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IJMLC 2019 Vol.9(4): 496-505 ISSN: 2010-3700
DOI: 10.18178/ijmlc.2019.9.4.832

Estimating the Consequences of Russia’s and the EU’s Sanctions Based on OLS Algorithm

I. V. Tregub and K. A. Dremva

Abstract—In the presented paper, financial analysis of the consequences of sanctions imposed by the European Union on Russian Federation and Russian counter-sanctions was carried out. With the application of the OLS algorithm, an econometric model was developed. The key factors, which influence the growth of the EU economy, have been identified. It was shown how exactly the EU would proceed after having severed or at least severely restricted its trade turnover with Russia. As it is showcased in the model, the EU is not particularly dependent on its ties with Russia in order to continue flourishing. Throughout this research, we have obtained a model, which best highlights the connection formed between Russia and the EU via studying the links between the aggregate GDP of the EU and the values for the export to Russia and import from Russia, as well as the price for gas, as the EU is the primary consumer of the Russian gas resources.

Index Terms—Computing, econometric model, Russia’s and the EU’s sanctions.

I. Tregub is with the Department of Data Analysis, Decision Making and Financial Technology, Financial University under the Government of Russian Federation. 49 Leningradsky Prospekt, Moscow, Russia, 125993 (e-mail: itregub@fa.ru).


Cite: I. V. Tregub and K. A. Dremva, "Estimating the Consequences of Russia’s and the EU’s Sanctions Based on OLS Algorithm," International Journal of Machine Learning and Computing vol. 9, no. 4, pp. 496-505, 2019.

Copyright © 2019 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

General Information

  • E-ISSN: 2972-368X
  • Abbreviated Title: Int. J. Mach. Learn.
  • Frequency: Quaterly
  • DOI: 10.18178/IJML
  • Editor-in-Chief: Dr. Lin Huang
  • Executive Editor:  Ms. Cherry L. Chen
  • Abstracing/Indexing: Inspec (IET), Google Scholar, Crossref, ProQuest, Electronic Journals LibraryCNKI.
  • E-mail: ijml@ejournal.net

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