{"title":"Hidden information as a source of misallocation: An application to the opioid crisis","authors":"Bayarmaa Dalkhjav , Loris Rubini","doi":"10.1016/j.jedc.2025.105081","DOIUrl":null,"url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":48314,"journal":{"name":"Journal of Economic Dynamics & Control","volume":"174 ","pages":"Article 105081"},"PeriodicalIF":1.9000,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Economic Dynamics & Control","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0165188925000478","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECONOMICS","Score":null,"Total":0}
Hidden information as a source of misallocation: An application to the opioid crisis
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.
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.