| dc.description.abstract | In post-apartheid South Africa, the thrust of macroeconomic framework and corresponding policies
inaugurated by the first democratically elected government have been geared towards, amongst
others, poverty alleviation, employment creation and economic growth. To date, South Africa still
faces many challenges in the fight against poverty. These challenges are characterised by a dynamic
nature, in that certain people transition in and out of poverty, whilst others remain deeply rooted in
chronic poverty. Injecting resources towards addressing this complex nature of poverty is still one
of the major problems faced by the South African government.
In spite of the fact that there are many money-metric studies on poverty in South Africa, these
studies failed to accurately depict the dynamic nature of poverty; throughout the years, many
studies have only attempted to examine poverty using static analysis by comparing cross-sectional
household surveys. It is for this foremost mentioned reason that these studies have produced
information that is inadequate for the elimination of persistent poverty. Examining and identifying
the characteristics of the different groups of poor using longitudinal data for the purpose of
comparing poverty levels and trends observed over time perhaps better capture the nature of
poverty in South Africa. Hence, in this study, panel data will be utilised to investigate the dynamic
aspect of poverty for the evaluation of dynamics at the individual level.
Using the balanced component of the panel data from the first four available waves of the National
Income Dynamics Study (NIDS) conducted in 2008-2015, the empirical findings indicate that the
followings individuals are significantly more likely to be chronically poor: female Africans without
Matric, aged younger than 25 years at the time of the first wave in 2008 (mean age being slightly
above 20 years), living in traditional areas or farms in the KwaZulu-Natal, Eastern Cape, Limpopo,
Northern Cape, Mpumalanga and Free State provinces, and inactive in the labour market. Also,
they came from households headed by unemployed female Africans with relatively higher mean
dependency ratio (above one) and household size (about seven) with either none or only one
employed member, as well as associated with a greater likelihood of the households receiving
social grant income and having inferior non-income welfare. | |
