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Socio-economic correlates with the prevalence and onset of diabetes in South Africa: Evidence from the first four waves of the National Income Dynamics Study
No full textWe make use of multiple waves of National Income Dynamics Study data, from 2008 to 2015, to
investigate the socio‐economic factors that correlate with the prevalence and onset of diabetes. Our
analysis follows a cohort of 3470 older adults aged forty and above, who are interviewed four times
over a six-year period. We use linear probability models and estimate the likelihood of diabetes as a
function of age, race, gender, education, income, exercise, and obesity. Our primary findings are that
age and obesity correlate strongly with diabetes, while income does not have a statistically significant
effect, conditional on the other covariates. Our regression estimates indicate that, of individuals who
reported not being diabetic in Wave 1, those who were obese and morbidly obese were 12.9 and 16.7
percentage points more likely to have experienced the onset of diabetes respectively, relative to those
with a BMI in the healthy range. In addition, frequent exercise does appear to have a slight protective
effect against the onset of diabetes, and there is some evidence that better educated people have a
lower risk of onset of the disease.Velenkosini Matsebula: Researcher, SALDRU, UCT. Email: [email protected], corresponding author.
Vimal Ranchhod: Chief Research Officer, SALDRU, UCT. Email:[email protected]
Acknowledgements:
Funding for this research from the Department of Planning, Monitoring and Evaluation is gratefully
acknowledged
The Measurement and Distribution of Household Wealth in South Africa using the National Income Dynamics Study (NIDS) Wave 4
No full textThis paper examines the household wealth construct as measured in NIDS Wave 4 (2014‐2015).
Questionnaire design changes in the wealth module between NIDS Waves 2 and 4 include the addition of questions on household possessions assets and the inclusion of a variable for private property versus communal property rights. For derived household net worth, the inclusion of household possessions assets reduces estimates of household inequality in Wave 4 compared to Wave 2, and alters the portfolio composition of household assets most markedly for low income households. A unique feature of NIDS Wave 4 is that it now allows for accurate identification of South Africa’s dual land tenure system. In Tribal Authority Areas (TAAs), households rarely have to finance the acquisition of a home partly because of communal property rights. This results in a very different portfolio of household liabilities than in other areas in the country, where real estate debt dominates the liability portfolio. When comparing NIDS aggregated national totals for estimates of household assets, liabilities and net worth with South African Reserve Bank (SARB) totals that use the national accounts, the NIDS Wave 4 data differs from the SARB data most significantly for financial assets, which are severely under‐estimated in NIDS. This is likely a result of disproportionately high attrition among high‐income households in the sample over time that cannot be compensated for sufficiently with survey weights. This suggests that it is urgent that the NIDS sample be refreshed, with an oversampling of high‐income households necessary.Reza C. Daniels: School of Economics, University of Cape Town: [email protected]
Taryn Augustine: Southern Africa Labour & Development Research Unit (SALDRU): [email protected]
Acknowledgements:
Funding for this research from the Department of Planning, Monitoring and Evaluation is gratefully
acknowledged
What Difference Does A Year Make? The Cumulative Effect of Missing Cash Transfers on Schooling Attainment
No full textSouth Africa's largest poverty alleviation tool, the child support grant, has benefited more than 12 million children, with many positive outcomes. However the implementation was not perfect ‐ the means test threshold was left unadjusted for ten years, requiring a more than one hundred percent adjustment when the government finally saw fit to change the threshold in 2008. In the interim, very many children missed out on the benefits of the grant.
Using exogenous changes to the age and income threshold values, this paper estimates the cumulative impact of missing grant receipt. We find that a South African child born in 1994 missed out on a year's worth of schooling compared to those born just one year later. The costs were not limited only to schooling attainment; increasing the means test threshold and rates of receipt appears to have improved maternal mental health.Katherine Eyal: School of Economics, University of Cape Town.
Lindokuhle Njozela: School of Economics, University of Cape Town.
All correspondence to [email protected].
Acknowledgements:
Funding for this research from the Department of Planning, Monitoring and Evaluation is gratefully acknowledged
Analysing the links between child health and education outcomes: Evidence from NIDS Waves 1 – 4
No full textThe focus of this discussion paper is on the relationship between child health and education outcomes in the National Income Dynamics Study (NIDS) panel data. NIDS collects detailed information on the health status of children, including anthropometric data, and on their progression through the schooling system, providing the unique opportunity to analyse the implications of child health for human capital accumulation over the life‐cycle at the national level. The 1993 Project for Statistics on Living Standards and Development (PSLSD) also collected data on both anthropometric and education outcomes for a nationally representative sample, but only at the cross‐section, while other longitudinal studies for South Africa with this information are region‐specific, have smaller sample sizes, and are from a much earlier period.Daniela Casale: Associate Professor, Economics, University of the Witwatersrand.
