KwaZulu-Natal Provincial Treasury
UTHUNGULU DISTRICT: SOCIO-ECONOMIC PROFILE
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8.1 Demographics
The KwaZulu-Natal Province has both, a growing and maturing population, presenting
opportunities and challenges to the province. According to Statistics South Africa mid-
year estimates (2008), the KwaZulu-Natal population was estimated at an average size
of 10,1 million people. The largest number of these people lived in eThekwini Metro
(32.6 percent of the provincial population), followed by uThungulu district (10.2%) and
uMgungundlovu (10.0%). Sisonke was the least populated district municipality (4,0%)
(Figure 8.1).
Figure 8.1: Total Population by DMs, average 2002-2008
Source: Global Insight, 2008; Stats SA, 2008
Figure 8.2 shows the distribution of the population across district municipalities by age
group. In uThungulu the largest proportion of the population was the age group 15-64
years (565,935), which constitute 57.4 percent of the district population1. This was
followed by age group 0-14 years (384,915), which is about 39.0 percent. The elderly
population made the smallest portion of the total population in the district at 3.9 percent.
In uThungulu the majority of the population was females across age groups (Figure 8.3).
1 The provincial estimate was 6,033,961.
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The total number of households in uThungulu made up 9.0 percent of the total
households in the province, almost consistent with its share of the provincial population.
Figure 8.2: Total population by age group across DMs; average 2002-2008
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
Ugu
Um
gung
undlov
u
Uth
ukela
Um
ziny
athi
Am
ajub
a
Zululan
d
Um
khan
yaku
de
uThu
ngulu
iLem
be
Sison
ke
eThe
kwini
%
0-14 15-64 65+
Source: Global Insight, 2008; Stats SA, 2008
Figure 8.3: Total population distribution by gender across DMs; average 2002-2008
40
42
44
46
48
50
52
54
56
Ugu Umgungundlovu Uthukela Umzinyathi Amajuba Zululand Umkhanyakude uThungulu iLembe Sisonke eThekwini
%
Male Female
Source: Global Insight, 2008; Stats SA, 2008
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8.2 Economic Outlook
8.2.1 Gross domestic product per municipality (GDP-M)
Between 2002 and 2008, the GDPR for KwaZulu-Natal was estimated at an annual
average of R184,8bn. There was significant growth of 29.9 percent from R162bn in 2002
to R210,4bn in 2007. UThungulu was the second largest contributor to the provincial
GDPR at an annual average of 9.25 percent, after eThekwini (64.9%), and was followed
by the uMgungundlovu district which contributed 8.43 percent. The least contributor was
uMzinyathi at 0.8 percent (Figure 8.4). UThungulu boasted significant growth between
2002 and 2007, moving from a GDP-R of 15,7bn to 18,3bn; a growth of 17 percent.
Figure 8.4: Districts contribution to KwaZulu-Natal GDPR, average 2002-2008
eThekwini, 64.85
Uthungulu, 9.25
uMgungundlovu, 8.43
iLembe, 3.36
Umkhanyakude, 1.06
Zululand, 1.50
Amajuba, 3.52
Umzinyathi, 0.78
Uthukela, 2.46
Ugu, 3.69
Sisonke, 1.09
Source: Global Insight, 2009
Figure 8.5 shows uThungulu’s GDP-M by economic sector between 2002 and 2008.
During this period the economy of the district grew by an annual average of 3.1 percent.
Manufacturing, Mining and Community Services sectors are the main economic drivers
in this district. These three sectors contributed respective annual averages of 40.9
percent, 12.4 percent and 11.9 percent to the district’s GDPM between 2002 and 2008.
However, Transport was the fastest growing sector at an annual average of 5.0 percent.
Agriculture and Electricity showed least growth, both at 1.1 percent. The negative impact
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of agriculture on uThungulu’s economy was mostly felt in 2006 as compared to other
years. This shows that there is a structural shift in the uThungulu’s economy from
agriculture to industrialized economy.
