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Lin, B., Jiang, Z, 2012. Designation and influence of household increasing block electricity tariffs in China. Energy Policy 42, pp. 164–173: How biased is the measurement of household’s loss?

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  • Salies, Evens

Abstract

The three-tier inclining block tariff (‘‘IBT’’) issued by the Chinese government in 2010 is focusing attention of energy economists, among whom Lin and Jiang (2012. Designation and influence of household increasing block electricity tariffs in China. Energy Policy 42, 164–173) who assert that the issued tariff is unsuited to meet the social and environmental objectives it was designed for. These authors offer an alternative four-tiered IBT, the performance of which they show by evaluating its welfare and income distribution effects taking the current uniform tariff as reference. To measure the surplus loss to a representative household in a given block the authors use the trapezoid approach. But, because of the limited data on demand, they calculate the household’s response by using a constant point estimate of the own-price elasticity of electricity demand. In this note I show there is an incompatibility between these two modeling assumptions. Combining them is causing an upward bias in the surplus loss, which is of significance given the large price change associated with the IBT. I then offer a correction to this bias.

Suggested Citation

  • Salies, Evens, 2012. "Lin, B., Jiang, Z, 2012. Designation and influence of household increasing block electricity tariffs in China. Energy Policy 42, pp. 164–173: How biased is the measurement of household’s loss?," MPRA Paper 46811, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:46811
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    References listed on IDEAS

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    1. Arjan Ruijs, 2009. "Welfare and Distribution Effects of Water Pricing Policies," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 43(2), pages 161-182, June.
    2. Freund, Caroline & Wallich, Christine, 1997. "Public-Sector Price Reforms in Transition Economies: Who Gains? Who Loses? The Case of Household Energy Prices in Poland," Economic Development and Cultural Change, University of Chicago Press, vol. 46(1), pages 35-59, October.
    3. Espey, James A. & Espey, Molly, 2004. "Turning on the Lights: A Meta-Analysis of Residential Electricity Demand Elasticities," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 36(1), pages 1-17, April.
    4. Andres Vazquez, 1998. "An alternative definition of the arc elasticity of demand," Journal of Economic Studies, Emerald Group Publishing, vol. 25(6), pages 553-562, October.
    5. Wang, Zhaohua & Zhang, Bin & Zhang, Yixiang, 2012. "Determinants of public acceptance of tiered electricity price reform in China: Evidence from four urban cities," Applied Energy, Elsevier, vol. 91(1), pages 235-244.
    6. Lin, Boqiang & Jiang, Zhujun, 2012. "Designation and influence of household increasing block electricity tariffs in China," Energy Policy, Elsevier, vol. 42(C), pages 164-173.
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    More about this item

    Keywords

    Increasing block tariffs; Electricity demand; Welfare measurement;
    All these keywords.

    JEL classification:

    • D11 - Microeconomics - - Household Behavior - - - Consumer Economics: Theory
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy

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