Publication: The Value of a Statistical Life in the Context of Road Safety: A New Value Transfer Approach
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Date
2025-05-20
ISSN
1538-957X
Published
2025-05-20
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Abstract
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. According to the literature, the VSL is strongly correlated with income per capita. Therefore, income elasticities from the literature are applied to account for the impact of per capita income on the VSL.
Results: The resulting VSL transfer functions are VSL = 0.404*(Y/5,726)1.2 for LMIC and VSL = 3.206*(Y/42,087)0.8 for HIC, where VSL is the VSL in million USD and Y is the Gross National Income per capita (USD, 2020 prices). The VSL ranges from approximately 22,000 USD to 1.1 million USD in LMIC and from 1.2 million USD to 4.8 million USD in HIC.
Conclusions: We recommend applying this VSL transfer approach for cost-benefit analysis and road crash costing in countries lacking appropriate country-specific VSL. Moreover, this study highlights that, despite the growing interest in LMIC in research on VSL, the number of studies in these countries is still limited, emphasizing the need for more VSL studies. Finally, developing transfer functions for non-fatal injuries is recommended, which is an essential input for CBA as well.
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Publication Value of a Statistical Life in Road Safety : A Benefit-Transfer Function with Risk-Analysis Guidance Based on Developing Country Data(Elsevier, 2014-10)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.Publication Valuing Mortality and Morbidity in the Context of Disaster Risks(2009-02-01)Benefit-cost analyses of disaster risk reduction (DRR) projects are an important tool for evaluating the efficiency of such projects, and an important input into decision making. These analyses, however, often fail to monetize the benefits of reduced death and injury. The authors review the literature on valuing reduced death and injury, and suggest methods for calculating order-of-magnitude estimates of these benefits. Because few empirical estimates of the Value of a Statistical Life (VSL) are available for developing countries, methods for transferring estimates from high income to middle and low income countries are reviewed. The authors suggest using the range of values implied by an income elasticity of 1.0 and an elasticity of 1.5. With regard to injury valuation they discuss arguments for and against monetizing Quality Adjusted Life Years, and provide shortcuts to valuing injuries that may be used to assess their importance in DRR benefit-cost analyses.Publication The Value of Statistical Life : A Contingent Investigation in China(2010-09-01)Economic analyses of development projects and policies often involve assigning an economic value to changes in the risk of loss of human life. A typical term used in the economic analyses is the value of statistical life, which reflects the aggregation of individuals' willingness to pay for fatal risk reduction and therefore the economic value to society to reduce the statistical incidence of premature death in the population by one. Studies on the value of a statistical life have been extensively conducted in the developed world; however, few such studies can be found for developing countries. This paper presents a study that estimates individuals' willingness to pay for cancer risk prevention in three provinces of China. The results imply that the mean value of willingness to pay for a cancer vaccine that is effective for one year is 759 yuan, with a much lower median value of 171 yuan. The estimated income elasticity of willingness to pay is 0.42. Using data on the incidence of cancer illness and death in the population, these willingness to pay figures imply that the marginal value of reducing the anticipated incidence of cancer mortality by one in the population is 73,000 yuan and an average value of 795,000 yuan, which are about six and 60 times average household annual income, respectively. The big difference between the marginal value and the average value of fatal risk reduction corresponds to a very low estimated elasticity of willingness to pay with respect to fatal risk reduction. This finding challenges the validity of previous studies of the value of a statistical life, which are mostly based on average willingness-to-pay values of mortality risk reduction.Publication World Bank Support for Social Safety Nets 2007-2013 : A Review of Financing, Knowledge Services, and Results(World Bank Group, Washington, DC, 2014-06)This review examines World Bank support to social safety nets between FY2007-13, including both financing and knowledge services. During this time period World Bank financing for safety nets totaled just over United States (U.S.) 12 billion dollars, 273 financing activities in 93 countries, the World Bank spent approximately U.S. 118 million dollars on 281 safety net studies and supported approximately 129 credible safety net impact evaluations covering in 24 countries. Among the 93 countries represented in the portfolio, 42 received little or no safety net support from the World Bank prior to FY2007. The growth in Bank support is especially notable during the period of the food, fuel, and financial crises. The analysis delves into these trends by region, type of intervention, and instruments involved. Finally, it delineates implications and outlook for the future based on lessons learned, results measured, and evaluative evidence.Publication Beyond Downscaling : A Bottom-Up Approach to Climate Adaptation for Water Resources Management(World Bank Group, Washington, DC, 2014-09-11)This report focuses on how we achieve water sustainability over long timescales - decades, even centuries from now. These timescales are important and relevant to our decisions about planning, infrastructure, and institutions today. Many of the methods we use to manage water, directly or indirectly, commit us to future decision pathways and restrict us from making other, alternative decisions. Across the first four chapters, this report describes the challenges of including climate change in water management decision-making and provides an overview of current practices in the adaptation field. After considering the pros and cons of these practices, the book concludes with a framework for an adaptation approach supported by Alliance for Global Water Adaptation (AGWA).
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