FORECASTING MODELS THE VOLUME OF OVERDUE DEBT ON LOANS

• Main Authors: N. N. Karabutov, V. G. Feklin
• Format: Article
• Language: Russian
• Published: Government of the Russian Federation, Financial University 2017-10-01
• Series: Финансы: теория и практика
• Subjects: loan; overdue debt; parametric identification; regression model; lagged variables; forecasting
• Online Access: https://financetp.fa.ru/jour/article/view/177

Dynamics of debt on loans is important characteristic of the development of the real sector of the economy. Growth of arrears indicates negative trend of the economic development of the real sector of the economy. In connection with the above monitoring and forecasting of the volume of the overdue debt has a very importance in the conditions of economic instability. We used the Official statistics of the Central Bank of the Russian Federation to show a steady decline in the share of overdue debt in the period from January 2011 to December 2013, and the change of this trend in the beginning of 2014. Greatest growth of overdue debts since the beginning of 2015, which was a manifestation of the crisis phenomena in the Russian economy.In this article we constructed models for predicting the volume of overdue debt on loans to legal entities and individual entrepreneurs. There was evaluated the predictive properties of the constructed models and showed the advantage of the use of the identification approach to the choice of model structure.