IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i2p893-d1024359.html
   My bibliography  Save this article

How Efficient China’s Tiered Pricing Is for Household Electricity: Evidence from Survey Data

Author

Listed:
  • Zihan Zhang

    (Research Institute for Eco-Civilization, Chinese Academy of Social Sciences, Beijing 100101, China)

  • Enping Li

    (Research Institute for Eco-Civilization, Chinese Academy of Social Sciences, Beijing 100101, China)

  • Guowei Zhang

    (School of Management, China Institute for Studies in Energy Policy, Xiamen University, Xiamen 361005, China)

Abstract

Due to the wide coverage of first-tier electricity consumption and the small price difference between different tiers, the current tiered pricing for household electricity (TPHE) cannot give full play to the advantages of the increasing block electricity tariffs (IBTs). Based on the microscopic survey data provided by the Chinese General Social Survey (CGSS) in 2015, this paper innovatively uses the predicted average electricity price as the instrumental variable of electricity price to explore the influencing factors of household electricity consumption in order to solve the possible endogenous problems. Simultaneously, the samples are further grouped by income and electricity consumption, and the electricity consumption characteristics of different groups are discussed separately. The results show that, for low-income groups, the price elasticity of electricity consumption is relatively low because the electricity consumption of low-income households is concentrated on meeting the energy demand necessary for basic life, while the price elasticity of high-income groups is relatively high because the electricity consumption of the high-income households is mostly the energy demand generated by improving the quality of life.

