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The Elasticity of Science

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  • Kyle Myers

Abstract

This paper identifies the degree to which scientists are willing to change the direction of their work in exchange for resources. Data from the National Institutes of Health are used to estimate how scientists respond to targeted funding opportunities. Inducing a scientist to change their direction by a small amount—to work on marginally different topics—requires a substantial amount of funding in expectation. The switching costs of science are large. The productivity of grants is also estimated, and it appears the additional costs of targeted research may be more than offset by more productive scientists pursuing these grants.

Suggested Citation

  • Kyle Myers, 2020. "The Elasticity of Science," American Economic Journal: Applied Economics, American Economic Association, vol. 12(4), pages 103-134, October.
    • Handle: RePEc:aea:aejapp:v:12:y:2020:i:4:p:103-34
    DOI: 10.1257/app.20180518
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    References listed on IDEAS

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    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Chris Sampson’s journal round-up for 19th October 2020
      by Chris Sampson in The Academic Health Economists' Blog on 2020-10-19 11:00:05

    Citations

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    Cited by:

    1. Sabrina T. Howell & Jason Rathje & John Van Reenen & Jun Wong, 2021. "Opening up military innovation: causal effects of reforms to U.S. defense research," POID Working Papers 004, Centre for Economic Performance, LSE.
    2. Mancuso, Raffaele & Rossi-Lamastra, Cristina & Franzoni, Chiara, 2023. "Topic choice, gendered language, and the under-funding of female scholars in mission-oriented research," Research Policy, Elsevier, vol. 52(6).
    3. Agarwal, Ruchir & Gaule, Patrick, 2022. "What drives innovation? Lessons from COVID-19 R&D," Journal of Health Economics, Elsevier, vol. 82(C).
    4. Joshua Krieger & Ramana Nanda & Ian Hunt & Aimee Reynolds & Peter Tarsa, 2022. "Scoring and Funding Breakthrough Ideas: Evidence from a Global Pharmaceutical Company," Harvard Business School Working Papers 23-014, Harvard Business School, revised Nov 2023.
    5. Aslan, Yasemin & Yaqub, Ohid & Rotolo, Daniele & Sampat, Bhaven N., 2023. "Cross-category spillovers in medical research," SocArXiv hpmxd, Center for Open Science.
    6. Yeon Hak Kim & Aaron D. Levine & Eric J. Nehl & John P. Walsh, 2020. "A bibliometric measure of translational science," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2349-2382, December.
    7. Tania Babina & Alex Xi He & Sabrina T. Howell & Elisabeth Ruth Perlman & Joseph Staudt, 2020. "The Color of Money: Federal vs. Industry Funding of University Research," NBER Working Papers 28160, National Bureau of Economic Research, Inc.
    8. Kyle R. Myers & Lauren Lanahan, 2022. "Estimating Spillovers from Publicly Funded R&D: Evidence from the US Department of Energy," American Economic Review, American Economic Association, vol. 112(7), pages 2393-2423, July.
    9. Kyle R. Myers, 2022. "Some Tradeoffs of Competition in Grant Contests," Papers 2207.02379, arXiv.org, revised Mar 2024.
    10. Rebecca McKibbin & Bruce A. Weinberg, 2021. "Does Research Save Lives? The Local Spillovers of Biomedical Research on Mortality," NBER Working Papers 29420, National Bureau of Economic Research, Inc.
    11. Fry, Caroline V. & Lynham, John & Tran, Shannon, 2023. "Ranking researchers: Evidence from Indonesia," Research Policy, Elsevier, vol. 52(5).
    12. Yi Zhang & Xiaojing Cai & Caroline V. Fry & Mengjia Wu & Caroline S. Wagner, 2021. "Topic evolution, disruption and resilience in early COVID-19 research," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 4225-4253, May.
    13. Gaetan de Rassenfosse & Kyle Higham & Orion Penner, 2022. "Scientific rewards for biomedical specialization are large and persistent," Working Papers 19, Chair of Science, Technology, and Innovation Policy.
    14. de Bettignies, Jean-Etienne & Ries, John, 2023. "When less is more: Information and the financing of innovation," Journal of Economic Behavior & Organization, Elsevier, vol. 214(C), pages 346-369.
    15. Jeffrey L. Furman & Florenta Teodoridis, 2020. "Automation, Research Technology, and Researchers’ Trajectories: Evidence from Computer Science and Electrical Engineering," Organization Science, INFORMS, vol. 31(2), pages 330-354, March.
    16. Kyle Myers & Wei Yang Tham, 2023. "Money, Time, and Grant Design," Papers 2312.06479, arXiv.org.
    17. Blandinieres, Florence & Pellens, Maikel, 2021. "Scientist's industry engagement and the research agenda: Evidence from Germany," ZEW Discussion Papers 21-001, ZEW - Leibniz Centre for European Economic Research.

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    More about this item

    JEL classification:

    • H51 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Health
    • I10 - Health, Education, and Welfare - - Health - - - General
    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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