Abstract:

This article studies the relationship between the main economic and social indicators characterizing the regions of Russia, and their impact on the value of average consumer spending per capita. The main goal of the study is to determine indicators that affect to a greater extent the value of average consumer spending per capita. The main research tools were selected methods of mathematical statistics, linear regression, mathematical regularization and machine learning. As the subject of the study, statistics were used for all 85 constituent entities of the Russian Federation for 2010-2019, provided by an official source, the Federal Service of the State Russian Federation. A large sample of statistical data guarantees the accuracy of the forecast and the reliability of our conclusions, which allows us to judge the scientific approach in our work. The study will make it possible to mathematically precisely substantiate which indicators contribute most to the value of average consumer spending per capita, which enables regional and federal authorities to obtain information on data that will help to better develop regional economic and social policies. Using machine learning methods, a mathematical model will also be developed that allows predicting average consumer spending per capita if other economic and social indicators of the region for the period preceding the study are known.