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Research On The Distribution Change And Its Reasons Decomposition Of The Gender Wages Gap In China's Urban Residents

Posted on:2013-02-06Degree:MasterType:Thesis
Country:ChinaCandidate:J LinFull Text:PDF
GTID:2219330374963085Subject:Statistics
Abstract/Summary:PDF Full Text Request
The gender income differences have a long history and exist commonly invarious countries. With opening-up and reform policy in China, the state change tomarket-oriented economy and Wages are determined by the market which results tothe problem of wage disparities in different income level. The gender wage gap alsobegins to highlight and arouses many scholars and public concern. Using CHNS datain1993,2000and2009, this paper researchs on the distribution changes and itsreasons decomposition in China's urban residents. This paper firstly apply descriptivestatistics and nonparametric estimation methods to observe the overall genderdifferential changes situation in China and to get an initial understanding whetherthere exists the glass ceiling effect or the sticky floor effects in three years. Nextauthor uses quantile regression method to analyze coefficients differential of theinfluential factors in the male and female wage equations. Lastly through applicationof the Neumark, Melly(2005) and JMP1991decomposition method, author studiesthe characteristic of changes and reasons in China's urban residents in three yearsfrom both view of horizontal and vertical contrast. The main results show that thegender wage gap in urban China reduce from1993to2000and expand from2000to2009. The gap blank between female and male cumulative distribution enlargeobviously from low distribution point to0.60in2009. There is a stick floor effect inurban in three years, while a glass ceiling effect exists in1993and exists in the0.90to reference point0.70in2000and2009. In2009the gender wage gap is almostunexplained and is almost caused by gender discrimination, and60.5%is the directdiscrimination to female. In the unexplained part of gender wage gap, the experienceand collective covariates makes larger contribution in1993, and the blue-collar in2000, the private and white-collar in2009. Coefficient differences across thedistribution change as same as total differences in there years, that is, the lower wagelevels, the greater gender wage gap, and the larger unexplained gender wage gap.
Keywords/Search Tags:Gender wage gap, Glass ceiling effect, Quantile regression, JMP1991decomposition
PDF Full Text Request
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