Analysis of child labour dimensions and causes in rural farm households of Ogun state, Nigeria

Abstract

The prevalence of child labour use in the agricultural sector has been widely reported
however, the intensity of its use is most times masked and marred by the informal and
culturally ingrained nature of peasant agriculture. The study aims at understanding the
dimensions and causes of child labour among rural farm households in Nigeria. A
multistage sampling technique was used to select 128 rural households for the survey; a
total of 352 children (5-17years) were interviewed to elicit first hand data for the study.
Structured questionnaire was used to collect data on child farm work hours, household
size, income, farm size, distance of home to school and other relevant socioeconomic
characteristics. Analytical techniques used were measures of central tendency and
dispersion, and censored Tobit regression model. Results show that the average age of
children is 10 years and many of these children (67.3%) are reported to be living with
their biological parents. While less than a third (26%) of the children work in paid and
non-family farms, the average weekly work hours per child was found to be 31.31
which increases with the age of the child. With reference to loss in school time due to
farm work, it was found that rural children in farm households sacrificed an average of
12.9 hours per week (42.9%) of school time to work on the farm; this varies from
season to season. Age and education level of the household head, farm and household
size, lack of child-level schools in the community, distance of home to school, sex of
child, absence of tarmac roads to community and proximity of households to major
roads were identified as factors that influence the prevalence and intensity of child farm
labour use. The study concluded that rural infrastructure development and households’
economic empowerment initiatives are central to child labour reduction strategies.

Key words: Child farm labour, rural households, determinants, Tobit regression