IDEAS home Printed from https://ideas.repec.org/a/aiy/journl/v2y2016i2p259-269.html
   My bibliography  Save this article

Econometric Modeling of Electricity Consumption by Households as a Tool for the Calculating of the Social Consumption Norm

Author

Listed:
  • Zaytseva, Yu. V.

Abstract

Since July 2016, it is planned to introduce electricity tariffs with the social consumption norm in all regions of Russia. The methodology for calculation the electricity social consumption norm for different types of households was legally adopted by resolutions of the Government of the Russian Federation. According to these regulations, at least 70 % of the actual volume of electric power supply to the population should fall within the social norm. This article analyzes the validity of the methodology for calculating the social norm. The research is based on the data about the consumption of electricity by Russian households. The purpose of this study is to construct an econometric model of electricity consumption and calculate model- based social norms for different types of households. Explanatory variables in the model are the factors that describe the household size and accommodation conditions: the number of residents, the presence or absence of electric cooker, the type of settlement (urban or rural), the climate of the region where the household lives. The simulation results show that 70 % of electricity will be consumed within the social norms, if the size of the norm for households consisting of one person, will be from 110 to 210 kW·h, depending on the accommodation conditions. The author also evaluates the necessary social norm increments for the second, third and subsequent members of different household types. The developed model takes into account the regional characteristics of energy consumption and can be useful for calculating the social norm of electricity consumption in the regions of Russian Federation.

Suggested Citation

  • Zaytseva, Yu. V., 2016. "Econometric Modeling of Electricity Consumption by Households as a Tool for the Calculating of the Social Consumption Norm," R-Economy, Ural Federal University, Graduate School of Economics and Management, vol. 2(2), pages 259-269.
  • Handle: RePEc:aiy:journl:v:2:y:2016:i:2:p:259-269
    DOI: 10.15826/recon.2016.2.2.023
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10995/47024
    Download Restriction: no

    File URL: https://libkey.io/10.15826/recon.2016.2.2.023?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Allcott, Hunt, 2011. "Social norms and energy conservation," Journal of Public Economics, Elsevier, vol. 95(9), pages 1082-1095.
    2. Rodney Maddock & Elkin Castano, 1991. "The Welfare Impact of Rising Block Pricing: Electricity in Colombia," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 65-78.
    3. Allcott, Hunt, 2011. "Social norms and energy conservation," Journal of Public Economics, Elsevier, vol. 95(9-10), pages 1082-1095, October.
    4. 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.
    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. Tumanyants, Karen (Туманянц, Карэн), 2020. "Income Residential Demand Elasticities for Electricity: Do We Need to Differentiate the Tariff? [Эластичность Спроса Населения На Электроэнергию По Доходам: Нужно Ли Диверсифицировать Тариф?]," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 4, pages 110-137, 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. Yulia Zaitseva, 2016. "Econometric Modeling of Electricity Consumption by Households as a Tool for the Calculation of Social Norms of Consumption," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, vol. 1(2), pages 405-416.
    2. Todd D. Gerarden & Richard G. Newell & Robert N. Stavins, 2017. "Assessing the Energy-Efficiency Gap," Journal of Economic Literature, American Economic Association, vol. 55(4), pages 1486-1525, December.
    3. Wang, Xiangrui & Lee, Jukwan & Yan, Jia & Thompson, Gary D., 2018. "Testing the behavior of rationally inattentive consumers in a residential water market," Journal of Environmental Economics and Management, Elsevier, vol. 92(C), pages 344-359.
    4. Belaïd, Fateh, 2017. "Untangling the complexity of the direct and indirect determinants of the residential energy consumption in France: Quantitative analysis using a structural equation modeling approach," Energy Policy, Elsevier, vol. 110(C), pages 246-256.
    5. Belaïd, Fateh & Garcia, Thomas, 2016. "Understanding the spectrum of residential energy-saving behaviours: French evidence using disaggregated data," Energy Economics, Elsevier, vol. 57(C), pages 204-214.
    6. Considine, Timothy J. & Sapci, Onur, 2016. "The effectiveness of home energy audits: A case study of Jackson, Wyoming," Resource and Energy Economics, Elsevier, vol. 44(C), pages 52-70.
    7. Schleich, Joachim & Gassmann, Xavier & Faure, Corinne & Meissner, Thomas, 2016. "Making the implicit explicit: A look inside the implicit discount rate," Energy Policy, Elsevier, vol. 97(C), pages 321-331.
    8. Mizobuchi, Kenichi & Takeuchi, Kenji, 2013. "The influences of financial and non-financial factors on energy-saving behaviour: A field experiment in Japan," Energy Policy, Elsevier, vol. 63(C), pages 775-787.
    9. Gans, Will & Alberini, Anna & Longo, Alberto, 2013. "Smart meter devices and the effect of feedback on residential electricity consumption: Evidence from a natural experiment in Northern Ireland," Energy Economics, Elsevier, vol. 36(C), pages 729-743.
    10. Vesterberg, Mattias, 2017. "Heterogeneity in price responsiveness of electricity: Contract choice and the role of media coverage," Umeå Economic Studies 940, Umeå University, Department of Economics.
    11. Suter, Jordan F. & Shammin, Md Rumi, 2013. "Returns to residential energy efficiency and conservation measures: A field experiment," Energy Policy, Elsevier, vol. 59(C), pages 551-561.
    12. Panzone, Luca A., 2013. "Saving money vs investing money: Do energy ratings influence consumer demand for energy efficient goods?," Energy Economics, Elsevier, vol. 38(C), pages 51-63.
    13. Lucas W. Davis & Alan Fuchs & Paul J. Gertler, 2012. "Cash for Coolers," NBER Working Papers 18044, National Bureau of Economic Research, Inc.
    14. Rockstuhl, Sebastian & Wenninger, Simon & Wiethe, Christian & Häckel, Björn, 2021. "Understanding the risk perception of energy efficiency investments: Investment perspective vs. energy bill perspective," Energy Policy, Elsevier, vol. 159(C).
    15. Lucas W. Davis & Gilbert E. Metcalf, 2016. "Does Better Information Lead to Better Choices? Evidence from Energy-Efficiency Labels," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 3(3), pages 589-625.
    16. Schleich, Joachim & Gassmann, Xavier & Meissner, Thomas & Faure, Corinne, 2023. "Making the factors underlying the implicit discount rate tangible," Energy Policy, Elsevier, vol. 177(C).
    17. Lucas W Davis, 2017. "Evidence of a decline in electricity use by U.S. households," Economics Bulletin, AccessEcon, vol. 37(2), pages 1098-1105.
    18. repec:hal:spmain:info:hdl:2441/60sgjahunh9dkqd8c1s048perp is not listed on IDEAS
    19. Hobman, Elizabeth V. & Frederiks, Elisha R. & Stenner, Karen & Meikle, Sarah, 2016. "Uptake and usage of cost-reflective electricity pricing: Insights from psychology and behavioural economics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 455-467.
    20. Peter John Robinson & W. J. Wouter Botzen, 2022. "Setting descriptive norm nudges to promote demand for insurance against increasing climate change risk," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 47(1), pages 27-49, January.
    21. Lillemo, Shuling Chen, 2014. "Measuring the effect of procrastination and environmental awareness on households' energy-saving behaviours: An empirical approach," Energy Policy, Elsevier, vol. 66(C), pages 249-256.

    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:aiy:journl:v:2:y:2016:i:2:p:259-269. 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: Irina Turgel (email available below). General contact details of provider: https://edirc.repec.org/data/seurfru.html .

    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.