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Sociológia (Sociology)
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2013
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vol. 45
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issue 5
435 – 469
EN
This article presents an analysis of the Czech presidential elections from the spatial analysis perspective in 2013. The main method applied for classifying the electoral results were spatial autocorrelation and spatial regression which play an important role in spatial statistics and spatial econometrics. First, the regionalisation of the presidential vote is measured to identify the specific regional clusters of votes; the global test (a Moran’s I statistic), and also local indicators of spatial association (a LISA statistic) are used. Secondly, the spatial regression is used to identify the key underlying factors explaining the spatial variation of the electoral results. The analysis proves an independent effect in the case of Morava macro-region for the territorial differences in voting decisions in the presidential elections, in contrast to the Czech parliamentary elections. On the other hand, in the case of the second analysed macro-region (formerly German-inhabited Sudetenland) no such independent effect is evident. Finally, after controlling for the impact of the spatial regimes, the independent effect of non-spatial indicators is analysed. The findings suggest that other factors, with independent effects to the electoral results, was largely easily interpretable. Their effect was largely similar to the impact of these indicators, which previous studies reported in the parliamentary elections, reflecting not only support of the strongest Czech political parties, but also, to a certain extent, the current form of the Czech party system cleavage structures.
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