Provincial Treasury Comparative Analysis for ZF Mgcawu District Municipality 2017

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Northern Cape Provincial Government District Municipality Comparative Analysis For ZF Mgcawu 2017

Comparative Analysis for ZF Mgcawu District Municipality | i Comparative Analysis for ZF Mgcawu District Municipality | ii Fax: +27 53Fax: 832-2220 Tel: +27 53 830-8358 Africa South 8300 Kimberley X5054 Bag Private Analysis Economic Directorate: Treasury Provincial Cape Northern contact: please document, of this copies additional obtain to and information For further revision. to or subject unaudited is information of this Some sources. other and departmental from information available latest the 2017using compiled is Municipality District Mgcawu ZF for Analysis Comparative The 2017 Municipality District Mgcawu for ZF Analysis Comparative 978-0-621-45331-7 ISBN: PR95/2017

Acting Head of Department: Northern Cape Provincial Treasury H.V. Gumbo ______resource allocation. I therefore request that municipalities ZFMgcawu inthe analysis this use to District enhance planning their and within adistrict. Municipalities lessons can certain learn from acomparison of performance the of various the municipalities introduced by government are inline with ever-changing the economic socio environment of region. the as well as other relevant stakeholders with planning and decision making as well as ensuring that any measures The aim this documentof is to assist and enablethe ZFMgcawu and District Local its Municipalities,Legislature assist with effective and efficientresource allocation. economic, labour and human development indicators. Thiscan provide municipalitieswith more information to Northernthe Cape Provincial Treasury to assist municipalities the with an analysis demographic, of selected This comparative analysis the ZFMgcawuof District Municipality and Local its Municipalities is prepared by Foreword

Comparative Analysis for ZF Mgcawu District Municipality | iii Comparative Analysis for ZF Mgcawu District Municipality | iv Chapter 2: Chapter 1: Executive Summary List of Acronyms______List of Tables______List of Figures______Table of Contents Chapter 3: 1.5 Conclusion ______1.4 1.3 Urbanisation______1.2 1.1 Introduction______3.2 3.1 Introduction______3.3 Conclusion______2.5 Conclusion ______2.4 Tourism______2.3 2.2 GDP______2.1 Introduction______Population Density ______1.2.5 1.2.4 Households______1.2.3 1.2.2 1.2.1 Population Profile ______Labour StatusLabour ______Economic Industries______Population______Pyramids Population and by______Gender Race Population Growth Rate______Total Population______

Economy Demography Labour ______viii vii 14 14 14 17 13 13 10 10 11 10 ix vi 9 8 8 4 3 3 2 2 2 2 2 Chapter 4: 4.6 4.5 4.4 4.2 4.1 Introduction______4.3 Conclusion______4.5.5 4.5.4 4.5.3 4.5.2 4.5.1 ______Access to Services Basic 4.4.2 4.4.1 Education______Access to Services 4.3.2 Poverty Indicators______4.3.1 Development Indicators______4.3.2.2 4.3.2.1 Access Removal to Refuse Access______to Electricity Access to Water ______Access to Sanitation______Type of______Dwelling Housing______Income Distribution ______Human Development Index______Human Development Annual Income Distribution______Gini______Coefficient ______25 26 25 24 24 23 23 23 22 22 21 20 20 18 18 19 18 19

Comparative Analysis for ZF Mgcawu District Municipality | v Comparative Analysis for ZF Mgcawu District Municipality | vi Chapter 4:Human Development Chapter 3:Labour Chapter 2:Economy Chapter 1: of List • • • • • • • • • • • • • • • • • Figure 4.3:Formal for Backlog Dwelling ZFMgcawu Municipalities, and District its Local 2005and 2015 Figure 4.2:Gini-Coefficient for ZF MgcawuLocal District and its Municipalities, 2005 and 2015 2015 Figure 4.1:Human Development Index for ZFMgcawu Municipalities, and District its Local 2005and 2015 Figure 3.2:Employment Distribution by Industry for ZFMgcawu Municipalities, and District its Local Municipality,District 2015 Municipalities’Figure 3.1:Local Contributions to Total Employment of Industry inZFMgcawu Each (Constant 2010 Prices) Figure 2.2:Average GDP Growth Rates for ZFMgcawu Municipalities, and District its Local 2005-2015 (Constant 2010 Prices) Figure 2.1:GDP Contributions Municipality Local per to ZFMgcawu Municipality, District 2005and 2015 Figure 1.10:Population Density for ZFMgcawu Municipalities, and District its Local 2005-2015 Figure 1.9:Urbanisation Rate for ZFMgcawu Municipalities, and District its Local 2005-2015 Figure 1.8:Population for Pyramid Kgatelopele Municipality, Local 2015 Figure 1.7:Population for Pyramid Tsantsabane Municipality, Local 2015 Figure 1.6:Population Municipality, for Pyramid Local !Kheis 2015 Figure 1.5:Population for Pyramid //Khara Hais Municipality, Local 2015 Figure 1.4:Population for Pyramid Kai Municipality, !Garib Local 2015 Figure 1.3:Population for Municipality, Pyramid Mier Local 2015 Figure 1.2:Population for Pyramid ZFMgcawu Municipality, District 2015 Figure 1.1:Population Growth Rate for ZFMgcawu Municipalities, and District its Local 2005-2015

