Introduction: The prevalence of bad perceived health status and depression, their sociodemographic determinants (education level, employment status, relative household income, race, age and gender) and the modifying effect of depression on PHS have been investigated among a cohort of young adults using data from the South African National Income Dynamics Study (NIDS) waves 1-5. South Africa is a middle-income country, with very high levels of socioeconomic inequality and a history of apartheid. Both depression and PHS tend to be affected by socio-demographic and environmental factors. Methods: Depression was measured using the CES-D-10 scale and PHS was measured on a 5- point likert scale ranging from excellent to poor. A binary version of PHS was generated which groups the categories excellent, very good and good into good and the categories poor and fair into bad PHS. Descriptive analysis and Mixed Effects Regression analysis were conducted. MER is appropriate for unbalanced panels as this method is robust to irregularly spaced measurements. Results: A high prevalence of depression was found in the study with about 13%-20% of the cohort being depressed at each wave. Surprisingly, a low level of bad PHS has been found in the cohort with less than 5% of the young adults having bad PHS at all waves. Completion of secondary and tertiary education and being employed have been found to significantly lower the odds of being depressed and increase the chances of having good PHS. Africans were significantly more likely to be depressed, as compared to other racial groups. Finally, being depressed was found to reduce the likelihood of good PHS. Discussion: Education level completed and being employed have been found to significantly protect individuals from being depressed and to increase the likelihood of good PHS. In post-apartheid South Africa, the effects of inequalities arising from apartheid social and economic policies are still present with Africans being found more likely to be depressed.

Magister Commercii - MCom / There have been many studies focussing on informal sector in South Africa in the last 25 years. This paper adds to the wealth of research that has been conducted in this field. It examines the linkages between the formal sector and informal sector, and how they interact with each other. The study uses probit models and fixed effects models to investigate how variables such as age, education and skill level affect employability and income in the labour market. This paper uses two data sets: wave 1 to wave 5 panel data of the 2008-2016 National Income Dynamics Study (NIDS) to investigate the nature of the formal sector and the informal sector in South Africa. To study the linkages between the firms in the formal and informal sector, it uses the eThekwini Large and Medium Manufacturing Firm Survey dataset collected in 2013/2014.