Establishing the relationship between indicators of the functioning of the labor market and demographic processes (on the example of the Orel region)

Автор: Zaitsev A.G., Takmakova E.V.

Журнал: Вестник аграрной науки @vestnikogau

Рубрика: Экономические науки

Статья в выпуске: 1 (100), 2023 года.

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One of the regions, the demographic situation in which leads to the depletion of the workforce, is the Orel region. The revealed trends of decline in the labor market for the period 2012-2021 cannot be considered without taking into account the deep demographic crisis of the territorial entity under consideration. The purpose of the work is to analyze the dependence of the functioning of the labor market of the Orel region on demographic processes in the Orel region. The conducted correlation and regression analysis confirmed the dependence of the number of employed population on demographic factors, with the help of which it is possible to influence the state of the labor market of the Orel region. Regression models of the number of people employed in the economy are constructed based on such indicators of the demographic situation as: the population at the beginning of the year, the number of births, the number of arrivals, the demographic load coefficient, the level of participation in the labor force of the population aged 15-72 years. The demographic situation is currently aggravated by the crisis that has arisen as a result of the COVID-19 coronavirus pandemic, which the regional government is solving by reducing tension in the labor market and increasing the number of employed people in the short term. However, in the long term, due to the current trend and the factors that hinder demographic development, it is difficult to talk about the possibility of overcoming the crisis of demography and the labor market, so the state can only prevent an even greater decline in indicators.

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Labor market, employment, demographic processes, population, number of employed

Короткий адрес: https://sciup.org/147240029

IDR: 147240029   |   DOI: 10.17238/issn2587-666X.2023.1.100

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