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Evaluating Design of Increasing Block Tariffs for Residential Natural Gas in China: A Case Study of Henan Province

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  • Chang Liu

    (Xiamen University)

  • Boqiang Lin

    (Xiamen University)

Abstract

Solving the problem of residential cross-subsidies for natural gas is a key and difficult point of further phasing out the fossil fuel subsidies in China. The government implemented the increasing block tariffs for residential natural gas to settle this issue. However, the relevant researches are still very limited. In this paper, we apply the price-gap approach and welfare evaluation methods to analyze the subsidies and increasing block tariffs for residential natural gas in Henan province in 2013 and find that the subsidies mainly benefited the high-income group, as they accounted for only 20% of the total population but received 32.36% of the total subsidies. The low-income group accounted for 20% of the total population, but obtained only 11.95% of the total subsidies. Residential natural gas subsidies lack fairness and efficiency, which mainly resulted in the excessive gas volume in the first block in Henan province. In addition, we design some schemes of increasing block tariffs for residential natural gas and find that more blocks and larger gap of gas price among different blocks can optimize the subsidy redistribution and improve its fairness and efficiency. The local governments should design proper volume in the first block, enlarge gap of gas price when implementing the increasing block tariffs; they should also enhance the awareness on energy conservation among the high income group.

Suggested Citation

  • Chang Liu & Boqiang Lin, 2018. "Evaluating Design of Increasing Block Tariffs for Residential Natural Gas in China: A Case Study of Henan Province," Computational Economics, Springer;Society for Computational Economics, vol. 52(4), pages 1335-1351, December.
    • Handle: RePEc:kap:compec:v:52:y:2018:i:4:d:10.1007_s10614-017-9674-8
    DOI: 10.1007/s10614-017-9674-8
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    References listed on IDEAS

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    Cited by:

    1. Malin Song & Ron Fisher, 2018. "How to Apply Advanced Statistical Analysis to Computational Economics: Methods and Insights," Computational Economics, Springer;Society for Computational Economics, vol. 52(4), pages 1045-1052, December.
    2. An, Yunfei & Zhou, Dequn & Wang, Qunwei & Shi, Xunpeng & Taghizadeh-Hesary, Farhad, 2022. "Mitigating size bias for carbon pricing in small Asia-Pacific countries: Increasing block carbon tax," Energy Policy, Elsevier, vol. 161(C).

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