Analyzing Nigeria’s unemployment problem: evidence from the quantile regression approach

Most studies on Okun’s Law focus on mean effects using ordinary least squares or dynamic models, with limited use of quantile regression. This leaves unexplored how output growth impacts unemployment across different points of the unemployment distribution. By applying a static quantile regression framework, this study fills this gap in analyzing the unemployment problem and its key determinants in Nigeria from 1991 to 2024. The findings showed that aggregate GDP growth reduces unemployment, with stronger effects at higher quantiles. However, results showed a weaker-than-expected Okun’s Law coefficient, reflecting the non-inclusive nature of Nigeria's economic growth. Sectoral analysis reveals that while Agriculture and Industry exert limited effects, the Construction and Services sectors significantly reduce unemployment, particularly through key activities such as Professional & Scientific Services, Trade, Real Estate, and Health. Government consumption largely worsens unemployment, whereas net FDI inflows foster job creation. The results highlight the need for structural transformation and policy realignment towards productive investments that strengthen the employment intensity of growth.