scholarly journals ANALYSIS OF GENDER WAGE DIFFERENTIAL IN CHINA’S URBAN LABOR MARKET

2017 ◽  
Vol 62 (02) ◽  
pp. 423-445 ◽  
Author(s):  
ALMAS HESHMATI ◽  
BIWEI SU

This paper estimates the gender wage gap and its composition in China’s urban labor market. The traditional Blinder–Oaxaca (1973) decomposition method with different weighing systems is employed. To correct for potential selection bias caused by women’s labor force participation, we employ the Heckman’s two-step procedure to estimate the female wage function. A large proportion of the gender wage gap is unexplained by differences of productive characteristics of individuals. Even though women have higher level of education attainments on average, they receive lower wages than men. Both facts suggest a potential discrimination against women in China.

2020 ◽  
Vol 20 (2) ◽  
pp. 79-96
Author(s):  
Muhammad Umair ◽  
Lubna Naz

Urban-urban migration has socio-economic and demographic consequences on the labor markets. It affects job mobility and gender-balance in the urban workplace. This study analyzes the gender wage gap among urban-urban migrant workers in Pakistan. The study used the most recent Labour Force Survey, a nationally representative dataset, to identify the determinants of wages for male and female migrant workers separately. The wages of urban-urban female migrants tend to be 45% lower than their male counterparts. The results indicated disparities in working hours and human capital endowment as some of the contributing factors to the increasing gender wage gap. This research calls for implementing drastic measures, i.e., gender-insensitive capacity building of urban migrant workers, workplace incentives for women, and enhancement of women leadership roles, to reduce gender inequalities in the urban labor market.  


2018 ◽  
Vol 10 (1) ◽  
pp. 36
Author(s):  
Muhammad Shahadat Hossain Siddiquee ◽  
Md Amzad Hossain

Using the Labor Force Survey 2010 dataset this paper examines gender wage gap in a large sample of urban workers in Bangladesh and explore whether gender wage gap varies across the wage distribution. Mincerian OLS regression and its Blinder-Oaxaca decomposition results reveal that the estimated wage gap between men and women workers is 21.2%. Adjusting women’s endowments levels to those of men increases women’s wage by 12.1% and a gap of 8.0% remains unexplained. The decomposition results based on the unconditional quantile regressions demonstrate that the estimated total gender wage gap is higher at lower end of the wage distribution compared to the higher end.


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