The data used for our analysis is drawn from the first four waves of the National Income Dynamic Study to determine the factors that influence poverty and household welfare in South Africa. Contrary to most existing studies, which have applied ordinary least squares and probit/logit models on cross-sectional data, this analysis captures unobserved individual heterogeneity and endogeneity, both via fixed effect, and via a robust alternative based on random effect probit estimation. The results from fixed effect and random effect probit indicate that levels of education of the household head, some province dummies, race of the household head, dependency ratio, gender of the household head, employment status of the household head and marital status of the household head are statistically significant determinants of household welfare. Consistent with previous research, we also found that, compared to traditional rural areas (used as reference category), households living in urban and farms are less likely to be poverty stricken, which implies that rural areas (traditional rural areas) should continue to be a major focus of poverty alleviation efforts in South Africa.
T. ZWANE is used to address possible endogeneity bias due to reverse causation between earnings and education. Aft er controlling for endogeneity, we found that an additional year of education increased an individual's earnings by 37.8 % in the full sample. Interestingly, the coeffi cient of education was found to be positive and statistically signifi cant in both samples (urban and rural), reinforcing the results of the full sample. However, despite the coeffi cient of years of education being similar in direction (positively associated to earnings) across all samples, our results show that the education impact on individual earnings was higher in absolute values in urban areas. Th us, the 44.4 % increase of returns to education in the urban subsample was signifi cantly higher than the increase of 33 % observed for the rural subsample. Th ese results were to be expected, given the fact that South Africa is still battling the impact of the institutionalised policies of apartheid. In addition, we found that household size, head of household's age and whether the head of household was married were important factors positively infl uencing earnings in both territorial subsamples. Th e policy implications derived from our empirical results suggest that the government should invest more heavily in academic infrastructure, particularly in rural areas where the poor live, so as to improve the educational attainment in those areas.
This paper investigates, using the first three waves of the National Income Dynamic dataset, the link between education and wages. Specifically it estimates the potential impact of the educational levels on wages in South Africa over the period 2008 – 2012. A two-stage least squares (2SLS) method is applied to account for endogeneity bias. More specifically, we use a lagged education as an instrumental variable in a two-stage least squares framework. Our results show that the proposed instruments is relevant and that there is an unambiguously positive effect on the wages of an individual from participation in education.
This paper employs a newly-available and representative National Income Dynamics Study (NIDS) data of South African households to investigate whether social grants crowd-out or displace remittances. The estimated results based on full sample reveal that while the social grants have a negative impact on the amount of remittances received, the effect is statistically insignificant – social grants do not crowd out or displace remittances. The coefficient on the social grant is also insignificant in both sub-samples (rural and urban), consistent with the results on the full sample
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