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10.5593/sgemsocial2017/13/S03.059

MODELING MARGINAL FACTORS OF CREDIT INSTITUTIONS: ELIMINATING A COLLINEARITY PROBLEM

E.Kadochnikova, S.Savdur, L. Sungatullina, E.Khisamova
Thursday 28 September 2017 by Libadmin2017

References: 4th International Multidisciplinary Scientific Conference on Social Sciences and Arts SGEM 2017, www.sgemsocial.org, SGEM2017 Conference Proceedings, ISBN 978-619-7408-15-7 / ISSN 2367-5659, 24 - 30 August, 2017, Book 1, Vol 3, 471-478 pp, DOI: 10.5593/sgemsocial2017/13/S03.059

ABSTRACT

The article seeks to identify the most important predictors of profit of credit institutions. This involves the use of multiple regression for econometric modeling of several variables on the results of banks’ operations. The study aims to show the capabilities of multi-factor regression in the analysis of credit institutions. The paper proposes a methodological approach to the measurement of marginal predictors of credit institutions. The authors use special techniques to adjust the models to avoid a collinearity problem: ridge regression, principal components method. Using Excel, Gretl software the authors seek to prove the predominant influence of bank stock and private deposits on the revenue dynamics of credit institutions. The article provides a comprehensive understanding of profit formation in credit institutions. The study aims to demonstrate the negative role of the debt load of households in the banking market. Empirical assessments have confirmed the feasibility of their practical use in the management of credit institutions.

Keywords: credit organizations, profit, ridge regression, principal components method, a collinearity problem

PAPER DOI: 10.5593/sgemsocial2017/13/S03.059 ; MODELING MARGINAL FACTORS OF CREDIT INSTITUTIONS: ELIMINATING A COLLINEARITY PROBLEM

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