Gender Wage Gap

2013 ◽  
Vol 4 (1) ◽  
pp. 53-67 ◽  
Author(s):  
Zuzana Machová ◽  
Lenka Filipová
Keyword(s):  
Gender Wage Gap ◽  
Wage Gap ◽  
Personal Characteristics ◽  
Probit Model ◽  
Wage Discrimination ◽  
Family Characteristics ◽  
Family Status ◽  
Men And Women ◽  
Wage Regression ◽  
And Gender

This paper was written as a part of a research project studying problem of wage determinant measuring and wage discrimination considering different wage requirements of men and women. The wage determinants and gender wage discrimination are analyzed using a probit model. The whole analysis is methodologically based on Mincer’s Wage Regression and Oaxaca-Blinder decomposition of gender wage gap. The wage variables include, aside from standard personal characteristics, dummies for institutional and firm characteristics and dummies for family status and family roles. The data were gained by a questionnaire survey carried out in Ostrava city. The results of the analysis, representative for the city, show statistically significant differences between wage determinants of men and women. The survey concluded in 2 statements: (1) family role is an important wage determinant and its inclusion to Mincer’s Wage Regression leads to better explanation of wages; and (2) including family characteristics in Oaxaca-Blinder decomposition can significantly reduce unexplained part of gender wage gap, i.e., a part of a wage difference usually ascribed to gender wage discrimination can be explained by different preferences of men and women on a labor market.

scholarly journals Wage Determination with Special Reference to Role in a Family

2011 ◽  
Vol 11 (1) ◽  
pp. 37-56 ◽  
Author(s):  
Lenka Filipová ◽  
Zuzana Machová
Keyword(s):  
Special Reference ◽  
Empirical Studies ◽  
Total Sample ◽  
Wage Discrimination ◽  
Family Characteristics ◽  
Wage Determination ◽  
Response Model ◽  
Men And Women ◽  
Wage Regression ◽  
Ordered Response

Wage Determination with Special Reference to Role in a Family The paper has arisen as a part of the project dealing with the questions of measuring of wage determinants and wage discrimination on the basis of different subjective requirements of women and men on their wages. Using the ordered-response model (Ordered Probit), it analysed wage determination on the basis of Mincer's Wage Regression including dummies for role in a family. The analysis was carried out with the total sample of respondents and subsequently separately for men and women. The data were gained from a questionnaire survey carried out in Ostrava city, Czech Republic. In general, the analysis did not prove previous conclusions of theories or empirical studies about prevailing influence of family characteristics on the wage rate. Nevertheless, it proved statistically significant differences in the wage determination between men and women, and showed that in the case of men, some family characteristics may have been important for determining the wages.

scholarly journals Occupational segregation and wage differences: the case of Poland

2018 ◽  
Vol 39 (3) ◽  
pp. 378-397 ◽  
Author(s):  
Pawel Strawinski ◽  
Aleksandra Majchrowska ◽  
Paulina Broniatowska
Keyword(s):  
Gender Wage Gap ◽  
Wage Gap ◽  
Occupational Segregation ◽  
Wage Discrimination ◽  
Similar Proportion ◽  
Wage Gaps ◽  
Wage Differences ◽  
Occupational Groups ◽  
Men And Women ◽  
Content Type

Purpose The purpose of this paper is to analyse the relation between occupational segregation and the gender wage differences using data on three-digit occupational level of classification. The authors examine whether a statistically significant relation between the share of men in employment and the size of the unexplained part of the gender wage gap exists. Design/methodology/approach Traditional Oaxaca (1973) – Blinder (1973) decomposition is performed to examine the differences in the gender wage gaps among minor occupational groups. Two types of reweighted decomposition – based on the parametric estimate of the propensity score and non-parametric proposition presented by Barsky et al. (2002) – are used as the robustness check. The analysis is based on individual data available from Poland. Findings The results indicate no strong relation between occupational segregation and the size of unexplained differences in wages. The unexplained wage differences are the smallest in strongly female-dominated and mixed occupations; the highest are observed in male-dominated occupations. However, they are probably to a large extent the result of other, difficult to include in the econometric model, factors rather than the effects of wage discrimination: differences in the psychophysical conditions of men and women, cultural background, tradition or habits. The failure to take them into account may result in over-interpreting the unexplained parts as gender discrimination. Research limitations/implications The highest accuracy of the estimated gender wage gap is obtained for the occupational groups with a similar proportion of men and women in employment. In other male- or female-dominated groups, the size of the estimated gender wage gaps depends on the estimation method used. Practical implications The results suggest that decreasing the degree of segregation of men and women in different occupations could reduce the wage differences between them, as the wage discrimination in gender balanced occupations is the smallest. Originality/value To the best of the authors’ knowledge, this study is one of the few conducted at such a disaggregated level of occupations, and one of few studies focused on Central and Eastern European countries and the first one for Poland.

