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Women in EU as Seen by Dynamic Principal Component Analysis (PCA)

Markowska, Małgorzata; Sokołowski, Andrzej; Rygiel, Agnieszka

Abstract:
The socio-economic activity of women in 28 European Union in 2000-2015 countries has been studied in this paper. Six variables covering the female labour market, educational and political activity, and researchers’ careers have been used. They were subject to Principal Component Analysis (PCA) in two versions. One – separately for each year, and the other – jointly for the whole period. The first one was used to identify and track the positions of variables in three-component, time dependent space. Principal components were explained and some changes in loadings were discussed. For the analysis of 28 European Union countries we study their trajectories defined by factor values. The countries were clustered by Ward’s agglomerative method. Four groups have been found. Two of them were easy to interpret – consisting generally of countries from the old and new European Union respectively. Linear trends were estimated for the movement of four groups in PC space. Then, differences between groups have been explained by the analysis of group trends of the original variables.

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Verlagsausgabe §
DOI: 10.5445/KSP/1000085951/18
Veröffentlicht am 30.04.2020
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Informationswirtschaft und Marketing (IISM)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2018
Sprache Englisch
Identifikator ISSN: 2363-9881
KITopen-ID: 1000118864
Erschienen in Archives of Data Science, Series A (Online First)
Band 4
Heft 1
Seiten A18, 18 S. online
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