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Clean Energy Job Quality and Education Data

This dataset contains data used in the Urban publication Who Has Access to Good Clean Energy Jobs? The dataset contains Standard Occupational Classification codes and titles for clean energy occupations, the number of jobs in each occupation, relevant clean energy sectors, individual measures related to job quality as well as an overall job quality score, and the typical level of education required at entry.

The research team used the work of the National Center for O*NET Development to identify occupations that will require enhanced skills, experience increased demand, or emerge in the three select clean energy sectors: energy efficiency, renewable-energy generation, and green construction. Job codes and job titles within those sectors come from the O*NET-SOC Taxonomy.

Job quality measures come from a previous Urban Institute publication titled Job Quality and Race and Gender Equity, which measures 11 elements of job quality, including wages and benefits, health and safety, union coverage, and stability. Overall job quality categories were calculated by summing the number of elements for which a particular job scored as “better than average”. High-quality jobs are those that received a score of 8 or higher. Medium-quality ratings correspond to scores of 5-7, and scores lower than that indicate low-quality jobs. Education requirements come from the U.S. Bureau of Labor Statistics’ Employment Projections program.

These data are combined with national and local demographic data from the 2022 American Community Survey Public Use Microdata Sample (ACS PUMS) in order to generate place-based statistics, accessed through IPUMS. The research team uses Geocorr from the Missouri Census Data Center to map each Public Use Microdata Area (PUMA) to in the census to the eight cities of interest based on the proportion of the population in a PUMA that lives in areas that overlap with the city. These proportions are combined with replicate weights provided in the American Community Survey Public Use Microdata Sample (PUMS) to determine how much weight to assign each observation in the sample.

These fields are compatible with DCAT, an RDF vocabulary designed to facilitate interoperability between data catalogs published on the Web.
Release Date
Contact Name
Urban Institute
Contact Email
Public Access Level
These fields are specific to Urban Institute.
Data Dictionary Files
Units of Observation
Data Quality or Limitations

Job-quality scores and the job counts used to weight results are not specific to clean-energy sectors, but rather apply to all jobs in a given occupation. For example, mechanical engineers are important occupations for both renewable energy and green construction, but the data on them is for all mechanical engineers—no matter what industry or sector they work in. For this reason, the mix of occupations within each clean-energy sector may differ from the overall mix in the labor market, and the quality of jobs within these sectors may also differ.

Citation Requirements

Urban Institute. 2024. Clean Energy Job Quality and Education Data . Accessible from Data originally sourced from [node:field_original_data_source], developed at the Urban Institute, and made available under the ODC-BY 1.0 Attribution License.