This study introduces different categories of green jobs and approaches to assessing green jobs, including in the latter both ‘top-down’ and ‘bottom-up’ assessment methods. ‘Top-down’ approaches consider all jobs within specific sectors or activities that are relevant for the zero-carbon transition to be ‘green’, while ‘bottom-up’ approaches identify specific activities within firms, or specific occupations that can be considered green. Within this second group, one approach (the O*NET occupational classifications) identifies jobs as being directly or indirectly green, depending on whether they contain explicitly ‘green’ tasks.
The study then uses the O*NET occupational classifications approach to quantify and describe green jobs in the United Kingdom (UK), and correlates these jobs with various educational and socioeconomic characteristics. It applies the O*NET green job classifications to Labour Force Survey (LFS) data for the UK from 2011 to 2019. Whereas previous studies have analyzed features of green jobs at the occupation level using O*NET data, this study analyzes individual-level microdata, to allow some analysis of the characteristics of individuals in green jobs versus their non-green counterparts.
The study finds that around 17% of jobs in the UK economy are directly or indirectly green, varying by sector and region. The sectors with the highest shares of green jobs are utilities, construction, manufacturing, the primary sector and transport. It also finds that green jobs are more likely to be held by men, while directly green jobs tend to be held by older workers. Green new and emerging jobs in particular appear to be held by individuals with higher levels of education, training, wages and more secure work contracts. Further, green jobs appear to be associated with a wage premium at lower skill levels, even after controlling for education and years of experience, and are at lower risk of automation.
In developing the Road Map for a Managed Transition of Coal-Dependent Regions in Western Macedonia (World Bank, in collaboration with the Regional Government of Western Macedonia), analysis was undertaken of the potential consequences of decarbonization for the labour force.
This report summarizes the region’s current labour market structure, and recent trends in the types of jobs available and working conditions in the lignite sector particularly. It then looks at the likely effects of transition away from lignite.
Methodologically, to estimate the indirect and induced labour effects this study used a firm survey, based on the list of subcontractors working for the Public Power Corporation over recent years (a representative sample of all firms which provided goods, materials, projects or services to the power company were contacted and asked about the nature of their activities with PPC as well as the number of people employed in Western Macedonia in producing these goods and services).
The analysis explores not only total employment impacts but also the breakdown of employees, and the impacts on firms whose business is linked to power and mining (noting those which are particularly dependent on the power company for their revenue). Unsurprisingly, it finds many jobs in the mining and electric power value chain are at stake as lignite plants close (an estimated 16,000). It also finds that the region has a high sensitivity to employment losses; some firms linked to power and mining are particularly dependent on the power company for their revenue, while youth and new labour market entrants lack the skills that may be needed to find enable employment. The report highlights that skills mismatches affect most occupations in Western Macedonia, especially among low-skilled blue collar jobs.
Another aspect of the analysis explored how the transition is perceived by affected workers, as well as their skills, aspirations and coping strategies. For this, it conducted some 13 focus groups discussions with different professional groups (within the power company and among subcontracting firms).
The report notes that the actual outcomes of coal closures will depend on the transition path chosen, including the timing and labor intensity of the power plant decommissioning and land reclamation plans, as well as the labor intensity of the new alternative activities promoted. It recommends that, as more clarity emerges on the strategic orientation to be taken, effort should be made to better tailor and target active labor market programs so that affected and other workers (especially youth) are supported in transitioning into the new positions.
In 2018, the World Bank and the International Labour Organization (ILO) undertook a joint assessment of the direct employment impacts of nine road infrastructure investment projects in Lebanon and Jordan.
The analysis explored: How many direct jobs were created, and how labour intensities varied with different types of projects; What kinds of jobs were created (e.g. permanent v temporary, skilled v unskilled, etc); Who got the jobs and how did marginalized groups such as women or migrants fare (finding, for instance, that women were employed in only 1 to 2% of the jobs created and were restricted to specific job categories); and how decent were the jobs (i.e. the working and remuneration conditions).
