The Application Of Local Indicators For Categorical Data (LICD) In The Spatial Analysis Of Economic Development

Abstract

The paper makes an attempt to apply local indicators for categorical data (LICD) in the spatial analysis of economic development. The first part discusses the tests which examine spatial autocorrelation for categorical data. The second part presents a two-stage empirical study covering 66 Polish NUTS 3 regions. Firstly, we identify classes of regions presenting different economic development levels using taxonomic methods of multivariate data analysis. Secondly, we apply a join-count test to examine spatial dependencies between regions. It examines the tendency to form the spatial clusters. The global test indicates general spatial interactions between regions, while local tests give detailed results separately for each region. The global test detects spatial clustering of economically poor regions but is statistically insignificant as regards well-developed regions. Thus, the local tests are also applied. They indicate the occurrence of five spatial clusters and three outliers in Poland. There are three clusters of wealth. Their development is based on a diffusion impact of regional economic centres. The areas of eastern and north western Poland include clusters of poverty. The first one is impeded by the presense of three indiviual growth centres, while the second one is out of range of diffusion influence of bigger agglomerations.

Keywords

• join-count test
• spatial dependence
• local indicators of spatial association (lisa)
• exploratory spatial data analysis (esda)
• economic development
• taxonomic analysis