The 10 most-cited articles in The Quarterly Journal of Economics, 2023

Abstract 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), $\operatorname{arcsinh}(Y)$). 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…

We build a publicly available database that tracks economic activity in the United States at a granular level in real time using anonymized data from private companies. We report weekly statistics on consumer spending, business revenues, job postings, and employment rates disaggregated by county, sector, and income group. Using the publicly available data, we show how the COVID-19 pandemic affected the economy by analyzing heterogeneity in its effects across subgroups. High-income individuals reduced spending sharply in March 2020, particularly in sectors that require in-person interaction. This reduction in spending greatly reduced the revenues of small businesses in affluent, dense areas. Those businesses laid off many of their employees, leading to widespread job losses, especially among low-wage workers in such areas. High-wage workers experienced a V-shaped recession that lasted a few weeks, whereas low-wage workers experienced much larger, more persistent job losses. Even though consumer spending and job postings had recovered fully by December 2021, employment rates in…

Abstract This article documents the economic relevance of measuring cognitive uncertainty: people’s subjective uncertainty over their ex ante utility-maximizing decision. In a series of experiments on choice under risk, the formation of beliefs, and forecasts of economic variables, we show that cognitive uncertainty predicts various systematic biases in economic decisions. When people are cognitively uncertain—either endogenously or because the problem is designed to be complex—their decisions are heavily attenuated functions of objective probabilities, which gives rise to average behavior that is regressive to an intermediate option. This insight ties together a wide range of empirical regularities in behavioral economics that are typically viewed as distinct phenomena or even as reflecting preferences, including the probability weighting function in choice under risk; base rate insensitivity, conservatism, and sample size effects in belief updating; and predictable overoptimism and -pessimism in forecasts of economic variables. Our results offer a blueprint for how a simple…

Abstract Reducing the emissions of greenhouse gases may be almost impossible without a green transition—a substantial transformation of consumption and production patterns. To study such transitions, we propose a dynamic model, which differs from the common approach in economics in two ways. First, consumption patterns reflect not just changing prices and taxes, but changing values. Transitions of values and technologies create a dynamic complementarity that can help or hinder a green transition. Second, and unlike fictitious social planners, policy makers in democratic societies cannot commit to future policy paths, as they are subject to regular elections. We show that market failures and government failures can interact to prevent a welfare-increasing green transition from materializing or make an ongoing green transition too slow.

Abstract Recent scholarship has suggested that artificial intelligence (AI) technology and autocratic regimes may be mutually reinforcing. We test for a mutually reinforcing relationship in the context of facial-recognition AI in China. To do so, we gather comprehensive data on AI firms and government procurement contracts, as well as on social unrest across China since the early 2010s. We first show that autocrats benefit from AI: local unrest leads to greater government procurement of facial-recognition AI as a new technology of political control, and increased AI procurement indeed suppresses subsequent unrest. We show that AI innovation benefits from autocrats’ suppression of unrest: the contracted AI firms innovate more both for the government and commercial markets and are more likely to export their products; noncontracted AI firms do not experience detectable negative spillovers. Taken together, these results suggest the possibility of sustained AI innovation under the Chinese regime: AI innovation entrenches the regime, and the regime’s investment in AI for political…

Abstract 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,…

Abstract We develop a new class of general-equilibrium models with partially unfunded debt to propose a fiscal theory of persistent inflation. In response to business cycle shocks, the monetary authority controls inflation and the fiscal authority stabilizes debt. However, the central bank accommodates unfunded fiscal shocks, causing persistent movements in inflation, output, and real interest rates. In an estimated quantitative model, fiscal inflation accounts for the bulk of inflation dynamics. In the aftermath of the pandemic, unfunded fiscal shocks sustain the recovery but also cause a persistent increase in inflation. The model is able to predict the inflationary effects of the American Rescue Plan Act fiscal stimulus out of sample and with real-time data.

More than two million U.S. households have an eviction case filed against them each year. Policy makers at the federal, state, and local levels are increasingly pursuing policies to reduce the number of evictions, citing harm to tenants and high public expenditures related to homelessness. We study the consequences of eviction for tenants using newly linked administrative data from two major urban areas: Cook County (which includes Chicago) and New York City. We document that before housing court, tenants experience declines in earnings and employment and increases in financial distress and hospital visits. These pre trends pose a challenge for disentangling correlation and causation. To address this problem, we use an instrumental variables approach based on cases randomly assigned to judges of varying leniency. We find that an eviction order increases homelessness and hospital visits and reduces earnings, durable goods consumption, and access to credit in the first two years. Effects on housing and labor market outcomes are driven by effects for female and Black tenants. In the…

Abstract We develop a model in which specialized bond investors must absorb shocks to the supply and demand for long-term bonds in two currencies. Since long-term bonds and foreign exchange are both exposed to unexpected movements in short-term interest rates, a shift in the supply of long-term bonds in one currency influences the foreign exchange rate between the two currencies, as well as bond term premia in both currencies. Our model matches several important empirical patterns, including the comovement between exchange rates and term premia, and the finding that central banks’ quantitative easing policies affect exchange rates. An extension of our model links spot exchange rates to the persistent deviations from covered interest rate parity that have emerged since 2008.

Abstract This article investigates gender differences in the job search process in the field and lab. Our analysis is based on rich information on initial job offers and acceptances from undergraduates of Boston University’s Questrom School of Business. We find (i) a clear gender difference in the timing of job offer acceptance, with women accepting jobs substantially earlier than men, and (ii) a sizable gender earnings gap in accepted offers, which narrows in favor of women over the course of the job search period. To understand these patterns, we develop a job search model that incorporates gender differences in risk aversion and overoptimism about prospective offers. We validate the model’s assumptions and predictions using the survey data and present empirical evidence that the job search patterns in the field can be partly explained by the greater risk aversion displayed by women and the higher levels of overoptimism displayed by men. We replicate these findings in a laboratory experiment that features sequential job search and provide direct evidence on the purported…