JOLTS by industry and state: what the headline hires-quits-layoffs rate doesn’t show
The monthly JOLTS release gets covered almost entirely at the national level: one hires rate, one quits rate, one layoffs rate. That average sits on top of enormous variation — leisure and hospitality workers change jobs at nearly five times the rate of federal employees, and a South Dakota worker is more than twice as likely to quit in a given month as one in Massachusetts. Seasonally adjusted BLS JOLTS data, national series through May 2026, industry series through May 2026, state series through December 2025 (state data is released on a roughly five-month lag).
National hires / quits / layoffs rate, May 2026
3.3% / 1.9% / 1.1%
The single national number most coverage stops at.
Industry hires-rate spread, same month
1.3% – 5.8%
State/local education vs. accommodation & food services — a 4.5x range hidden inside the 3.3% average.
State quits-rate spread, Dec 2025
1.3% – 3.4%
Massachusetts vs. South Dakota. Zero states or regions are covered in typical JOLTS write-ups.
National hires, quits, and layoffs rates, 2000–2026
The standard chart: three national rates, monthly, seasonally adjusted. Useful for spotting recessions and the 2021–22 “Great Resignation” quits spike — but it’s an average across every industry and every state, which is where the rest of this piece goes.
Hires rate
Quits rate
Layoffs & discharges rate
Unemployed workers per job opening, 2001–2026
Most JOLTS commentary shows openings and unemployment as two separate level lines. Dividing unemployed workers by openings collapses them into a single tightness reading: below 1.0 means there are more openings than unemployed workers to fill them (a “tight,” worker-favorable market); above 1.0 means more job seekers than openings (a “slack” market). The ratio peaked at 6.5 unemployed workers per opening in July 2009, in the aftermath of the financial crisis — far worse, and far more prolonged, than the shorter 2020 COVID spike. It then fell all the way to 0.5 (two openings per unemployed worker) at the height of the 2021–22 hiring boom, before drifting back up toward roughly 1:1 recently — a labor market with about as many openings as job seekers, not the acute worker shortage of a few years ago.
Reading the gap near 2025: October 2025’s point is interpolated — the federal appropriations lapse that month paused BLS data collection, so no unemployment figure exists to pair with that month’s openings. Treat the dip as a missing observation, not a real one-month move.
Hires, quits, and layoffs rates by industry, May 2026
All 19 published industry groups, mutually exclusive (aggregates like “Total private” and “Government” are excluded so nothing is double-counted). Sorted by hires rate. The gray connector spans each industry’s low-to-high rate across the three measures — a short bar means the three rates cluster together; a long one means an industry has, say, high hiring but low separations (net growth) or the reverse.
Hires rate
Quits rate
Layoffs & discharges rate
On “AI-exposed” layoffs: Information and Professional & Business Services are tied for the 4th-highest layoffs rate (1.8%) this month — real, but behind Construction and Arts/Entertainment (2.1% each), both of which are ordinary cyclical/seasonal sectors, not AI-exposed white-collar ones. Those same two sectors also hire briskly (2.9%–4.3%), so the churn reads as elevated turnover, not a one-way net loss of jobs.
Quits rate by state, December 2025 (most recent available)
State-level JOLTS runs about five months behind the national release, which is why this chart lags the others. The dashed line marks the December 2025 national average (2.0%). Quits track hiring ease more than layoffs do — workers quit more freely where jobs are easy to replace — so this is close to a map of where workers currently have the most leverage.
The pattern: the highest-quits states skew smaller, lower-cost-of-living, and energy/agriculture-heavy (South Dakota, Indiana, Alaska, Montana, North Dakota, Wyoming); the lowest are dense, high-cost coastal and Northeastern labor markets (Massachusetts, DC, Georgia, Washington, New Jersey). That’s consistent with quits behaving like a proxy for how easy workers judge it to be to land a comparable job nearby — not simply a function of a state’s overall unemployment rate.
Is the “labor shortage” number a big-business number?
JOLTS job-openings data gets cited constantly to argue employers can’t find domestic workers — the same argument used to justify sending jobs overseas and importing labor on guest-worker visas. We tested whether the survey behind that number is actually built from large-firm responses. Sources: BLS JOLTS establishment-size research series (Dec 2000–May 2026) and DOL OFLC H-1B/H-1B1/E-3 LCA disclosure data (FY2026 Q1–Q2).
