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pro-poor growth and social protection in south africa : exploring the interactions

pro-poor growth and social protection in south africa : exploring the interactions. Haroon Bhorat & Carlene van der Westhuizen Development Policy Research Unit School of Economics University of Cape Town Presentation to the National Planning Commission, April 2011. Introduction.

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pro-poor growth and social protection in south africa : exploring the interactions

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  1. pro-poor growth and social protection in south africa: exploring the interactions Haroon Bhorat & Carlene van der Westhuizen Development Policy Research Unit School of Economics University of Cape Town Presentation to the National Planning Commission, April 2011

  2. Introduction • Consistent positive economic growth post-1994 • But what has the impact of this positive economic growth been on social welfare? • Evidence from 1995 – 2000: No major shifts in poverty levels, but increase in inequality • Release of the 2005 IES enables a 10 yr overview • Aims of the Study: • A Brief Profile of Poverty and Inequality Shifts: 1995 – 2005 • The Impact of economic growth on household poverty & inequality • The role of state social assistance and wage income in understanding economic growth, poverty and inequality outcomes

  3. Data and Methodology • 1995 and 2005 Income and Expenditure Surveys • All measures are individual poverty and inequality measures, calculated using per capita total household expenditure • Based on the standard FGT class of poverty measures and two • standard poverty lines (R322/”cost of basic needs” and R174/2$ a day in 2000 prices) • Poverty shifts without poverty lines (Cumulative Distribution Functions) • Inequality measures: Gini Coefficients, Theil-index, Lorenz Curves

  4. Poverty Shifts, by Race of HH Head Source: Statistics South Africa (1995 and 2008) and Own Calculations Notes: 1. Poverty lines are in 2000 prices 2. At both poverty lines, the changes in the headcount rate are statistically significant at the 5 percent level at the aggregate and for Africans (indicated by the shaded cells) 3. The population in 1995 has been weighted by population weights according to the 1996 Census. The population in 2005 has been weighted by the household weight multiplied by the household size. The 2005 weights are based on the 2001 Census

  5. Poverty Shifts by Gender of HH Head Source: Statistics South Africa (1995 and 2008) and Own Calculations Notes: 1. Poverty lines are in 2000 prices 2. At both poverty lines, the changes in the headcount rate are statistically significant at the 5 percent level at the aggregate and for Africans (indicated by the shaded cells) 3. The population in 1995 has been weighted by population weights according to the 1996 Census. The population in 2005 has been weighted by the household weight multiplied by the household size. The 2005 weights are based on the 2001 Census

  6. Poverty Shifts without Poverty Lines Cumulative Distribution Functions for SA Source: Statistics South Africa (1995 and 2008) and own calculations Notes: 1. Per capita expenditure as converted to real per capita expenditure (expressed in 2000 prices) using the Consumer Price Index 2. The population in 1995 has been weighted by population weights according to the 1996 Census. The population in 2005 has been weighted by the household weight multiplied by the household size. The 2005 weights are based on the 2001 Census

  7. Inequality Shifts by Race: Gini Coefficients Source: Statistics South Africa (1995 and 2008) and own calculations Notes: 1. The changes in the values of the Gini coefficients between 1995 and 2005 are statistically significant at the 5 percent level, with the exception of Africans (indicated by the shaded cells) 2. The population in 1995 has been weighted by population weights according to the 1996 Census. The population in 2005 has been weighted by the household weight multiplied by the household size. The 2005 weights are based on the 2001 Census

  8. Lorenz Curves for Africans and Whites Source: Statistics South Africa (1995 and 2008) and own calculations Notes: The population in 1995 has been weighted by population weights according to the 1996 Census. The population in 2005 has been weighted by the household weight multiplied by the household size. The 2005 weights are based on the 2001 Census

  9. Inequality within and between Race Groups, using the Theil Index Source: Statistics South Africa (1995 and 2008) and own calculations Notes: The population in 1995 has been weighted by population weights according to the 1996 Census. The population in 2005 has been weighted by the household weight multiplied by the household size. The 2005 weights are based on the 2001 Census

  10. Relationship between Growth, Poverty and Inequality • Growth a necessary but not sufficient condition for poverty reduction • What is the role of inequality in the growth process? • Utilise GIC methodology to examine GPI interactions • The role played by social assistance in the growth, poverty inequality dynamic in South Africa

  11. Growth Incidence Curve: South Africa, 1995 – 2005 Source: Statistics South Africa (1995 & 2008), own calculations Notes: 1. Frequency weights are assumed with the population in 1995 weighted according to the 1996 Census and the population in 2005 weighted according to the 2001 Census 2. Figures are annualised growth rates

  12. GIC: African Headed Households, 1995 - 2005 Source: Statistics South Africa (1995 & 2008), own calculations Notes: 1. Frequency weights are assumed with the population in 1995 weighted according to the 1996 Census and the population in 2005 weighted according to the 2001 Census 2. Figures are annualised growth rates

  13. Measures of Pro-poor Growth by Race, 1995 - 2005 Source: Statistics South Africa (1995 & 2008), own calculations Notes: 1. Frequency weights are assumed with the population in 1995 weighted according to the 1996 Census and the population in 2005 weighted according to the 2001 Census 2. Figures are annualised growth rates

