1. THE SOUTH AFRICA I KNOW, THE HOME I UNDERSTAND STATS SA Census Education level of the labour force, 2011 Assets and capabilities poverty in South Africa Sandile Simelane Statistics South Africa 1

2. THE SOUTH AFRICA I KNOW, THE HOME I UNDERSTAND STATS SA Census Education level of the labour force, 2011 Outline Background Research questions Data & methods Results Discussion, conclusions & policy implications 2

3. THE SOUTH AFRICA I KNOW, THE HOME I UNDERSTAND STATS SA Census Education level of the labour force, 2011 Background This paper uses a composite index of household assets and capabilities data to examine levels and trends of poverty for provinces, district councils (DCs) and local municipalities of South Africa. The resulting index: the assets and capabilities poverty (ACP) – Calculated at household level – demonstrates that poverty can be measured in the absence of income or expenditure data. – The index of ACP is a complement not replacement of income & expenditure measures of poverty 3

4. THE SOUTH AFRICA I KNOW, THE HOME I UNDERSTAND STATS SA Census Education level of the labour force, 2011 Background contd…. Motivations for the approach 1.The paper conceptualizes poverty as a multidimensional phenomenon that can be proxied by the socioeconomic variables that are commonly collected in pop. censuses and household surveys. 2.South Africa’s current socio-economic policy (RDP) states that meeting basic needs for all in the country’s population is the top priority for government. 3.Income data are poorly measured in LDCs (Bollen, Glanville and Stecklov 2001; World Bank 1995), including South Africa (Statistics South Africa 2000). 4.The index used has been found to be a good measure of wealth in other developing countries (Filmer and Pritchett 2001). 4

5. THE SOUTH AFRICA I KNOW, THE HOME I UNDERSTAND STATS SA Census Education level of the labour force, 2011 Research questions Who are assets and capabilities poor in South Africa and what has been the trend in poverty levels between 1996 and 2007? How are the are the assets and capabilities poor (hholds/ individuals) distributed, spatially, in the country? What are the defining characteristics of the poor? 5

6. THE SOUTH AFRICA I KNOW, THE HOME I UNDERSTAND STATS SA Census Education level of the labour force, 2011 Data & methods Data Pooled dataset comprising the 2007 CS and the 1996 & 2001 censuses of South Africa Revisions to this work will include census 2011 Q. Why pooled data? A. To control for the cross-dataset differences in the distribution of the variables used & derive estimate that are comparable across the datasets. CS 2007 – Large sample survey – Representative at municipality level 6

7. THE SOUTH AFRICA I KNOW, THE HOME I UNDERSTAND STATS SA Census Education level of the labour force, 2011 Data & methods contd… Methods Identification of Assets & Capabilities poor households Step 1: Computation of the index Index of ACP computed using Principal Components Analysis (PCA) by combining information on 8 categories of household assets/characteristics and 2 measures of household functional capabilities. 7

8. THE SOUTH AFRICA I KNOW, THE HOME I UNDERSTAND STATS SA Census Education level of the labour force, 2011 8 Data & methods contd… About PCA PCA is a statistical procedure that reduces the dimensionality of multiple variables by transforming them into few linear components that are uncorrelated. For each component, PCA assigns to each observation (household) a scoring factor based on the household’s possession (or lack) of the variables included in the computation, after taking into account the covariation of these variables in the population being studied. – These scores can be used to sort the observations (households) from the poorest to the wealthiest. The 1 st component accounts for the largest proportion of the total variation in the set of variables used. For this reason, the 1 st component is used as the index of ACP.

9. THE SOUTH AFRICA I KNOW, THE HOME I UNDERSTAND STATS SA Census Education level of the labour force, 2011 9 Data & methods contd… Hhold asset/characteristics 1. Telephone/ cell phone [yes/no] 2. Type of dwelling structure [modern; traditional/informal; other/caravan/tent] 3. Type of toilet [flush/chemical; pit latrine/bucket; no toilet/other e.g. open land] 4. Source of water [piped water inside; piped water outside; public tap; other source] 5. Refuse removal [local auth/private co.; communal/own dump; no disposal facility] 6. Energy for cooking [ electricity/gas, paraffin, wood/coal/animal dung/other ] 7. Energy for lighting [ electricity/gas, paraffin, wood/coal/animal dung/other ] 8. Energy for heating [ electricity/gas, paraffin, candles/other ] Capabilities 1. Adult employment ratio 2. Proportion of adults with high school education & above Variables used in PCA 23 binary variables & 2 continuous variables

10. THE SOUTH AFRICA I KNOW, THE HOME I UNDERSTAND STATS SA Census Education level of the labour force, 2011 10 Data & methods contd… Assessment of the index The scoring factors are all in the expected direction. – All the variables associated with higher SES—e.g. having piped water inside the dwelling—have bigger (and +ve) scoring factors than those that are perceived to measure lower levels of SES

11. THE SOUTH AFRICA I KNOW, THE HOME I UNDERSTAND STATS SA Census Education level of the labour force, 2011 11 Data & methods contd… Identification of Assets & Capabilities poor households Step 2: Calculation of the poverty line Poverty line = ½ median value of index of ACP. – based on theory of Justice as Fairness (Rawls 1971) Thus estimate of poverty level in a give geographic unit =

12. THE SOUTH AFRICA I KNOW, THE HOME I UNDERSTAND STATS SA Census Education level of the labour force, 2011 12 Data & methods contd… Analysis of characteristics of poor households Logistic regression model is employed pTi = probability that household (i) is classified as poor in year T Explanatory variables include: sex of the head of household; rural/ urban residence; province; age of household head; tenure status of dwelling unit; type of residence; crowding; etc. NB: No causality implied