Figure 8.5: UThungulu GDP-M by Sectors: 2002-2008
Agriculture
Mining
Manufacturing
Transport
Community services
Electricity
Construction
Trade
Finance
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
-10.0% 0.0% 10.0% 20.0% 30.0% 40.0% 50.0%
Contribution to GDP-R
An
nu
al G
DP
-R
Source: Global Insight, 2007
8.2.2 International trade
Figure 8.6 shows the percentage of exports, imports and trade balance (as a proportion
of GDP-M) across all DMs. It reveals that the economy of uThungulu is mainly
dominated by international trade, and that it exports more than it imports; the percentage
of export and import to GDP-M is 103.8 percent and 35.4 percent respectively. This
results in a positive trade balance of 68.6 percent, the highest in the province, followed
by uMgungundlovu (19.0%). Many DMs including eThekwini, had a negative trade
balance.
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Figure 8.6: Export, Import and Trade Balance (percent of GDP), average 2002-08
0.00
20.00
40.00
60.00
80.00
100.00
120.00
eThe
kwini
Ugu
uMgu
ngun
dlov
u
Uth
ukela
Um
ziny
athi
Amajub
a
Zululan
d
Um
khan
yaku
de
Uth
ungu
lu
iLem
be
Sison
ke
%
Exports Imports Trade Balance
Source: Global Insight, 2007
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8.3 The labour market 8.3.1 The labour force and the economically active population
As mentioned earlier, between 2002 and 2006, the provincial labour force approximated
at 6,0 million people per annum (approximately 60.0 percent of total provincial
population). Of this total, the economically active population (EAP)2 was approximately
3,1 million. More than 1,4 million of these people were in eThekwini (Figure 8.7).
UThungulu had approximately 221 thousand people falling in this category.
As a proportion of the district labour force, uThungulu’s EAP was about 42 percent, the
slightly less than the provincial average (52.9%). It is the fourth most economically active
district after uMgungundlovu (58.3%), Amajuba (56.0%) and the Metro (66.7%). This
shows that although uThungulu has more people in the labour force category than
Amajuba, more people in the latter district are available for employment than in the
former.
Figure 8.7: The economically active population by municipal district, average 2002-2006
0
50,000
100,000
150,000
200,000
250,000
300,000
350,000
400,000
450,000
20.0% 25.0% 30.0% 35.0% 40.0% 45.0% 50.0% 55.0% 60.0% 65.0% 70.0%
uMgungundlovu
(359, 942; 60.6%)
uThukela uMkhanyakude
Umzinyathi
Sisonke
Zululand
iLembe
Ugu
Uthungulu
(220,627; 41.5%)
Amajuba
(159,278; 54.6%)
eThekwini EAP =
1,444,201 (66.8%)
KZN avg 52.5%
Labour participation rates
EA
P (
siz
e)
Source: Global Insight, 2007; Mahlatsi, 2007
2 The category EAP is made up of people who are either employed or unemployed. The employed consists
of employers and employees, while unemployment are those not having a job but are actively seeking one
(official definition), or they do not have a job, are actively seeking one or have given up searching yet still
available for work at anytime (expanded definition).
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8.3.2 Unemployment
Between 2002 and 2006, the number of unemployed people in uThungulu averaged
112, 000. This was the third highest unemployment figure after the Metro (562, 000) and
uMgungundlovu (172, 000).
Figure 8.8 gives the average unemployment rates (the unemployed as proportion of the
EAP) in the districts between 2002 and 2006. It transpires from the graph that although
uThungulu has a lower labour participation rate than Amajuba (Figure 4.7), the former
fails to absorb even the few people that are readily available for work; the average
unemployment rate for uThungulu was 46.8 percent against 45.4 percent for Amajuba.
This is a serious condition and needs probing and appropriate correction.
Figure 8.8: Unemployment rate3 by district, average 2002-2007
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
Kw
aZulu
-Nata
l
eThekw
ini
Metr
opolita
n
Munic
ipality
DC21:
Ugu
DC22:
uM
gungundlo
vu
DC23:
Uth
ukela
DC24:
Um
zin
yath
i
DC25:
Am
aju
ba
DC26:
Zulu
land
DC27:
Um
khanyakude
DC28:
Uth
ungulu
DC29:
iLem
be
DC43:
Sis
onke
Source: Global Insight, 2007
As could be expected, the unemployment rate was higher among Blacks than the other
population groups. This ranged between 47.0 percent (uMgungundlovu) and 75.1
percent (uMzinyathi). UThungulu’s respective figure was 50.8 percent.
