At present, the Russian economic situation is characterized by significant imbalances in regional development. So, the forecasting of the indexes of regional social and economic development has become especially relevant. The authors offer a technique of the forecasting of regional social and economic development, it consists of two blocks. The first one is the estimation and forecasting of the level of regional social and economic development. For the purposes of this block, we applied a method of development level and some adaptive methods. The informative basis is the data on the social and economic development of the Republic of Crimea. The change of the integrated index’s growth rate, which is used for the inertial and realistic scenarios, defined the conclusions on the regional socio-economic development. The second block of this technique includes the estimation and forecasting of the social and economic state of considered region. This block is based on the methods of cluster, discriminate and adaptive analyses. The information basis is the data of the social and economic situation of 79 Russian regions for the last 14 years. On the basis of cluster analysis, we divide all Russian regions into two clusters according to their social and economic position. Discriminate models allowed to determine the prospective rate of the Republic of Crimea. The adaptive methods made possible the identification of the researched region to a certain cluster. In the article, the presented models support a complex estimation of the level of regional socio-economic development in the current forecast period and can be considered as a tool of decision-making support at the multivariate scenario analysis of the regional development strategy.

The economics of the Russian Federation is characterized by imbalanced social-economic development of its regions. For assessing the local regional imbalances we used the methods of multidimensional classification along with the methods of convergence analysis: methods of factor analysis, cluster analysis, discriminant analysis. The article offers to use exploratory factor analysis to cluster the Russian Federation’s regions. This method allows performing the procedure of classification structures’ identification when there is a large number of classification’s objects described by dozens of variables each. We checked the hypothesis that at a definite moment or period of time each region is described by some set of interconnected variables. This interconnection occurs due to exploratory factors which make these valuables interconnect in the necessary way. The model of exploratory factor analysis describes this situation. The basis of our research was the official Rosstat’s statistics for the period from 2014 to 2016. This specific period is characterized by changes in Russia’s spatial organization as two federal subjects, the city of Sevastopol and the Republic of Crimea, were included. As a result of calculations three exploratory factors have been defined: the first one encourages the usage of natural resources to form the gross regional product; the second one is interpreted as the factor that is not promoting the economic growth; the third one indicates the necessity to develop activity which is not connected with natural resources. We have distinguished eight economic clusters of subjects of three federal districts and have defined the character of the exploratory factors’ influence. The results of this research can be taken into account by the federal authorities during the comparative analysis of the economic development of the Russian Federation’s subjects, and formation of a developing strategy of the whole country in general and each subject in particular.