A non-parametric assessment of efficiency of South African public universities

Nkohla, T. V. ; Munacinga, S. ; Marwa, N. ; Ncwadi, R. (2021)

CITATION: Nkohla, T. V., et al. 2021. A non-parametric assessment of efficiency of South African public universities. South African Journal of Higher Education, 35(2):158-187, doi:10.20853/35-2-3950.

The original publication is available at http://www.journals.ac.za/index.php/sajhe


This article seeks to assess the efficiency of 23 South African public universities using a Data Envelope Analysis (DEA) model for the period 2009–2016. A recent study on this subject matter found a decline in the average TE score of the South African public universities from 83 per cent in 2009 to 78 per cent in 2013. However, the study did not account for non-academic staff among other input variables that are assumed to potentially influence performance outcomes of the universities. We believed that a biased conclusion on the subject matter is likely if academic staff are assumed to dominate efficiency of public universities in South Africa, while the effort of non-academic staff is not considered. In this respect, our model incorporates both academic and non-academic staff as input variables among others. Our findings show that over the study period 2009–2016 the average Technical Efficiency (TE) of the South African public universities increased from 91 per cent to 95 per cent. For this result in particular, we deduce that in assessing efficiency of South African public universities, academic and non-academic staff can be deemed as mutually inclusive variables and therefore, neglecting either of the two can lead to biased estimated average TE scores. In addition to this empirical contribution, we also estimate scale and pure efficiency. Our findings show that on average South African public universities are relatively better off in scale efficiency (at 97%) as compared to pure technical efficiency (at 96%). The efficiency levels provided in this study can be used as performance benchmarks for identifying potential improvements required to reach a satisfactory level of efficiency.

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