Demography

Figures Chapter 4:Human Development Chapter 3:Labour Chapter 2:Economy Chapter 1:Demography of List • • • • • • • • • • • • • • • • • • • • and its Local Municipalities,and its Local 2005and 2015 Table 1.3:Number of Households and Average Number of People Household per for ZFMgcawu District Table 1.2:Population and by for Gender Race ZFMgcawu Municipalities, and District its Local 2015 Table 1.1:Population Profile for ZFMgcawu and District Local its Municipalities, 2005 and 2015 Municipalities, 2005 and 2015 Table 4.8:Number of Households by Access Removal to for Refuse ZFMgcawu and District its Local Municipalities, 2005 and 2015 Table 4.7:Number of Households Usage by Electricity for ZFMgcawu and District its Local Municipalities, 2005and 2015 Table 4.6:Number of Households by of Level Access to Water for ZFMgcawu and District its Local 2005 and 2015 Table 4.5:Number of Households by Type of Toilet for ZFMgcawu Municipalities, and District its Local Municipalities, 2005and 2015 Table 4.4:Number of Households by Type of Unit Dwelling for ZFMgcawu and District its Local Table 4.3:Education Attained inZFMgcawu Municipalities, and District its Local 2015 Table 4.2:Annual Income Distribution for ZFMgcawu Municipalities, and District its Local 2015 Table 4.1:Poverty Indicators for ZFMgcawu Municipalities, and District its Local 2005and 2015 Municipalities, 2005-2015 Table 3.4:Changes inUnemployment Rate and by for Gender Race ZFMgcawu and District its Local Municipalities, 2015 Table 3.3:Employment and Unemployment and by for Gender Race ZFMgcawu and District its Local Municipalities, 2005 Table 3.2:Employment and Unemployment and by for Gender Race ZFMgcawu and District its Local Table Characteristics for 3.1:Labour ZFMgcawu Municipalities, and District its Local 2005and 2015 and 2015 Table Municipality 2.5:Local Contributions to Total of ZFMgcawu Bednights Municipality, District 2005 (Constant 2010Prices) Table 2.4:Growth Industry Rate for per ZFMgcawu Municipalities, and District its Local 2005and 2015 Municipality, 2005and 2015(Constant 2010Prices) Table 2.3:Contributions Municipalities by Local to Economic Industry Totals for ZFMgcawu District (Constant 2010Prices) Table 2.2:Annual GDP Growth Rates for ZFMgcawu Municipalities, and District its Local 2005-2015 (R1000)] Table 2.1:GDP for ZFMgcawu Municipalities, and District its Local 2005-2015[Constant 2010Prices Tables

