Creating Spatial Models of Demographic Processes Using Cluster Analysis for Demographic Policy Planning in Bulgaria

Author:

KASTREVA Penka1ORCID,PATARCHANOVA Emilia1ORCID

Affiliation:

1. South-West University “Neofit Rilski”, Faculty of Mathematics and Natural Sciences, Blagoevgrad, BULGARIA

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.

Publisher

Babes-Bolyai University

Subject

Geography, Planning and Development

Reference30 articles.

1. 1. Andreeva P., Andreev A. (2020), On the problems related to the implementation of geographic information systems in Bulgaria. [online], URL: https://www.aadcf.nvu.bg/scientific_events/papers/dtf2020.pdf. Accessed on 28.11.2021

2. 2. Antipova E., Fakeyeva L. (2012), Settlement system of Belarus: spatial and temporal trends at the end of 20th and the beginning of the 21st centuries. Journal of Settlements and Spatial Planning, 3 (2), 129–139. URL: http://geografie.ubbcluj.ro/ccau/jssp/arhiva_2_2012/09JSSP022012.pdf

3. 3. Delgado Viñas C. (2013), Population Dynamics of Spanish Mountain Areas: Case Study of Two Regions in the Cantabrian Mountains (Spain). Journal of Settlements and Spatial Planning, Special Issue (2), 207-217. URL: https://geografie.ubbcluj.ro/ccau/jssp/arhiva_si2_2013/04JSSPSI022013.pdf

4. 4. ESRI (2014), An overview of the Mapping Clusters toolset. [online], URL: https://desktop.arcgis.com/en/arcmap/10.3/tools/spatial-statistics-toolbox/an-overview-of-the-mapping-clusters-toolset.htm. Accessed on 05.06.2021

5. 5. ESRI (2014), How Grouping Analysis works. [online], URL: https://desktop.arcgis.com/en/arcmap/10.3/tools/spatial-statistics-toolbox/grouping-analysis.htm. Accessed on 05.06.2021

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