performance of municipalities in 2015 - salga 2016/statssa.pdfperformance of municipalities in 2015...

9 June 2016 Dr Pali Lehohla

Performance of Municipalities in 2015

( SERVICE DELIVERY, INDIGENT AND EMPLOYMENT NUMBERS FROM MUNICIPALITIES)

1

ContextNDP: Address the triple challenge of Poverty Inequality and Unemployment

Education level zero income, age & level of

education

20 40 60 80+30 50 70

10%

20%

30%

40%

50%

60%

70%

80%

No

in

co

me

Age

No schooling

Grade 11

Grade 12

Diploma

Bachelors degree

0.0

0.1

0.2

0.3

1950 1960 1970 1980 1990 2000 2010 2020

Pro

po

rtio

n c

om

ple

tin

g a

bac

he

lor'

s d

egr

ee

af

ter

com

ple

tin

g gr

ade

12

Year

White

Indian/Asian

Black African

Coloured

The alarming evidence points

to regressive proportions in

Bachelor’s completion

rates amongst Blacks

0% 10% 20% 30% 40% 50% 60% 70% 80%

15-24

25-34

35-44

45-54

55-64

15-24

25-34

35-44

45-54

55-64

15-24

25-34

35-44

45-54

55-64

15-24

25-34

35-44

45-54

55-64

Bla

ck

Afr

ica

nC

olo

ure

dIn

dia

nW

hit

e

1994

2014The percentage of workers in skilled occupations increased in all age and all race groups,

except for black Africans aged 25-34, which decreased

Percentage of workers in each age group who are skilled (managers,

professionals, technicians)

There were much weaker gains in the black African

group for all ages

0.670.65 0.65

0.54

0.560.55

0.57

0.52 0.530.530.50

0.45

0.430.39

0.42

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

2006 2009 2011

%

RSA

Black African

Coloured

Indian/Asian

White

Inequality in South Africa

Geography as a dimension: Human Settlements policy The 2011 settlement patterns illustrate that policy intentions and public action

are at variance with densification on the margins

Population Density - Census 2001Census 2011 shows increasing urban

sprawl on the periphery instead

Spatio-Cultural and Temporal Dimensions of Measurement

Real GDP

decreased by

-1,2%in Q1 2016

(quarter-on-quarter)

Seasonally adjusted and annualised

Real GDP

decreased by

-0,2%in Q1 2016(year-on-year)

Unadjusted

1. Background

2. General Results

iv. Employment

i. Basic Services

ii. Free Basic Services

iii. Indigent Households

Table of contents: NFCM 2015

3. Concluding Remarks

2

Household Questionnaires

Services - various

Income

Areas

Employment

Various other demography

Population census

Community survey 2016

GHS

Etc

NFCM questionnaire

Employment in municipalities

– By division, type, gender

Infrastructure

Basic and free basic services:

– Water

– Electricity

– Sewerage & sanitation

– Solid waste management

Compliance

Indigents

HOUSEHOLDS

CONSUMER UNITS

What i s asked

Service provided:

Funded by municipality, and /or

Agreements with service providers and/or

Agreements with national and provincial

departments

(where the municipality does not have the funds or

infrastructure to provide service)

3

Households = 140 reporting units

Consumer unit ≠ Household

10027121

+ ++

Consumer units = 5 minimum; 70? maximum reporting units

+ ++

11 1 1

12 27 20?1

+

1

10?

Consumer Unit explained - illustration

4

6kl of water free per household per month

50kwh of electricity free per household per month

R50 average for Solid Waste Management

R50 average for Sewerage and Sanitation

Free Basic Service Policy: Introduced in 2001

5

• These are poor households as determined by municipalities.

• The basis on which a municipality determines if a household

is indigent (and the criteria used for such determination) can

vary.

• Not necessarily consistent across municipalities, even in

same province.

Indigent household

6

Broad-based approach:

Each consumer unit in that municipality receives free basic services on the current billing

system of the municipality.

