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Economic Analysis: Theory and Practice
 

Managing the risk of probability of default of the Russian Federation subjects

Vol. 15, Iss. 4, APRIL 2016

PDF  Article PDF Version

Received: 30 July 2015

Received in revised form: 30 November 2015

Accepted: 1 February 2016

Available online: 27 April 2016

Subject Heading: MATHEMATICAL METHODS AND MODELS

JEL Classification: C4, C5

Pages: 179-188

Mitsel' A.A. National Research Tomsk Polytechnic University, Tomsk, Russian Federation
maa@asu.tusur.ru

German A.V. National Research Tomsk Polytechnic University, Tomsk, Russian Federation
Anuto4ra70@yandex.ru

Importance Currently, to obtain a credit rating is not a problem. However, despite the fact that the cost of the procedure is quite high and not always justified, the authorities need to assess of the expected level of rating prior to paying for the services of rating agencies, and, in the event of low rating, to be able to manage it.
Objectives The aim of the study is to develop a model to manage the risk of the probability of default of subjects of the Russian Federation.
Methods The model is based on the quadratic criteria and the linear control law.
Results The model is designed so that it may be applied not only by subjects having an assigned rating, but also by those subjects of the Russian Federation that do not yet have a rating assigned by one of leading rating agencies (Standard & Poor's, Fitch Ratings and Moody's). This was possible owing to defining single indicators to calculate the risk of probability of default for all subjects of the Russian Federation. The developed algorithm was applied to the Tomsk oblast.
Conclusions The study revealed that to obtain desired probability over predetermined period, it is necessary to increase certain indicators, like direct debt to individual income ratio, State debt to GRP ratio, public debt expense to budget expense ratio, and some others, and to decrease the ratio of contingent liability to own income, the share of own income in budget revenues, budget deficit to own income ratio, and others.

Keywords: credit rating, constituent entity, Russian Federation, probability of default, risk management

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