Data-driven innovation and growth

Hao Li, Gaowang Wang and Liyang Yang

MPRA Paper from University Library of Munich, Germany

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.

Keywords: data as innovation; endogenous growth; data property rights; interactions between quality innovation and variety innovation (search for similar items in EconPapers)
JEL-codes: E1 O3 O41 (search for similar items in EconPapers)
Date: 2024-10-13
New Economics Papers: this item is included in nep-cse and nep-gro
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