Gabriel Chodorow-Reich and John Coglianese’s article, “Projecting unemployment durations: A factor-flows simulation approach with application to the COVID-19 recession,” was published in the Journal of Public Economics on March 5, 2021. Publisher Elsevier has partnered with the Copyright Center RightsLink service to offer a variety of options for reusing this content. This article is part of a special series on the state of the public economy during COVID-19.
In their work, the authors propose a new method for predicting unemployment, which is carried out in three stages. Since the paper is part of a series, the Chodorow-Reich and Coglianese article complements other research in the field that analyzes changes in the labor market during the COVID-19 recession. The peculiarity of the article is that the study is aimed at the consequences in the future, also considering the changes that occurred at the beginning of the pandemic (Chodorow-Reich & Coglianese, 2021). The study’s primary goal is to obtain a forecast of the overall unemployment rate, using the authors ‘ value-factor model.
As a result of the research, the authors use basic modeling to determine the peak and its estimated duration. According to researchers, the number of people unemployed for more than 26 weeks peaks in December 2020 at 4.2 million people (Chodorow-Reich & Coglianese, 2021). The rise of very long-term unemployment peaks around the present time, namely at the beginning of 2022. Based on their analysis, the authors also assume a historically rapid recovery of the labor market. That is true: in some areas, there is already a decrease in unemployment by 35 percent or more (Raifman et al., 2021). In addition, many studies point to an increasing trend of remote work.
I like the Chodorow-Reich and Coglianese study because the authors propose a new three-stage factor flow modeling approach to predict the duration distribution of unemployment. The article presents numerous graphs explaining the operation and features of their model. For example, the heterogeneity of re-employment after dismissal dramatically affects the unemployment rate. Chodorow-Reich and Coglianese analyze other studies on the topic and put forward their predictive model.
Reference
Chodorow-Reich, G., & Coglianese, J. (2021). Projecting unemployment durations: A factor-flows simulation approach with application to the COVID-19 recession. Journal of Public Economics, 197, 104398. Web.
Raifman, J., Bor, J., & Venkataramani, A. (2021). Association between receipt of unemployment insurance and food insecurity among people who lost employment during the COVID-19 pandemic in the United States. JAMA Network Open, 4(1). Web.