The Use of Multivariate Techniques for the Unemployment Analysis

Elena Bugudui ()

Academic Journal of Economic Studies, 2016, vol. 2, issue 2, 134-146

Abstract: The present paper includes the results of an analysis of different aspects which influence the unemployment evolution in Romania; the analysis was conducted using exploratory multidimensional techniques such as Principal Component Analysis, Factor Analysis and Cluster Analysis. The present research aims to extend the comprehension of the labor market state, offering a formula which reflects the unemployment multidimensionality, the simultaneous action of more factors and establish a framework for the evaluation of the labor market conditions. There are presented different typologies of unemployment, extracted according to the level of education, the unemployment duration and gender for the period 1996- 2014 for four age groups. The analysis highlights the specific behavior of the young generation and also of the generation over 50 years.

Keywords: Unemployment; principal component analysis; factor analysis; cluster analysis; multivariate analysis (search for similar items in EconPapers)
JEL-codes: C33 C54 J21 J70 (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:khe:scajes:v:2:y:2016:i:2:p:134-146

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