arXiv subjects

Ali Shourideh

Publications and source records attributed to Ali Shourideh.

5 recordsLinked to original sources

arXiv2025

Divide and Confer: Aggregating Information without Verification

We examine receiver-optimal mechanisms for aggregating information divided across many biased senders. Each sender privately observes an unconditionally independent signal about an unknown state, so no sender can verify another's report. A receiver makes a binary accept/reject decision that determines the players' payoffs via the state. When information is divided across a small population, and bias is low, the receiver-optimal mechanism coincides with the sender-preferred allocation, and can be implemented by letting senders confer privately before reporting. However, for larger populations, the receiver can benefit from the informational divide. We introduce a novel incentive-compatibility-in-the-large approach to solve the high-dimensional mechanism design problem for the large-population limit. Using this, we show that optimal mechanisms converge to one that depends only on the accept payoff and punishes excessive consensus in the direction of the common bias. These surplus burning punishments lead to payoffs that are bounded away from the first-best.

econ.TH↗

arXiv2025

Good Data and Bad Data: The Welfare Effects of Price Discrimination

We study how a monopolist's use of consumer data for price discrimination affects welfare. To answer this question, we develop a model of market segmentation subject to residual uncertainty. We fully characterize when data usage monotonically increases or decreases welfare or when the effect is non-monotone. The characterization reduces the problem to one with only two demand curves, and gives a condition for the two-demand-curves case that highlights that information affects welfare in three distinct ways. In the non-monotone case, we provide tight bounds on the welfare effects of information and identify the best local direction for providing additional information.

econ.TH↗

arXiv2024

Getting the Agent to Wait

We examine the strategic interaction between an expert (principal) maximizing engagement and an agent seeking swift information. Our analysis reveals: When priors align, relative patience determines optimal disclosure -- impatient agents induce gradual revelation, while impatient principals cause delayed, abrupt revelation. When priors disagree, catering to the bias often emerges, with the principal initially providing signals aligned with the agent's bias. With private agent beliefs, we observe two phases: one engaging both agents, followed by catering to one type. Comparing personalized and non-personalized strategies, we find faster information revelation in the non-personalized case, but higher quality information in the personalized case.

econ.TH↗

arXiv2023

Indicator Choice in Pay-for-Performance

We study the classic principal-agent model when the signal observed by the principal is chosen by the agent. We fully characterize the optimal information structure from an agent's perspective in a general moral hazard setting with limited liability. Due to endogeneity of the contract chosen by the principal, the agent's choice of information is non-trivial. We show that the agent's problem can be mapped into a geometrical game between the principal and the agent in the space of likelihood ratios. We use this representation result to show that coarse contracts are sufficient: The agent can achieve her best with binary signals. Additionally, we can characterize conditions under which the agent is able to extract the entire surplus and implement the first-best efficient allocation. Finally, we show that when effort and performance are one-dimensional, under a general class of models, threshold signals are optimal. Our theory can thus provide a rationale for coarseness of contracts based on the bargaining power of the agent in negotiations.

econ.TH↗

arXiv2020

Optimal Rating Design under Moral Hazard

We study optimal rating design under moral hazard and strategic manipulation. An intermediary observes a noisy indicator of effort and commits to a rating policy that shapes market beliefs and pay. Whether optimal ratings reveal or censor information depends on how effort shifts the outcome distribution: when effort increases tail risk, optimal ratings use lower censorship, pooling poor outcomes to encourage risk-taking; when effort reduces tail risk, upper censorship discourages negligence. In multi-task settings with window dressing, a monotone relative informativeness property again delivers upper- or lower-censorship ratings. In an application to redistributive test design, optimal tests can feature mid-censorship. These results follow from a general characterization of optimal ratings via concavification of a gain function, accommodating violations of monotone likelihood ratios and distributional concerns.

econ.TH↗