Labour market returns to educational attainment, school quality, and numeracy in South Africa

Van Broekhuizen, Hendrik (2011-12)

Thesis (MComm)--Stellenbosch University, 2011.

Thesis

ENGLISH ABSTRACT: This study investigates the extent to which educational attainment, school quality and numeric competency influence individuals’ employment and earnings prospects in the South African labour market using data from the 2008 National Income Dynamics Study (NIDS). While NIDS is one of the first datasets to contain concurrent information on individual labour market outcomes, educational attainment levels, numeric proficiency and the quality of schooling received in South Africa, it is also characterised by limited and selective response patterns on its school quality and numeracy measures. To account for any estimation biases that arise from the selective observation of these variables or from endogenous selection into labour force participation and employment, the labour market returns to human capital are estimated using the Heckman Maximum Likelihood (ML) approach. The Heckman ML estimates are then compared to Ordinary Least Squares (OLS) estimates obtained using various sub-samples and model specifications in order to distinguish between the effects that model specification, estimation sample, and estimation procedure have on estimates of the labour market returns to human capital in South Africa. The findings from the multivariate analysis suggest that labour market returns to educational attainment in South Africa are largely negligible prior to tertiary levels of attainment and that racial differentials in school quality may explain a significant component of the observed racial differentials in South African labour market earnings. Neither numeracy nor school quality appears to influence labour market outcomes or the convex structure of the labour market returns to educational attainment in South Africa significantly once sociodemographic factors and other human capital endowment differentials have been taken into account. Though the regression results vary substantially across model specifications and estimation samples, they are largely unaffected by attempts to correct for instances of endogenous selection using the Heckman ML procedure. These findings suggest that the scope for overcoming data deficiencies by using standard parametric estimation techniques may be limited when the extent of those deficiencies are severe and that some form of sensitivity analysis is warranted whenever data imperfections threaten to undermine the robustness of one’s results.

AFRIKAANSE OPSOMMING: Hierdie studie ondersoek in watter mate opvoedingspeil, skoolgehalte en numeriese vaardighede individue se werks- en verdienstevooruitsigte in die Suid-Afrikaanse arbeidsmark beïnvloed. Die studie gebruik data van die 2008 National Income Dynamics Study (NIDS). Alhoewel NIDS een van die eerste datastelle is wat inligting oor individuele arbeidsmarkuitkomste, opvoedingsvlakke, numeriese vaardighede sowel as skoolgehalte bevat, word dit ook gekenmerk deur beperkte en selektiewe responspatrone rakende skoolgehalte en die numeriese vaardigheidmaatstaf. Die arbeidsmarkopbrengs op menslike kapitaal word deur middel van die Heckman ‘Maximum Likelihood (ML)’-metode geskat om te kontroleer vir moontlike sydighede wat mag onstaan weens selektiewe waarneming van hierdie veranderlikes of as gevolg van endogene seleksie in arbeidsmarkdeelname of indiensneming. Die Heckman ML-skattings word dan vergelyk met gewone kleinste-kwadrate-skattings wat met behulp van verskeie modelspesifikasies en steekproewe beraam is, om sodoende te bepaal hoe verskillende spesifikasies, steekproewe en beramingstegnieke skattings van die arbeidsmarkopbrengste op menslike kapitaal in Suid-Afrika beïnvloed. Die meerveranderlike-analise dui daarop dat daar grotendeels onbeduidende arbeidsmarkopbrengste is op opvoeding in Suid-Afrika vir opvoedingsvlakke benede tersiêre vlak, en dat rasseverskille in skoolgehalte ’n beduidende deel van waargenome rasseverskille in arbeidsmarkverdienste mag verduidelik. Indien sosio-demografiese faktore en ander menslike kapitaalverskille in ag geneem word, beïnvloed syfervaardigheid en skoolgehalte nie arbeidsmarkuitkomstes en die konvekse struktuur van die arbeidsmarkopbrengste op opvoeding in Suid-Afrika beduidend verder nie. Terwyl die regressieresultate aansienlik tussen die verskillende modelspesifikasies en steekproewe verskil, word die resultate weinig geraak deur vir gevalle van endogene seleksie met behulp van die Heckman ML-metode te kontroleer. Hierdie bevindinge dui daarop dat daar net beperkte ruimte bestaan om ernstige dataleemtes met behulp van standaard parametriese beramingstegnieke te oorkom, en dat die een of ander vorm van sensitiwiteitsanalise benodig word wanneer datagebreke die betroubaarheid van die beraamde resultate nadelig kan raak.

Please refer to this item in SUNScholar by using the following persistent URL: http://hdl.handle.net/10019.1/17820
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