Knowledge that Transforms

How effective are physicians at diagnosing heart attacks? To answer this question, we contrast physician testing decisions with a machine learning model of risk. When the two deviate, we use actual health outcome data to judge whether the algorithm or the physician was right. We find physicians over-test: tests that are predictably useless are still performed. At the same time, physicians also under-test: many predicted high-risk patients are untested and then suffer adverse health events (including death) at high rates. A natural experiment using shift-to-shift testing variation confirms these findings: increasing testing improves health and reduces mortality, but only for patients flagged as high-risk by the algorithm. The simultaneous existence of over- and under-testing cannot easily be explained by incentives alone, and instead suggests errors. We provide suggestive evidence on the psychology behind these errors:(i) physicians use too simple a model of risk, suggesting bounded rationality; (ii) they over-weight salient information; and (iii) they over-weight symptoms that are representative or stereotypical of heart attack. Together, these results suggest the need for health care models and policies to incorporate not just physician incentives, but also physician mistakes.

We document two robust features of the cross-sectional distribution of usual weekly hours and hourly wages. First, usual weekly hours are heavily concentrated around 40 hours, while at the same time a substantial share of total hours come from individuals who work more than 50 hours. Second, mean hourly wages are nonmonotonic across the usual hours distribution, with a peak at 50 hours. We develop and estimate a model of labor supply to account for these features. The novel feature of our model is that earnings are nonlinear in hours, with the extent of nonlinearity varying over the hours distribution. Our estimates imply significant wage penalties for people who deviate from 40 hours in either direction, leading to a large mass of people who work 40 hours and are not very responsive to shocks. This has important implications for the role of labor supply as a mechanism for self-insurance in a standard heterogeneous-agent incomplete-markets model and for empirical strategies designed to estimate labor supply parameters.

This article uses administrative tax data to estimate top wealth in the United States. We assemble new data that link people to their sources of capital income and develop new methods to estimate the degree of return heterogeneity within asset classes. Disaggregated fixed-income data reveal that rich individuals earn much more of their interest income in higher-yielding forms and have much greater exposure to credit risk. Consequently, in recent years, the interest rate on fixed income at the top is approximately 3.5 times higher than the average. We value the population of U.S. firms using firm-level characteristics and apportion this wealth using firm-owner links. We combine this new data on fixed income and pass-through business returns with refined estimates of C-corporation equity, housing, and pension wealth to deliver new capitalized wealth estimates that build upon the methods of Saez and Zucman (2016a). From 1989 to 2016, the top 1%, 0.1%, and 0.01% wealth shares increased by 6.6, 4.6, and 2.9 percentage points, respectively, to 33.7%, 15.7%, and 7.1%. Overall, although we estimate a large degree of return heterogeneity, accounting for this heterogeneity does not change the fundamental story for top wealth shares and their growth—wealth inequality is high and has risen substantially over recent decades.

The economic analysis of racial discrimination in public accommodations is remarkably limited. To study this issue, we construct a national data set of nondiscriminatory establishments from the Negro Motorist Green Books, a travel guide published from 1936 to 1966 to aid Black Americans in finding nondiscriminatory retail and service establishments. We document patterns in the geographic spread and evolution of Green Book establishments, as well as the correlates of Green Book presence. We find that economic and social measures, as well as state laws relating to racial discrimination and antidiscrimination, were correlated with the provision of nondiscriminatory services. We then use the Green Book data to test whether market conditions and white consumer discrimination led businesses to bar Black customers prior to the Civil Rights Act of 1964. We use plausibly exogenous variation from white World War II casualties and Black migration patterns to isolate the effect of a change in the racial composition of consumers on the growth of nondiscriminatory businesses. We find that the share of nondiscriminatory establishments grew faster in locations with larger increases in the share of the Black population, but the magnitudes were small. These results highlight the importance of federal legislation in ending racial discrimination in public accommodations.

I offer an axiomatization of risk models where the choices of the decision maker are correlation sensitive. By extending the techniques of conjoint measurement to the nondeterministic case, I show that transitivity is the von Neumann-Morgenstern axiom that has to be relaxed to allow for these richer patterns of behavior. To illustrate the advantages of the modeling choice, we provide a simple axiomatization for the salience theory model in our general framework. This approach leads to clear comparison to popular preexisting models, such as regret and reference dependence, and allows one to single out the ordering property as the feature that brings salience theory outside the prospect theory realm.

