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Strategies aimed at reducing poverty need to identify factors that are strongly associated with poverty and that could be influenced by policy changes. The study reported here used household level data to analyze determinants of household poverty in a South Africa Township of Bophelong. A Logistic regression was estimated based on this data with the economic status (that is poor and non-poor) as the dependent variable and a set of demographic variables as the explanatory variables. The results show that household size, age and the employment status of the household head significantly explain the variations in the likelihood of being poor. The age and employment status of the household head reduces the probability of being poor, whereas household size is associated with an increased probability of being poor. The strongest predictor of poverty status is the employment status of the household head.
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