Spatial association of population pyramids across Europe: The application of symbolic data, cluster analysis and join-count tests
Autor: | Justyna Wilk, Roger Bivand, Tomasz Kossowski |
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Rok vydání: | 2017 |
Předmět: |
Statistics and Probability
education.field_of_study media_common.quotation_subject 05 social sciences Population Management Monitoring Policy and Law Spatial distribution Disease cluster 01 natural sciences Symbolic data analysis 010104 statistics & probability Population pyramid Geography 0502 economics and business Pyramid Economic geography 050207 economics 0101 mathematics Computers in Earth Sciences education Spatial analysis Demography Diversity (politics) media_common |
Zdroj: | Spatial Statistics. 21:339-361 |
ISSN: | 2211-6753 |
DOI: | 10.1016/j.spasta.2017.03.003 |
Popis: | Demographic processes across European regions show great diversity, but because of this diversity, it is hard to gain an overview of similarities and differences. This paper aims to examine the application of a new combination of existing approaches to the analysis of regional population pyramids to offer such an overview. Symbolic data analysis and cluster analysis are used to identify typical shapes of population pyramids, before applying join-count tests to examine the spatial distribution of these pyramid shapes. The data used are for 1397 NUTS regional units in 37 European countries in 2015. We find that Irish regions, Cyprus and some of the capital cities of Western Europe present the youngest population across Europe, while the population of Eastern Germany is the oldest and shrinking in size. Countries of East-central Europe are the most homogeneous in their demographic processes for the chosen period, while the large demographic discrepancies occur within Spain, France, the UK, Finland, and Sweden between NUTS regions. A spatial study indicated positive spatial autocorrelation, and the transnational character of demographic processes across Europe. For a detailed examination of East-central Europe, we applied local statistics, and revealed three transnational spatial clusters resulting from historical and socio-economic processes. |
Databáze: | OpenAIRE |
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