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.

In virtually all areas of the U.S. healthcare service sector, physicians are barred from referring patients to entities in which they have an ownership stake. But this is not the case for the dialysis industry, which is exempt from such restrictions. Joint ventures between physicians and dialysis facilities exist at nearly 20 percent of facilities. This research will explore how physicians’ ownership ties with dialysis firms affect steering, spending, and outcomes. Using data obtained from a Freedom of Information Act request from the Centers for Medicare and Medicaid Services, Eliason, McDevitt, and Roberts will construct a first-of-its-kind dataset that tracks the ownership of dialysis facilities, including whether physicians have an ownership stake. They will add in data on dialysis providers and patients, including detailed Medicare claims and rich information on patient characteristics and health outcomes. An event-study analysis will allow the three researchers to test whether there is a clear trend-break in new patient arrivals and referrals when parties enter into a joint venture in order to examine how integration affects competition. The analysis will enable the researchers to study how patient caseloads and referrals at unintegrated facilities change after a nearby rival forms a joint venture, along with the impact of vertical integration on patient outcomes such as hospitalizations and mortality, as well as overall Medicare spending. Prior research has found that Black, Latinx, and low-income patients suffer disproportionately from kidney failure and often receive worse care, potentially making these groups especially vulnerable to providers’ growing market power and physicians’ conflicting interests.

Johnson and Levine seek to understand how enforcement of government safety regulations affects workers’ wages and how the effect differs across groups of workers based on income, race, and ethnicity in the United States. While prior work focused on whether inspections lower subsequent workplace injuries and affect overall establishment payroll, scholars don’t know much, if anything, about the impact of inspections on individual workers’ wages. If regulatory enforcement lowers wages at the same time it improves health and safety, then the overall effects on worker well-being may be mixed. The two researchers will utilize the randomness of inspections by the U.S. Occupational Safety and Health Administration. This setting offers a unique opportunity to evaluate the effects of inspections as if examining a randomized controlled trial. Johnson and Levine plan to compare the trajectories of establishments (and workers at those establishments) randomly selected for inspection to those eligible but not selected for inspection. Inspection data will be linked to the Longitudinal Employer-Household Dynamics data series. In addition to yielding new evidence about the impact of safety and health regulatory enforcement on workers’ wages, this work also has the potential to contribute to the current literature on monopsony power in labor markets by investigating whether the effect of inspections on wages varies by local labor market concentration.

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.

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.

When humans undertake physically intensive tasks, the body must release heat to maintain a safe internal temperature. Worker safety organizations have strict guidelines for climate conditions under which it is safe for workers to perform strenuous manual labor. Rising temperatures from climate change will increase the risk of heat stress, making outdoor work more difficult. This study seeks to quantify these implications for capital accumulation, growth, and consumption by building a discrete time growth model of a closed economy. Unlike standard climate-economy models, Casey, Fried, and Gibson will account for differences in the way that climate affects the production of investment goods and services, compared to consumption goods and services. The model is designed to capture how vulnerability to climate change differs between consumption and investment sectors and how this difference evolves over time. It builds on past work by considering climate change as a determinant of productivity and considering a more disaggregated representation of the economy.