An analysis and application of different methodologies for measuring poverty in Sharpeville
Sekatane, Mmapula Brendah
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This thesis studies the different methodologies for measuring poverty in Sharpeville. The study focuses on two main areas, namely, an analysis and application of the methodologies used by Stats SA and Slabbert for measuring poverty. The two methodologies are applied on the same set of data from the 2004 household survey from Sharpeville. When measuring poverty, Stats SA determines a proxy income for households and compares it with a standard poverty line which causes this methodology to be inaccurate. The methodology used by Stats SA to determine the headcount index also does not lend itself to determine the poverty gap, as proxy income values are used instead of real income values. This measure, therefore, does not show how far the poor are below the poverty line. Slabbert measures poverty by comparing the total income of households' with their respective poverty lines, determined by calculating a basket of necessities for each and every member of the household. The methodology used by Slabbert proves to be more accurate and can, in addition, determine the depth of poverty (the poverty gap). Economic impact assessments can also be conducted through Slabbert's method, such as the impact of an increase in child grants and the impact of an increase in basic income. Applying the two methodologies on the same set of data from Sharpeville, this thesis shows that the Stats SA poverty measure that is used country-wide does not accurately identify the poor population. The population in Sharpeville is estimated at 41,031 and the average household size is 4.9, meaning that there are 8,374 households in Sharpeville. Using Slabbert's method, the headcount index as calculated from the 2004 survey data for Sharpeville is 0.431, meaning that from the 8,374 households in Sharpeville, 3,609 households live in poverty. That means 17,685 people are poor in Sharpeville. The poverty gap index was determined at 0.32, indicating that on average poor households lack 32% of the necessary income to attain a level equal to their poverty line. When employing Stats SA's measure of poverty different results are found. Stats SA's 2001 poverty line of R800 was inflated to 2004 by the CPI to give a poverty line of R963.73, and that poverty line (R963.73) compared with the actual household income from the 2004 survey data to give a headcount index of 0.155, of which the An analysis and application of different methodologies for measuring poverty in . . . 111 Sharpeville following is determined. The population is still estimated to be 41,031 and the average household 4.9, meaning that there are 8,374 households, same as above. However, when the inflated Stats SA's poverty line is used it indicates that the percentage of poor households is reduced from 43.1% to 15.5%, meaning that the headcount index is reduced from 0.431 to 0.155. A headcount index of 0.155 means that from the 8,374 households in Sharpeville, 1,299 households live in poverty. This means that 6,365 people are poor in Sharpeville. It is evident from the figures above that when Stats SA methodology is employed the poverty rate is lower than the one determined by Slabbert. When the poverty rate is low it leads to a lower number of households and people that are being determined as poor and this will mislead policy makers as it does not to reflect the true state of affairs of the inhabitants of the townshiplsquatter areas of Sharpeville with regard to poverty. This thesis suggests that the Census questionnaire should be revised to ask households1individuaIs to reveal their exact income as it is currently not the approach. To accommodate those households/individuals who don't feel comfortable revealing their income or those who don't have fixed incomes, the Census questionnaire can have two options for revealing income, with option one for exact income and option two for a category. This thesis also suggests that Stats SA should change its practice of employing a standard poverty line, and instead, determine a poverty line for each household and compare this to actual household income. Thus, the headcount index and poverty gap can be accurately measured since the problem with poverty is "how far are the poor below the poverty line?"
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