Suggested Citation

  • Zihan Zhang & Enping Li & Guowei Zhang, 2023. "How Efficient China’s Tiered Pricing Is for Household Electricity: Evidence from Survey Data," Sustainability, MDPI, vol. 15(2), pages 1-17, January.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:2:p:893-:d:1024359
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/2/893/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/15/2/893/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lin, Boqiang & Du, Zhili, 2017. "Can urban rail transit curb automobile energy consumption?," Energy Policy, Elsevier, vol. 105(C), pages 120-127.
    2. Hung, Ming-Feng & Huang, Tai-Hsin, 2015. "Dynamic demand for residential electricity in Taiwan under seasonality and increasing-block pricing," Energy Economics, Elsevier, vol. 48(C), pages 168-177.
    3. Massimo Filippini & Lester C. Hunt, 2011. "Energy Demand and Energy Efficiency in the OECD Countries: A Stochastic Demand Frontier Approach," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 59-80.
    4. Zheng, Xinye & Wei, Chu & Qin, Ping & Guo, Jin & Yu, Yihua & Song, Feng & Chen, Zhanming, 2014. "Characteristics of residential energy consumption in China: Findings from a household survey," Energy Policy, Elsevier, vol. 75(C), pages 126-135.
    5. Hausman, Jerry & McFadden, Daniel, 1984. "Specification Tests for the Multinomial Logit Model," Econometrica, Econometric Society, vol. 52(5), pages 1219-1240, September.
    6. Yu, Biying & Yang, Xiaojuan & Zhao, Qingyu & Tan, Jinxiao, 2020. "Causal Effect of Time-Use Behavior on Residential Energy Consumption in China," Ecological Economics, Elsevier, vol. 175(C).
    7. Sean Cleary, 1999. "The Relationship between Firm Investment and Financial Status," Journal of Finance, American Finance Association, vol. 54(2), pages 673-692, April.
    8. Belaïd, Fateh & Joumni, Haitham, 2020. "Behavioral attitudes towards energy saving: Empirical evidence from France," Energy Policy, Elsevier, vol. 140(C).
    9. He, Xiaoping & Reiner, David, 2016. "Electricity demand and basic needs: Empirical evidence from China's households," Energy Policy, Elsevier, vol. 90(C), pages 212-221.
    10. Xie, Lunyu & Yan, Haosheng & Zhang, Shuhan & Wei, Chu, 2020. "Does urbanization increase residential energy use? Evidence from the Chinese residential energy consumption survey 2012," China Economic Review, Elsevier, vol. 59(C).
    11. Athukorala, Wasantha & Wilson, Clevo & Managi, Shunsuke & Karunarathna, Muditha, 2019. "Household demand for electricity: The role of market distortions and prices in competition policy," Energy Policy, Elsevier, vol. 134(C).
    12. Hargreaves, Tom & Nye, Michael & Burgess, Jacquelin, 2013. "Keeping energy visible? Exploring how householders interact with feedback from smart energy monitors in the longer term," Energy Policy, Elsevier, vol. 52(C), pages 126-134.
    13. Koichiro Ito, 2014. "Do Consumers Respond to Marginal or Average Price? Evidence from Nonlinear Electricity Pricing," American Economic Review, American Economic Association, vol. 104(2), pages 537-563, February.
    14. 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.
    15. Hu, Wenhao & Ho, Mun S. & Cao, Jing, 2019. "Energy consumption of urban households in China," China Economic Review, Elsevier, vol. 58(C).
    16. Druckman, A. & Jackson, T., 2008. "Household energy consumption in the UK: A highly geographically and socio-economically disaggregated model," Energy Policy, Elsevier, vol. 36(8), pages 3167-3182, August.
    17. Jeffrey M. Wooldridge, 2002. "Inverse probability weighted M-estimators for sample selection, attrition, and stratification," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 1(2), pages 117-139, August.
    18. Shen, Bo & Ghatikar, Girish & Lei, Zeng & Li, Jinkai & Wikler, Greg & Martin, Phil, 2014. "The role of regulatory reforms, market changes, and technology development to make demand response a viable resource in meeting energy challenges," Applied Energy, Elsevier, vol. 130(C), pages 814-823.
    19. Wang, Xiaolei & Wei, Chunxin & Wang, Yanhua, 2022. "Does the current tiered electricity pricing structure still restrain electricity consumption in China's residential sector?," Energy Policy, Elsevier, vol. 165(C).
    20. Pothitou, Mary & Hanna, Richard F. & Chalvatzis, Konstantinos J., 2016. "Environmental knowledge, pro-environmental behaviour and energy savings in households: An empirical study," Applied Energy, Elsevier, vol. 184(C), pages 1217-1229.
    21. Boiteux, M., 1971. "On the management of public monopolies subject to budgetary constraints," Journal of Economic Theory, Elsevier, vol. 3(3), pages 219-240, September.
    22. Fang, Yingkai & Asche, Frank & Novan, Kevin, 2018. "The costs of charging Plug-in Electric Vehicles (PEVs): Within day variation in emissions and electricity prices," Energy Economics, Elsevier, vol. 69(C), pages 196-203.
    23. Flaig, Gebhard, 1990. "Household production and the short- and long-run demand for electricity," Energy Economics, Elsevier, vol. 12(2), pages 116-121, April.
    24. Belaïd, Fateh & Youssef, Adel Ben & Lazaric, Nathalie, 2020. "Scrutinizing the direct rebound effect for French households using quantile regression and data from an original survey," Ecological Economics, Elsevier, vol. 176(C).
    25. Sun, Chuanwang, 2015. "An empirical case study about the reform of tiered pricing for household electricity in China," Applied Energy, Elsevier, vol. 160(C), pages 383-389.
    26. Dubin, Jeffrey A & McFadden, Daniel L, 1984. "An Econometric Analysis of Residential Electric Appliance Holdings and Consumption," Econometrica, Econometric Society, vol. 52(2), pages 345-362, March.
    27. Labandeira, Xavier & Labeaga, José M. & López-Otero, Xiral, 2012. "Estimation of elasticity price of electricity with incomplete information," Energy Economics, Elsevier, vol. 34(3), pages 627-633.
    28. Liddle, Brantley & Smyth, Russell & Zhang, Xibin, 2020. "Time-varying income and price elasticities for energy demand: Evidence from a middle-income panel," Energy Economics, Elsevier, vol. 86(C).
    29. Muratori, Matteo & Kontou, Eleftheria & Eichman, Joshua, 2019. "Electricity rates for electric vehicle direct current fast charging in the United States," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
