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A Model of the Data Economy

Author

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  • Maryam Farboodi
  • Laura Veldkamp

Abstract

In a data economy, transactions of goods and services generate information, which is stored, traded and depreciates. How are the economics of this economy different from traditional production or innovation economies? How do these differences matter for measurement of GDP, firm values, depreciation rates, welfare and externalities? Despite incorporating active experimentation and data as an intangible asset, we devise a tractable recursive representation. Because the resulting model maps to many observable macro and finance measures, it can be calibrated and estimated like its old-economy DSGE counterpart. The model also delivers insights: It rationalizes why apps are often “free,” why firm size is diverging and why even non-digital economic activity might be greater than GDP suggests.

Suggested Citation

  • Maryam Farboodi & Laura Veldkamp, 2021. "A Model of the Data Economy," NBER Working Papers 28427, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:28427
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    Cited by:

    1. Toni Ahner & Katrin Assenmacher & Peter Hoffmann & Agnese Leonello & Cyril Monnet & Davide Porcellacchia, 2024. "The Economics of Central Bank Digital Currency," International Journal of Central Banking, International Journal of Central Banking, vol. 20(4), pages 221-274, October.
    2. Koski, Heli & Fornaro, Paolo, 2024. "Digitalization and Resilience: Data Assets and Firm Productivity Growth During the COVID-19 Pandemic," ETLA Working Papers 113, The Research Institute of the Finnish Economy.
    3. 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).
    4. Wang, Zhen & Tang, Pei, 2024. "Substantive digital innovation or symbolic digital innovation: Which type of digital innovation is more conducive to corporate ESG performance?," International Review of Economics & Finance, Elsevier, vol. 93(PB), pages 1212-1228.
    5. Bianchi, Milo & Bouvard, Matthieu & Gomes, Renato & Rhodes, Andrew & Shreeti, Vatsala, 2023. "Mobile payments and interoperability: Insights from the academic literature," Information Economics and Policy, Elsevier, vol. 65(C).
    6. Bessen, James & Impink, Stephen Michael & Reichensperger, Lydia & Seamans, Robert, 2022. "The role of data for AI startup growth," Research Policy, Elsevier, vol. 51(5).
    7. Ehsan Valavi & Joel Hestness & Newsha Ardalani & Marco Iansiti, 2022. "Time and the Value of Data," Papers 2203.09118, arXiv.org.
    8. Liu, Rui & Zheng, Linhao & Chen, Zheang & Cheng, Mengyao & Ren, Yuzhuo, 2024. "Digitalization through supply chains: Evidence from the customer concentration of Chinese listed companies," Economic Modelling, Elsevier, vol. 134(C).
    9. Kaiwen Hou, 2023. "Adaptive Bayesian Learning with Action and State-Dependent Signal Variance," Papers 2311.12878, arXiv.org, revised Nov 2023.
    10. Agrawal, Ajay & McHale, John & Oettl, Alexander, 2024. "Artificial intelligence and scientific discovery: a model of prioritized search," Research Policy, Elsevier, vol. 53(5).
    11. Romeo Victor Ionescu & Monica Laura Zlati & Valentin Marian Antohi & Florina Oana Virlanuta & Silvius Stanciu, 2022. "Quantifying the Digitalisation Impact on the EU Economy. Case Study: Germany and Sweden vs. Romania and Greece," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 24(59), pages 1-61.

    More about this item

    JEL classification:

    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights
    • O4 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity

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