Endogenous Growth Under Multiple Uses of Data
Lin William Cong (1), Wenshi Wei (2), Danxia Xie (2), Longtian Zhang, (3) ((1) Cornell University, (2) Tsinghua University, (3) Central University, of Finance, Economics)

TL;DR
This paper models a dynamic data economy with endogenous growth driven by data sharing and usage across sectors, highlighting the impact of data nonrivalry, spillovers, and policy interventions on growth efficiency.
Contribution
It introduces a model where data's nonrivalry and knowledge spillovers influence growth, revealing market failures and policy solutions in a data-driven economy.
Findings
Innovation sector dominates data usage and growth contribution
Market power and privacy costs lead to data underutilization
Policy interventions can improve data market efficiency
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 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) data are dynamically nonrival and add to knowledge accumulation, and (ii) innovations "desensitize" raw data and enter production as knowledge, which allays consumers' privacy concerns. Data uses in both sectors interact to generate spillover of allocative distortion and exhibit an apparent substitutability due to labor's rivalry and complementarity with data. Consequently, growth rates under a social planner and a…
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Taxonomy
TopicsFiscal Policy and Economic Growth · Economic Growth and Productivity · Local Government Finance and Decentralization