Geographical approach:

The process whereby consumers living in a particular area are assumed to have the same

socio-economic profile and therefore tariffs can be set on location.

Self-targeting approach:

It is essentially an income-based system which municipalities use as a basis to determine if the

household receives the service at lower, discounted or on a free basis.

Technical targeting approach:

The process whereby technology is used to regulate the provision of free basic services

(including water and electricity meters).

Other targeting methods:

Consumption-based

Property value

Plot size

Mechanisms used for provision of Free Basic Services

7

NFCM 2015: KEY FINDINGS

BS: Basic Service

FBS: Free Basic Service2014* 2015

Indigent households

registered with municipalities

3,5 million 3,6 million

Bucket toilets provided

by municipalities

85 718 80 119

12,2 million (BS)

4,7 million (FBS)

12,5 million (BS)

4,6 million (FBS)

Water: consumer units

10,4 million (BS)

2,6 million (FBS)

10,9 million (BS)

2,7 million (FBS)

Electricity: consumer units

10,4 million (BS)

3,3 million (FBS)

10,9 million (BS)

3,3 million (FBS)

Sewerage & Sanitation:

consumer units

9,0 million (BS)

2,3 million (FBS)

8,6 million (BS)

2,4 million(FBS)

Solid Waste Management:

consumer units

Based on all 278 municipalities

(100% response rate)

8

WATER

9

ContextNDP: Increase in the percentage of households with access to a functional water service from 85% in 2013 to 90% by 2019.

11 027 242 11 422 425 11 661 29512 208 266

12 518 180

4 190 397

4 896 539 5 129 1634 672 586 4 588 790

2 000 000

4 000 000

6 000 000

8 000 000

10 000 000

12 000 000

14 000 000

2011 2012 2013 2014* 2015

Co

nsu

me

r u

nit

s

Year

Basic Water

Free Basic Water

Basic water and free basic water consumer units:

2011-2015

10

Consumer units receiving basic water: 2015

EC

1. Nelson Mandela MM (334 275)

2. O.R. Tambo DM (319 385)

3. Amathole DM (247 500)

FS

1. Mangaung MM (171 050)

2. Maluti-A-Phofung (119 411)

3. Matjhabeng LM (100 379)

GP

1. Johannesburg MM (978 406)

2. Ekurhuleni MM (837 180)

3. Tshwane MM (794 649)

KZN

1. Ethekwini MM (896 895)

2. Msunduzi LM (1605 97)

3. Ugu DM (152152)

LP

1. Mopani DM (262 987)

2. Vhembe DM (249 824)

3. Greater Sekhukhune (218 679)

MP

1. Mbombela LM (224 885)

2. Bushbuckridge LM (145 174)

3. Govan Mbeki LM (101 197)

NW

1. Matlosana LM (167 225)

2. Madibeng LM (129 512)

3. Rustenburg LM (129 234)

NC

1. Sol Plaatjie LM (63 224)

2. Ga-Segonyana LM (24 791)

3. Joe Morolong LM (24 250)

WC

1. Cape Town MM (823 206)

2. Drakenstein LM (43 711)

3. Stellenbosch LM (37 846)

Top 3 municipalities per province

12

Percentage of households with

access to piped or tap water in their dwellings, off-site

or on-site

2002: 85%

2015: 89%

WC, 99.2

EC, 74.9

FS, 96.1

KZN, 84.2

GP, 97.7

MP, 85.5

LP, 78.8

50%

55%

60%

65%

70%

75%

80%

85%

90%

95%

100%

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

There were very high proportions of households in Western Cape (99,2%), Gauteng (97,7%), Northern Cape (96,5%) with access to piped or tap water off and on site

Percentage of households with access to piped or tap water in their

dwellings, off-site or on-site by province, 2002–2015

Percentage of households rating the quality of water services provided by the

municipality as good, and those that reported water interruptions, by province,

2015

32.4%

40.2%

40.2%

49.4%

51.1%

51.6%

57.5%

62.0%

76.8%

86.4%

LP

MP

NC

GP

EC

KZN

FS

SA

NW

WC

Quality

LP MP NC GP EC KZN FS SA NW WC

60.9%

59.4%

50.8%

37.8%

26.1%

36.1%

30.7%

25.4%

6.6%

3.1%

Interruptions

LP MP NC GP EC KZN FS SA NW WC

vsAn inverse relationship between the perceived quality of services and the number of interruptions seems to exist.

