Abstract
In this paper, I examine child labour and schooling in Tanzania. I use Tanzania Labour Force Survey data containing detailed information on children aged 5–17. I find that girls are more likely to do household chores and spend more hours on household chores than boys. On the other hand, boys are more likely to do activities for pay, profit or home use and spend more hours on economic activities than girls. I also find a positive and statistically significant relationship between the number of children below 5 years (preschoolers) and the time children aged 5–17 years spend on household chores, suggesting that the latter may be spending more time caring for the former. Furthermore, I find a negative and statistically significant relationship between asset ownership and child labour. Concerning child labour and the educational performance of the children, I find that children who were engaged in household duties or economic activities, children who did any activities for pay, profit or home use and those who spent more hours on household chores are more likely to perceive that they get poor grades at school because of work. Regarding potential pathways, time spent by the children on economic activities, household chores and working in any activities for pay, profit or home use are found to affect the children's regular school attendance or studies.
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Notes
Child labour is any work that deprives children of their childhood, their potential and dignity, and that is harmful to physical and mental development (International Labour Organisation [ILO] et al., 2019). It is defined by the ILO Minimum Age Convention, 1973 (No. 138), the Worst Forms of Child Labour Convention, 1999 (No. 182), and the United Nations Convention on the Rights of the Child (ILO, OECD 2019). In this paper, the definition is broader than the conventional one because it includes household chores.
Notwithstanding, since independence in 1961, the country has put in place several policies to promote the welfare, enhance education opportunities and protect the rights of children (e.g. see National Child Labour Survey: Tanzania national child labour survey 2014: Analytical Report (ilo.org).
These numbers exclude the worst forms of child labour such as child trafficking, commercial sexual exploitation and child slavery because information on children involved in these worst forms of child labour is limited.
In 2018, national dropout was at 0.7% of the total enrolment and only about 28.4% of 13-year-old children reached Standard VII (United Republic of Tanzania [URT], 2018).
In 2018, the total number of pupils living in vulnerable environment was 124,057, equivalent to 8.7% of total enrolment (URT, 2018).
However, there is a possibility that children in child labour may be learning valuable skills, accumulating experiences, bringing in resources, establishing independence, supporting their family, paying for their schooling, developing a sense of effectiveness and enhancing their self-confidence (Heady 2003).
Article 5. -(1) of the Tanzania Employment and Labour Relations Act, 2004 states that no person shall employ a child under the age of fourteen years (URT, 2004). Article 5.-(2) reads as follows: “A child of fourteen years of age may only be employed to do light work, which is not likely to be harmful to the child's health and development; and does not prejudice the child's attendance at school, participation in vocational orientation or training programmes approved by the competent authority or the child's capacity to benefit from the instruction received” (URT, 2004).
Since primary education begins at the age of 7, the age group (5 to 17 years) of children this paper examines, are supposed to be in preprimary education, primary education or lower secondary education.
See Mugizi (2022a) for details on other levels of education.
Under such contexts, it might be possible for children to attend school and work before or after class.
Some schools, especially private schools, extend beyond this time.
Traditionally child labour is defined based on economic activities.
These chores performed by a child during the week preceding the survey include shopping, repairing equipment, cooking, cleaning utensils/house washing clothes for the household taking care of the preschoolers, old or sick-and other household tasks.
This index is created by using principal component analysis (PCA) technique. This technique extracts a linear combination of all the household chores performed by a child. The PCA best describes and transforms them into one index (Mugizi & Matsumoto 2020; 2021; Mugizi 2022b). It then determines weights intrinsically and assigns them to each indicator by its relative importance. The first principal component which captures the greatest variation among the set of variables is used as the index.
During the survey, each household was asked whether it owns the following assets: car, tricycle, motorcycle, bicycle, cart, refrigerator, cooker, television, iron, phone, radio, plough, stove, livestock, tiller, others. I use principal component analysis technique to construct an index for asset ownership.
They are censored at zero because they are observed only for the children who worked. The Tobit model is typically used for such dependent variables. However, I do not rely on it due to its strict error term assumption–normality. Moreover, the output from nonlinear models such as Tobit must be converted into marginal effects to have a meaningful interpretation of the results. It has been shown that linear model estimates and marginal effects of nonlinear models like Tobit are quite similar (Angrist & Pischke, 2009 p.103–107). I, therefore, report and discuss the estimation results from the linear models. Nonetheless, the results from Tobit estimation (though not reported to economise space) remain qualitatively similar.
In all these estimations, the main results remain qualitatively similar (see Table 8 in the appendix).
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Mugizi, F.M.P. Child labour and schooling in Tanzania. J. Soc. Econ. Dev. (2024). https://doi.org/10.1007/s40847-024-00333-9
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DOI: https://doi.org/10.1007/s40847-024-00333-9