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Data and the Aggregate Economy

Author

Listed:
  • Laura Veldkamp
  • Cindy Chung

Abstract

Recent data technology innovations, such as artificial intelligence and machine learning, have transformed the production of knowledge and increased the importance of data. This review explores how data—digitized information—has been modeled within classic macroeconomic frameworks. It compares the economics of data to other concepts such as ideas, patents, and learning-by-doing. This paper also shows potential ways to model applications for data, including innovation, process optimization, and matching. Because this research area is nascent, much of the article is devoted to open questions and directions for future data economy research.

Suggested Citation

  • Laura Veldkamp & Cindy Chung, 2024. "Data and the Aggregate Economy," Journal of Economic Literature, American Economic Association, vol. 62(2), pages 458-484, June.
    • Handle: RePEc:aea:jeclit:v:62:y:2024:i:2:p:458-84
    DOI: 10.1257/jel.20221580
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    Citations

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    Cited by:

    1. Zhang, Xiaoru & Jiang, Wei & Wu, Chuanqing, 2026. "Does data factor marketisation effect labour income share? Evidence from Chinese A-share listed companies," Journal of Business Research, Elsevier, vol. 206(C).
    2. Huang, Lingyu & Zhang, Yuxuan & Xian, Rui & Chen, Xinxian, 2026. "Data asset disclosure and corporate innovation: Evidence from China," International Review of Financial Analysis, Elsevier, vol. 109(C).
    3. 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).
    4. Alexandre Kohlhas & Vladimir Asriyan, 2025. "The Macroeconomics of Data: Scale, Product Choice, and Pricing in the Information Age," Economics Series Working Papers 1073, University of Oxford, Department of Economics.
    5. Yang, Jiaquan & Zhu, Yihui & Cheng, Yingfei, 2026. "Welfare effects in the dominant market with price discrimination under differential information protection policies," International Journal of Production Economics, Elsevier, vol. 293(C).
    6. Wu, Desheng & Xie, Yu, 2026. "Government data accessibility and firm dynamics: Encouraging entrepreneurship or accelerating exit?," World Development, Elsevier, vol. 200(C).
    7. Jun Qian & Xiao Sun & Yueting Chai & Xiao Xue, 2025. "Evolutionary Dynamics in Data Trading with Risk Compensation," Mathematics, MDPI, vol. 13(5), pages 1-18, February.
    8. Chaminda Rajeev Samarage & A. Abigail Payne, 2025. "The Melbourne Institute Data Lab, a Secure Access Environment for Informing Future Social and Economic Policy," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 58(3), pages 259-271, September.
    9. Nguyen, Manh-Hung, 2026. "Epistemic Capital and Two-Trap Growth in the AI Era," TSE Working Papers 26-1722, Toulouse School of Economics (TSE).
    10. Ge, Shilong & Tu, Zhenyu & Chen, Yalin & Chong, Heap-Yih, 2025. "Data driven-sustainability: The impact of data trading platforms on corporate ESG performance," International Review of Financial Analysis, Elsevier, vol. 105(C).
    11. Yang, Chen & Hu, Zongyi, 2026. "Data element resource supply and enterprise green innovation quality," International Review of Financial Analysis, Elsevier, vol. 109(C).
    12. Adams, Jonathan J. & Fang, Min & Liu, Zheng & Wang, Yajie, 2026. "The rise of AI pricing: Trends, driving forces, and implications for firm performance," Journal of Monetary Economics, Elsevier, vol. 157(C).
    13. Zhi Chen & Jussi Keppo, 2025. "R&D Data Sharing in New Product Development," Manufacturing & Service Operations Management, INFORMS, vol. 27(4), pages 1275-1294, July.
    14. Wu, Desheng & Xie, Yu, 2024. "Unveiling the impact of public data access on collaborative reduction of pollutants and carbon emissions: Evidence from open government data policy," Energy Economics, Elsevier, vol. 138(C).
    15. Zhang, Wenkang & Wu, Jing, 2025. "Endogenous growth and data heterogeneity in data economics," Finance Research Letters, Elsevier, vol. 78(C).

    More about this item

    JEL classification:

    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
    • D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • E23 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Production
    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • J23 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Demand

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