No 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.

No abstract

In this research, an integrated gravity-based model was built, and a scenario analysis was conducted to project the demand levels for routes related to the highway projects suggested in TINA-Turkey. The gravity-based model was used to perform a disaggregated analysis to estimate the demand levels that will occur on the routes which are planned to be improved in specific regions of Turkey from now until 2020. During the scenario development phase for these gravity-based models, the growth rate of Turkey's GDP, as estimated by the World Bank from now until 2017, was used as the baseline scenario. Besides, it is assumed that the gross value added (GVA) of the origin and destination regions of the selected routes will show a pattern similar to GDP growth rates. Based on the estimated GDP values, and the projected GVA growth rates, the demand for each selected route was projected and found that the demand level for some of these road projects is expected to be very low, and hence additional measures would be needed to make these investments worthwhile.

No abstract