Comparative Analysis for ZF Mgcawu District Municipality | vii Comparative Analysis for ZF Mgcawu District Municipality | viii List of AcronymsList VIP UN StatsSA RDP NDP LM IDP HDI GDP DM ------Ventilation Improved Pit (Toilets) United Nations Statistics South Africa Reconstruction and Development Programme National Development Plan MunicipalityLocal Integrated Development Plan Human Development Index Gross Domestic Product Municipality District an increase number inthe of households refuse was removed whose by community members. lighting and over Tsantsabane other purposes period. this was only the municipality to experience district in the piped water in2015.There was an increaseall in municipalitiesthe in number of households usingfor electricity where there was aslight increase. municipalities All had an increase number inthe of households with no formal was a significantthe in decrease number of households usingthe bucket system toilet except for //Khara Hais householdswhile living in formal, traditional and other 2005and dwelling between 2015.There decreased types In number the district. in the district, the of households formal living and invery informal dwellings increased and acertificate or diploma and matric bachelor’sand a improved degree. services The basic of delivery overall people werethese in //Khara Hais and Kai !Garib. //Khara Hais had largest the also number of people with matric in 2015.With regards to education, had 12 084people with district no the schooling in2015.The majority of Thelargest number of households thewere district in earning withinthe R192000 to R360000incomecategory and district, the measures have will put to be inplace inorder to gap the lessen rich and the between poor. sulted improving district inthe from 0.55in2005to 0.66in2015.There is an unequal distribution of income in cent34.0 per of population the lived still inpoverty in2015.The HDIs all of municipalities increased,which re- Even though progress remained poverty still made poverty district, inalleviating inthe achallenge has been as an increase. infivedecreased the local of municipalitiesbetween 2005 andthe 2015.!Kheis is only municipalitythat recorded labour market of region the it when comes to addressing gender equality, as unemployment the rate of females unemployment rate in2015across municipalities of all local the except inKgatelopele. There was progressthe in demand the between and supply of In skills. terms of unemployment by race, Coloureds recorded highest the potentialthe to influencethelabour status are migration, educationandskills and ensuringthat there is a match fairly is still with an district the high unemployment rate of cent 20.3 per in2015.Some of factors the that have unemployment inthe decrease rates of Kai !Garib, //Khara Hais, Tsantsabane and Kgatelopele, unemployment in and to create decent and sustainable jobs.Although unemployment the rate due district inthe to a decreased Thelabour characteristics showsthat more workbe done to needs inZF Mgcawu unemploymentto minimise and smallest. 2015with the being !Kheis In tourism, //Khara Hais and Kai !Garib were largest the contributors to total the of in2005 bednights district the in agriculture, mining and construction. of All municipalities the saw adecline inagriculture and mining in2015. district’sthe GDP. The negativeeconomic growth inZFMgcawube in2015could attributed largeto contractions Hais and Kai !Garib are economic the hubs of ZF Mgcawu the together District, contributing more than of half evident This was thedistrict. contractions in in agricultural and mining output in2015.//Khara the district in andcountry commodity falling the prices; since agriculture and mining are major the economic inthe activities economyThe the ZFMgcawuof District Municipality was adversely affected the by drought that the hit entire lation density. //Khara Hais had largest the number of households. Most of municipalities the in popu arise - had experienced largestthe share of district’s the population, followed by Kai Mier !Garib population had smallest the while size. lation followed by Africans. //Khara Hais Municipality Local had atotal of 103104people in2015,representing females. With regard to race, Coloured the population contributed largest the share to district’s the total popu- of Northern the Cape’s total population. population Ofthis cent 50.3per cent were 49.7per were while males The ZFMgcawu District Municipalitypopulation had a which of 254768in2015 represented aboutper cent 21 SummaryExecutive

