The Great Resignation by the Numbers, JOLTS Data on the 2021–2023 Quits Wave
Between 2021 and 2023, American workers quit their jobs at rates never recorded in the modern era. Here is what the JOLTS data actually shows, industry by industry, state by state, before, during, and after the wave.
Key Takeaway
The Great Resignation peaked in November 2021 with 4.5 million quits in a single month, a three percent quits rate that shattered every prior JOLTS record. It was not evenly distributed: accommodation, food services, and retail saw catastrophic turnover while government and finance remained comparatively stable. By mid-2023 the wave had largely subsided, but left behind a labor market permanently more fluid than before.
What the JOLTS Data Actually Showed
The Great Resignation is often described in qualitative terms, workers reassessing priorities, seeking flexibility, escaping toxic workplaces. JOLTS translates those narratives into hard numbers. The data shows a multi-year episode of elevated voluntary separations unlike anything in the 20+ year JOLTS history.
The quits rate is calculated as the number of voluntary separations during the month divided by total employment, expressed as a percentage. A roughly three percent reading on the quits rate means that in a given month, 3 out of every 100 workers voluntarily left their jobs. In a 150-million-person workforce, that is 4.5 million quits in a single month.
Quits Rate: Before, During, and After
The table below shows the national monthly quits rate across key reference periods, using BLS JOLTS data. The contrast between the recession bottom and the Great Resignation peak is stark:
| Period | Quits Rate | Monthly Quits (M) | Context |
|---|---|---|---|
| 2009 low (recession trough) | 1.3% | ~1.7 | Workers afraid to quit; jobs scarce |
| 2019 avg (pre-pandemic) | 2.3% | ~3.5 | Healthy tight market; normal mobility |
| Apr 2020 (COVID shock) | 1.6% | ~2.1 | Workers froze; uncertainty peak |
| Apr 2021 (wave begins) | 2.8% | ~4.0 | Pent-up quits releasing; reopening |
| Nov 2021 (peak) | about 3.0 percent | ~4.5 | All-time JOLTS record; wages surging |
| 2022 avg (elevated) | 2.7% | ~4.1 | Still well above normal; tight market |
| Mid-2023 (declining) | 2.4% | ~3.6 | Wave ending; market cooling |
Approximate figures based on BLS JOLTS national series. Source: BLS JOLTS. See national trends for current data.
Compiled by the " research team.
Which Industries Saw the Biggest Exodus
The Great Resignation was not a single phenomenon, it was several overlapping waves concentrated in different sectors. Consumer-facing and lower-wage industries were hit hardest and earliest. Knowledge industries saw elevated but less extreme turnover.
| Industry | Pre-pandemic (2019) | Peak (2021–22) | Change | Driver |
|---|---|---|---|---|
| Accommodation & Food Services | 4.5% | 6.0–6.4% | +1.5–1.9pp | Pandemic stress; alternative jobs available |
| Retail Trade | 3.2% | 4.4–5.0% | +1.2–1.8pp | Wage competition; e-commerce alternatives |
| Healthcare & Social Assistance | 2.0% | 2.8–3.2% | +0.8–1.2pp | Burnout; travel nursing premiums |
| Professional & Business Services | 2.1% | 2.8–3.2% | +0.7–1.1pp | Remote work enabled job-shopping |
| Manufacturing | 1.7% | 2.2–2.5% | +0.5–0.8pp | Moderate increase; union contracts limited mobility |
| Government | 0.9% | 1.1–1.3% | +0.2–0.4pp | Pension benefits; job security kept workers |
Approximate figures based on BLS JOLTS industry series. Source: BLS JOLTS. See industry pages for current data.
Compiled by the " research team.
Why Different Industries Responded Differently
The magnitude of the Great Resignation by sector was not random. Several structural factors explain which industries saw catastrophic turnover and which were largely spared:
- Pandemic direct exposure: Workers in customer-facing roles (restaurants, hospitality, retail) bore direct pandemic risk, physical exposure, mask conflicts, difficult customers. This accelerated burnout and made leaving feel urgent.
- Wage floor competition: When Amazon, Target, and Walmart raised minimum wages to $15–$18/hour, they effectively raised the floor for all low-wage workers. Incumbent employers who could not match lost workers rapidly.
