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This study examines whether movement out of agriculture accelerates productivity convergence in West Africa. We assemble an annual country panel for 16 West African economies over 2000–2023 from the World Development Indicators, Penn World Table 11.0 and Worldwide Governance Indicators. The estimable dynamic specification contains 237 country-year observations for 11 economies because the Penn World Table human-capital series determines the common complete-case sample. A pre-specified two-step System GMM model is rejected because second-order serial correlation is significant and the Hansen test is uninformative. Inference therefore rests on a dynamic country-and-year fixed-effects model with Driscoll–Kraay standard errors, supplemented by a first-order Nickell-bias assessment and a three-sector shift-share decomposition. Labour productivity is conditionally convergent: the lag coefficient is 0.841, implying a four-year half-life, or about 9.7 years under the conservative bias approximation. Capital deepening is positive and statistically precise, while manufacturing, services and agricultural-employment shares are not separately significant. This absence of statistical precision does not imply that structural transformation is irrelevant: employment reallocation contributes positively in all 16 economies. Regionally, within-sector gains account for 75.2% of observed productivity change, reallocation for 29.3%, and the interaction term for −4.5%. Policy should combine labour mobility with capital formation and productivity upgrading inside agriculture, manufacturing and services rather than pursue sector-share targets alone.

Education is generally considered to be the core source of individuals’ better life and countries' economic and social development. Consequently, attending university and getting high qualifications are perceived as tools that generate and enhance economic growth. The current study aimed to analyse the effect of various educational levels on South African economic growth. The study employed quarterly data from 1995Q1 to 2021Q4. The autoregressive distributed lag (ARDL) model was employed to assess both long-run and short-run relationships among variables. The long-run results revealed that people who completed their grade 12 (with matric certificate) and bachelor's degrees contribute positively to South African economic growth. However, honours and higher degrees (master's and PhD) were found to have an inverse relationship with economic growth in South Africa. On the other hand, the short-run relationship indicated that all education levels contribute to economic growth in the short term. Based on these findings, the author suggests that the South African higher education curriculum should be revised as the negative effect of high education towards economic growth should be resulting in growing unemployment and graduates waiting to be employed rather than creating jobs themselves. Additionally, increasing job creation for graduates with higher qualifications would reduce the number of graduates that leave the country looking for employment abroad.