National Occupational Estimates 2023
This dataset provides occupational staffing patterns and proportional estimates across sub-sectors tracked by the US Energy Employment Report (USEER), including Advanced Natural Gas, Bioenergy, CHP, Coal, Geothermal, Land-Based Wind, Low-Impact Hydro, Natural Gas, Nuclear, Oil, Offshore Wind, Solar PV, and Traditional Hydro. The data are designed to support accurate prediction of occupational impacts from energy job creation across 76 USEER sub-technologies and their associated value chains.
Occupational proportions were derived through a two-track methodology. For sub-technologies where industry staffing is well-characterized by public sources, the research team mapped relevant 6-digit NAICS codes - weighted by energy activity - to Bureau of Labor Statistics (BLS) Industry-Occupation Matrix data to determine occupational incidence by value chain. Where 6-digit NAICS detail was unavailable, the nearest 4- or 5-digit equivalent was substituted. For sub-technologies requiring greater precision - including construction, installation, manufacturing, operations and maintenance in electric power generation, and construction activities in energy efficiency - BW Research conducted primary proprietary research with 1,095 industry stakeholders to establish staffing patterns.
Baseline occupational estimates were produced by applying 2022 employment figures from the 2023 USEER across nine value chain categories (agriculture, mining and extraction, utilities, construction, manufacturing, wholesale trade, pipeline transportation, professional and business services, and other services) to the sub-technology-level staffing patterns. These estimates serve as the foundation for a forthcoming Workforce Needs Assessment, which will be updated with 2023 employment data upon publication of the 2024 USEER.
Citation Formats
TY - DATA
AB - This dataset provides occupational staffing patterns and proportional estimates across sub-sectors tracked by the US Energy Employment Report (USEER), including Advanced Natural Gas, Bioenergy, CHP, Coal, Geothermal, Land-Based Wind, Low-Impact Hydro, Natural Gas, Nuclear, Oil, Offshore Wind, Solar PV, and Traditional Hydro. The data are designed to support accurate prediction of occupational impacts from energy job creation across 76 USEER sub-technologies and their associated value chains.
Occupational proportions were derived through a two-track methodology. For sub-technologies where industry staffing is well-characterized by public sources, the research team mapped relevant 6-digit NAICS codes - weighted by energy activity - to Bureau of Labor Statistics (BLS) Industry-Occupation Matrix data to determine occupational incidence by value chain. Where 6-digit NAICS detail was unavailable, the nearest 4- or 5-digit equivalent was substituted. For sub-technologies requiring greater precision - including construction, installation, manufacturing, operations and maintenance in electric power generation, and construction activities in energy efficiency - BW Research conducted primary proprietary research with 1,095 industry stakeholders to establish staffing patterns.
Baseline occupational estimates were produced by applying 2022 employment figures from the 2023 USEER across nine value chain categories (agriculture, mining and extraction, utilities, construction, manufacturing, wholesale trade, pipeline transportation, professional and business services, and other services) to the sub-technology-level staffing patterns. These estimates serve as the foundation for a forthcoming Workforce Needs Assessment, which will be updated with 2023 employment data upon publication of the 2024 USEER.
AU - Wegner Guilfoyle, Kristin
DB - Open Energy Data Initiative (OEDI)
DP - Open EI | National Laboratory of the Rockies
DO -
KW - energy
KW - power
KW - occupational staffing patterns
KW - workforce
KW - 2023
KW - data
KW - processed data
KW - estimate
KW - staffing
KW - USEER
KW - occupational
LA - English
DA - 2026/04/13
PY - 2026
PB - National Laboratory of the Rockies (NLR)
T1 - National Occupational Estimates 2023
UR - https://data.openei.org/submissions/8660
ER -
Wegner Guilfoyle, Kristin. National Occupational Estimates 2023. National Laboratory of the Rockies (NLR), 13 April, 2026, Open Energy Data Initiative (OEDI). https://data.openei.org/submissions/8660.
Wegner Guilfoyle, K. (2026). National Occupational Estimates 2023. [Data set]. Open Energy Data Initiative (OEDI). National Laboratory of the Rockies (NLR). https://data.openei.org/submissions/8660
Wegner Guilfoyle, Kristin. National Occupational Estimates 2023. National Laboratory of the Rockies (NLR), April, 13, 2026. Distributed by Open Energy Data Initiative (OEDI). https://data.openei.org/submissions/8660
@misc{OEDI_Dataset_8660,
title = {National Occupational Estimates 2023},
author = {Wegner Guilfoyle, Kristin},
abstractNote = {This dataset provides occupational staffing patterns and proportional estimates across sub-sectors tracked by the US Energy Employment Report (USEER), including Advanced Natural Gas, Bioenergy, CHP, Coal, Geothermal, Land-Based Wind, Low-Impact Hydro, Natural Gas, Nuclear, Oil, Offshore Wind, Solar PV, and Traditional Hydro. The data are designed to support accurate prediction of occupational impacts from energy job creation across 76 USEER sub-technologies and their associated value chains.
Occupational proportions were derived through a two-track methodology. For sub-technologies where industry staffing is well-characterized by public sources, the research team mapped relevant 6-digit NAICS codes - weighted by energy activity - to Bureau of Labor Statistics (BLS) Industry-Occupation Matrix data to determine occupational incidence by value chain. Where 6-digit NAICS detail was unavailable, the nearest 4- or 5-digit equivalent was substituted. For sub-technologies requiring greater precision - including construction, installation, manufacturing, operations and maintenance in electric power generation, and construction activities in energy efficiency - BW Research conducted primary proprietary research with 1,095 industry stakeholders to establish staffing patterns.
Baseline occupational estimates were produced by applying 2022 employment figures from the 2023 USEER across nine value chain categories (agriculture, mining and extraction, utilities, construction, manufacturing, wholesale trade, pipeline transportation, professional and business services, and other services) to the sub-technology-level staffing patterns. These estimates serve as the foundation for a forthcoming Workforce Needs Assessment, which will be updated with 2023 employment data upon publication of the 2024 USEER.},
url = {https://data.openei.org/submissions/8660},
year = {2026},
howpublished = {Open Energy Data Initiative (OEDI), National Laboratory of the Rockies (NLR), https://data.openei.org/submissions/8660},
note = {Accessed: 2026-04-16}
}
Details
Data from Apr 13, 2026
Last updated Apr 15, 2026
Submitted Apr 13, 2026
Organization
National Laboratory of the Rockies (NLR)
Contact
Kristin Wegner Guilfoyle
Authors
Research Areas
Keywords
energy, power, occupational staffing patterns, workforce, 2023, data, processed data, estimate, staffing, USEER, occupationalDOE Project Details
Project Name Energy Workforce Needs Assessment (EWNA)
Project Number 53954