Comparative Analysis for ZF Mgcawu District Municipality | ix Comparative Analysis for ZF Mgcawu District Municipality | x Comparative Analysis for ZF Mgcawu District Municipality | 1 Comparative Analysis for ZF Mgcawu District Municipality | 2 population growth that may as aresult be of for instance migration, and birth death. level as it was previous in the year Insight, (Global population 2016).The growth rate showstrend a in an area’s two years. The opposite fortrue is a negative output. the rateIf is 0% it meansthat populationthe is samethe at population from one year to next. the If output the is positive, it implies that population the the increased between municipalities from 2005 topopulation 2015.The growth rate representspercentagethe change selected the in graphThe below populationthe depicts growth rate forthe ZFMgcawu District Municipality and its local 1.2.2 Population Growth Rate rate,birth mortality rate decreased and inward migration. annual basis. An increase population in the attributed size could be to a number of factors including an increased had an increase population intheir size, with Tsantsabane recording largest the at cent 3.0 per on an average Municipalities, with former the largest the experiencing drop at cent. -1.6per The remaining local municipalities municipalities,local only adecline population inthe two 2experienced and were these Mier the and Local !Kheis ZF Mgcawu’s population has shown average annual growth of cent 1.5 per 2005and between 2015.With regard to guide planning and budget allocation. 2015. This is important, as it showsthere if adecrease populationbeen theor increasehas in thereforeand can Table 1.1below provides total the population for ZFMgcawu the and municipalities District its local for 2005and 1.2.1 Total Population 1.2 Population Profile analysis on indicators including population, urbanisation and population density. data for municipality new the was not available at of time the compiling document. this This chapter will provide Municipality.Dawid KruiperLocal However, analysis this refer will to two the municipalities individually as 2016. Since Mier the then, and //Khara Hais Municipalities Local have merged and municipality new the is called !Garib, Kgatelopele and Tsantsabane) before government local the elections that took place on third the of August The ZFMgcawu District Municipality was made up of 6local municipalities (!Kheis, Mier, //Khara Hais, Kai planning. in that it can assist municipalities to and know district local) (both status their quo, inturn assist will which with and changes their can which result from fertility, mortality and migration. This demographic analysis is crucial municipalities. Demography refers to study the of size, the composition, and distribution of human populations This chapter providesthe demographic profile the ZF for Mgcawu District Municipality together local with its 1.1 Introduction Chapter 1:Demography Source: Global Insight, 2016 [Version 993 (2.5v)] Table 1.1: Population Profile for ZF Mgcawu District and itsLocal Municipalities, 2005and 2015 % Change Change % 2015 2005 ZF Mgcawu DM 254 768 219 639 1.5 Mier LM 7 280 8 588 -1.6 Kai !GaribKai LM 67 789 62 138 0.9 //Khara Hais LM //Khara Hais 103 104 86 068 1.8 !Kheis LM !Kheis 17 180 18 022 -0.5 Tsantsabane LM Tsantsabane 39 272 29 303 3.0 Kgatelopele LM Kgatelopele 20 141 15 521 2.6 municipalities for 2005and 2015. numberthe of households and average number of household people per for ZFMgcawu and District its local jointly and/or with food other essentials for living, or lives asingle person who alone.table The below provides InsightGlobal (2016)defines a householdgroup as a personsof who live together whoand providethemselves 1.2.4 Households Kgatelopele had Africans representing largest the proportion of population. the comprised of more for Coloureds, case municipality the is which district also the as awhole. Tsantsabane and had more females than In males. terms of race, population the of Mier, Kai !Garib, //Khara Hais and are !Kheis than females and were these Mier, Kai !Garib, Tsantsabane and Kgatelopele. In contrast, //Khara Hais and !Kheis making up largest the share of total the population. With regard municipalities, to local the four had more males The ZFMgcawu District Municipality had morethanColoured males withthe in2015, females population for 2015. Table 1.2below provides population the by raceand gender for ZFMgcawu the and municipalities District its local 1.2.3 Population and Gender by Race municipalitieslocal showed positive growth throughout except under review for period the Mier and !Kheis. growth rate for Mier remained negativepopulation in2015.The growth rate the district of municipality and its on other the hand, show an upward trend after having rates falling from experienced 2006, butpopulationthe Tsantsabane and Kgatelopele have shown adownward trend inpopulation growth since 2009.Mier and !Kheis, Source: Global Insight, 2016[Version 993(2.5v)] Figure 1.1: Population Municipalities, Growth 2005-2015 Rate for and District its ZF Local Mgcawu Source: Global Insight, 2016 [Version 993 (2.5v)] Total Asian Coloured White African Race Table 1.2: Population and by Race Gender for ZF Mgcawu District and itsLocal Municipalities, 2015 Kgatelopele LM Kgatelopele LM Tsantsabane LM !Kheis LM Hais //Khara LM !Garib Kai LM Mier DM Mgcawu ZF 128 118 ZF Mgcawu DM 76 407 10 687 39 894 1 130 Male -4.0% -3.0% -2.0% -1.0% 1.0% 4.0% 0.0% 2.0% 3.0% PopulationGrowth Rate forZFMgcawu District anditsLocal 126 650 emale Fe 81 527 11 767 32 478 878 1.3% 1.9% 0.7% 1.4% 0.9% 0.1% 1.2% 2005 3 773 3 270 Male 183 298 22 -0.7% Mier LM 1.7% 2.2% 0.1% 0.8% 1.2% 1.5% 2006 emale Fe 3 507 3 097 156 227 27 Municipalities, 2005 Municipalities, -1.0% -2.3% 2.5% 2.8% 1.7% 0.7% 1.3% 2007 35 211 21 534 11 011 Kai !GaribKai LM 2 331 Male 335 -1.7% -3.3% 3.3% 3.5% 2.0% 0.8% 1.5% 2008 emale Fe 32 579 22 646 2 580 7 009 344 //Khara Hais LM //Khara Hais -1.6% -3.3% 11 905 49 783 32 594 3.4% 3.5% 2.0% 0.8% 1.5% 2009 4 879 Male 405 - 2015 emale Fe 11 127 53 322 36 070 -0.9% -2.3% 3.1% 3.5% 2.0% 0.9% 1.6% 5 796 2010 329 8 498 7 196 Male -0.3% -1.4% 2.8% 3.2% 1.9% 0.9% 1.7% 2011 439 736 127 !Kheis LM !Kheis emale Fe 8 682 7 705 -1.1% 402 492 2.6% 3.1% 0.0% 1.9% 1.0% 1.6% 2012 83 Tsantsabane LM Tsantsabane 10 987 20 675 1 859 7 625 Male 204 -0.8% 2.5% 2.9% 0.1% 1.8% 1.0% 1.6% 2013 emale Fe 18 597 1 760 9 074 7 717 46 -0.7% 2.3% 2.7% 0.2% 1.7% 0.9% 1.5% 2014 Kgatelopele LM Kgatelopele 10 177 4 957 4 189 Male 995 36 -0.5% 2.1% 2.4% 0.3% 1.6% 0.9% 1.4% 2015 emale Fe 1 074 4 549 9 964 4 292 49