13. THE SOUTH AFRICA I KNOW, THE HOME I UNDERSTAND STATS SA Census Education level of the labour force, 2011 13 Data & methods contd… Statistical analysis of spatial distribution of poor households Moran’s I = global test for clustering/ autocorrelation – Operates like correlation coefficient

14. THE SOUTH AFRICA I KNOW, THE HOME I UNDERSTAND STATS SA Census Education level of the labour force, 2011 14 Data & methods contd… Statistical analysis of spatial distribution of poor households Local indicator of spatial association (LISA) statistics Interpretation of LISA positive Ii means either a high value is surrounded by high values (high-high) or a low value is surrounded by low values (low-low). A negative score of Ii means either a high value is surrounded by low values (high-low) or vice versa (low-high).

15. THE SOUTH AFRICA I KNOW, THE HOME I UNDERSTAND STATS SA Census Education level of the labour force, 2011 15 Results : levels & trend Cumulative Distribution Functions (CDFs) of index of ACP, 1996-2007 Huge but declining, levels of inequality in living stds during the period 1996-2007 Decline in national level of ACP driven by improvements among the poor

16. THE SOUTH AFRICA I KNOW, THE HOME I UNDERSTAND STATS SA Census Education level of the labour force, 2011 16 Results : levels & trend Levels and trend in household assets and capabilities poverty by province, 1996-2007 Province Census 1996 Census 2001 CS 2007 Western Cape16.615.86.3 Gauteng23.82314.5 Northern Cape41.033.527.5 Free State55.149.227.2 KwaZulu-Natal55.452.548.2 North West65.45444.6 Mpumalanga65.159.360.1 Eastern Cape7366.658.3 Limpopo82.775.879.5 South Africa49.145.138.2 3 rd 3 rd 3 rd

17. THE SOUTH AFRICA I KNOW, THE HOME I UNDERSTAND STATS SA Census Education level of the labour force, 2011 17 Results contd… spatial distribution of ACP Map showing the proportion (%) of assets & capabilities poor households by local Municipality, South Africa 1996.

18. THE SOUTH AFRICA I KNOW, THE HOME I UNDERSTAND STATS SA Census Education level of the labour force, 2011 18 Results contd… spatial distribution of ACP Lisa Cluster map for ACP, 1996 Moran’s I = 0.4088, p<0.05

19. THE SOUTH AFRICA I KNOW, THE HOME I UNDERSTAND STATS SA Census Education level of the labour force, 2011 19 Results contd… spatial distribution of ACP

20. THE SOUTH AFRICA I KNOW, THE HOME I UNDERSTAND STATS SA Census Education level of the labour force, 2011 20 Results contd… spatial distribution of ACP Lisa Cluster map for ACP, 2007 Moran’s I = 0.5090, p<0.05

21. THE SOUTH AFRICA I KNOW, THE HOME I UNDERSTAND STATS SA Census Education level of the labour force, 2011 21 Results contd… spatial distribution of ACP While there was general improvement in poverty levels nationally and in FS b/t 1996 & 2007 clustering of households according to poverty status worsened during the period. Lisa Cluster map for ACP, 1996 Moran’s I = 0.4088, p<0.05 Lisa Cluster map for ACP, 2007 Moran’s I = 0.5090, p<0.05

22. THE SOUTH AFRICA I KNOW, THE HOME I UNDERSTAND STATS SA Census Education level of the labour force, 2011 22 Results contd… characteristics of assets & capabilities poor households Odds ratios from logistic regression model of probability of hhold asset & capabilities poverty on selected variables, 2007 EffectPoint Est. 95% Wald Confidence Iimits Province Western Cape (RC)1.000 Eastern Cape 4.4454.1724.736 Northern Cape 3.8443.5824.125 Free State 3.2072.9863.445 KwaZulu-Natal 3.5753.3543.810 North West 1.7611.6421.890 Gauteng 2.3622.2192.516 Mpumalanga 5.1854.8245.572 Limpopo 4.5274.2154.862 RC= reference category Likelihood of ACP highest in MP, EC, LP compared to RC A hhold in FS was 3.2 times more likely to be poor than one in WC in 2007

23. THE SOUTH AFRICA I KNOW, THE HOME I UNDERSTAND STATS SA Census Education level of the labour force, 2011 23 Results : characteristics of assets & capabilities poor households Other findings Assets & capabilities poverty highest in rural areas Household headed by females more likely to be ACP Households headed by Black Africans more likely to be poor than other groups

24. THE SOUTH AFRICA I KNOW, THE HOME I UNDERSTAND STATS SA Census Education level of the labour force, 2011 24 Discussion SA experienced huge but declining, levels of inequality in living stds during the period 1996-2007. Proportion of households that are assets & capabilities poor decreased nationally from 49.1% in 1996 to 38.2% in 2007. The same applies to Free State

25. THE SOUTH AFRICA I KNOW, THE HOME I UNDERSTAND STATS SA Census Education level of the labour force, 2011 25 Discussion ….. contd Assets & capabilities poverty highest in rural areas Household headed by females more likely to be ACP Households headed by Black Africans more likely to be poor than other groups

26. THE SOUTH AFRICA I KNOW, THE HOME I UNDERSTAND STATS SA Census Education level of the labour force, 2011 26 Criticism of the index The index is not a good indicator of performance of individual households because it is based on community variables. Reflection It is true that most of the variables included in the index are community based but in a setting like in RSA where policy is clear that ALL households should enjoy the assets/variables it important to profile the hholds that lag behind…. Conclusion