Knowledge that Transforms

Standard labor market models assume that workers hold accurate beliefs about the external wage distribution, and hence their outside options with other employers. We test this assumption by comparing German workers’ beliefs about outside options with objective benchmarks. First, we find that workers wrongly anchor their beliefs about outside options on their current wage: workers that would experience a 10% wage change if switching to their outside option only expect a 1% change. Second, workers in low-paying firms underestimate wages elsewhere. Third, in response to information about the wages of similar workers, respondents correct their beliefs about their outside options and change their job search and wage negotiation intentions. Finally, we analyze the consequences of anchoring in a simple equilibrium model. In the model, anchored beliefs keep overly pessimistic workers stuck in low-wage jobs, which gives rise to monopsony power and labor market segmentation.

Gun violence is the most pressing public safety problem in U.S. cities. We report results from a randomized controlled trial (N = 2,456) of a community-researcher partnership called the Rapid Employment and Development Initiative (READI) Chicago. The program offered an 18-month job alongside cognitive behavioral therapy and other social support. Both algorithmic and human referral methods identified men with strikingly high scope for gun violence reduction: for every 100 people in the control group, there were 11 shooting and homicide victimizations during the 20-month outcome period. Fifty-five percent of the treatment group started programming, comparable to take-up rates in programs for people facing far lower mortality risk. After 20 months, there is no statistically significant change in an index combining three measures of serious violence, the study’s primary outcome. Yet there are signs that this program model has promise. One of the three measures, shooting and homicide arrests, declined 65% (p = .13 after multiple-testing adjustment). Because shootings are so costly, READI generated estimated social savings between $182,000 and $916,000 per participant (p = .03), implying a benefit-cost ratio between 4:1 and 18:1. Moreover, participants referred by outreach workers—a prespecified subgroup—saw enormous declines in arrests and victimizations for shootings and homicides (79% and 43%, respectively) which remain statistically significant even after multiple-testing adjustments. These declines are concentrated among outreach referrals with higher predicted risk, suggesting that human and algorithmic targeting may work better together.

When studying an outcome Y that is weakly positive but can equal zero (e.g., earnings), researchers frequently estimate an average treatment effect (ATE) for a “log-like” transformation that behaves like log (Y) for large Y but is defined at zero (e.g., log (1 + Y), arcsinh(Y)). We argue that ATEs for log-like transformations should not be interpreted as approximating percentage effects, since unlike a percentage, they depend on the units of the outcome. In fact, we show that if the treatment affects the extensive margin, one can obtain a treatment effect of any magnitude simply by rescaling the units of Y before taking the log-like transformation. This arbitrary unit dependence arises because an individual-level percentage effect is not well-defined for individuals whose outcome changes from zero to nonzero when receiving treatment, and the units of the outcome implicitly determine how much weight the ATE for a log-like transformation places on the extensive margin. We further establish a trilemma: when the outcome can equal zero, there is no treatment effect parameter that is an average of individual-level treatment effects, unit invariant, and point identified. We discuss several alternative approaches that may be sensible in settings with an intensive and extensive margin, including (i) expressing the ATE in levels as a percentage (e.g., using Poisson regression), (ii) explicitly calibrating the value placed on the intensive and extensive margins, and (iii) estimating separate effects for the two margins (e.g., using Lee bounds). We illustrate these approaches in three empirical applications.

We propose an economic framework for determining the optimal allocation of a scarce supply of vaccines that become gradually available during a public health crisis, such as the COVID-19 pandemic. Agents differ in observable and unobservable characteristics, and the designer maximizes a social welfare function over all feasible mechanisms—accounting for agents’ characteristics, as well as their endogenous behavior in the face of the pandemic. The framework emphasizes the role of externalities and incorporates equity as well as efficiency concerns. Our results provide an economic justification for providing vaccines immediately and for free to some groups of agents, while at the same time showing that a carefully constructed pricing mechanism can improve outcomes by screening for individuals with the highest private and social benefits of receiving the vaccine. The solution casts light on the classic question of whether prices or priorities should be used to allocate scarce public resources under externalities and equity concerns.

We show that in a broad class of menu cost models, the first-order dynamics of aggregate inflation in response to arbitrary shocks to aggregate costs are nearly the same as in Calvo models with suitably chosen Calvo adjustment frequencies. We first prove that the canonical menu cost model is first-order equivalent to a mixture of two time-dependent models, which reflect the extensive and intensive margins of price adjustment. We then show numerically that in any plausible parameterization, this mixture is well approximated by a single Calvo model. This close numerical fit carries over to other standard specifications of menu cost models. Thus, for shocks that are not too large, the Phillips curve for a menu cost model looks like the New Keynesian Phillips curve, but with a higher slope.