Comparative Analysis for ZF Mgcawu District Municipality | 3 Comparative Analysis for ZF Mgcawu District Municipality | 4 Figure 1.2:Population for Municipality, District ZFMgcawu Pyramid 2015 municipalitieslocal for 2015. Figures 1.2to 1.8provide population the pyramids for ZFMgcawu the Municipality District together with its paneleft depicting males righttheand pane axis depictingthe depicts 5-year the females; agevertical categories. by gender and age for year and selected the region. The horizontal axisthe depicts number people,of withthe InsightGlobal population (2016) defines a pyramid visual as a representation populationthe of broken down 1.2.5 Population Pyramids households at cent. Municipality 26per Mier Local number had smallest the of households district. inthe making up centdistrict 39per of total the number of households. This was followed by Kai !Garibwith 18 018 When it comes municipalities, to local //Khara Hais had 26 719 households was which largest the number inthe The district municipality had a total of 68 823 householdswith in2015 an average household size people.of 3.70 than in2015. females district inthe and district provincethe the as awhole. The pyramid is skewed the left, to indicating that there were moremales to ensurewithin district the that large the youth can positively within district the contribute to economy the of cohort population with smallest the sizeis 75and more years. This indicates a forneed youth employment creation The agedistrict. cohort 20-24 years representsthelargest share the district’sof population total the agewhile The district municipality’spopulation pyramidbase, indicating haswide a large a number of childrenthe in Source: Global Insight, 2016[Version 993(2.5v)] Source: Global Insight, 2016 [Version 993 (2.5v)] 2015 2005 Table 1.3: Number of Households and Number Average of People per Household for ZF Mgcawu District and itsLocal Municipalities, 2005and 2015 15 000 Male households Number of of Number ZF Mgcawu DM 68 823 58 882 10 000 people per per people household of number Average Average 3.70 3.73 households Number of of Number Population Pyramid for ZF Mgcawu District Municipality, Municipality, District Mgcawu ZF for Pyramid Population 5 000 2 029 2 099 Mier LM people per per people household of number Average Average 3.59 4.09 00-04 05-09 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75+ households Number of of Number 0 Kai !GaribKai LM 18 018 19 067 people per per people household of number Average Average 3.76 3.26 5 000 households Number of of Number //Khara Hais LM //Khara Hais 26 719 20 992 Source: Source: people per per people household of number Average Average IHS Global Insight RegionalIHS Global eXplorer version 10 3.86 4.10 000 2015 households Number of of Number 4 504 4 504 !Kheis LM !Kheis Female people per per people household of number Average Average 15 000 3.81 4.00 households Number of of Number 993 TsantsabaneLM 11 508 7 898 people per per people household of number Average Average 3.71 3.41 households Number of of Number Kgatelopele LM Kgatelopele 4 323 6 045 people per per people number of of number household Average Average 3.59 3.33 Source: Global Insight, 2016[Version 993(2.5v)] Figure 1.4:Population Municipality, for Kai Local !Garib Pyramid 2015 more than males females, shown by skewness the of pyramid the to left. the aged15-19, whereas 70-74 years those comprised share smallest the of population. the The municipality had education have will prioritised to be within municipality. the The agegroup withthelargest population sizewas Mier’s population pyramid has a broad also and base implies this that development early childhood and primary Source: Global Insight, 2016[Version 993(2.5v)] Figure Municipality, 1.3:Population for Local Mier Pyramid 2015 6 400 000 Male Male 5 000 300 4 000 200 3 000 Population Pyramid for Mier Local Municipality, Local Mier for Pyramid Population Population Pyramid for Kai !Garib Local Municipality, Municipality, Local !Garib Kai for Pyramid Population 2 000 100 1 000 60-64 65-69 70-74 00-04 05-09 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 75+ 00-04 05-09 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 0 75+ 0 100 1 000 2 000 Source: Source: 200 Source: Source: 2015 IHS Global Insight RegionalIHS Global eXplorer version IHS Global Insight RegionalIHS Global eXplorer version 3 000 2015 300 4 000 Female Female 5 000 400 993 993

