US state wage-pressure intelligence (BLS CES, monthly)
US state wage-pressure intelligence from the BLS Current Employment Statistics state program bulk flat files (keyless, U.S. public domain): 50 states plus DC and Puerto Rico, monthly January 2007 to the latest published month, NOT seasonally adjusted. Core measures: average hourly earnings of all private employees (dollars) and average weekly hours. Method: the closed 104-series slice (2 measures x 52 areas) is resolved from sm.series; every per-state data file is streamed and only wanted series are kept; M13 annual averages are dropped; any in-window gap, duplicate, or non-positive value fails the ingest loudly. Derived signals per state: year-over-year percent change of earnings and hours (the seasonal proxy for unadjusted data), month-over-month change of earnings, within-month national ranks of earnings and hours growth, a documented 0-100 wage_pressure_score (fixed weights: 50% earnings-YoY level vs the state's own history, 30% clipped YoY direction, 20% clipped hours direction), within-month national quintile tier of the score, and flags for rapid wage growth (YoY >= 5%), wage decline, hours contraction, and 12-month record earnings. Use as prediction features: join to customers/orders/leads by state_code + month for demand, churn, and lead-scoring models — local wage growth leads changes in discretionary spending and subscription affordability, while contracting hours lead labor-market softening. Caveats: the data are not seasonally adjusted so always use YoY (not MoM) signals; the score is relative to each state's own history, not an absolute cross-state level comparison; the latest 1-2 months are routinely revised.
Les titres et les descriptions proviennent des sources de données, en anglais.
- Lignes
- 12 197
- Colonnes
- 23
- Cadence de la source
- Mensuelle
- Dernière actualisation
- 29 sept. 2026
- Thème
- labor
| Colonne | Type | Description |
|---|---|---|
| month | string | Reference month (first day, YYYY-MM-DD). |
| year | integer | Reference year. |
| month_num | integer | Reference month number (1-12). |
| country | string | Country name (United States). |
| country_code | string | ISO alpha-3 country code (USA). |
| state_fips | string | 2-digit state FIPS code. |
| state_code | string | USPS 2-letter state/territory code. |
| state_name | string | State / district / territory name. |
| avg_hourly_earnings_usd | float | Average hourly earnings of all private employees, dollars (BLS CES data type 03, NOT seasonally adjusted). |
| avg_weekly_hours | float | Average weekly hours of all private employees (BLS CES data type 02, NOT seasonally adjusted). |
| earn_yoy_pct | float | 12-month percent change of average hourly earnings — the seasonal proxy for unadjusted data. |
| hours_yoy_pct | float | 12-month percent change of average weekly hours — the seasonal proxy for unadjusted data. |
| earn_mom_pct | float | Month-over-month percent change of average hourly earnings (use with care: not seasonally adjusted). |
| earn_yoy_rank | integer | Within-month national rank of earn_yoy_pct across states (1 = fastest wage growth; ties share the rank). |
| hours_yoy_rank | integer | Within-month national rank of hours_yoy_pct across states (1 = fastest hours growth; ties share the rank). |
| wage_pressure_score | float | 0-100 gauge of how hot the state labor market is running vs its own history: 100 * (0.5 * min-max earnings-YoY level + 0.3 * clipped-YoY direction + 0.2 * clipped-hours direction), fixed weights documented in the connector. |
| pressure_tier | integer | Within-month national quintile of wage_pressure_score (1 = coolest fifth, 5 = hottest fifth). |
| rapid_wage_growth_flag | integer | 1 when earn_yoy_pct >= 5.0 (rapid wage growth). |
| wage_decline_flag | integer | 1 when earn_yoy_pct < 0 (nominal wage decline). |
| hours_contraction_flag | integer | 1 when hours_yoy_pct < 0 (hours contracting — labor-market softening signal). |
| record_earnings_12m_flag | integer | 1 when average hourly earnings equal the trailing 12-month maximum. |
| row_hash | string | Content hash (sha256, 16 hex) over state, month, and core measures. |
| source_url | string | Canonical BLS CES state program page. |
10 premières lignes d’exemple — un aperçu, pas le jeu de données complet.
