IDEAS home Printed from https://ideas.repec.org/a/ura/ecregj/v1y2016i2p405-416.html
   My bibliography  Save this article

Econometric Modeling of Electricity Consumption by Households as a Tool for the Calculation of Social Norms of Consumption

Author

Listed:
  • Yulia Zaitseva

    (Volgofrad State Univercity)

Abstract

Since July 2016, in all regions of Russia, it is planned to introduce the electricity tariffs with the social norm of consumption. The calculation method of the social norms of consumption for the different types of households is approved by the Government decree of the Russian Federation. The resolutions of the decree regulate the volume of electricity supply within a social norm not less than 70 % of the real volume of the supply of electric energy to the population. In this article, the analysis of the validity of the methods for calculating the social norm on the basis of the statistical analysis of the data on electricity consumption by Russian households is made. The purpose of this work is to develop an econometric model of electricity consumption by Russian households and to calculate reasonable social norms for different categories of households on the basis of this model. As the explanatory variables, the factors describing the size and living conditions of households were selected: the number of residents, the presence or absence of electric stove, the type of settlement (city or village), the climatic conditions of the region. The simulation results showed that according to the requirements of the social norm (at least 70 percent of the actual volume of electric energy delivery), the norms for households consisting of one person should be from 110 to 210 kWh depending on the living conditions. The necessary increment of social norms for the second, third and subsequent members of the households of different categories are also identified. The received values of social norms are not quite consistent with the values regulated by the legislatively approved method. For some types of households, the values are underestimated. The developed model considers the regional specific features of electricity consumption and can be useful for the calculation of the social norms of electricity consumption in the regions of the Russian Federation.

Suggested Citation

  • 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.
    • Handle: RePEc:ura:ecregj:v:1:y:2016:i:2:p:405-416
    as

    Download full text from publisher

    File URL: http://economyofregion.ru/Data/Issues/ER2016/June_2016/ERJune2016_405_416.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. Allcott, Hunt, 2011. "Social norms and energy conservation," Journal of Public Economics, Elsevier, vol. 95(9-10), pages 1082-1095, October.
    4. Allcott, Hunt, 2011. "Social norms and energy conservation," Journal of Public Economics, Elsevier, vol. 95(9), pages 1082-1095.
    Full references (including those not matched with items on IDEAS)

    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. 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.
    2. Lucas W Davis, 2017. "Evidence of a decline in electricity use by U.S. households," Economics Bulletin, AccessEcon, vol. 37(2), pages 1098-1105.
    3. 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.
    4. 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.
    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. 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.
    7. 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).
    8. Schleich, Joachim & Gassmann, Xavier & Meissner, Thomas & Faure, Corinne, 2023. "Making the factors underlying the implicit discount rate tangible," Energy Policy, Elsevier, vol. 177(C).
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. Lucas W. Davis & Alan Fuchs & Paul J. Gertler, 2012. "Cash for Coolers," NBER Working Papers 18044, National Bureau of Economic Research, Inc.
    16. 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.
    17. 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.
    18. 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.
    19. Carattini, Stefano & Gillingham, Kenneth & Meng, Xiangyu & Yoeli, Erez, 2024. "Peer-to-peer solar and social rewards: Evidence from a field experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 219(C), pages 340-370.
    20. Chatzigeorgiou, I.M. & Andreou, G.T., 2021. "A systematic review on feedback research for residential energy behavior change through mobile and web interfaces," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(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:ura:ecregj:v:1:y:2016:i:2:p:405-416. 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: Alexey Naydenov (email available below). General contact details of provider: http://www.economyofregion.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.