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Ididio Explores
Which jobs are recovering the most quickly from COVID losses?

Our estimates show strong recovery in personal services jobs, and new losses in transportation.

According to industry-level Bureau of Labor Statistics data, employment figures were at their worst in April 2020. We created career-level estimates to ferret out the fastest recoveries and the workers who are still feeling the most pain.

Which jobs have recovered the most?

We see lots of growth in the personal services -- the people who tend to our appearance in life and after we die -- as well as growth for jobs that enable some entertainment and nourishment outside our homes. We note that although the picture has improved greatly for these workers, it’s still rough with about a fourth of the workforce still missing.

Career-level COVID impacts
Selecting a career will take you to Ididio’s career page.
SOURCES:
2020 BLS Current Employment
2017 ACS microdata

Which workers are hurting more in June than they were in April?

Select the “Change June vs. April” and the table will show you jobs who lost workers from April 2020 to June 2020. It seems that many transportation and mining/energy jobs tried to keep workers on their employment rolls, and eventually were forced for furlough.

Which workers are still hurting the most?

Let’s sort the table one more time, and select the “Estimated annual change” header. Here we that performers and athletes are experiencing the highest job losses, with only two-thirds of employees still working.



Methodology
Unfortunately, monthly employment data is typically available by industry rather than by career, so we had to get a bit creative to estimate the change in employment.
We began with our aggregations from the American Community Survey. With a few exceptions, we’re able to classify each worker surveyed by occupation and by a 3-digit NAICS industry identification. In some cases, the 2-digit classification is all that is available, and in a few cases a hybrid designation is assigned.
For each ACS job designation, we calculated the percentage of workers within each industry classification as described above. We also calculated a distribution for the education attained and the 10th, 25th, 50th, 75th, and 90th salary percentiles for each ACS job designation.
We then used recently released data from the Bureau of Labor Statistic’s (BLS) Current Employment Statistics program to calculate the percentage of employment change from April 2019 to April 2020 by the 2- and 3-digit NAICS classifications. We chose April because that is the month with the smallest total employment reported by Current Employment Statistics during the pandemic. We then created the same percentage from June 2019 to June 2020, and we calculated the relative percentage of recovery using these two change figures.
In our final step, we combined the BLS employment data with the ACS survey data. For each job designation, we used the percentage within each industry classification as weights to average the percentage of employment change calculated using the BLS data. For the few industry designations that did not match the 2- and 3-digit NAICS data from the BLS, we simply omitted those workers from our calculation.
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