    30. Faruqui, Ahmad & Sergici, Sanem & Sharif, Ahmed, 2010. "The impact of informational feedback on energy consumption—A survey of the experimental evidence," Energy, Elsevier, vol. 35(4), pages 1598-1608.
    31. Auffhammer, Maximilian & Mansur, Erin T., 2014. "Measuring climatic impacts on energy consumption: A review of the empirical literature," Energy Economics, Elsevier, vol. 46(C), pages 522-530.
    32. Du, Limin & Guo, Jin & Wei, Chu, 2017. "Impact of information feedback on residential electricity demand in China," Resources, Conservation & Recycling, Elsevier, vol. 125(C), pages 324-334.
    33. Belaïd, Fateh & Roubaud, David & Galariotis, Emilios, 2019. "Features of residential energy consumption: Evidence from France using an innovative multilevel modelling approach," Energy Policy, Elsevier, vol. 125(C), pages 277-285.
    34. Guo, Hongye & Davidson, Michael R. & Chen, Qixin & Zhang, Da & Jiang, Nan & Xia, Qing & Kang, Chongqing & Zhang, Xiliang, 2020. "Power market reform in China: Motivations, progress, and recommendations," Energy Policy, Elsevier, vol. 145(C).
    35. Schulte, Isabella & Heindl, Peter, 2017. "Price and income elasticities of residential energy demand in Germany," Energy Policy, Elsevier, vol. 102(C), pages 512-528.
    36. Du, Gang & Lin, Wei & Sun, Chuanwang & Zhang, Dingzhong, 2015. "Residential electricity consumption after the reform of tiered pricing for household electricity in China," Applied Energy, Elsevier, vol. 157(C), pages 276-283.
    37. Pu, Lei & Wang, Xiuhui & Tan, Zhongfu & Wang, Huaqing & Yang, JiaCheng & Wu, Jing, 2020. "Is China's electricity price cross-subsidy policy reasonable? Comparative analysis of eastern, central, and western regions," Energy Policy, Elsevier, vol. 138(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Cosmina-Simona Toader & Ciprian Ioan Rujescu & Andrea Feher & Cosmin Salasan & Lavinia Denisia Cuc & Karoly Bodnar, 2023. "Generation Differences in the Behaviour of Household Consumers in Romania Related to Voluntary Measures to Reduce Electric Energy Consumption," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 25(64), pages 710-710, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Khanna, Nina Zheng & Guo, Jin & Zheng, Xinye, 2016. "Effects of demand side management on Chinese household electricity consumption: Empirical findings from Chinese household survey," Energy Policy, Elsevier, vol. 95(C), pages 113-125.
    2. Wang, Yao & Lin, Boqiang, 2021. "Performance of alternative electricity prices on residential welfare in China," Energy Policy, Elsevier, vol. 153(C).
    3. Liu, Chang & Lin, Boqiang, 2020. "Is increasing-block electricity pricing effectively carried out in China? A case study in Shanghai and Shenzhen," Energy Policy, Elsevier, vol. 138(C).
    4. Lin, Boqiang & Wang, Yao, 2020. "Analyzing the elasticity and subsidy to reform the residential electricity tariffs in China," International Review of Economics & Finance, Elsevier, vol. 67(C), pages 189-206.
    5. Fateh Belaïd & Christophe Rault & Camille Massié, 2022. "A life-cycle theory analysis of French household electricity demand," Journal of Evolutionary Economics, Springer, vol. 32(2), pages 501-530, April.
    6. Lin, Boqiang & Zhu, Penghu, 2021. "Has increasing block pricing policy been perceived in China? Evidence from residential electricity use," Energy Economics, Elsevier, vol. 94(C).
    7. Yang, Changhui & Meng, Chen & Zhou, Kaile, 2018. "Residential electricity pricing in China: The context of price-based demand response," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2870-2878.
    8. Li, Chuan-Zhong & Wei, Chu & Yu, Yang, 2020. "Income threshold, household appliance ownership and residential energy consumption in urban China," China Economic Review, Elsevier, vol. 60(C).
    9. Kuang, Yunming & Lin, Boqiang, 2021. "Performance of tiered pricing policy for residential natural gas in China: Does the income effect matter?," Applied Energy, Elsevier, vol. 304(C).
    10. Li, Lanlan & Luo, Xuan & Zhou, Kaile & Xu, Tingting, 2018. "Evaluation of increasing block pricing for households' natural gas: A case study of Beijing, China," Energy, Elsevier, vol. 157(C), pages 162-172.
    11. Lin, Boqiang & Chen, Xing, 2018. "Is the implementation of the Increasing Block Electricity Prices policy really effective?--- Evidence based on the analysis of synthetic control method," Energy, Elsevier, vol. 163(C), pages 734-750.
    12. Hung, Ming-Feng & Chie, Bin-Tzong, 2017. "The long-run performance of increasing-block pricing in Taiwan's residential electricity sector," Energy Policy, Elsevier, vol. 109(C), pages 782-793.
    13. Li, Yao & Fan, Jin & Zhao, Dingtao & Wu, Yanrui & Li, Jun, 2016. "Tiered gasoline pricing: A personal carbon trading perspective," Energy Policy, Elsevier, vol. 89(C), pages 194-201.
    14. Fateh Belaïd & Christophe Rault & Camille Massié, 2021. "A Life-Cycle Analysis of French Household Electricity Demand," CESifo Working Paper Series 8814, CESifo.
    15. Wang, Chen & Zhou, Kaile & Yang, Shanlin, 2017. "A review of residential tiered electricity pricing in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 533-543.
    16. Wang, Yuanping & Hou, Lingchun & Hu, Lang & Cai, Weiguang & Wang, Lin & Dai, Cuilian & Chen, Juntao, 2023. "How family structure type affects household energy consumption: A heterogeneous study based on Chinese household evidence," Energy, Elsevier, vol. 284(C).
    17. Du, Limin & Guo, Jin & Wei, Chu, 2017. "Impact of information feedback on residential electricity demand in China," Resources, Conservation & Recycling, Elsevier, vol. 125(C), pages 324-334.
    18. Hu, Wenhao & Ho, Mun S. & Cao, Jing, 2019. "Energy consumption of urban households in China," China Economic Review, Elsevier, vol. 58(C).
    19. Wang, Xiaolei & Wei, Chunxin & Wang, Yanhua, 2022. "Does the current tiered electricity pricing structure still restrain electricity consumption in China's residential sector?," Energy Policy, Elsevier, vol. 165(C).
    20. Li, Jiapeng & Zuo, Xuguang & Sun, Chuanwang, 2023. "The effect of urban renewal on residential energy consumption expenditure--the example of shantytown renovation," Energy Policy, Elsevier, vol. 183(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:2:p:893-:d:1024359. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.