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What explains the high levels of child labour found in some regions of Kenya? Inequalities behind child labour can be examined using a statistical method. We test for social and regional differences, including household and personal characteristics. Area differences in education are found.
We analyse the reasons for very high levels of child labour found in some regions of Kenya. We approach this by applying multilevel modeling with an evidence-based approach and a multidisciplinary orientation. Our interpretation has multiple explanatory strands. We test for explanations of high/low child labour risk, both with household and personal variables, and variables representing districts' characteristics. The prominence of mining and quarrying in a district offers significant explanatory purchase on Kenya's recorded child labour. A district's poverty level is also a risk factor. We tested socio-cultural hypotheses, combining them with the usual economic hypotheses. We found that Kenyan children living with a more educated female carer are less likely to be in harmful child labour. This paper uses a cautious definition consistent with both ILO and UNICEF definitions, which includes farming work, domestic work, and work in goods and services above set weekly hours-thresholds. We used data from 2015/6 Kenyan Integrated Household Survey.