Footnote:
Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments September 15, 2007 erstellt
Description:
Several types of attribute-based vehicle feebates, including weight-based, footprint-based, and volume-based, are analyzed and compared using model-year 2005 sales data for the U.S. market. Due to the high correlation of weight with fuel consumption, a weight-based feebate would be most effective at minimizing distributional costs. For example, the following table illustrates distributional metrics of several multi-class feebates based on different attributes, but using the same class partitioning method:US MY 2005 feebate simulation: weight-based; footprint-based; volume-basedaggregate fees and rebates: $4.522B; $7.238B; $8.926BTruck-to-Car feebate revenue flow: $1.057B; $3.432B; $3.417B(This example uses 19 overlapping attribute classes.) A weight-based feebate could be constructed to neutralize (not invert) the extreme downweighting incentive of an attribute-neutral feebate, making it neutral with respect to weight-changing incentives (either downweighting or upweighting). A complementary policy could be employed to incentivize downweighting by substituting lightweight engineering materials for conventional materials, thus circumventing the tradeoff between weight and technology incentives