Studying the Dynamics of Per Capita Income Using Statistical Methods: Time Series Analysis

T he relevance of the study on Russian per capita income dynamics depends on several factors, primarily lagging behind inflation and asynchrony in its fluctuations compared to real income. The purpose of this study is to use a set of mathematical and statistical techniques on a database that reflects the dynamics of income per capita for the Russian households. Visualization and analysis of initial data, as well as calculation, were performed in the R development environment. To accomplish this goal, we used general scientific methods like analysis, synthesis, and comparison, as well as specific mathematical and statistical approaches, including graphing and econometrics. The results of the study can be summarized as follows: per capita income has shown an overall upward trend from 2012 until 2022, with adjustments due to crises. The dynamics were described using three competing models; the most effective were ARIMA and HoltWinter. Forecasts based on these models predicted further growth in income while maintaining seasonal patterns. Future work on this topic will involve analysing regional differences in income levels across Russia and identifying factors influencing variations in regional incomes.