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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
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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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