An application of synthetic panel data to poverty analysis in South Africa
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There is a wide-reaching consensus that data required for poverty analysis in developing countries are inadequate. Concerns have been raised on the accuracy and adequacy of household surveys, especially those emanating from Sub-Saharan Africa. Part of the debate has hinted on the existence of a statistical tragedy, but caution has also been voiced that African statistical offices are not similar and some statistical offices having stronger statistical capacities than others. The use of generalizations therefore fails to capture these variations. This thesis argues that African statistical offices are facing data challenges but not necessarily to the extent insinuated. In the post-1995 period, there has been an increase in the availability of household surveys from developing countries. This has also been accompanied by an expansion of poverty analyses efforts. Despite this surge in data availability, available household survey data remain inadequate in meeting the demand to answer poverty related enquiry. What is also evident is that cross sectional household surveys were conducted more extensively than panel data. Resultantly the paucity of panel data in developing counties is more pronounced. In South Africa, a country classified as ‘data rich’ in this thesis, there exists inadequate panel surveys that are nationally representative and covers a comprehensive period in the post-1995 period. Existing knowledge on poverty dynamics in the country has relied mostly on the use of the National Income Dynamic Study, KwaZulu Natal Dynamic Study and smaller cohort-based panels such as the Birth to Twenty and Birth to Ten cohort studies that have rarely been used in the analysis of poverty dynamics. Using mixed methods, this thesis engages these data issues. The qualitative component of this thesis uses key informants from Statistics South Africa and explores how the organization has measured poverty over the years. A historical background on the context of statistical conduct in the period before 1995 shows the shaky foundation that characterised statistical conduct in the country at the inception of Statistics South Africa in 1995. The organization since then has expanded its efforts in poverty measurement; partly a result of the availability of more household survey data. Improvements within the organization also are evidenced by the emergence of a fully-fledged Poverty and Inequality division within the organization. The agency has managed to embrace the measurement of multidimensional poverty. Nevertheless, there are issues surrounding available poverty related data. Issues of comparability affect poverty analysis, and these are discussed in this thesis. The informants agreed that there is need for more analysis of poverty using available surveys in South Africa. Against this backdrop, the use of pseudo panels to analyse poverty dynamics becomes an attractive option. Given the high costs associated with the conduct of panel surveys, pseudo panels are not only cost effective, but they enable the analysis of new research questions that would not be possible using existing data in its traditional forms. Elsewhere, pseudo panels have been used in the analysis of poverty dynamics in the absence of genuine panel data and the results have proved their importance. The methodology used to generate the pseudo panel in this thesis borrows from previous works including the work of Deaton and generates 13 birth cohorts using the Living Conditions Surveys of 2008/9 and 2014/15 as well as the IES of 2010. The birth cohorts under a set of given assumptions are ‘tracked’ in these three time periods. The thesis then analysed the expenditure patterns and poverty rates of birth cohorts. The findings suggested that in South Africa, expenditures are driven mostly with incomes from the labour market and social grants. The data however did not have adequate and comparative variables on the types of employment to further explore this debate. It also emerged that birth cohorts with male headship as well as birth cohorts in urban settlements and in White and Indian households have a higher percentage share of their income coming from labour market sources. On the other hand, birth cohorts with female headship and residing in rural, African and in Coloured households are more reliant on social grants. The majority of recipients of social grants receive the Child Social Grant and its minimalist value partly explains why birth cohorts reporting social grants as their main source of income are more likely to be poor when compared to birth cohorts who mostly earn their income from the labour market. Residing in a female-headed household, or in a rural area as well as in Black African and Coloured increases the chances of experiencing poverty. This supports existing knowledge on poverty in South Africa and confirms that these groups are deprived. The results of the pseudo panel analysis also show that poverty reduced between 2006 and 2011 for most birth cohorts but increased in 2015. Policy recommendations to reduce poverty therefore lie in the labour market. However, given the high levels of unemployment in the country today, more rigorous labour incentives are required.