We present a task-based model in which high- and low-skill workers compete against machines in the production of tasks. Low-skill (high-skill) automation corresponds to tasks performed by low-skill (high-skill) labor being taken over by capital. Automation displaces the type of labor it directly affects, depressing its wage. Through ripple effects, automation also affects the real wage of other workers. Counteracting these forces, automation creates a positive productivity effect, pushing up the price of all factors. Because capital adjusts to keep the interest rate constant, the productivity effect dominates in the long run. Finally, low-skill (high-skill) automation increases (reduces) wage inequality.

Maddison’s international panel data show that technically it was the faster growth rate of the US economy that led to its overtaking the United Kingdom as economic superpower. We explore the contributing factors. Identifying the land-grant college system triggered by the 1862/1890 Morrill Acts (MAs) as a major contributor, we develop this hypothesis theoretically and test it via difference-in-differences regression analyses viewing the MAs as the experiment, the United States or US states as treatment groups, and the United Kingdom as the chief control group in the country-level comparisons. Using national and state-level data, we estimate that the MAs produced sizeable educational and economic returns that catapulted the United States into its leading status.

This paper analyzes the nonmarket benefits of education and ability. Using a dynamic model of educational choice, we estimate returns to education that account for selection bias and sorting on gains. We investigate a range of nonmarket outcomes, including incarceration, mental health, voter participation, trust, and participation in welfare. We find distinct patterns of returns that depend on the levels of schooling and ability. Unlike the monetary benefits of education, the benefits to education for many nonmarket outcomes are greater for low-ability persons. College graduation decreases welfare use, lowers depression, and raises self-esteem more for less-able individuals.

This paper assesses cross-country variation in life-cycle human capital accumulation, using new evidence from US immigrants. The returns to experience accumulated in an immigrant’s birth country before migrating are positively correlated with birth-country GDP per capita. To understand this fact, we build a model of life-cycle human capital accumulation that features three potential theories: differential human capital accumulation, differential selection, and differential skill loss. We use new data on the characteristics of immigrants and nonmigrants from a large set of countries to distinguish between these theories. The most likely theory is that immigrants from poor countries accumulate less human capital in their birth countries before migrating. Our findings imply that life-cycle human capital stocks are much larger in rich countries.

Technical change, even if it is limited in scope, can have effects that ripple throughout the economy. Here a flexible and tractable framework, with heterogeneous workers and technologies and many tasks, is used to analyze the general equilibrium effects of technical change for a limited set of tasks. The equilibria feature positively assortative matching between workers and technologies. The effects of technical change on employment, output, prices, and wages up and down the skill and technology ladders are sharply characterized. The effects of low-skill immigration, minimum-wage legislation, and international trade are also described.

We examine whether dynastic human capital (DHC) can explain the black-white wage gap. We fit a quantity-quality model to state-level data on fertility, mortality, and schooling but, notably, not earnings. Racial discrimination raised the cost of black schooling, thus depressing DHC not only of the current generation but of future generations via its role in producing human capital. Birth-state DHC helps explain the wage gap among stayers, while current-state DHC helps explain the gap among movers. These findings highlight the role of intergenerational transmission in the persistence of the wage gap and the role of migration in reducing it.