DETERMINANTS OF CHILD LABOR IN MALAWI AND TANZANIA

Abstract: Using the Malawi Integrated Household Survey of2009 and the Tanzania National Panel Survey of 2010, this study seeks to understand the factors that increase a child's likelihood of labor participation. A greater percentage of children in the Tanzania sample than those from the Malatii sample partidpate in child labor. Logistic regression analyses showed that, as hypothesised, the greatest influence on child labor observed at the individual level is the child's school enrollment status. Enrollment reduces the likelihood of engaging in child labor in both countries. When tested in the combined model older children in Tansania remain at higher risk of child labor participation, school enrolled children in both countries an less likely to be child laborers and the rural based children in Tansania have higher odds of being child laborers. At the household level a father with at least a primay education in Malawi is associated tilth a lesser likelihood of participation. At the community level, Hiring in a rural area drastically increases the odds for child labor participation in Tansania. In mew of these results, county specific solutions to prevent child labor maybe necessay, given the differentpredictors of child labor participation in each county.Keywords: Malawi; Tansania; child labor.1. IntroductionThere is a growing consensus that child labor is an undesirable form of work and greater investments should be made in developing children's human capital (World Bank, 2002). There is, however, wide disagreement on how to tackle it. Child labor, also referred to as "harmful child work" is the focus of attention by governments, as well as international and national civic society organizations. The current situation faced by millions of children is deplorable and requires urgent international action. The latest report by the International Labor Organization (ILO) (2010) states that for over a decade it has been recognized as a key human rights issue, starting from 1996 when governments made fresh calls to end child labor.This research is an attempt to better understand the factors that lead to the likelihood that child labor will occur in two Sub Saharan African countries, namely Malawi and Tanzania. The literature has noted that there has been a shift in emphasis from mere quantification of child labor to an econometric analysis of its determinants (Bhalotra and Tzannatos, 2003). This research analyzes this issue from multiple levels because they all work in concert to constitute one's habitus - how people become who they are (Bourdieu, 1977). Most research on child labor focused on predictors at a single level; either the family level (Buchman, 2000; Patrinos and Psacharopoulos, 1997) or the national level (e.g. Kis-Katos and Schultze, 2006). It is important to highlight that the determinants of child labor are multi-dimensional. In order to get in-depth theoretical underpinnings of why children engage in this practice, greater and more current information on the individual, household and contextual factors is required (Whitsel, 2010). The focus of this paper is on Sub Saharan Africa, a region flagged as having the highest participation by children in the worst forms of child work (ILO, 2010). Malawi and Tanzania make excellent case studies for three reasons. The first is because they have been highlighted to have high rates of child labor (ILO, 2004; 2010; 2012). The second reason is simply because the data are available. The third reason is that these countries are a good reflection of Sub Saharan Africa. They have unique socio-economic characteristics that can be fertile ground for children engaging in work. Both Malawi and Tanzania have agro-based economies - the sector that provides the most employment for children; Tanzania also has mining (Bhalotra and Tzannatos, 2003). Studying Malawi and Tanzania will highlight key issues around child labor in the region and provide suggestions for policy amendments that could lead to the reduction and elimination of child labor in other countries (ILO, 2010). …