Limiting Sender's Information in Bayesian Persuasion (Games and Economic Behavior, 2019)
This paper studies how the outcome of Bayesian persuasion depends on Sender's information.
I study a game in which, prior to Sender's information disclosure, Designer can restrict the most informative signal that Sender can generate.
In the binary action case, I consider arbitrary preferences of Designer and characterize all equilibrium outcomes.
As a corollary, I derive an information restriction that maximizes Receiver's payoffs: Whenever Designer can increase Receiver's payoffs by restricting Sender's information, the Receiver-optimal way coincides with an equilibrium of the game in which Receiver persuades Sender.
Non-competing Data Intermediaries (New!)
I study competition among data intermediaries—technology companies and data brokers that collect consumer data and sell them to downstream firms. When firms’ use of data hurts consumers, intermediaries need to compensate consumers for collecting their data. However, competition may not increase compensation: If intermediaries offer high compensation, consumers share data with multiple intermediaries, which lowers the price of data in the downstream market and hurts intermediaries. This leads to multiple equilibria: There is a monopoly equilibrium, and an equilibrium with greater data concentration benefits intermediaries and hurts consumers. I use my results to solve information design by data intermediaries.
Online Privacy and Information Disclosure by Consumers (conditionally accepted at American Economic Review)
I study the welfare and price implications of consumer privacy.
A consumer discloses information to a multi-product seller, which learns about his preferences, sets prices, and makes product recommendations.
While the consumer benefits from accurate product recommendations, the seller may use the information to price discriminate.
I show that the seller prefers to commit to not price discriminate to encourage information disclosure.
However, this commitment hurts the consumer, who could be better off by precommitting to withhold some information.
In contrast to single-product models, total surplus may be lower if the seller is able to price discriminate.
Auction Timing and Market Thickness (with Isaias N. Chaves)
An auctioneer faces a pool of potential bidders that changes over time. She can delay the auction at a cost, in the hopes of having a thicker market later on. We identify a property of the distribution of bidder values—its "price elasticity"—that governs the distortions caused by revenue maximization: a seller inefficiently over-invests in market thickness (delays the auction excessively) if that elasticity is increasing, and under-invests if it is decreasing. We also show that dynamically responding to changes in the bidder pool is essential: committing to delay until an optimal deadline can waste most of the achievable revenue.
Consumer-Optimal Disclosure with Costly Information Acquisition
I study the question of how much product information should be available to consumers.
A monopolist sells one unit of product.
The consumer is initially uninformed of the product value but can incur costs to observe a noisy signal of his valuation.
I show that if it is costly to acquire information, consumer surplus can be increasing in the informativeness of the signal, because the seller sets a lower price to deter the consumer's learning.
I also show that there is a positive level of information acquisition cost that maximizes both consumer and total surplus.