard Njindan Iyke & Paresh Kumar Narayan, 2022. "The role of R&D and economic policy uncertainty in Sri Lanka’s economic growth," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-19, December.
    12. Lenihahn, Helena & Mulligan, Kevin & Perez-Alaniz, Mauricio & Rammer, Christian, 2023. "Serving the right menu of R&D policy instruments to firms: An analysis of policy mix sequencing," ZEW Discussion Papers 23-009, ZEW - Leibniz Centre for European Economic Research.
    13. Kwangsoo Shin & Minkyung Choy & Chul Lee & Gunno Park, 2019. "Government R&D Subsidy and Additionality of Biotechnology Firms: The Case of the South Korean Biotechnology Industry," Sustainability, MDPI, vol. 11(6), pages 1-22, March.
    14. Jan Schnellenbach & Christian Schubert, 2019. "A note on the behavioral political economy of innovation policy," Journal of Evolutionary Economics, Springer, vol. 29(5), pages 1399-1414, November.
    15. Maoyan She & Die Hu & Yuandi Wang & Li Li, 2023. "How do top management team characteristics affect government R&D subsidy grants? Evidence from an information economics perspective," Asian Business & Management, Palgrave Macmillan, vol. 22(1), pages 330-353, February.
    16. Mulier, Klaas & Samarin, Ilia, 2021. "Sector heterogeneity and dynamic effects of innovation subsidies: Evidence from Horizon 2020," Research Policy, Elsevier, vol. 50(10).
    17. Arash Ketabforoush Badri & Parsa Ketabforoush Badri & Mostafa Cham, 2019. "R&D Spending and Economic Growth in Selected OECD Countries," International Journal of Applied Economics, Finance and Accounting, Online Academic Press, vol. 5(2), pages 48-54.
    18. Aalto, Eero & Gustafsson, Robin, 2020. "Innovation Promotion Rationales and Impacts – A Review," ETLA Reports 99, The Research Institute of the Finnish Economy.
    19. Aurélien Quignon & Nadine Levratto, 2021. "Innovation Performance and the Signal Effect: Evidence from a European Program," EconomiX Working Papers 2021-34, University of Paris Nanterre, EconomiX.
    20. Paul Hünermund & Dirk Czarnitzki, 2020. "Innovation Policy and Causality," ifo DICE Report, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 17(04), pages 03-06, January.
    21. Pietro Santoleri & Andrea Mina & Alberto Di Minin & Irene Martelli, 2020. "The causal effects of R&D grants: evidence from a regression discontinuity," LEM Papers Series 2020/18, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    22. Kyoungmi Lee & Sunglok Choi & Jae-Suk Yang, 2021. "Can expensive research equipment boost research and development performances?," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(9), pages 7715-7742, September.
    23. Hyytinen, Ari, 2021. "Shared problem solving and design thinking in entrepreneurship research," Journal of Business Venturing Insights, Elsevier, vol. 16(C).

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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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