Artificial intelligence (AI) reshapes workers’ comparative advantage by altering the tasks they perform and the skills those tasks require. We develop a dynamic task-based model to quantify the general-equilibrium effects of task-specific technical change. Workers have multidimensional skills, choose occupations, and accumulate skills on the job; occupations combine tasks, and productivity depends on how workers’ skills match task requirements. We develop a computationally efficient procedure to estimate the model using panel data and a new database of task-level skill requirements. We apply the model to AI, allowing it to augment, automate, and simplify tasks. We find that AI narrows wage inequality and raises average wages across scenarios ranging from slow to rapid AI progress. The key equalizing force is simplification: by lowering tasks’ skill requirements, AI lets lower-skill workers compete for previously inaccessible jobs. Adoption costs, highest for lower-skill workers, dampen but do not eliminate the decline in inequality.

Media: Fox Business; Fortune; MIT Technology Review; Marginal Revolution; National Affairs; WirtschaftsWoche.

This paper studies the distributional effects of two general purpose technologies: steam and electric power. Using newly collected historical data from the US and the Netherlands and plausibly exogenous variation in adoption, I show that steam power increased firm sizes and top income and wealth inequality, while electric power had opposite effects. These effects reveal a key link between technology and inequality: scale bias—the extent to which technical change increases returns to scale. Steam entailed high fixed costs and was mainly adopted by large firms, whereas electricity was small-scale-biased. A model of occupational and technological choice illustrates how large-scale-biased technical change raises top income inequality by concentrating entrepreneurial income.

Awards: Sir John Hicks Prize for an Outstanding Doctoral Thesis (best thesis in LSE's Department of Economics between 2024 and 2026); UniCredit Foundation Best Paper Award.

Early-career jobs often serve as stepping stones to more productive occupations later in life. Automating such jobs may therefore disrupt skill accumulation. We study this possibility in an overlapping-generations economy with career ladders. Our main result is that so-so automation of junior tasks is immiserizing: automation that is just productive enough to be adopted lowers steady-state output by backloading labor income over the life cycle, reducing the attractiveness of experience-intensive careers and the future supply of experienced workers. By contrast, sufficiently productive automation raises output and welfare. Because the competitive equilibrium is Pareto efficient, policies that avert immiseration necessarily hurt some workers. Consistent with the model’s central mechanism, U.S. Census data show that industries more exposed to junior-task automation subsequently experienced larger declines in employment.

When a European firm moves its headquarters to the United States, when a US firm expands by hiring across many states, or when a Japanese firm raises funding from US investors, these choices reveal what makes the United States attractive to firms. This paper builds a model in which firms make location choices across multiple activities—where to hire production workers, where to expand their sales staff, where to raise funding, where to place the headquarters—and these choices reveal the sources of a region's attractiveness. It constructs a new global database that tracks where firms locate these activities and it develops an econometric strategy to separately estimate the contribution of each source. Applying the framework to the EU-US comparison, it finds that the productivity gap between them is driven by higher efficiency of the US's funding markets, higher costs of operating across the EU’s fragmented internal market, and a scale-dependent penalty on profits of larger EU firms.

Defense spending is the largest component of US discretionary spending and a quarter of it is spent on military personnel. The US military is the largest single employer in the US. This paper studies the general equilibrium effects of military employment on labor markets and the macro-economy. Military employment is concentrated in the 18-24 age group; military jobs have higher skill requirements than the average civilian job and resemble the more technical jobs in the goods-producing sector. This has made military employment historically a de facto training ground for a large segment of the labor force. In the early 90s, this labor market was hit by the Cold War Demobilization shock: the military shed 700,000 employees. Using an event study around the end of the Cold War, we find that income in occupations similar to military jobs suffered a 5% hit to income. This shock hit similar populations to those affected by trade and automation in the past three decades but we show that this is a separate and distinct shock. We explore the implications of the military as an employer in a general equilibrium model of occupational choice and human capital accumulation. The model illustrates that the military draw-down affected not only exposed populations, but also had an effect on aggregate income, through human capital externalities.

How did the US become a land of opportunity? Previous historical research on intergenerational mobility has focused on father-son income correlations, masking the role of mothers. We introduce a new mobility measure that incorporates both parents' human capital, develop a latent variable method leveraging literacy as a proxy, and construct a representative linked panel that includes women. We find that intergenerational mobility—in both human capital and income—rose sharply from the 19th to the 20th century. Initially, maternal human capital was most predictive of children's outcomes. However, as schooling expanded, this reliance declined and intergenerational mobility rose. Investments in mass education have therefore been central to America's rise as a mobile society.

Media: Marginal Revolution; SIEPR Policy Brief; Macro Roundup; National Affairs; BSE Focus.

This paper studies the long-run effects of slavery and restrictive Jim Crow institutions on Black Americans' economic outcomes. We track individual-level census records of each Black family from 1850 to 1940, and extend our analysis to neighborhood-level outcomes in 2000 and surname-based outcomes in 2023. We show that Black families whose ancestors were enslaved until the Civil War have considerably lower education, income, and wealth than Black families whose ancestors were free before the Civil War. The disparities between the two groups have persisted substantially because most families enslaved until the Civil War lived in states with strict Jim Crow regimes after slavery ended. In a regression discontinuity design based on ancestors' enslavement locations, we show that Jim Crow institutions sharply reduced Black families' economic progress in the long run.

Media: The Guardian; Marginal Revolution; 2025 Nobel Lecture; VoxEU; Hoover Institution; Frankfurter Allgemeine; National Affairs; Helsingin Sanomat; VoxDev.
Awards: Erik Olin Wright Prize; Urban Economics Association Prize; IPUMS USA Research Award.