Page 38 - Contributed Paper Session (CPS) - Volume 2

CPS1414 Bashiru. I.I S. at el.

Spatial heterogeneity in child labour practices
and its determinants in Ghana
Bashiru I.I. Saeed, Lucy Twumwaah Afriyie, Abukari Alhassan
Kumasi Technical University

Abstract
Child labour practices is considered as one of the problems pertaining to
children in many countries in the world and Ghana is no exception. To combat
the situation, many research studies have been undertaken using different
modelling techniques with the framework of generalized linear model (GLM).
However, the GLM approach fails to capture the spatial heterogeneity that
exists in the relationship between the child labour practices and related
factors. The study addresses this gap by exploring the spatial heterogeneity in
child labour practices and its determinant in Ghana using geographically
weighted linear model (GWLM). This study used Ghana Living Standard Survey
Round 6 (GLSS6) data collected in 2012 by Ghana Statistical Services. The
target population was children aged 5‒17 years. GLM was used as a starting
point for selecting the appropriate predictors. Moran’s I statistics was tested
to ensure the presence of the spatial autocorrelation in the dataset under the
null hypothesis of spatial auto correlation. Several factors including proportion
of children in school, proportion of aged household head, number of
household head in construction sector and proportion of household head in
agricultural sector were considered in the models. It was showed that the
GWLM was useful and established that there is a spatially non-stationary
relationships between the proportion of child labour and the covariate at the
district level. The findings highlight the importance of taken the spatial
heterogeneity into consideration.

Keywords
Child labour; Spatial heterogeneity; Geographically Weighted Linear Model;
Ghana

1. Introduction
Child labour is a phenomenon that exists in the world (ILO-IPEC & Diallo,
2013; International Labour Organization, 2013).
Thus, the estimates of such conventional models may be bias and could
lead to misleading conclusion that may not be beneficial when addressing
policy issues that have a wider impact (Li, Wang, Loiu, Bigham, & Raglad,
2013). It is important to consider spatial variations in the analysis of child
labour practices and its determinants in a wider study area. Such analysis will

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