Use of Binary Dependent Variables for Modelling Borrowers’ Creditworthiness

E I Kadochnikova,L D Badrieva,E A Grigoreva,E A Polovkina

doi:10.5539/ass.v11n11p396

E I Kadochnikova, L D Badrieva + Show 2 more

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https://doi.org/10.5539/ass.v11n11p396

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Journal: Asian Social Science	Publication Date: Apr 30, 2015
Citations: 5	License type: cc-by

Affiliation: Kazan Federal University

Abstract

This article provides an econometric analysis of borrowers’ creditworthiness in order to create corporateorganizational and economic knowledge. It stresses the need for modern methods of applied analysis of creditportfolio management. The authors seek to prove the feasibility of using binary variables to identify and measurecreditworthiness drivers in cognitive supporting of a credit institution management. The paper proposes amethodological approach to modeling the creditworthiness of potential borrowers based on models with binarydependent variables. The results of empirical evaluations which were received through the application of Gretlsoftware confirmed their feasibility in management of the loan portfolio by credit institutions.

Highlights

Credit operations while playing an important role in the development of banks and welfare of legal entities determine the efficiency of the economy as a whole
The authors seek to prove the feasibility of using binary variables to identify and measure creditworthiness drivers in cognitive supporting of a credit institution management
The paper proposes a methodological approach to modeling the creditworthiness of potential borrowers based on models with binary dependent variables

Summary

Introduction

Credit operations while playing an important role in the development of banks and welfare of legal entities determine the efficiency of the economy as a whole. Improving techniques for objective evaluation of the creditworthiness of borrowers legal entities are relevant in the instable economy of the country. In this context, the aim of the study is to construct an econometric model of borrowers creditworthiness using binary dependent variable (Y takes the value of one if the loan was issued, and a value of zero in case of rejection) (Wooldridge, 2013; Kupriyanov, Borzenkova, & Sergeevna, 2013; Hirth, 2014) and forecasting lender’s loan approval. The practical significance of the study is the possibility of using the developed model by commercial banks in order to enhance the validity of credit decisions

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