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Measuring the Causal Economic Effects of Scientific Research — Evidence from the Staggered Foundation of the SENAI Innovation Institutes in Brazil

Author

Listed:
  • Schubert, Torben

    (CIRCLE, Lund University)

  • Darold, Denilton

    (Fraunhofer Institute for Systems and Innovation Research ISI)

  • Will, Markus

    (Fraunhofer Institute for Production Systems and Design Technology IPK)

Abstract

How to estimate the economic returns of public science is a longstanding but equally challenging topic in quantitative science studies. In this paper, we exploit the staggered foundation of the SENAI Innovation Institutes (ISI) in Brazil since 2012, to estimate their effects on GDP using a difference-in-differences (DiD) approach. Building on historical and institutional insights from interviews on the foundation process, we unravel the conditions under which the parallel trends assumption is likely to hold. Our analysis reveals that these institutes significantly contribute to GDP per capita, with an average treatment effect of 985 BRL (approximately €160). Moreover, by relying on detailed project-level data, we were able to show that the effects come almost exclusively from genuine research projects and not from the provision of scientific services, such as metrology. Finally, tentative calculations suggest that the SENAI institutes may account for about 0.66% of Brazil's overall GDP, emphasising the importance of applied science in regional economic development and providing insights into effective collaboration between research and industry.

Suggested Citation

  • Schubert, Torben & Darold, Denilton & Will, Markus, 2024. "Measuring the Causal Economic Effects of Scientific Research — Evidence from the Staggered Foundation of the SENAI Innovation Institutes in Brazil," Papers in Innovation Studies 2024/14, Lund University, CIRCLE - Centre for Innovation Research.
    • Handle: RePEc:hhs:lucirc:2024_014
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    References listed on IDEAS

    as
    1. Benjamin F. Jones & Lawrence H. Summers, 2020. "A Calculation of the Social Returns to Innovation," NBER Chapters, in: Innovation and Public Policy, pages 13-59, National Bureau of Economic Research, Inc.
    2. Sant’Anna, Pedro H.C. & Zhao, Jun, 2020. "Doubly robust difference-in-differences estimators," Journal of Econometrics, Elsevier, vol. 219(1), pages 101-122.
    3. Dalia Ghanem & Pedro H. C. Sant'Anna & Kaspar Wüthrich, 2022. "Selection and Parallel Trends," CESifo Working Paper Series 9910, CESifo.
    4. Maietta, Ornella Wanda, 2015. "Determinants of university–firm R&D collaboration and its impact on innovation: A perspective from a low-tech industry," Research Policy, Elsevier, vol. 44(7), pages 1341-1359.
    5. Callaway, Brantly & Sant’Anna, Pedro H.C., 2021. "Difference-in-Differences with multiple time periods," Journal of Econometrics, Elsevier, vol. 225(2), pages 200-230.
    6. Maietta, Ornella Wanda, 2015. "Determinants of R&D University-Frim Collaboration and Its Impact on Innovation: a Perspective from the Italian Food and Drink Industry," 2015 Conference, August 9-14, 2015, Milan, Italy 225668, International Association of Agricultural Economists.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    SENAI ISI; public research; economic effects; GDP per capita;
    All these keywords.

    JEL classification:

    • O12 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Microeconomic Analyses of Economic Development
    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General
    • O38 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Government Policy

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