| month | year | month_num | country | country_code | state_fips | state_code | state_name | avg_hourly_earnings_usd | avg_weekly_hours | earn_yoy_pct | hours_yoy_pct | earn_mom_pct | earn_yoy_rank | hours_yoy_rank | wage_pressure_score | pressure_tier | rapid_wage_growth_flag | wage_decline_flag | hours_contraction_flag | record_earnings_12m_flag | row_hash | source_url |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2007-01-01 | 2 007 | 1 | United States | USA | 01 | AL | Alabama | 19,24 | 36,2 | — | — | — | — | — | — | — | 0 | 0 | 0 | 1 | c4dfd3ca0ad9b580 | https://www.bls.gov/sae/ |
| 2007-01-01 | 2 007 | 1 | United States | USA | 02 | AK | Alaska | 25,28 | 34,4 | — | — | — | — | — | — | — | 0 | 0 | 0 | 1 | eede20349bf71b10 | https://www.bls.gov/sae/ |
| 2007-01-01 | 2 007 | 1 | United States | USA | 04 | AZ | Arizona | 19,98 | 35,4 | — | — | — | — | — | — | — | 0 | 0 | 0 | 1 | 5cf819e5f977fc7d | https://www.bls.gov/sae/ |
| 2007-01-01 | 2 007 | 1 | United States | USA | 05 | AR | Arkansas | 15,89 | 33,7 | — | — | — | — | — | — | — | 0 | 0 | 0 | 1 | 0caeaac9197d787f | https://www.bls.gov/sae/ |
| 2007-01-01 | 2 007 | 1 | United States | USA | 06 | CA | California | 25,03 | 33,9 | — | — | — | — | — | — | — | 0 | 0 | 0 | 1 | 4eb8c7bc2f5cb289 | https://www.bls.gov/sae/ |
| 2007-01-01 | 2 007 | 1 | United States | USA | 08 | CO | Colorado | 22,66 | 34,2 | — | — | — | — | — | — | — | 0 | 0 | 0 | 1 | 236a8af9d9434dc5 | https://www.bls.gov/sae/ |
| 2007-01-01 | 2 007 | 1 | United States | USA | 09 | CT | Connecticut | 25,86 | 34 | — | — | — | — | — | — | — | 0 | 0 | 0 | 1 | 90ffe83220ca14a4 | https://www.bls.gov/sae/ |
| 2007-01-01 | 2 007 | 1 | United States | USA | 10 | DE | Delaware | 22,05 | 33,5 | — | — | — | — | — | — | — | 0 | 0 | 0 | 1 | 4669166b2d818f00 | https://www.bls.gov/sae/ |
| 2007-01-01 | 2 007 | 1 | United States | USA | 11 | DC | District of Columbia | 32,94 | 35,7 | — | — | — | — | — | — | — | 0 | 0 | 0 | 1 | d42371567fc35e31 | https://www.bls.gov/sae/ |
| 2007-01-01 | 2 007 | 1 | United States | USA | 12 | FL | Florida | 20,21 | 35,2 | — | — | — | — | — | — | — | 0 | 0 | 0 | 1 | 5b5182c60421fa05 | https://www.bls.gov/sae/ |
- Actuelle
20260929T213025Z-490661404232 · sha256 490661404232…
12 197 lignes · premier instantané
Dirigez n’importe quel LLM vers le point d’accès des métadonnées — la documentation ci-dessus est aussi lisible par machine (JSON-LD + Croissant).
curl "https://datazimuts.com/v1/datasets/bls_state_wage_pressure_intel/us_state_wage_pressure_monthly" | jq '{title, rows, columns_count, license}'import requests
ds = requests.get("https://datazimuts.com/v1/datasets/bls_state_wage_pressure_intel/us_state_wage_pressure_monthly").json()
print(ds["title"], ds["rows"], "rows")
# Sample rows for an LLM context window
for row in ds.get("sample_rows", [])[:5]:
print(row)Point d’accès API : https://datazimuts.com/v1/datasets/bls_state_wage_pressure_intel/us_state_wage_pressure_monthly
Astuce : récupérez /llms.txt pour le catalogue complet lisible par machine.
D’où viennent ces données et ce qui en a été fait. Le travail des autres apparaît sous forme de décomptes ; seuls les projets partagés sont nommés.
Citer cet instantané
Épinglé à l’instantané 20260929T213025Z-490661404232 et à son empreinte, pour que vos lecteurs obtiennent exactement les données utilisées.
U.S. Bureau of Labor Statistics. (2026). US state wage-pressure intelligence (BLS CES, monthly) [Data set, snapshot 20260929T213025Z-490661404232, sha256 490661404232]. Datazimuts. Retrieved 2026-09-30, from https://datazimuts.com/fr/datasets/bls_state_wage_pressure_intel/us_state_wage_pressure_monthly?snapshot=20260929T213025Z-490661404232
@misc{dz_bls_state_wage_pressure_intel_us_state_w_49066140,
title = {{US state wage-pressure intelligence (BLS CES, monthly)}},
author = {{U.S. Bureau of Labor Statistics}},
year = {2026},
publisher = {Datazimuts},
howpublished = {\url{https://datazimuts.com/fr/datasets/bls_state_wage_pressure_intel/us_state_wage_pressure_monthly?snapshot=20260929T213025Z-490661404232}},
note = {Snapshot 20260929T213025Z-490661404232, sha256 49066140423278b638741b605b12976081804575e7ab2ba0a17142cb0af5a3e1; accessed 2026-09-30}
}Intégrer un tableau ou un graphique
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<iframe src="https://datazimuts.com/embed/chart?dataset=bls_state_wage_pressure_intel%2Fus_state_wage_pressure_monthly&lang=fr&theme=auto&snapshot=20260929T213025Z-490661404232&x=year&y=year&agg=avg" title="US state wage-pressure intelligence (BLS CES, monthly)" width="100%" height="380" style="border:0" loading="lazy"></iframe>
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