Layoffs in the technology sector dominated the news cycle in the second half of 2022, and the trend seems to be continuing into 2023: In January, Google and Microsoft announced another 12,000 and 10,000 layoffs, respectively. So, are these layoffs in or out of proportion with the labor market in general?
FRED has employment data specific to the Information industry. While this industry doesn’t exclusively represent the tech sector, it does include sectors where computer programmers, computer support specialists, computer systems analysts, and software developers are likely to work. These sub-industries are publishing, internet broadcasting, telecommunications, and—most relevant for this post—data processing, hosting, and related services.
The FRED graph above shows layoff levels for workers in the Information industry (in red) and for all nonfarm workers (in blue), indexed to 100 in April 2022. In that month, layoffs were at “normal” levels for both industries. This transformation enables us to see whether layoffs in Information have been increasing and, if so, whether they’ve increased more sharply relative to layoffs overall.
The graph shows that Information layoffs and layoffs overall had increased by similar percentages in May. But Information layoffs have gone up by more since then and remain more elevated. This pattern became more pronounced at the end of 2022: The last available month of data is December 2022, when Information layoffs were up by 65.5% compared with an increase of 26% for layoffs overall. Recent layoff announcements have continued into 2023, so we’ll look at the January 2023 data to compare with 2022 data.
How this graph was created: Search FRED for “Layoffs and Discharges: Total Nonfarm” and select “Monthly, Level in Thousands, Not Seasonally Adjusted” from the options. Next, click the “Edit Graph” button and use the “Add Line” tab to add “Layoffs and Discharges: Information.” Select “Edit Line 1” and change “Units” to “Index (Scale value to 100 for chosen date).” Next, select “2022-04-01” as the date to equal 100 for your custom index and “Copy to all.” Finally, enter “2022-04-01” to “2022-12-01” above the figure on the right to adjust the time period.
Suggested by Victoria Gregory and Elizabeth Harding.