The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.
Knowledge Accumulation, Privacy, and Growth in a Data Economy
Open accessAbstract
We build an endogenous growth model with consumer-generated data as a new key factor for knowledge accumulation. Consumers balance between providing data for profit and potential privacy infringement. Intermediate good producers use data to innovate and contribute to the final good production, which fuels economic growth. Data are dynamically nonrival with flexible ownership while their production is endogenous and policy-dependent. Although a decentralized economy can grow at the same rate (but are at different levels) as the social optimum on the Balanced Growth Path, the R&D sector underemploys labor and overuses data—an inefficiency mitigated by subsidizing innovators instead of direct data regulation. As a data economy emerges and matures, consumers’ data provision endogenously declines after a transitional acceleration, allaying long-run privacy concerns but portending initial growth traps that call for interventions. This paper was accepted by Kay Giesecke, finance.
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Cites
Endogenous Technological Change
Romer, P. M. (1990) · Journal of Political Economy · doi:10.1086/261725 · Cited by 17,711
Endogenous Technological Change
Romer, P. (1989) · National Bureau of Economic Research · doi:10.3386/w3210 · Cited by 13,303
(2011) · Cited by 5,203
The Environment and Directed Technical Change
Acemoglu, D., Aghion, P., Bursztyn, L., & Hemous, D. (2012) · American Economic Review · doi:10.1257/aer.102.1.131 · Cited by 3,734
R & D-Based Models of Economic Growth
Jones, C. I. (1995) · Journal of Political Economy · doi:10.1086/262002 · Cited by 3,059
“The Global Decline of the Labor Share”
Karabarbounis, L., & Neiman, B. (2014) · The Quarterly Journal of Economics · doi:10.1093/qje/qjt032 · Cited by 2,152
The Private and Social Value of Information and the Reward to Inventive Activity
HIRSHLEIFER, J. (1978) · Uncertainty in Economics · doi:10.1016/b978-0-12-214850-7.50038-3 · Cited by 1,571
Limited Asset Market Participation and the Elasticity of Intertemporal Substitution
Vissing‐Jørgensen, A. (2002) · Journal of Political Economy · doi:10.1086/340782 · Cited by 1,011
Stokey, N. L. (1998) · International Economic Review · doi:10.2307/2527228 · Cited by 1,007
Nonrivalry and the Economics of Data
Jones, C. I., & Tonetti, C. (2020) · American Economic Review · doi:10.1257/aer.20191330 · Cited by 905
Cited by
Ma, D., & Zhu, Q. (2022) · Journal of Business Research · doi:10.1016/j.jbusres.2022.03.041 · Cited by 853
Metadata
- Authors
- Cong, L. W., Xie, D., & Zhang, L.
- Venue
- Management Science
- Published
- 2021-10
- Volume
- 67
- Issue
- 10
- Pages
- 6480-6492
- ISSN
- 0025-1909 (ISSN-L)
- 1526-5501
- OpenAlex
- W3193815270
- Cited by
- 267
- References
- 27
- FWCI
- 19.76
- Type
- journal article
- Language
- en
- Open access
- green
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