Abstract:

The article studies the relationship of macroeconomic and social indicators and their impact on the value of gross regional product. In the framework of our scientific work, GRP was chosen by us as the main indicator characterizing the well-being of the subject of the Russian Federation. The aim of the study is to highlight the indicators that have the greatest impact. In addition to the main indicators that are highlighted in such works as an indicator of the average per capita income of the population, we also decided to use indicators that are usually ignored, as the percentage of the population married in the region. The main tools are methods of mathematical statistics, linear regression, methods of mathematical regularization and machine learning. As the subject of the study, statistics were used for all 85 constituent entities of the Russian Federation for 2010-2018, data taken from the official resource of the Federal State Statistics Service “RosStat”. 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 allow mathematically and accurately determine which indicators contribute the most to the value of GRP, which will allow regional and federal authorities to more accurately understand the weaknesses and weaknesses in their current policies. Using machine learning methods, we also developed a mathematical model that allows us to predict GRP based on other economic and social indicators of the region that we used in the study.