Assessing the impact of banking efficiency, operations, and regulation on banking performance: Fresh insight using dynamic correlated framework on the data set of Russia and Ukraine

Abstract

The purpose of this study is to investigate how banking industry-specific variables like regulation, efficiency, and operations affected nonperforming loans (NPLs) in Ukraine and Russia from 1995 to 2019. This study has employed the robust unit root test and cross-sectional dependencies technique along with a new DCCE approach. The dynamic correlated method is employed as it provides the best results when data suffers from cross-sectional dependencies. The study concludes that loose credit policy and lower profitability help in rising NPLs. However, in the context of macroeconomic variables, volatile interest rates, and exchange rate fluctuations are the main reason for NPLs in Russia and Ukraine.
 The research work also highlights the issue of cross-sectional dependencies and provide substantial methods to resolve the problem of cross-sectional dependencies and provide robust results. Findings will help policymakers to recognize the relevance of industry-specific variables in managing NPLs along with other macroeconomic variables.

The Impact of Financial Development and Macroeconomic Fundamentals on Nonperforming Loans among Emerging Countries: An Assessment Using the NARDL Approach

“…Likewise, financial development lowers the effect of risk ratios on banks' efficiency. Developed capital markets reduce financing frictions as they enable banks to raise additional equity to expand their lending scope, and therefore their efficiency level increases [42,43]. Contrary to the first viewpoint, the second one highlights that a higher level of financial development leads to tough competition and undue interference from foreign entities, creating monopolistic tendencies and lower technical efficiency.…”