TY - JOUR
T1 - Understanding demographic and economic patterns in sparsely populated areas
T2 - A global typology approach
AU - Karacsonyi, David
AU - Taylor, Andrew
N1 - Funding Information:
This work was supported by Australian Government, Research Training Program Scholarship. We would like to thank the two anonymous Referees for their comments, which greatly helped to improve the flow of our manuscript. We also thank Dr Sigurd Dyrting and Prof. Ferenc Probáld, emeritus professor at Eötvös Loránd University, Budapest, for helpful comments on an earlier draft of this paper.
Publisher Copyright:
© 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
PY - 2023
Y1 - 2023
N2 - Sparsely Populated Areas are perceived as regions with the least human impact but the greatest potential for change. For some decades, the human geography of sparsely populated areas has attracted studies seeking to explain and differentiate their economic and demographic polarization in comparison to respective national averages. Evaluation of the economic, demographic and social progression of these sparsely populated areas is however obfuscated by the absence of globally agreed definitions on the qualifying criteria and, concurrently, inconsistent nomenclature to identify such regions internationally. Therefore, the aim of this study is to demonstrate the capacity for a globally consistent typology to identify the economic and demographic patterns in common, but within very different environmental constraints and institutional frameworks. To do so we focus on first-tier subnational geographical units with extremely low population densities and apply multivariable typology to understand and differentiate the key demographic and economic issues for sparsely populated areas. Using multivariable typology we identify three types of demographic and economic patterns as ‘marginal’, ‘semi’ and ‘very remote’ sparsely populated areas. The results emphasize the diversity of circumstances among these areas as a result of their past economic and demographic trajectories, but also as functions of institutional and political constraints.
AB - Sparsely Populated Areas are perceived as regions with the least human impact but the greatest potential for change. For some decades, the human geography of sparsely populated areas has attracted studies seeking to explain and differentiate their economic and demographic polarization in comparison to respective national averages. Evaluation of the economic, demographic and social progression of these sparsely populated areas is however obfuscated by the absence of globally agreed definitions on the qualifying criteria and, concurrently, inconsistent nomenclature to identify such regions internationally. Therefore, the aim of this study is to demonstrate the capacity for a globally consistent typology to identify the economic and demographic patterns in common, but within very different environmental constraints and institutional frameworks. To do so we focus on first-tier subnational geographical units with extremely low population densities and apply multivariable typology to understand and differentiate the key demographic and economic issues for sparsely populated areas. Using multivariable typology we identify three types of demographic and economic patterns as ‘marginal’, ‘semi’ and ‘very remote’ sparsely populated areas. The results emphasize the diversity of circumstances among these areas as a result of their past economic and demographic trajectories, but also as functions of institutional and political constraints.
KW - cluster analysis
KW - factor analysis
KW - quantitative typology
KW - regional development
KW - regional geography
KW - Sparsely populated areas
UR - http://www.scopus.com/inward/record.url?scp=85134731267&partnerID=8YFLogxK
U2 - 10.1080/04353684.2022.2103445
DO - 10.1080/04353684.2022.2103445
M3 - Article
AN - SCOPUS:85134731267
SN - 0435-3684
VL - 105
SP - 228
EP - 247
JO - Geografiska Annaler: Series B, Human Geography
JF - Geografiska Annaler: Series B, Human Geography
IS - 3
ER -