Percentage of households rating the quality of water services provided by the

municipality as good, and those that reported water interruptions, by Metro,

2015

87.8%

84.4%

79.6%

77.4%

75.9%

73.7%

58.0%

55.6%

52.9%

City of Cape Town

eThekwini

City of Johannesburg

All Metros

Ekurhuleni

City of Tshwane

Nelson Mandela Bay

Buffalo City

Mangaung

Quality

City of Cape Town eThekwini City of Johannesburg All Metros Ekurhuleni City of Tshwane Nelson Mandela Bay Buffalo City Mangaung

3.6%

7.1%

6.0%

7.6%

6.3%

9.6%

5.9%

15.2%

31.1%

Interruptions

vsAn inverse relationship between the perceived quality of services and the number of interruptions seems to exist.

Mangaung has a significantly higher percentage of interruptions than the average for all metros

Electricity

17

ContextNDP: The proportion of people with access to the electricity grid should rise to at least 90 percent by 2030

Number of consumer units basic electricity

and free basic electricity: 2011-2015

9 119 7569 748 720 9 998 039

10 440 88810 885 520

2 476 100 2 555 177 2 528 672 2 623 343 2 747 490

0

2 000 000

4 000 000

6 000 000

8 000 000

10 000 000

12 000 000

2011 2012 2013 2014* 2015

Co

nsu

me

r u

nit

s

Year

Basic Electricity

Free Basic

0

18


Number of consumer units receiving basic electricity :

2015

EC

1. Nelson Mandela MM (314 398)

2. Buffalo City MM (148 065)

3. King Sabata Dalindyebo (53 362)

FS


2. Maluti-A-Phofung LM (100 228)


GP


2. Tshwane MM (704056)


KZN



3. Newcastle LM (81 412)

LP

1. Polokwane LM (159 928)

2. Makhado LM (104 292)

3. Thulamela LM (96 467)

MP



3. Nkomazi LM (86 492)

NW

1. City of Matlosana (167 225)

2. Madibeng LM (136 488)


NC



3. //Khara Hais LM (21 874)

WC



3. George LM (44 920)

2820

The percentage of South African

households that were connected to

the mains electricity supply

2002: 77%

2015:86%

The percentage of households connected to the mains electricity

supply by province

93% 92%90% 89% 88%

86% 84% 83% 82% 82%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

LP NC WC FS MP SA NW GP EC KZN

The percentage of South African households that were connected to the mains electricity supply increased from 77,1% in 2002 to 86% in 2015.

Percentage distribution of wood as a source of energy used for

cooking by province, 2015

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

LP MP KZN EC RSA NW NC FS WC GP

Wood still represent a significant source of energy for cooking in Limpopo, along with other provinces with significant rural communities

Less than one per cent of households usually used wood for cooking in Western Cape and Gauteng (0,7% and 0,5% respectively).

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

WC EC NC FS KZN NW GP MP LP RSA

2010

2011

2012

2013

2014

2015

EC quality of the electricity supply services has been consistently declining over the time period

The percentage of households in the country that rated electricity supply as ‘good’ increased to 66,5% in 2014 before dropping to 60,2% in 2015.

