Equity Measures and Their Performance in Transportation

Abstract

This paper aims at equity implications of transportation policies by using a range of equity measures in two case studies. Different measures of inequality embrace different normative judgments. Early studies have warned about placing too much trust in a single measure. One approach is to address equity considerations by assuming an explicit form of social welfare function and the choice of a desired inequality aversion parameter. A second approach is to apply an inequality measure to a given pair of distributions of a variable (e.g., income and accessibility) that changes as the result of a policy. The latter approach is adopted in this paper. A partial equilibrium model of transportation is used for the calculation of the changes in income, accessibility, and the net benefit for different social groups. This paper demonstrates the challenges that arise in addressing equity with a partial equilibrium model of transportation. An overview of some equity measures and their properties is provided first. The performances of these equity measures are evaluated for alternative road pricing schemes for Oslo, Norway. The paper illustrates that relating the equity objective to a predefined value of any of these measures is not desirable. It is difficult to make a judgment about the equity implication of a policy on the basis of a single measure and without a thorough examination of several measures. The paper also shows that the sizes of the equity measures are quite sensitive to the level of spatial disaggregation.

Income and access inequalities of a cordon pricing

“…However, since different measures of justice provide different classifications of income distributions, Ramjerdi (2006) shows several indicators of inequalities can provide different results. She recommends using several inequality indicators and not studying the justice associated with a specific value of these indicators.…”

“…The inequality indicators 1.1.1. The Gini index Even if the assessment of the impact of urban tolls on inequalities is rarely dealt with in the literature, the Gini index is commonly used (Karlstr€ om & Franklin, 2007;Ramjerdi, 2006;Sumalee et al, 2005). Sumalee et al (2005) show that the double boundary type zone is the worst in terms of Gini inequalities.…”

“…However, the sub estimation is important when the number of class is weak (Deltas, 2003;Lerman & Yitzhaki, 1989;Wodon & Yitzhaki, 2003). Ramjerdi (2006) underlines the Gini sensitivity to the selected level of spatial division and to the weak number of income classes. Furthermore, the Gini coefficient can be biased by very small sample and without any decomposition, income are the only parameter taken into account (Dagum, 1980).…”

“…With the exception of Ramjerdi (2006) and Tillema, Verhoef, Wee, and Amelsfort (2011), scarce are papers which measure the consequences of urban road pricing on accessibility. Despite a general reduction in the level of accessibility resulting from the toll, the results are affected by the size of the zones.…”

“…In spite of its being one of the bestknown indicators, 2 the Gini coefficient of inequality is little used in the literature on urban road pricing (Condeço-Melhorado, Gutierrez, & Garcia-Palomares, 2011;Karlstr€ om & Franklin, 2007;Ramjerdi, 2006;Sumalee, May, & Shepherd, 2005). The variation of gravity-based potential is used classically to measure accessibility (Geurs & van Wee, 2004;Hansen, 1959;Morris, Dumble, & Wigan, 1978).…”