Allocating scarce resources in the presence of private information and heterogeneous favoritism
成果类型:
Article
署名作者:
Fan, Xiaoshuai; Chen, Ying-Ju; Tang, Christopher S. S.
署名单位:
Southern University of Science & Technology; Hong Kong University of Science & Technology; University of California System; University of California Los Angeles; Southern University of Science & Technology
刊物名称:
PRODUCTION AND OPERATIONS MANAGEMENT
ISSN/ISSBN:
1059-1478
DOI:
10.1111/poms.13957
发表日期:
2023
页码:
2068-2086
关键词:
allocation scheme
favoritism
information asymmetry
mechanism design
scarce resource
摘要:
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).
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