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ABSTRACT
Given the rapid scale-up of antiretroviral treatment (ART), it is necessary to explore the impact of ART on labour force participation, employment and labour productivity. This article investigates labour market outcomes in a prospective cohort of public-sector ART clients in the Free State province of South Africa. Empirical results suggest that labour force participation increased markedly as the proportion of those too ill to work declined, becoming indistinguishable from participation rates in the general population. Unemployment rates, however, remain above those reported for the general population. ART and its health-related benefits therefore translate into increases in labour force participation, but not employment. Employment status at HIV diagnosis strongly predicts absorption in the labour force. Public-sector ART clients should be referred to vocational rehabilitation and occupational therapy programmes, and to welfare-to-work programmes, and the unskilled to adult education and training and further education and training programmes.
Acknowledgements
The authors thank the study participants and the fieldwork staff as well as the Free State Department of Health and the National Health Laboratory Service.
Notes
1 The public-sector ART programme did not commence simultaneously in all five health districts. The original sampling frame excluded patients eligible for ART (i.e. CD4 ≤ 200 and/or WHO AIDS stage 4) but who were not certified as ready to commence with treatment by a physician, in many cases due to patients having to first complete their tuberculosis treatment. The results thus cannot be generalised to all patients eligible for ART, but rather to public-sector patients ready to commence ART.
2 In Xhariep district, the list included less than 80 patients: as a result, all treatment and non-treatment cases were included in the study.
3 Theoretically, the data also allow an investigation of predictors of labour market transitions, such as becoming a labour force participant, gaining employment or being newly absorbed in the labour force. Unfortunately, the numbers of transitions in the dataset are relatively small, which substantially reduces the statistical power of the ensuing FE multivariate regression analyses, given the ‘expensive [nature of FE] in terms of degrees of freedom’ (Gujarati, Citation2003:647) as a result of losing those observations where yit =0 for all t or yit =1 for all t (Cameron & Trivedi, Citation2009:614).
4 The labour market indicators and definitions used in the LFS comparisons correspond to those used by Statistics South Africa in its LFSs and Quarterly Labour Force Surveys. Unemployment refers to all individuals aged 15 to 64 years who were not employed in the seven days preceding their interviews; who were willing and able to work during this time, while having taken active steps to find employment in the four weeks prior to the interview. Labour force participants are either employed or unemployed, while the labour force participation rate is obtained by dividing the number of labour force participants by number of people aged 15 to 64 years. The labour force absorption rate is obtained by dividing the number of employed individuals by the number of individuals aged 15 to 64 years.
5 Admittedly, the general economic upswing experienced in South Africa during 2006/07 may play an important part in explaining the observed trends in labour market outcomes during this period. However, it is not possible to determine its role in explaining these trends in the absence of comparable data for a representative panel of economically active individuals in the Free State province.