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

[摘要] ENGLISH ABSTRACT: This study investigates the extent to which educational attainment, school quality and numericcompetency influence individuals' employment and earnings prospects in the South African labourmarket using data from the 2008 National Income Dynamics Study (NIDS). While NIDSis one of the first datasets to contain concurrent information on individual labour market outcomes,educational attainment levels, numeric proficiency and the quality of schooling receivedin South Africa, it is also characterised by limited and selective response patterns on its schoolquality and numeracy measures. To account for any estimation biases that arise from the selectiveobservation of these variables or from endogenous selection into labour force participationand employment, the labour market returns to human capital are estimated using the HeckmanMaximum Likelihood (ML) approach. The Heckman ML estimates are then compared to OrdinaryLeast Squares (OLS) estimates obtained using various sub-samples and model specificationsin 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 inSouth Africa.The findings from the multivariate analysis suggest that labour market returns to educationalattainment in South Africa are largely negligible prior to tertiary levels of attainment and thatracial differentials in school quality may explain a significant component of the observed racialdifferentials in South African labour market earnings. Neither numeracy nor school qualityappears to influence labour market outcomes or the convex structure of the labour market returnsto educational attainment in South Africa significantly once sociodemographic factors and otherhuman capital endowment differentials have been taken into account. Though the regressionresults vary substantially across model specifications and estimation samples, they are largelyunaffected by attempts to correct for instances of endogenous selection using the Heckman MLprocedure. These findings suggest that the scope for overcoming data deficiencies by usingstandard parametric estimation techniques may be limited when the extent of those deficienciesare severe and that some form of sensitivity analysis is warranted whenever data imperfectionsthreaten to undermine the robustness of one's results.

[发布机构] Stellenbosch University