Literature DB >> 21957946

Valuing mortality risk reductions from environmental, transport, and health policies: a global meta-analysis of stated preference studies.

Henrik Lindhjem1, Ståle Navrud, Nils Axel Braathen, Vincent Biausque.   

Abstract

We conduct, to our knowledge, the first global meta-analysis (MA) of stated preference (SP) surveys of mortality risk valuation. The surveys ask adults their willingness to pay (WTP) for small reductions in mortality risks, deriving estimates of the sample mean value of statistical life (VSL) for environmental, health, and transport policies. We explain the variation in VSL estimates by differences in the characteristics of the SP methodologies applied, the population affected, and the characteristics of the mortality risks valued, including the magnitude of the risk change. The mean (median) VSL in our full data set of VSL sample means was found to be around $7.4 million (2.4 million) (2005 U.S. dollars). The most important variables explaining the variation in VSL are gross domestic product (GDP) per capita and the magnitude of the risk change valued. According to theory, however, VSL should be independent of the risk change. We discuss and test a range of quality screening criteria in order to investigate the effect of limiting the MA to high-quality studies. When limiting the MA to studies that find statistically significant differences in WTP using external or internal scope tests (without requiring strict proportionality), we find that mean VSL from studies that pass both tests tend to be less sensitive to the magnitude of the risk change. Mean VSL also tends to decrease when stricter screening criteria are applied. For many of our screened models, we find a VSL income elasticity of 0.7-0.9, which is reduced to 0.3-0.4 for some subsets of the data that satisfy scope tests or use the same high-quality survey.
© 2011 Society for Risk Analysis.

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Year:  2011        PMID: 21957946     DOI: 10.1111/j.1539-6924.2011.01694.x

Source DB:  PubMed          Journal:  Risk Anal        ISSN: 0272-4332            Impact factor:   4.000


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