FACTORS OF GENDER PAY GAP IN THE HIGHEST WAGES OF EMPLOYEES IN THE SLOVAK REPUBLIC
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Technická Univerzita v Liberci
Technical university of Liberec, Czech Republic
Technical university of Liberec, Czech Republic
Abstract
The article contains the results of empirical analysis of data on one percent of employees with the highest salaries in the Slovak Republic in 2020. The starting point for the analysis there is 11,570 anonymized individual values of average gross monthly wage and also personal data of the employees whose wage exceeded the 99th percentile of the sample survey The Informational System on Labour Costs, implemented in the Slovak Republic since 1992 by the company Trexima Bratislava. The aim of the article is to assess the gender pay gap for the best-earning men and women and assess the significance of the impact of selected factors that contribute it. Given the availability of data the monitored factors of the gender pay gap there are education, region of residence, the type of occupation, and the categorized age of employees. To achieve the objective, selected quantitative methods were used, namely methods of descriptive statistics and statistical inference, as goodness-of-fit tests, chi-squared tests of independence and machine learning methods, as normalized Shannon entropy and regression decision tree models. The results of analyses by these methods have been preferably presented in a graphical form. Based on the application of the above methods the significant wage differences by gender at the highest wages (over the 99th percentile of the sample) and significant impact of monitored factors has been confirmed not only on the gender pay gap, but also on the structure of their employment. The results of the analyses lead to the conclusion that the significant wage differences by gender at the highest wages are caused precisely by unequal representation of men and women on the different levels of the monitored factors. The obtained results are partially compared with the results of a similar analysis based on data from 2010 (Pacáková et al., 2012).
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Subject(s)
comparisons, gender pay gap, factors, highest wages, chi-squared tests, regression tree
Citation
ISSN
1212-3609