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Analyzing reasons for projected long-term growth of real GDP of Russia

Vol. 18, Iss. 11, NOVEMBER 2019

Received: 3 October 2019

Received in revised form: 17 October 2019

Accepted: 1 November 2019

Available online: 29 November 2019

Subject Heading: MONETARY ACCOMMODATION

JEL Classification: E42, E50, E58, E59, O42

Pages: 2575–2593

https://doi.org/10.24891/fc.25.11.2575

Smirnov V.V. I.N. Ulianov Chuvash State University (ChuvSU), Cheboksary, Chuvash Republic, Russian Federation
v2v3s4@mail.ru

https://orcid.org/0000-0002-6198-3157

Mulendeeva A.V. I.N. Ulianov Chuvash State University (ChuvSU), Cheboksary, Chuvash Republic, Russian Federation
alena-mulendeeva@yandex.ru

https://orcid.org/0000-0002-9852-9804

Osipov D.G. I.N. Ulianov Chuvash State University (ChuvSU), Cheboksary, Chuvash Republic, Russian Federation
denps@mail.ru

ORCID id: not available

Babaeva A.A. I.N. Ulianov Chuvash State University (ChuvSU), Cheboksary, Chuvash Republic, Russian Federation
any9196@yandex.ru

https://orcid.org/0000-0001-7639-8113

Gorbunova P.G. I.N. Ulianov Chuvash State University (ChuvSU), Cheboksary, Chuvash Republic, Russian Federation
polina7103@mail.ru

https://orcid.org/0000-0003-1044-5305

Subject The article considers the real GDP growth in Russia within the projected long-term period and analyzes its drivers.
Objectives The aim of the study is to identify reasons for projected long-term growth of Russia's real GDP and to link it up with the ontology through the understanding of changes in economic systems.
Methods The study employs the systems approach, using the techniques of statistical, cluster, and neural network analysis.
Results We identified various systems to assess changes in the GDP of Russia that enable to show its rise and fall. Changes in the nominal GDP of Russia used by the Bank of Russia as a criterion for its assessment make it possible to rationalize the validity of the inflation targeting policy. The combination of inflation targeting and the ‘deleverage’ mechanism applied by the Bank of Russia creates conditions for share price growth in the face of slow pace of investment growth and falling domestic demand. The findings may be helpful for explaining the reasons for changes in the nominal and real GDP of Russia, as well as for educational process.
Conclusions The reasons for the forecast volatility of long-term growth of Russia's real GDP include the targeted reduction of inflation and leverage that caused an increase in stock price in the context of slow investment growth and a fall in domestic demand.

Keywords: domestic demand, long-term growth, investment, nominal GDP, real GDP, share price

References:

  1. Gibson H.D., Hall S.G., Tavlas G.S. Nonlinear Forecast Combinations: An Example Using Euro-Area Real GDP Growth. Journal of Economic Behavior & Organization. (In press, corrected proof). URL: Link
  2. Plante M., Richter A.W., Throckmorton N.A. The Zero Lower Bound and Endogenous Uncertainty. The Economic Journal, 2018, vol. 128, iss. 611, pp. 1730–1757. URL: Link
  3. Reinhart C.M., Reinhart V.R. Author Notes. Financial Crises, Development, and Growth: A Long-term Perspective. The World Bank Economic Review, 2015, vol. 29, iss. suppl_1, pp. S53–S76. URL: Link
  4. Glaz'ev S.Yu. [Stabilization of the monetary and financial market as a necessary condition for the transition to sustainable development]. Ekonomika regiona = Economy of Region, 2016, vol. 12, no. 1, pp. 28–36. URL: Link (In Russ.)
  5. Glaz'ev S.Yu. [Priorities of the Russian economy's accelerated development during the transition to a new technological mode]. Ekonomicheskoe vozrozhdenie Rossii = Economic Revival of Russia, 2019, no. 2, pp. 12–16. URL: Link (In Russ.)
  6. Ivanter V.V. [Prospects of economic growth in Russia]. Nauchnye trudy Vol'nogo ekonomicheskogo obshchestva Rossii = Scientific Works of the Free Economic Society of Russia, 2015, vol. 196, no. 7, pp. 195–202. (In Russ.)
  7. Maevskii V.I. [Mesolevel and hierarchical structure of the economy]. Journal of Institutional Studies, 2018, vol. 10, no. 3, pp. 18–29. (In Russ.) URL: Link
  8. Makarov V.L., Bakhtizin A.R., Khabriev B.R. [Performance evaluation of the mechanisms strengthening the State sovereignty of Russia]. Finansy: teoriya i praktika = Finance: Theory and Practice, 2018, vol. 22, no. 5, pp. 6–26. (In Russ.) URL: Link
  9. Keister T. The Interplay Between Liquidity Regulation, Monetary Policy Implementation and Financial Stability. Global Finance Journal, 2019, vol. 39, pp. 30–38. URL: Link
  10. De Moraes C.O., Montes G.C., Antunes J.A.P. How Does Capital Regulation React to Monetary Policy? New Evidence on the Risk-Taking Channel. Economic Modelling, 2016, vol. 56, pp. 177–186. URL: Link
  11. Tayler W.J., Zilberman R. Macroprudential Regulation, Credit Spreads and the Role of Monetary Policy. Journal of Financial Stability, 2016, vol. 26, pp. 144–158. URL: Link
  12. Lazar J., Feng J.H., Hochheiser H. Chapter 4: Statistical Analysis. In: Research Methods in Human Computer Interaction (Second Edition). Elsevier, 2017, pp. 71–104. URL: Link
  13. Schofield S. Impressive Statistical Analysis. Science and Public Policy, 1993, vol. 20, iss. 3, pp. 214–215. URL: Link
  14. Adolfsson A., Ackerman M., Brownstein N.C. To Cluster, or Not to Cluster: An Analysis of Clusterability Methods. Pattern Recognition, 2019, vol. 88, pp. 13–26. URL: Link
  15. Favero L.P., Belfiore P. Chapter 11: Cluster Analysis. In: Data Science for Business and Decision Making. Elsevier, 2018, pp. 311–382. URL: Link

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