• Journal of Technology Innovation
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• v.22 no.1
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• pp.89-117
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• 2014

Employing female in the field of science and engineering is becoming increasingly important with diversity and creativity emerging as key factors to build Creative Economy. Under these circumstances, it is necessary to recognize and discourage gender discrimination in the labor market by analyzing wages - the market value of labor which determines one's economic status. This study uses the Oaxaca-Ransom decomposition (1994) to analyze the gender wage gap and identify factors influencing the pay gap in science and engineering labor force. The results of this study are as follows: First, the average wage of female scientists and engineers reaches only 65% of that of male labor force, and the male scientist and engineers are superior in terms of personal attributes, for instance, education background. Second, looking at the factors that influence wages, wage premiums are associated with higher education background, older age, longer period of service, and weekly working hours for both male and female in managerial positions. Third, the wage decomposition shows that in the case of science and engineering labor force, the productivity difference by personal attributes reaches about 58%, and gender discrimination by the characteristics of the labor market stands at about 41%. This means the wage gap by productivity level in science and engineering labor force is wider, and the gender gap is smaller compared to non-science and engineering fields. However, the results of an analysis on specialties and education background of male and female scientists and engineers suggest that the discrimination against women is more serious when the percentage of the female labor force is low and the percentage of temporary workers in the labor market is high. In order to eliminate this discrimination, it is necessary to reduce the imbalance of female scientists and engineers in the labor market, among others, while female scientists and engineers, themselves, need to make continuous efforts to strengthen their capabilities.

• Journal of Labour Economics
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• v.30 no.2
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• pp.1-31
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• 2007

The purpose of this paper is to analyse wage differentials between non-regular and regular works. Data from EAPS(Economically Active Population Survey) 2005 show that the monthly wage level of non-regular worker is only 63% of regular worker and thus there exist 37% wage differentials. However, these wage differentials do not control for hours of work, the amount of human capital, job characteristics, and other individual characteristics affecting wages. If these variables are added to the hourly wage regression equation, the wage gap between non-regular and regular workers drastically decreases to 2.2%. Furthermore, decomposition of the wage differentials by Oaxaca method shows that productivity difference between non-regular and regular workers explains up to 91% of the wage gap. This implies that the magnitude of wage discrimination against non-regular workers is at most 0.2% of hourly wage of regular workers. To control for unobserved individual heterogeneities more accurately, we also construct panel data and estimate wage differentials. The results from the panel data approach show that there is no difference in the hourly wages between non-regular and regular workers. In some specifications, the wage rate of non-regular worker is rather higher than that of regular worker. These results are consistent with economic theory. Other things being equal, workers with unstable employment may require higher wages to compensate their unstability. Firms are willing to pay higher wages if they can get more flexibility from non-regular employment. Empirical results in this paper cast doubt on the view that there is wage discrimination against non-regular workers in the labor market. Public policies should be targeted for disadvantaged groups among non-regular workers, not for non-regular workers in general.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.2
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• pp.231-238
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• 2019

This study aims is to analyze of existing concepts of gender stereotypes and gender differences in wages, defining of gender pay gap determinants, and to evaluate the level of discrimination against women in Kazakhstan. This paper begins by reviewing trends in gender stereotypes and gender segregation during the past several decades. In this research, authors propose the methodological tools for presenting a standard form of evaluation of gender pay gap. The developed methodological tools will allow providing authentic and formal analysis on gender pay gap and identifying the main determinants of gender pay differences. Further, the obtained results showed the distribution of wage gap in Kazakhstan's regions and the Duncan's dissimilation index allows us to trace the dynamics of changes in the professional structure between men and women. According to the results, gender pay gap is narrowing with the reduction of the job level and discrimination is related to differences in human capital and education. Wages in the industrial sector are higher for men than for women, because men's professions are characterized by severe and unhealthy working conditions. In addition, employers prefer male managers, but if they take woman managers, they give them salary 3 times less.

• Review of Culture and Economy
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• v.21 no.2
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• pp.3-28
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• 2018

This study focuses on analyzing the glass ceiling effect in arts and culture professionals through the quintile decomposition applied to the RIF unconditional quantile regression and Oaxaca-Blinder decomposition technique. From the industrial viewpoint, we divide arts and culture professionals into cultural contents professionals(large category J industry) and arts professionals(large category R industry). For our analysis, we employ the pooling data of 'Wage Structure Survey' from 2009 to 2016. Our results are summarized as follows. First, as OLS wage decomposition showed that the gender wage gap among the arts professionals was lower than cultural contents professionals, but the discrimination portion of total gender wage gap was larger. Second, from quintile regression decompositions, the glass ceiling effects of two types of professionals showed different results. Cultural contents sector was observed with the "steady glass ceiling effect" as the portion of the discrimination was continuously increased, while the arts sector was observed with the "limited glass ceiling effect" as the discrimination had drastically increased in the 80s and 90s.

