Use of Binary Dependent Variables for Modelling Borrowers’ Creditworthiness

Abstract

This article provides an econometric analysis of borrowers' creditworthiness in order to create corporate organizational and economic knowledge. It stresses the need for modern methods of applied analysis of credit portfolio management. 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. The results of empirical evaluations which were received through the application of Gretl software confirmed their feasibility in management of the loan portfolio by credit institutions.