Rating of the quality of the electricity supply services, 2010 - 2015

SEWERAGE AND SANITATION

25

ContextNDP: Increase in the percentage of households with access to a functional sanitation service from 84% in 2013 to 90% by 2019,

9 367 622 9 400 6829 853 993

10 434 58410 870 460

2 681 875 2 813 507 3 135 604 3 285 393 3 308 837

0

2 000 000

4 000 000

6 000 000

8 000 000

10 000 000

12 000 000

2011 2012 2013 2014* 2015

Co

nsu

me

r u

nit

s

Year

Basic Sewerage and Sanitation

Free Basic Sewerage and Sanitation

Number of consumer units receiving basic sewerage and

sanitation and free basic sewerage and sanitation : 2011-2015

26

EC

1. Nelson Mandela Bay (334 275)

2. O.R. Tambo DM (317 043)


FS


2. Maluti-A-Phofung (119 651)


GP



3. Tshwane MM (596 753)

KZN



3. Uthukela DM (130 379)

LP


2. Greater Sekhukhune (164 101)

3. Vhembe DM (127 994)

MP




NW



3. Mahikeng LM (77 232)

NC




WC



3. Mossel Bay LM (36 862)

Sewerage and sanitation consumer units: 2015


3627

WC, 93.3

NC FS, 81.1

KZN, 77.3 NW

GP, 91.0

MP, 65.8

LP, 53.8

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Percentage of households that have access to RDP

standard sanitation per province, 2002–2015

vsNationally, the percentage of households with access to ‘RDP─standard’ sanitation increased from 62,3% in 2002 to 80% in 2015.

WC

93.3

NC

FS81.1

67.4

KZN

77.3

66.4

GP 91.0

MP

65.8

LP53.8

RSA 79.9

40%

50%

60%

70%

80%

90%

100%

2012 2013 2014 2015

Percentage of households that have access to RDP

standard sanitation per province, 2012–2015

vsNationally, the percentage of households with access to ‘RDP─standard’ sanitation increased from 62,3% in 2002 to 80% in 2015.

KZN has shown steady increases in improving access to RDP sanitation standard over the last 3 years

0%

5%

10%

15%

20%

25%

30%

35%

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Percentage of households that have no toilet facility or

were using a bucket toilet, 2003 - 2015

vsPercentage without toilet facilities, or buckets, improved from 12,3% in 2002 to 4,9% in 2002, nationally. Largest decrease in EC (28,3 pct pts to 8,5%)

Municipality provision of bucket toilets: 2011 - 2015

90 000

75 000

105 000

60 000

45 000

Nu

mb

er

of

ho

useh

old

s

30 000

2011Year 2012 2013 2014* 2015

67 419

89 751

100 618

85 718

0

15 000

80 119

32

Number of consumer units using bucket toilets provided by the municipalities in

each province: 2014 and 2015

Free State

KwaZulu-Natal

Eastern Cape

Northern Cape

Mpumalanga

Western Cape

Gauteng

North West

Limpopo

No bucket toilet system provided by municipality in 2015

33

SOLID WASTE MANAGEMENT

38

9,0 million consumer units

nationally received basic

solid waste management

services

Just over 1 in 4 of these units

received free basic services

58% of indigent households

benefitted from indigent support on

solid waste management

Number of consumer units receiving

solid waste management: 2015

39

Number of consumer units receiving basic solid waste

management and free basic solid waste management: 2011-2015

7 923 100 8 008 5838 391 693

8 575 1029 027 572

2 171 8942 554 059 2 428 389 2 359 365 2 306 036

0

1 000 000

2 000 000

3 000 000

4 000 000

5 000 000

6 000 000

7 000 000

8 000 000

9 000 000

10 000 000

2011 2012 2013 2014* 2015

Co

nsu

me

r u

nit

s

Year

Basic Solid Waste Management

Free Basic Solid Waste Management

40

Number of consumer units receiving basic solid waste management services:

2015


EC

1. Nelson Mandela Bay (317 206)


3. King Sabata Dalindyebo (30 000)

FS



3. Metsimaholo LM (42 500)

GP

1. Johannesburg MM (1 015 257)

2. Tshwane MM (830 815)


KZN



3. uMhlathuze LM (64 000)

LP


2. Mogalakwena LM (52 342)

3. Thulamela LM (49 700)

MP

1. Nkomazi LM (82 126)

2. Thembisile LM (74 822)


NW



3. Moses Kotane LM (63 000)

NC



3. Gamagara LM (14 791)

WC

1Cape Town MM (781 290)

