Projecting unemployment durations: A factor-flows simulation approach with application to the COVID-19 recession

• 成果类型: Article
• 署名作者: Chodorow-Reich, Gabriel; Coglianese, John
• 署名单位: Federal Reserve System - USA
• 刊物名称: JOURNAL OF PUBLIC ECONOMICS
• ISSN/ISSBN: 0047-2727
• DOI: 10.1016/j.jpubeco.2021.104398
• 发表日期: 2021
• 关键词: unemployment duration; Labor market simulation; COVID recession

摘要

We propose a three-step factor-flows simulation-based approach to forecast the duration distribution of unemployment. Step 1: estimate individual transition hazards across employment, temporary layoff, per-manent layoff, quitter, entrant, and out of the labor force, with each hazard depending on an aggregate component as well as an individual's labor force history. Step 2: relate the aggregate components to the overall unemployment rate using a factor model. Step 3: combine the individual duration depen-dence, factor structure, and an auxiliary forecast of the unemployment rate to simulate a panel of indi-vidual labor force histories. Applying our approach to the November Blue Chip forecast of the COVID-19 recession, we project that 750,000 workers laid off in April 2020 remain unemployed eight months later. Total long-term unemployment rises thereafter and eventually reaches 4.2 million individuals unemployed for more than 26 weeks and 1.4 million individuals unemployed for more than 46 weeks. Long-term unemployment rises even more in a more pessimistic recovery scenario, but remains below the level in the Great Recession due to a high amount of labor market churn. (c) 2021 Elsevier B.V. All rights reserved.