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...

In this paper, we use a data-driven approach to predict the "green potential" of ISCO occupations based on their corresponding skills. With this information, we can investigate the relationship between environmental regulations and occupation-level employment in the manufacturing sector of 19...

We use a data-driven methodology to quantify the importance of different skills in performing green tasks. For Switzerland, we estimate the green potential to be 16.7% of the total of employed persons and 18.8% of full-time equivalents in 2017, respectively. Employed persons in jobs with high...

Using a data-driven methodology that allows to quantify the importance of different skills in performing green tasks, we estimate the green potential for 26 European countries. By green potential we mean the share of employed persons in occupations characterised by skills that are important for...

We examine whether 'pioneer' regions - early leaders in generating new ideas in emerging scientific fields - develop and maintain an innovation advantage in the same fields over time. Our analysis covers 24 disruptive technologies (e.g. AI, cloud computing) in thousands of OECD regions over 20...

Despite tremendous growth in the volume of new scientific and technological knowledge, the popular press has recently raised concerns that disruptive innovative activity is slowing. These dire prognoses were mainly driven by Park et al. (2023), a Nature publication that uses decades of data and...