Characteristics and Determinants of Underemployment in Cameroon

Hyefouais Stephane and Ngniodem Achille

Working Papers from African Economic Research Consortium

Abstract: The objective of this study was to improve the analysis of the labour market in Cameroon, through a better understanding of the characteristics and determinants of underemployment. Specifically, this study aims to: identify the profile of an average visible and invisible underemployed; identify the determinants of the visible and invisible underemployment; and assess the contribution of these determinants to the underemployment gap existing between rural and urban residents. The method used for empirical analysis was both descriptive and econometric. The level of visible underemployment was 11.5% among individuals aged between 15 and 64 years. It showed no disparity in age, gender and place of residence, and increased with education. The estimated invisible underemployment rate was about 62.7%. Visible underemployment affects young people and women the most. Although it is more accentuated in rural areas, the informal sector represents the seat of the lowincome jobs. Probit and sample selection, and Fairlie decomposition (2006) are the econometric techniques used to model the probability of being underemployed. The results of the probit models suggest that education, business sector, employment sector, socio-professional category, sex, age and location have significant impact on the probability of being underemployed. The total gap in mean probability of the invisible underemployment between rural and urban workers was 26.4%. Results of the Fairlie decomposition shows that 81.1% of this gap are explained by the difference in the distribution of observable characteristics between rural and urban populations. The remaining 18.9% can be assigned to the difference due to the effects of observed characteristics. The findings also indicate that the business sector has the highest contribution (36.4%) in the distribution of observable characteristics, alongside education (13.1%) and the employment sector (10.8%).

Date: 2019-10-05
Note: African Economic Research Consortium
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