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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
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    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 LP, 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.
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    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)

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