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Endogenous growth and data heterogeneity in data economics

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  • Zhang, Wenkang
  • Wu, Jing

Abstract

Innovations in the Internet of Things (IoT) and Industrial IoT makes the data generation subject no longer limited to consumers, but more from the product life cycle. By integrating demand-driven consumption data and innovation-driven production data, this paper constructs an endogenous growth model with data heterogeneity. It reveals that the synergy of heterogeneous data accelerates output growth, improves innovation and higher welfare. Production data alleviate inefficiencies in data resource allocation, reduce privacy concerns, and mitigate structural unemployment. Consumption data can cause a multiplier effect on production. The model extends the theoretical boundaries of data economics and provide significant policy implications.

Suggested Citation

  • Zhang, Wenkang & Wu, Jing, 2025. "Endogenous growth and data heterogeneity in data economics," Finance Research Letters, Elsevier, vol. 78(C).
    • Handle: RePEc:eee:finlet:v:78:y:2025:i:c:s1544612325004489
    DOI: 10.1016/j.frl.2025.107185
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    References listed on IDEAS

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    Cited by:

    1. Chu, Zhaopeng & Chen, Xin & Yang, Jun, 2025. "Impact of data factor and data integration on economic development: Empirical insights from China," Telecommunications Policy, Elsevier, vol. 49(8).

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