The analysis used a combination of data collection methods, including:
- Key informants’ interviews with government authorities and other actors involved in road project construction in both countries, as well as contractors and suppliers;
- Site visits to support the assessment of the quality of employment and the progress of the work;
- Document analysis, including of Bills of Quantities for individual projects, appraisal reports, design reports, site records, and physical and financial progress reports (where available); and
- Analysis of quantitative employment data, as well as qualitative employment policies and other relevant information
This paper analyzes the employment impacts of mine closures in two Australian case studies, specifically a uranium mine in the Northern Territory and a coal mine in South Australia.
Methodologically, the analysis first established the employment structure of each local economy ex ante (before the impact), which helped to identify the way mining is connected to other support industries and other sectors of the economy. Then, once the employment structure of the local economy was estimated, the likely loss of jobs because of mine closure was estimated, not only in the mining sector but also in supporting and related subsectors such as construction, and then also in other subsectors that may be indirectly related to mining activities. The analysis considered 111 industry subsectors, and developed an approach to categorize the strength of connections between mining and levels of employment and income in each subsector. It also applied “location quotients” to the 111 subsector categories, to provide a measure of employment concentration and thus a means of estimating the regional concentration of employment losses, and vulnerability of local economies.
In both cases examined, the assessment finds employment impacts of mine closure are significant, not only among direct jobs in the mines themselves but also in supporting industries, particularly construction, and more broadly across the economy. In terms of their distribution, the analysis finds these impacts are greatest locally, however there are also impacts at state and even national scales (because some workers commute from afar to work shifts at these mines). It also highlights that negative employment effects will be significant for Aboriginal and Torres Strait Islander people, communities which tend to experience economic disadvantage already.
This study introduces different categories of green jobs and approaches to assessing green jobs, including in the latter both ‘top-down’ and ‘bottom-up’ assessment methods. ‘Top-down’ approaches consider all jobs within specific sectors or activities that are relevant for the zero-carbon transition to be ‘green’, while ‘bottom-up’ approaches identify specific activities within firms, or specific occupations that can be considered green. Within this second group, one approach (the O*NET occupational classifications) identifies jobs as being directly or indirectly green, depending on whether they contain explicitly ‘green’ tasks.
The study then uses the O*NET occupational classifications approach to quantify and describe green jobs in the United Kingdom (UK), and correlates these jobs with various educational and socioeconomic characteristics. It applies the O*NET green job classifications to Labour Force Survey (LFS) data for the UK from 2011 to 2019. Whereas previous studies have analyzed features of green jobs at the occupation level using O*NET data, this study analyzes individual-level microdata, to allow some analysis of the characteristics of individuals in green jobs versus their non-green counterparts.
The study finds that around 17% of jobs in the UK economy are directly or indirectly green, varying by sector and region. The sectors with the highest shares of green jobs are utilities, construction, manufacturing, the primary sector and transport. It also finds that green jobs are more likely to be held by men, while directly green jobs tend to be held by older workers. Green new and emerging jobs in particular appear to be held by individuals with higher levels of education, training, wages and more secure work contracts. Further, green jobs appear to be associated with a wage premium at lower skill levels, even after controlling for education and years of experience, and are at lower risk of automation.
This study, prepared for the ILO, estimates the scale and distribution of green employment in the economy of Bangladesh, focusing on the sectors of agriculture, sustainable forestry, green transport, manufacturing, waste management and recycling, and climate change adaptation.
The study estimates environment-related employment in Bangladesh, the employment sustained by more environmentally friendly activities and, within those areas, the number of decent jobs that might fairly be categorized as a ‘green job’ under the UNEP/ILO definition of the term.
Data constraints are noted as a challenge to undertaking this analysis. For job estimates and analysis of conditions of decent work, the analysis draws on a literature review and interviews with key experts. The interviews were used to provide some qualitative information on the quality of jobs, though were not considered conclusive and were supplemented by general sector-based indicators for decent work, where available. The indirect effects were estimated using a modification of the input-output table for Bangladesh.
The study suggests that most green jobs are created by transforming existing jobs or substituting to greener activities within the same sector.
This study analyzed the impacts on employment, GDP and emissions of Nigeria’s intended actions on climate change (as articulated in the country’s nationally determined contributions (NDCs) submitted to the UNFCCC). Job creation impacts and growth potential were examined in the short- to medium-term (primary impacts) and long-term (secondary impacts). The assessment covers policies and actions in various sectors, including energy, transport, agriculture, forestry and industry.
