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Can South Africa celebrate the International Day for the Eradication of Poverty?


The answer to this question is a unanimous 'YES"......... and "NO". Programmes implemented since 1994 such as the social grants has seen a dramatic improvement in the welfare of many South Africans. This is reflected in the annual monitoring of Living Standard Measures (LSM) that has shown a systematic decline in the LSMs 1-3 in rural areas and LSM 6 in urban areas as people in these classes move up the LSM continuum. However, income inequality still remains resistantly high and the reality is that the 10 municipalities shown to be the most impoverished in 2004 are probably still the worst off after 13 years.

The article below was published in 2004 by the author while at the Human Sciences Research Council (HSRC). It is a stark reminder of where we have come from and what still needs to be done to bring millions of South Africans into a better quality of life. Much of this can be done with the use of geospatial information and appropriate policies and programmatic interventions.

INTRODUCTION

New estimates of poverty show that the proportion of people living in poverty in South Africa has not changed significantly between 1996 and 2001. However, those households living in poverty have sunk deeper into poverty and the gap between rich and poor has widened. The Human Sciences Research Council (HSRC) in collaboration with Mr Andrew Whiteford, a South African economist, has generated these estimates.

Approximately 57% of individuals in South Africa were living below the poverty income line in 2001, unchanged from 1996. Limpopo and the Eastern Cape had the highest proportion of poor with 77% and 72% of their populations living below the poverty income line, respectively. The Western Cape had the lowest proportion in poverty (32%), followed by Gauteng (42%). See Table 1.

The HSRC has estimated poverty rates for each municipality. The majority of municipalities with the lowest poverty rates are found in the Western Cape. These include Stellenbosch (23%) and Saldanha Bay (25%). The major city with the lowest poverty rate is Cape Town (30%). Pretoria and Johannesburg have somewhat higher rates of 35% and 38%, respectively, while Durban has a rate of 44%. The poorest municipality is Ntabankulu in the Eastern Cape, where 85% of its residents live below the poverty line. The figure below shows that seven of the 10 poorest municipalities are located in the Eastern Cape while two are located in Limpopo and one in the Free State.

Figure 2. Poverty rate (%) in South African municipalities (see map above)

While the poverty rate measures the proportion of a region’s population living below the poverty line it does not give any indication of how far below the poverty line poor households are. For this the HSRC has used a measure called the poverty gap that measures the required annual income transfer to all poor households to bring them out of poverty. The HSRC study has shown that the poverty gap has grown from R56-billion in 1996 to R81-billion in 2001 indicating that poor households have sunk deeper into poverty over this period.

With its large, poor population KwaZulu-Natal has the biggest poverty gap (R18 billion). The Eastern Cape and Gauteng follow KwaZulu-Natal. The Gauteng’s poverty gap has grown faster between 1996 and 2001 than all other provinces. This is probably a result of its population growth rapidly exceeding economic growth. Among municipalities, Durban has the largest poverty gap, followed by Johannesburg and East Rand.

The poverty gap has grown faster than the economy indicating that poor households have not shared in the benefits of economic growth. In 1996 the total poverty gap was equivalent to 6.7% of gross domestic product (GDP); by 2001 it had risen to 8.3%.

The fact that poorer households have not shared in the proceeds of economic growth is reflected in the rise in inequality between rich and poor. To measure inequality the HSRC have used the Gini coefficient, which can vary from 0 in the case of a highly even distribution of income, to 1 in the case of a highly unequal distribution. South Africa’s Gini coefficient rose from 0.69 in 1996 to 0.77 in 2001. While historically South Africa has had one of the most unequal distributions of income in the world this rise is likely to place it at the top of the world rankings.

In the past inequality in South Africa was largely defined along race lines. It has become increasingly defined by inequality within population groups as the gap between rich and poor within each group has increased substantially The Gini coefficient for the African population has risen from 0.62 in 1991 to 0.72 in 2001. This level of inequality is comparable with the most unequal societies in the world. The white population has a Gini coefficient of 0.60 that is extremely high for a group whose education and occupational profile matches that of societies in highly industrialised countries.

Table 2. Gini coefficient by population group

METHODOLOGY

Aggregate Poverty Gap

The poverty gap measures the difference between each poor household’s income and the poverty line. Thus, it measures the depth of poverty of each poor household. The aggregate poverty gap is calculated by summing the poverty gaps of each poor household. Therefore, it is equivalent to the total amount by which the incomes of poor households need to be raised each year to bring all households up to the poverty line and, hence, out of poverty. The poverty line varies according to household size, the larger the household the larger the income required to keep its members out of poverty. The poverty lines used were based on the Bureau of Market Research’s Minimum Living Level.

Table 3. Poverty income by household size (R per month)

In order to calculate the aggregate poverty gap a cross tabulation of household income by household size, municipality and race was drawn from the 2001 census. This data, viewed together with the poverty income data shown in Table 1, enables the number of households living in poverty and the poverty gap of each poor household to be determined. The poverty gap of each poor household was summed to arrive at the aggregate poverty gap for each municipality.

Gini Coefficient

The Gini coefficient is a summary statistic of income inequality that varies from 0 (in the case of perfect equality where all households earn equal income) to 1 (in the case where one household earns all the income and other households earn nothing).

Figure 2. Lorenz curve

The Gini coefficient is calculated from the Lorenz curve that plots the cumulative percentages of total income received against the cumulative number of recipients, starting with the poorest household. Figure 2 shows a hypothetical Lorenz curve. The Gini measures the area between the Lorenz curve and a hypothetical line of absolute equality, expressed as a percentage of the maximum area under the line. In geometric terms the Gini coefficient is measured as:

In a situation of perfect equality the Lorenz curve would overlap the line of perfect equality and the Gini coefficient would equal zero. In the theoretical situation of one household earning all the income, the Lorenz curve would coincide with the axes and the Gini coefficient would equal one.

The Gini coefficient was estimated for each municipality by calculating the area between the Lorenz curve and the line of perfect equality. As census income data is presented in income categories an assumption was made that each household in an income category earns the category midpoint. Under this assumption the Lorenz curve is a series of connected chords.

AVAILABLE GEOINFORMATION

Using the National Treasury's poverty line, Africascope is able to provide geospatial data on poverty for South Africa at a detailed level.


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