Estimating the Green Potential of Occupations: A New Approach Applied to the U.S. Labor Market

Christian Rutzer (), Matthias Niggli () and Rolf Weder ()
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Christian Rutzer: University of Basel
Matthias Niggli: University of Basel
Rolf Weder: University of Basel

Working papers from Faculty of Business and Economics - University of Basel

Abstract: This paper presents a new approach to estimate the green potential of occupations. Using data from O*NET on the skills that workers possess and the tasks they carry out, we train several machine learning algorithms to predict the green potential of U.S. occupations classified according to the 6-digit Standard Occupational Classication. Our methodology allows existing discrete classications of occupations to be extended to a continuum of classes. This improves the analysis of heterogeneous occupations in terms of their green potential. Our approach makes two contributions to the literature. First, as it more accurately ranks occupations in terms of their green potential, it leads to a better understanding of the extent to which a given workforce is prepared to cope with a transition to a green economy. Second, it allows for a more accurate analysis of differences between workforces across regions. We use U.S. occupational employment data to highlight both aspects.

Keywords: green skills; green tasks; green potential; supervised learning; labor market (search for similar items in EconPapers)
JEL-codes: C53 J21 J24 Q52 (search for similar items in EconPapers)
Date: 2020-03-01
New Economics Papers: this item is included in nep-big, nep-cmp and nep-lma
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:bsl:wpaper:2020/03

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