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Analyzing the distributional effects of fuel taxation in China

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Abstract

As an effective policy instrument to reduce energy consumption and CO2 emissions, the effects of fuel taxation on income distribution have been the critical factor that determines whether a fuel tax could be acceptable in China. This paper estimates the distributional effects of a fuel tax on households in various income groups by using the input-output model. Results indicate that the total distributional effects of fuel taxes are moderately progressive; that is, high-income households would bear more tax burden compared to low-income households. In addition, the indirect effects are larger than the direct effects. Moreover, the Kakwani and Suits indices show that fuel excise taxes are progressive, implying that a fuel tax could improve the unfair income distribution. In order to reduce the negative impact of fuel taxes on low-income households, it is necessary for the government to design a reasonable redistribution mechanism of tax revenue or adopt compensatory measures such as the transfer payments targeted on low-income groups.

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Acknowledgements

We would like to express our sincere gratitude to the anonymous referees for their insightful and constructive comments. The paper is supported by the National Natural Science Foundation of China (71503155, 71603084), Social Sciences Research supported by Ministry of Education of China (16YJC790078), Shanghai Social Science Foundation (2015110478), Social Sciences Research supported by Shanghai Planning Office of Philosophy and Social Science (2016EJB003), and Social Sciences Research and Think Tank Project supported by East China Normal University (2016zk017).

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  1. Institute of Finance and Economics Research, School of Urban and Regional Science, Shanghai University of Finance and Economics, Shanghai, 200433, China

    Zhujun Jiang

  2. Department of Economics, School of Economics, Faculty of Economics and Management, East China Normal University, Shanghai, 200062, China

    **aoling Ouyang

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Appendix

Appendix

Suits index

The Suits index proposed by Suits (1977) is a measurement of the level of tax progressivity (fairness). The index of progressivity is developed from the Lorenz curve and Gini coefficient, and accumulated percent of income is plotted vertically against accumulated percent of population. The Suits index varies from −1 to 1. In the case of regressivity, L > K and −1 ≤ S < 0, while proportional tax implies L = K, so S = 0. A progressive tax yields L < K and 0 < S ≤ 1.

Suggested in Suits (1977),

$$ S=1-\frac{1}{10,000}\sum_{i=1}^n\left[ T\left({y}_i\right)+ T\left({y}_{i-1}\right)\right]\left({y}_i-{y}_{i-1}\right) $$
(A1)

where y i denotes the accumulated percent of the income, measured on the horizontal axis, which ranges from 0 to 100; T(y i ) is the corresponding accumulated percent of the tax burden from a given tax; and n stands for the number of household income groups. Figure 8 depicts an example of a concentration curve that is similar to a Lorenz curve.

Fig. 8
figure 8

Concentration curve with the areas used to calculate the Suits index

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Kakwani index

A closely related alternative to the Suits coefficient is the Kakwani index (Kakwani 1977). Figure 9 depicts the concentration and Lorenz curves. The Kakwani index is given by twice the difference in the areas below the Lorenz curve and the concentration curve and is computed as follows:

$$ K=2\underset{0}{\overset{1}{\int }}\left[{L}_x(p)-{L}_T(p)\right] dp $$
(A2)

where L x (p) is the Lorenz curve; L T (p) is the concentration curve of taxes, in which the accumulated percent of tax burden is plotted vertically against the accumulated percent of population on the horizontal axis; and p is the accumulated percent of population on the horizontal axis. The Kakwani index also varies from −1 to 1. When the Lorenz curve lies above the concentration curve, the index K is positive for progressive taxes. In addition, when the Lorenz curve is below the concentration curve, the index K is negative for the regressive taxes.

Fig. 9
figure 9

Concentration and Lorenz curves

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Jiang, Z., Ouyang, X. Analyzing the distributional effects of fuel taxation in China. Energy Efficiency 10, 1235–1251 (2017). https://doi.org/10.1007/s12053-017-9512-9

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