Thesis (MComm)--Stellenbosch University, 2011. / 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.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:sun/oai:scholar.sun.ac.za:10019.1/17820 |
| Date | 12 1900 |
| Creators | Van Broekhuizen, Hendrik |
| Contributors | Van der Berg, Servaas, Stellenbosch University. Faculty of Economic and Management Sciences. Dept. of Economics. |
| Publisher | Stellenbosch : Stellenbosch University |
| Source Sets | South African National ETD Portal |
| Language | en_ZA |
| Detected Language | Unknown |
| Type | Thesis |
| Format | 143 p. : ill. |
| Rights | Stellenbosch University |
Page generated in 0.002 seconds