We assess the impact of an increase in the co-payments for nursing home care on care use and welfare. Nursing home residents often have to pay substantial user fees, which expose them to a financial risk. Co-payments may incentivize efficient care use, but empirical evidence is limited. We leverage a reform in the Netherlands that increased co-payments for a group of individuals, and implement a difference-in-differences approach. An increase in the monthly co-payment induces users to postpone permanent nursing home admissions. The resulting savings are only partially offset by increases in home care use. There are no overall effects on mortality nor on children's care use and income. While the change in the monthly co-payment is modest, average lifetime payments increase substantially. The welfare loss due to the associated increase in financial risk for potential users likely outweighs the gains caused by the reduction in publicly financed care.
In aging societies, sustaining retirement income is a key policy challenge. Delaying public pension claims can mitigate longevity risk, especially for individuals with longer-than-average life expectancy or continued work capacity. Using survey-based experiments targeting Japanese workers aged 40-59, we evaluate policies to encourage delayed claiming. We examine three financial incentives-tax disincentives for early retirement, actuarially fair lump-sum payments, and steeper actuarial adjustments-with and without work opportunities beyond age 65. We also assess raising the normal pension age (NPA) from 65 to 67, distinguishing statutory from framing-based increases. Raising the NPA is most effective, delaying claims by 1.1 years on average. Work opportunities delay claims by 0.5 years, while financial incentives alone have limited effects. Packages combining a framed NPA reference age, work opportunities, and steeper adjustments may offer a politically feasible alternative to a statutory NPA increase.
Index insurance holds promise for smallholder farmers in developing countries, but its value is limited by basis risk. If basis risk can be informally shared, the value of index insurance may increase, potentially raising demand. Conversely, formal insurance may reduce informal risk sharing; if farmers anticipate this, their demand may decline, making the net effect ambiguous. We designed a lab experiment to study how informal risk sharing affects demand for index insurance and implemented it among farmers in Uganda. We find that demand for index insurance decreases in the presence of risk sharing, suggesting that informal arrangements crowd out formal insurance. We also find that absolute informal transfers are larger under index than under indemnity insurance. At the same time, the availability of risk sharing paradoxically reduces demand for index insurance, primarily by lowering high coverage choices. We discuss how strong sharing norms and behavioral motives may explain this finding.
We examine health insurance nonparticipation using a behavioral framework that integrates optimism bias with institutional safety nets. In our model, optimistic consumers underestimate their probability of health shocks. We show that nonparticipation-even under subsidized premiums-is rationalized by the interaction between optimism and an implicit medical bankruptcy floor that limits financial downside for low-wealth households. Testing these predictions with data from the Medical Expenditure Panel Survey, we create a proxy for optimism bias: the wedge between subjective health reports and objective clinical benchmarks. Consistent with theory, both lower income and higher optimism significantly depress insurance enrollment, with the behavioral friction concentrated among lower-income households. Finally, because optimism bias positively predicts ex-post healthcare expenditures across multiple care channels, our results are more consistent with a cognitive bias than private information.
This paper studies how information frictions shape demand, screening, and contract design in the U.S. cyber insurance market. I develop a framework in which firms sort into coverage based on latent cyber risk while insurers screen using coarse signals and manage residual exposure more through coverage quantities than through price. Using proprietary broker data, I document three findings consistent with this mechanism. First, higher-risk firms are more likely to enter the brokered market and apply for coverage. Second, conditional on application, insurer acceptance is more closely related to a survey-based score than to external risk measures that better capture realized incidents. Third, among issued policies, differences in assessed risk are reflected more in limits and adjusted coverage than in price. The results show that cyber insurance capacity is constrained not only by aggregate supply, but by how coarse risk classification generates residual adverse selection that insurers manage through contract design.
