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The current stage of economic development requires the use of science-based economic solutions that increase the efficiency of socio-economic development of the region. The impact of various factors on the final result can be estimated using the economic and statistical methods. Their application makes it possible to analyze the studied statistical indicators, build a model and calculate the predicted values on the basis of the obtained data. Economic forecasting is based on the study of the most important principles of the economic processes of expanded reproduction. The quality of the forecast and the success of the strategy formulated on its basis directly affect the effectiveness of decisions at the regional and state levels. The Belgorod region, an actively developing region, was chosen as the object of research. The paper notes that the main indicator characterizing the development potential of the region is the gross regional product (GRP) per capita. On the example of the Belgorod region, using the correlation and regression analysis and the extrapolation method, the authors constructed multifactor models of socio-economic development of the region. At the first stage of the study, factors were selected for inclusion in the model. Among the many factors influencing the dynamics of the effective feature, it is revealed that the strongest impact is made by the consolidated budget revenues and the average annual number of employees in the economy. During the assessment of the adequacy of the constructed models, a comparative analysis was carried out and a regression model of the power function was recommended as a statistically significant one. At the second stage, trend models are constructed and separate forecast values for each factor are obtained. The use of these models allowed building a forecast of GRP per capita with a fairly high degree of accuracy. The results of the study indicate the sustainable development of the Belgorod region.
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