By Damian Whittard
Climate change is a major challenge faced by the global community, environmentally but also economically. International governments have set ambitious plans to transform to a net zero economy, with the UK targeting 2050.
Green jobs are at the core of this transition and have an important role in delivering environmental management strategies that promote sustainable economic development. This evolution provides an opportunity to address embedded labour market inequalities.
Government and businesses need to develop policy and strategy based on a robust and reliable evidence base to support a fair and just transition. Currently, this evidence base is lacking. Green jobs have potential as a catalyst for social equity, but little is known about the impact of the transition on different groups.
A new ESCoE discussion paper from Damian Whittard, Peter Bradley, Van Phan and Felix Ritchie uses O*NET data linked to ASHE-Census 2011 to identify green occupational employment in England and Wales and explore the disparities between gender and ethnic groups. This links to other ESCoE work on net-zero, climate change and the environment and to Office for National Statistics (ONS) work on developing a method for measuring time spent on green tasks.
How we did it
We linked O*NET data to ASHE linked to Census 2011 data. This enabled us to use an occupation-based approach to identifying ‘green’ jobs. The mapping allowed us to identify jobs which were either directly or indirectly ‘green’. Directly green means new jobs or jobs that required enhanced skills. Indirectly green jobs are ones that were impacted due to the greening of the economy.
Our full sample for the single year included approximately 175,000 employees, while the sample totalled approximately 1.4 million across all years.
We used regression models to estimate the likelihood of working in green occupations (direct and indirect) and the pay-premium for working in a green occupation. We compared:
- The effect of gender and ethnicity on the likelihood of being in a green job.
- Raw pay gap – the difference between average pay for green and non-non green jobs.
- Adjusted pay gap – the difference between average pay for green and non-non green jobs, while controlling for all other characteristics.
- Gender and ethnic pay gap for those working just in green occupations.
Including interaction terms (e.g. being female and looking after dependent children) allowed us to uncover nuanced characteristics that are driving some of the gender inequality in pay.
What we found
- Individuals are more likely to work in green occupations if they are white and male
The raw figures reveal that >68% of all green occupations were filled by men, this compares to 52% of all employment. Green occupations accounted for one in three occupations for white workers, whereas this dropped to less than one in four for black and black British workers.
- There is a pay premium for working in a green job, which reduces the gender pay gap overall
Our analysis used a variety of models to estimate the pay premium. The raw data showed that those working in green occupations earned approximately 25% more than those working in other occupations.
Table 1: hourly average earnings by gender (2018, median pay):
After taking account of a variety of factors, in our regression analysis, we estimate that there is still a pay premium of around 4% for working in a green occupation.
- When looking at just those that work in green jobs, there is still evidence that the gender and ethnic pay gaps persist
The results of the regression analysis reveals that the same pay inequalities (gender and ethnicity) that are present in the wider labour market are still present when looking solely at green occupational employment.
Table 2: Hourly average savings by gender (2018, median pay)
Why it matters
The identification of a pay premium in green occupations suggests that these jobs are not only vital for environmental sustainability but are also becoming economically sustainable and desirable. This can help shift public perception of green jobs from being “alternative” or “niche” roles to mainstream career paths that offer competitive or even superior compensation. For policymakers, this finding can justify more robust support and investment in the green economy, leveraging economic incentives to meet environmental goals. And for businesses, it emphasises the importance of aligning business practices with sustainability goals to attract talent and capital in an increasingly eco-conscious market environment.
The greening of the economy offers the potential for a more inclusive and just transition. However, policymakers should note the dual inequality that green occupational employment appears to bring about. Women and ethnic groups are underrepresented in green employment, and when they are employed in green jobs, they are paid less than their counterparts. Further research is needed to explore the mechanisms through which this occurs, and policies put into place to mitigate this.
What’s next?
Following recommendations of the UK’s Green Jobs Taskforce report (2021), the ONS have recently published their revised definition of a green job. However, other approaches are still required when analysing internationally and when using UK historic data series.
This project aims to test the robustness of our findings by taking both a ‘top-down’ and alternative ‘bottom-up’ approach. For example, top-down estimates can be generated by linking data on emissions at the sector, industry or company level, while bottom-up approaches can be supported through links to additional datasets (e.g. The ONS’s Low Carbon and Renewable Energy Economy Survey).
In ongoing analysis, we are looking to explore the influence of other factors on the gender and ethnic pay gap reported in green jobs. For example, we intend to exploit the employee-employer link of the ASHE-Census 2011 dataset by exploring the role that employers play in shaping labour market differences in green jobs. By decomposing the observed gaps, we can estimate the precise role that employers play in driving the pay gap, and the gap which remains unexplained (e.g. discrimination). We would also like to explore spatial issues and their influence on inequality in more depth.
ESCoE blogs are published to further debate. Any views expressed are solely those of the author(s) and so cannot be taken to represent those of the ESCoE, its partner institutions or the Office for National Statistics.
This work was produced using statistical data owned by ONS and accessed through the ONS Secure Research Service. The use of the ONS statistical data in this work does not imply the endorsement of the ONS in relation to the interpretation or analyses of the statistical data. The work uses research datasets which may not exactly reproduce National Statistics aggregates.