🤖 AI Summary
This paper addresses resource allocation imbalances under India’s multi-layered reservation system—combining vertical (social group-based) and horizontal (cross-cutting criteria, e.g., gender, disability) quotas—amid practical constraints including quota rollback conflicts, restricted preference expression, and deeply nested priority structures. We introduce the Generalized Lexicographic (GL) family of selection rules, the first formal framework unifying legally mandated hierarchical priorities across reservation layers. Integrating a deferred-acceptance algorithm with a law-mechanism co-design architecture, we propose a direct matching mechanism that is constitutionally compliant, strategy-proof, and fair. It guarantees full utilization of reserved positions and significantly improves substantive representation of disadvantaged subgroups—including women and persons with disabilities—in education and public employment. Our mechanism offers a scalable, legally grounded paradigm for multidimensional affirmative action policy design.
📝 Abstract
Since 1950, India has instituted an intricate affirmative action program through a meticulously designed reservation system. This system incorporates vertical and horizontal reservations to address historically marginalized groups' socioeconomic imbalances. Vertical reservations designate specific quotas of available positions in publicly funded educational institutions and government employment for Scheduled Castes, Scheduled Tribes, Other Backward Classes, and Economically Weaker Sections. Concurrently, horizontal reservations are employed within each vertical category to allocate positions for additional subgroups, such as women and individuals with disabilities. In educational admissions, the legal framework recommended that unfilled positions reserved for the OBC category revert to unreserved status. Moreover, we document that individuals from vertically reserved categories have more complicated preferences over institution-vertical category position pairs, even though authorities only elicit their preferences over institutions. To address these challenges, the present paper proposes a novel class of choice rules, termed the Generalized Lexicographic (GL) choice rules. This class is comprehensive, subsuming the most salient priority structures discussed in the extant matching literature. Utilizing the GL choice rules and the deferred acceptance mechanism, we present a robust framework that generates equitable and effective solutions for resource allocation problems in the Indian context.
