Abstract
This paper investigates a number of factors responsible for asset poverty in South Africa. We use data from the first four waves of the National Income Dynamic Study to bring new evidence to bear on the determinants of assets poverty. We use the Principal Component Analysis (PCA) to create the asset index and the logit model to identify the main determinants of asset poverty in South Africa. Results of the logit model show that some factors such as education levels (secondary, matric and tertiary), race dummies and location dummies (farms and urban areas) have a reducing effect on asset poverty in South Africa. However, other factors - employment and household size have no significant effect on asset poverty.
Original language | English |
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Pages (from-to) | 55-78 |
Number of pages | 24 |
Journal | Journal of Economic Cooperation and Development |
Volume | 40 |
Issue number | 1 |
Publication status | Published - 2019 |
Keywords
- Asset poverty
- Kaiser-meyer-olkin
- Logit model
- Principal component analysis
ASJC Scopus subject areas
- Business and International Management
- Economics and Econometrics
- Political Science and International Relations