Knowledge that Transforms

When people receive new information, sometimes they revise their beliefs too much, and sometimes too little. We show that a key driver of whether people overinfer or underinfer is the strength of the information. Based on a model in which people know which direction to update in, but not exactly how much to update, we hypothesize that people will overinfer from weak signals and underinfer from strong signals. We then test this hypothesis across four different environments: abstract experiments, a naturalistic experiment, sports betting markets, and financial markets. In each environment, our consistent and robust finding is overinference from weak signals and underinference from strong signals. Our framework and findings can help harmonize apparently contradictory results from the experimental and empirical literatures.

By augmenting the continuous-time specification of Harris and Laibson (2013) with the assumption that hard borrowing constraints do not bind in equilibrium, present bias can be tractably incorporated into rich consumption-saving models featuring stochastic income, risky and illiquid assets, and costly borrowing. I present closed-form expressions characterizing how present bias affects consumption, illiquid asset demand, and welfare. This welfare analysis specifies the channels through which present bias can matter for policy and uncovers the present-bias dilemma: present bias can have large welfare costs, but individuals have little ability to alleviate these costs using financial commitment devices like illiquid assets.

I develop a model of the social construction of race. Racial categories emerge from labor conflict when elites privilege intrinsically irrelevant traits to divide workers against each other and extract workers’ surplus. I show that elites use color to grant unequal rights and track these rights across generations because it is heritable, observable, and relatively immutable. Depending on the demographic conditions the elites face, the system of racialization manifests either as ancestry-based or color-based categories. This approach to the social construction of race provides a unified explanation of skin-tone inequality, racial homophily in marriage, the social status of mixed-race people, the psychological wage of Jim Crow, and legal restrictions on manumission. I test for historical variations in racial boundaries using census data from the United States and Brazil and for differential patterns of skin-tone inequality between ancestry-based and color-based systems using survey data from across the Americas.

We study markup cyclicality in a granular macroeconomic model with oligopolistic competition. We first characterize how firm, sectoral, and aggregate markups comove with output at different levels of aggregation in response to firm-level shocks. We quantify the model’s ability to reproduce salient features of the cyclical properties of measured markups in French administrative firm-level data from the bottom (firm) level to the aggregate level. We document that (i) firm-level markups rise with market share and sector-level markups with concentration, (ii) the relationship between markups and sectoral output varies by firm size—negative for small firms but positive for large ones, (iii) sector-level markups move positively with sectoral output, and (iv) sectoral markups show no systematic relationship with aggregate output. Our model helps rationalize these seemingly conflicting patterns of markup cyclicality in the data.

Schooling may build human capital not only by teaching academic skills but by expanding the capacity for cognition. We focus specifically on cognitive endurance: the ability to sustain effortful mental activity over a continuous stretch of time. As motivation, we document that globally and in the United States, the poor exhibit cognitive fatigue more quickly than the rich do across field settings; they also attend schools that offer fewer opportunities to practice thinking for continuous stretches. Using a field experiment with 1,600 Indian primary school students, we randomly increase the amount of time students spend in sustained cognitive activity during the school day—using either math problems (mimicking good schooling) or nonacademic games (providing a pure test of our mechanism). Each approach markedly improves cognitive endurance: students show 22% less decline in performance over time when engaged in intellectual activities—listening comprehension, academic problems, or IQ tests. They also exhibit increased attentiveness in the classroom and score higher on psychological measures of sustained attention. Moreover, each treatment improves students’ school performance by 0.09 standard deviations. This indicates that the experience of effortful thinking itself—even when devoid of any subject content—improves general cognitive capacity. Finally, we complement these results with quasi-experimental variation indicating that an additional year of schooling improves cognitive endurance, but only in higher-quality schools. Our findings suggest that schooling disparities may further disadvantage poor children by hampering the development of a core mental capacity.

ABSTRACT What is the effect of the real minimum wage on wages and inequality? I develop a theory that nests the race between education and technology. The theory predicts that the effect of changes in minimum wages is initially small but grows over time. I present empirical evidence of these dynamic effects: the elasticity of real wages grows substantially over a three-year period. I show that minimum wages help rationalize a considerable decline in real wages of low-education workers in the 1980s and play a role in shaping the evolution of the U.S. college premium.

From a new data set, we infer time series of term structures of yields on U.S. federal bonds during the gold standard era from 1791–1933 and use our estimates to reassess historical narratives about how the United States expanded its fiscal capacity. We show that U.S. debt carried a default risk premium until the end of the nineteenth century, when it started being priced as an alternative safe asset to U.K. debt. During the Civil War, investors expected the United States to return to a gold standard so the federal government was able to borrow without facing denomination risk. After the introduction of the National Banking System, the slope of the yield curve switched from down to up and the premium on U.S. debt with maturity less than one year disappeared.

We leverage spatial variation in the severity of the Great Recession across the United States to examine its impact on mortality and explore the quantitative implications. We estimate that an increase in the unemployment rate of the magnitude of the Great Recession reduces the average annual age-adjusted mortality rate by 2.3%, with effects persisting for at least 10 years. Mortality reductions appear across causes of death and are concentrated in the half of the population with a high school degree or less. We estimate similar percentage reductions in mortality at all ages, with declines in elderly mortality thus responsible for about three-quarters of the total mortality reduction. Recession-induced mortality declines are driven primarily by external effects of reduced aggregate economic activity on mortality, and reduced air pollution appears to be a quantitatively important mechanism. Incorporating our estimates of procyclical mortality into a standard macroeconomic framework substantially reduces the welfare costs of recessions, particularly for people with less education, and at older ages.

Noncarceral conviction is a common outcome of criminal court cases: for every person incarcerated, there are approximately three who were recently convicted but not sentenced to prison or jail. We extend the binary-treatment judge IV framework to settings with multiple treatments and use it to study the consequences of noncarceral conviction. We outline assumptions under which widely used 2SLS regressions recover margin-specific treatment effects, relate these assumptions to models of judge decision-making, and derive an expression that provides intuition about the direction and magnitude of asymptotic bias when a key assumption on judge decision-making is not met. We find that noncarceral conviction (relative to dismissal) leads to a large and long-lasting increase in recidivism for felony defendants in Virginia. In contrast, incarceration (relative to noncarceral conviction) leads to a short-run reduction in recidivism, consistent with incapacitation. Our empirical results suggest that noncarceral felony conviction is an important and overlooked driver of recidivism.

We develop and estimate a dynamic model of risky prescription opioid use that allows us to unpack the role of person- and place-specific drivers of the opioid epidemic and to assess the impact of state opioid policies. Event studies indicate that, among adults receiving federal disability insurance from 2006 to 2019, moves to states with higher rates of risky use produce an immediate jump in the probability of risky use, followed by an additional gradual increase for the next several years. Using a potential outcomes framework, we show how these results map to the person- and place-specific factors in the model. Model estimates imply large effects of place on both the likelihood of transitioning to addiction and the availability of prescription opioids; they also indicate that these place effects change significantly when state laws restricting pain clinics are enacted. A one standard deviation reduction in all place effects would have reduced risky use by about 40 percent over our study period. One particular source of place effects, pain clinic laws, reduced risky use by 5 percent, but could have reduced it by 30 percent if they had been enacted earlier, with much of this magnification operating through the dynamics of addiction.