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The application of local indicators for categorical data (LICD) in the spatial analysis of economic development

Author

Listed:
  • Michal Bernard Pietrzak

    (Nicolaus Copernicus University, Poland)

  • Justyna Wilk

    (Wroclaw University of Economics, Poland)

  • Tomasz Kossowski

    (Adam Mickiewicz University in Poznan, Poland)

  • Roger Bivand

    (Norwegian School of Economics (NHH) in Bergen, Norway)

Abstract

The objective of this paper is to identify classes of regions presenting different economic situations and apply a join-count test to examine spatial dependences between these classes. The test examines spatial autocorrelation on the basis of qualitative data. The global join-count test indicates general interactions occurring between regions, while the local join-count test examines a tendency to form the spatial clusters (e.g. metropolitan areas). The study covers the situations of 66 Polish NUTS 3 regions in 2011. Regions were divided into two classes presenting relatively low and high levels of economic development. Taxonomic methods of multivariate data analysis were applied in the research. The global test proved spatial clustering of economically poor regions but was statistically insignificant as regards well-developed regions. Thus the join-count local join-count test was additionally applied. The test indicated the occurrence of five spatial clusters of NUTS 3 regions. Three of them include economically well-developed regions, while two of them present poor economic situations. Furthermore three spatial outliers (local growth centres), which deteriorate the economic situation of eastern Poland, were also recognized.

Suggested Citation

  • Michal Bernard Pietrzak & Justyna Wilk & Tomasz Kossowski & Roger Bivand, 2014. "The application of local indicators for categorical data (LICD) in the spatial analysis of economic development," Working Papers 14/2014, Institute of Economic Research, revised Sep 2014.
    • Handle: RePEc:pes:wpaper:2014:no14
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    References listed on IDEAS

    as
    1. Barry Boots, 2003. "Developing local measures of spatial association for categorical data," Journal of Geographical Systems, Springer, vol. 5(2), pages 139-160, August.
    2. Michal Bernard Pietrzak & Justyna Wilk & Tomasz Kossowski & Roger Bivand, 2013. "The identification of spatial dependence in the analysis of regional economic development – join-count test application, IER Working Papers, 2013, No. 30," Working Papers 30/2013, Institute of Economic Research, revised Jul 2013.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    join-count test; spatial dependence; local indicators of spatial association (LISA); explorative spatial data analysis (ESDA); economic development;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • J64 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment: Models, Duration, Incidence, and Job Search
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes

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