APProjects/us-layoffs-by-industry-sector-warn-act

US layoffs by industry sector — 60,945 WARN Act notices, 1988-2026, sector per employer

Rebuilt 2026-09-15. 32,036 of 60,945 dated notices (52.6%; 61,320 on record, 375 lack a usable date) carry a sector; the rest are unclassified and stay in every total. In 2026 so far the largest sector by reported workers is Logistics, transport & warehousing (23,761 workers, 193 notices); in the last 90 days it is Food & beverage manufacturing, agriculture (7,728 workers).

No state WARN portal publishes an industry field — none of the 48 does, so the flagship archive has no NAICS or sector column to filter on. This dataset assigns one by reading the resolved employer name against an auditable rule table (19 sectors, 2441 patterns, first match wins), and redoes it every morning as new employers file. Every row says which pattern fired, so any assignment can be checked or disputed.

Read this before quoting a number

• Sector comes from the NAME, nothing else. "St. John Hospital" is healthcare; "ICU Medical" (a device maker) is also healthcare, because the table reads medical. A staffing agency filing for a factory closure is staffing. If you need NAICS precision, this is not it.
• unclassified is a real row, not an error (47.4% of notices). Names like "Acme" or a bare surname give no sector, and we do not guess. Sector shares are computed over ALL notices, so shares never sum to 100 among named sectors.
• Manual audit: on 2026-09-12 a human read 60 randomly-drawn classified rows (python3 hf_sectors.py --audit-sample) and found 4 with the wrong sector for the employer named (one random row per employer (seed 41), graded by hand after the rule table was frozen; the 4 misses were a produce grower named 'Church Brothers' (read as a church), a hospital food-service contractor (read as healthcare), a plumbing-fixtures maker (read as construction) and a residential community called 'Village of ...' (read as a municipality)). The rule table changes → the audit is redone and this line updated. Removed-for-precision tokens are listed in hf_sectors.py (GENERIC).
• Coverage is uneven before ~2020. Most state portals begin between 2010 and 2023; a sector's early-year count is a count among the states we hold, not the country. The states_with_notices column on by_year says how many states fed that cell.
• workers_reported sums employees_affected as filed. Portals do not say whether a second notice for the same site is cumulative, so rolling programmes can be overstated.
• Employer names are resolved by alias_merge.py (spellings, not corporate parents).

2026 so far, by sector

sector	notices	workers reported
Unclassified (name gives no sector)	1,351	121,269
Logistics, transport & warehousing	193	23,761
Healthcare & medical	219	18,436
Technology, software & electronics	141	17,264
Food & beverage manufacturing, agriculture	89	15,683
Hotels, restaurants, food service & leisure	149	11,457
Retail	125	10,638
Aerospace, defense & airlines	43	10,279
Finance, insurance & real estate	130	7,585
Education	113	6,457
Manufacturing (other)	89	5,840
Media, publishing & telecom	43	4,149
Automotive & auto parts	18	3,831
Pharma, biotech & life sciences	47	3,818
Energy, utilities & mining	41	3,020
Government & non-profit	21	1,201
Construction & building trades	11	1,121
Facility, security & janitorial services	12	603
Call centers & outsourcing	6	548
Staffing & employment services	7	507

Files

file	rows	one row per
data/notices_by_sector.csv	60,945	notice — id joins to the flagship archive; sector, sector_label, sector_rule
data/sector_by_year.csv	690	year × sector — notices, workers, distinct employers, states, share of that year
data/sector_by_state_year.csv	6,527	state × year × sector

