My research focuses on three topics. First, I study the distributional implications of new production technologies using micro data that link workers, firms, and robots. Second, I explore the technology adoptions that drove the Second Industrial Revolution using newly-digitized microdata from the Census of Manufactures. Finally, I evaluate whether educational policies can help workers adjust to new technologies.
Working Papers
Changing Tracks: Human Capital Investment after Loss of Ability, with Pernille Plato and Jakob R. Munch.
Conditionally Accepted, American Economic Review.
Coverage: Becker Friedman Institute, Chicago Booth Review [video], Forked Lightning, University of Copenhagen.
Abstract: We provide the first evidence on how workers invest in human capital after losing ability. Using quasi-random work accidents in Danish administrative data, we find that workers enroll in bachelor’s programs after physical injuries, pursuing degrees that build on their past training and experience. Exploiting institutional differences in the stackability of degrees, we find that higher education moves injured workers from disability benefits to full-time employment, earning 25% more than before injury. Reskilling subsidies for injured workers pay for themselves four times over, and current rates of reskilling are substantially below the social optimum, especially for middle-aged workers.
The Adoption of ChatGPT, with Emilie Vestergaard.
Accepted, Proceedings of the National Academy of Sciences [new version released soon].
Coverage: Becker Friedman Institute, Podcast, Wage Against the Machine, IZA World of Labor, Charter, The Economist (#1), Marginal Revolution, The Economist (#2), MIT Sloan Management Review, Chicago Booth Review. In Danish: Børsen, Berlingske
Abstract: We study the adoption of ChatGPT, the icon of Generative AI, using a large-scale survey experiment linked to comprehensive register data in Denmark. Surveying 100,000 workers from 11 exposed occupations, we document that ChatGPT is widespread, but substantial inequalities have emerged. Women are 20 percentage points less likely to have used the tool. Furthermore, despite its potential to lift workers with less expertise, users of ChatGPT earned more already before its arrival. Workers see a substantial productivity potential in ChatGPT but are often hindered by employer restrictions and the need for training. Informing workers about expert assessments of ChatGPT shifts workers' beliefs but has limited impacts on actual adoption.
What Works for the Unemployed? Evidence From Quasi-Random Caseworker Assignments, with Jakob R. Munch and Mette Rasmussen.
Revised and Resubmitted, Journal of Political Economy.
Abstract: This paper examines if active labor market programs help unemployed job seekers find jobs using a novel random caseworker instrumental variable (IV) design. Leveraging administrative data from Denmark, our identification strategy exploits that (i) job seekers are quasi-randomly assigned to caseworkers, and (ii) caseworkers differ in their tendencies to assign similar job seekers to different programs. Using our IV strategy, we find assignment to classroom training increases employment by 29% two years after initial job loss of compliers. This finding contrasts with the conclusion reached by ordinary least squares (OLS), which suffers from a negative bias due to selection on unobservables. The employment effects are driven by job seekers who complete the programs (post-program effects) rather than job seekers who exit unemployment upon assignment (threat effects), and the programs help job seekers change occupations. We show that job seekers exposed to offshoring – who tend to experience larger and more persistent employment losses – also have higher employment gains from classroom training. By estimating marginal treatment effects, we conclude that total employment may be increased by targeting training toward job seekers exposed to offshoring.
Gaining Steam: Incumbent Lock-in and Entrant Leapfrogging, with Richard Hornbeck, Shanon Hsuan-Ming Hsu, and Martin Rotemberg.
Revision Requested, Journal of Political Economy.
Coverage: NBER Digest
Abstract: We examine the long transition from water to steam power in US manufacturing, focusing on early users of mechanical power: lumber and flour mills. Digitizing Census of Manufactures manuscripts for 1850-1880, we show that as steam costs declined, manufacturing activity grew faster in counties with less waterpower potential. This growth was driven by steam powered entrants and agglomeration, as water powered incumbents faced switching barriers primarily from sunk costs. Estimating a dynamic model of firm entry and steam adoption, we find that the interaction of switching barriers and high fixed costs creates a quantitatively important and socially inefficient drag on technology adoption. Despite substantial entry and exit, switching barriers remained influential for aggregate steam adoption throughout the 19th century, as water power required lower fixed costs and therefore was attractive to relatively low productivity entrants. These entrants then became incumbents, locked into water power even if their productivity grew.
Historical Differences in Female-Owned Manufacturing Establishments: The United States, 1850--1880, with Ruveyda Gozen, Richard Hornbeck, and Martin Rotemberg
In preparation for, AEA Papers & Proceedings
Abstract: We characterize female-owned manufacturing establishments using newly digitized manuscripts from the US Census of Manufactures (1850, 1860, 1870, 1880). Female-owned establishments were smaller than male-owned establishments and had lower capital-to-output ratios, which could reflect more-constrained financial access and other distortions. Female-owned establishments employed more women and paid women higher wages, creating a potential cycle between increased female business ownership and increased female labor market participation. Female-owned establishments concentrated in sub-industries like women's clothing and millinery, which is associated with some but not all of these differences. We also show how female owners differed from other women in the Population Census.
Robot Adoption and Labor Market Dynamics
Abstract: I study the distributional impact of industrial robots using administrative data that link workers, firms, and robots in Denmark. I estimate a dynamic model of how firms select into and reorganize production around robot adoption. I find that firms expand output, lay off production workers, and hire tech workers when they adopt robots. I embed the firm model into a general equilibrium framework that endogenizes the dynamic choice for workers to switch occupations in response to robots. To this end, I develop a fixed-point algorithm for solving the general equilibrium that features two-sided (firm and worker) heterogeneity and dynamics. I estimate that robots have increased average real wages by 0.8 percent but have lowered the real wages of production workers by 5.4 percent. Welfare losses from robots are concentrated on old production workers, as younger workers benefit from the option value of switching into tech.
Artificial Intelligence and College Majors, with Bjørn Meyer
Abstract: We study how Artificial Intelligence (AI) technology relates to the returns to college majors. Using microdata from Denmark, we first rank college majors according to whether their graduates work in AI firms. We show that AI cuts through the category of STEM degrees: while computer science and mathematics majors specialize in AI producer firms, we find that the laboratory sciences concentrate in firms that only use AI. We document that AI producer relevance correlates with higher wages, and that these earnings premiums are rising. In contrast, AI user majors do not earn wage premiums, nor have experienced differential earnings growth. Using a regression discontinuity design, we estimate the causal effects of admitting students to more AI-relevant college majors. We find that admission cutoffs are effective in increasing the AI relevance of college graduates. The causal earnings gain from higher AI producer relevance is at least as large as the correlation.
Works in Progress
Integrators: The Firm Boundaries of Capital-Skill Complementarity, with Gert Bijnens and Stijn Vanormelingen
Digitization of the Establishment-level Census of Manufactures from 1850, 1860, 1870, and 1880, with Richard Hornbeck and Martin Rotemberg
Equilibrium Impacts of Training Subsidies
Other Publications
Globalization, Flexicurity and Adult Vocational Training in Denmark (October 2019), with Jakob R. Munch Published in World Trade Organization book Making Globalization More Inclusive: Lessons from Experience with Adjustment Policies.