another. In theory, the total social value associated with the decrease in risk of a given health

problem resulting from a given reduction in pollution concentrations is generally taken to be the

sum of everyone’s WTP for the benefits they receive.

Epidemiological studies allow us to estimate the number of cases of an adverse health effect that

would be avoided by a given reduction in pollutant concentrations. If we have an estimate of the

average individual’s WTP for the risk reduction conferred upon him, we can derive from that an

estimate of the value of a statistical case avoided. Suppose, for example, that a given reduction in

pollutant concentrations results in a decrease in mortality risk of 1/10,000. Then for every

10,000 individuals, one individual would be expected to die in the absence of the reduction in

pollutant concentrations (who would not be expected to die in the presence of the reduction in

pollutant concentrations). If the average individual’s WTP for this 1/10,000 decrease in mortality

risk is \$100, then the value of a statistical life is 10,000 x \$100, or \$1 million. In general, the ex

ante WTP for a risk reduction of x can be converted into an ex post value of a statistical case

avoided by dividing the average individual’s WTP for the risk reduction of x by x (e.g.

\$100/0.0001 = \$1,000,000). The same type of calculation can produce values for statistical

incidences of other health endpoints.

Sometimes those values come from contingent valuation studies, in which study participants are

queried about their WTP to avoid a specific adverse health effect. When WTP estimates are not

available, it can be approximated by other measures, most notably cost of illness measures.

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