US initial jobless claims, weekly

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Weekly US initial jobless-claims intelligence panel, 1967-01-07 onward: initial claims for unemployment insurance (FRED ICSA, U.S. Employment and Training Administration, seasonally adjusted, weekly ending Saturday, number of claims, redistributed keyless via FRED fredgraph.csv). Carries the trailing 4-week average (the standard ICSA read), 1-week and 52-week changes (levels and percents), the change of the 4-week average, a trailing 52-week z-score (the layoff speedometer), and an elevated_flag marking a labor-softening watch when the 52-week percent change reaches +15%. One row per Saturday x USA; in-window nulls fail loudly, never imputed. Who joins this: employment teams join hiring plans on year_week + country_code and use the 4-week average / elevated_flag as layoff-regime features; consumer-spending models use the z-score as the income-risk gauge.

Source: US Initial Jobless-Claims Intelligence (FRED, keyless)
Rows: 3,116
Columns: 14
Source cadence: Weekly
Last refreshed: Sep 30, 2026
Theme: labor

Column	Type	Description
week_date	date	Saturday ending the claims reference week (ICSA is weekly, ending Saturday). (unit: date)
year_week	string	ISO calendar week as YYYY-Www (panel join key). (unit: string)
country	string	Country name (shared normalization layer). (unit: string)
country_code	string	ISO 3166-1 alpha-3 country code (USA). (unit: string)
initial_claims	float	Initial claims for unemployment insurance (FRED ICSA; U.S. Employment and Training Administration, seasonally adjusted). (unit: number of claims)
claims_4w_ma	float	Trailing 4-week average of initial claims — the standard ICSA read (null for the first 3 panel weeks). (unit: number of claims)
claims_wow	float	1-week change in initial claims (null for the first panel week). (unit: number of claims)
claims_wow_pct	float	1-week percent change in initial claims (null for the first panel week). (unit: percent)
claims_4w_ma_wow	float	1-week change of the 4-week average — the layoff-turn gauge (null until the 4-week average has two observations). (unit: number of claims)
claims_yoy	float	52-week change in initial claims (null for the first panel year). (unit: number of claims)
claims_yoy_pct	float	52-week percent change in initial claims (null for the first panel year). (unit: percent)
claims_z_52w	float	Z-score of initial claims vs the trailing 52-week mean and sample standard deviation (null until 20 observations) — the layoff speedometer. (unit: standard deviations)
elevated_flag	integer	1 when the 52-week percent change is at least +15% (documented fixed cut: the labor-softening watch), else 0 (warm-up weeks carry 0: no YoY basis). (unit: flag)
row_hash	string	Deterministic 16-hex sha256 of year_week + the claims level (idempotency key). (unit: string)

First 10 sample rows — a preview, not the complete dataset.

week_date	year_week	country	country_code	initial_claims	claims_4w_ma	claims_wow	claims_wow_pct	claims_4w_ma_wow	claims_yoy	claims_yoy_pct	claims_z_52w	row_hash
1967-01-07	1967-W01	United States	USA	208,000	—	—	—	—	—	—	—	e54cbc94b2a34a0a
1967-01-14	1967-W02	United States	USA	207,000	—	-1,000	-0.481	—	—	—	—	77d49ae9b3e2b0d2
1967-01-21	1967-W03	United States	USA	217,000	—	10,000	4.831	—	—	—	—	b245da677b3502b4
1967-01-28	1967-W04	United States	USA	204,000	209,000	-13,000	-5.991	—	—	—	—	e73a2018fc2d7be6
1967-02-04	1967-W05	United States	USA	216,000	211,000	12,000	5.882	2,000	—	—	—	aa2aa5d2383d9eda
1967-02-11	1967-W06	United States	USA	229,000	216,500	13,000	6.019	5,500	—	—	—	dad9a7599dae6d1f
1967-02-18	1967-W07	United States	USA	229,000	219,500	0	0	3,000	—	—	—	d8c2c92c661a861c
1967-02-25	1967-W08	United States	USA	242,000	229,000	13,000	5.677	9,500	—	—	—	18566e3975e20d39
1967-03-04	1967-W09	United States	USA	310,000	252,500	68,000	28.099	23,500	—	—	—	91614284a387d19a
1967-03-11	1967-W10	United States	USA	241,000	255,500	-69,000	-22.258	3,000	—	—	—	be9fb7815f305cbc

