Hidden information as a source of misallocation: An application to the opioid crisis

IF 1.9 3区 经济学 Q2 ECONOMICS Journal of Economic Dynamics & Control Pub Date : 2025-03-14 DOI:10.1016/j.jedc.2025.105081
Bayarmaa Dalkhjav , Loris Rubini
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Abstract

We develop a general equilibrium model where key employee information is hidden from managers, leading to a suboptimal allocation of resources. The health of the employees is not verifiable by managers, and an employee with poor health is less productive than a healthy one. We use this framework to study the loss of resources due to misallocation associated with the opioid crisis. Individuals with opioid use disorder are less productive and absent more often, which by itself generates output losses. In addition, since managers cannot distinguish unhealthy from healthy workers, wages differ from marginal productivity, creating a suboptimal allocation of resources. Calibrating the model to the U.S., we estimate that opioid misuse reduced output by $218.07 billion in 2023, with 12.4% of this loss attributable to misallocation.
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我们建立了一个一般均衡模型,在这个模型中,管理者无法获知员工的关键信息,从而导致资源的次优配置。管理者无法核实员工的健康状况,健康状况不佳的员工比健康的员工工作效率低。我们利用这一框架来研究与阿片类药物危机相关的资源配置不当造成的资源损失。患有阿片类药物使用障碍的人工作效率较低,缺勤次数较多,这本身就会造成产出损失。此外,由于管理者无法区分不健康的工人和健康的工人,工资与边际生产力存在差异,从而造成资源的次优配置。将模型校准到美国,我们估计阿片类药物滥用会在 2023 年使产出减少 2180.7 亿美元,其中 12.4% 的损失可归因于资源配置不当。
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来源期刊
CiteScore
3.10
自引率
10.50%
发文量
199
期刊介绍: The journal provides an outlet for publication of research concerning all theoretical and empirical aspects of economic dynamics and control as well as the development and use of computational methods in economics and finance. Contributions regarding computational methods may include, but are not restricted to, artificial intelligence, databases, decision support systems, genetic algorithms, modelling languages, neural networks, numerical algorithms for optimization, control and equilibria, parallel computing and qualitative reasoning.
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