A statistical modelling of the factors contributing to child labour in Namibia

Evidence from the 2018 labour force survey

Authors

  • Opeoluwa F Oyedele University of Namibia: School of Science
  • Anna-Lisa Shilongo University of Namibia: School of Science

Keywords:

Child labour, Multinomial logistic, regression, Namibia

Abstract

Despite children not allowed to work by law in Namibia, child labour is still being practised in the country. In this paper, the multinomial logistic regression model was used to statistically examine the factors contributing to child labour in Namibia using the 2018 Namibia Labour Force Survey. Results showed that the children’s characteristics such as their residential area, region, age group, highest educational attainment, school attendance and the types of social grants received had a significant impact on the children’s engagement in child labour activities, while the sex of the children did not. In addition, economically inactive children aged 8-9 years, who already attained a pre-primary education and were currently attending school were more likely to engage in child labour activities,
while employed children who were receiving special maintenance grants meant for disabled children, war veterans/ex-combatants grants and other types of social grants were less likely to. It is therefore recommended that the Namibian government and policy makers constantly engage and collaborate with community leaders to assist in the improvement of the standards of living through the creation of decent employment for the children’s parents/guardians, thereby providing decent income to cover at least the basic needs of the children’s households.

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Published

2022-01-31

How to Cite

Oyedele, O. F., & Shilongo, A.-L. . (2022). A statistical modelling of the factors contributing to child labour in Namibia: Evidence from the 2018 labour force survey. International Science and Technology Journal of Namibia, 15, 16–25. Retrieved from https://journals.unam.edu.na/index.php/ISTJN/article/view/1644

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