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

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.