2. George LM (53 200)


4541

Number of consumer units receiving basic

solid waste management services: 2015

Magareng

2014*: 4 985

2015: 7 363

Change: +2 378

Service extended to

various communities,

including Warrenvale

and Ikhutseng areas

42

LP6%

Percentage of households whose refuse is removed by the municipality

6.6%

86.4%84.1%

8.6%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Removed at leastonce a weak

Removed less oftenthan once a week

Communal refusedump

Own refuse dump Dump or leaverubbish anywhere

Other

Urban Rural

Households in urban areas were much more likely to receive some rubbish removal service than those in rural areas, and rural households were therefore much more likely to rely on their own rubbish dumps

Households refuse removal by geotype, 2015

The percentage of households who experience

specific kinds of environmental problems,2003 - 2015

Waste, 39%

Water, 16%

Air, 19%

Land, 31%

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

The proportion of households that felt that there were problems with littering and waste removal in their areas increased notably since 2003 when 28,8% of households regarded this as a problem.

NDP urges the rapid expansion of recyclinginfrastructure, and encouraging the composting of organic domestic waste to bolster economic activity in poor urban communities

Msinga

2014*: 0

2015: 2 112

Change: +2 112

Municipality solid

waste management

services was

provided for the first

time in Keates Drift,

Tugela Ferry and

Pomeroy


management services: 2015

43

Nyandeni

2014*: 1 081

2015: 3 000

Change: + 1 919

Services extended to:

a. Various wards in Ntlaza;

