Industry and State Employment Recovery Since the Beginning of the COVID-19 Pandemic

The recovery of the economy since the initial shutdowns from the COVID-19 pandemic indicate that the United States has recovered the number of jobs lost; however, the gains are not consistent across industry and state.

Using data from the Bureau of Labor Statistics (BLS) and United States Department of Housing and Urban Development (HUD), the tool below allows you to explore how each state has been impacted across 11 “super sectors” between March 2020 and November 2022.

To use the interactive charts below simply select a state from the Blue drop down menu labeled Choose State Here:

The ranking graphics utilize a polar area chart, which shows how each state ranks in terms of employment growth. The further the shaded area goes out, the better the rank in terms of the percentage change in employment. To view the data, hover over the wedge or bar.

The charts on the bottom reflect recommended housing costs for the average worker in each industry in comparison to the average rent in the state. Toggle the button below to observe the differences between the recommended cost for someone working 40 hours a week, versus the average hours worked in that industry. 

For some of the industries in some of the states, BLS either combines super sectors, or does not report that specific super sector because it does not have enough activity to be relevant. In those cases, the graphics simply will not produce graphs for those super sectors.

For a more holistic view and to see each sector’s top and bottom ten states for growth, check out our other charts here.

The wage, employment, and hours worked data were pulled from BLS’s Current Employment Statistics. The time points data are from November 2022 and March 2020, the month before employment numbers crashed due to pandemic-driven shutdowns. PPA calculated the percentage change between these two data points for each industry in each state for both the percentage change graphs and the ranking graphs. 

Rent data was gathered from HUD’s 50th Percentile Rent Estimates. These estimates are for median rents by county. To estimate rent on a state level, PPA calculated a weighted average using the 2017 population numbers provided in the HUD dataset. To estimate recommended rent, hourly wage data were multiplied separately by average wages and 40 (for 40 hours a week). Those numbers were then multiplied by 4.345, the average length of the month and then by 30%, which is a common recommended housing expenditure.

We processed the data in Python and all charts were created using HTML, CSS, and JavaScript, utilizing Charts.js.