U.S. unemployment due to the onset of the coronavirus pandemic was widespread, as was U.S. economic insecurity. In terms of consumption, aggregate retail sales fell by 16 percent in April 2020, the largest fall on record. While retail spending recovered by mid-July, spending on services remained significantly depressed. In contrast to aggregate spending and U.S. labor market data, there is little real-time data on the impact of the coronavirus pandemic on consumer spending inequality. This project will use a new transaction-level, real-time dataset from Earnest Research to measure consumer spending inequality in the United States and assess the impact of the pandemic on consumption inequality. The dataset contains information on a panel of 6 million households and is updated with a delay of just 1 week. Abdelwahed and Robbins will be able to study the outflows of spending, as well as the inflows of payments from wages and salaries, stimulus payments, and other government transfers into the households’ accounts, allowing them to construct a series on various ratios of spending between the top and bottom percentiles in order to study changes in consumer spending inequality along the distribution. They will also measure the effects of the pandemic on consumption of those who lost their jobs or experienced lower incomes and will compare them to individuals who retained their jobs. Abdelwahed and Robbins will estimate the impact of government stimulus payments and Unemployment Insurance on consumer spending inequality and consumption patterns. The data will be released publicly at the aggregate level at both the state and county levels, and the two researchers plan to release quarterly reports, providing other researchers and policymakers with a valuable new data source.

The 2008 global financial crisis outlined the need for a policy toolkit that lessens the pain of financial cycles for the real economy. In particular, conventional macroeconomic policies undertaken by public authorities in the aftermath of the crisis lead to extremely low interest rates and put public finances under heavy strain. During this period, macroprudential regulation established itself as a new cornerstone of regulators’ toolkits. Yet most models evaluating the potential benefits from macroprudential regulation consider redistribution as a side effect by using representative agent models. This project asks whether the redistribution channel calls for stronger or weaker macroprudential regulations, how the effectiveness of prudential capital controls as a financial stability tool are affected by the distribution of income, and what the distributional implications are of prudential regulations. The authors will build on existing research that presents models showing that monetary policy may impact income inequality in ways that then turn out to affect the transmission mechanism for such policy. First, they will be extending models that focus on the closed economy context to the open economy context. Second, they will be providing both a theoretical and a quantitative analysis of the transmission channels associated with capital controls. Third, they will perform their analysis in a dynamic context.

Understanding the degree to which, and how, hurricanes have had disparate effects across disadvantaged and advantaged groups in the United States is key to policymakers’ ability to craft climate policy that ensures disadvantaged communities do not bear the brunt of our warming world. Most of the literature in this area has focused on average impacts, with relatively little attention paid to heterogeneity. But even in cases where no negative impacts of natural disasters are found, on average, some subgroups may experience substantial negative effects. This project leverages newly linked administrative tax data from the IRS and demographic information from the American Community Survey and decennial census with exogenous variation in individual-level exposure to all hurricanes in the United States between 1995 and 2019. The analysis seeks to uncover a deeper understanding of the consequences of and responses to hurricanes, and how these effects differ across socioeconomic and demographic groups.

Confronting climate change will require the United States to dramatically reshape large portions of its economy. Carbon-intensive sectors in manufacturing and mining, which have long been bastions for middle-class jobs in communities across the country, are expected to shrink. Fears among workers and the communities that rely on these jobs are not unjustified, given recent economic research on the effect of trade shocks and environmental regulations. Yet reductions in carbon-intensive industries are only one side of the coin in addressing climate change. While many industries may shrink, a dramatic investment in green and renewable industries may create new opportunities for workers throughout the country. There is almost no economic research, however, exploring whether and how green jobs will benefit workers and their communities. Leveraging job-posting data from Burning Glass Technologies, along with the U.S. Census Bureau’s Longitudinal Employer Household Dynamics, Curtis and Marinescu will estimate the long-run benefits that workers accrue when green technology investments in solar and wind are made in their communities, as well as which types of workers benefit and which do not. The three researchers also are planning to estimate the effect of having more green jobs on local economic outcomes, such as the employment rate, poverty rate, and average incomes.

This project will convene economists, political scientists, energy scholars, and policy practitioners to synthesize collective expertise on the role of carbon pricing and innovation in climate policy. Participants will discuss how carbon pricing has been used around the world, its economic and political potential as a climate policy tool, and the importance of considering political economy in the design, implementation, and durability of climate policies.

Forty-two percent of Americans report that they do not have savings that could be used to cover unexpected expenses, a staggeringly high number. And there are stark racial differences, with 38 percent of White households and 55 percent of Black households saying they don’t have money to cover an emergency expense—one manifestation of the Black-White wealth divide. Yet there is surprisingly little research on how typical month-to-month fluctuations in income affect consumption and even less evidence on how this consumption smoothing varies with wealth. Given how central consumption dynamics are for macroeconomics, it’s important to understand the sensitivity of consumption to income and how that might vary by race and wealth. This project uses exciting new data to explore how income shocks may be passed through to consumption. By linking deidentified administrative bank data with self-reported race information from voter registration records, the authors will be able to identify the response of consumption by race with a large enough dataset (the analysis sample consists of 1.8 million matched bank-voter records) to identify racial differences credibly. Understanding how well households can smooth consumption, and how and why some groups—such as Black and Hispanic households who have lower-than-average wealth—may face greater challenges in doing so, is central for developing policy to address economic inequality and ensure vulnerable households achieve economic security.