Last updated May 1, 2024
With the passage of the 2021 Bipartisan Infrastructure Law (BIL) and the 2022 Inflation Reduction Act (IRA), billions of federal dollars are flowing into communities across the US to invest in clean energy.
This funding will help create new jobs in clean energy, and many communities are working to ensure these jobs are high quality and accessible to people of color and women. However, local data related to the quality of clean-energy jobs and who has access to them is limited.
To help local leaders create the good jobs and equity plans required by many BIL- and IRA-funded programs, we examine the quality of jobs in three clean-energy sectors—energy efficiency, renewable-energy generation, and green construction. We then assess how well people of color and women are positioned to take advantage of these opportunities nationally and in eight select cities.
Clean-Energy Jobs Vary in Terms of Quality and Education Requirements
We 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. Then we classified these occupations using a job-quality index that measures 11 elements of job quality, including wages and benefits, health and safety, union coverage, and stability.
Compared with the overall labor market, we found that a larger share of energy-efficiency and renewable energy–generation jobs are high quality.
The Quality of Energy Efficiency and Renewable Energy-Generation Jobs Tends to Be Higher than in the Overall Labor Market
Share of jobs by sector
Source: Occupational job-quality ratings summing across 11 dimensions of job quality from Job Quality and Race and Gender Equity weighted by total employment from the Occupational Employment and Wage Survey (OEWS).
Notes: High-quality ratings indicate a score of 8 or higher. Medium-quality ratings correspond to scores of 5–7, and scores lower than that indicate low quality.
Next, we looked at the typical level of education required at entry for high- and medium-quality clean-energy jobs. We found that educational barriers to entry are highest for energy efficiency, a sector where more than two-thirds of the good jobs require at least a four-year degree. More than half of high-quality jobs in this sector are in management (52 percent) or engineering and architecture (9 percent). Medium-quality jobs are concentrated in business and financial operations (86 percent).
Most High- and Medium-Quality Jobs in Energy Efficiency Require at Least a Bachelor’s Degree
Share of jobs that require at least a bachelor's degree, by sector
Source: Total employment from the 2022 Occupational Employment and Wage Survey (OEWS) and education requirements from the Employment Projections program.
Notes: High-quality ratings indicate a score of 8 or higher. Medium-quality ratings correspond to scores of 5–7, and scores lower than that indicate low quality.
High- and medium-quality jobs in these sectors that don’t require a bachelor’s degree tend to also have relatively high union coverage. These kinds of jobs are prominent in renewable energy and green construction, and are concentrated in installation, maintenance, and repair as well as construction and extraction occupations.
Many High- and Medium-Quality Jobs in Renewable-Energy Generation and Green Construction Have High Union Coverage and Require Less Education
Share of jobs with high union coverage that don't require a bachelor's degree
Source: Total employment from the 2022 Occupational Employment and Wage Survey (OEWS) and education requirements from the Employment Projections program. Union coverage from the occupational job-quality ratings from Job Quality and Race and Gender Equity.
Notes: High-quality ratings indicate a score of 8 or higher. Medium-quality ratings correspond to scores of 5–7, and scores lower than that indicate low quality.
Explore Access to Clean-Energy Jobs by Race and Ethnicity and Gender
Recent federal investments in clean energy will likely create many high-quality jobs, but will women and people of color have equitable access to them?
Use the drop-down menu below to explore the potential workforce for new jobs in energy efficiency, renewable-energy generation, and green construction and access to high-quality jobs in these sectors nationwide and in eight select cities. For each geography, we explore access among women and the two largest communities of color. In cities where the second largest community of color is less than 15 percent of the workforce, we combine this group with all other communities of color to ensure our results are statistically meaningful.
Across the US, Women and People of Color Will Likely Face Substantial Challenges Accessing High-Quality Clean-Energy Jobs
Jobs in energy efficiency are the most challenging for women and people of color to access. Compared with the other sectors, energy efficiency has the largest share of high-quality jobs and greater educational requirements.
