Assessing Labor Market Conditions Using High-Frequency Data

Abstract

When the COVID-19 pandemic struck in March 2020, the U.S. economy experienced a sharp, unexpected recession with large employment losses. The information on employment available from traditional data sources arrives with a lag and does not promptly reflect sudden changes in labor market conditions. In this article, we discuss how new high-frequency data from Homebase and Ultimate Kronos Group can offer critical information on the state of labor markets in real time. Using these datasets, we construct coincident employment indices to assess employment at a high frequency. Employment during the pandemic reacted to changes in the number of infections and the restrictions imposed by government officials (see, e.g., the discussion in Dvorkin and Bharadwaj, 2020). Our latest data suggest that employment has recently increased and will continue to increase as the pandemic wanes.

Introduction

The coronavirus pandemic severely affected economic activity in the United States and the rest of the world. In the United States, gross domestic product contracted by almost 33 percent in annual terms in the second quarter of 2020, creating the deepest and sharpest recession since World War II. Economic activity has substantially recovered since, but this plunge in economic activity translated into unprecedented job losses, and the level of U.S. employment in April 2020 showed 25 million fewer people employed relative to January 2020. Since April 2020, employment has recovered at a fast pace, but employment levels are still below those seen at the beginning of 2020. 

The study of U.S. labor market conditions typically relies on two monthly surveys. The first is the Current Population Survey (CPS), which surveys around 60,000 U.S. households and is the main source of official unemployment measures. The second is the Current Employ­­ment Statistics survey (CES), which surveys around 145,000 U.S. businesses and government agencies and is the main source of changes in payroll, employment, and wages.

In normal times, labor market conditions change slowly, and monthly information from the CPS and CES on employment and unemployment is sufficient to gauge the state of labor markets and predict their evolution. However, the rapidly changing conditions during the pandemic called for higher-frequency data to evaluate the state of labor markets in real time. In a recent working paper, Chetty et al. (2020) developed a granular real-time publicly available dataset to address this challenge. We also use high-frequency employment data from two companies with ample coverage of U.S. labor markets, Homebase and Ultimate Kronos Group (UKG). Kurmann, Lalé, and Ta (2020) use the Homebase data to demonstrate how business closures by firm size impacted employment throughout the pandemic. In this article, we use the Homebase and UKG data to create and track useful measures of aggregate and regional employment conditions.