Debates about the taxation of business owners often center on the distributional effects of these taxes, particularly the degree to which they affect workers. Drawing on a new linked owner-firm-worker data set created from U.S. administrative tax records, I analyze how an increase in the top marginal tax rate faced by business owners affected the earnings of their employees. I use panel difference-in-differences methods to compare the earnings of workers in similar firms but whose owners were differentially exposed to the tax increase. I estimate that 11–18 cents per dollar of new business income tax liability was passed through to employee earnings. I find no change in employment in response to the tax increase. The responses were generally associated with lower earnings growth, not changes in workforce composition. The burden was not borne equally by all workers. Essentially all of the workers’ share of the burden was borne by those in the top 30% of the earnings distribution, highlighting that the ultimate distributional effects of the policy depend not only on the share of the burden borne by workers but on the shares borne by different types of workers. Furthermore, since the owners bore the majority of the burden, the policy resulted in a decrease in after-tax earnings inequality between top-bracket owners and lower-bracket workers. I discuss the implications of the findings for the mediating labor market mechanisms and for welfare analyses of income taxation using a marginal value of public funds framework.

This article explores the use of social signaling as a policy tool to sustainably affect childhood immunization. In a 26-month field experiment with public clinics in Sierra Leone, I introduce a verifiable signal-in the form of color-coded bracelets-given to children upon timely completion of the first four or all five required vaccinations. Signals increase parents' belief in the visibility of their actions and knowledge of other children's vaccine status. The impact of signals varies significantly with the cost and perceived benefits of the action. There are no discernible effects on timely and complete immunization when the signal is linked to an easier-to-complete vaccine with low perceived benefits, and large positive effects when the signal is linked to a costlier-to-achieve vaccine with high perceived benefits. Parents adjust their behavior nine months before realizing the social image benefit, demonstrating the motivational strength of signaling incentives. Of substantive policy importance, bracelets increase full immunization at one year of age by 9 percentage points, with impacts persisting at two years of age. At a marginal cost of US$24.7 per fully immunized child, social signals can be as cost-effective as financial or in-kind incentives.

The racial wealth gap is the largest of the economic disparities between Black and white Americans, with a white-to-Black per capita wealth ratio of 6 to 1. It is also among the most persistent. In this article, we construct the first continuous series on white-to-Black per capita wealth ratios from 1860 to 2020, drawing on historical census data, early state tax records, and historical waves of the Survey of Consumer Finances, among other sources. Incorporating these data into a parsimonious model of wealth accumulation for each racial group, we document the role played by initial conditions, income growth, savings behavior, and capital returns in the evolution of the gap. Given vastly different starting conditions under slavery, racial wealth convergence would remain a distant scenario, even if wealth-accumulating conditions had been equal across the two groups since Emancipation. Relative to this equal-conditions benchmark, we find that observed convergence has followed an even slower path over the past 150 years, with convergence stalling after 1950. Since the 1980s, the wealth gap has widened again as capital gains have predominantly benefited white households, and convergence via income growth and savings has come to a halt.

The Neolithic revolution saw the independent development of agriculture among at least seven unconnected hunter-gatherer populations. I propose that the rapid spread of agricultural techniques resulted from increased climatic seasonality causing hunter-gatherers to adopt a sedentary lifestyle and store food for the season of scarcity. Their newfound sedentary lifestyle and storage habits facilitated the invention of agriculture. I present a model and support it with global climate data and Neolithic adoption dates, showing that greater seasonality increased the likelihood of agriculture’s invention and its speed of adoption by neighbors. This study suggests that seasonality patterns played a dominant role in determining our species’ transition to farming.

Many consumers care about climate change and other externalities associated with their purchases. We analyze the behavior and market effects of such “socially responsible consumers” in three parts. First, we develop a flexible theoretical framework to study competitive equilibria with rational consequentialist consumers. In violation of price taking, equilibrium feedback nontrivially dampens the impact of a person’s consumption on aggregate consumption, undermining the motive to mitigate. This leads to a new type of market failure, where even consumers who fully “internalize the externality” overconsume externality-generating goods. At the same time, socially responsible consumers change the relative effectiveness of taxes, caps, and other policies in lowering the externality. Second, since consumer beliefs about and preferences over their market impacts play a crucial role in our framework, we investigate them empirically via a tailored survey. Consistent with our model, consumers are often consequentialist, and many believe that they have a dampened impact on aggregate consumption. Inconsistent with our model, however, we also find many respondents who expect to have a one-to-one impact on aggregate consumption. Third, therefore, we analyze how such “naive” consumers modify our theoretical conclusions. They consume less than rational consumers in a single-good economy, but may consume more in a multigood economy with cross-market spillovers. A mix of naive and rational consumers may yield the worst outcomes.