This article studies how exclusive social groups shape upward mobility and whether interactions between low- and high-status peers can integrate the top rungs of the economic and social ladders. Our setting is Harvard University in the 1920s and 1930s, where new groups of students arriving on campus encountered a social system centered on exclusive old boys’ clubs. Combining archival and census records, we first show that students from prestigious private feeder schools are overrepresented in old boys’ clubs, while academic high achievers and ethnic minorities are almost completely absent. Club members earnmore than other students and are more likely to work in finance and join country clubs, both characteristic of the era’s elite. We use random variation in room assignment to show that exposure to high-status peers expands gaps in college club membership, adult social club membership, and finance careers by high school type, with large positive effects for private school students and zero or negative effects for others. To conclude, we turn to more recent cohorts. We show that the link between exclusive college clubs and finance careers persists across the twentieth century even as Harvard diversifies, and that elite university students from the highest-income families continue to outearn their peers.

We study the effects of becoming a supplier to multinational corporations (MNCs) using tax data tracking firm-to-firm transactions in Costa Rica. Event study estimates reveal that domestic firms experience strong and persistent gains in performance after supplying to a first MNC buyer. Four years after, domestic firms employ 26% more workers and have a 4% to 9% higher total factor productivity (TFP). These effects are unlikely to be explained by demand effects or changes in tax compliance. Moreover, suppliers experience a large drop in their sales to all other buyers except the first MNC buyer in the year of the event, followed by a gradual recovery. The dynamics of adjustment in sales to others suggests that firms face short-run capacity constraints that relax over time. Four years later, the sales to others grow by 20%. Most of this growth comes from the acquisition of new buyers, which tend to be “better buyers” (e.g., larger and with more stable supplier relationships). Finally, we collected survey data from domestic firms and MNCs to provide further insights into the wide-ranging benefits of supplying to MNCs. According to our surveys, these benefits range from better managerial practices to a better reputation.

We document a nationwide “assessment gap” that leads local governments to place a disproportionate fiscal burden on racial and ethnic minorities. We show that holding taxing jurisdictions and property tax rates fixed, Black and Hispanic residents face a 10%–13% higher tax burden for the same bundle of public services. We decompose this disparity into between- and within-neighborhood components and find that just over half of it arises between neighborhoods. We then present evidence on mechanisms. Property assessments are less sensitive to neighborhood attributes than market prices are. This generates spatial variation in tax burden within jurisdiction and leads to overtaxation of communities with a high share of minority residents. We also find appeals behavior and appeals outcomes differ by race within neighborhood. Inequality does not arise from (i) racial differences in transaction prices or (ii) differences in features of the housing stock.

I show that a disruption to the financial sector can reshape the patterns of global trade for decades. I study the first modern global banking crisis originating in London in 1866 and collect archival loan records that link multinational banks headquartered there to their lending abroad. Countries exposed to bank failures in London immediately exported significantly less and did not recover their lost growth relative to unexposed places. Their market shares within each destination also remained significantly lower for four decades. Decomposing the persistent market-share losses shows that they primarily stem from lack of extensive-margin growth, as the financing shock caused importers to source more from new trade partnerships. Exporters producing more substitutable goods, those with little access to alternative forms of credit, and those trading with more distant partners experienced more persistent losses, consistent with the existence of sunk costs and the importance of finance for intermediating trade.

Since the beginning of the all-volunteer era, millions of young Americans have chosen to enlist in the military. These volunteers disproportionately come from disadvantaged backgrounds, and while some aspects of military service are likely to be beneficial, exposure to violence and other elements of service could worsen outcomes. This article links the universe of army applicants between 1990 and 2011 to their federal tax records and other administrative data and uses two eligibility thresholds in the Armed Forces Qualification Test (AFQT) in a regression discontinuity design to estimate the effects of army enlistment on earnings and related outcomes. In the 19 years following application, army service increases average annual earnings by over $4,000 at both cutoffs. However, whether service increases long-run earnings varies significantly by race. Black servicemembers experience annual gains of $5,500 to $15,000 11–19 years after applying while white servicemembers do not experience significant changes. By providing Black servicemembers a stable and well-paying army job and by opening doors to higher-paid postservice employment, the army significantly closes the Black-white earnings gap in our sample.