The sectors

• call_center_bpo — Call centers & outsourcing: 256 notices, 46,159 workers on file
• staffing — Staffing & employment services: 199 notices, 35,007 workers on file
• aerospace_defense_airlines — Aerospace, defense & airlines: 1,548 notices, 307,639 workers on file
• automotive — Automotive & auto parts: 1,315 notices, 184,299 workers on file
• pharma_biotech — Pharma, biotech & life sciences: 815 notices, 77,057 workers on file
• healthcare — Healthcare & medical: 3,538 notices, 358,987 workers on file
• hospitality_food_service — Hotels, restaurants, food service & leisure: 6,324 notices, 915,224 workers on file
• retail — Retail: 4,321 notices, 427,305 workers on file
• education — Education: 1,163 notices, 90,413 workers on file
• government_nonprofit — Government & non-profit: 710 notices, 115,638 workers on file
• finance_insurance — Finance, insurance & real estate: 2,079 notices, 178,576 workers on file
• tech_software — Technology, software & electronics: 1,732 notices, 191,402 workers on file
• media_telecom — Media, publishing & telecom: 842 notices, 101,435 workers on file
• logistics_transport — Logistics, transport & warehousing: 1,882 notices, 226,255 workers on file
• energy_utilities_mining — Energy, utilities & mining: 1,277 notices, 138,323 workers on file
• facility_services — Facility, security & janitorial services: 228 notices, 18,359 workers on file
• construction — Construction & building trades: 300 notices, 37,203 workers on file
• food_beverage_manufacturing — Food & beverage manufacturing, agriculture: 1,280 notices, 173,217 workers on file
• manufacturing — Manufacturing (other): 2,227 notices, 257,044 workers on file

Where the rows come from

The free, CC BY 4.0 normalized WARN archive rebuilt daily from 48 state portals (site, GitHub). Related cuts of the same archive: the largest layoff events and layoffs per capita by state.

Get told the day an employer on your list files, in any of the 48 states: free 30-day watch (no card) or WARN Watch, $49/year for a list of up to 500 employers.

Automated publisher (APProjects). Not affiliated with any government agency. Verify critical figures against the state source linked from each notice.

A layoff record you can audit, not just download

This dataset is one cut of a single daily rebuild: 61,320 US WARN Act layoff notices from 48 state agencies, 1988 to today, one schema, no login, no delay, CC BY 4.0. Snapshot as of 2026-09-15; the files above are rebuilt every day, so the live count is the truth.

Several projects publish a current WARN scrape and two of them carry more rows than we do. None of them publish what the records used to say:

• 616 observed changes to already-published notices, logged daily since 2026-08-31. data/revisions.csv records every field that differed between two consecutive daily builds — employee counts, effective dates, notice types, company names — with the old value, the new value and the date we saw it. We publish the observation and not the cause: a change is equally explained by the agency amending the notice or by our own parser improving, and we do not guess which (see data/revisions.README.txt). A scrape that starts tomorrow cannot backfill any of it; it only exists if someone was watching.
• 6,799 notices whose state agency page no longer lists them. Agencies take notices down. We keep them, flagged as archive-only, so a count you ran last year still reconciles.
• Point-in-time employer identity. The ticker crosswalk resolves a filer to the company as it existed at the time of the notice — Kmart, Sears Holdings, Symantec — not to whatever is on today's ticker file.

If you have to defend a number to an editor, a referee or a compliance reviewer, that provenance layer is the part you cannot rebuild yourself. How to cite this dataset →

Look something up right now — free, no signup, nothing to install. Check any employer or state against the last 180 days → It runs in your browser against these same files.

Building something with it? The same files are a free HTTP API — JSON and CSV, no key, no signup, access-control-allow-origin: * so fetch() works from a browser: endpoints, schema and curl examples →

Need one industry only? The same filings, cut by an auditable employer-name rule (each row keeps the rule that fired): tech companies · hospitals & healthcare · retail store closings · restaurants & hotels · factory & plant closings · all 20 sectors.

Or have it watch a list for you. Coming back to look is the part a CSV cannot do. WARN Watch — $49 for a year, one payment, nothing auto-renews, 14-day refund, no login: up to 500 employer names plus whole states, matched on every daily refresh, delivered to a private alert page + calendar (.ics) + RSS + an optional Slack / Discord / Teams webhook. Every alert carries that employer's whole filing history from the archive, which a keyword rule on an RSS feed cannot see. There is no built-in email — we do not claim one.

• See a real alert page before paying · what you get
• Try it free for 30 days, no card · Buy — $49/year

Not deciding today? Join the update list → — used only for a state added, a column change or a tier change; nothing promotional. The list is shared across APProjects datasets, holds an email address only, is run by Gumroad, and any message unsubscribes you. Rather give no address at all? Watch the repo's releases — GitHub notifies you on every daily republish, and a new state or changed field is in those notes the day it lands.

Reaching a human. WARN Feed is published by APProjects, an automated data publisher — that is stated plainly rather than dressed up. Corrections, coverage gaps, schema questions and refund requests all go here and are read: open an issue. Payments are handled by Gumroad as merchant of record, so an invoice can carry your company name.

Source, scrapers and methodology · the 48-state site

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