{"title":"斯洛伐克共和国最高工资雇员的性别工资差距因素","authors":"V. Pacáková, V. Labudová, Ľ. Sipková","doi":"10.15240/tul/001/2022-4-002","DOIUrl":null,"url":null,"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).","PeriodicalId":46351,"journal":{"name":"E & M Ekonomie a Management","volume":"108 1","pages":""},"PeriodicalIF":1.4000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"FACTORS OF GENDER PAY GAP IN THE HIGHEST WAGES OF EMPLOYEES IN THE SLOVAK REPUBLIC\",\"authors\":\"V. Pacáková, V. Labudová, Ľ. Sipková\",\"doi\":\"10.15240/tul/001/2022-4-002\",\"DOIUrl\":null,\"url\":null,\"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. 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引用次数: 0
摘要
这篇文章包含了对斯洛伐克共和国2020年工资最高的1%员工的数据进行实证分析的结果。分析的起点是11,570个匿名的个人平均月毛工资值,以及工资超过抽样调查的第99百分位的员工的个人数据。劳动成本信息系统自1992年以来由Trexima Bratislava公司在斯洛伐克共和国实施。本文的目的是评估收入最高的男性和女性的性别薪酬差距,并评估造成这种差距的选定因素的影响的重要性。鉴于数据的可用性,监测的性别工资差距因素有教育程度、居住地区、职业类型和雇员的分类年龄。为了实现这一目标,选择了定量方法,即描述性统计和统计推断方法,如拟合优度检验、独立性的卡方检验和机器学习方法,如归一化香农熵和回归决策树模型。这些方法的分析结果最好以图形形式表示。基于上述方法的应用,最高工资(超过样本的第99百分位)的显著性别工资差异和监测因素的显著影响已经得到证实,不仅对性别工资差距,而且对其就业结构。分析的结果得出的结论是,在最高工资水平上,男女之间的显著工资差异恰恰是由于男女在监测因素的不同层次上的代表性不平等造成的。将获得的结果与基于2010年数据的类似分析结果进行部分比较(Pacáková et al., 2012)。
FACTORS OF GENDER PAY GAP IN THE HIGHEST WAGES OF EMPLOYEES IN THE SLOVAK REPUBLIC
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).