Allocating scarce resources in the presence of private information and heterogeneous favoritism

Xiaoshuai Fan, Ying‐Ju Chen and Christopher S. Tang

Production and Operations Management, 2023, vol. 32, issue 7, 2068-2086

Abstract: Motivated by the challenge of allocating scarce resources from the federal government to different states during the COVID‐19 pandemic, this paper studies optimal schemes for allocating scarce resources to agents with private demand information under different favoritism structures. Through an investigation of a mechanism design model that aims to induce agents to report their demands truthfully, we find the following results. First, when the principal purely cares about social welfare and when the principal has sufficient resources to satisfy all agents' demands, we find that the optimal allocation scheme is efficient in the sense that it is identical to the optimal scheme for the “benchmark” case when favoritism differentials and information asymmetry are both absent. Second, when rationing is needed due to resource scarcity, we show that heterogeneity in “event‐independent” favoritism across agents will cause the principal to allocate more resources to agents with larger favoritism and less resources to others, resulting in inefficient allocations. Third, when agents possess heterogeneous “event‐specific” favoritism due to the existence of outside options, the resulting allocation may boost all agents' expected utilities, including those agents who do not have any outside option. Finally, we show that the “allocation distortion” caused by both information asymmetry and heterogeneous favoritism can be reduced when “positive externality” is present (i.e., allocating resources to one agent can benefit other agents).

Date: 2023
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