We study the allocative challenges that governmental and nonprofit organizations face when tasked with equitable and efficient rationing of a social good among agents whose needs (demands) realize sequentially and are possibly correlated. As one example, early in the COVID-19 pandemic, the Federal Emergency Management Agency faced overwhelming, temporally scattered, a priori uncertain, and correlated demands for medical supplies from different states. In such contexts, social planners aim to maximize the minimum fill rate across sequentially arriving agents, where each agent's fill rate is determined by an irrevocable, one-time allocation. For an arbitrarily correlated sequence of demands, we establish upper bounds on the expected minimum fill rate (ex-post fairness) and the minimum expected fill rate (ex-ante fairness) achievable by any policy. Our upper bounds are parameterized by the number of agents and the expected demand-to-supply ratio, yet we design a simple adaptive policy called projected proportional allocation (PPA) that simultaneously achieves matching lower bounds for both objectives (ex-post and ex-ante fairness), for any set of parameters. Our PPA policy is transparent and easy to implement, as it does not rely on distributional information beyond the first conditional moments. Despite its simplicity, we demonstrate that the PPA policy provides significant improvement over the canonical class of non-adaptive target-fill-rate policies. We complement our theoretical developments with a numerical study motivated by the rationing of COVID-19 medical supplies based on a standard SEIR modeling approach that is commonly used to forecast pandemic trajectories. In such a setting, our PPA policy significantly outperforms its theoretical guarantee as well as the optimal target-fill-rate policy.
翻译:我们研究政府和非营利组织在负责公平和高效地分配社会公益物时所面临的分配挑战,这些代理机构的需求(需求)依次实现,而且可能相互关联。举例来说,在COVID-19大流行初期,联邦紧急管理署面临压倒性、暂时分散、先验性的不确定性以及对不同州医疗用品的相关需求。在这种情况下,社会规划者的目标是使按顺序抵达的代理机构的最低填补率最大化,每个代理机构的填补率由不可撤销的一次性分配来确定。对于任意关联的需求顺序,我们为预期的最低填补率(前端公平)和任何政策都能达到的最低预期填补率(前端公平)设定上限。我们的上端界限由代理机构的数量和预期的供需比率来设定参数,但我们设计了一个简单的适应性政策,即预测比例分配(PPA)同时为两个目标(前端和前端公平性分配率)设定相应的下限。 对于任意关联的需求顺序,我们的PPPPA政策是透明且易于执行的上限,因为它并不依赖于任何政策的标准化性(前端)政策(前端端端端端端),因为我们的分发政策没有显著的平价比标,我们提供了一个最优的交付政策。