b. The Ziphunzana area


management services: 2015

44

Indigents

45

Number of indigent households registered

with municipalities per province: 2014 & 2015

2014*: 3 478 158

2015: 3 570 602

Free State KwaZulu-Natal

North West

Eastern Cape

Northern Cape

Mpumalanga

Limpopo

Western Cape

Gauteng

689 859

484 861

71 274

76 458

413 259360 238

825 269

843 181

122 611

165 333

184 510172 322

770 049

735 041

140 777

126 405

465 548401 765

2,7%(92 444) increase in

indigent identified by

the municipalities in

2015

46

Indigent households in each province and

services they receive: 2015

3,6 million indigent households

WC EC NC FS KZN NW GP MP LP

Identified

Be

nef

itti

ng

354 145

353 424

329 900 68 527 133 685 231 679 153 162 689 018 121 112 158 289

541 507 64 524 133 958 413 690 87 162 300 351 90 655 108 843

223 940 64 327 133 947 648 403 88 713 360 154 90 827 94 082

356 521

359 334 543 739 70 302 133 874 599 696 114 373 292 991 121 952 183 693

360 238 843 181 76 458 165 333 735 041 172 322 689 859 126 405 401 765

47

EMPLOYMENT

48

Gender breakdown of executive mayors and mayors: 2014 & 2015

38%38%

62%62%

2014*

2015

278 posts

49

Gender breakdown of executive mayors and mayors (%)*: 2015

27%

29%

33%

33%

38%

39%

42%

43%

60%

73%

71%

67%

67%

62%

61%

58%

57%

40%

0% 20% 40% 60% 80% 100%

Western Cape

Free State

KwaZulu-Natal

Gauteng

Northern Cape

North West

Eastern Cape

Mpumalanga

Limpopo

Female Male* Rounded off

50

31 38432 928

Municipality positions* per province: 2014 & 2015

2014*: 305 648

2015: 310 559

48 29748 387

*Including: full–time + part-time +

vacant + managerial positions

15 50916 96215 410

16 619

21 22921 553

9 8589 270

93 64793 728

16 91417 440

Northern Cape

Western Cape

Eastern Cape

Free State

North West

KwaZulu-Natal

Mpumalanga

LimpopoGauteng

51

ProvinceType of municipality

Metros Districts Locals Total

2014* 2015 2014* 2015 2014* 2015 2014* 2015

Western Cape 29 242 28 675 2 105 2 504 16 950 17 208 48 297 48 387

Eastern Cape 12 534 13 493 4 886 5 605 13 964 13 830 31 384 32 928

Northern Cape 0 0 769 640 9 089 8 630 9 858 9 270

Free State 6 256 7 803 546 588 14 427 13 162 21 229 21 553

KwaZulu-Natal 26 655 24 725 5 575 6 375 21 170 22 572 53 400 53 672

North West 0 0 1 571 2 234 13 839 14 385 15 410 16 619

Gauteng 78 819 78 567 1 137 1 149 13 691 14 012 93 647 93 728

Mpumalanga 0 0 548 658 14 961 16 304 15 509 16 962

Limpopo 0 0 4 465 4 749 12 449 12 691 16 914 17 440

South Africa 153 506 153 263 21 602 24 502 130 540 132 794 305 648 310 559

Employment by type* of municipality : 2014 & 2015

*Including: full –time + part-time + vacant + managerial positions

52

Free StateKwaZulu-Natal

North West

Eastern Cape

Northern Cape

Mpumalanga

Limpopo

Western Cape

Gauteng

10,3%

17,6%

15,9%

25.6%9,2%

19,4%12,4%

18,4%

10,8%

Municipal staff vacancy rates

by province: 2015

13,3% (41 303)of

310 559 municipal posts

throughout the

country are vacant

53

Vacancy rates in ALL MUNICIPALITIES per

department: 2015

Electricity

Sport &

recreation

Waste water

management

Public safety

Environmental

protection

Waste

management

Finance &

administration

Community &

Social services

Health

Water

13%

vacancy

rate in all

departments

10%

11%

11%

11%12%

14%

16%

18%

20%

23%

9%

Road

transport

12%

Excludes managerial positions

& other.

54

Vacancy rates in District municipalities

per department: 2015 Electricity

Sport &

recreation

Waste water

management

Road

transport

Public safety

Environmental

protection

Waste

management

Finance &

administration

Community &

Social services

Health

Water

13%

vacancy

rate in all

departments

8%

11%

13%

13% 16%

18%

18%

24%

37%

41%

1%


& other.

55

Vacancy rates in Metropolitan

municipalities per department: 2015

Electricity

Sport &

recreation

Waste water

management

Road

transportPublic safety

Environmental

protection

Waste

management

Finance &

administration

Community &

Social services Health

Water

10%

vacancy

rate in all

departments

5%

7%

7%

7% 8%

10%

10%

11%

20%

28%

4%


& other.

56

Vacancy rates in Local municipalities

per department: 2015

Electricity

Sport &

recreation

Waste water

management

Road

transport

Public safety

Environmental

protection

Waste

management

Finance &

administrationCommunity &

Social services

Health

Water

18%

vacancy

rate in all

departments

13%

14%

16%

16% 21%

21%

21%

24%

28%

36%

13%


& other.

57

Results Survey date is October to November 2015

BackgroundThere are five types of Municipalities in KZN

Type A1

Type B1

Type B2

Type B3

Type B4

TYPE A : 1MUNICIPALITY

TYPE B1: 3 MUNICIPALITIES




28

13

6

3

1

Municipal Infrastructure Investment Framework (MIIF) used to distinguish

Municipalities

Metropolitan municipalities (metros)

Secondary cities, local municipalities with the largest budgets

Local municipalities with alarge town as core

Local municipalities with small towns, relativelysmall population, significant proportion of

urban population but with no large town as core

Local municipalities which are mainly rural with communal tenure and with,

at most, one or two small townsin their area

Background

in terms of service delivery Kzn has shown

progressive improvements over time which

includes water, sanitation and electricity amongst

others and this has resulted in the B4

Municipalities reducing head count poverty the

greatest

76%

87%

2002 2014

Access to piped water

69%

82%

2002 2014

Electricity for lighting

51%

76%

2002 2014

Sanitation

Context: KZN Service Delivery Progress

Source GHS 2014

Context: Poverty headcount by municipality – 2001-2011 (South African multidimensional