Nationally, and in almost all eight cities, women have inequitable access to clean-energy jobs. They are underrepresented in the potential workforce and in both high- and medium-quality jobs in all three sectors.
Nationally, Black people are underrepresented in all three sectors and have inequitable access to high- and medium-quality clean-energy jobs. But representation varies by city. For example, the experiences of Black people in Chicago, Detroit, and New Orleans follow national trends. However, in Memphis and Minneapolis, Black people have inequitable access to jobs in only one sector, energy efficiency.
Compared with Black workers, the national outlook for Latine workers is more positive. They are well represented in the potential workforce for all three sectors and tend to have equitable access to both high- and medium-quality clean-energy jobs. Our analysis of the potential workforce in Miami—a majority Latine city—mirrors these positive national trends. However, in Fresno, Rochester, and Chicago, Latine workers are underrepresented in the potential workforce for energy-efficiency jobs and have inequitable access to high-quality opportunities in the sector.
Smaller communities of color fare differently depending on the racial and ethnic composition of the city. In majority Black cities like Detroit, Memphis, and New Orleans, communities of color that are less than 15 percent of the population, such as people who are Latine, Asian American or Pacific Islander, or Native American, have equitable access to jobs across clean-energy sectors. However, in Minneapolis, a majority white city where Black people are the largest community of color, smaller communities of color have inequitable access to high-quality jobs in energy efficiency and renewable energy. In majority Latine cities, like Miami and Fresno, additional communities of color are underrepresented in the potential workforce for all three sectors.
To ensure women and communities of color can fully enjoy the economic benefits of new federal investments in clean energy, cities should consider strategies to create more equitable pathways to good clean-energy jobs. Local leaders could work with colleges and universities to diversify graduates from engineering and other essential clean-energy bachelor’s degree programs. They could also work with clean-energy companies to eliminate unnecessary education requirements for management, business, and financial operations positions where possible, and collaborate with unions to create more pathways to good clean-energy jobs in construction, repair, and installation for women and people of color.
About
Federal agencies do not yet agree on how to define or gather data on clean-energy jobs. For this reason, we used the foundational work of the National Center for O*NET Development to identify occupations that will require enhanced skills, experience increased demand, or emerge in three key clean-energy sectors: energy efficiency, renewable-energy generation, and green construction. We then sourced data on the number of jobs (total employment) for these occupations from the 2022 Occupational Employment and Wage Survey, and classified the occupations’ quality using Urban’s job-quality scoring method, which looks at 11 elements of job quality.
To analyze access to clean-energy jobs by race and ethnicity and gender, we utilize national and local demographic data from the 2022 American Community Survey Public Use Microdata Sample (ACS PUMS). We chose these cities because our funder, the Kresge Foundation, supports several community initiatives in these cities. We identified all people working in energy efficiency, renewable-energy generation, and green construction occupations, as well as those working in adjacent occupations sharing the same four-digit Standard Occupational Code (SOC). This allowed us to estimate the demographics of the potential clean-energy workforce, or people with skills and competencies applicable to clean-energy jobs.
Population data are drawn from the US Census Bureau’s 2022 QuickFacts tool. We use Invest.gov’s public investments data as of January 2024 to calculate Bipartisan Infrastructure Law and Inflation Reduction Act funding.
We use Geocorr from the Missouri Census Data Center to map each Public Use Microdata Area (PUMA) in the census to the eight cities, based on the proportion of the population in a PUMA that lives in areas that overlap with the city. We combine these proportions 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.
The data have several limitations. Both the job-quality scores and the job counts we use to weight the 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 are 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. Additionally, employment estimates are subject to American Community Survey sampling error and reflect uncertainty, particularly for subsets of the data by city, sector, quality, and gender or race and ethnicity that contain small numbers of people.
This research was led by Molly M. Scott, Judah Axelrod, and Hailey D’Elia. Communications support was provided by Aleszu Bajak, Alex Dallman, and Dana Ferrante.