This analysis used the ILO’s Green Jobs Assessment Model (GJAM) to measure social and employment impacts. The GJAM combines a macroeconomic model that is solved iteratively moving forward one year at a time with a demand-driven input-output model with industry detail and exports and population as exogenous drivers. The structure of Nigeria’s economy, employment and emissions were empirically based on national data; specifically, the national accounts, labour force survey and emissions inventory are all harmonized for the single year 2018 (thus, referred to as estimates) and are used as the starting points for all scenario simulations of the GJAM.
The report notes that GJAMs are not economic forecasting models, but rather tools that provide information about the possible effects of "what-if" scenarios on emissions and labour demand by industries, assuming that the remaining structure of the economy does not change. Thus, the results indicate the direction and possible size of the effects but should not be taken as definitive, not least because actual labour market outcomes also depend on other factors, as well as dynamic labour market adjustments, that are not considered by the GJAM.
The study finds that, in all of the sectors and policies examined, Nigeria should experience positive contributions to economic growth, employment creation, and emission reduction, as long as these programmes are accompanied by supportive economic, social, and labor market policies. It concludes that, among other things, the type of climate policy will significantly affect the social and labor market outcomes. Further, it recommends that social protection measures and social dialogue mechanisms can help to signal to the affected population that the government will buffer any negative impacts of these structural changes.
This report details an assessment of the social, employment and economic impacts (i.e. impacts on the labor market, gender, economic growth and greenhouse gas emissions) of twelve of Zimbabwe’s climate policies targeting different sectors: energy, transport, forestry and agriculture.
The methodology is based on use of the ILO’s Green Jobs Assessment Model (GJAM), a scenario-based tool for exploring and comparing outcomes under different pathways (rather than a detailed and comprehensive analysis of most likely outcomes). For each of the sectors in focus, scenarios were defined and then assessed using the GJAM in combination with detailed data about the Zimbabwean economy. Employment in each sector is broken down by gender and by skill level. The report, however, notes data availability for some parameters was constrained; for example, no data were available for labour indicators such as employment by age group and industry, so these were unable to be separately considered by the analysis. Other input to the development of the study came from government officials and other stakeholders during a one-week online workshop, and from a review of literature and compilation of specific expert knowledge by the Zimbabwe Economic Policy Analysis and Research Unit (ZEPARU).
An important finding is that the type of investment, more so than the size of investment, is crucial to the likely outcomes. Per dollar invested, the analysis suggests Zimbabwe’s biogas program could create more jobs economy-wide compared to commercial solar and hydro programmes. Promotion of energy efficient cookstoves would create many new jobs, but would also undermine some jobs (e.g. firewood collection, which is a particularly important income source for women). These types of insights help in the design of decarbonization strategies, so that they can be targeted in ways that maximize employment. They also highlight areas where social protection and re-skilling programmes might be best targeted to ensure those people who are most vulnerable to change are properly supported.
Kazakhstan’s metal and coal mining and petroleum extraction contribute a significant share of the country’s GDP. In the context of pressure for transition to a lower carbon economy, this study of the labour market focused specifically on women’s role in the energy sector. It examined the extent to which women have benefited from employment opportunities in this sector, compared female and male employee earnings, and explored what impact a transition to carbon neutrality might have for women who are currently employed in the energy sector.
The study used was exploratory statistical analyses of employment and labour compensation data reported by the Ministry of Economy of Kazakhstan, and from the Kazakhstan Labour Force Survey. The International Labour Organization’s International Standard Classification of Occupations and Kazakhstan’s National Classifier of Occupations (NCO) were used to identify occupations.
The study finds that women occupied 30% of the jobs in the power industry, 22% of the jobs in coal mining, and 18% of the jobs in petroleum extraction (higher than rates in the European Union), and that rates vary considerably depending on the type and skill levels of different jobs and skill levels.
Over time, there has been steady growth in female-held jobs as unskilled laborers in all sectors, and high growth in science/IT professionals in petroleum extraction and the power industry. However, women’s share among managers declined in coal mining and the power industry, as well as among engineers and surveyors in petroleum extraction and the power industry. The share of women across all occupations declined at 1% per year in coal mining and 4% per year in petroleum extraction.
