GCRO Publications

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Visit the GCRO home page at www.gcro.ac.za For information on accessing GCRO Publications collection content please contact Bongi Mphuti via email : bongi.mphuti@wits.ac.za or Tel (W) : 011 717 1978

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    An analysis of well-being in Gauteng province using the capability approach
    (Gauteng City-Region Observatory, 2020-12-08) Mushongera, Darlington; Kwenda, Prudence; Ntuli, Miracle
    The purpose of this occasional paper is to analyse well-being in Gauteng province from a capability perspective. We adopt a standard ‘capability approach’ consistent with Amartya Sen’s concept of capabilities (1985; 1993; 1999). This study builds on earlier research on poverty and inequality in the Gauteng City-Region (GCR) focusing on income inequality (Tseng, 2018), labour market inequalities (Kwenda & Benhura, 2018) and multidimensional poverty (Mushongera et al., 2017; Mushongera et al., 2018). These analyses were based mainly on objective characteristics of well-being, such as income, employment, housing and schooling. However, adopting a capability approach provides us with a more holistic view of well-being in Gauteng by focusing simultaneously on both objective and subjective aspects. According to Robeyns (2016, p. 1), the capability approach is a theoretical framework that entails two core normative claims: first, the claim that the freedom to achieve well-being is of primary moral importance, and second, that freedom to achieve well-being is to be understood in terms of people’s capabilities, that is, their real opportunities to do and be what they have reason to value. Writing from a feminist and social justice perspective, Nussbaum (2003) generated a list of what she considered the most central capabilities. These capabilities are relevant to the analysis of well-being in general and generate useful insights that can potentially provide an additional lens within the policy realm. They can be combined into indices that capture ‘functionings’, or the ‘hard’ and ‘soft’ indicators of well-being. Out of the ten capabilities suggested by Nussbaum (2003), our analysis is based on eight, namely ‘play’, ‘emotions’, ‘other species’, ‘affiliation’, ‘bodily health’, ‘bodily integrity’, ‘senses, imagination and thought’ and ‘control over one’s environment’. The analysis uses data from the Gauteng City-Region Observatory Quality of Life (GCRO QoL) Survey IV-2015/16 (GCRO, 2016), which asks a wide range of questions, and the response options vary significantly. For instance, some questions have binary responses while others have multiple possible responses, such as those captured by a Likert scale. To generate similar units of measurement, all indicators were normalised using a standard ordinal ranking procedure. Normalisation is a simple technique whereby all variables are scored consistently so that the lowest rank always indicates the worst outcomes and the highest means the best in relative terms; for example, for the Health Status Indicator, a rank of 1 is assigned to individuals with very poor health; 2 for poor health; 3 for good health; and 4 for excellent health (OECD, 2008). Each capability index in our analysis was computed as a weighted average of its related normalised indicator variables. The weights were generated using multiple correspondence analysis (MCA), which is an objective statistical approach. The results of our analysis indicate that the capabilities with high scoring indices are ‘play’ and ‘senses, imagination and thought’, while ‘bodily integrity’ and ‘affiliation’ scored very low. Capability achievements vary across race, age, gender, income level and location. The results confirm the well-known heterogeneity in human conditions among South African demographic groups. However, we observe broader (in both subjective and objective dimensions) levels of deprivation that are otherwise masked in earlier studies. Policies that directly target indicators for capabilities where historically disadvantaged and vulnerable groups (such as youth, elderly and the physically challenged) are deprived are highly recommended. Given the spatial heterogeneities in capability achievements, we recommend localised interventions in capabilities that are lagging in certain areas of the province.
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    A composite index of quality of life for the Gauteng city-region: a principal component analysis approach
    (2015-03-30) Greyling, Talita
    GCRO's 'Quality of Life' survey and outputs are increasingly part of the research landscape, with both policy and academic uptake. However, to ensure that the results are as accurate as possible, we commission external reviews using alternative analytic methods, to see if they generate similar or very different findings, in addition to the in-house quality control measures in place. In this way, all spheres of government - and GCRO ourselves - can be reassured that rigorous peer review and critique is an integral part of our work. In this paper, UJ economist Talita Dalton-Greyling uses PCA (Principal Component Analysis) to re-run the 2011 Quality of life data and see if her outcomes are similar to ours - which they were. The paper also provides an interesting overview of the global move away from GDP and other economistic measurements of growth to more quality of life and/or well-being measures, and locates her and our work in a broader global context.