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This paper investigates social interactions in endogenous groups. We specify a two-sided many-to-one matching model, where individuals select groups based on preferences, while groups admit individuals based on qualifications until reaching…

Econometrics · Economics 2025-05-06 Shuyang Sheng , Xiaoting Sun

The prevalence and importance of algorithmic two-sided marketplaces has drawn attention to the issue of fairness in such settings. Algorithmic decisions are used in assigning students to schools, users to advertisers, and applicants to job…

Machine Learning · Computer Science 2023-06-19 Siddartha Devic , David Kempe , Vatsal Sharan , Aleksandra Korolova

We investigate the allocation of children to childcare facilities and propose solutions to overcome limitations in the current allocation mechanism. We introduce a natural preference domain and a priority structure that address these…

Theoretical Economics · Economics 2023-08-29 Ata Atay , Antonio Romero-Medina

Large language models (LLMs) are increasingly deployed in decision-support systems for high-stakes domains such as hiring and university admissions, where choices often involve selecting among competing alternatives. While prior work has…

Artificial Intelligence · Computer Science 2026-04-15 Haonan Yin , Shai Vardi , Vidyanand Choudhary

We study the impacts of incomplete information on centralized one-to-one matching markets. We focus on the commonly used Deferred Acceptance mechanism (Gale and Shapley, 1962). We show that many complete-information results are fragile to a…

Theoretical Economics · Economics 2021-07-12 Marcelo Ariel Fernandez , Kirill Rudov , Leeat Yariv

When making important decisions such as choosing health insurance or a school, people are often uncertain what levels of attributes will suit their true preference. After choice, they might realize that their uncertainty resulted in a…

Physics and Society · Physics 2021-10-12 Tom Dvir , Renana Peres , Zeév Rudnick

In many predictive decision-making scenarios, such as credit scoring and academic testing, a decision-maker must construct a model that accounts for agents' propensity to "game" the decision rule by changing their features so as to receive…

Machine Learning · Computer Science 2022-08-26 Yonadav Shavit , Benjamin Edelman , Brian Axelrod

In a setting of many-to-one two-sided matching with non-transferable utilities, e.g., college admissions, we study conditions under which preferences of both sides are identified with data on one single market. Regardless of whether the…

Econometrics · Economics 2023-07-11 YingHua He , Shruti Sinha , Xiaoting Sun

We develop methodology for causal inference in observational studies when using propensity score subclassification on data constructed with probabilistic record linkage techniques. We focus on scenarios where covariates and binary treatment…

Methodology · Statistics 2018-04-03 Joan Heck Wortman , Jerome P. Reiter

Group configurations play a pivotal role in shaping social skills and learning outcomes by fostering student interaction and collaboration. Yet, the factors influencing group formation, social cohesion, and group stability remain…

Physics Education · Physics 2023-09-28 Diego Ramírez , Eugenio J. Guzman-Lavın , Javier Pulgar , Cristian Candia

Strategic incentives may lead to inefficient and unequal provision of public services. A prominent example is school admissions. Existing research shows that applicants "play the system" by submitting school rankings strategically. We…

We study the design of information acquisition games-environments where a designer contracts their action on Sender's choice of experiment and the realized signals about some state-and identify which predictions can be made absent knowledge…

Theoretical Economics · Economics 2026-01-22 Eric Gao , Daniel Luo

We study the problem of agent selection in causal strategic learning under multiple decision makers and address two key challenges that come with it. Firstly, while much of prior work focuses on studying a fixed pool of agents that remains…

Artificial Intelligence · Computer Science 2024-02-06 Kiet Q. H. Vo , Muneeb Aadil , Siu Lun Chau , Krikamol Muandet

When estimating causal effects using observational data, it is desirable to replicate a randomized experiment as closely as possible by obtaining treated and control groups with similar covariate distributions. This goal can often be…

Methodology · Statistics 2010-10-28 Elizabeth A. Stuart

Because preferences naturally arise and play an important role in many real-life decisions, they are at the backbone of various fields. In particular preferences are increasingly used in almost all matching procedures-based applications. In…

Artificial Intelligence · Computer Science 2019-03-26 Youssef Hamadi , Souhila Kaci

Public and private institutions must often allocate scare resources under uncertainty. Banks, for example, extend credit to loan applicants based in part on their estimated likelihood of repaying a loan. But when the quality of information…

Computers and Society · Computer Science 2021-10-11 William Cai , Johann Gaebler , Nikhil Garg , Sharad Goel

A decision maker typically (i) incorporates training data to learn about the relative effectiveness of treatments, and (ii) chooses an implementation mechanism that implies an ``optimal'' predicted outcome distribution according to some…

Econometrics · Economics 2025-05-29 Anders Bredahl Kock , David Preinerstorfer

Choice problems refer to selecting the best choices from several items, and learning users' preferences in choice problems is of great significance in understanding the decision making mechanisms and providing personalized services.…

Information Retrieval · Computer Science 2023-08-16 Qingming Li , H. Vicky Zhao

In longitudinal studies where units are embedded in space or a social network, interference may arise, meaning that a unit's outcome can depend on treatment histories of others. The presence of interference poses significant challenges for…

Methodology · Statistics 2025-08-26 Ye Wang , Michael Jetsupphasuk

Consider the problem of estimating the causal effect of some attribute of a text document; for example: what effect does writing a polite vs. rude email have on response time? To estimate a causal effect from observational data, we need to…

Machine Learning · Statistics 2023-02-09 Lin Gui , Victor Veitch