Knowledge that Transforms

This paper uses newly collected data on the allocation of dowry to examine its role in resolving intergenerational frictions around migration in India. Migration disrupts traditional elderly support structures, in which sons live near their parents and care for them in old age. We develop a model in which dowry can promote migration by allowing sons to make upfront transfers to their parents and ease constraints on income sharing. To test this hypothesis, we collect two new data sets that measure the distribution of dowry between family members. We document for the first time that net transfers of dowry to a man’s parents are common but far from universal. Consistent with using dowry for income sharing, such transfers occur more often when sons migrate, especially when they work in higher-earning occupations. In nationally representative data, migration rates are higher in areas with stronger historical dowry traditions. Finally, exploiting a large-scale highway construction program, we show that men from areas with stronger historical dowry traditions migrate more when migration costs fall. Our findings provide some clues as to why dowry persists despite its well-documented adverse consequences.

Concerns about excessive mobile phone use among youth are mounting. We present estimates of behavioral and contextual peer effects, along with comprehensive evidence on how students’ own and their peers’ app usage affect academic performance, physical health, and labor market outcomes. Our analysis draws on administrative data from a Chinese university covering three student cohorts over four years. We exploit random roommate assignments, differential exposure to a policy shock (gaming restrictions for minors), and differential exposure to a discrete event (the introduction of a blockbuster video game) for identification. App usage is contagious: a one s.d. increase in roommates’ in-college app usage raises own usage by 5.8%. High app usage is harmful across all measured outcomes. A one s.d. increase in app usage reduces GPAs by 36.2% of a within-cohort-major s.d. and lowers wages by 2.3%. Roommates’ app usage reduces a student’s GPA and wages through both disruptions and behavioral spillovers, generating a total negative effect that exceeds half the magnitude of the impact from the student’s own app usage. Extending China’s three-hour-per-week gaming restriction for minors to college students would boost their initial wages by 0.9%. High-frequency GPS and app usage data show that heavy app users spend less time in study halls, are more frequently late or absent from class, and get less sleep.

We present a theory of choice in which attention to the features of options is determined by the decision maker’s categorization of the current problem in a set of problems she solved in the past. Categorization depends on goal-relevant and contextual problem-level features. The model yields heterogeneity in attention and choice in a given problem based on different past experiences and instability when changes in irrelevant context cause recategorization. We show that heterogeneous and unstable representations of a choice problem unify major biases in judgment and decision making.

This article studies the effects of automation in a task-based economy in which some jobs pay workers rents—wages above workers' outside options. We show that automation targets high-rent tasks, dissipating rents, amplifying wage losses, and reducing within-group wage dispersion in exposed groups. This form of rent dissipation is inefficient and offsets the productivity gains from automation. Using U.S. data from 1980 to 2016, we find evidence of sizable rent dissipation and reduced within-group wage dispersion due to automation. Automation accounts for 52% of the increase in between-group inequality since 1980, with rent dissipation explaining one-fifth of this total. Our estimates imply that inefficient rent dissipation has offset 60%–90% of the productivity gains from automation over this period.

Why do banks fail? We create a panel covering most commercial banks from 1863 through 2024 to study the history of failing banks in the United States. Failing banks are characterized by rising asset losses, deteriorating solvency, and an increasing reliance on expensive noncore funding. These commonalities imply that bank failures are highly predictable using simple accounting metrics from publicly available financial statements. Failures with runs were common before deposit insurance, but these failures are strongly related to weak fundamentals, casting doubt on the importance of non-fundamental runs. Furthermore, low recovery rates on failed banks’ assets suggest that most failed banks subject to runs were fundamentally insolvent, barring large value destruction of receiverships. Altogether, our evidence suggests that the primary cause of bank failures and banking crises is almost always and everywhere a deterioration of bank fundamentals.

We use anonymized admissions data from several colleges linked to income tax records and SAT and ACT test scores to study the determinants and causal effects of attending Ivy-Plus colleges (Ivy League, Stanford, MIT, Duke, and Chicago). Children from families in the top 1% are more than twice as likely to attend an Ivy-Plus college as those from middle-class families with comparable SAT/ACT scores. Two-thirds of this gap is due to higher admission rates for students with comparable test scores from high-income families; the remaining third is due to differences in rates of application and matriculation. In contrast, children from high-income families have no admissions advantage at flagship public colleges. The high-income admissions advantage at Ivy-Plus colleges is driven by three factors: (i) preferences for children of alumni, (ii) weight placed on nonacademic credentials, and (iii) athletic recruitment. Using a new research design that isolates idiosyncratic variation in admissions decisions for waitlisted applicants, we show that attending an Ivy-Plus college instead of the average flagship public college increases students’ chances of reaching the top 1% of the earnings distribution by 50%, nearly doubles their chances of attending an elite graduate school, and almost triples their chances of working at a prestigious firm. The three factors that give children from high-income families an admissions advantage are uncorrelated or negatively correlated with postcollege outcomes, whereas academic credentials such as SAT/ACT scores are highly predictive of postcollege success.

This article estimates that the macroeconomic damages from climate change are an order of magnitude larger than previously thought. Exploiting natural global temperature variability, we find that 1ºC warming reduces world GDP by over 20% in the long run. Global temperature correlates strongly with extreme climatic events, unlike country-level temperature used in previous work, explaining our larger estimate. We use this evidence to estimate damage functions in a neoclassical growth model. Business-as-usual warming implies a present welfare loss of more than 30%, and a social cost of carbon in excess of $1,200 per ton. These impacts suggest that unilateral decarbonization policy is cost-effective for large countries such as the United States.

This article empirically studies the effects of the early law and economics movement on the U.S. judiciary. We focus on the Manne Economics Institute for Federal Judges, an intensive economics course that trained almost half of federal judges between 1976 and 1999. Using the universe of published opinions in U.S. Circuit Courts and 1 million District Court criminal sentencing decisions, we estimate the within-judge effect of Manne program attendance. Selection into attendance was limited, as the program was popular among judges of all backgrounds, frequently oversubscribed, and admitted participants on a first-come, first-served basis. We find that after attending economics training, participating judges use more economics language in their opinions, rule against regulatory agencies more often, and impose more severe criminal sentences. We argue that economics, as a rigorous social science, was especially effective in persuading judges.

We study the effect of monetary and fiscal policy in a heterogeneous-agent model where households have present-biased time preferences and naive beliefs. The model features a liquid asset and illiquid home equity, which households can use as collateral for borrowing. Because present bias substantially increases households’ marginal propensity to consume (MPC), present bias increases the effect of fiscal policy. Present bias also amplifies the effect of monetary policy, but at the same time, slows down the speed of monetary transmission. Interest rate cuts incentivize households to conduct cash-out refinances, which become targeted liquidity injections to high-MPC households. Present bias also introduces a motive for households to procrastinate refinancing their mortgages, which slows down the speed with which this monetary channel operates.

This article quantifies the role played by education in the reduction of global poverty. I propose tools for identifying the contribution of schooling to economic growth by income group, integrating imperfect substitution between skill groups into a macroeconomic growth decomposition. I bring this “distributional growth accounting” framework to the data by exploiting a new microdatabase representative of nearly all of the world’s population, new estimates of the private returns to schooling, and historical income distribution statistics. Education can account for about 45% of global economic growth and 60% of pretax income growth among the world’s poorest 20% from 1980 to 2019. A significant fraction of these gains was made possible by skill-biased technical change amplifying the returns to education. Because they ignore the distributional effects of schooling, standard growth accounting methods substantially underestimate economic benefits of education for the global poor.