Modelling dependence indicators of labor market using advanced statistical methods

Abstract

Aim this paper is an analysis of disparities in the labor market in the Czech Republic. It is based on qualitative indicators. Unemployment is today increasingly perceived as a negative factor that affects the labor market and economy of the state. Due to the nature of the data, categorical data analysis and logistic regression was selected to reveal opportunities to change the role of unemployed persons to employed ones on the labor market. Cluster analysis on categorical data was used for division of regions into similar groups based on parameters affecting the market status of mentioned person in the labor market. Statistical calculations were performed in SPSS statistical software, version 18. The data from the Labor Force Survey was used for evaluation. Specifically, the fourth quarter of 2009, differentiated according to the NUTS 3 (regions of the Czech Republic). These factors were evaluated: age group, highest completed education, disability, participation in informal education, registration in employment office and family status. Based on the analysis we can conclude that the labor market in the CR is considerably regionally, educationally and physically structured. The workforce of individual does not always have the same weight for an employer. More likely to become unemployed, are people with lower education, disabled people and people who are divorced or widowed. Contrariwise, higher chances to be to employed have people who are registered in employment office and are further self-educating people.

Keywords

• labor market
• the regions of the Czech Republic
• categorical data
• cluster analysis
• logistic regression