IDEAS home Printed from https://ideas.repec.org/a/ris/apltrx/0412.html
   My bibliography  Save this article

Analysis of the spatial features of regional power consumption in the Russian Federation

Author

Listed:
  • Petrov, Mikhail

    (Institute of Economics of the Ural Branch of RAS, Ekaterinburg, Russian Federation)

  • Serkov, Leonid

    (Institute of Economics of the Ural Branch of RAS, Ekaterinburg, Russian Federation)

  • Kozhov, Konstantin

    (Institute of Economics of the Ural Branch of RAS, Ekaterinburg, Russian Federation)

Abstract

The article analyzes the features of interregional power consumption within the framework of spatial econometrics. Using the Moran's method, it is shown that the level of electricity consumption in a certain region is positively correlated with the level of electricity consumption in neighboring regions. To assess the energy-economic factors providing this positive impact, spatial autoregression models have been built. Of all the models analyzed, the most appropriate is the one with the spatial lag of the dependent variable (SAR model). From the assessment of the marginal effects (direct, indirect and general), it was concluded that the regional distribution of electricity consumption is largely explained by the processes taking place within the region than in neighboring regions. A model with an extended specification that takes into account the presence and interaction of price and non-price zones is analyzed. The results obtained indicate that the spatial relationships between the regions of the price zone differ from the relationships between the regions of the non-price zone.

Suggested Citation

  • Petrov, Mikhail & Serkov, Leonid & Kozhov, Konstantin, 2021. "Analysis of the spatial features of regional power consumption in the Russian Federation," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 61, pages 5-27.
    • Handle: RePEc:ris:apltrx:0412
    as

