Information about preferences for treatment and prevention policies can help policy makers more effectively allocate public health resources. We estimate a random utility model of preferences for treatment and prevention policies and explore sources of systematic heterogeneity in preferences. Marginal utility associated with avoided deaths is about twice as high for prevention policies as for treatment policies, and there is significant heterogeneity with respect to disease type, the group targeted by the policy, and respondent characteristics.
The "value of a statistical life" (VSL) is shorthand for an important concept, but the term tends flummox people who are unfamiliar with it. The VSL actually measures people's "willingness to swap alternative goods and services for a tiny reduction in the chance of sudden death." The general public (and many politicians) would be less angry/alarmed/confused if we came up with a better shorthand. I also argue that economists' continual pursuit of a single number for "the" VSL is misguided and can be misleading.
We estimate demand for environmental polices to improve health, using choice experiments concerning community-lvel illnesses and premature deaths avoided, policy duration, and the affected population size. Preferences for policy attributes vary systematically with the scenario design, with the source of risk and type of health threat, and with respondent characteristics. Omission of illness information biases upwards the value of avoided premature deaths, and individuals view avoided deaths and avoided illnesses as substitutes.
Individuals’ demands for programs targeting a particular illness are higher when there is a history of that illness and when subjective risks are higher. A history of other illnesses and greater other-illness subjective risks decrease demand. These comorbidity effects operate through the marginal utilities of both (i) adverse health states and (ii) income.
We develop and test an empirical model of individuals' intertemporal demands for programs to mitigate health risks over the remaining years of their lives. We find qualified support for the Erhlich (2000) life-cycle model, which predicts that individuals expect to derive increasing marginal utility from reducing health risks that come to bear later in their lives. However, we also find that as individuals age, there appears to be a systematic downward shift in their anticipated schedule of marginal utility for risk reduction at future ages. Our model improves upon earlier work by differentiating between the respondent's current age and the future ages at which they would experience adverse health states.