A Model to Evaluate Vehicle Emission Incentive Policies in Japan

NBER Working Paper No. 20333

Issued in July 2014

NBER Program(s):Environment and Energy Economics, Public Economics



Using three years of data from the 47 prefectures of Japan, we estimate behavior of households who simultaneously make discrete decisions about vehicle ownership and continuous decisions about driving distance. We use the estimated parameters to calculate elasticities and to simulate the effects of alternative pollution control policies such as taxes on gasoline, on distance, or on particular cars. Given choices about cars and distance, we also calculate emissions. Since we model simultaneous choices, both the chosen distance and the chosen car can be affected either by a tax on distance or by a tax on car characteristics. We find expected signs for coefficients on price and income. Car choices are relatively inelastic, however, either to taxes on cars or to taxes on gas or distance. Thus emissions are more affected by taxes on gasoline than by taxes on particular vehicles.

Yet taxes on cars have lower costs on consumers and thus lower marginal cost of abatement. Given that the existing gas tax already achieves some abatement, mostly through driving reduction, this analysis suggests that further abatement from the use of distance-reducing taxes is more costly than achieving some marginal abatement from induced changes in car choices. The option with the lowest cost is to tax each car at a rate proportional to its emission rate.

Acknowledgments

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Document Object Identifier (DOI): 10.3386/w20333

Published: Don Fullerton & Li Gan & Miwa Hattori, 2015. "A model to evaluate vehicle emission incentive policies in Japan," Environmental Economics and Policy Studies- The Official Journal of the Society for Environmental Economics and Policy Studies / The Official Journal of the East Asian Association of Environmental and, Society for Environmental Economics and Policy Studies - SEEPS, vol. 17(1), pages 79-108, January. citation courtesy of

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