Identification of Employment Concentration Areas

Abstract

This article presents a method to identify “Absolute and Relative Employment Concentration (AREC) areas” for a particular industry. Two novel characteristics of the method are that it simultaneously analyses AREC, and that it combines spatial concentration per area with the spatial concentration in neighbouring areas. The method is easy to understand and apply. It is developed to assist regional policy makers and corporate decision-makers with their investment decisions related to new infrastructure or plants. The identification of concentration areas also allows for analysing the performance of these areas in relation to characteristics such as infrastructure availability and the housing and labour market. This can yield new academic insights that are relevant for regional planners. An application of the newly developed method to five industries in a Dutch province subdivided into 502 areas illustrates the value of the method in comparison to other methods.

Acknowledgements

The authors are grateful to the Provincie Noord-Brabant for financial support, provision of data and helpful discussions.

Notes

1. Since this average is highly influenced by the number of areas in which the industry's firms are located, this average has to be calculated only based on the areas in which there actually is employment in the industry, which makes the method less dependent on the size of the industry and the number of areas defined.

2. The Nomenclature of Territorial Units for Statistics (NUTS) was established by Eurostat in order to provide a single uniform breakdown of territorial units for the production of regional statistics for the European Union. NUTS 2 regions are identified as basic regions for the application of regional policies (Eurostat, 2011).

3. An LQ equal to 2 means that the share of industry employment is twice as large as the share of total employment in that particular area; all areas that are that specialized in a particular industry should be taken into account in the analysis.

4. It does not make sense to combine neighbouring areas if only one variable is used. Especially in the case of only using an absolute cut-off value, this would mean that all areas are combined into one area, since combining areas always results in more absolute employment. In the case of only using a relative cut-off value, combining neighbouring areas could in principle be done. However, also in this case combining neighbouring areas does not give additional value. If only the LQ is used as cut-off value, one area with only some employment and (almost) all of this employment in industry i (“the shepherd in the desert”), can be combined with almost all neighbouring areas, since its LQ is that large that it will compensate for almost all low LQ values.