• Journal of the Society of Disaster Information
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• v.15 no.1
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• pp.143-152
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• 2019

Purpose : To analyze how the Fourth Industrial Revolution affects the gender gap. Method : This study regressed the relationship between ICT development index, network Readiness index and gender gap in 145 countries all over the world. Results : The ICT development index was not statistically significant, but the network readiness index was positively correlated with female labor participation rate and gender wage equality ratio, indicating that the progress of the $4^{th}$ industrial revolution increased female participation in labor but the wage gap has been shown to intensify. Conclusion : The results verify the hypothesis that the $4^{th}$ industrial revolution led by the information and communication revolution affects the labor market conditions of women.

• Journal of Labour Economics
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• v.43 no.3
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• pp.33-61
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• 2020

The purpose of this study is to analyze the disparity in on-the-job training between regular and non-regular workers and to compare the wage effects of on-the-job training. Using the Korean micro data from the Programme for the International Assessment of Adult Competencies(PIAAC) published by OECD, Propensity Score Method(PSM) is applied to overcome the endogeneity problem. The average treatment effect(ATT) on the training participation is analyzed, using non-regular workers as treatment group and regular workers as comparison group. Odds ratios of non-regular employees' training participation compared to regular employees shows 0.67 times after constructing matching sample and this means that non-regular workers are facing a disadvantageous training opportunity compared to regular workers. In order to estimate the wage effect of on-the-job training, the average treatment effect(ATT) of on-the-job training on average wages for regular workers and non-regular workers is estimated respectively. I find insignificant wage effect from on-the-job training among regular workers and significant positive effect on non-regular worker's wage from on-the-job training.

• Journal of Labour Economics
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• v.42 no.3
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• pp.39-74
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• 2019

In this paper, the wage equations of local labor markets for college graduates in Korea are estimated by Dahl(2002)'s methodology to correct for selection bias. The results suggest that the variations of coefficients in wage equations across the local labor markets are mostly remained after correcting for selection bias. The gender wage gap is hardly affected by selection bias. The variations of return to education and the major premium are reduced about 18% and 11% respectively. Meanwhile, the selection bias is negligible in the national capital region, which suggests that college graduates prefer the national capital region regardless of their gender, level of education, and major.

• Journal of Engineering Education Research
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• v.18 no.1
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• pp.20-30
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• 2015

The recent increase of wages is considered to be the result of lawsuits on ordinary wage expansion and the reduction of working hours. This may enlarge the wage gap between enterprise and small business, and thus worsen the insufficient supply of workforce to small businesses. Therefore, it is necessary to provide strategies to control the increase of wages in order to resolve the difficulty in the industrial workforce supply and to enforce the industrial competitiveness.

• 한국사회정책
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• v.25 no.4
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• pp.125-161
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• 2018

This article aims to investigate the impact of Korean employment protection legislation that has implemented since 2007 on eliminating discrimination on non-regular worker's wage and social security. It is used the panel Tobit model reflecting the variation of implementation time according to the size of establishments. Although the employment protection laws for non-regular workers have implemented, the wage gap and discrimination in social security for non-regular workers have continued. Of course, the discrepancies on wage and social security were founded not only between regular and non-regular workers but also within non-regular workers. For reducing the discriminations, this study proposes to restrict the reason for justifying discrimination, and the introduction of a new approach to accessing the discrimination and complimentary credit system. Besides, this study suggests to actively review the strengthening of regulations on the use of non-regular workers.

• Journal of Korea Port Economic Association
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• v.37 no.2
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• pp.133-152
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• 2021

The purpose of this study is to investigate the factors affecting the wages of workers in the logistics industry and to identify the current status of employment and wages in the logistics industry. Based on this, it sought to find analytical factors on the wages of workers in the logistics industry and explain their impact on the wage gap. The analysis data were interpreted as cross-sectional data from the National Statistical Office over the past decade and the analysis data were set to three types. The results of the analysis could be explained that three factors understood as wage discrimination factors that do not directly affect productivity generally have a significant impact on wage gap among workers in the logistics industry. Air and water transport industries received high salaries due to factors in the industry. The very low-paid sector for that was the land transport industry, and the courier industry as a detailed sector. Due to the nature of job factors, technicians and assistants received lower wages than other jobs. Due to the nature of the company's size factors, companies with 51 or more employees received higher wages than companies with 50 or less employees. In testing the effectiveness of multiple sources of ANOVA, the common 'industry × enterprise size' variable was explained to have a significant effect on gaps in wages for workers in the logistics industry. In addition, the comparison of the influence of the main effects of the three factors put into the analysis model shows that the industry has the most influence.