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Exploratory analysis of selected indicators of the Czech Republic regional labour markets

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  • Bohumil Kába

    (Katedra statistiky, Provozně ekonomická fakulta, Česká zemědělská univerzita v Praze, Kamýcká 129, 165 21 Praha 6-Suchdol, Česká republika)

Abstract

This paper is focusing on the presentation of statistic exploratory procedures enabling the evaluation of the disparities in regional labour markets in the Czech Republic. Most of the data on labour markets are of multidimensional nature since both employment and unemployment can be described by a lot of various indicators offered by the Ministry of Labour and Social Affairs of the Czech Republic and by the Czech Statistical Office. An analysis of the data collected hence, has to employ multivariate statistical procedures. The choice of indicators in the study presented has been carried out such that it can represent the phenomena basically affecting the economic position of separate regions. The number of indicators analyzed has been limited by the level of applicability of the multivariate methods of statistical processing chosen. In order to reach the target of the paper the indicators of employment and unemployment have been applied to order the separate CR regions and to identify the regions outlying. To this end a composite indicator has been constructed by the so-called point method, one that is capable of aggregating the information supplied by all the separate indicators considered. The first section of the paper describes the way of construction of this aggregate indicator. In the next section then, some algorithms of the cluster analysis are introduced that have been employed to classify regional labour markets of the CR in more detail.

Suggested Citation

  • Bohumil Kába, 2011. "Exploratory analysis of selected indicators of the Czech Republic regional labour markets," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 59(4), pages 123-128.
  • Handle: RePEc:mup:actaun:actaun_2011059040123
    DOI: 10.11118/actaun201159040123
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    References listed on IDEAS

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    1. Antonio Mucherino & Petraq J. Papajorgji & Panos M. Pardalos, 2009. "Data Mining in Agriculture," Springer Optimization and Its Applications, Springer, number 978-0-387-88615-2, June.
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