I examine the effects that the 1986 Immigration Reform and Control Act (IRCA), which legalized almost 3 million immigrants, had on crime in the United States. I exploit the IRCA's quasi-random timing as well as geographic variation in the intensity of treatment to isolate causal impacts. I find decreases in crime of 3-5 percent, primarily due to decline in property crimes, equivalent to 120,000-180,000 fewer violent and property crimes committed each year due to legalization. I calibrate a labor market model of crime, finding that much of the drop in crime can be explained by greater labor market opportunities among applicants.

The increasing availability of data derived from linked consumer financial accounts has the potential to dramatically expand the potential for research. Examining the most comprehensive existing set of linked-account data, consisting of transaction and balance sheet data for millions of Americans, I demonstrate the power and versatility of such sources. I discuss advantages and concerns arising from this type of data and match a range of distributional moments to external sources. As one application, I test consumption elasticities across households with varying levels, and types, of debt. I find that heterogeneity in consumption elasticity can be explained entirely by credit and liquidity.

Job search is a key choice variable in theories of labor markets but is difficult to measure directly. We develop a job search activity index based on Google search data, the Google Job Search Index (GJSI). We validate the GJSI with both survey- and web-based measures of job search. Unlike those measures, the GJSI is high frequency, geographically precise, and available in real time. We demonstrate the GJSI’s utility by using it to study the effects of unemployment insurance policy changes between 2008 and 2014. We find no evidence of an economically meaningful effect of these changes on aggregate search.

Abstract Utilizing transaction-level financial data, we explore how household consumption responded to the onset of the COVID-19 pandemic. As case numbers grew and cities and states enacted shelter-in-place orders, Americans began to radically alter their typical spending across a number of major categories. In the first half of March 2020, individuals increased total spending by over 40% across a wide range of categories. This was followed by a decrease in overall spending of 25%–30% during the second half of March coinciding with the disease spreading, with only food delivery and grocery spending as major exceptions to the decline. Spending responded most strongly in states with active shelter-in-place orders, though individuals in all states had sizable responses. We find few differences across individuals with differing political beliefs, but households with children or low levels of liquidity saw the largest declines in spending during the latter part of March.

Abstract No previous infectious disease outbreak, including the Spanish Flu, has affected the stock market as forcefully as the COVID-19 pandemic. In fact, previous pandemics left only mild traces on the U.S. stock market. We use text-based methods to develop these points with respect to large daily stock market moves back to 1900 and with respect to overall stock market volatility back to 1985. We also evaluate potential explanations for the unprecedented stock market reaction to the COVID-19 pandemic. The evidence we amass suggests that government restrictions on commercial activity and voluntary social distancing, operating with powerful effects in a service-oriented economy, are the main reasons the U.S. stock market reacted so much more forcefully to COVID-19 than to previous pandemics in 1918–1919, 1957–1958, and 1968.

We examine a dynamic model of up-or-down problem solving. A decision maker can either spend resources investigating a new problem before deciding what to do or decide on the basis of similarity with precedent problems. Over time, a decision-making framework, or jurisprudence, develops. We focus on the model’s application to judge-made law. We show that judges summarily apply precedent in some cases. The law may converge to efficient or inefficient rules. With positive probability, identical cases are treated differently. As the court learns over time, inconsistencies become less likely. We discuss the existing empirical evidence and the model’s testable implications.

Abstract The 2020 CARES Act directed large cash payments to households. We analyze households’ spending responses using data from a Fintech nonprofit, exploring heterogeneity by income, recent income declines, and liquidity as well as linked survey responses about economic expectations. Households respond rapidly to payments, with spending increasing by about $0.14 per dollar during the first week and plateauing around 0.25–0.30 over 3 months. In contrast to previous stimulus programs, we see little response of durables spending. Households with lower incomes, greater income declines, and less liquidity display stronger responses whereas households that expect employment losses and benefit cuts display weaker responses.

Abstract How households shift spending across firms in response to income fluctuations is an important source of firm risk. Using transaction-level data, we study how households interact with the universe of retailers following income changes. We find that income increases within and across households result in substitution toward retailers in a category that are higher quality; smaller; more profitable; and have higher labor intensity, research and development (R&D) intensity, and equity betas. Although not all shifts are economically large, they do not average out across retailers. Thus, retailer choice has implications for key financial and macroeconomic outcomes, such as aggregate profitability and labor demand.

By matching a large database of individual macroforecaster data with the universe of sizable natural disasters across 54 countries, we identify a set of new stylized facts: forecasters are persistently heterogeneous in how often they issue or revise a forecast; information rigidity declines significantly following large, unexpected natural disaster shocks; and disagreement decreases among inattentive agents while it might increase for attentive ones. We develop a learning model that captures the two channels through which natural disaster shocks affect expectation formation: attention effect—the visibly large shocks induce immediate and synchronized updating of information for inattentive agents—and uncertainty effect—attentive agents might increase their acquisition of private information to compensate for the higher uncertainty after shocks.

Households tend to hold substantial amounts of non-financial assets in the form of consumer goods inventories that are unobserved by traditional measures of wealth, about $725 on average for products covered by our sample. Such holdings can eclipse total financial assets among households in the lowest income quintile. Households can obtain significant financial returns from strategically shopping and managing these inventories. In addition, they choose to maintain liquid savings—household working capital—not just for precautionary motives but also to support this inventory management. We demonstrate that households earn high marginal returns from investing in household working capital, well above 20% at low levels of inventory, though these marginal returns decline rapidly as inventory increases. Nevertheless, average returns from inventory management are high—about 50% for the typical household—and affect household portfolio returns substantially for all but the top income and asset quintiles. We provide evidence from scanner and survey data that supports this conclusion. For many households, working capital is therefore an important asset class that has been largely ignored by the household finance literature, and inventory management provides them with an alternative to investing in risky financial markets at low levels of liquid wealth.