Facilitating Fairness in Societal Decision Making and Markets

Abstract

This thesis studies how fairness can be facilitated in societal decision making and markets through the design of information and allocation mechanisms. In many modern economic scenarios, including marketplaces, hiring and admissions, public budgeting, and fair division, decision-makers must allocate resources or opportunities among agents with heterogeneous preferences and imperfectly observed information. While efficient solutions often exist, they typically distribute benefits unevenly among different parties, hence raising fairness concerns.We investigate fairness in three domains. First, we study price discrimination in markets with information intermediaries and characterize how regulatory constraints and buyer-level welfare objectives shape the allocation of market surplus. Second, we analyze information design in selection and competition problems with limited resources. We developed majorization-based fairness guarantees and study the efficiency loss from strategic information disclosure. Third, we study preference aggregation problems, including participatory budgeting and fair division. We focus on coalitional stability and envy-based share guarantees. Across these settings, we provide approximation algorithms, impossibility results, and tight bounds that characterize what fairness guarantees can be achieved.