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The Use of Multivariate Techniques for the Unemployment Analysis

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  • Elena Bugudui

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.

Suggested Citation

  • Elena Bugudui, 2016. "The Use of Multivariate Techniques for the Unemployment Analysis," Academic Journal of Economic Studies, Faculty of Finance, Banking and Accountancy Bucharest,"Dimitrie Cantemir" Christian University Bucharest, vol. 2(2), pages 134-146, June.
    • Handle: RePEc:khe:scajes:v:2:y:2016:i:2:p:134-146
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    References listed on IDEAS

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    More about this item

    Keywords

    Unemployment; principal component analysis; factor analysis; cluster analysis; multivariate analysis;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling
    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • J70 - Labor and Demographic Economics - - Labor Discrimination - - - General

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