【 Webinar Series 】The Supply and Demand for Data Privacy: Evidence from Mobile Apps
【 Webinar Series 】The Supply and Demand for Data Privacy: Evidence from Mobile Apps

11 Jan 2023 (Wed)
10:00 am - 11:10 am (Hong Kong Time UTC+8)
Huan TANG, London School of Economics and Political Science

【 Webinar Series - Innovation, Productivity, and Challenges in the Digital Era: Asia and Beyond 】

The Supply and Demand for Data Privacy: Evidence from Mobile Apps



Date: 11 Jan 2023 (Wed)

Time: 10am – 11:10am (Hong Kong Time, UTC+8)

Abstract: This paper investigates how consumers and investors react to the standardized disclosure of data privacy practices. Since December 2020, Apple has required all apps to disclose their data collection practices by filling out privacy "nutrition" labels that are standardized and easy-to-read. The authors web-scrape these privacy labels and first document several stylized facts regarding the supply of privacy. Second, augmenting privacy labels with weekly app downloads and revenues, the authors examine how this disclosure affects consumer behavior. The authors exploit the staggered release of privacy labels and use the nonexposed Android version of each app to construct the counterfactual. After privacy label release, an average iOS app experiences a 14% (15%) drop in weekly downloads (revenues) when compared to its Android counterpart, with an even stronger effect for more privacy-invasive and substitutable apps. Consumers in the US, UK, and France respond more negatively, suggesting that they are most averse to data collection. Moreover, the authors observe adverse stock market reactions, especially among firms that harvest more data, corroborating the findings on product markets. Their findings highlight data as a key asset for firms in the digital era.




Assistant Professor of Finance, Department of Finance, London School of Economics and Political Science



Bo BIAN, Assistant Professor in Finance, UBC Sauder School of Business, University of British Columbia

Xinchen MA, PhD candidate in Finance, Department of Finance, London School of Economics & Political Science



Ginger Zhe JIN, Professor of Economics, Department of Economics, University of Maryland



Event Website: https://abfer.org/events/abfer-events/webinar-series/324:ws-ipc-20230111



About the Webinar

Artificial Intelligence (AI), Big Data, multilevel neural nets, the Internet of Things (IoT) and other digital technologies are transforming the world. They are strengthening innovation and productivity and innovation by rendering the future more predictable and reshaping individual, business, social, and government behavior. Asia leads the world in some of these endeavors, e.g., digital platforms. The OECD lists 40% of big new digital technologies as Asian. Almost half of global digital platform business-to-consumer revenues are Asian, versus only 22% from the U.S. and 12% from the Eurozone. Profound new policy challenges arising, in consequence, include: shifting skills demanded in labor markets and “digital divide” inequality, (ii) AI expanding financial inclusion or encoding inequality, expanding or obscuring accountability, increasing transparency or obscuring amoral decision-making, and (iii) digital privacy, unsanctionable on-line libel, misinformation, manipulation, and propaganda. The ABFER, therefore, plans a monthly e-seminar series spotlighting important new research, particularly the Asia-pacific related, into these issues and providing “state-of-the-art” overviews by prominent scholars. We hope policy makers and practitioners will find the e-seminars helpful and will alert researchers to issues needing attention.



Collaborating Organizers

ABFER, The Chinese University of Hong Kong-Zhejiang University Joint Research Center for Digital Economy, The Chinese University of Hong Kong (CUHK) Department of Economics and Center for Internet Development and Governance, Fanhai International School of Finance (FISF), Fudan University, National Tsing Hua University College of Technology Management and Tsinghua University School of Economics and Management (Tsinghua SEM)