With continuous growth of students' enrolments in the public universities and limited funding, assessing the efficiency of universities is vital for effective allocation and utilisation of educational resources. Are higher education institutions in South Africa making the most efficient use of resources made available to them? This study attempts to provide an answer to this question. We apply a Data Envelopment Analysis (DEA) method to estimate technical efficiency (TE) of 22 public universities in South Africa for the period 2009 to 2013. A university is said to be efficient if it is producing maximum output (number of graduates and publications) from a minimum quantity of inputs (staff numbers, students' enrolments, and expenditure). The results indicate that over the study period the average TE of universities declined from 0.83 to 0.78. Research-intensive universities were more efficient than professional-oriented universities. These results can help key decision-makers such as the Commission on Higher Education and universities management in identifying possibilities for improving institutional performance by identifying their strengths and weaknesses and benchmarking with their peers.

Recent high dropout and low graduation rates in the South African higher education institutions as well as government funding cuts and the economic uncertainty due to COVID-19 pandemic have heightened the urgency for the higher education sector to improve its productivity. However, empirical evidence on the productivity growth of the sector remains unexplored. To address this gap, we applied a Färe-Primont index approach to a panel data of 22 public universities over an 8-year period to measure total factor productivity (TFP) and its components—technological change, technical, scale and mix efficiency changes. We also used a feasible generalised least squares model to assess the determinants of productivity and efficiency growth. The results show that the average TFP of the sector for the study period was 0.631, led by historically advantaged universities (0.894), whilst historically disadvantaged universities had lower average TFP (0.823). During the period, TFP increased by 3.43%, largely driven by scale and mix efficiency changes (5.32%) and technical efficiency change (0.83%), whilst technical change declined by 1.80%. In terms of university types, the comprehensive universities achieved the largest TFP growth (6.13%) followed by traditional universities (4.85%), and technology universities by 1.41%. TFP growth was positively influenced by student graduation rates, quality of academics and academic-student ratios. Therefore, policy considerations to improve the sector’s productivity and efficiency should consider investment on research and development, adoption of teaching and research innovations, re-skilling through training and education and aligning admission policies with staffing.

The prevailing economic conditions as a result of COVID-19, climate change, and the Russia–Ukraine conflict, have led to renewed global interest in the efficiency of the agricultural sector. As a result of this, we investigated the efficiencies of 64 broiler producers in three districts covering the North West and Limpopo provinces in South Africa from 2019 to 2022, using a two-stage data envelopment analysis method with input orientation. The results show that producers operate on the upper bounds toward efficiency, but room for improvement still exists at 10%, 20%, and 28% on technical, allocative, and cost efficiencies. This indicates that inputs can still be reduced without changing the level of output and that the input combination is incompatible with cost minimization. Consequently, only 13%, 8%, and 4% of the sampled broiler producers exhibited technical, allocative, and cost efficiencies, respectively; the majority were women. The Vhembe, Capricorn, and Dr. Kenneth Kaunda (DRKK) districts had vastly different scores for each efficiency type, indicating that their differences in resource endowments, technology, and climate, necessitate the formulation of district-specific policies. The mortality rate, heating costs, and investments in health emerged as significant efficiency determinants. Overall, the findings provide insights into refocusing the country’s poultry sector in light of current shocks and the notable aspirations of the poultry master plan.

The effort to increase agricultural productivity continues to receive interest in Africa as low productivity levels, poverty and food insecurity remain or even increase. This study used the Färe-Primont Index to estimate agricultural total factor productivity growth for 49 African countries. Panel data consisting of 833 observations for the period 2000 to 2016 were obtained from the United State Department of Agriculture Economic Research Service database. The results show that the average growth rate for agriculture in Africa is 0.73% per annum. The sector experienced increased growth after the Maputo Declaration, which was sustained during the global financial crisis. West Africa experienced the largest growth while Southern Africa suffered a substantial decline. The study also discovered that growth differed between countries indicating that customization of the Comprehensive Africa Agriculture Development Programme into regional and country-specific policy interventions is important to boost agricultural productivity. Finally, the growth was achieved through technical change, while efficiency change constrained growth. Policy-makers should increase investment in agricultural extension services, education and training to enhance managerial capacity (efficiency change) because improved managerial capacity could increase agricultural growth and thereby increase food security and alleviate poverty in Africa.