The paper explains how a country can fall into a “low-skill, bad-job trap,” in which workers acquire insufficient training and firms provide insufficient skilled vacancies. In particular, the paper argues that in countries where a large proportion of the workforce is unskilled, firms have little incentive to provide good jobs (requiring high skills and providing high wages), and if few good jobs are available, workers have little incentive to acquire skills. In this context, the paper examines the need and effectiveness of training policy, and provides a possible explanation for why western countries have responded so differently to the broad-based shift in labor demand from unskilled to skilled labor.
COVID-19 has exacerbated concerns about the rise of the robots and other automation technologies. This paper analyzes empirically the impact of past major pandemics on robot adoption and inequality. First, we find that pandemic events accelerate robot adoption, especially when the health impact is severe and is associated with a significant economic downturn. Second, while robots may raise productivity, they could also increase inequality by displacing low-skilled workers. We find that following a pandemic, the increase in inequality over the medium term is larger for economies with higher robot density and where new robot adoption has increased more. Our results suggest that the concerns about the rise of the robots amid the COVID-19 pandemic seem justified.