Health expenditures as a share of GDP in the United States have more than tripled over the past half-century. A common conjecture is that this is a consequence of rising income. We investigate this hypothesis by instrumenting for local area income with time series variation in oil prices interacted with local oil reserves. This strategy enables us to capture both partial equilibrium and local general equilibrium effects of income on health expenditures. Our central income elasticity estimate is 0.7, with 1.1 as the upper end of the 95% confidence interval, which suggests that rising income is unlikely to be a major driver of the rising health expenditure share of GDP.

Those involved with the criminal justice system have disproportionately high rates of mental illness and substance-use disorders, prompting speculation that health insurance, by improving treatment of these conditions, could reduce crime. Using the 2008 Oregon Health Insurance Experiment, which randomly made some low-income adults eligible to apply for Medicaid, we find no statistically significant impact of Medicaid coverage on criminal charges or convictions. These null effects persist for high-risk subgroups, such as those with prior criminal cases and convictions or mental health conditions. In the full sample, our confidence intervals can rule out most quasi-experimental estimates of Medicaid’s crime-reducing impact.

There is substantial waste in U.S. healthcare but little consensus on how to combat it. We identify one source of waste: long-term care hospitals (LTCHs). Using the entry of LTCHs into hospital markets in an event study design, we find that most LTCH patients would have counterfactually received care at Skilled Nursing Facilities—facilities that provide medically similar care but are paid significantly less—and that substitution to LTCHs leaves patients unaffected or worse off on all dimensions we can objectively measure. Our results imply Medicare could save about $4.6 billion per year by not allowing discharge to LTCHs.

We use linked survey and administrative data to document differences across multiple socio-economic and demographic groups in the extent of adverse economic and health impacts of the first two years of the COVID-19 pandemic in the United States. Across a wide set of characteristics-including race/ethnicity, education, industry, and occupation-the impacts of the pandemic on all-cause mortality and on employment were disproportionately concentrated in the same groups in the population. As the pandemic progressed, disparities in the pandemic's mortality impacts narrowed substantially between Black and White Americans and between Hispanic and White Americans, but persisted along the educational divide. For economic damages, only Hispanic-White disparities narrowed; Black-White and educational disparities persisted for the first two years of the pandemic. We also document greater mortality impacts for lower income individuals, with this negative income-excess mortality gradient becoming steeper in the pandemic's second year. Together our findings-using a consistent set of methods and measures on nationally representative data with a wide set of measures of socio-economic status-paint a detailed picture of the heterogeneous impacts of the first two years of the COVID-19 pandemic on health and economic well-being.

Using data from employer-provided health insurance and Medicare Part D, we investigate whether healthcare utilization responds to the dynamic incentives created by the nonlinear nature of health insurance contracts. We exploit the fact that, because annual coverage usually resets every January, individuals who join a plan later in the year face the same initial ("spot") price of healthcare but a higher expected end-of-year ("future") price. We find a statistically significant response of initial utilization to the future price, rejecting the null that individuals respond only to the spot price. We discuss implications for analysis of moral hazard in health insurance.

We study the sources of high end-of-life spending for cancer patients. Even among patients with similar initial prognoses, spending in the year postdiagnosis is over twice as high for those who die within the year than those who survive. Elevated spending on decedents is predominantly driven by higher inpatient spending, particularly low-intensity admissions. However, most such admissions do not result in death, making it difficult to target spending reductions. Furthermore, end-of-life spending is substantially more elevated for younger patients, compared to older patients with similar prognoses. Results highlight sources of high end-of-life spending without revealing any natural “remedies.”