Abstract

According to Rosstat for 2020, the population of Russia as a result of its natural movement decreased by 688.7 thousand people. If the birth rate in relation to 2019 decreased by 3.0%, then mortality increased by 17.9%. For many regions of the country (oddly enough, in the first place of its European part), the situation turned out to be even more difficult. At the same time, heterogeneous factors had an impact on each other - a change in the age structure of the population, the COVID-19 pandemic, a decrease in real income, etc. Under these conditions, the problem of obtaining accurate predictive assessments of the situation development in order to develop government policies to improve it is updated. Objectively necessary is the introduction of relevant information systems built on the basis of integrated economic and mathematical models. In this regard, the article discusses the development and application of modern tools for analyzing and predicting the development of territorial systems, including demographic aspects. It is indicated that a significant factor is the development of the social infrastructure of the territory. A system of criteria and indicators are proposed to assess the impact of its level of development on demographic processes. In particular, areas such as health care, education, culture and leisure, housing, trade and services are considered. An approach to the formation of integral indicators in various areas of life of society and an example of developing regression equations based on them is presented. It is noted that in different regions of the country, the degree of influence of the level of development of social infrastructure on demographic processes may differ significantly, which requires accounting within the framework of the model being formed. The possibility and need to build a decision support system based on the obtained model complex and is defined by such a toolkit in the strategic development management system of the region. The key stages of developing tools are described. The results obtained can be used as part of modeling changes in the demographic potential of regions in the context of the transformation of the territorial settlement system.

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