Creating Spatial Models of Demographic Processes Using Cluster Analysis for Demographic Policy Planning in Bulgaria
Penka KASTREVA*1, Emilia PATARCHANOVA1
* Corresponding author
1 South-West University “Neofit Rilski”, Faculty of Mathematics and Natural Sciences, Blagoevgrad, BULGARIA
penkakastreva@gmail.com https://orcid.org/0000-0002-5863-532X
emilia_patarchanova@swu.bg https://orcid.org/0000-0002-1806-557X
Pages: 119-130
Abstract. Despite the demographic policy conducted by the state, demographic processes in Bulgaria have been negative for more than 30 years, with spatial differences in their manifestation and results. The main goal of our research is to find demographically stable municipalities that can be accepted as a model of demographic policy implementation to achieve positive changes in the population growth. For this purpose we investigated and identified the changes in the main demographic indicators of population for 2011 and 2019, using cluster analysis. We created spatial models of these demographic processes showing that the number of demographically sustainable municipalities is lower than that of the ones in an advanced depopulation process. Several statistical methods (tools) of specialized software - cluster analysis, Hot Spot Analysis, Spatial Autocorrelation were used. Our hypothesis that the demographic stability of a municipality is most strongly influenced by its economy was confirmed. The analysis proved that demographically stable municipalities are represented by the largest cities and economic centres of Bulgaria. A large number of them, located mainly in mountainous and/or rural areas of Bulgaria, are highly depopulated. The significant socioeconomic inequalities in Bulgaria are a major factor that stimulates internal migration to economic centres and deepens the depopulation of vast parts of the country. They are home to older people and, therefore, these municipalities record very low birth rate and high mortality.
K e y w o r d s: demographic processes, depopulation, spatial models, cluster analysis, Hot Spot Analysis, Spatial Autocorrelation, sustainable municipalities, Bulgaria