The article offers the results of statistical analysis of data on the highest wages of employees in the Slovak Republic in 2020. Descriptive analysis of sample data is supplemented by generalizing the results to the population of all employees whose salary exceeds the 99th percentile of the sample, by selected methods of statistical inference, which are probability models of the highest wages and analysis of variance. The analysis focuses on assessing the significance of the impact of selected demographic and social factors on the highest salaries of employees in SR in 2020 and their differences. The investigated factors there are gender, level of education, region of residence, the label of occupation, and age category. The article also focuses on inequalities in the number of employees at different levels of the monitored factors. The obtained results of the analysis are compared with the results of similar analysis from 2010.
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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