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Financial Analytics: Science and Experience
 

The impact of financial and economic crises on the banking sector of Russia: Statistical evaluation

Vol. 15, Iss. 2, JUNE 2022

Received: 25 February 2019

Received in revised form: 10 March 2019

Accepted: 22 March 2019

Available online: 30 May 2022

Subject Heading: MATHEMATICAL ANALYSIS AND MODELING IN ECONOMICS

JEL Classification: С10, C15, G21

Pages: 232–248

https://doi.org/10.24891/ea.18.4.770

Rafkat S. GAISIN Russian Timiryazev State Agrarian University (RTSAU), Moscow, Russian Federation
gaisin@rgau-msha.ru

ORCID id: not available

Denis V. BYKOV Russian Timiryazev State Agrarian University (RTSAU), Moscow, Russian Federation
bykov1997@mail.ru

ORCID id: not available

Subject. The banking sector, having an increasing impact on the economy, is very receptive to changes occurring at the macro- and micro-level. This area of bank activity is assuming greater urgency in conditions of international integration, unstable political situation in the world and increased likelihood of financial crises.
Objectives. We aim to develop a methodology and test the statistical evaluation of financial and economic crises’ influence on the condition of the Russian banking sector.
Methods. The study employs the correlation and regression analysis, including the multidimensional average-based one, the method of periodization, time series analysis, method of extrapolation.
Results. Our retrospective statistical analysis of the impact of financial crises on banking activities showed a strong and direct link. However, the default of 1998 differs significantly from the crises of 2008 and 2014 in terms of its implications for the banking environment. The paper includes a forecast of main indicators of banking activity with regard to potential financial crises for the period up to 2021.
Conclusions. Macroeconomic indicators most affected by inflationary pressures are increasing even during periods of crisis, while banking indicators suggest decelerating growth. Our unique methods enabled to reveal a tendency to GDP growth and GDP deflator decrease.

Keywords: statistical analysis, banking sector, regression analysis, multidimensional average, forecasting

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