Improving the Valuation of Risk Reductions

University Of Oregon Eugene, Eugene OR

Investigators

Abstract

This project develops strategies for dealing with a number of common methodological challenges in the non-market valuation of risk reductions. The findings can be expected to improve the way researchers infer the benefits of reduced mortality and morbidity risks when they conduct benefit-cost analyses for public policies intended to protect human life and health. Using an unusually large and rich survey data set, the primary research agenda is to model demands for risk mitigation in a way that accommodates an unusually wide array of individual differences. The survey sample is drawn from the general population, including men and women as well as a wide range of ethnicities, ages, and income groups, and it assesses a wide range of health risks, including the most prevalent set of major health risks (named illnesses and injuries) and a wide range of illness profiles and risk reductions. The purpose is to develop richer predictive behavioral models. We will study: (a) Respondents' subjective updating of any risk information that is provided as part of a valuation survey. In both valuation studies and public education campaigns, individuals may not fully accept the asserted risk level, the risk reduction, or the latency period associated with the onset of risk. We will control for subjective risks and simulate counterfactual values for risk reductions that would have been expressed had each respondent passively accepted the "objective" risk information. (b) Perceived availability of averting/defensive/mitigating measures and the value of risk reductions. Available data include individuals' perceptions of the availability, the costs, and the effectiveness of averting/defensive/mitigating behaviors for reducing specific health risks. Demands for risk reductions may depend on the perceived costs of substitutes, and we will assess these effects; and, (c) Whether the value of a risk reduction is proportional to the size of the risk reduction. This proportionality assumption is central to the calculation of the Value of a Statistical Life (VSL), the expedient one-size-fits-all measure of benefits that is widely used to evaluate lifesaving policies. The proportionality assumption will be evaluated against at least four alternative assumptions about the marginal utility of risk mitigation.