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Finance and Credit
 

An analysis of structural functionalism of Russia's financial system

Vol. 25, Iss. 6, JUNE 2019

Received: 16 April 2019

Received in revised form: 30 April 2019

Accepted: 14 May 2019

Available online: 28 June 2019

Subject Heading: Financial system

JEL Classification: E26, F30, P43

Pages: 1280–1296

https://doi.org/10.24891/fc.25.6.1280

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

Subject The article focuses on the structure of Russia’s financial system today and analyzes its functionality.
Objectives The study determines parameters of structural functionalism of the current financial system in Russia and infers the versatile procedure for its analysis.
Methods The study is based on a systems approach, statistical, cluster, neural network and nonparametric analyses.
Results The article provides the rationale for implementing principles of the structural functionalism theory in the current financial system of Russia to ensure the mobile adaptability to a new institutional order of the world. The Central Bank of Russia was found to deal with micromanagement tasks to handle the Ruble money supply, adjusting any deviations through the issue of debt securities denominated in the foreign currency. The volatility of debts due from the non-financial sector and households in foreign currency affects the rate of growth in the volume of debt securities issued in foreign currency. The quality of governmental guarantees on the above debts depend on the rate of growth in the volume of debt securities issued in foreign currency and respective interest rate. Cluster, neural network and nonparametric analyses helped us identify clusters intended to regulate cash flows by managing volumes of net foreign assets and internal requirements, and importance of the requirements to people.
Conclusions and Relevance Requirements to people drive the implementation of monetary policy in the Russian Federation. The general debt burden of Russia was reduced as the debt of the non-financial sector and households shrank as well due to a decrease in the money supply. The findings may prove useful for improving the financial system and increasing the efficiency of monetary policy in Russia.

Keywords: monetary policy, cluster analysis, neural network analysis, nonparametric analysis, financial system

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