Eyong Ako

The University of Bamenda, Northwest Region, Cameroon

School: Higher Institute of Commerce and Management,

Department: Organisational Sciences,

E-mail: akorolly87@yahoo.com

ORCID Id: https://orcid.org/0009-0005-8689-6788

 Njie Immaculate Lum

mmaculatelum71@gmail.com

Department of Money and Banking

Higher Institute of Commerce and Management

The University of Bamenda

To cite: Eyong and Njie (2026, June 10). Human Capital, Technological Catch-up, and Growth Divergence in Sub-Saharan Africa: A Moderated-Mediation Analysis of Underemployment and Technology Adoption. The Journal of Tertiary and Industrial Sciences, JTIS (JTIS), HTTTC Kumba. https://doi.org/10.5281/zenodo.20597752

Submission Date: 27/02/2026                                                                                     Acceptance Date: 21/05/2026

Abstract

This study investigates the mechanisms through which human capital influences economic growth in Sub-Saharan Africa (SSA), with particular focus on technological catch-up as a mediator and underemployment as a moderator of the human capital-growth relationship. Motivated by persistent growth divergence across SSA countries despite decades of human capital investment, the study addresses five objectives: quantifying the human capital-growth relationship, testing underemployment as a conditional constraint, evaluating technology adoption as a transmission channel, analysing sub-regional heterogeneity in catch-up dynamics, and distinguishing short-run from long-run adjustment processes. The study employs a quantitative longitudinal panel design using secondary data from World Bank WDI, Penn World Table, ILO ILOSTAT, and World Governance Indicators covering 2000-2025. The sample comprises 35 SSA countries (875 observations) distributed across four economic blocs: ECOWAS (10), EAC (7), SADC (10), and ECCAS (6). Data analysis techniques include fixed effects regression with Driscoll-Kraay standard errors, moderation analysis with interaction terms, mediation analysis following Baron and Kenny (1986), sub-regional analysis using seemingly unrelated estimation, and ARDL-Pooled Mean Group estimation to distinguish short-run from long-run dynamics. The results reveal that human capital positively affects growth, with a one-unit increase in the Human Capital Index associated with 3.18 percentage points higher annual growth, consistent with Nelson-Phelps catch-up predictions. Underemployment significantly moderates this relationship, reducing the marginal effect from 5.68 at zero underemployment to 2.32 at 40% underemployment, indicating that labour underutilization is a binding constraint on catch-up growth. Technology adoption mediates 44.8% of human capital’s effect on growth, confirming that human capital facilitates growth primarily through enhancing technological catch-up capacity. Significant growth divergence exists across sub-regions: ECOWAS shows no significant catch-up effect (coefficient 2.15, p > 0.10) while EAC (4.32, p < 0.05) and SADC (4.85, p < 0.05) exhibit strong effects, explaining persistent growth divergence within SSA. Long-run effects exceed short-run effects by a factor of 4.7, with an error correction term of -0.32 indicating rapid adjustment to long-run equilibrium catch-up trajectories. The study concludes that human capital investment alone is insufficient for catch-up growth in SSA; underemployment must be addressed as a binding constraint, technology adoption requires coordinated policy attention, and sub-regional growth divergence demands tailored rather than uniform policy approaches. Recommendations include implementing labour market information systems to reduce skill mismatches, prioritizing learning quality over access expansion, coordinating human capital investment with technology and infrastructure policies, adopting graduate tracking systems following Rwanda’s model, and targeting structural reforms in ECOWAS to improve the growth responsiveness of its large labour force to human capital accumulation.

Keywords: Human capital, economic growth, underemployment, technology adoption, Sub-Saharan Africa, panel data