Browsing by Author "Goga, Sumayya."

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Understanding the gender earnings gap in the post-apartheid South African labour market.
(2008) Goga, Sumayya.; Posel, Dorrit Ruth.
In this thesis, I analyse the gender earnings gap in South Africa using Labour Force Survey (LFS) data, for the period between 2001 and 2005. In addition to providing estimates of the gender earnings differential at the mean of the wage distribution (using a pooled regression), I also provide quantile regression estimates to account for the gap at different points of the distribution. To further explore reasons for the gender earnings gap, I separate the male and female earnings equations and employ a decomposition technique. This allows me to determine the proportion of the gap that is not explained by differences in observable characteristics between men and women. The 'unexplained' part of the earnings gap is suggestive of gender discrimination in the labour market. Using Ordinary Least Squares (OLS) the pooled regression (controlling for sample selection), indicates an increase in the gender pay gap between 2001 and 2005. In turn, the quantile regression estimates for the period also illustrate a widening gender earnings differential throughout the distribution, except at the mean. By contrast, the descriptive statistics and the separated male and female earnings estimations show a decrease in the earnings gap over the period. Given that the pooled regression assumes the same returns to observable characteristics for males and females, which I reject through the use of a Chow test, the results from the separated estimations hold more weight. The Oaxaca (1973) decomposition on the separated male and female earnings estimations illustrates that the 'unexplained' component of the gap accounts for a greater proportion of the gap than the 'explained' component in both years. Furthermore, the 'unexplained' proportion of the gap increased in the period, while the 'explained' proportion decreased. Thus, if the 'unexplained' part of the gap is considered to be a measure of discrimination, then the data indicates an increase in discrimination in earnings between the sexes over the period 2001 to 2005, even though there was a narrowing of the gender earnings differential.