Poverty index (SAMPI)

Poverty headcount by municipality – 2001-2011

(SAMPI)

Poverty headcount by municipality – 2001-2011

(SAMPI)Reductions in intensity

and Headcount

SAMPI 2011 SAMPI 2001

2%

3%

5%

6%

6%

6%

7%

7%

8%

15%

35%

Child Mortality

School Attendance

Assets

Lighting

Cooking

Dwelling

Heating

Water

Sanitation

Years of Schooling

Unemployment

Drivers of Poverty in KZN–2011 (SAMPI)

Strong linkage between years

of schooling and

unemployment

Inequality has remained high especially amongst

the Blacks with a gini that dropped marginally

from 0.53 to 0.51

Inequality amongst Indians has declined overtime

from a gini of 0.53 to 0.46

Amongst Whites the gini is low showing more

equality with a gini that dropped from 0.39 to 0.37

0.66

0.610.64

0.53 0.54

0.51

0.460.42

0.56

0.480.46

0.390.38

0.37

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

2006 2009 2011

KwaZulu Natal Black African Coloured Indian/Asian White

Gini-coefficient: KwaZulu-Natal 2006-2011

White

Indian/Asian

Black African

Coloured*

KZN

Significant variations in inequality by population

group

Note that Colored population Numbers too small in KZN to

make conclusive determination on inequality

trends

*Small sample size for Coloured persons in KZN province may influence figure provided

Whilst inequality is acknowledged improvement in real life circumstances have rapidly increased

Yet despite this level of change the Level of satisfaction with overall performance of

Kwazulu-Natal provincial government shows surprising results

Now the Results follow

33%Outright Satisfaction

with overall performance of KwaZulu-Natal

provincial government

31%Somewhat Satisfied

with overall performance of KwaZulu-Natal

provincial government

36%Dissatisfaction with overall performance

of KwaZulu-Natal provincial

government

However marked differences in the ratings by population group, education level, income

level and district

Satisfaction rates are similar across age and Sex

Outright Satisfaction with overall performance of provincial government differs by

Population Group but colored population numbers too few to be conclusive

Coloured 48.0%

White 35.7% Satisfaction ofPerformance of Provincial Government

Black African 32.5%

Indian/Asian 31.1%

Dissatisfaction ofPerformance of Provincial Government

Black African 37.6%

Indian/Asian 20.1%

Outright Dissatisfaction with overall performance of provincial government

Coloured 16.2%

White 32.4%

Changes in ranking of population

groups when viewed from

dissatisfaction perspective

28%

30%

34%

33%

36%

No Education

Some Primary

Some High School

Completed Matric

Certificate with Matric

Outright Satisfaction with performance of provincial government by educational

level

Lower Educational attainment linked with

lower rates of outright

satisfaction

21%

26%

31%34%

31%33% 34%

33%

42% 40%

34%

44%42%

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

R1 - R2400 R2401-R6000

R6001 -R12000

R12001 -R18000

R18001 -R30000

R30001 -R42000

R42001 -R54000

R54001 -R72000

R72001 -R96000

R96001 -R132000

R132001 -R192000

R192001 -R360000

R360000+

Outright satisfaction with performance of provincial government by Incomelevel

Those Households

with the least income show

the least outright

satisfaction

More than twice as likely to be satisfied than low income earners

Annual Household Income

Locality is also a key differentiator in rates of satisfaction

Different municipalities have differing abilities to serve the citizens given based on financial,

technical and management resources

Outright satisfaction with performance of provincial government by municipality

Areas with higher outright

satisfaction with overall

performance of provincial

government more dispersed

6.5 –10.5%

10.51– 25.5%

25.51 – 35.8%

35.81 – 50.1%

50.11 – 64.5%

Outright satisfaction

Outright dissatisfaction with performance of provincial government by municipality