Comparative Analysis for ZF Mgcawu District Municipality | 5 Comparative Analysis for ZF Mgcawu District Municipality | 6 Source: Global Insight, 2016[Version 993(2.5v)] Municipality,Figure 1.6:Population for Local !Kheis Pyramid 2015 municipalitylocal had more females than as males indicated by pyramid’s the skewness to right. the age group that had largest the population is 15-19years 70-74years while number had smallest the of people. The //Khara Hais’ population pyramid indicating has base awide that there are more children municipality. inthe The Source: Global Insight, 2016[Version 993(2.5v)] Figure Municipality, 1.5:Population for Hais //Khara Local Pyramid 2015 indicating alarger number of incomparison males to females. employment creation important very is also municipality. inthis The municipality’s pyramid is skewed the left, to active population. With a large portion of people within municipality the ages the between of 15 and 34, youth of ages 70-74years were contributing share, smallest the implies which on economically less the dependency Young people aged 20-24years had largest the portionof population the of Kai !Garib in2015.Older people 1 6 500 000 Male Male 1 4 000 000 Population Pyramid for !Kheis Local Municipality, Local !Kheis for Pyramid Population Population Pyramid for //Khara Hais Local Municipality, Local Hais //Khara for Pyramid Population 2 500 000 00-04 05-09 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 00-04 05-09 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75+ 75+ 0 0 2 500 000 Source: Source: Source: IHS Global Insight Regional IHS Global eXplorer version Source: 2015 IHS Global Insight RegionalIHS Global eXplorer version 1 4 000 000 2015 Female Female 1 6 500 000 993 993 had the smallest populationhad smallest the sizeis 75and more years. The age cohort 25-29 years contributedthelargest share the to municipality’spopulation. total The age cohort that Source: Global Insight, 2016[Version 993(2.5v)] Figure 1.8:Population Municipality, for Kgatelopele Local Pyramid 2015 females. aged 70-74years those while represented percentage. smallest the The municipality had also more than males With regards to Tsantsabane, youth of age the 25-29years represented largest the percentage of total the population Source: Global Insight, 2016[Version 993(2.5v)] Figure 1.7:Population for Tsantsabane Pyramid Municipality, Local 2015 municipality.the its pyramid that has anarrow The base. pyramid is skewedright, the to indicatinglarger a number of in females aged 70-74yearsthose The had smallest. the local municipality had asmall also number of children as shown by In children !Kheis, of age the group 10-14years had largest the proportion of population the in2015,whereas 3 1 000 500 Male Male 2 500 1 000 2 000 1 500 PopulationPyramid forTsantsabane Local Municipality, PopulationPyramid forKgatelopele Local Municipality, 500 1 000 500 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 00-04 05-09 10-14 15-19 20-24 25-29 75+ 0 00-04 05-09 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75+ 0 500 500 1 000 Source: Source: Source: Source: IHS Global Insight RegionalIHS Global eXplorer version IHS Global Insight RegionalIHS Global eXplorer version 1 500 1 2015 2015 000 2 000 Female Female 2 1 500 500 993 993