Profiled Sep 30, 2026 from snapshot

Measured

Completeness: 99.7%
Rows: 3,116
Columns: 14
Columns with gaps: 7

Rows per yearweek_date · 1967–2026 · 60 years

19672026

Column	Missing	Distinct	Range	Distribution
week_datedate	0%	3,069	Jan 7, 1967 → Sep 19, 2026	—
year_weekvarchar	0%	3,605	—	1967-W011 1967-W021 1967-W031
countryvarchar	0%	1	—	United States3,116
country_codevarchar	0%	1	—	USA3,116
initial_claimsdouble	0%	478	162,000 → 6,137,000median 338,000	61 outside 1st–99th percentile
claims_4w_madouble	0.1%	1,238	179,000 → 5,288,250median 338,000	64 outside 1st–99th percentile
claims_wowdouble	0.03%	131	-1,268,000 → 3,032,000median -1,000	63 outside 1st–99th percentile
claims_wow_pctdouble	0.03%	2,445	-25 → 967.4median -0.2353	64 outside 1st–99th percentile
claims_4w_ma_wowdouble	0.13%	203	-835,250 → 1,482,250median -250	63 outside 1st–99th percentile
claims_yoydouble	1.7%	683	-5,492,000 → 5,941,000median -10,000	62 outside 1st–99th percentile
claims_yoy_pctdouble	1.7%	3,375	-89.49 → 3,031median -3.36	62 outside 1st–99th percentile
claims_z_52wdouble	0.61%	3,081	-3.29 → 7.07median -0.3924	62 outside 1st–99th percentile
elevated_flagbigint	0%	2	0 → 1median 0
row_hashvarchar	0%	3,036	—	000d96d7faa407671 0015a34ca820bb801 002f84f2d66188251

Point any LLM at the metadata endpoint — the documentation above is machine-readable too (JSON-LD + Croissant).

cURL

curl "https://datazimuts.com/v1/datasets/fred_labor_claims_intel/us_initial_claims_weekly" | jq '{title, rows, columns_count, license}'

Python

import requests

ds = requests.get("https://datazimuts.com/v1/datasets/fred_labor_claims_intel/us_initial_claims_weekly").json()
print(ds["title"], ds["rows"], "rows")

# Sample rows for an LLM context window
for row in ds.get("sample_rows", [])[:5]:
    print(row)

API endpoint: https://datazimuts.com/v1/datasets/fred_labor_claims_intel/us_initial_claims_weekly

Tip: fetch /llms.txt for the full machine-readable catalog.

Cite this snapshot

Pinned to snapshot 20260930T101342Z-73dfe9b3c2fe and its content hash, so readers get exactly the data you used.

APA

US Initial Jobless-Claims Intelligence (FRED, keyless). (2026). US initial jobless claims, weekly [Data set, snapshot 20260930T101342Z-73dfe9b3c2fe, sha256 73dfe9b3c2fe]. Datazimuts. Retrieved 2026-09-30, from https://datazimuts.com/en/datasets/fred_labor_claims_intel/us_initial_claims_weekly?snapshot=20260930T101342Z-73dfe9b3c2fe

BibTeX

@misc{dz_fred_labor_claims_intel_us_initial_claim_73dfe9b3,
  title        = {{US initial jobless claims, weekly}},
  author       = {{US Initial Jobless-Claims Intelligence (FRED, keyless)}},
  year         = {2026},
  publisher    = {Datazimuts},
  howpublished = {\url{https://datazimuts.com/en/datasets/fred_labor_claims_intel/us_initial_claims_weekly?snapshot=20260930T101342Z-73dfe9b3c2fe}},
  note         = {Snapshot 20260930T101342Z-73dfe9b3c2fe, sha256 73dfe9b3c2fe065889c8b4c3c6cccdcad4ad31146b33d8bb903a29e6640758f1; accessed 2026-09-30}
}

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US initial jobless claims, weekly

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