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As Science Evolves, How Can Science Policy?

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  • Benjamin F. Jones

Abstract

Getting science policy right is a core objective of government that bears on scientific advance, economic growth, health, and longevity. Yet the process of science is changing. As science advances and knowledge accumulates, ensuing generations of innovators spend longer in training and become more narrowly expert, shifting key innovations (i) later in the life cycle and (ii) from solo researchers toward teams. This paper summarizes the evidence that science has evolved - and continues to evolve - on both dimensions. The paper then considers science policy. The ongoing shift away from younger scholars and toward teamwork raises serious policy challenges. Central issues involve (a) maintaining incentives for entry into scientific careers as the training phase extends, (b) ensuring effective evaluation of ideas (including decisions on patent rights and research grants) as evaluator expertise narrows, and (c) providing appropriate effort incentives as scientists increasingly work in teams. Institutions such as government grant agencies, the patent office, the science education system, and the Nobel Prize come under a unified focus in this paper. In all cases, the question is how these institutions can change. As science evolves, science policy may become increasingly misaligned with science itself - unless science policy evolves in tandem.
(This abstract was borrowed from another version of this item.)
(This abstract was borrowed from another version of this item.)

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  • Benjamin F. Jones, 2011. "As Science Evolves, How Can Science Policy?," Innovation Policy and the Economy, University of Chicago Press, vol. 11(1), pages 103-131.
    • Handle: RePEc:ucp:ipolec:doi:10.1086/655820
    DOI: 10.1086/655820
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    1. Benjamin F. Jones, 2009. "The Burden of Knowledge and the "Death of the Renaissance Man": Is Innovation Getting Harder?," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 76(1), pages 283-317.
    2. Bruce A. Weinberg & David W. Galenson, 2019. "Creative Careers: The Life Cycles of Nobel Laureates in Economics," De Economist, Springer, vol. 167(3), pages 221-239, September.
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    4. Scott Stern, 2004. "Do Scientists Pay to Be Scientists?," Management Science, INFORMS, vol. 50(6), pages 835-853, June.
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    6. Jacob Mincer, 1958. "Investment in Human Capital and Personal Income Distribution," Journal of Political Economy, University of Chicago Press, vol. 66(4), pages 281-281.
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    Cited by:

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    2. Pierre Dubois & Jean-Charles Rochet & Jean-Marc Schlenker, 2014. "Productivity and mobility in academic research: evidence from mathematicians," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 1669-1701, March.
    3. Matthias Krapf, 2015. "Age and complementarity in scientific collaboration," Empirical Economics, Springer, vol. 49(2), pages 751-781, September.
    4. Jensen, Scott & Liu, Xiaozhong & Yu, Yingying & Milojevic, Staša, 2016. "Generation of topic evolution trees from heterogeneous bibliographic networks," Journal of Informetrics, Elsevier, vol. 10(2), pages 606-621.
    5. Fons-Rosen, Christian & Gaule, Patrick & Hrendash, Taras, 2023. "Why Has Science Become an Old Man's Game?," IZA Discussion Papers 16365, Institute of Labor Economics (IZA).
    6. Andrey GNIDCHENKO, 2011. "Defragmentation Of Economic Growth With A Focus On Diversification: Evidence From Russian Economy," Theoretical and Practical Research in the Economic Fields, ASERS Publishing, vol. 2(1), pages 44-80.
    7. Alexander Ugarov, 2023. "Peer Prediction for Peer Review: Designing a Marketplace for Ideas," Papers 2303.16855, arXiv.org.
    8. Amit Jain & Will Mitchell, 2022. "Specialization as a double‐edged sword: The relationship of scientist specialization with R&D productivity and impact following collaborator change," Strategic Management Journal, Wiley Blackwell, vol. 43(5), pages 986-1024, May.
    9. Annamaria Conti & Christopher C. Liu, 2014. "The (Changing) Knowledge Production Function: Evidence from the MIT Department of Biology for 1970-2000," NBER Working Papers 20037, National Bureau of Economic Research, Inc.
    10. Liang, Zhentao & Ba, Zhichao & Mao, Jin & Li, Gang, 2023. "Research complexity increases with scientists’ academic age: Evidence from library and information science," Journal of Informetrics, Elsevier, vol. 17(1).
    11. Benjamin Jones & E.J. Reedy & Bruce A. Weinberg, 2014. "Age and Scientific Genius," NBER Working Papers 19866, National Bureau of Economic Research, Inc.
    12. Margaret K. Kyle, 2019. "The Alignment of Innovation Policy and Social Welfare: Evidence from Pharmaceuticals," NBER Chapters, in: Innovation Policy and the Economy, Volume 20, pages 95-123, National Bureau of Economic Research, Inc.
    13. Marta Magdalena Roszkiewicz, 2014. "On The Influence Of Science Funding Policies On Business Sector R&D Activity," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 9(3), pages 9-27, September.
    14. Boh, Wai Fong & Evaristo, Roberto & Ouderkirk, Andrew, 2014. "Balancing breadth and depth of expertise for innovation: A 3M story," Research Policy, Elsevier, vol. 43(2), pages 349-366.
    15. Ba, Zhichao & Liang, Zhentao, 2021. "A novel approach to measuring science-technology linkage: From the perspective of knowledge network coupling," Journal of Informetrics, Elsevier, vol. 15(3).
    16. Kyle, Margaret K., 2022. "Incentives for pharmaceutical innovation: What’s working, what’s lacking," International Journal of Industrial Organization, Elsevier, vol. 84(C).
    17. Leonardo Costa Ribeiro & Márcia Siqueira Rapini & Leandro Alves Silva & Eduardo Motta Albuquerque, 2018. "Growth patterns of the network of international collaboration in science," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(1), pages 159-179, January.
    18. Ajay Agrawal & Avi Goldfarb & Florenta Teodoridis, 2013. "Does Knowledge Accumulation Increase the Returns to Collaboration?," NBER Working Papers 19694, National Bureau of Economic Research, Inc.
    19. Yin, Yian & Wang, Dashun, 2017. "The time dimension of science: Connecting the past to the future," Journal of Informetrics, Elsevier, vol. 11(2), pages 608-621.
    20. 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.
    21. Ginger Zhe Jin & Benjamin Jones & Susan Feng Lu & Brian Uzzi, 2013. "The Reverse Matthew Effect: Catastrophe and Consequence in Scientific Teams," NBER Working Papers 19489, National Bureau of Economic Research, Inc.
    22. Florenta Teodoridis, 2018. "Understanding Team Knowledge Production: The Interrelated Roles of Technology and Expertise," Management Science, INFORMS, vol. 64(8), pages 3625-3648, August.
    23. Annamaria Conti & Christopher C. Liu, 2014. "The (Changing) Knowledge Production Function: Evidence from the MIT Department of Biology for 1970–2000," NBER Chapters, in: The Changing Frontier: Rethinking Science and Innovation Policy, pages 49-74, National Bureau of Economic Research, Inc.

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    JEL classification:

    • I2 - Health, Education, and Welfare - - Education
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights
    • O43 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Institutions and Growth

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