Epidemiological studies suggesting a causal relationship between exposure to specific environmental pollutants and adverse health effects in children have flourished in recent years. Concern for children’s health risks from environmental pressures is reflected in the numerous examples of laws and regulations aimed at protecting children’s health.

Epidemiological studies suggesting a causal relationship between exposure to specific environmental pollutants and adverse health effects in children have flourished, particularly with respect to air pollution. Concern for children’s health risks from environmental pressures is reflected in the numerous examples of laws and regulations aimed at protecting children’s health.

Epidemiological studies suggesting a causal relationship between exposure to specific environmental pollutants and adverse health effects in children have flourished, particularly with respect to air pollution.1 While the evidence is far from definitive, it is becoming increasingly clear that children are particularly vulnerable to certain kinds of environmental health risks. Concern for children’s health risks from environmental pressures is reflected in the numerous examples of laws and regulations aimed at protecting children’s health [see Scapecchi (2007) for an overview].

Environmental policy affects human health by reducing environmental risks that result in either premature mortality or non-fatal ill-health. People attach value to the reductions in health risk associated with environmental policies, and valuing such benefits can be undertaken using either revealed preference or stated preference methods. Depending on the nature of the environmental pressure and health impact, it has been found that health benefits can represent a majority of benefits of policy interventions. However, most such studies have been done using adult samples, and there is a need for similar estimates for children.

There are a number of methodological complications which arise when valuing health risk reductions. These include issues associated with: the elicitation of preferences from third parties; household decision-making and composition; the low probability and unfamiliar or uncertain nature of the risks faced; the effects of different characteristics or types of risk; and, the discounting of future benefits for latent health impacts. In some cases these complications are likely to be most acute for the valuation of risk reductions for children.

Given the methodological complications associated with the valuation of health risk reductions for children, a considerable amount of survey development work was undertaken in the VERHI project. This involved innovative ways to communicate risk, present scenarios of wealth-risk trade-offs, and incorporate a rich set of alternative risk characteristics and types of risk reduction. Two different survey instruments were developed, one involving a conjoint choice experiment (Italy and Czech Republic) and the other a chaining methodology (United Kingdom and Czech Republic). In both cases contingent valuation methods were also applied, and in the Czech Republic a method involving direct “person trade-offs” was applied.

Value of Statistical Life (VSL) estimates both for children and adults are presented. Analysis of the data indicates (qualified) support for evidence for a ’child premium’, which is consistent with previous literature. This evidence is more robust in the case of the chaining instrument. Moreover, the effects on the estimated VSL of a large number of risk characteristics, demographic and economic factors, and programme attributes were obtained, and the main results are summarised. For instance, it is clear that context matters, but it plays a different role in the case of children and adults, with less variation across context for children than for adults.

While it is clear that there is no single ratio which can capture differences in risk preferences for children and adults, there is some evidence that the VSL for a child is greater than that of an adult. This has implications for policy evaluation and prioritisation, perhaps resulting in certain policy interventions passing benefit-cost tests when this would not have been the case with the use of an undifferentiated VSL. However, it is clear that further work is required.