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Related papers: Persuasion and Welfare

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This paper investigates the value of recommendations for disseminating economic information, with a focus on frictions resulting from preference heterogeneity. We consider Bayesian expected-payoff maximizers who receive non-strategic…

General Economics · Economics 2025-05-02 Jean-Michel Benkert , Armin Schmutzler

Welfare economics relies on access to agents' utility functions: we revisit classical questions in welfare economics, assuming access to data on agents' past choices instead of their utilities. Our main result considers the existence of…

Theoretical Economics · Economics 2024-06-26 Christopher P Chambers , Federico Echenique

While real-world decisions involve many competing objectives, algorithmic decisions are often evaluated with a single objective function. In this paper, we study algorithmic policies which explicitly trade off between a private objective…

Machine Learning · Computer Science 2020-07-17 Esther Rolf , Max Simchowitz , Sarah Dean , Lydia T. Liu , Daniel Björkegren , Moritz Hardt , Joshua Blumenstock

We study the effectiveness of information design in reducing congestion in social services catering to users with varied levels of need. In the absence of price discrimination and centralized admission, the provider relies on sharing…

Computer Science and Game Theory · Computer Science 2022-10-24 Jerry Anunrojwong , Krishnamurthy Iyer , Vahideh Manshadi

Individuals often navigate several options with incomplete knowledge of their own preferences. Information provisioning tools such as public rankings and personalized recommendations have become central to helping individuals make choices,…

Theoretical Economics · Economics 2025-06-05 Omar Besbes , Yash Kanoria , Akshit Kumar

We address the fundamental problem of selection under uncertainty by modeling it from the perspective of Bayesian persuasion. In our model, a decision maker with imperfect information always selects the option with the highest expected…

Computer Science and Game Theory · Computer Science 2024-10-16 Siddhartha Banerjee , Kamesh Munagala , Yiheng Shen , Kangning Wang

Neuroeconomics promises to ground welfare analysis in neural and computational evidence about how people value outcomes, learn from experience and exercise self-control. At the same time, policy and commercial actors increasingly invoke…

Machine Learning · Computer Science 2025-11-26 Yiven , Zhu

One of the major concerns of targeting interventions on individuals in social welfare programs is discrimination: individualized treatments may induce disparities across sensitive attributes such as age, gender, or race. This paper…

Econometrics · Economics 2022-07-01 Davide Viviano , Jelena Bradic

We study the problem of selection in the context of Bayesian persuasion. We are given multiple agents with hidden values (or quality scores), to whom resources must be allocated by a welfare-maximizing decision-maker. An intermediary with…

Computer Science and Game Theory · Computer Science 2025-11-18 Yannan Bai , Kamesh Munagala , Yiheng Shen , Davidson Zhu

We present a recommender system based on the Random Utility Model. Online shoppers are modeled as rational decision makers with limited information, and the recommendation task is formulated as the problem of optimally enriching the…

Computer Science and Game Theory · Computer Science 2024-09-24 Benjamin Heymann , Flavian Vasile , David Rohde

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…

Theoretical Economics · Economics 2025-11-20 Maryam Farboodi , Nima Haghpanah , Ali Shourideh

To choose between two discrete goods, a consumer pays attention to only those with prices below a threshold. From these, she chooses her most preferred good. We assume consumers in a population have the same preference but may have…

Theoretical Economics · Economics 2025-11-07 Kaushil Patel

Policymakers often face the decision of how to allocate resources across many different policies using noisy estimates of policy impacts. This paper develops a framework for optimal policy choices under statistical uncertainty. I consider a…

Econometrics · Economics 2026-02-03 Sarah Moon

This paper studies a decentralized many-to-one matching market where preferences remain uncertain during the matching process. Institutions initiate matching by sending offers, and applicants decide whether to accept upon receiving them.…

Theoretical Economics · Economics 2025-11-14 Yu-Ting Ho

Machine learning algorithms are increasingly used for consequential decision making regarding individuals based on their relevant features. Features that are relevant for accurate decisions may however lead to either explicit or implicit…

Machine Learning · Computer Science 2021-06-09 Sajad Khodadadian , Mohamed Nafea , AmirEmad Ghassami , Negar Kiyavash

The broad concept of an individual's welfare is actually a cluster of related specific concepts that bear a "family resemblance" to one another. One might care about how a policy will affect people both in terms of their subjective…

Theoretical Economics · Economics 2019-03-20 Edward J. Green

Empirical welfare analyses often impose stringent parametric assumptions on individuals' preferences and neglect unobserved preference heterogeneity. We develop a framework to conduct individual and social welfare analysis for discrete…

Theoretical Economics · Economics 2025-05-20 Bart Capéau , Liebrecht De Sadeleer , Sebastiaan Maes

To determine the welfare implications of price changes in demand data, we introduce a revealed preference relation over prices. We show that the absence of cycles in this relation characterizes a consumer who trades off the utility of…

Econometrics · Economics 2024-07-03 Rahul Deb , Yuichi Kitamura , John K. -H. Quah , Jörg Stoye

In many decision-making scenarios, individuals strategically choose what information to disclose to optimize their own outcomes. It is unclear whether such strategic information disclosure can lead to good societal outcomes. To address this…

Computer Science and Game Theory · Computer Science 2026-04-07 Siddhartha Banerjee , Kamesh Munagala , Yiheng Shen , Kangning Wang

This study proposes the General Bayes framework for policy learning. We consider decision problems in which a decision-maker chooses an action from an action set to maximize its expected welfare. Typical examples include treatment choice…

Machine Learning · Statistics 2026-03-02 Masahiro Kato
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