Research
Research
Working papers
This paper examines how offshoring affects firms’ organization and skill composition, constructing an instrument to address the endogeneity of the offshoring decision. The findings indicate that Danish firms adjust their skill composition through two distinct channels on different segments of their task structure: retraining manual workers for less production-specific roles and hiring younger, more educated workers for cognitive tasks. The results suggest that internal labor markets and retraining can facilitate structural transformations, though they may not fully address skill gaps arising from changes in task demand.
IZA DP No. 16717; RFBerlin DP 14/24
Despite widespread concern, the labour-market impacts of artificial intelligence (AI) remain hard to quantify. We construct a Dynamic AI Occupational Exposure (DAIOE) index—tracking annual frontier gains across nine AI subdomains (2010–2023)—and link it to employer–employee registers in Denmark, Portugal, and Sweden. While AI exposure has no net effect on total firm employment, it is consistently tied to compositional up-skilling: firms with higher DAIOE scores increase their high-to-low skill employment ratios. Firms with higher DAIOE scores tend to expand high-skill white-collar positions and reduce low-skill clerical roles. Blue-collar effects average out but vary sharply by subdomain. Our findings underscore the need to unpack “AI” into its component technologies when evaluating labour-market outcomes.
This paper provides new evidence on how automation transforms firms’ demand for skills, not by changing the occupational composition, but by reshaping what existing jobs require. Using matched data on firm-level automation investments and detailed job ads from Denmark, we extract multidimensional skill profiles through natural language processing. Guided by a task-based framework, we decompose changes in skill demand into within- and between-occupation components and find that within-occupation adjustments dominate. Automation increases the demand for soft skills in professional and managerial roles and reduces the reliance on routine hard skills in production jobs. Register data confirm parallel shifts in workforce composition: increased experience in high-skill occupations and intensified retraining among lower-skilled workers. Our findings highlight that automation reconfigures work from within, with important implications for training policy and labor market resilience.
Selected Work in Progress
Who Adopts AI? Evidence from Firms and Workers in Denmark with Hildegunn Kyvik Nordås, Magnus Lodefalk, Mariola Pytlikova, Sarah Schroeder
The Employment Effects of AI Adoption with Mariola Pytlikova, Sarah Schroeder