1. Insights into Poverty and Inequality Pali Lehohla
Context and Reality
Pali Lehohla
Statistics South Africa

2. Beyond cyclical events such as economic boom and busts and matters of weather, The matters of demography and poverty have generational effects

3. Age structure based on CS 2016
Source: Community Survey 2016

4. Age structure based on CS 2016
The life circumstances of first demographic wave have not achieved full potential
High Unemployment/Poor Educational outcomes
Need to invest in second demographic wave to achieve outcomes not seen in their parents generation
First demographic wave: Children of 1996
Second demographic wave
Source: Community Survey 2016

5. Population pyramid, South Africa, Source: Stats SA and calculations
Male
There was a narrowing of the population pyramid base, and the working-age ratio increased from 55% in 1960 to 65% in 2010
Female

6. Demographic Transition: % Working Age Population
South Africa along with East Asian and Latin American Countries experienced a demographic transition but Economic Growth varied
Percentage
* Population aged 15–64 as a percentage of the total population

7. Real GDP per capita, average annual growth (%), 1961–2015 Growth Rates for Selected Countries
A demographic transition on its own does may not result in extended periods of high growth
South Africa’s per capita growth rate from 1961 to 2015 averaged just 1%, which was well below the East Asian growth rates and below five of the six Latin American growth rates.
Source: World Bank and calculations

8. Economic Growth
Recent performance in South Africa’s economic growth stands in sharp contrast to the target indicated in the National Development Plan (NDP).
South Africa’s historical GDP growth performance suggests that its demographic transition has very little, if anything, to show for itself in terms of producing a demographic dividend.

9. Portrait of the Growth Accounting Framework
Income Per Capita
Labour Productivity
Total Factor Productivity
Capital Deepening
Economies of Scale
Absorption
Rate
Participation Rate
Employment Rate
Job Creation
Terms of
Trade
Gainfully Employed
Working Poor
Knowledge Generating Employees
Knowledge Processing Employees
Young Dependency Ratio
Demographic
Dividend
Elderly Dependency Ratio
Demographic
Dividend

10. The outcomes at higher levels of education, show great disparity both by population group and age

11. 2016: Proportion of Matric Graduates who attain a bachelor degree
1975
1980
1985
1990
1995
2000
2005
2010
2015 16
Source: Community Survey 2016

12. Absolute vs Proportions
Source: Adapted from HE Broekhuizen (Hemis Aggregate Figures) Excludes undergraduate diplomas and certificates
Source: Adapted from HE Broekhuizen (Hemis Aggregate Figures ) with addition of population estimates for time points Excludes undergraduate diplomas and certificates

13. The disparities are played out within the employment realm

14. Not economically active*
The labour market Q2:2017
37,2 million
People of working age in South Africa (15 – 64 year olds)
Labour force
Not economically active*
22,3 million
14,9 million
Employed
Unemployed
discouraged
work seekers M M M M
Employed
Unemployed
ILO hierarchy – Employed first then unemployed and the remainder is NEA (including discouraged job-seekers). 3 mutually exclusive groups. Cannot be in two groups at the same time

15. Unemployment Rate by Population Group
Significant variation in Unemployment by Population Group
White
Indian/Asian
Coloured
Black African
Source QLFS Q2:2017

16. Unemployment Rates: TVET vs University
For older Age Groups there is a less than 5% point difference between TVET and University Graduates
20% Point Difference
11,7 % Point Difference
*University includes those whose post-school qualification was obtained from University, Technikon or College.
Source QLFS Q2:2017

17. Skilled employment as a percentage of total employment within each population group, by age group (South Africa)
Amongst the youth, i.e. age groups 15–24 and 25–34, there were increases in skilled employment (as a proportion of corresponding total employment) between 1994 and 2016 in all population groups except black African

19. Education and Unemployment continue to drive Multidimensional Poverty

20. Multidimensional Poverty by Municipalities 2001-2016
Msinga Headcount 24,5%
Msinga Headcount 37,2%
Msinga Headcount 59,8%
Intsika Yethu Headcount 27,7%
In wide dispersion of Poverty with Msinga having a poverty Headcount of around 60%
Between 2001 and 2011 poverty generally declines for all municipalities
However between 2011 and poverty trends diverge between municipalities

21. Poverty Drivers 40 52 33
10 Years
5 Years
CS 2016

22. Main contributors to poverty amongst Youth (15-24)
The major contributor to the poverty situation of the youth in South Africa is educational attainment.
Source CS 2016

