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Dynamics of rural areas: an assessment of clusters of employment in Sweden

Journal of Rural Studies
Publication Date
DOI: 10.1016/s0743-0167(01)00028-6
  • Design
  • Economics
  • Education


Abstract There are numerous examples in the empirically based literature, which argue in favour of the importance of firms’ agglomeration in space as a way of creating and sustaining economic competitive advantages. One way to identify the degree of agglomeration of economic activity is through identification of the trends in clustering patterns relating to employment. The objective of this paper is thus to investigate patterns of clustering in both traditional and modern branches of the economy for two Swedish rural study regions (two leading areas and two lagging ones), assessing their location in relation to national economic dynamics. Standardised Employment Rates (SERs) are calculated and mapped using Geographic Information Systems (GIS) for thirty-seven economic branches. The Getis–Ord statistic is used to identify clusters of employment. The findings show that the study areas are to different degrees included in most of the clusters of the traditional branches, but not in a uniform way. Well performing areas often tend to be included in clusters composed of traditional private businesses, whilst lagging areas tend to be part of clusters in which the public sector is responsible for employment, this is particularly so in the sparsely populated areas of North Sweden. Most of the robust clusters relating to the modern branches of the economy are concentrated in the larger urban areas of Sweden, though in some cases, also in other larger regional urban centres. The most surprising result was perhaps that clusters of employment within such modern branches are relatively over-represented in certain parts of some lagging areas, a fact that may reflect the effects of regional policy measures on the decentralisation of R&D and post secondary education. Maps showing SERs and patterns of employment using clustering analysis often reflect the boundaries of functional regions, the degree of economic specialisation, and the dynamism of a region in a national context, all of which suggests that such a methodology can be utilised in the new toolbox designed to help aid the process of regional policy programme evaluations.

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