    Download full text from publisher

    File URL: http://pe.cemi.rssi.ru/pe_2021_61_005-027.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kukoverov, M., 2019. "On Price Elasticity of Electicity Demand," Journal of the New Economic Association, New Economic Association, vol. 42(2), pages 70-92.
    2. Blázquez Gomez, Leticia M. & Filippini, Massimo & Heimsch, Fabian, 2013. "Regional impact of changes in disposable income on Spanish electricity demand: A spatial econometric analysis," Energy Economics, Elsevier, vol. 40(S1), pages 58-66.
    3. Oleg Turygin, 2018. "Internal Sources to Increase Financing for Fixed Investments in a Company," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, vol. 1(4), pages 1498-1511.
    4. E. V. Galperova, 2019. "Long-Term Analysis of Energy Consumption by Household," Studies on Russian Economic Development, Springer, vol. 30(2), pages 146-153, March.
    5. Hubert Jayet & Julie Le Gallo & Luc Anselin, 2008. "Spatial Econometrics and Panel Data Models," Post-Print hal-02389412, HAL.
    6. Gaivoronskaia, E. & Tsyplakov, A., 2018. "Using a Modified Erev-Roth Algorithm in an Agent-Based Electricity Market Model," Journal of the New Economic Association, New Economic Association, vol. 39(3), pages 55-83.
    7. Yuriy Vladimirovich Pavlov & Elena Nikolaevna Koroleva, 2014. "Spatial Interactions: Evaluation with the Help of Global and Local Moran’s Index," Spatial Economics=Prostranstvennaya Ekonomika, Economic Research Institute, Far Eastern Branch, Russian Academy of Sciences (Khabarovsk, Russia), issue 3, pages 95-110.
    8. Demidova, Olga, 2014. "Spatial-autoregressive model for the two groups of related regions (eastern and western parts of Russia)," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 34(2), pages 19-35.
    9. LeSage, James P. & Kelley Pace, R., 2007. "A matrix exponential spatial specification," Journal of Econometrics, Elsevier, vol. 140(1), pages 190-214, September.
    10. Elena Kurushina & Mikhail Petrov, 2018. "Performance Criteria of Spatial Development Projects Based on Interregional Integration," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, vol. 1(1), pages 176-189.
    11. Richard York & Eugene A. Rosa & Thomas Dietz, 2002. "Bridging Environmental Science with Environmental Policy: Plasticity of Population, Affluence, and Technology," Social Science Quarterly, Southwestern Social Science Association, vol. 83(1), pages 18-34, March.
    12. Luc Anselin, 2010. "Thirty years of spatial econometrics," Papers in Regional Science, Wiley Blackwell, vol. 89(1), pages 3-25, March.
    13. David M. Drukker & Ingmar Prucha & Rafal Raciborski, 2013. "Maximum likelihood and generalized spatial two-stage least-squares estimators for a spatial-autoregressive model with spatial-autoregressive disturbances," Stata Journal, StataCorp LLC, vol. 13(2), pages 221-241, June.
    14. David M. Drukker & Peter Egger & Ingmar R. Prucha, 2013. "On Two-Step Estimation of a Spatial Autoregressive Model with Autoregressive Disturbances and Endogenous Regressors," Econometric Reviews, Taylor & Francis Journals, vol. 32(5-6), pages 686-733, August.
    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. Gaivoronskaia, Elizaveta, 2020. "Electricity demand elasticity and regional effects: Spatial econometric approach," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 58, pages 76-95.
    2. Bivand, Roger & Piras, Gianfranco, 2015. "Comparing Implementations of Estimation Methods for Spatial Econometrics," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i18).
    3. Marcos Herrera Gomez, 2015. "Econometría espacial usando Stata. Breve guía aplicada para datos de corte transversal," Working Papers 13, Instituto de Estudios Laborales y del Desarrollo Económico (IELDE) - Universidad Nacional de Salta - Facultad de Ciencias Económicas, Jurídicas y Sociales.
    4. Álvarez, Inmaculada C. & Barbero, Javier & Zofío, José L., 2017. "A Panel Data Toolbox for MATLAB," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 76(i06).
    5. Stephen Matthews & Daniel M. Parker, 2013. "Progress in Spatial Demography," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 28(10), pages 271-312.
    6. repec:rri:wpaper:201301 is not listed on IDEAS
    7. Byvaltseva-Stankevich, Anastasia & Panova, Anna, 2025. "Application of spatial econometric methods to analyze factors attracting young faculty to Russian universities," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 77, pages 91-115.
    8. Anna Gloria Billé & Roberto Benedetti & Paolo Postiglione, 2017. "A two-step approach to account for unobserved spatial heterogeneity," Spatial Economic Analysis, Taylor & Francis Journals, vol. 12(4), pages 452-471, October.
    9. Bing Su & Fukang Zhu & Ke Zhu, 2023. "Statistical inference for the logarithmic spatial heteroskedasticity model with exogenous variables," Papers 2301.06658, arXiv.org.
    10. Chen, Yuyu & Jin, Ginger Zhe & Kumar, Naresh & Shi, Guang, 2013. "The promise of Beijing: Evaluating the impact of the 2008 Olympic Games on air quality," Journal of Environmental Economics and Management, Elsevier, vol. 66(3), pages 424-443.
    11. Malabika Koley & Anil K. Bera, 2022. "Testing for spatial dependence in a spatial autoregressive (SAR) model in the presence of endogenous regressors," Journal of Spatial Econometrics, Springer, vol. 3(1), pages 1-46, December.
    12. Bouke Klein Teeselink & Georgios Melios, 2022. "Weather to Protest: The Effect of Black Lives Matter Protests on the 2020 Presidential Election," Working Papers CEB 22-007, ULB -- Universite Libre de Bruxelles.
    13. Marco Baudino, 2020. "Environmental Engel curves in Italy: A spatial econometric investigation," Papers in Regional Science, Wiley Blackwell, vol. 99(4), pages 999-1018, August.
    14. Hyunjung Ji & Mark Patrick Tate, 2021. "Spillover effects of central cities on sustainability efforts in a metropolitan area," Policy Sciences, Springer;Society of Policy Sciences, vol. 54(1), pages 95-121, March.
    15. L.A. Serkov & M.B. Petrov & K.B. Kozhov, 2021. "Modeling the Interaction of the Regions of Russia and the Republic of Belarus in the Sphere of the Processing Industry," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, vol. 20(2), pages 217-240.
    16. Jangik Jin & Kurt Paulsen, 2018. "Does accessibility matter? Understanding the effect of job accessibility on labour market outcomes," Urban Studies, Urban Studies Journal Limited, vol. 55(1), pages 91-115, January.
    17. Florian M. Hollenbach, 2021. "Elite interests and public spending: Evidence from Prussian cities," The Review of International Organizations, Springer, vol. 16(1), pages 189-211, January.
    18. Nakano, Yuko & Tsusaka, Takuji W. & Aida, Takeshi & Pede, Valerien O., 2018. "Is farmer-to-farmer extension effective? The impact of training on technology adoption and rice farming productivity in Tanzania," World Development, Elsevier, vol. 105(C), pages 336-351.
    19. Herrera Gómez, Marcos, 2017. "Fundamentos de Econometría Espacial Aplicada [Fundamentals of Applied Spatial Econometrics]," MPRA Paper 80871, University Library of Munich, Germany.
    20. David M. Drukker & Ingmar Prucha & Rafal Raciborski, 2013. "A command for estimating spatial-autoregressive models with spatial-autoregressive disturbances and additional endogenous variables," Stata Journal, StataCorp LLC, vol. 13(2), pages 287-301, June.
    21. Peng Chen & Pan Sun & Zaijun Li, 2025. "A Ride on the Wave of “Digital” and an Advance Towards “Green”: The Spatial and Temporal Impacts of the Integration of Digital and Green Finance on the Pollution and Carbon Reduction Performance in Ch," Sustainability, MDPI, vol. 17(6), pages 1-30, March.

    More about this item

    Keywords

    region; power consumption; interregional connections; spatial autocorrelation; spatial development; Morans method;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)

    Statistics

    Access and download statistics

    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:ris:apltrx:0412. 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: Anatoly Peresetsky (email available below). General contact details of provider: http://appliedeconometrics.cemi.rssi.ru/ .

    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.