Evidence of clustering with

regards to outright

dissatisfaction with overall

performance of provincial

government

15.2 –24.2%

24.21– 33.5%

33.51 – 49.8%

49.81 – 65.3%

65.31 – 78.8%

Outright dissatisfaction

Outright dissatisfaction with performance of provincial government by Municipality

! Many of the most Outright

Dissatisfied areas are

governed by coalition

15.2 –24.2%

24.21– 33.5%

33.51 – 49.8%

49.81 – 65.3%

65.31 – 78.8%

Outright Dissatisfaction

Outright satisfaction with performance of provincial government by Municipal Status

Despite more resources Ethekwini (only type A municipality) does not rank as high

23%

27%

34%

37%

45%

0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50%

B3

B4

A

B2

B1

Mu

nic

ipal

Typ

e

Outright Satisfaction

Municipalities

Outright Dissatisfaction is particularly apparent in uMkhanyakude, Zululand and uThukela districts

Where nearly 7out of every 10

respondents reported that they are

dissatisfied with the overall performance of their local municipality.

Perceived importance of municipal services and programmes

What are the top three priority areas?

#1 Job CreationBlack African #1 Provision Housing#2 Provision Housing#3

#1 Job CreationColoured

#1Education & skills

Development#2 Poverty eradication#3

#1 Job CreationIndian/Asian #1 Crime prevention#2 Fighting corruption#3

#1 Job CreationWhite

#1 Poverty eradication#2 Fighting corruption#3

KZN Citizens Priority Areas by population group

! For All Population Groups Job Creation is the Main Priority

Ratings of performance of KZN Provincial Government in selected areas

Overall 62.6% of KZN

citizens were satisfied* with the provincial government in providing basic education

Providing healthcare and maintaining provincial roads also ranked relatively higher performance ratings at around 50%satisfaction rating* Satisfied rating is based on Good, Very Good or Excellent responses

Performance Of KZNProvincial Government in selected areas

49.1% Of KZN citizens

ranked provincial government as poor ineliminating fraud and corruption

Promoting accountable government and enhancing entrepreneurship and SMME were also ranked relatively poorly

Performance Of KZNProvincial Government in selected areas

52%

40%

39%

36%

34%0 10 20 30 40 50 60

Water

Electricity

Clinics

Sanitation

Housing

More than 50% view Water as critically

important

Municipal services and programmesviewed as critically Important

Percentage Critically Important

What are the satisfaction rates, of services that are viewed as critically important by type of

municipality?

Type A

Type B1

Type B2

Type B3

Type B4

-10% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90%

OutrightSatisfaction with services provided

B3 and B4 Municipality

have particular concerns with

Quality of water provision

AffordableHousing ranks

lowest amongst all

MIIF categories

High Satisfaction

with Electricity services almost

universal

Percentage Outright Satisfied

Mapping the poverty headcount by Municipality

Eastern Cape – 2001-2011 (SAMPI)

Poverty headcount by municipality – 2001-2011 (SAMPI)

3


4


5

1.3

16.3

3.6

5.9

7.5

7.3

6.3

7.0

5.4

6.6

32.9

1.5

13.7

2.3

5.2

7.3

6.3

6.5

7.4

5.4

4.5

39.8

Child mortality

Years of schooling

School attendance

Lighting

Heating

Cooking

Water

Sanitation

Dwelling

Assets

Unemployment

2011 2001

Unemployment is

now the major

driver of poverty in

the country

Living standard

Education

Health

Economic activity

0.0

5.0

10.0

15.0

20.0

25.0

30.0

2001 2011 2012 2013

Men Women

Total

Unemployment rate

Poverty drivers in

South Africa are

multidimensional

Unit data for all 278 municipalities for 2014 and 2015 is available on the Stats SA website (or on request)

Thank you

Technical queries:

Mr Malibongwe Mhemhe ([email protected])

(Cell: 0829068964 Office: 012 3106928)

Dr Patrick Naidoo ([email protected])

(Cell: 0828882509 Office: 012 3108307)

58

mailto:[email protected]

mailto:[email protected]

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