Child Deprivation and Income Poverty in Ghana
Kofinti, Raymond Elikplim; Annim, Samuel Kobina (2016). 'Child Deprivation and Income Poverty in Ghana' Paper presented at the annual conference of the HDCA, Tokyo 2016.
This study assesses temporal and spatial distribution of child deprivation and income poverty using the fifth and sixth rounds of the Ghana Living Standards Survey. The first order dominance methodology was used to examine five dimensions of deprivation of children aged 7 to 17 years, and the outcomes were compared to the incidence of income poverty. The analyses reveal the following: reduction in child deprivation across all five dimensions over time; wide disparities across geographical areas; and differences in regional rankings of deprivation and income poverty. Distinct policies for child deprivation and income poverty are imperative for different locations in Ghana.
Keywords: Deprivation, Income, Child Poverty, First Order Dominance and Ghana.
In spite of the evidence that global poverty is on the decline, disparities in rates of reduction across countries as well as large disparities in levels of living standards continue to cause concern among policymakers, development partners and researchers. These wide disparities in poverty levels are discernible in the African economies (Ajakaiye et al., 2014). In sub-Saharan Africa, 47.5 percent of its population, representing approximately 386 million people, lived below the poverty line of US$1.25 a day in 2008, down from 51.5 per cent in 1981 (World Bank, 2012).
The measurement of poverty can be divided broadly into unidimensional and multidimensional approaches (Alkire and Foster, 2011 and Sen 1976). The use of a unidimensional measurement of poverty is biased towards adults, with limited attention paid to children. (Gordon et al., 2003; Munujin 2014; UNICEF et al. 2007). However, most of the studies on poverty in Ghana (Annim et al., 2012; Boateng et al., 1992; Coulombe and Wodon, 2007) are adult oriented. The few studies on child poverty in Ghana (Mba and Badasu, 2010; Mba et al., 2009) employed the Bristol (Headcount) approach to measure the spatial distribution of child poverty across the country at a point in time.
The headcount approach provides no incentive for policy makers to prioritize the poorest children (Alkire and Roche,2012). In addition, welfare functions that aggregate separate dimensions of well-being into a headcount ratio typically requires imposition of weighting schemes, which could affect the consistency of ranking. One way to ensure consistent ranking of populations is provided by multidimensional stochastic dominance conditions (Yalonetzky, 2013). The methodology of First Order Dominance (FOD) is in this family:. The FOD approach enables welfare comparisons between two or more populations with multidimensional discrete well-being indicators observed at the micro level without recourse to arbitrarily weighting scheme.
This study assesses the temporal and spatial distribution of child poverty and well-being for four sets of geographical groupings of Ghana, namely national, rural/urban, ecological zones and administrative regions. It uses the Ghana Living Standards Survey (GLSS) rounds five and six. The study employs the FOD methodology in five deprivation indicators – water, sanitation, shelter, education and information – to measure the poverty and well-being of children aged 7 to 17 years old. In addition, the study employs a monetary approach in income to measure the incidence of children living in low-income households. Finally, the study compares the distribution of child poverty from a multidimensional deprivation based analysis using FOD with that of income poverty.
The rest of the paper is presented as follows: section 2 reviews related literature on child poverty. Methods of study and discussion of the results are presented in sections 3 and 4 respectively. The final section highlights the main findings and policy recommendations.
Review of related literature
The last decade has seen a proliferation of empirical studies on child poverty across the globe: Alkire and Roche, (2012); Arndt et al. (2012); Gordon et al. (2003); Minujin (2011); Minujin (2014); Minujin and Nandy, (2012); and Roche, (2013). In the context of Ghana, Mba et al. (2009) conducted a study on child poverty and disparity in Ghana. Both studies employed the deprivation model of Gordon et al. (2003) in dimensions of water, sanitation, shelter, education, health, nutrition and information for children between 0 and 17 years. In both studies, absolute poverty was defined as children having two or more severe deprivations in any of the mentioned deprivations. Their main findings reveal the three Northern regions as the poorest regions in Ghana.
Methods and Data
Multidimensional FOD approach
The methodology follows the FOD approach operationalised by Arndt et al. (2012).
This study chooses five main indicators of welfare for children aged 7 to 17 years by following closely the severe deprivation model of Gordon et al. (2003) in the following child deprivation indicators: Water, Sanitation, Education, Shelter and Information.
An income based approach
The income approach for measuring child poverty conceptualizes child poverty as children living in low income households. This monetary poverty approach takes the household as the unit of analysis but makes a strong assumption about the intra household distribution of resources. The poor are identified by setting a poverty line corresponding to a given threshold of household income (Roelen and Gassmann, 2008).
For both approaches, the study employs the GLSS as its main data source. The GLSS is a nationwide survey carried out by the Ghana Statistical Service. This study focuses on the last two rounds of the GLSS (5 and 6), and the population in focus for the FOD methodology is children aged 7 to 17 years. The fifth round contains information on 8,687 households, and in these households there were 10,515 children aged 7 to 17 years. The sixth round contains information on 16,772 households, and in these households there were 20,082 children between the ages of 7 and 17.