Two Approaches to Predicting the Path of the COVID-19 Pandemic: Is One Better?

We compare two types of models used to predict the spread of the coronavirus, both of which have been used by government officials and agencies. We describe the nature of the difference between the two approaches and their advantages and limitations. We compare examples of each type of model—the University of Washington IHME or “Murray” model, which follows a curve-fitting approach, and the Ohio State University model, which follows a structural approach. Read More  

Economic Inclusion 2000–2020: Labor Market Trends by Race in the US and States

This Commentary examines the extent to which disparities exist between Blacks and whites in labor market outcomes such as levels of labor force participation, unemployment rates, and earnings. To gauge whether disparities have narrowed or widened since 2000, national trends in these outcomes during the past two decades are compared to the trends in three states: Kentucky, Ohio, and Pennsylvania. Finally, to assess the current state of economic inclusion as reflected in the labor market, gaps in Black and white outcomes are compared across US states in 2020. Read More  

The Decline in Access to Jobs and the location of Employment Growth in US Metro Areas: Implications for Economic Opportunity and Mobility

Increasing workers’ access to jobs has been found to significantly decrease the duration of joblessness among lower-income unemployed workers. Policies that influence the location of employment growth within a metro area could impact the pace of the labor market recovery from the COVID-19-induced recession. By studying trends in job access, we discern developments that might inform our policy choices. Read More  

Layoffs during the COVID-19 Pandemic: Four Findings from WARN Act Data

With economic conditions changing so rapidly during the COVID-19 pandemic, the standard layoff indicators that policymakers and analysts use are falling short. Worker Adjustment and Retraining Notification (WARN) Act data—a more timely indicator—reveal four findings about job loss during this pandemic. Read More  

Assessing Layoffs in Four Midwestern States during the Pandemic Recession

We use WARN data to assess layoffs in four Midwestern states during the current pandemic-induced recession—Kentucky, Ohio, Pennsylvania, and West Virginia. The data come from the advance layoff notices filed under the Worker Adjustment and Retraining Notification (WARN) Act. We find that the number of workers affected by layoff announcements rose sharply in the second half of March and April, and unexpected changes in economic conditions meant that workers received little advance notice before layoff. Layoff announcements have affected workers across these four states, and workers in mining and leisure and hospitality have been affected the most. Most recently, the number of workers affected by WARN notices has almost returned to prerecession levels. Read More