Mileage-Based User Fee Winners and Losers - RAND Corporation

calculated by taking the partial derivative of the demand function in Equation 3.2 with respect to
price as shown in Equation 3.3:
lnM
ln
p
i
i
= β 1 + β 7 lnY i + β 8 lnMPG i + (β V2 + β V3 ) (3.3)
Each household has only one of the parameters β V2 & β V3 factor into their price elasticity depending
on the number of household vehicles (with no parameter for a household with only one vehicle).
The mean price elasticity is -0.43, a value that is close to the β 1 coefficient in the linear model
fitted with pooled data, as is expected. The most elastic value is -0.98, which is still inelastic, and the
maximum value is 0.02. A positive value for price elasticity is somewhat unexpected because it
means that these households increase VMT as the price of driving increases. 137 observations,
representing less than 0.1 percent of the population, have a positive price elasticity. The distribution
of price elasticity in the population, as illustrated in Figure 3.1, is bi-modal. This is not directly
attributable to income but, as illustrated in Figure 3.2, to vehicle ownership. The predicted price
elasticities for households with more than 2 vehicles lie predominately between zero and the average,
while the predicted price elasticities for households with one to two vehicles lie predominately
between the average and -1. Household vehicle ownership is associated with many correlated factors
including income, unobserved derived demand for travel, and characteristics of the built
environment (such as the density of development, availability of parking, urban traffic congestion,
and access to alternative modes of travel).
It is difficult to interpret the results, however, and the reader should not mistake correlation,
in this case, with causality. Household demand for VMT is the product of land use, income
(including the price of travel relative to the prices of all other consumer goods), and household
preferences and consumption, which are all factors that are imperfectly or indirectly measured by the
NHTS instrument.
Predictors of Household Demand for VMT
This section describes each of the predictors of household demand for VMT. The reasoning
for including each variable is discussed as well as the expected and actual effect on the demand for
travel. The expected and actual effect on the estimated price elasticity of variables that are interacted
with the natural log of price is also discussed. The technical details regarding how each variable was
constructed is assumed to be of interest to a limited audience and these are provided in the
Technical Appendix.
Price per Mile
The price per mile of travel is a composite variable based on the VMT-weighted average fuel
price of household vehicles divided by the VMT-weighted average household MPG. The price is
disaggregated into the cost of fuel and state and federal taxes in order to facilitate the distributional
analysis of alternative tax policies (in which the federal and state fuel excise tax rates are either
increased or, depending on the alternative being assessed, replaced by or supplemented with MBUFs
of various rates and designs). In fitting the model, however, the current retail prices, as reported in
the NHTS data are used to calculate this variable.
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