Characterising green employment: The impacts of ‘greening’ on workforce composition

By A. Bowen, Karlygash Kuralbayeva, Eileen Tipoe. 2018

145 citations recorded by the source corpus.

This paper estimates the share of jobs in the US that would benefit from a transition to the green economy, and presents different measures for the ease with which workers are likely to be able to move from non-green to green jobs. Using the US O*NET database and its definition of green jobs, 19.4% of US workers could currently be part of the green economy in a broad sense, although a large proportion of green employment would be ‘indirectly’ green, comprising existing jobs that are expected to be in high demand due to greening, but do not require significant changes in tasks, skills, or knowledge. Analysis of task content also shows that green jobs vary in ‘greenness', with very few jobs only consisting of green tasks, suggesting that the term ‘green’ should be considered a continuum rather than a binary characteristic. While it is easier to transition to indirectly green rather than directly green jobs, greening is likely to involve transitions on a similar scale and scope of existing job transitions. Non-green jobs generally appear to differ from their green counterparts in only a few skill-specific aspects, suggesting that most re-training can happen on-the-job. Network analysis shows that the green economy offers a large potential for short-run growth if job transitions are strategically managed.

Subfields: Economics and Econometrics, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/9cb0018e1a1ded13a2ca0bc13dc99377b15d837d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. Giovanni Marin
2. Francesco Vona
3. David Popp
4. H. Bakhshi

In Renewable Energy, Sustainability and the Environment

1. Giovanni Marin
2. Francesco Vona

Citations in the corpus

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