[email protected]
Acknowledgements:
Funding for this research from the Department of Planning, Monitoring and Evaluation is gratefully
acknowledged
Determinants of civil war and excess zeroes
No full textThis paper considers the determinants of civil conflict, using a zero-inflated modelling approach that deals with the problem of excess zero observations, which we argue are related to two distinct data generation processes. Despite their continued use in the literature, traditional probit and logit models have limited capacity in dealing with this issue and can create misleading results. This is illustrated by estimating the model in Elbadawi and Sambanis (2002) using their data and a zero-inflated modelling procedure, which leads to results that suggest a role for the grievance variables in contrast to the original article. A general greed-grievance model is then estimated on a sample of 134 countries, over 54 years. Again, while the standard probit model results tend to emphasise opportunity variables, as found in other studies, the zero-inflated model gives more support for grievance effects. In particular, polity, ethnicity and inequality are found to play a significant role in contrast to earlier studies
How much does military spending affect growth? Causal estimates from the World’s non-rich countries
No full textWhile not always a concern for the general economic growth literature, the debate over the effects of military spending on growth continues to develop, with no consensus, but a deepening understanding of the limitations of previous work. One important issue that has not been adequately dealt with, is the endogeneity of military spending in the growth equation, mainly because of the difficulty of finding any variables that would make adequate instruments. This paper considers this issue, using an endogenous growth model estimated on a large sample of 109 non-high income countries for the period 1998-2012. The empirical analysis is framed within an instrumental variable setting that exploits the increase in military
spending that occurs when unrest in a country escalates to turmoil. The estimation results show that endogeneity arising from reverse causality is a crucial issue, with the instrumental variable estimates providing a larger significant negative effect of military spending on growth than OLS would. This result is found to be robust to different sources of heterogeneity and different time periods
The Impact of Maternal Death on Children’s Health and Education Outcomes
No full textThe HIV/AIDS pandemic continues to have a devastating impact, particularly on the lives of sub‐
Saharan African children. In addition to reversing the downward secular trend in infant and child
mortality, HIV/AIDS has orphaned millions of children. Substantial progress has been made in reducing mother‐to‐child transmission, but rates of orphanhood continue to climb despite increased availability of antiretroviral therapy. UNAIDS estimates that in sub‐Saharan Africa in 2014, 11 million children under the age of 18 had lost one or both of their parents to AIDS (UNAIDS 2016).
Recent empirical evidence suggests that children in sub‐Saharan Africa who have suffered parental
loss are at risk of poorer educational outcomes (Beegle, de Weerdt and Dercon 2006; Bicego, Bicego
et al 2003; Case, Paxson and Ableidinger 2004; Evans and Miguel 2007; Guarcello et al. 2004; Monasch and Boerma 2004; Ardington and Leibbrandt 2010; Case and Ardington 2006; Ardington 2009). In South Africa, there are significant differences in the impact of a mother and a father’s death. The loss of a child’s mother is a strong predictor of poor schooling outcomes, while the loss of a child’s father is a significant correlate of poor household socioeconomic status. In two localised longitudinal studies, Case and Ardington (2006) and Ardington and Leibbrandt (2009) use the timing of mothers’ deaths relative to children’s educational shortfalls to argue that mothers’ deaths have a causal effect on children’s education. They cannot, however, answer the question of why children whose mothers have died fall behind in school.Cally Ardington: Professor, School of Economics and Deputy Director of SALDRU, University of Cape Town: [email protected]
Megan Little: Researcher, SALDRU, UCT: [email protected]:
Funding for this research from the Department of Planning, Monitoring and Evaluation is gratefully
acknowledged
Inter-household transfers in South Africa: prevalence, patterns and poverty
No full textIn this paper, I use unique and detailed data, collected in four waves of the National Income
Dynamics Study, to provide a descriptive overview of inter‐household transfers in South Africa, including their prevalence and size, and how they compare with other developing countries. I take advantage of the panel nature of the data to investigate whether the likelihood that individuals receive or send transfers responds to changes in the economic wellbeing and composition of the individual’s household, and to the receipt of public transfers or social grants. I also use the panel data to explore persistence in private transfers over time, and to compare the relative contribution of private and public transfers to poverty reduction.Dorrit Posel: Associate Professor, Economics, University of the Witwatersrand.
[email protected]
Acknowledgements:
Funding for this research from the Department of Planning, Monitoring and Evaluation is gratefully
acknowledged
Measuring and profiling financial literacy in South Africa
No full textMicroeconomic theories of financial behaviour tend to assume that consumers possess financial skills necessary to undertake related financial decisions. We investigate this assumption by exploring the distribution of financial literacy among South Africans. In the absence of a standard measure, a financial literacy index is constructed for the country using data collected on attitudes (towards), access to and use of financial services over the period 2005 – 2009. We use the index to examine the extent to which differences in financial literacy correlate with demographic and economic characteristics. The Index reveals substantial variation in financial literacy by age, education, province and race. Overall, demographic characteristics contribute up to 10% of the financial literacy differences among individuals in South Africa. These results can be used to guide policy makers where to place more emphasis in terms of financial education for South Africans.Elizabeth Lwanga Nanziri acknowledges funding from the Carnegie Corporation and the National Research Foundation for financial support for her doctoral work.
Murray Leibbrandt acknowledges the Research Chairs Initiative of the Department of Science and Technology, and the National Research Foundation for funding his work as the Chair in Poverty and Inequality Research
Inter-household transfers in South Africa: prevalence, patterns and poverty
No full textIn this paper, I use unique and detailed data, collected in four waves of the National Income
Dynamics Study, to provide a descriptive overview of inter‐household transfers in South Africa, including their prevalence and size, and how they compare with other developing countries. I take advantage of the panel nature of the data to investigate whether the likelihood that individuals receive or send transfers responds to changes in the economic wellbeing and composition of the individual’s household, and to the receipt of public transfers or social grants. I also use the panel data to explore persistence in private transfers over time, and to compare the relative contribution of private and public transfers to poverty reduction.Dorrit Posel: Associate Professor, Economics, University of the Witwatersrand.
[email protected]
Acknowledgements:
Funding for this research from the Department of Planning, Monitoring and Evaluation is gratefully
acknowledged