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A quantile regression analysis of the conditional female wage distribution in post-apartheid South Africa
Includes bibliographical references.
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| Main Author: | |
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| Other Authors: | |
| Format: | Thesis |
| Language: | English |
| Published: |
School of Economics
2015
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| _version_ | 1867613328675700737 |
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| access_status_str | Open Access |
| author | Khan, Safia |
| author2 | Leibbrandt, Murray |
| author_browse | Khan, Safia Leibbrandt, Murray |
| author_facet | Leibbrandt, Murray Khan, Safia |
| author_sort | Khan, Safia |
| collection | Thesis |
| description | Includes bibliographical references. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/13121 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:34:23.309Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2015 |
| publishDateRange | 2015 |
| publishDateSort | 2015 |
| publisher | School of Economics |
| publisherStr | School of Economics |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/13121 A quantile regression analysis of the conditional female wage distribution in post-apartheid South Africa Khan, Safia Leibbrandt, Murray Economics Includes bibliographical references. The democratisation of South Africa in 1994 brought about increased economic opportunity for labour market participants. The impact of democratisation on the labour market outcomes of both males and females of various races has been studied extensively in terms of mean earnings. However, because of the heterogenous distribution of South African labour force participants, a mean analysis is not sufficient. This paper investigates changes in the post-Apartheid conditional earnings distribution of women in South Africa of all races using conditional quantile regression analysis. Women are exclusively analysed because the labour market choices and constraints they face are unique. A two part model is estimated with the rest part correcting for sample selection into employment in a South African context. Then, quantile regression analysis is employed to parsimoniously describe the entire conditional wage distribution aiding the understanding of female labour force dynamics in South Africa. Individual data on the South African labour market from Statistics S.A is utilised for the analysis. White women are found to earn more than black and coloured women at all quantiles of the wage distribution conditional on education, skills level and sector of employment. Inequality is found to be increasing among women in higher skilled occupations. Women in lower skilled occupations have witnessed an increase in real wages at all quantiles of the conditional wage distribution. 2015-06-26T11:20:13Z 2015-06-26T11:20:13Z 2014 Master Thesis Masters MCom http://hdl.handle.net/11427/13121 eng application/pdf School of Economics Faculty of Commerce University of Cape Town |
| spellingShingle | Economics Khan, Safia A quantile regression analysis of the conditional female wage distribution in post-apartheid South Africa |
| thesis_degree_str | Master's |
| title | A quantile regression analysis of the conditional female wage distribution in post-apartheid South Africa |
| title_full | A quantile regression analysis of the conditional female wage distribution in post-apartheid South Africa |
| title_fullStr | A quantile regression analysis of the conditional female wage distribution in post-apartheid South Africa |
| title_full_unstemmed | A quantile regression analysis of the conditional female wage distribution in post-apartheid South Africa |
| title_short | A quantile regression analysis of the conditional female wage distribution in post-apartheid South Africa |
| title_sort | quantile regression analysis of the conditional female wage distribution in post apartheid south africa |
| topic | Economics |
| url | http://hdl.handle.net/11427/13121 |
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