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 provide a graphical illustration of how standard consumer and producer theory can be used to quantify the welfare loss associated with inefficient pricing in insurance markets with selection. We then show how this welfare loss can be estimated empirically using identifying variation in the price of insurance. Such variation, together with quantity data, allows us to estimate the demand for insurance. The same variation, together with cost data, allows us to estimate how insurer's costs vary as market participants endogenously respond to price. The slope of this estimated cost curve provides a direct test for both the existence and nature of selection, and the combination of demand and cost curves can be used to estimate welfare. We illustrate our approach by applying it to data on employer-provided health insurance from one specific company. We detect adverse selection but estimate that the quantitative welfare implications associated with inefficient pricing in our particular application are small, in both absolute and relative terms.

We develop a set of frameworks for welfare analysis of Medicaid and apply them to the Oregon Health Insurance Experiment, a Medicaid expansion for low-income, uninsured adults that occurred via random assignment. Across different approaches, we estimate recipient willingness to pay for Medicaid between $0.5 and $1.2 per dollar of the resource cost of providing Medicaid; estimates of the expected transfer Medicaid provides to recipients are relatively stable across approaches, but estimates of its additional value from risk protection are more variable. We also estimate that the resource cost of providing Medicaid to an additional recipient is only 40% of Medicaid's total cost; 60% of Medicaid spending is a transfer to providers of uncompensated care for the low-income uninsured.

Approaches to Estimating the Health State Dependence of the Utility Function by Amy Finkelstein, Erzo F. P. Luttmer and Matthew J. Notowidigdo. Published in volume 99, issue 2, pages 116-21 of American Economic Review, May 2009

We estimate the effect of current location on elderly mortality by analyzing outcomes of movers in the Medicare population. We control for movers' origin locations as well as a rich vector of pre-move health measures. We also develop a novel strategy to adjust for remaining unobservables, using the correlation of residual mortality with movers' origins to gauge the importance of omitted variables. We estimate substantial effects of current location. Moving from a 10th to a 90th percentile location would increase life expectancy at age 65 by 1.1 years, and equalizing location effects would reduce cross-sectional variation in life expectancy by 15 percent. Places with favorable life expectancy effects tend to have higher quality and quantity of health care, less extreme climates, lower crime rates, and higher socioeconomic status.

We document four similarities between American human healthcare and American pet care: (i) rapid growth in spending as a share of GDP over the last two decades; (ii) strong income-spending gradient; (iii) rapid growth in the employment of healthcare providers; and (iv) similar propensity for high spending at the end of life. We speculate about possible implications of these similar patterns in two sectors that share many common features but differ markedly in institutional features, such as the prevalence of insurance and of public sector involvement.

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.

We leverage spatial variation in the severity of the Great Recession across the United States to examine its impact on mortality and explore the quantitative implications. We estimate that an increase in the unemployment rate of the magnitude of the Great Recession reduces the average annual age-adjusted mortality rate by 2.3%, with effects persisting for at least 10 years. Mortality reductions appear across causes of death and are concentrated in the half of the population with a high school degree or less. We estimate similar percentage reductions in mortality at all ages, with declines in elderly mortality thus responsible for about three-quarters of the total mortality reduction. Recession-induced mortality declines are driven primarily by external effects of reduced aggregate economic activity on mortality, and reduced air pollution appears to be a quantitatively important mechanism. Incorporating our estimates of procyclical mortality into a standard macroeconomic framework substantially reduces the welfare costs of recessions, particularly for people with less education, and at older ages.

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.