Comparative Analysis for ZF Mgcawu District Municipality | 7 Comparative Analysis for ZF Mgcawu District Municipality | 8 municipalities 2005to for 2015. period the graph2016). The below illustrates populationthe density forthe ZFMgcawu District Municipality and its local by area the sizeof that region. The output thisthe of is number peoplekilometreper of squared (Global Insight, Population density measures concentration the of people inaregion by dividing population the of region the 1.4 Population Density Khara Hais recorded (6.8percentage smallest the points). With regard municipalities, to local the largest the Mier experienced increase (35.4 percentage points) // while a decrease. The district municipality’s urbanisation rate percentagerose by 10.7 points per cent to 85.8 in 2015. municipalities2015. All an increase inurbanisation experienced by end the of 2015except Kgatelopele had which ZF Mgcawu and municipalities its local generally showed an upward trend inurbanisation 2005and between Source: Global Insight, 2016[Version 993(2.5v)] Figure 1.9:Urbanisation Municipalities, 2005-2015 Rate for and District its Local ZFMgcawu Municipality together municipalities with its local 2005to for 2015. period the and employment opportunities. Figure 1.9 below provides urbanisation the rate for ZF Mgcawu the District urbanised. This maybe encouraged by various factors including standard of living, availability services of Urbanisation means movement the of people from to urban areas rural areas as well as rural becoming more 1.3 Urbanisation Kgatelopele Tsantsabane !Kheis //Khara Hais !Garib Kai Mier DM Mgcawu ZF Urbanisation Rate Urbanisation Rate for ZFMgcawu District andits Local Municipalities, 120.0% 100.0% 20.0% 40.0% 60.0% 80.0% 0.0% 88.9% 79.8% 65.1% 87.7% 56.9% 59.5% 75.1% 2005 88.8% 81.5% 68.1% 88.8% 59.0% 65.3% 76.8% 2006 90.1% 84.6% 72.3% 72.2% 79.9% 91.3% 62.1% 2007 91.5% 87.9% 76.7% 94.1% 65.4% 79.6% 83.2% 2008 2005 - 2015 80.2% 95.5% 67.9% 86.1% 85.3% 91.6% 89.9% 2009 81.5% 94.4% 68.4% 90.0% 85.1% 89.3% 89.3% 2010 83.8% 94.4% 69.9% 94.6% 85.8% 88.2% 89.9% 2011 84.6% 94.5% 70.5% 94.7% 86.3% 89.0% 90.8% 2012 85.4% 94.5% 71.2% 94.9% 86.8% 89.9% 91.7% 2013 85.6% 94.5% 71.3% 95.0% 87.0% 90.0% 92.0% 2014 83.3% 94.5% 69.4% 94.9% 85.8% 87.7% 89.6% 2015 density. Khara Hais had largest the number of households. Most of municipalities the inpopulation arise had experienced largest share of district’s the population, followed by Kai Mier !Garib population had smallest the while size. // followed by Africans. //Khara Hais people in2015,representing Municipality Local had atotal the of 103 104 females. With regard to race, Coloured the population contributed largest the share to district’s the total population of Northern the Cape’s total population. population Ofthis cent 50.3per cent were 49.7per were while males The ZFMgcawu District Municipalitypopulation had a which in2015 of 254 768 represented aboutper cent 21 1.5 Conclusion stability. resources and height the as well as shape of land. the Human factors may include and economic, political social an area’s population density andnatural can be these or human factors. Natural factors may include climate, municipalities that had adecline population intheir densities. There are a number of factorsthat can influence population density, with Kgatelopele recording largest the increase. Mier and were !Kheis only the two local municipalities of Kai !Garib, //Khara Hais, Tsantsabane and Kgatelopele an increase inthe experienced also 2015. This impliesthat therethe district in rise municipality’s was a population relative to its area size.local The ZF Mgcawu’s population density increased by square 0.34people per kilometre from 2.14in2005to 2.48in Source: Global Insight, 2016[Version 993(2.5v)] Figure 1.10:Population Municipalities, 2005-2015 Density for and District its Local ZFMgcawu Kgatelopele Tsantsabane !Kheis Hais //Khara !Garib Kai Mier Mgcawu ZF Population Density for ZF Mgcawu District and its Local Municipalities, Municipalities, Local its and District for ZFMgcawu Density Population 0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00 9.00 2005 6.25 1.08 2.09 3.58 2.92 0.45 2.14 2006 6.36 1.11 2.10 3.64 2.95 0.44 2.16 2007 6.52 1.14 2.08 3.70 2.97 0.43 2.19 2008 6.74 1.18 2.04 3.77 2.99 0.42 2.22 2005 2009 6.96 1.22 2.01 3.85 3.01 0.40 2.26 - 2015 2010 7.18 1.26 1.99 3.93 3.04 0.39 2.30 2011 7.38 1.30 1.98 4.01 3.07 0.39 2.33 2012 7.58 1.34 1.98 4.08 3.10 0.38 2.37 2013 1.38 1.99 4.15 3.13 0.38 7.77 2.41 2014 7.95 1.42 1.99 4.22 3.16 0.38 2.45 2015 8.12 1.45 2.00 4.29 3.19 0.38 2.48

