🤖 AI Summary
This paper addresses the problem of coordinating charitable contributions under Leontief preferences—where donors maximize the weighted minimum of their contributions to complementary public goods. Decentralized mechanisms suffer from efficiency losses, while centralized ones struggle to respect individual preferences. To bridge this gap, we propose a novel coordination mechanism that unifies Lindahl equilibrium and Nash welfare maximization within a group-strategy-proof implementation framework—the first such integration. Our mechanism guarantees group-strategy immunity, monotonicity, and uniqueness of equilibrium. Leveraging convex optimization and best-response dynamics, it computes the unique Lindahl equilibrium in polynomial time, ensuring incentive compatibility, fairness, and significantly improved resource allocation efficiency and donor satisfaction. Theoretically rigorous and practically deployable, our approach advances both mechanism design theory and real-world philanthropic coordination.
📝 Abstract
Charity is typically carried out by individual donors, who donate money to charities they support, or by centralized organizations such as governments or municipalities, which collect individual contributions and distribute them among a set of charities. Individual charity respects the will of the donors, but may be inefficient due to a lack of coordination; centralized charity is potentially more efficient, but may ignore the will of individual donors. We present a mechanism that combines the advantages of both methods for donors with Leontief preferences (i.e., each donor seeks to maximize an individually weighted minimum of all contributions across the charities). The mechanism distributes the contribution of each donor efficiently such that no subset of donors has an incentive to redistribute their donations. Moreover, it is group-strategyproof, satisfies desirable monotonicity properties, maximizes Nash welfare, returns a unique Lindahl equilibrium, can be computed efficiently, and implemented via natural best-response spending dynamics.
