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<p>Poverty is extensively acknowledged as a multidimensional phenomenon and has been the subject of extensive research all over the world. When it comes to child poverty, the impacts differ significantly due to the critical stages of physical, cognitive and socioemotional growth which make them vulnerable to the negative impacts of poverty. This paper analysed the impact of households’ income sources on child’s (0–17 years) fuzzy multidimensional poverty indicators in South Africa. The South African General Household Survey (GHS) datasets for the years 2017, 2018 and 2019 were used. The data were collected using the stratified two-stage sampling method with sampled households comprising 25,915, 25,224, and 20,083 children in 2017, 2018 and 2019, respectively. The fuzzy set methodology was used to compute child’s multidimensional poverty indicator (MPI), which was later analysed with the Tobit regression model and treatment effects potential outcome framework using regression adjustment estimator. The results of the Tobit regression indicate that geography type, residence in Eastern Cape, North-West and Limpopo provinces, parental presence and income sources significantly (<i>p</i> &lt; 0.01) influenced child’s fuzzy multidimensional poverty. Additionally, children identified as Coloured, Indian/Asian and White and those who were biological children of household heads had significantly lower (<i>p</i> &lt; 0.01) poverty. With respect to the Average Treatment Effect (ATE) and the Average Treatment Effect on the Treated (ATET), the results showed that children from households that were receiving social grants, salaries, income from business, remittances, pensions and other sources of income had significantly lower (<i>p</i> &lt; 0.01) fuzzy MPI, when compared to the control group. In contrast, children from households that were receiving once off grants had significantly higher fuzzy MPI significantly (<i>p</i> &lt; 0.01) higher compared to the control group. It was concluded that some income sources possess MPI reducing tendency. Therefore, development programmes to enhance households’ access to them are recommended.</p>

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Impact of Households’ Income Sources on Child’s Multidimensional Poverty in South Africa

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月9日

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  • Thonaeng Charity Molelekoa

摘要

Poverty is extensively acknowledged as a multidimensional phenomenon and has been the subject of extensive research all over the world. When it comes to child poverty, the impacts differ significantly due to the critical stages of physical, cognitive and socioemotional growth which make them vulnerable to the negative impacts of poverty. This paper analysed the impact of households’ income sources on child’s (0–17 years) fuzzy multidimensional poverty indicators in South Africa. The South African General Household Survey (GHS) datasets for the years 2017, 2018 and 2019 were used. The data were collected using the stratified two-stage sampling method with sampled households comprising 25,915, 25,224, and 20,083 children in 2017, 2018 and 2019, respectively. The fuzzy set methodology was used to compute child’s multidimensional poverty indicator (MPI), which was later analysed with the Tobit regression model and treatment effects potential outcome framework using regression adjustment estimator. The results of the Tobit regression indicate that geography type, residence in Eastern Cape, North-West and Limpopo provinces, parental presence and income sources significantly (p < 0.01) influenced child’s fuzzy multidimensional poverty. Additionally, children identified as Coloured, Indian/Asian and White and those who were biological children of household heads had significantly lower (p < 0.01) poverty. With respect to the Average Treatment Effect (ATE) and the Average Treatment Effect on the Treated (ATET), the results showed that children from households that were receiving social grants, salaries, income from business, remittances, pensions and other sources of income had significantly lower (p < 0.01) fuzzy MPI, when compared to the control group. In contrast, children from households that were receiving once off grants had significantly higher fuzzy MPI significantly (p < 0.01) higher compared to the control group. It was concluded that some income sources possess MPI reducing tendency. Therefore, development programmes to enhance households’ access to them are recommended.