Publication: Value of a Statistical Life in Road Safety : A Benefit-Transfer Function with Risk-Analysis Guidance Based on Developing Country Data
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2014-10
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2014-10
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We model a value of statistical life (VSL) transfer function for application to road-safety engineering in developing countries through an income-disaggregated meta-analysis of scope-sensitive stated preference VSL data. The income-disaggregated meta-analysis treats developing country and high-income country data separately. Previous transfer functions are based on aggregated datasets that are composed largely of data from high-income countries. Recent evidence, particularly with respect to the income elasticity of VSL, suggests that the aggregate approach is deficient because it does not account for a possible change in income elasticity across income levels. Our dataset (a minor update of the OECD database published in 2012) includes 123 scope-sensitive VSL estimates from developing countries and 185 scope-sensitive estimates from high-income countries. The transfer function for developing countries gives VSL = 1.3732E−4 × (GDP per capita)∧2.478, with VSL and GDP per capita expressed in 2005 international dollars (an international dollar being a notional currency with the same purchasing power as the U.S. dollar). The function can be applied for low- and middle-income countries with GDPs per capita above $1268 (with a data gap for very low-income countries), whereas it is not useful above a GDP per capita of about $20,000. The corresponding function built using high-income country data is VSL = 8.2474E+3 × (GDP per capita)∧.6932; it is valid for high-income countries but over-estimates VSL for low- and middle-income countries. The research finds two principal significant differences between the transfer functions modeled using developing-country and high-income-country data, supporting the disaggregated approach. The first of these differences relates to between-country VSL income elasticity, which is 2.478 for the developing country function and .693 for the high-income function; the difference is significant at p < 0.001. This difference was recently postulated but not analyzed by other researchers. The second difference is that the traffic-risk context affects VSL negatively in developing countries and positively in high-income countries. The research quantifies uncertainty in the transfer function using parameters of the non-absolute distribution of relative transfer errors. The low- and middle-income function is unbiased, with a median relative transfer error of −.05 (95% CI: −.15 to .03), a 25th percentile error of −.22 (95% CI: −.29 to −.19), and a 75th percentile error of .20 (95% CI: .14 to .30). The quantified uncertainty characteristics support evidence-based approaches to sensitivity analysis and probabilistic risk analysis of economic performance measures for road-safety investments.
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Publication The Value of a Statistical Life in the Context of Road Safety: A New Value Transfer Approach(Taylor and Francis, 2025-05-20)Objective: The value of a statistical life (VSL) is a key input for cost-benefit analysis (CBA) in the context of road safety and for calculations of the socio-economic costs of road crashes. However, many countries, especially low- and middle-income countries (LMIC), lack country-specific VSL estimates. To address this, value transfer is often used, where VSL estimates from other countries are adapted to local situations to estimate the VSL in the countries with no VSL estimates. This paper presents new guidance for VSL value transfer in the context of road safety. Method: A unit value transfer approach is applied, which implies that a base VSL is determined and used to estimate the VSL in other countries. We collected VSL estimates from 32 countries worldwide to determine base VSLs for both high-income countries (HIC) and LMIC. 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