- Remote work optionality: Workers in professional services discovered they could search for new jobs without geographic constraints. A software developer in Ohio could quit a local company and join a San Francisco startup fully remote.
- Credential mobility: Licensed healthcare workers (nurses, physical therapists, pharmacists) found that their credentials were highly portable, and the market was bidding aggressively for them through travel agency premiums and signing bonuses.
- Benefits lock-in: Government employees with defined-benefit pensions, union workers with seniority-based pay increases, and older workers with employer-sponsored healthcare stayed put, the switching cost was too high.
State-Level Variation During the Wave
The Great Resignation was not felt equally across states. The geographic distribution reflected industry composition and local labor market conditions:
- Tourism-heavy states (Nevada, Hawaii, Florida) saw some of the highest quits rates because of the outsized hospitality and leisure sector exposure
- Technology-concentrated states (California, Washington, Massachusetts) saw large absolute numbers due to remote work mobility and aggressive competitor recruiting
- States with large manufacturing and government sectors (Ohio, Michigan, Virginia) saw more muted increases, the structural lock-in factors kept quits contained
- Sun Belt migration destinations (Texas, Arizona, Tennessee) saw elevated hires alongside elevated quits as newly relocated workers churned through jobs
Explore state-level quits data on PlainLabor's state profiles to see how your state's patterns compare to the national wave.
The Job Openings Side of the Story
The Great Resignation was both cause and consequence of unprecedented job openings. The two-sided dynamic is visible in the JOLTS data:
- Job openings surged from ~5 million pre-pandemic to nearly 12 million at peak, the highest ever recorded in JOLTS history (March 2022)
- More openings meant workers had real options when considering a quit, the risk of being unemployed was historically low
- The openings-to-unemployed ratio reached 1.9 in early 2022: nearly two unfilled jobs for every worker looking
- This ratio was the primary signal prompting the Federal Reserve to begin aggressive interest rate increases in March 2022
Read more about how job openings and hires interact in our guide to job openings vs. hires.
What Ended the Great Resignation
The Great Resignation did not end with a single event, it faded gradually through a combination of forces:
- Interest rate increases: The Fed's 525 basis point rate hike cycle (2022–2023) cooled hiring in rate-sensitive sectors (finance, real estate, technology) and reduced overall labor demand
- Exhaustion of pent-up quits: Workers who had been meaning to quit eventually did, and once that backlog cleared, the flow returned to more normal levels
- Pandemic savings depletion: The fiscal cushion that gave workers the confidence to quit without immediate replacement gradually eroded as inflation consumed savings
- Return-to-office dynamics: Employers who required office attendance effectively reduced the geographic flexibility that had enabled aggressive job-shopping
- Tech layoffs reducing alternative supply: Visible tech sector layoffs in 2022–2023 made workers in other sectors more cautious about quitting
See how the national trends look today on PlainLabor's national trends page, or browse industry pages to see where quits remain elevated.
Frequently Asked Questions
What caused the Great Resignation?
The Great Resignation was driven by several intersecting forces. The COVID-19 pandemic prompted many workers to reassess their careers and life priorities. Widespread remote work demonstrated that office attendance was not required for productivity, reducing geographic constraints on job switching. Pandemic savings gave some workers financial cushion to quit without immediate replacement. And a historically tight labor market, with openings nearly doubling unemployed workers, made job-switching unusually easy. Research by Anthony Klotz, who coined the term, also identified a backlog of pent-up resignations from workers who had delayed quitting during the initial pandemic uncertainty.
When exactly did the Great Resignation peak?
The Great Resignation peaked in November 2021, when the national quits rate hit 3.0% - the highest level recorded since JOLTS began in 2000. Total quits that month reached approximately 4.5 million workers. The elevated quit rate persisted through most of 2022 before beginning a sustained decline in late 2022 and 2023 as the labor market cooled, interest rate increases reduced economic activity, and the pool of workers seeking change was gradually exhausted.
Which industries had the highest quit rates during the Great Resignation?
Accommodation and food services led with quit rates exceeding 6% at peak, meaning more than 1 in 17 workers quit every single month. Retail trade followed at around 5%. Healthcare saw elevated quits (above 3%) as burned-out workers exited the sector after the pandemic strain. By contrast, government and financial services saw relatively modest increases, the Great Resignation was most acute in consumer-facing, lower-wage, high-contact industries where pandemic stress was greatest.
