Abstract
The high levels of unemployment in South Africa have resulted in high levels of poverty and inequality. The majority of impoverished people do not have the means to create increased meaning in their lives, leading to low levels of life satisfaction. This paper investigates the determinants of life satisfaction in a poor community. With nearly half of the South African population living in poverty, the question of which variables predict life satisfaction, with specific reference to poor communities, could be asked. The literature indicates that a number of variables can be predictors of life satisfaction in poor areas. The research methodology includes a quantitative household survey in a traditional poor township in southern Gauteng, namely Sicelo. The satisfaction with life scale (SWLS) was used to determine levels of life satisfaction, and a logistic regression analysis was utilised to determine which variables predict life satisfaction. The results of the research confirm that poor communities have relatively low levels of life satisfaction and that specific variables could predict life satisfaction. The logistic regression analysis indicated variables that predict life satisfaction including income levels, employment status, poverty status and government services amongst others. The implication of the research is that policy formulators should also look at the subjective quality of life indicators when compiling and refining policies. This research provides valuable insights into the predictors of life satisfaction of poor people in a traditional South African township.
Original language | English |
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Pages (from-to) | 163-171 |
Number of pages | 9 |
Journal | Mediterranean Journal of Social Sciences |
Volume | 5 |
Issue number | 13 SPEC. ISSUE |
DOIs | |
Publication status | Published - Jun 2014 |
Externally published | Yes |
Keywords
- Binary logistic regression
- Determinants
- Life satisfaction
- Poverty
- Sicelo township
ASJC Scopus subject areas
- General Arts and Humanities
- General Social Sciences
- Economics, Econometrics and Finance (all)