economy_industry_group_employment_county_year
9 HFAW industry groups + 3 AI exposure aggregate shares, county-year (E4). Private sector only (own_code='5'). Tier A with suppression caveat. See README for group definitions and national validation ranges.
tier aadmin_record
overview
overview
3,207 counties. Private sector only (own_code='5'). 9 HFAW industry groups + 3 AI exposure aggregates.
current vintage — 2024
history — Recomputable from QCEW back to 2001 (NAICS-based)
provenance
source & licensing
authority
U.S. Bureau of Labor Statistics
dataset
Quarterly Census of Employment and Wages (QCEW) — 9 industry groups (2024)
source url
methodology
license
Public domain (U.S. Federal Government work)
citation
U.S. Bureau of Labor Statistics. QCEW - derived 9-group industry aggregation, 2024.
schema
fields
| name | type | definition |
|---|---|---|
| construction_employment | int64 · workers | Estimated number of private-sector employees in the construction industry group in the county for the reference year, sourced from QCEW. Subject to BLS suppression; suppressed cells are null. |
| construction_employment_share | float64 · share (0–1) | Construction industry employees as a share of total classified private-sector employment (construction_employment / total_classified_employment). Higher values may reflect active development activity or cyclical construction demand in the county. |
| 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. |
| education_private_employment | int64 · workers | Estimated number of private-sector employees in the private education industry group in the county for the reference year, sourced from QCEW. Excludes public school and government-operated educational institutions. Subject to BLS suppression; suppressed cells are null. |
| education_private_employment_share | float64 · share (0–1) | Private education employees as a share of total classified private-sector employment (education_private_employment / total_classified_employment). Reflects the private education sector's contribution to the local job base. |
| finance_employment | int64 · workers | Estimated number of private-sector employees in the finance industry group (e.g., finance, insurance, real estate) in the county for the reference year, sourced from QCEW. Subject to BLS suppression; suppressed cells are null. |
| finance_employment_share | float64 · share (0–1) | Finance industry employees as a share of total classified private-sector employment (finance_employment / total_classified_employment). Higher values indicate greater local specialization in financial services. |
| healthcare_employment | int64 · workers | Estimated number of private-sector employees in the healthcare industry group in the county for the reference year, sourced from QCEW. Subject to BLS suppression; suppressed cells are null. |
| healthcare_employment_share | float64 · share (0–1) | Healthcare industry employees as a share of total classified private-sector employment (healthcare_employment / total_classified_employment). Higher values indicate greater local reliance on healthcare as an employment base. |
| high_or_higher_ai_exposure_share | float64 · share (0–1) | Share of total classified private-sector employment in occupations rated as having high or higher AI exposure, based on occupation-level AI exposure scores mapped to QCEW industry composition. Higher values indicate a larger fraction of local jobs at elevated risk of AI-driven task displacement. |
| knowledge_economy_employment | int64 · workers | Estimated number of private-sector employees in the knowledge economy industry group (e.g., professional/technical services, information) in the county for the reference year, sourced from QCEW. Subject to BLS suppression for low-employment counties; suppressed cells are null. |
| knowledge_economy_employment_share | float64 · share (0–1) | Knowledge economy employees as a share of total classified private-sector employment (knowledge_economy_employment / total_classified_employment). Higher values indicate a greater concentration of knowledge-sector jobs in the local economy. |
| logistics_retail_employment | int64 · workers | Estimated number of private-sector employees in the logistics and retail industry group (e.g., wholesale trade, retail trade, transportation, warehousing) in the county for the reference year, sourced from QCEW. Subject to BLS suppression; suppressed cells are null. |
| logistics_retail_employment_share | float64 · share (0–1) | Logistics and retail employees as a share of total classified private-sector employment (logistics_retail_employment / total_classified_employment). Higher values indicate greater local concentration in distribution-oriented or consumer-facing industries. |
| manufacturing_employment | int64 · workers | Estimated number of private-sector employees in the manufacturing industry group in the county for the reference year, sourced from QCEW. Subject to BLS suppression; suppressed cells are null. |
| manufacturing_employment_share | float64 · share (0–1) | Manufacturing employees as a share of total classified private-sector employment (manufacturing_employment / total_classified_employment). Higher values indicate a more manufacturing-intensive local economy. |
| medium_or_higher_ai_exposure_share | float64 · share (0–1) | Share of total classified private-sector employment in occupations rated as having medium, high, or higher AI exposure; a superset of high_or_higher_ai_exposure_share. Higher values indicate broader potential AI impact across the local workforce, including moderately exposed occupations. |
| personal_local_services_employment | int64 · workers | Estimated number of private-sector employees in the personal and local services industry group (e.g., accommodation, food services, arts, entertainment, personal care) in the county for the reference year, sourced from QCEW. Subject to BLS suppression; suppressed cells are null. |
| personal_local_services_employment_share | float64 · share (0–1) | Personal and local services employees as a share of total classified private-sector employment (personal_local_services_employment / total_classified_employment). Higher values indicate a local economy oriented toward hospitality, food service, and consumer personal services. |
| resource_economy_employment | int64 · workers | Estimated number of private-sector employees in the resource economy industry group (e.g., agriculture, forestry, fishing, mining, oil and gas) in the county for the reference year, sourced from QCEW. Subject to BLS suppression; suppressed cells are null. |
| resource_economy_employment_share | float64 · share (0–1) | Resource economy employees as a share of total classified private-sector employment (resource_economy_employment / total_classified_employment). Higher values indicate greater dependence on extractive or agricultural industries. |
| state_idkey | string | 2-character FIPS code identifying the state.Part of primary key. Joins dim.states on state_id. |
| total_classified_employment | int64 · workers | Sum of private-sector employees across all 9 HFAW industry groups for the county-year. Serves as the denominator for all employment share calculations; excludes any QCEW-reported employment in industries not assigned to one of the 9 groups. |
| 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_industry_employment_county_year_naics on (county_id, year)
economy_industrial_concentration_county_year on (county_id, year)
usage
how to use this table
method
Aggregates QCEW NAICS-2 employment into 9 HFAW groups: manufacturing, knowledge_economy, finance, healthcare, education_private, resource_economy, construction, logistics_retail, personal_local_services. Three AI-exposure aggregates from Felten-Raj-Seamans scores. own_code='5' filters to private sector.
do not use for
Government employment shares (excluded - see government_employment_share in employment_levels); cross-year comparison with NAICS revision year (small reclassifications); national-level AI exposure benchmarking (AI exposure scores are county-relative aggregates).
known issues
Sector shares sum to ~1.20 (not 1.00) due to government double-counting noted in scorecard_v4 issues. Investigate before using as denominator.
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last updated · Jul 7, 2026