Abstract
Demographic processes have been disturbed on those Ukrainian territories which have undergone occupation as a result of Russian Federation’s war against Ukraine. However, in order to rebuild such territories, local authorities need information on the prospects of demographic situation. Therefore, determining possible information sources and choosing models to forecast demographic indicators for local communities is relevant. The purpose of this work is identifying possible information sources and choosing models to predict demographic indicators for local communities; forecasting of population numbers, birth rate and mortality via splines for Vyshgorodsky district, Kyiv oblast communities. Novelty: forecasting of demographic indicators for local communities via spline functions. It has been shown that retrospective demographic research at local communities level is possible, if the communities’ contemporary borders correspond to the past administrative and territorial division. However, there are certain limitations regarding the indicators set. The analysis of 1979-2020 data on population numbers, birth rate and mortality for Ivankivsky and Polisky local communities has shown that the 1986-1988 data cannot be used for forecasting, since it varies considerably. This has been caused by the evacuation of residents from Chornobyl Exclusion Zone and administrative and territorial changes. The usage of spline functions in forecasting has shown that splines which have 5-7 knots are optimal. The most adequate forecasts of population numbers can be obtained via cubic splines, whereas the most trustworthy forecasts of birth rate and mortality – via linear continuous splines. It has been determined that the last years’ trends in population numbers, birth rate and mortality would continue in Vyshgorodsky district, Kyiv oblast local communities during 2021-2024. Due to hostilities on the territory of the district, there is no true data on demographic situation, and actual data may turn out to be far from the forecasted because of families with children emigration and mortality growth. Further research to improve the methodology of demographic forecasting by taking into account accidents that cause unfavorable demographic consequences is necessary.
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