Too Much Data: Prices and Inefficiencies in Data Markets

• 成果类型: Article
• 署名作者: Acemoglu, Daron; Makhdoumi, Ali; Malekian, Azarakhsh; Ozdaglar, Asu
• 署名单位: Massachusetts Institute of Technology (MIT); Duke University; University of Toronto; Massachusetts Institute of Technology (MIT)
• 刊物名称: AMERICAN ECONOMIC JOURNAL-MICROECONOMICS
• ISSN/ISSBN: 1945-7669
• DOI: 10.1257/mic.20200200
• 发表日期: 2022
• 页码: 218-256
• 关键词: Information disclosure; big data; privacy; ECONOMICS; auctions

摘要

When a user shares her data with online platforms, she reveals infor-mation about others. In such a setting, externalities depress the price of data because once a user's information is leaked by others, she has less reason to protect her data and privacy. These depressed prices lead to excessive data sharing. We characterize conditions under which shutting down data markets improves welfare. Platform competition does not redress the problem of excessively low data prices and too much data sharing and may further reduce welfare. We propose a scheme based on mediated data sharing that improves efficiency.