Value of a statistical life in road safety: A benefit-transfer function with risk-analysis guidance based on developing country data

Abstract

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.

Social costs of road crashes: An international analysis

“…However, as the number of countries in this overview is limited, a study on a larger scale is recommended to obtain figures that are more representative on the global level. Secondly, value transfer functions relating the VOSL to GDP per capita have been developed (Milligan et al, 2014;McMahon and Dahdah, 2008;Miller, 2000). These functions may be used as a rule of thumb to estimate the costs per fatality and total costs of fatalities if a country-specific VOSL is not available.…”

Country-Level Cost-Effectiveness Thresholds: Initial Estimates and the Need for Further Research

“…The GDP per capita estimates for 2013 were obtained from the World Bank data set. In line with the literature on the VSL, elasticities were applied to countries’ GDP per capita adjusted for PPP [21] (see, e.g., Milligan et al [22]). CETs are reported in 2013 PPP-adjusted US dollar values.…”

“…The relationship between the VSL and per capita income at the level of jurisdictions is investigated in a small but emerging literature [19], [22], [25]. The literature has evolved out of a longer standing body of work that has examined the relationship between income and health valuation at the level of individuals (i.e., “within” countries) [18], [25].…”

“…The recent consensus then is that the income elasticity of VSL to transfer estimates across countries should be more than 1 [19], [22]. A range of elasticities were selected for this analysis (1.0, 1.5, and 2.0) to reflect uncertainty in the literature.…”

“…A range of elasticities were selected for this analysis (1.0, 1.5, and 2.0) to reflect uncertainty in the literature. On the basis of the study by Milligan et al [22], a function of an elasticity of 0.7 was also applied for high-income countries (those with GDP per capita >$10,725, 2005 price year, PPP), and of 2.5 for countries with per capita incomes less than this threshold. In line with the recommendations by Milligan et al, the elasticities from this study were applied to 2013 PPP-adjusted GDP, deflated to reflect 2005 international dollars.…”