2014
DOI: 10.2478/cer-2014-0041
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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 sp… Show more

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Cited by 8 publications
(5 citation statements)
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References 14 publications
(14 reference statements)
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“…The usage of static areas in investigations of geographical distributions is common in studies based on typologies of areas. In the domain of the EU, the use of Nomenclature of Territorial Units for Statistics (NUTS) or local administrative units (LAUs) is the standardized way to understand social geography (European Commission, 2007;Pietrzak et al, 2014). The reason the EU decided to implement standardized units of space was to make cross-country analysis more homogenous by securing similar population sizes within each area unit.…”
Section: Figure 1: Nuts-levelmentioning
confidence: 99%
“…The usage of static areas in investigations of geographical distributions is common in studies based on typologies of areas. In the domain of the EU, the use of Nomenclature of Territorial Units for Statistics (NUTS) or local administrative units (LAUs) is the standardized way to understand social geography (European Commission, 2007;Pietrzak et al, 2014). The reason the EU decided to implement standardized units of space was to make cross-country analysis more homogenous by securing similar population sizes within each area unit.…”
Section: Figure 1: Nuts-levelmentioning
confidence: 99%
“…Therefore, for irregular lattice, higher order windows are required, and cell classification becomes more complex. Pietrzak et al (2014) developed a simple method to estimate local spatial dependency for cells with variable size (Polish NUTS regions), by applying JCS to contiguity matrices (or k-nearest neighbour matrix) detemined for each region. The advantage of this method over Boots' method is that it does not rely on a regular moving window and it is less computationally demanding (for large areas).…”
Section: Local Indicators For Categorical Datamentioning
confidence: 99%
“…2010Pietrzak i in. 2014a;2014b]. Rozkład przestrzenny wartości zmiennej niemetrycznej może być losowy bądź wykazywać tendencję do przestrzennego grupowania się.…”
Section: Istota Testu Join-countunclassified
“…metodę trzech średnich, metodę trzech median oraz metodę opartą na średniej arytmetycznej i odchyleniu standardowym zob. [Nowak 1999]). Wyniki zaprezentowano na rys.…”
Section: Identyfikacja Zależności Przestrzennych W Analizie Poziomu R...unclassified