The study also highlights how women’s employment is more vulnerable to external crisis: Prior to the covid19 pandemic, women worked in 62–71% of occupations in coal mining and petroleum extraction and 100% of occupations in the power industry but by 2021 women’s representation in these occupations fell to 35–40% in all three sectors – possibly, the study argues, a result of the care functions that women are expected to provide for families.
In 2010, the ADB in conjunction with the Ministry of Education (MOE) and the Ministry of Labor and Social Welfare (MOLSW) undertook a Labour Market Assessment for Laos. It focused on labour market demand, to clarify current and potential labour market needs in different sectors of the formal economy, with particular attention on TVET graduates at different levels and the transition from school to work. In addition to the gathering of data about skill shortages and inadequately met labour needs, the assessment investigated the factors that influence the labour market, particularly the role of infrastructure, of cross border flows of labour, and the impact of the 2008 financial crisis.
The methodology used involved a questionnaire for businesses across eight provinces of the country. The survey targeted economic sectors with significant employment potential in Lao PDR and thus focused on businesses in: Mining and electricity/ hydropower, garment, textile construction, tourism/ hospitality, agriculture, wood processing, furniture, handicrafts, wholesale and retail, manufacturing. In addition to the survey, meetings and interviews were conducted with employers associations, trade associations, large companies representing the key sectors and other stakeholder groups. These were used to confirm, extend, or elaborate the findings of the survey.
Among the findings highlighted by the assessment is the observation that there are major skills shortages in several key sectors, including furniture, construction, tourism and hospitality, and mechanical maintenance. Various factors are assessed as contributing to this, including the lack of career guidance or counseling structures, or information systems, which could deliver relevant labor market information to youth and adults about job requirements, opportunities and workplace expectations, and communication gaps between employers and TVET institutions, which hinders the development of relevant curricula for students.
For countries across the Asia Pacific region, this report explores the data practices of countries in relation to monitoring international labor mobility. After a macro-economic and labor market overview, the report summarizes international labor migration trends in the Asia Pacific region, discusses data collection and sharing on labor market indicators, and assesses the state of international labor migration statistics in APEC countries.
It assesses the frequency of data collection, the types of data sources used, the scope, quality and usefulness of the indicators and estimates produced, as well as data-sharing practices and overall availability of data. In addition, the report summarizes many different types of data that are useful to systematic assessment of labor market requirements (i.e. labor and skills shortages).
This report, prepared by a task force of experts from national statistical offices, provides an overview of the ways international labor mobility is measured. It introduces the main definitions and concepts of statistics on international migration, labor and labor mobility, and provides an overview of the availability of various kinds of relevant data.
It also provides several practical examples of how international labor mobility is measured, from Israel, Italy, Mexico and Norway. In these cases, the report describes how Labor Force Survey data and other relevant data sources are compiled, and provides some recommendations for how data collection could be strengthened in a way that would improve the assessment of labor market mobility.
The report is intended to guide national statistical offices and other producers of migration statistics, while also offering other users an insight into the production of the migration statistics they use.
This report summarizes a study investigating the potential for using social media data when calculating citizen mobility, in this case in the EU context.
The proliferation of social media offers potential new data sources that could be used in an analysis of labor mobility, complementing traditional sources for mobility statistics such as census data, aggregated statistics from national offices, and household surveys. Social media generates high quantities of individual geo-tagged data (i.e. metadata that contains information linked to the geographical location of the content).
The report explores the potential of harvesting and using geo-referenced social-media data in a way that could provide nearly real-time estimates about changes in intra-state mobility. It covers some of the key concepts associated with defining and measuring migration, including the advantages and disadvantages of new and traditional data sources, and what is known about new methodologies using social-media data. It reviews the literature on data and methods for assessing migration, including data sources in the EU context, and presents methodologies to provide recent estimates of stocks of EU movers and EU mobility flows using geo-tagged social-media data in combination with traditional data sources. It then describes some of the results of applying these models using real-world data. It concludes with recommendations for how to improve the proposed method for estimating stocks of movers in the future.