3 Expanded definition; includes those unemployed but not actively seeking a job.
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8.3.3 Employment
8.3.3.1 Total employment
During the same period, KwaZulu-Natal employment totaled an annual average of 2,1
million workers. UThungulu had the third highest employment after uMgungundlovu and
the Metro (Figure 8.9).
This reflects dual economy syndrome in the district as there are impressively a sizeable
number of workers among a significant number of unemployed others.
Figure 8.9: Total employment by district, average 2002-2007
230,863
105,702
146,440
-
50,000
100,000
150,000
200,000
250,000
DC21:
Ugu
DC22:
uM
gungundlo
vu
DC23:
Uth
ukela
DC24:
Um
zin
yath
i
DC25:
Am
aju
ba
DC26:
Zulu
land
DC27:
Um
khanyakude
DC28:
Uth
ungulu
DC29:
iLem
be
DC43:
Sis
onke
eThekwini
1,117,578
Source: Global Insight, 2007
8.3.3.2 Formal employment
Throughout the period, formal employment played the most significant role in the
province, ranging between 60 percent and 80 percent of districts’ total employment
(Figure 8.10). As in the total employment, uThungulu’s formal employment held the third
position too, after uMgungundlovu and the Metro – all the three districts had higher than
provincial average formal employment.
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Figure 8.10 also reveals why Amajuba has been able to absorb its labour force faster
than uThungulu; the district had the lowest formal employment share to its total
employment (64.4%).
The formal employment sector in uThungulu was quite ‘balanced’ between the five major
employing economic sectors (Community Services4, Manufacturing, Agriculture, Finance
and Trade). The district’s Community Services was the biggest employer (22.1%),
followed by Manufacturing (19.9%), Agriculture (13.8%) and Trade (9.9%). The least
contributors to formal employment were Electricity (0.7%) and Construction, Mining (4.5
percent each).
Figure 8.10: Formal employment within districts (%), average 2002-2007
77.7%
74.5%
74.8%
76.4%
64.4%
20.0% 40.0% 60.0% 80.0% 100.0%
KwaZulu-Natal
eThekwini Metropolitan
Municipality
DC21: Ugu
DC22: uMgungundlovu
DC23: Uthukela
DC24: Umzinyathi
DC25: Amajuba
DC26: Zululand
DC27: Umkhanyakude
DC28: Uthungulu
DC29: iLembe
DC43: Sisonke
Source: Global Insight, 2007
Education was the largest engine behind the Community Service performance,
contributing a solid half of the sector’s employment. Health and Social Work also played
a good role (Figure 8.11). This shows that the education-and-health inclined provincial
expenditure budget reaches this district proportionately.
4 This was the most dominant sector in all the districts except eThekwini, Amajuba, iLembe and Sisonke.
In fact, in all the districts, it was one of the two leading sectors with either Manufacturing or Agriculture.
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Figure 8.11: UThungulu formal employment by economic sector (%), average 2002-2007
Construction
Mining
Electricity
Community services 22%
Education
Health and social work
Other service activities
Public admin and defence
Manufacturing 19%Agric 13%
Trade 10%
Households 9%
Finance 9%Trans 7%
11%
Source: Global Insight, 2007
8.3.3.3 Informal employment
Informal sector employment was recorded mainly in Manufacturing, Construction, Trade,
Transport, Finance and Community Services. In all the districts, Trade was the main
employer with all but four districts having more than half employment in this sector.
UThungulu was one of the leading districts in informal Trade employment5 (Figure 8.12).
Given the district’s geographical location, this employment could be parallel to the formal
Trade employment (see Figure 8.13), but to a less extent in Hotels and Restaurants.
