economy_unemployment_county_year
LAUS annual county unemployment: labor force, employed, unemployed, rate (C2). Tier C (modeled). History 1990-present.
tier cregression_model
overview
overview
All 3,221 counties x 35 years. LAUS modeled monthly with annual averages.
current vintage — 2024 annual averages
history — LAUS: 1976 to present
provenance
source & licensing
authority
U.S. Bureau of Labor Statistics
dataset
Local Area Unemployment Statistics (LAUS) — county annual averages
source url
methodology
license
Public domain (U.S. Federal Government work)
citation
U.S. Bureau of Labor Statistics. Local Area Unemployment Statistics (LAUS), 1990-2024.
schema
fields
| name | type | definition |
|---|---|---|
| country_idkey | string | ISO alpha-2 country code (always 'US' for domestic tables).Part of primary key. |
| county_idkey | string | 5-character FIPS code identifying the county.Part of primary key. Joins dim.counties on county_id. |
| employed | int64 · count | Number of civilians in the county who are employed during the reference year, as estimated by the BLS LAUS program. Higher values indicate a larger employed workforce. |
| labor_force | int64 · count | Total civilian labor force in the county for the reference year, equal to the sum of employed and unemployed persons as estimated by the BLS LAUS program. Higher values indicate a larger working-age population actively participating in the labor market. |
| state_idkey | string | 2-character FIPS code identifying the state.Part of primary key. Joins dim.states on state_id. |
| unemployed | int64 · count | Number of civilians in the county who are unemployed during the reference year, as estimated by the BLS Local Area Unemployment Statistics (LAUS) program. Higher values indicate more labor market slack. |
| unemployment_rate | float64 · percent (0–100) | Share of the civilian labor force that is unemployed, expressed as a percentage. Higher values indicate weaker local labor market conditions. |
| yearkey | int64 | Reference year of the observation.Part of primary key. |
relationships
joins
primary key
county_id, state_id, country_id, year
common joins
dim.geographies on county_id
economy_employment_levels_county_year on (county_id, year)
usage
how to use this table
method
BLS uses signal-extraction model combining CPS state estimates, UI claims, CES employment, and ACS commuting flows to produce county labor force, employment, and unemployment.
do not use for
Single-month change in counties <50k labor force (model volatile); current-month tracking (subject to revision); structural unemployment vs cyclical decomposition.
known issues
Model-based - Tier C reliability. Annual revisions in March can shift recent years materially.
last updated · Jul 7, 2026