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Energy Efficient Development Model for Regions of the Russian Federation: Evidence of Crypto Mining

Author

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  • Artur Meynkhard

    (Department of financial markets and banks, Financial University under the Government of the Russian Federation, Moscow, Russia.)

Abstract

Paper proposes a model of energy efficient development of the regional energy complex, in which provided by mixing and iterative matching forecasts of energy consumption and energy production. The novelty of this method is that it formed in the framework of the regional model, is part of the overall regional product-sector balance formed for the region, which allows to simulate the mutual influence of energy complex and the rest of the economy through interbalance relations. Search for optimal solutions are carried out by iteration using a specially designed approach based on the Stiglitz-Sen-Fitoussi approach. It includes the following welfare components: economic well-being, non-monetary characteristic welfare and reproduction potential of the economy. System of crypto mining based on the evidence of proof-of-work protocol are extremely no energy efficient. Paper also gives evidence of Russian regions for mining of cryptocurrencies in Russia.

Suggested Citation

  • Artur Meynkhard, 2019. "Energy Efficient Development Model for Regions of the Russian Federation: Evidence of Crypto Mining," International Journal of Energy Economics and Policy, Econjournals, vol. 9(4), pages 16-21.
    • Handle: RePEc:eco:journ2:2019-04-3
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    References listed on IDEAS

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    Cited by:

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    2. Vladislav Trubnikov & Ulf Henning Richter, 2020. "China Energy Policy: Evidence of China-Russia Cooperation," International Journal of Energy Economics and Policy, Econjournals, vol. 10(1), pages 145-149.
    3. Pavel Baboshkin, 2020. "Strategic Energy Partnership between Russia and China," International Journal of Energy Economics and Policy, Econjournals, vol. 10(5), pages 158-163.
    4. Rolando Rubilar-Torrealba & Karime Chahuán-Jiménez & Hanns de la Fuente-Mella, 2023. "A Stochastic Analysis of the Effect of Trading Parameters on the Stability of the Financial Markets Using a Bayesian Approach," Mathematics, MDPI, vol. 11(11), pages 1-14, May.
    5. Miguel Ángel Echarte Fernández & Sergio Luis Náñez Alonso & Javier Jorge-Vázquez & Ricardo Francisco Reier Forradellas, 2021. "Central Banks’ Monetary Policy in the Face of the COVID-19 Economic Crisis: Monetary Stimulus and the Emergence of CBDCs," Sustainability, MDPI, vol. 13(8), pages 1-18, April.
    6. Anton Lisin, 2020. "Biofuel Energy in the Post-oil Era," International Journal of Energy Economics and Policy, Econjournals, vol. 10(2), pages 194-199.
    7. Artur Meynkhard, 2020. "Priorities of Russian Energy Policy in Russian-Chinese Relations," International Journal of Energy Economics and Policy, Econjournals, vol. 10(1), pages 65-71.
    8. Jaehyung An & Alexey Mikhaylov & Sang-Uk Jung, 2020. "The Strategy of South Korea in the Global Oil Market," Energies, MDPI, vol. 13(10), pages 1-8, May.
    9. Nishant Sapra & Imlak Shaikh & Ashutosh Dash, 2023. "Impact of Proof of Work (PoW)-Based Blockchain Applications on the Environment: A Systematic Review and Research Agenda," JRFM, MDPI, vol. 16(4), pages 1-29, March.
    10. Sergio Luis Náñez Alonso & Javier Jorge-Vázquez & Miguel Ángel Echarte Fernández & Ricardo Francisco Reier Forradellas, 2021. "Cryptocurrency Mining from an Economic and Environmental Perspective. Analysis of the Most and Least Sustainable Countries," Energies, MDPI, vol. 14(14), pages 1-22, July.
    11. Dmitry V. Boguslavsky & Natalia P. Sharova & Konstantin S. Sharov, 2021. "Cryptocurrency as Epidemiologically Safe Means of Transactions: Diminishing Risk of SARS-CoV-2 Spread," Mathematics, MDPI, vol. 9(24), pages 1-19, December.
    12. Jaehyung An & Mikhail Dorofeev & Shouxian Zhu, 2020. "Development of Energy Cooperation between Russia and China," International Journal of Energy Economics and Policy, Econjournals, vol. 10(1), pages 134-139.

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    More about this item

    Keywords

    energy; resource saving; energy efficient development; energy indicators; forecasting;
    All these keywords.

    JEL classification:

    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy

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