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...

A significant reallocation of labour towards "green" jobs will be crucial for the transition to a decarbonised economy. Skills mismatches challenge the feasibility of this reallocation, particularly with many developed countries also facing substantial labour shortages. This paper analyses the...

We analyse the impact of robot adoption on employment composition using novel micro data on robot use in German manufacturing plants linked with social security records and data on job tasks. Our task-based model predicts more favourable employment effects for the least routine-task intensive...

Building on the task-based approach of technological change, this paper discusses the interaction between occupational polarization (e.g. a gradual increase of native employment in the lowest and highest-paying jobs) and employment opportunities of immigrant workers. Using high quality...

Using a semi-structural approach based on a dynamic monopsony model, we examine to what extent workers performing different job tasks are exposed to different degrees of monopsony power, and whether these differences in monopsony power have changed over the last 30 years. We find that workers...

We use data from a new international dataset - the European Skills and Jobs Survey - to create a unique measure of skills-displacing technological change (SDT), defined as technological change that may render workers' skills obsolete. We find that 16 percent of adult workers in the EU are...

As the pace of digitalization and automation accelerates globally, and more disruptive innovations in machine learning, artificial intelligence and robotics are expected, new data sources and measurement tools are needed to complement existing valuable statistics and administrative data. This is...