This thesis explores the multidimensional nature of poverty as well as the impact of units of analysis on the creation of poverty pictures. The multidimensional nature of poverty is explored through the comparison of income and an asset-based measure (Living Standard Measure) and is conducted across five South African Development Community countries. This is done via six main avenues of investigation: income and its predictors; the asset-based Living Standard Measure; the consistency of the Living Standard Measure; a comparison of income and the Living Standard Measure; a comparison at different units of analysis of poverty across the five countries; the multidimensional nature of poverty.
Socio-economic and political secondary data obtained from the Human Sciences Research Council was used for the comparisons. In total, 5927 respondents were drawn from the five countries. Findings from this study indicate that there is a large degree of agreement and overlap as to the poverty pictures created by income and the Living Standard Measure. There also appears to be a convergence in poverty picture created
at different levels of analysis as well as with different measures. Despite these similarities, and the fact that different dimensions and units of analysis do not alter the general poverty picture drastically, an argument is made that these two elements do have important roles in poverty measurement as they provide details to the general picture. These details have an impact on the success of the interventions chosen. In conclusion this thesis suggests that there is a possibility that the multidimensionality of poverty has been over-emphasised in recent literature. / Thesis (M.A.)-University of KwaZulu-Natal, Pietermaritzburg, 2006.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:ukzn/oai:http://researchspace.ukzn.ac.za:10413/4742 |
| Date | January 2006 |
| Creators | Von Maltzahn, Robyn. |
| Contributors | Durrheim, Kevin. |
| Source Sets | South African National ETD Portal |
| Language | en_ZA |
| Detected Language | English |
| Type | Thesis |
Page generated in 0.0018 seconds