Competitive Implications of Data and Information Sharing
Paper Session
Sunday, Jan. 5, 2025 8:00 AM - 10:00 AM (PST)
- Chair: Alessandro Bonatti, Massachusetts Institute of Technology
Competitive Markets for Personal Data
Abstract
We study competitive data markets in which consumers own their personal dataand can trade it with intermediaries, such as e-commerce platforms. Intermediaries
use this data to provide services to the consumers, such as targeted offers from
third-party merchants. Our main results identify a novel inefficiency, resulting in
equilibrium data allocations that fail to maximize welfare. This inefficiency hinges
on the role that intermediaries play as information gatekeepers, a hallmark of the
digital economy. We provide three solutions to this market failure: establishing
data unions, which manage consumers’ data on their behalf; taxing the trade of
data; and letting the price of data depend on its intended use.
Platform Competition and Information Sharing
Abstract
Digital platforms, empowered by artificial intelligence algorithms, facilitate efficient inter-actions between consumers and merchants that allow the collection of profiling information
which drives innovation and welfare. Private incentives, however, lead to information asym-
metries resulting in market failures. This paper develops a product differentiation model of
competition between two platforms to study private and social incentives to share information.
Sharing information can be welfare-enhancing because it solves the data bottleneck market
failure. Our findings imply that there is scope for the introduction of a mandatory information
sharing mechanism from big platforms to their competitors that help the latter improve their
network value proposition and become more competitive in the market. The price of information in this sharing mechanism matters. We show that price regulation over information
sharing like the one applied in the EU jurisdiction increases the incentives of big platforms to
collect and analyze more data. It has ambiguous effects on their competitors that depend on
the exact relationship between information and network value.
Consumer-Optimal Segmentation in Multi-Product Markets
Abstract
We analyze how market segmentation affects consumer welfare when a monopolist can engage in both second-degree price discrimination (through product differentiation) and third-degree price discrimination (through market segmentation). We characterize the consumer-optimal market segmentation and show that it has several striking properties: (1) the market segmentation displays monotonicity—higher-value customers always receive higher quality product than lower-value regardless of their segment and across any segment; and (2) when aggregate demand elasticity exceeds a threshold determined by marginal costs, no segmentation maximizes consumer surplus. Our results demonstrate that strategic market segmentation can benefit consumers even when it enables price discrimination, but these benefits depend critically on demand elasticities and cost structures. The findings have implications for regulatory policy regarding price discrimination and market segmentation practices.Discussant(s)
Ilya Segal
,
Stanford University
Ellen Muir
,
Massachusetts Institute of Technology
Michael Katz
,
University of California-Berkeley
Justin Johnson
,
Cornell University
JEL Classifications
- L1 - Market Structure, Firm Strategy, and Market Performance
- D4 - Market Structure, Pricing, and Design