  14. Expenditure at the Top of the Distribution, Average Annual Growth Rates, 1995 - 2995 Source: Statistics South Africa (1995 & 2008), own calculations Notes: 1. Frequency weights are assumed with the population in 1995 weighted according to the 1996 Census and the population in 2005 weighted according to the 2001 Census 2. Figures are annualised growth rates

  15. Percentage of Population with Access to Wage Income, 1995 - 2005 Source: Statistics South Africa (1995 & 2008), own calculations Notes: 1. Frequency weights are assumed with the population in 1995 weighted according to the 1996 Census and the population in 2005 weighted according to the 2001 Census 2. Figures are annualised growth rates

  16. Social Grants Beneficiary Numbers by Type of Grant, 1997 - 2011 Source: Pauw & Mncube (2007), calculated using data from National Treasury, and Budget Review 2011/2012 Note: The child support grant was introduced in 1998, the 1997 beneficiaries shown in the table therefore corresponds to the child maintenance grant. 1 Projected numbers at fiscal year-end.

  17. Determinants of Growth in Expenditure of the Poor since 1995 • Impact of Social Grants • Number of beneficiaries has increased from about 3 million in Aug 1997 to 13.8 million in 2010/2011 • Driven by the extension of the Child Support Grant (< 1 million in 2001 to 9.4 million in 2010/2011)

  18. HH Access to Social Grants per Household Income Deciles, 1995 and 2005 Source: Statistics South Africa (1995 and 2008) and own calculations Notes: The population in 1995 has been weighted according to the 1996 Census, while the population in 2005 has been weighted according to the 2001 Census. In both datasets, the population has been weighted by the household weight multiplied by the household size.

  19. Per Capita Grant Income as Proportion of Total HH Income, 1995 and 2005 Source: Statistics South Africa (1995 and 2008) and own calculations Notes: The population in 1995 has been weighted according to the 1996 Census, while the population in 2005 has been weighted according to the 2001 Census. In both datasets, the population has been weighted by the household weight multiplied by the household size.

  20. Gini Coefficients for Total Per Capita Income with and without Grant Income by Race, 1995 and 2005 Source: Statistics South Africa (1995 and 2008) and own calculations Notes: 1. The changes in the values of the Gini coefficients between 1995 and 2005 are “in bold” when the results are statistically significant at the 95 percent level. 2. The population in 1995 has been weighted according to the 1996 Census, while the population in 2005 has been weighted according to the 2001 Census. In both datasets, the population has been weighted by the household weight multiplied by the household size.

  21. Lorenz Curves for Africans: With and Without Grant Income, 1995 and 2005 Source: Statistics South Africa (1995 and 2008) and own calculations Notes: 1. The changes in the values of the Gini coefficients between 1995 and 2005 are statistically significant at the 95 percent level. 2.The population in 1995 has been weighted according to the 1996 Census, while the population in 2005 has been weighted according to the 2001 Census. In both datasets, the population has been weighted by the household weight multiplied by the household size.

  22. Growth Incidence Curves for SA:Income including Grant Income, 1995 and 2005 Source: Statistics South Africa (1995 & 2008), own calculations Notes: 1. Frequency weights are assumed with the population in 1995 weighted according to the 1996 Census and the population in 2005 weighted according to the 2001 Census 2. Figures are annualised growth rates

  23. Growth Incidence Curves for SA : Income excluding Grant Income, 1995 and 2005 Source: Statistics South Africa (1995 & 2008), own calculations Notes: 1. Frequency weights are assumed with the population in 1995 weighted according to the 1996 Census and the population in 2005 weighted according to the 2001 Census 2. Figures are annualised growth rates

  24. Rates of Pro-poor Growth for South Africa, 1995 and 2005 Source: Statistics South Africa (1995 & 2008), own calculations Notes: 1. Frequency weights are assumed with the population in 1995 weighted according to the 1996 Census and the population in 2005 weighted according to the 2001 Census 2. Figures are annualised growth rates

  25. Growth Incidence Curves for Rural HH’s : Income including Grant Income, 1995 and 2005 Source: Statistics South Africa (1995 & 2008), own calculations Notes: 1. Frequency weights are assumed with the population in 1995 weighted according to the 1996 Census and the population in 2005 weighted according to the 2001 Census 2. Figures are annualised growth rates

  26. Growth Incidence Curves for Rural HH’s : Incomeexcluding Grant Income, 1995 and 2005 Source: Statistics South Africa (1995 & 2008), own calculations Notes: 1. Frequency weights are assumed with the population in 1995 weighted according to the 1996 Census and the population in 2005 weighted according to the 2001 Census 2. Figures are annualised growth rates

  27. Conclusions • Poverty: • Significant (at 5 % level) decline in absolute and relative poverty at the aggregate, for African- and female-headed HHs: Shift is invariant to choice of any feasible poverty line • Inequality: • Income Inequality: Significant increase (at 5 % level) in Gini coefficient at • national level • Positive economic growth has delivered decrease in poverty, but sharp increases in inequality • The incomes of those at the bottom of the distribution are supported through social transfers: is this a desirable and/or sustainable growth and development trajectory?

  28. Conclusions • Growth Incidence: • Absolute pro-poor growth evident • Large changes at the top end....the “missing middle”? • Rise in incomes at the bottom end of the distribution • Social Assistance Comes to the Rescue of an Unequal Growth Path • Nature of the Growth Path: • The incomes of those at the bottom of the distribution are supported through social transfers: • Is this a sustainable growth and development trajectory? • Why is the labour market not functioning optimally within those households at the bottom of the distribution?

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