Education as a Driver of Sectoral Employment in Rwanda: A Panel Regression Analysis of Selected Economic Sectors (2019–2023)

This study investigates the influence of educational attainment on sectoral labor absorption in Rwanda, utilizing a panel regression framework across thirteen economic sectors from 2019 to 2023. Grounded in Human Capital Theory, the research evaluates how varying levels of schooling dictate the distribution of employment within an evolving economy. Drawing on secondary data from the National Institute of Statistics of Rwanda (NISR) Labour Force Surveys, the analysis employs descriptive statistics, trend analysis, and econometric modeling. Diagnostic testing via the Hausman specification (χ² = 0.03, p = 0.8718) confirmed the suitability of the Random Effects model for the longitudinal data. The findings reveal a persistent reliance on primary and lower secondary education within low-productivity sectors, notably agriculture. While agriculture’s share of informal employment contracted from 61.2% in 2019 to 51.7% by 2023, it remains a primary labor sponge for the unskilled workforce. Conversely, a robust positive correlation ($r = 0.80$) was observed between university-level attainment and growth in knowledge-intensive domains, including finance, ICT, and education. These results suggest a steady structural transition, with labor force participation in services rising from 53.3% to 59.3% during the study period. The research concludes that while education acts as a critical driver of labor market transformation, a significant quality gap remains. Policy recommendations emphasize the strategic decentralization of high-value services and the alignment of technical and vocational training with specific industrial demands to ensure sustainable, inclusive economic growth in Rwanda.

Education; Sectoral Employment; Human Capital Theory; Panel Data Analysis; Labour Market; Structural Transformation.

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