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Rising costs of disability insurance (DI) programs are putting increased strain on central government budgets, yet little is known about how well countries target those in the poorest health. In this paper, we use the SHARE and HRS surveys to measure the average health of people aged 50-64 receiving DI, and the effectiveness of the DI safety net in covering those in poor health. The U.S. and Denmark appear successful at targeting benefits, with France and Belgium less so. These measures can also be used over time to evaluate country-level policy changes.

There is strong interest in both developing and developed countries toward expanding health insurance coverage. How should the benefits, and costs, of expanded coverage be measured? While the value of reducing the financial risks that result from insurance coverage have long been recognized, there has been less attention in how best to measure such benefits. In this paper, we first provide a framework for assessing the financial value from health insurance. We focus on three distinct potential benefits: Pooling the risk of unexpected medical expenditures between healthy and sick households, redistributing resources from high- to low-income recipients and smoothing consumption over time. We then use this theoretical framework and an illustrative example to provide practical guidelines for benefit-cost analysis in capturing the full benefits (and costs) of expanding health insurance coverage. We conclude by considering other potential financial effects of broad insurance coverage, such as the ability to consolidate purchases and thus lower input prices.

There is growing concern over the rising share of the US economy devoted to health care spending. Fueled in part by demographic transitions, unchecked increases in entitlement spending will necessitate some combination of substantial tax increases, elimination of other public spending, or unsustainable public debt. This massive increase in health spending might be warranted if each dollar devoted to the health care sector yielded real health benefits, but this does not seem to be the case. Although we have seen remarkable gains in life expectancy and functioning over the past several decades, there is substantial variation in the health benefits associated with different types of spending. Some treatments, such as aspirin, beta blockers, and flu shots, produce a large health benefit per dollar spent. Other more expensive treatments, such as stents for cardiovascular disease, are high value for some patients but poor value for others. Finally, a large and expanding set of treatments, such as proton-beam therapy or robotic surgery, contributes to rapid increases in spending despite questionable health benefits. Moving resources toward more productive uses requires encouraging providers to deliver and patients to consume high-value care, a daunting task in the current political landscape. But widespread inefficiency also offers hope: Given the current distribution of resources in the US health care system, there is tremendous potential to improve the productivity of health care spending and the fiscal health of the United States.

Even among households with similar socioeconomic characteristics, saving and wealth vary considerably. Life-cycle models attribute this variation to differences in time preference rates, risk tolerance, exposure to uncertainty, relative tastes for work and leisure at advanced ages, and income replacement rates. These factors have testable implications concerning the relation between accumulated wealth and the shape of the consumption profile. Using the Panel Study of Income Dynamics and the Consumer Expenditure Survey, we find little support for these implications. The data are instead consistent with "rule of thumb," "mental accounting," or hyperbolic discounting theories of wealth accumulation. (JEL D1, D91, E21)