Routine-Biased technical change: Individual-Level evidence from a plant closure

Regional Structural Change and the Effects of Job Loss

“…rience stronger employment penalties in every region type. This is in line with findings of Blien et al ( 2021) and Goos et al (2020), who study how the costs of job displacement vary with routine intensity at the occupation level. Our results suggest that the regional context matters: While workers from other occupations have similar employment probabilities in all region types, the losses of RM workers are highest in regions with the strongest decline in RM occupations.…”

“…This suggests that job displacement might be particularly disruptive if it exposes routine workers to a labor market with a decreasing demand for their specific skill set. In line with this, routine workers are generally more likely to experience sustained unemployment and larger earnings losses after displacement (Blien et al, 2021;Goos et al, 2020;Dauth et al, 2021). Complementing this evidence, we find that the detrimental effects of structural change are confined to individuals who are displaced from their current jobs and that the associated costs are strongest in regions hit hardest by structural change.…”

“…However, these papers focus on the role of general labor demand during the business cycle for the costs of job loss, rather than the impact of long-term structural shifts in labor demand. Blien et al (2021) and Goos et al (2020), on the other hand, suggest that postdisplacement employment and earnings losses increase with the prior routine intensity of work due to routine-replacing technological change, but they do not establish any direct link between structural change and post-displacement outcomes. Our study takes up both recent strands of the displacement literature and shows that the regional exposure to task-biased structural change is an important determinant of the costs of job loss.…”

Is There Job Polarization in Developing Economies? A Review and Outlook

“…Similarly, Goos et al (2021) explore survey data of workers previously employed in a large Belgium establishment in the automotive sector. After the plant closed and in line with the RBTC hypothesis, workers in routine-intensive occupations were less likely to find a job 1,5 years after the event.…”

“…Goos et al (2021) can observe the direct impact of automation on workers' probability of separation. Using Dutch micro-data from 2000 to 2016,Bessen et al (2019) employ a direct measure of automation at the firm level and find that automation increases the probability of incumbent workers separating from their employers.…”