Methodology of analyzing quality of life in a region[Методика Анализа Качества Жизни В Регионе]

Introduction. One of the priority areas of modern government policy is to improve the quality of life of citizens. The strategic state acts: the Decree of the President of the Russian Federation “On the national development goals of the Russian Federation for the period until 2030”, and the “National Security Strategy of the Russian Federation” formulate priority directions for improving the quality of life of citizens. Since the socio-economic development of the country is impossible without increasing the efficiency of the regions, much attention is paid to the development of new methods and approaches to analyzing the quality of life of the population. Today, despite the presence of numerous studies in this area, there is no universal mathematical apparatus for analyzing and predicting quality of life indicators in the region. This circumstance contributes to a decrease in the efficiency of management activities and, as a result, weak control over the life activity of territories. Therefore, the purpose of the study was to develop a methodology for analyzing and predicting the quality of life in the region. Materials and methods. The basis of the developed methodology is a mathematical model of system dynamics. The model includes system variables, external factors, and functional dependencies that determine positive and negative relationships between the elements of the model. Indicators of socio-economic development of the region are used as model variables. The mathematical model consists of eight differential equations, the solution of which, given the initial conditions and time interval, is the predicted values of quality of life indicators. Results. The practical implementation of the developed methodology for analyzing the quality of life in the Saratov region is shown. The characteristics of the current state of the socio-economic situation of the Saratov region are given. Multivariate forecasting is implemented in the development of various scenarios for the socio-economic development of the region. Graphs of predicted values of quality of life indicators for the time interval [2023;2027] are presented. The algorithm for implementing the developed methodology at varying time intervals and different control levels is shown using an information-logical diagram. Discussions and conclusions. The presented author's methodology for analyzing indicators of the quality of life of the population in the region is aimed at timely provision of information to decision makers for making the necessary management decisions.