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Data-driven innovation and growth

Author

Listed:
  • Li, Hao
  • Wang, Gaowang
  • Yang, Liyang

Abstract

We develop an endogenous growth model where data drives innovation. In this model, big data fosters quality improvements by influencing the likelihood and magnitude of successful quality-enhancing innovations. It also promotes variety innovation through the efficient allocation of labor as a fixed cost, ultimately driving long-run economic growth. The social planner reduces the welfare costs associated with monopoly production and internalizes the externalities present in decentralized economies. As a result, the optimal growth rate exceeds the equilibrium growth rates under two data property rights regimes. Data property rights play a crucial role in determining long-run growth and steady-state welfare, which depend largely on two key model parameters: the weight for privacy and the frequency of creative destruction. This model also explores the interactions between quality innovation and variety innovation.

Suggested Citation

  • Li, Hao & Wang, Gaowang & Yang, Liyang, 2024. "Data-driven innovation and growth," MPRA Paper 122388, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:122388
    as

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    References listed on IDEAS

    as
    1. Cong, Lin William & Wei, Wenshi & Xie, Danxia & Zhang, Longtian, 2022. "Endogenous growth under multiple uses of data," Journal of Economic Dynamics and Control, Elsevier, vol. 141(C).
    2. Lin William Cong & Danxia Xie & Longtian Zhang, 2021. "Knowledge Accumulation, Privacy, and Growth in a Data Economy," Management Science, INFORMS, vol. 67(10), pages 6480-6492, October.
    3. Peretto, Pietro F, 1998. "Technological Change and Population Growth," Journal of Economic Growth, Springer, vol. 3(4), pages 283-311, December.
    4. Thompson, Peter & Waldo, Doug, 1994. "Growth and trustified capitalism," Journal of Monetary Economics, Elsevier, vol. 34(3), pages 445-462, December.
    5. Charles I. Jones & Christopher Tonetti, 2020. "Nonrivalry and the Economics of Data," American Economic Review, American Economic Association, vol. 110(9), pages 2819-2858, September.
    6. Avinash K. Dixit & Robert S. Pindyck, 1994. "Investment under Uncertainty," Economics Books, Princeton University Press, edition 1, number 5474, December.
    7. Alwyn Young, 1998. "Growth without Scale Effects," Journal of Political Economy, University of Chicago Press, vol. 106(1), pages 41-63, February.
    8. Merton, Robert C., 1971. "Optimum consumption and portfolio rules in a continuous-time model," Journal of Economic Theory, Elsevier, vol. 3(4), pages 373-413, December.
    9. Romer, Paul M, 1990. "Endogenous Technological Change," Journal of Political Economy, University of Chicago Press, vol. 98(5), pages 71-102, October.
    10. Segerstrom, Paul S, 1998. "Endogenous Growth without Scale Effects," American Economic Review, American Economic Association, vol. 88(5), pages 1290-1310, December.
    11. Jones, Charles I, 1995. "R&D-Based Models of Economic Growth," Journal of Political Economy, University of Chicago Press, vol. 103(4), pages 759-784, August.
    12. Iain M. Cockburn & Rebecca Henderson & Scott Stern, 2018. "The Impact of Artificial Intelligence on Innovation," NBER Working Papers 24449, National Bureau of Economic Research, Inc.
    13. Peter Howitt, 1999. "Steady Endogenous Growth with Population and R & D Inputs Growing," Journal of Political Economy, University of Chicago Press, vol. 107(4), pages 715-730, August.
    14. Ajay Agrawal & John McHale & Alexander Oettl, 2018. "Finding Needles in Haystacks: Artificial Intelligence and Recombinant Growth," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 149-174, National Bureau of Economic Research, Inc.
    15. Dinopoulos, Elias & Thompson, Peter, 1998. "Schumpeterian Growth without Scale Effects," Journal of Economic Growth, Springer, vol. 3(4), pages 313-335, December.
    16. Iain M. Cockburn & Rebecca Henderson & Scott Stern, 2018. "The Impact of Artificial Intelligence on Innovation: An Exploratory Analysis," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 115-146, National Bureau of Economic Research, Inc.
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    Keywords

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    JEL classification:

    • E1 - Macroeconomics and Monetary Economics - - General Aggregative Models
    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights
    • O41 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - One, Two, and Multisector Growth Models

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