23. The effects of the economic and labour situation is not felt equally
Investigating inequality and poverty

24. Based on the results of the 2011 Census, South Africans were shocked at the distribution of income

25. Census 2011

26. Census 2011

27. Census 2011

28. Census 2011

29. No Income by Level of Education and age
Source: Census 2011

30. What does this picture look like today?

31. Average Expenditure Average Income
Average annual household consumption expenditure and income by population group of household head
White-headed households (R ) spent five times more than black African-headed households (R67 828) and three times more than the national average
White
Indian
Coloured
Black African
Average Expenditure
Average Income
Source LCS 2014/15

32. Inequality is also found within Population Groups

33. Average annual household consumption expenditure by population group of household head Median vs Mean R
Coloured
Mean
Median
R65975 R
White
Median
Mean R
Mean
R67 828
Black African
Median
R36 501
Mean R
Indian
Median R
Rands ‘000

34. Highest Fourth Middle Second Lowest
Percentage distribution of households by expenditure per capita quintiles and population group of the household head
Highest
Fourth
Middle
Second
Lowest
Almost half of black African-headed households (46,58%) fell within the lowest two expenditure quintiles combined
Source LCS 2014/15

35. Share of bottom 40% of households income = 8,34%
Household Income, LCS 2015
100% %
Share of bottom 40% of households income = 8,34%
households
Income
40%
Source LCS 2014/15

36. Significant differences exist in proportions of certain categories between the lowest and highest expenditure deciles
Expenditure Categories
Decile 10
Decile 1
Source LCS 2014/15

37. Proportion of total annual household consumption expenditure on food, beverages & tobacco by selected population group of household head
Average for All Population Groups
13,75% (R14 202)
Black African
17,9%
White
7,1%
(R12 163)
R24 998
Black African-headed households had the highest proportion (17,93%) across all population groups, while white-headed households spent the most in monetary terms (R )

38. The money metric poverty headcounts, provide an overview of the current poverty landscape

39. R992 R647 R441 Upper-Bound Poverty Line Lower-Bound Poverty Line
Threshold of relative deprivation below which people cannot afford the minimum desired lifestyle by most South Africans
R992
Lower-Bound Poverty Line
R647
Austere threshold below which one has to choose between food and important non-food items
Food Poverty Line
Threshold of absolute deprivation. The amount of money required to purchase the minimum required daily energy intake
R441
* Based on 2015 prices

40. Poverty headcounts in 2015
In 2015, more than a quarter of the population were living below the food poverty line
Upper-Bound Poverty Line
Lower-Bound Poverty Line
Food Poverty Line
Source: Stats SA Poverty Trends in South Africa

41. Poverty headcounts based on the FPL, LBPL and UBPL
Upper-Bound Poverty Line
Lower-Bound Poverty Line
Food Poverty Line
Approximately 13,8 million South Africans were living below the FPL in 2015, down from a peak of 16,7 million in 2009.
Source: Stats SA Poverty Trends in South Africa

42. Individual poverty by level of education (UBPL)
An individual’s educational level is closely related to poverty
Percentage
No Education
Some Primary
Primary
Some Secondary
79,2% of individuals with no formal education were poor compared to only 8,4% of individuals who had a post-matric qualification in 2015
Matric
Higher Education
For Periods 2006 / 2009 / 2011 / 2015
Data applies to persons age 18+
Source: Stats SA Poverty Trends in South Africa

43. “
significant progress is possible and is within our reach as we gain better handle on planning through the planning tools. 
Minister in the Presidency: Planning, Monitoring and Evaluation, Mr Jeffrey Thamsanqa Radebe

44. Level 3: Provision of Advanced Analytical Intelligence
System-wide infusion and intelligence
Description - Diagnosis - Prediction - Prescription - Adaptation
Linked National-Provincial Macroeconomic Model
Modelling
Level 3: Provision of Advanced Analytical Intelligence
Multi-sector Macroeconomic Model
Linked Macro-Education Model
Public Employment Model
Poverty-Inequality Model
Input-Output Table
Supply & Use Table
Social Accounting
Matrix (SAM)
Growth Accounting
Framework (GAF)
Level 2: Provision of Basic Analytical Intelligence
STATS SA'S PROVISION OF DATA AND ANALYTICAL INTELLIGENCE
Financial statistics
Labour force
Trade Statistics
Employment and Earnings
Census
Household Survey
Price data
Community Survey
Service delivery
Level 1:Provision of Raw Data Intelligence
to plan we need 5 capabilities in our data systems, namely descriptive, diagnostic, predictive, prescriptive and adaptive capability.