Although theories from economics and evolutionary biology predict that one's age, health, and survival probability should be associated with one's subjective discount rate (SDR), few studies have empirically tested for these links. Our study analyzes in detail how the SDR is related to age, health, and survival probability, by surveying a sample of individuals in townships around Durban, South Africa. In contrast to previous studies, we find that age is not significantly related to the SDR, but both physical health and survival expectations have a U-shaped relationship with the SDR. Individuals in very poor health have high discount rates, and those in very good health also have high discount rates. Similarly, those with expected survival probability on the extremes have high discount rates. Therefore, health and survival probability, and not age, seem to be predictors of one's SDR in an area of the world with high morbidity and mortality.

The relationship between costs and health benefits of branded pharmaceuticals remains controversial. This paper examines the incremental costs incurred for incremental health benefits gained from the largest available sample of cost-effectiveness studies of branded drugs in the USA, the 1994–2015 Tufts Registry of Cost-Effectiveness Analyses. Earlier studies used small, specialized samples of drugs. We use linear regression analysis to estimate the association in those studies between additional quality-adjusted life years (QALYs) and incremental pharmaceutical costs. The preferred sample uses 476 studies involving branded pharmaceuticals with both higher costs and increased effectiveness compared to the previous standard of care. Regressions of costs on QALYs imply that an additional QALY is associated, on average, with a $28,561 increase in cost (95 % CI, $18,853–$38,270). This regression explains 20 % of the variation in sample costs. In this analytical sample, a share of the variation in the cost of pharmaceuticals is, therefore, not random but rather associated with variation in QALYs; prices are to some extent “value-based.” Our results are robust to varying sample inclusion criteria and to the funding source. In subgroup analyses, the highest cost per QALY was $44,367 (95 % CI, $35,373–$53,361). Costs of pharmaceuticals in this data set are, on average, lower than common estimates of the monetary value of a QALY to American consumers. As in other studies, we find that sellers of patent-protected beneficial new technology appear to capture only a fraction of the benefits provided.

There have been few empirical studies on how consumers respond to their loss experience over time when choosing between high- and low-deductible health insurance plans. To address this question, we designed a ten-period web-based experiment to explore how subjects respond to the presence or absence of illness-related costs in a given period when making their future health insurance choices when they are explicitly informed that future premiums or loss probabilities will not change over time. A sizable minority of the respondents who initially chose high-deductible plans switched after a loss, and switching is more likely if they self-report negative emotional responses to experiencing an uninsured loss. Switching from low- to high-deductible plans is less likely and less responsive to loss experience. The study reveals that many individuals make their health insurance choices by considering factors not included in classical economic models of choice.