A mathematical model for the evaluation of the RF regions' credit rating
Importance The rating agencies calculate credit rating by using the present and past financial histories. These agencies can be either regional or sectoral ones, i.e. they are specialists in a specific geographic region or industry, or they represent the international rating agencies, which include Standard & Poor's, Moody's Investors Service and Fitch Ratings. It is obvious that getting a credit rating is not a problem. However, with sufficiently high and not always reasonable expenses, the government bodies are in need to assess the expected rating level before they will have to pay to agencies for services provided. This article is considering the development of a model, allowing estimating the likely level of credit rating, thus preventing the risk of failure of the assigned rating. Objectives The research aims to define input data of a mathematical model, based on which the rating agencies assign ratings; check baseline information in terms of statistical indicators; develop a risk assessment of refinancing model for territorial entities, which already have a rating; consider the use of models for subjects, which do not yet have a rating. Methods To build the financial indicator model of the Russian Federation territorial entities, we used the most significant models by means of a factor analysis. To build a model to determine the possible level of credit ratings of the Russian Federation regions, we used a regression analysis. Results Within the framework of research, we have solved the following tasks: identified the most important factors that influence an entity's rating. Using the regression analysis, we have constructed a model to determine the possible level of credit ratings of the Russian Federation regions with aid of eight financial performances of the region. Conclusions and Relevance We conclude that in today's economy, a ranking evaluation depends not only on financial performances, but also on economic, political, demographic, and other ones. Therefore, while using the model, it is necessary to probe the minimum impact of other factors on the level of rating.