Topic: The Boundary of Open Data: Implications for Financial Market and Real Efficiency
Time: 10:00 AM —11:30 AM, April 24, 2025
Location: Room A618, New Main Building
Guest: Qiu Zhigang, Professor of the Department of Money and Finance, School of Finance, Renmin University of China
Abstract:
We analyze the optimal boundary for open data in an economy where financial and real-sector participants access both open and private data. The distinctive features of open access and non-rivalrous usage of open data enable its dual roles as a public information source and innovation input, yet raise privacy concerns. Our model reveals a novel trade-off: while enhanced private data precision substitutes for open data's information source role, its ability to amplify innovation benefits (via improved investment efficiency) establishes a crucial complementary relationship. This induces a crowding-in impact on the optimal open data boundary under low uncertainty, but crowding-out under high uncertainty. The innovation role further generates non-monotonic scaling effects, which initially reduces productivity at small scales but increases at larger scales, yielding complex, non-linear impacts on market and real efficiency. These findings highlight critical policy trade-offs in balancing innovation, market efficiency, and privacy in digital age.
