HIV/AIDS and Poverty in South Africa: a Bayesian Estimation

In this paper we assess the causal impact of HIV/AIDS on monetary poverty using a panel data-set from South Africa and modeling the consequences of the illness on both earnings and transfers. Two major econometric problems are likely to bias the estimation: endogeneity of the HIV/AIDS dummy variable, and autoselection of the individuals participating to the labour market or to transfers networks. We solve both of them by proposing an original framework where we include correlated fixed-effects both in the level and the participation equations, which are estimated simultaneously with original Bayesian methods. The procedure is tested and very well-behaved. Splitting the sample into urban and rural population, we show that HIV/AIDS has a significant but moderate impact on poverty for urban population, because transfers partly compensate the fall of earnings entailed by the decrease in labour market participation. On the contrary, HIV/AIDS has an important impact on poverty for the rural population because it causes a fall of transfers. Surprisingly the effect on earnings is not significant . We argue that those results can be explained by the existence of an efficient public safety net in urban settings, while in contrast private transfers are subject to moral hazard and imperfect commitment that characterize risk-sharing in rural settings.