Sociability Capital and Gender Wage Gap

2019 ◽  
Author(s):  
Herman Sahni ◽  
Suresh Lazarus Paul
Keyword(s):  
Gender Wage Gap ◽  
Wage Gap ◽  
And Gender

Gender wage gap decomposition methods: Comparative analysis

2021 ◽  
Vol 62 ◽  
pp. 5-31
Author(s):  
Sergey Roshchin ◽  
◽  
Natalya Yemelina ◽  
Keyword(s):  
Comparative Analysis ◽  
Gender Wage Gap ◽  
Wage Gap ◽  
Decomposition Methods ◽  
Influence Functions ◽  
Quantile Regressions ◽  
Men And Women ◽  
Distribution Parameters ◽  
Monitoring Survey ◽  
The Mean

This study introduces a comparative analysis of the gender wage gap decomposition methods with the Russian Longitudinal Monitoring Survey (RLMS) data for 2018. To decompose the differences in average wages, approaches based on the Oaxaca–Blinder decomposition are used. Apart from the mean wages, the study focuses on other distribution statistics. Using the quantile regressions, the wage gap between men and women is decomposed for the distribution parameters such as median, lower and upper deciles. The decomposition estimates of conditional and unconditional (based on recentered influence functions) quantile regressions are compared.

scholarly journals Organizational Work–Life Policies and the Gender Wage Gap in European Workplaces

2018 ◽  
Vol 46 (2) ◽  
pp. 111-148 ◽  
Author(s):  
Tanja Van der Lippe ◽  
Leonie Van Breeschoten ◽  
Margriet Van Hek
Keyword(s):  
Gender Inequality ◽  
Family Life ◽  
Gender Wage Gap ◽  
Parental Leave ◽  
Wage Gap ◽  
Work Life ◽  
Multilevel Analyses ◽  
Men And Women ◽  
Dependent Care ◽  
Organizational Work

Many organizations in Europe offer work–life policies to enable men and women to combine work with family life. The authors argue that the availability of organizational work–life policies can also reduce gender inequality in wages. The authors test their expectations using the European Sustainable Workforce Survey, with data from 259 organizations and their employees in 9 European countries. Multilevel analyses show that organizations that offer work–life policies have a smaller gender wage gap. Their findings also suggest that both the type and number of policies matter. Contrary to their expectations, dependent care policies, such as parental leave and childcare support, are less important for the gender wage gap than flexibility policies. Controlling for organizational culture regarding family supportiveness does not alter the results.

scholarly journals Psychological bias and gender wage gap

2010 ◽  
Vol 76 (3) ◽  
pp. 563-573 ◽  
Author(s):  
Frédéric Palomino ◽  
Eloïc-Anil Peyrache
Keyword(s):  
Gender Wage Gap ◽  
Wage Gap ◽  
And Gender ◽  
Psychological Bias

Interindustry Wage Differentials and the Gender Wage Gap

ILR Review ◽  
1995 ◽  
Vol 49 (1) ◽  
pp. 105-120 ◽  
Author(s):  
Judith Fields ◽  
Edward N. Wolff
Keyword(s):  
Population Survey ◽  
Wage Differentials ◽  
Gender Wage Gap ◽  
Wage Gap ◽  
Female Worker ◽  
Industry Effects ◽  
Men And Women ◽  
Female Workers ◽  
Highly Correlated ◽  
Using Data

Using data from the March 1988 Current Population Survey, the authors find that the wages of female workers differ significantly by industry, even when the analysis controls for workers' productivity-related characteristics. Although these interindustry wage differentials are at least as large as men's and are highly correlated with them as well, there are statistically significant differences between the two. Of the overall gender wage gap (the average female worker earns about 65% as much as the average male worker), 12–22% can be explained by differences between the patterns of interindustry wage differentials of men and women and 15–19% by differences in the distribution of male and female workers across industries. Thus, the combined industry effects explain about one-third of the overall gender wage gap.

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