Did workers who quit during the Great Resignation get better jobs?
On average, yes. Atlanta Federal Reserve wage tracker data showed that job-switchers outpaced job-stayers in wage growth during 2021–2022, often by 2–4 percentage points annually. Workers who quit into new jobs in tight-market industries like technology, healthcare, and finance captured the largest gains. However, workers who quit without a new job lined up, or who left into declining industries, did not always fare better. The aggregate wage gains for job-switchers were real but unevenly distributed.
Is the Great Resignation over?
By most JOLTS measures, the Great Resignation ended by mid-2023. The national quits rate returned to approximately 2.2–2.4% - elevated compared to pre-pandemic 2019 levels of around 2.3%, but well below the 3.0% peak. Job openings fell from nearly 12 million to around 8–9 million. The labor market has remained relatively tight by historical standards, but the extreme churn of 2021–2022 has subsided. Some researchers argue a structural shift persists, workers are more selective and more willing to quit than they were pre-pandemic.
Did the Great Resignation happen in other countries?
Labor market tightening occurred in many developed economies in 2021–2022, but the phenomenon was most pronounced in the United States. Higher U.S. household savings, larger fiscal stimulus payments, and a more flexible at-will employment system made it easier for American workers to quit. Countries with stronger employment protections, shorter work authorization windows, or less pandemic-era fiscal support saw smaller resignation waves. Canada and the UK saw elevated quits relative to their pre-pandemic norms, but not to the degree recorded by U.S. JOLTS data.
Explore the Data
- Browse 51 state profiles - quits rates and labor market trends by state
- Browse 28 industries - sector-level quits, hires, and openings
- National trends - how quits, openings, and hires have shifted over time
- Labor market indicators - how to read the quits rate in context
- Which industries are hiring fastest - current hire rate rankings by sector
Reading the Great Resignation in numbers
The peak quits-rate signal
During the November 2021 peak, JOLTS recorded a roughly three percent national quits rate, the highest reading since the series began in 2000. That figure represented roughly 4.5 million workers leaving their jobs voluntarily in a single month, an unprecedented scale of voluntary turnover during a non-recessionary period.
Sectoral concentration
Hospitality and retail led the wave with quits rates above 6%, more than double their long-run averages. Healthcare followed closely as burnout from pandemic-era patient volumes pushed nurses and aides into private-duty or contract work.
Wage growth as a downstream effect
The Federal Reserve Bank of Atlanta wage-growth tracker followed the JOLTS quits cycle with roughly a one-quarter lag, reaching its 2022 peak at 6.7% nominal year-over-year, the highest reading in the series history. This corroborates that the quits surge translated into real wage outcomes for the workers who switched jobs.
Worked example: comparing pre-pandemic to peak
Pre-pandemic baseline: roughly 2.3% quits rate vs roughly the 3.0 figure peak, a 30% relative increase. Hospitality jumped from approximately 4.5% to 6.5% - a 44% relative increase, far above the headline number. The compositional effect alone explains why economy-wide wage growth lagged sectoral acceleration.
| Period | Quits rate | Hospitality quits rate | Wage growth (Atlanta tracker) |
|---|---|---|---|
| 2019 baseline | 2.3% | 4.5% | 3.4% |
| Nov 2021 peak | three percent | 6.5% | 4.3% |
| 2022 wage peak | 2.8% | 5.9% | 6.7% |
| 2024 cooled | 2.2% | 4.7% | 4.6% |
Sources
- Bureau of Labor Statistics, Job Openings and Labor Turnover Survey (JOLTS), bls.gov/jlt
- Federal Reserve Bank of Atlanta, Wage Growth Tracker, atlantafed.org/chcs/wage-growth-tracker
- Federal Reserve Board, FOMC minutes and monetary policy statements (2022–2023)
- BLS, Employment Situation Summary historical releases
This content is for informational and educational purposes only. Labor market data from BLS JOLTS is subject to revision. All figures are approximate based on published BLS data. This is not financial, investment, or employment advice. Always verify current figures at bls.gov.
