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Recent literature on computational notions of fairness has been broadly divided into two distinct camps, supporting interventions that address either individual-based or group-based fairness. Rather than privilege a single definition, we…

Computer Science and Game Theory · Computer Science 2017-07-07 Lily Hu , Yiling Chen

Cooperation is fundamental for society's viability, as it enables the emergence of structure within heterogeneous groups that seek collective well-being. However, individuals are inclined to defect in order to benefit from the group's…

Multiagent Systems · Computer Science 2026-02-10 Yao-hua Franck Xu , Tayeb Lemlouma , Arnaud Braud , Jean-Marie Bonnin

It is well known that a game equilibrium can be far from efficient or fair, due to the misalignment between individual and social objectives. The focus of this paper is to design a new mechanism framework that induces an efficient and fair…

Computer Science and Game Theory · Computer Science 2017-08-11 Lin Gao , Jianwei Huang

The widening inequality in income distribution in recent years, and the associated excessive pay packages of CEOs in the U.S. and elsewhere, is of growing concern among policy makers as well as the common person. However, there seems to be…

Economics · Quantitative Finance 2014-11-13 Venkat Venkatasubramanian , Yu Luo , Jay Sethuraman

Deploying an algorithmically informed policy is a significant intervention in society. Prominent methods for algorithmic fairness focus on the distribution of predictions at the time of training, rather than the distribution of social goods…

Computers and Society · Computer Science 2024-06-18 Sebastian Zezulka , Konstantin Genin

We introduce a novel framework that considers how a firm could fairly compensate its workers. A firm has a group of workers, each of whom has varying productivities over a set of tasks. After assigning workers to tasks, the firm must then…

Theoretical Economics · Economics 2022-05-04 John E. Stovall

Dynamic, risk-based pricing can systematically exclude vulnerable consumer groups from essential resources such as health insurance and consumer credit. We show that a regulator can realign private incentives with social objectives through…

Artificial Intelligence · Computer Science 2025-06-05 Jesse Thibodeau , Hadi Nekoei , Afaf Taïk , Janarthanan Rajendran , Golnoosh Farnadi

Frequent violations of fair principles in real-life settings raise the fundamental question of whether such principles can guarantee the existence of a self-enforcing equilibrium in a free economy. We show that elementary principles of…

Theoretical Economics · Economics 2021-07-28 Ghislain H. Demeze-Jouatsa , Roland Pongou , Jean-Baptiste Tondji

In prediction-based decision-making systems, different perspectives can be at odds: The short-term business goals of the decision makers are often in conflict with the decision subjects' wish to be treated fairly. Balancing these two…

Computers and Society · Computer Science 2023-05-03 Corinna Hertweck , Joachim Baumann , Michele Loi , Eleonora Viganò , Christoph Heitz

We consider the problem of allocating a set on indivisible items to players with private preferences in an efficient and fair way. We focus on valuations that have dichotomous marginals, in which the added value of any item to a set is…

Computer Science and Game Theory · Computer Science 2020-12-25 Moshe Babaioff , Tomer Ezra , Uriel Feige

This paper studies an incentive structure for cooperation and its stability in peer-assisted services when there exist multiple content providers, using a coalition game theoretic approach. We first consider a generalized coalition…

Networking and Internet Architecture · Computer Science 2015-03-19 Jeong-woo Cho , Yung Yi

The persistence of racial inequality in the U.S. labor market against a general backdrop of formal equality of opportunity is a troubling phenomenon that has significant ramifications on the design of hiring policies. In this paper, we show…

Computer Science and Game Theory · Computer Science 2018-02-22 Lily Hu , Yiling Chen

An econometric or statistical model may undergo a marginal gain if we admit a new variable to the model, and a marginal loss if we remove an existing variable from the model. Assuming equality of opportunity among all candidate variables,…

Machine Learning · Statistics 2020-03-16 Xingwei Hu

High performance machine learning models have become highly dependent on the availability of large quantity and quality of training data. To achieve this, various central agencies such as the government have suggested for different data…

Machine Learning · Computer Science 2019-11-27 Zhiliang Chen

This study explores the impact of unemployment benefits on employment quality, job stability, and tenure within complex labour market dynamics. Given the macroeconomic consequences of changes in unemployment benefits, including their impact…

General Economics · Economics 2024-07-31 Jessica Reale , Frederik Banning , Michael Roos

This paper develops a new model of business cycles. The model is economical in that it is solved with an aggregate demand-aggregate supply diagram, and the effects of shocks and policies are obtained by comparative statics. The model builds…

Theoretical Economics · Economics 2022-03-22 Pascal Michaillat , Emmanuel Saez

We study a dynamic labor market in which a risk-averse worker with career concerns chooses each period between self-employment, which generates publicly observed binary output, and employment at a firm, which pays a flat wage but keeps…

Theoretical Economics · Economics 2025-11-25 Georgy Lukyanov , Konstantin Popov , Shubh Lashkery

Managing unemployment is one of the key issues in social policies. Unemployment insurance schemes are designed to cushion the financial and morale blow of loss of job but also to encourage the unemployed to seek new jobs more pro-actively…

Statistical Finance · Quantitative Finance 2019-09-05 Jason S. Anquandah , Leonid V. Bogachev

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 propose a unified framework for fair regression tasks formulated as risk minimization problems subject to a demographic parity constraint. Unlike many existing approaches that are limited to specific loss functions or rely on challenging…

Methodology · Statistics 2026-01-16 Yongzhen Feng , Weiwei Wang , Raymond K. W. Wong , Xianyang Zhang
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