Share of job openings from 5,000+ employee establishments
3.2%
May 2026, Total Private. Barely moved from 2.0% in 2019 and 1.9% in 2015 — a stable feature of the data, not a recent shift.
JOLTS survey response rate, 2020 → 2024
58% → 33%
And per BLS/Federal Reserve research, response is lower in the largest size classes — those estimates are the least reliable, not the most.
“Certainty stratum” in the sample design
100% sampling
Every establishment above a size threshold is included with certainty by design — it’s the small ones that get randomly subsampled.
Where the nation’s job openings actually sit
JOLTS classifies every sampled unit into one of six employment-size classes and publishes job-openings levels for each. This is establishment size — a single physical location — not firm size. Read at face value, the headline “can’t find workers” number is overwhelmingly a small-and-mid-business number: locations under 250 employees account for ~77% of measured openings.
Response rates cut the other way too: BLS and Federal Reserve researchers have both flagged that the largest size classes have the lowest survey response, meaning the already-small 5,000+ slice is also the noisiest one in the published data.
Establishment ≠ firm: why “large employer” doesn’t mean “large establishment”
A firm is one or many establishments under a common EIN. A retail or restaurant chain with 50,000 employees shows up in JOLTS as thousands of separate small locations — most falling into the “under 250” buckets above. A company that concentrates its U.S. workforce into a handful of huge campuses shows up as a few units in the certainty stratum instead. Using this project’s own H-1B/LCA disclosure data, distinct worksite addresses per employer vary enormously — illustrating just how differently “large employer” maps onto establishment size class from one company to the next.
Distinct worksite street addresses named across each employer’s FY2026 LCA filings. Not a headcount measure — DOL’s position-count fields turned out to be batch-filing ceilings (e.g. Qualcomm’s LCAs are routinely filed in round lots of 100), not confirmed hires, so we didn’t use them for anything requiring real magnitude.
The gap nobody outside BLS can check: JOLTS never publishes an industry × establishment-size cross-tabulation — not for tech, not for any sector. So the sharper version of the “big offshoring-heavy employers drive the shortage number” claim can’t actually be tested against public JOLTS data, by us or anyone else. That’s a real transparency limit in the dataset, not evidence either way.
Are job openings turning into real hiring? A tech-sector check
Testing whether elevated JOLTS job openings actually convert to hires in tech-heavy sectors, and how H-1B tech hiring volume compares to the broader trend. Seasonally adjusted BLS JOLTS data (Information & Professional/Business Services) and DOL H-1B LCA disclosure data (Computer & Mathematical occupations, SOC 15-xxxx), 2020-2026.
Info sector: openings vs hires gap (last 12mo avg)
+0.8 pts
Openings rate minus hires rate. Positive = postings outpacing hires.
Prof/Biz Services: same gap (last 12mo avg)
+0.9 pts
Pre-2020, this sector’s hires rate typically ran ABOVE openings.
H-1B tech volume vs JOLTS tech hires, latest
101 vs 92
Mar 2026 index values (Jan 2020 = 100 each)
Openings rate vs. hires rate, by sector
If openings run persistently above hires, postings aren’t converting into hires at the historical rate. Pre-2020, hires typically ran above openings in both sectors below — that relationship has flipped since.
Information
Professional & Business Services
Openings rate
Hires rate
H-1B tech hiring volume vs. JOLTS tech-sector hires (indexed, Jan 2020 = 100)
JOLTS tech-sector hires (indexed)
H-1B tech LCA volume (indexed)
H-1B volume = certified LCAs for Computer & Mathematical occupations, by decision month (DOL disclosure data). JOLTS = combined Hires level, Information + Professional/Business Services (BLS). Both indexed to their own Jan 2020 value so two different-unit series can share one axis.
Oct-Nov 2025 spike/dip: the Oct 2025 federal lapse in appropriations paused DOL case processing; decisions backlogged and were pushed through in November once government reopened. Read that pair of months as one disrupted period, not real volume swings.