Moskva, Moscow, Russian Federation
Plekhanov Russian University of Economics
The relevance of the study is determined by the fact that the current geopolitical situation makes the problem of ensuring energy efficiency of the Russian national economy particularly significant. The indicator "energy intensity of GDP" is used as a key indicator characterizing the efficiency of using energy resources. It is shown that in the period 2012-2022, there was a positive trend towards reducing the energy intensity of GDP due to energy conservation and increased energy efficiency. The regression analysis method was used to evaluate and predict the energy efficiency of the Russian economy. The formed regression model, which includes eight factor indicators, shows that the technological factor is a key driver of reducing the energy intensity of the GDP of the Russian Federation. The performed forecast estimates allow us to state that in the medium term, we should expect a return to the positive downward trend that took place in the period 2012-2022. Current and prospective estimates of the energy intensity of GDP suggest a likely increase in the efficiency of the Russian economy in terms of the use of energy resources.
energy efficiency of the national economy, energy intensity of GDP, strategic planning document, medium-term forecasting, sanctions restrictions
1. Chemezov A.V., Yakhina E.R., Shamarova N.A. On the issue of defining the concept of "Energy efficiency"// Vestnik IrGTU [Bulletin of the IrGTU], 2015, no. 10. pp. 258-262. (in Russian). EDN: https://elibrary.ru/VCPCXV
2. Ponomarev-Stepnoy N.N., Cibul'skiy V.F. Energoemkost' kak kriteriy energoeffektivnosti // Zhurnal prikladnyh issledovaniy. 2010. №1-3. S. 41-43. EDN: https://elibrary.ru/HLWTNM
3. Federal'nyy zakon ot 28.06.2014 N 172-FZ «O strategicheskom planirovanii v Rossiyskoy Federacii». URL: https://www.consultant.ru/document/cons_doc_LAW_164841/fe7140d7cfc6c641ae322fe648d99702d8b2a8f1/
4. Gerashchenko I.P. Forecasting methods in regression and adaptive models for dynamic series analysis // Matematicheskie struktury i modelirovanie [Mathematical Structures and modeling], 2000, no. 5, pp. 140-154. (in Russian). EDN: https://elibrary.ru/VQFYXF
5. Kumratova A. M., Plotnikov V.A. Primenenie metodov nelineynoy dinamiki i mashinnogo obucheniya dlya prognozirovaniya ekonomicheskih volatil'nyh processov // π-Economy. 2024. T. 17, № 3. S. 81-95. DOIhttps://doi.org/10.18721/JE.17306. EDN: https://elibrary.ru/BPTKWE
6. Ukaz Prezidenta RF ot 07.05.2024 N 309 «O nacional'nyh celyah razvitiya Rossiyskoy Federacii na period do 2030 goda i na perspektivu do 2036 goda». URL: https://www.consultant.ru/law/hotdocs/84648.html
7. Technological development of economic sectors. URL: https://rosstat.gov.ru/folder/11189
8. Izmailov M. K. Ways to increase the efficiency of using fixed assets // Vestnik Moskovskogo universiteta imeni S. YU. Vitte. Seriya 1: Ekonomika i upravlenie [Bulletin of the S. Y. Witte Moscow University. Series 1: Economics and Management], 2019, no. 3 (30), pp. 95-101. (in Russian). DOI: https://doi.org/10.21777/2587-554X-2019-3-95-101; EDN: https://elibrary.ru/EORMFX
9. Smirnov V.V. Effective development of the Russian economy // Nacional'nye interesy: prioritety i bezopasnost' [National interests: priorities and security], 2014, no.33, pp.16-28. (in Russian). EDN: https://elibrary.ru/SKABIH
10. Albiter L.M., Chechina O.S. Assessment of changes in fund returns under the influence of basic technical and economic factors // Vestnik SamGU [Bulletin of the Samara State University], 2014, no 2 (113), pp. 174-179. (in Russian).
11. Zharov V.S. Investment and innovation analysis of the activities of production systems // Nauchno-tekhnicheskie vedomosti SPbGPU. Ekonomicheskie nauki [Scientific and Technical Bulletin of St. Petersburg State Pedagogical University. Economic sciences], 2018, vol. 11, no. 6, pp. 142-152. DOI:https://doi.org/10.18721/JE.11612 (in Russian). EDN: https://elibrary.ru/YUKCLJ
12. On the state of energy conservation and energy efficiency improvement in the Russian Federation in 2022. The State report. URL: https://www.economy.gov.ru/material/file/d81b29821e3d3f5a8929c84d808de81d/energyefficiency2019.pdf?ysclid=m5a1a76gx3588919825
13. Ponomarev-Stepnoy N.N., Tsibulsky V.F. Energy intensity as a criterion of energy efficiency // ZHurnal prikladnyh issledovanij [Journal of Applied Research], 2010, no. 1-3, pp. 41-43. (in Russian). EDN: https://elibrary.ru/HLWTNM
14. Federal Law No. 172-FZ dated 06/28/2014 "On Strategic Planning in the Russian Federation". URL: https://www.consultant.ru/document/cons_doc_LAW_164841/fe7140d7cfc6c641ae322fe648d99702d8b2a8f1/
15. Kumratova A.M., Plotnikov V.A. Application of nonlinear dynamics and machine learning methods for forecasting economic volatile processes // π-Economy [π-Economy], 2024, vol. 17, no. 3, pp. 81-95. DOIhttps://doi.org/10.18721/JE.17306. (in Russian).
16. Decree of the President of the Russian Federation No. 309 dated 05/07/2024 "On the National Development Goals of the Russian Federation for the period up to 2030 and for the future up to 2036". URL: https://www.consultant.ru/law/hotdocs/84648.html



