Affiliation:
1. Kherson State University
Abstract
The article analyzes the possible individual aspects of the use of regression analysis in demographic research. The possibilities of analyzing the relationship between the parameters of the formation of the population and its constituent elements are shown. So, the highest correlation coefficient is demonstrated by the pair of signs �population formation (changes) - total migration balance�
The regression method is widely used in natural and social sciences, including geography. The purpose of the presented work is the approbation of models of the spatial regression method for the analysis of features of demographic processes at the regional level. The research region was the Kherson region of Ukraine. It was established that the Kherson region has the following spatial trend: with increasing distance to the regional center, there is a decrease in population formation indicators. Which, the negative balance of migrations, as well as the balance of internal migrations, mortality is also increasing sharply. The conducted regression analysis made it possible to draw conclusions that confirm the postulates of the �Core-Periphery� concept. This concept, in the aspect of demographic processes, emphasizes changes in population formation indicators with increasing distance from the Core to the Periphery. The proposed approach can be used to determine changes in process parameters in both temporal and spatial aspects.
Reference13 articles.
1. [1] Anselin L. Spatial econometrics: methods and models. Springer Science & Business Media, 1988, 284 �. https://doi.org/10.1007/978-94-015-7799-1
2. [2] Golikov A. P.. Economic and geographical modeling of world economic processes: Textbook. Kharkov, KhNU, 2003, 104 p. (in Ukrainian)
3. [3] Malchykova, D., Gukalova, I., Omelchenko, N., & Napadovska, H. Integrated coastal zone management: Restrictions and priorities of development, the implementation of administrative and territorial organization reform. International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM, 19(5.1), 2019, pp. 407-414.
4. [4] Mezentsev K.V. Socio-geographical forecasting of regional development: Monograph, Kyiv, Publishing and Printing Center �Kyiv University�, 2005, 253 p. (in Ukrainian)
5. [5] Mezentsev, K., Oliynyk, Ya., & Mezentseva, N. Urban Ukraine: in the center of spatial changes. Kyiv, Feniks, 2017, 438 p. (in Ukrainian)