Layoffs Have Been Declining for Over 50 Years

08.13.2026

For 25 years the Department of Labor (DOL) has released monthly data from the Job Openings and Labor Turnover Survey (JOLTS) including the number of layoffs, quits, new hires, and job openings in the U.S. Layoffs are defined in JOLTS as involuntary separations and discharges initiated by the employer.[1] The layoff rate has been steadily declining in the JOLTS data period; there were 37% more layoffs (per employee) in the early 2000s compared to January 2022 to April 2026. We can use other DOL data series, with a longer history, to examine whether the downward trend in layoffs began even earlier.

In this Edgeworth Insight I use the DOL’s weekly administrative data on new unemployment insurance (UI) claims to project layoff rates each month between 1970 and the beginning of the JOLTS data. I find that the steady downward trend in the layoff rate reported by JOLTS over the past 25 years would extend back for another three decades had comparable layoff data been reported. In other words, the layoff rate has been declining steadily since at least 1970 and millions fewer workers are laid off today than would be expected using layoff rates from the 1970s.

I estimate that the layoff rate was about 2.74 times higher in the early 1970s than in the period since January 2022. According to JOLTS, 21.2 million workers in the U.S. were laid off in the most recent 12 months (ending April 2026). I find that nearly 37 million more workers would have been laid off in the past year if the current layoff rate matched the layoff rate of the early 1970s.

Figure 1 shows the new UI claims and layoff rates (monthly not seasonally adjusted new UI claims and total layoffs expressed as a percentage of total non-farm employment). The data in Figure 1 cover the period over which JOLTS was reported. Both data series have a downward trend and are highly correlated due to seasonal and business cycle effects. The new UI claimant rate and the layoff rate increased sharply during recessions and especially during the COVID lockdown period.

Figure 2 shows the new UI claimant rate between 1970 and 2026 using a 12-month moving average to smooth out month-to-month fluctuations. Because layoffs are higher during recessions, and recessions since 1970 have differed substantially in their severity and duration, my analysis of downward trends focuses on non-recessionary periods. The first non-recessionary period in Figure 2 is between January 1971 and September 1973, while the most recent non-recessionary period is January 2022 to the present.

New UI claimants represented about 1.57% of total payroll employment between January 1971 and September 1973, and only about 0.61% of total payroll employment since January 2022. The new UI claimant rate was therefore almost 2.6 times higher in the early 1970s than in the recent past. If the share of laid-off workers collecting UI remained the same since the 1970s, it would be reasonable to assume that the layoff rate in the early 1970s was also 2.6 times the layoff rate since 2022. This estimate may be conservative since, If the share of laid off workers collecting UI has increased over time because it is now easier to apply for and collect UI benefits online, the layoff rate in the early 1970s was likely even more than 2.6 times higher than in the recent past.

Alternatively, I estimate an empirical relationship between the log of total layoffs and the log of contemporaneous and lagged new UI claimants, with controls for recessions, the COVID lockdown period, seasonal effects, and a time trend using the data in Figure 1. I use this regression to project the layoff rate from 1970 to the present based on UI data. Figure 3 presents the projected layoff rate, using a 12-month moving average to smooth out month-to-month fluctuations. The data in Figure 3 shows a steady downward trend in the layoff rate interrupted by increases during recessions and the period impacted by COVID policies.

The following Table compares the average layoff rate during each non-recessionary period covered since 1970. The average layoff rate in each successive non-recessionary period is lower than in the previous period. The average layoff rate from January 2022 to April 2026, is only 1.07%, compared to an average of 3.13% from 1971 Q1 to 1973 Q3. The average layoff rate in non-recessionary months in the early 1970s was about 2.9 times the average layoff rate in the recent past.

Average Layoff Rate in Non-Recessionary Periods
(1970 to Present)
Period Start	Period End	Projected Average Layoff Rate	JOLTS Reported Average Layoff Rate
1971 Q1	1973 Q3	3.13%
1975 Q2	1979 Q4	2.79%
1980 Q4	1981 Q2	2.37%
1983 Q1	1990 Q2	2.17%
1991 Q2	2000 Q4	1.74%
2002 Q1	2007 Q3	1.46%	1.47%
2009 Q3	2019 Q4	1.30%	1.31%
2022 Q1	Present	1.07%	1.07%

Using the midpoint of the two estimates presented here, I find that the average layoff rate in the early 1970s was about 2.74 times higher than it has been since January 2022. As noted earlier, 21.2 million workers were laid off in the past 12 months but if the current layoff rate matched the layoff rate of the early 1970s about 58 million workers would have been laid off in the past year.

A possible question for labor economists to research is how and why the U.S. labor market is able to reallocate workers across employers with relatively fewer layoffs than in the early 1970s. Downsizing employers today may rely more on attrition than a reduction in force (RIF) and layoffs to reach employment targets compared to the 1970s. Employees can more easily engage in job search while employed than 50 years ago because of the internet. This may cause employees of downsizing businesses to find alternative employment before layoffs are initiated, thereby reducing the magnitude of the RIF. Differences in the mix of employment across industries today compared to the economy of the 1970s may also help explain employers’ reduced reliance on layoffs.

Regardless of the reason for the decline in the average layoff rate, the data presented here suggest that the current U.S. labor market can adjust to reallocations of labor due to sectoral shifts more efficiently than at any time since the 1970s. While potentially large employment reallocations are expected to accompany the current AI boom, which will present challenges to businesses and workers, the U.S. labor market has never been more efficient at adapting to structural changes.

I thank Akshat Sinha for excellent research assistance and Brent Butgereit, Elliot Delahaye, and Nathan Woods for helpful comments.

CITATIONS

[1] According to the JOLTS website Layoffs include: layoffs with no intent to rehire; formal suspension from pay status lasting or expected to last more than seven days; discharges resulting from mergers, downsizing, or closings; firings or other discharges for cause; terminations of permanent or short-term employees; and terminations of seasonal employees (whether or not they are expected to return the next season).