5 An unfortunate hindrance is the absence of detailed data on this issue.
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Figure 8.12: Informal employment by district and main economic sector (%), average 2002-2007
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
Kw
aZulu
-N
ata
l
eThekw
ini
Metr
opolita
n
Munic
ipality
DC21: U
gu
DC22:
uM
gungundlo
vu
DC23: U
thukela
DC24: U
mzin
yath
i
DC25: A
maju
ba
DC26: Z
ulu
land
DC27:
Um
khanyakude
DC28: U
thungulu
DC29: iLem
be
DC43: S
isonke
Trade Constr Comm serve Manufacturing Trans Finance
Source: Global Insight, 2007
Figure 8.13: UThungulu formal employment in Trade (%), average 2002-2007
Retail trade and repairs of
goods, 37.4%
Wholesale and commission
trade, 24.9%
Hotels and restaurants,
17.9%
Sale and repairs of motor
vehicles, sale of fuel,
19.9%
Source: Global Insight, 2007
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8.4 Crime Between 2002 and 2007, there has been a consistent decline in reported incidences of
crime in the province (2.45% annual average). The overall number of crimes reported in
uThungulu has declined by 18.2 percent over the same period.
However, 2003 forwards have seen a similar experience, though with differing
magnitudes. The provincial collapse rate in crime was 5.1 percent, while uThungulu’s
respective figure was 4.1 percent; this was the third lowest achievement after eThekwini
and iLembe.
Figure 8.14: Number of reported crime incidents in uThungulu, averages 2002-2007
25,000
27,000
29,000
31,000
33,000
35,000
37,000
39,000
41,000
43,000
2002 2003 2004 2005 2006 2007
Nu
mb
er
of
rep
ort
ed
cri
me
s
Source: Global Insight, 2007
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8.6 Land cover and use
KwaZulu-Natal’s land size is 93,378 km2 (approximately 8 percent of the South African
land). UThungulu’s size is about 9 percent of this; the sixth largest cover after Zululand
(15.9%), uMkhanyakude (13.7%), uThukela (12.1%), Sisonke (11.9%) and
uMgungundlovu (9.6%).
UThungulu’s largest share of the land is covered in unimproved grasslands, followed by
thicket & bushland. The important ‘cultivated’ and ‘forest’ coverages are relatively small
(Figure 8.15).
Figure 8.15: UThungulu land use, 2007
Cultivated temporary,
16.9%
Cultivated permanent,
9.1%
Thicket & bushland (etc),
22.9%
Unimproved grassland,
26.1%
Forest and Woodland, 4.9%Forest plantations, 11.5%
to expand
Source: Global Insight, 2007
Given the escalating agricultural (particularly food) prices in the province (the country
and the world), the barren land could be used to expand the productive piece.
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8.6 Social Development
Where is uThungulu ranked with other district municipalities in terms of development?
Figure 8.16 shows average poverty rate, HDI, illiteracy rate and no schooling rate across
districts from 2002 until 2006. UThungulu (at 57.3%) is among the districts with lowest
poverty rate, although still slightly above the provincial average (53.1%). It ranked third
after eThekwini (29.8%) and uMgungundlovu (50.2%). UMzinyathi, uMkhanyakude and
Zululand were districts with the highest poverty rate.
Figure 8.16: Poverty, HDI, Illiteracy and No Schooling Rates, average (2002-07)
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
2002 2003 2004 2005 2006 2007
HDI GINI POVERTY
Source: Global Insight, 2007
Unlike with its poverty rate, uThungulu is a bit behind in terms of HDI. It is the fourth
highest DM after eThekwini (67.0%), uMgungundlovu (59.0%) and Amajuba (55.0%).
This is not surprising seeing that the district is the fifth lowest in terms of illiteracy rate
(36.8%) and, fourth highest district in terms of no schooling rate (22.1%).
The relatively low poverty rate (although still at 50s) with high level of household income
and high rate of no schooling in uThungulu suggests that there may be more number of
uneducated self-employed people in the district. Hence, if empowered through
education and skills development, one would be able to see a greater reduction in the
number of the poor living in this district.
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