Endogenous Growth Under Multiple Uses of Data

55 Pages Posted: 27 Aug 2021 Last revised: 8 Aug 2022

See all articles by Lin William Cong

Lin William Cong

Cornell University - Samuel Curtis Johnson Graduate School of Management; National Bureau of Economic Research (NBER)

Wenshi Wei

Tsinghua University - Institute of Economics

Danxia Xie

Tsinghua University - Institute of Economics

Longtian Zhang

Central University of Finance and Economics

Date Written: August 25, 2021

Abstract

We model a dynamic data economy with fully endogenous growth where agents generate data from consumption and share them with innovation and production firms. Different from other productive factors such as labor or capital, data are nonrival not only among firms but also in their uses across sectors, which affect both the level and growth of economic outputs. Despite the vertical nonrivalry, the innovation sector dominates the production sector in data usage and contribution to growth because (i) innovations are cumulative and benefit from data that are durable and dynamically nonrival; and (ii) innovations "desensitize" raw data into knowledge when entering production, which allays consumers' privacy concerns. Data uses in both sectors interact in generating allocative distortions and an apparent substitutability due to labor's rival usage across sectors and complementarity with data. Consequently, growth rates diverge under a social planner and a decentralized equilibrium, which is novel in the literature and has policy implications. Specifically, consumers' failure to fully internalize knowledge spillover while bearing privacy costs, combined with firms' market power, leads to an underpricing of data and inefficient data supply, causing underemployment in the innovation sector and suboptimal long-run growth. Improving data usage efficiency is ineffective in mitigating the underutilization of data, but interventions in the data market and direct subsidies hold promises.

Keywords: Big Data, Endogenous Growth, Innovation, Nonrivalry, Privacy

JEL Classification: O4

Suggested Citation

Cong, Lin and Wei, Wenshi and Xie, Danxia and Zhang, Longtian, Endogenous Growth Under Multiple Uses of Data (August 25, 2021). Journal of Economic Dynamics and Control, 2022, Available at SSRN: https://ssrn.com/abstract=3911264 or http://dx.doi.org/10.2139/ssrn.3911264

Lin Cong (Contact Author)

Cornell University - Samuel Curtis Johnson Graduate School of Management ( email )

Ithaca, NY 14853
United States

HOME PAGE: http://www.linwilliamcong.com/

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Wenshi Wei

Tsinghua University - Institute of Economics ( email )

MingZhai Building
Beijing, 100084
China

Danxia Xie

Tsinghua University - Institute of Economics ( email )

MingZhai Building
Beijing, 100084
China

HOME PAGE: http://danxiaxie.com

Longtian Zhang

Central University of Finance and Economics ( email )

Shahe Higher Education Park
Changping District
Beijing, Beijing 102206
China

HOME PAGE: http://longtianzhang.com

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