South African unemployment and economic growth: A disaggregated analysis by education attainment<b></b>
Ronewa Mudzanani ORCID ↗ · Matamela Netshikulwe
International Journal of Research in Business and Social Science · 2026 · Vol. 14 / Issue 9 · 274-282
Publication metrics
External links open provider records or DOI searches. Provider counts are not combined. Mendeley readership measures saves, not citations.
Dimensions
Live provider badge. If unavailable, use the Dimensions link above.
Observed 21 Oct 2026, 07:22 UTC
Observed 21 Oct 2026 07:23 UTC
OpenAlex and Mendeley observations refresh on article visits, at most once per 24 hours. Unavailable data is not zero. Google Scholar opens a DOI search.
Citations received by this article, grouped by the year of the citing work. Crossref and OpenAlex lifetime totals remain separate in Publication metrics.
2017–2026 Annual history last updated:
Citations received
OpenAlex · year of the citing work
Hover over a year or focus the chart and use arrow keys to inspect values.
2017–2026 annual-history window. 2026 is year to date. Unknown years have gaps.
View data & coverage
2026 is incomplete. Within a successfully fetched ten-year window, omitted years mean zero. Years beyond a saved observation’s window remain unknown (—). Older citations are excluded, so this chart’s sum may differ from the OpenAlex lifetime total. The date above belongs to this annual history; an unsuccessful refresh keeps the previous observation.
Abstract
This study examines the correlation between unemployment and economic growth in South Africa through a disaggregated analysis focused on educational attainment. Grounded in the Solow growth model and human capital theory, the research utilises annual time-series data from 1994 to 2022, obtained from the World Bank Indicators. Economic growth is represented by GDP growth, labour is indicated by unemployment rates categorised by advanced, intermediate, and basic education levels, and capital is measured by gross fixed capital creation. The Autoregressive Distributed Lag (ARDL) framework is utilised after conducting unit root and bounds tests, which validate the existence of long-run cointegration. The findings reveal a negative and statistically significant long-term association between economic growth and unemployment for those with basic and intermediate education, but unemployment among those with advanced education shows a negative but minor influence. Investment consistently demonstrates a favourable and substantial effect on growth. The findings emphasise structural unemployment and skills mismatches, highlighting the necessity for enhanced alignment between educational systems and labour market requirements to foster inclusive and sustainable economic growth in South Africa.
Keywords: {'name': 'ARDL'}, {'name': 'economic growth'}, {'name': 'unemployment'}, {'name': 'advanced education'}, {'name': 'intermediate education'}
Authors & affiliations
Ronewa Mudzanani
University of Venda
Matamela Netshikulwe
University of Venda
Deposited references
Supplied references, not a list of publications citing this article.
Akeju, K. F., & Olanipekun, D. B. (2015). Unemployment and economic growth in Nigeria. International Journal of African and Asian Studies, 11(4), 92–99. www.iiste.org
Askenazy, P., Chevalier, M., & Erhel, C. (2015). Okun's laws differentiated by education [Working paper].
DOI: 10.1093/acprof:oso/9780199379231.001.0001
Becker, G. (1964). Human capital: A theoretical and empirical analysis. University of Chicago Press.
Cobb, C. W., & Douglas, P. H. (1928). A theory of production. The American Economic Review, 18(1, Supplement), 139–165.
Graham, P. (2017). Review of Human Capital: A Theoretical and Empirical Analysis, with special reference to education, by G. S. Becker; The residual factor and economic growth; Econometric models of education. The Economic Journal.
DOI: 10.3390/su151511955
International Labour Organisation. (2019). Inclusive future of work republic of South Africa. https://www.ilo.org/wcmsp5/groups/public/---dgreports/---cabinet/documents/publication/wcms_732871.pdf
International Labour Organization (ILO). (2015). Global employment trends for youth 2015. ILO.
DOI: 10.3844/jssp.2011.228.231
DOI: 10.1016/B978-0-444-53444-6.00003-1
DOI: 10.1016/0304-3932(88)90168-7
Mandelker, G. (1974). Schooling, experience, and earnings. Journal of Political Economy, 1(1), 303–335.
Morsy, H., & Mukasa, A. N. (2019). Youth jobs, skill and educational mismatches in Africa. Working Paper Series, (326), 29–35.
DOI: 10.1142/11458
Pesaran, M. H. (2008). An autoregressive distributed-lag modelling approach to cointegration analysis. In Econometrics and economic theory in the 20th century: The Ragnar Frisch centennial symposium. https://doi.org/10.1016/S0573-8555(00)80016-4
DOI: 10.1093/biomet/75.2.335
DOI: 10.1080/09645292.2018.1484426
SAQA. (2015). The South African Qualifications Authority (SAQA). Level descriptors for the South African National Qualification Framework.
DOI: 10.31384/jisrmsse/2017.15.1.2
DOI: 10.3390/books978-3-03897-779-7-1
Schultz, T. W. (1961). Investment in human capital. The American Economic Review, 51(1), 1–17.
DOI: 10.2307/1884513
The Department of Education. (2004). Government gazette. Prevention, 469(869), 4–6. http://www.nsw.gov.au/sites/default/files/Government_Gazette_2_December.pdf#page=15