This paper develops a search-and-matching model that incorporates temporary unemployment and applies the model to study the labor market dynamics of the COVID-19 recession in the United States. We calibrate the model using panel data from the Current Population Survey for 2001–2019, and we find that the model-based job-finding rates match observed job-finding rates during the entire sample period and out of sample up through July 2020. We also find that the Beveridge curve is well behaved and that there is little change in market tightness in 2020 once we use the calibrated model to adjust for changes in the composition of the unemployed. We then use the model to project the path of unemployment over the next eighteen months. Under a range of assumptions about job losses and labor demand, our model predicts a more rapid recovery compared to a model that does not distinguish between temporary and permanent unemployment and compared to professional and academic forecasts. In order to rationalize the professional forecasts of the unemployment rate, some combination of the vacancy rate, the job-separation rate, and the recall rate of workers on temporary layoff must deteriorate substantially in the next several months.

本文开发了一个包含临时失业的搜索匹配模型，并应用该模型来研究美国 COVID-19 衰退的劳动力市场动态。我们使用 2001-2019 年当前人口调查的面板数据校准模型，我们发现基于模型的求职率与在整个样本期间和截至 2020 年 7 月的样本外观察到的求职率相匹配。还发现贝弗里奇曲线表现良好，一旦我们使用校准模型来调整失业者构成的变化，2020 年的市场紧张程度几乎没有变化。然后我们使用该模型来预测未来 18 个月的失业路径。在一系列关于失业和劳动力需求的假设下，与不区分临时失业和永久失业的模型相比，以及与专业和学术预测相比，我们的模型预测复苏速度更快。为了使失业率的专业预测合理化，空缺率、离职率和临时解雇工人的召回率的某些组合必须在未来几个月内大幅恶化。