# **1. Introduction**

Economic analyses of development projects and policies often involve assigning monetary values to human lives, especially in the areas of public health, occupational safety, transportation, and environmental protection, where human lives can be significantly affected by a proposed project or policy change. As resources are finite, trade-offs between other resource uses and reducing risks to life are inevitable. In order to help make rational choices in these tradeoffs, a concept of value of a statistical life (VSL), as opposed to a specific person’s life, has been defined and extensively studied<sup>2</sup> . VSL is an economic value which measures the break-even point at which society as a whole is willing to pay (WTP) in order to reduce the statistical risk of death.

Extensive VSL studies have been conducted in the industrialized countries, however, few studies on VSL can be found in the developing world. Almost all of the previous studies indicate that the VSL estimation results are sensitive to the sectors studied, the estimation methods employed, the risk reduction levels as well as the demographic and economic characteristics of the studied population. It is therefore very important to directly estimate VSL for a country of concern.

A significant number of earlier VSL estimates come from studies that measure compensating differentials for on-the-job risk exposures in labor markets. Since the 1990s, however, the contingent valuation (CV) method has been widely used to estimate the value of a statistical life. An individual’s WTP for a specified death risk reduction can be elicited with a plausible CV scenario and a VSL can be estimated by dividing the WTP by the change in death probability. The advantage of the CV method over the traditional market approach is that a CV study can be flexibly designed even when no similar markets exist. This nature of the CV approach is especially important for the developing country context, because a good competitive market can hardly be found and data on risk and compensation are rarely available in most of the developing countries. However, the challenges in using the CV method to estimate VSL are enormous. Beside the conventional challenges in using CV method: questionnaire design, statistical analysis, strategic responses and elicitation method choices, etc., a particular challenge comes from the empirical finding that individuals may have difficulties in understanding a numeric probability change. Our analyses also show that the VSLs obtained from the previous CV studies which estimated WTPs for a couple of numeric risk reductions are incompatible with the theoretically defined marginal WTPs. These findings lead to suspicion of the validity and reliability of most of the previous CV studies for VSL estimation.

A contingent valuation study of health risk reduction was conducted in three provinces of China in 2000. A VSL can be calculated based upon the WTP information from that survey and the cancer morbidity and mortality data. In the CV survey, respondents are not asked to evaluate the abstract probability reduction as done in conventional risk valuation studies, which is usually a difficult task for the respondents to complete. Instead, they are asked whether or not they are willing to buy a cancer vaccine that is effective for one year. This CV scenario is easy to understand and is similar to a market transaction. WTP functions of risk reduction can be estimated with data of cancer morbidity and mortality, and a marginal value estimation of risk

> 2 A comprehensive literature review on VSL studies can be found  in Miller (1999), Viscusi and Aldy (2003) and Australian Safety and Compensation Council (2008).

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