An analysis of the relationship between health and the labour market in South Africa

 

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dc.contributor.advisor Woolard, Ingrid en_ZA
dc.contributor.advisor Piraino, Patrizio en_ZA
dc.contributor.author Nwosu, Chijioke Osinachi en_ZA
dc.date.accessioned 2015-12-08T11:44:09Z
dc.date.available 2015-12-08T11:44:09Z
dc.date.issued 2015 en_ZA
dc.identifier.citation Nwosu, C. 2015. An analysis of the relationship between health and the labour market in South Africa. University of Cape Town. en_ZA
dc.identifier.uri http://hdl.handle.net/11427/15695
dc.description.abstract The relationship between health and labour market outcomes is of academic and policy interest due to the essential role the labour market plays in engendering economic growth. It is in this regard that this thesis is both timely and essential especially in light of scant literature on the health-labour market relationship in South Africa. South Africa presents an interesting case for a study of this nature as it had experienced high disease burden and mortality, coupled with declining labour force participation in the period prior to this study. Furthermore, the relationship between health and labour market earnings as well as impairment-related wage discrimination is not well-known in South Africa. Therefore, this thesis sought to establish the relationship between health on the one hand, and labour force participation, wage determination and wage discrimination on the other, in South Africa. Data was obtained from the first and third waves of the National Income Dynamics Study (collected in 2008 and 2012 respectively), a rich and nationally representative survey dataset of South African households. Descriptive analysis and different econometric techniques like instrumental variables, censored quantile regression and Blinder-Oaxaca decomposition were used for estimation. For the cross-sectional analysis, the study found significant impact of health on labour force participation of between 20% and 33% depending on the measure, while longer term relationships indicated statistically significant association (up to 11% for females and 16% for males). These figures indicate that the relationship between health and labour force participation was not just temporary. Males had higher labour force participation probability than females. Furthermore, grant receipt was associated with reduced labour force participation probability while education and age were associated with increased labour force participation. Also, marriage/cohabitation was negatively (positively) associated with female (male) labour force participation. In addition, labour force participation probability was generally higher in other areas relative to traditional authority locations. These results conform to a priori expectations. On the relationship (or gradient) between health and wages, the study established positive and statistically significant gradients between better physical, psychological and general health on the one hand, and wages on the other, among Africans and coloureds. This was even after controlling for education and other important wage determinants like occupational category, industry, union membership and gender. These gradients ranged from an elasticity of -0.06 to -0.07 for psychological health/depression to an elasticity of 0.31-0.45 for physical health (proxied by body mass index) in the short term. Also, persistently adverse general health and psychological conditions exhibited steep gradients. Finally, the study found evidence of non-trivial impairment-related differences in returns to wage-determining characteristics (loosely termed wage discrimination) in both 2008 and 2012 for the average wage, while the proportion of estimated wage gaps contributed by impairment-related differences in returns increased over time. Similar findings were obtained across the wage distribution, as the proportion of total estimated wage gaps accounted for by returns to characteristics increased across waves in virtually all deciles of the wage distribution. Even in terms of magnitude, the returns/discrimination component of total estimated impairment-related wage gaps increased for most quantiles of the wage distribution. Finally, education and occupational class contributed the most to the explained wage gap across waves. en_ZA
dc.language.iso eng en_ZA
dc.subject.other Economics en_ZA
dc.title An analysis of the relationship between health and the labour market in South Africa en_ZA
dc.type Thesis / Dissertation en_ZA
uct.type.publication Research en_ZA
uct.type.resource Thesis en_ZA
dc.publisher.institution University of Cape Town
dc.publisher.faculty Faculty of Commerce en_ZA
dc.publisher.department School of Economics en_ZA
dc.type.qualificationlevel Doctoral en_ZA
dc.type.qualificationname PhD en_ZA
uct.type.filetype Text
uct.type.filetype Image


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