Comparative Analysis for ZF Mgcawu District Municipality | 9 Comparative Analysis for ZF Mgcawu District Municipality | 10 municipalities from also 2005to 2015. over Figure same the 2.2 illustrates period. average the GDP growth rates for ZF Mgcawu and District its local Tablewhile 2.2provides annual the GDP growth rates for ZF Mgcawu the and municipalities District its local Table 2.1shows GDP the for ZFMgcawu the and municipalities District its local 2005to for 2015 period the contributionsincreased their 2005and between 2015. Mier onlywhile contributed cent. 2.0per Tsantsabane and Kai !Garib are municipalities only the local that 2005and inboth smallest 2015.//Khara Hais contributed cent 34.6per to district’s the total economy in2015 //Khara Hais followed by Kai !Garib made largest the contributions to district’s the Mier GDP made the while Source: Global Insight, 2016[Version 933(2.5v)] (Constant 2010Prices) MunicipalityFigure 2.1: GDP to Municipality, District Contributions ZF Mgcawu Local per 2005 and 2015 to economy the of ZFMgcawu for District 2005and 2015. over aone plus year period, taxes and minus subsidies. Figure 2.1shows contribution the municipalities by local GDP is defined by Global that Insight the (2016) valueareas services and all goods of producedwithin a region, 2.2 GDP region.in the be done through Thiswill the analysis grossthe of domestic performanceproduct (GDP), industry and tourism This chapter looks economicthe at performance the ZF Mgcawuof District Municipality and its local municipalities. 2.1 Introduction Chapter 2:Economy Source: Global Insight, 2016[Version 933(2.5v)] ZF Mgcawu DM Kgatelopele LM Tsantsabane LM LM !Kheis //Khara Hais LM LM !Garib Kai LM Mier Table 2.1: GDP for ZF Mgcawu District and itsLocal Municipalities, 2005-2015 [Constant 2010Prices (R1000)] 10.0% 15.0% 20.0% 25.0% 30.0% 35.0% 40.0% 0.0% 5.0% 2015 2005 Mier LM Mier 2.0% 2.5% 12 934233 1 659431 2 655508 4 618750 3 081739 GDP Contributions per Local Municipality to ZF Mgcawu District District Mgcawu ZF to Municipality Local per Contributions GDP 2005 600 635 318 170 Municipality, 2015(Constant 2005and 2010Prices) 13 440511 1 634631 2 642556 4 997050 3 213302 2006 Kai !Garib LM !Garib Kai 620 457 332 515 24.9% 23.8% 13 851272 1 617482 2 648164 5 130453 3 469476 2007 640 019 345 677 13 924124 //Khara Hais //Khara 1 470123 2 402689 5 311256 3 696273 361 903 681 881 2008 34.6% 35.7% LM 13 690745 1 556514 2 518885 5 021403 3 606358 2009 336 219 651 366 !Kheis LM !Kheis 14 062182 1 637219 2 613041 3 741637 5 098231 4.0% 4.6% 2010 660 028 312 027 14 338190 3 891023 1 569166 2 753273 5 174336 2011 656 429 293 962 Tsantsabane LM Tsantsabane 23.1% 20.5% 15 191926 2012 1 791259 3 203671 5 300218 3 943875 652 959 299 944 Kgatelopele LM Kgatelopele 15 692507 1 873659 3 408250 5 466990 3 991994 2013 644 348 307 265 11.3% 12.8% 15 983967 3 965030 1 818593 3 721666 5 540571 2014 624 551 313 555 15 637666 3 894730 1 765684 3 615192 5 415477 2015 629 723 316 860 forces. achieved. Thus, it is important to explorewhy the prevailingeconomic conditions exist whatand arethe driving and it policies, is to vital understand underlying the economic challenges or where growth to best the see is major economic In district. inthe activities order for municipalities the to implement intervention programmes The ZFMgcawu District’s IntegratedDevelopment Plan (IDP) 2015/16 agriculturerecognises and mining as Industries2.3 Economic municipality negative to experience average annual growth. Kai highest the average !Garib experienced annual growth Mier had lowest. the while only Mierthe was also local ZF Mgcawu had an average annual growth rate of cent 1.92per 2005and between 2015.Tsantsabane followed by Kgatelopele!Kheis. and Tsantsabane had largest the negative growth rates in2015. contractions inKai !Garib, //Khara Hais, Tsantsabane and Kgatelopele together with low growth inMier and grew at cent economy in2015the 6.6per while contracted by cent. 2.2per This declinebe could attributed to economicThe growth hasthe declined under district of study.period overthe In 2005, ZF Mgcawu’seconomy Source: Global Insight, 2016[Version 933(2.5v)] (Constant 2010Prices) Figure 2.2:Average GDP Municipalities, Growth 2005-2015 Rates for and District its Local ZFMgcawu Source: Global Insight, 2016[Version 933(2.5v)] ZF Mgcawu DM Kgatelopele LM Tsantsabane LM LM !Kheis //Khara Hais LM LM !Garib Kai LM Mier Table 2.2: Annual GDP Growth for ZF Rates Mgcawu District and itsLocal Municipalities, 2005-2015 (Constant 2010Prices) % GDP Growth GDP -0.50 0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 Average GDP Growth Rates for ZFMgcawu District andits Local ZF Mgcawu ZF 2005 1.92 DM 13.3% 15.2% 15.9% 11.2% -9.1% -6.0% 6.6% Municipalities, 2005 Municipalities, 2006 -1.5% -0.5% 3.9% 3.3% 8.2% 4.3% 4.5% Mier LM Mier -0.04 2007 -1.0% 3.1% 0.2% 3.2% 2.7% 8.0% 4.0% Kai !Garib Kai 2.37 LM 2008 -9.1% -9.3% - 0.5% 6.5% 3.5% 6.5% 4.7% 2015 (Constant2010 Prices) 2009 Hais LM Hais -1.7% -2.4% -4.5% -5.5% -7.1% //Khara 5.9% 4.8% 1.60 2010 -7.2% 2.7% 3.7% 1.3% 1.5% 3.8% 5.2% !Kheis LM !Kheis 0.47 2011 -5.8% -4.2% -0.5% 2.0% 5.4% 4.0% 1.5% Tsantsabane 2012 16.4% 14.2% -0.5% 3.13 6.0% LM 2.4% 1.4% 2.0% 2013 -1.3% 3.3% Kgatelopele 6.4% 3.1% 1.2% 2.4% 4.6% 0.62 LM 2014 -3.1% -0.7% -2.9% 1.9% 9.2% 2.0% 1.3% 2015 -2.2% -2.9% -2.3% -1.8% -2.9% 0.8% 1.1%

Comparative Analysis for ZF Mgcawu District Municipality | 11 Comparative Analysis for ZF Mgcawu District Municipality | 12 for 2005and 2015. Table 2.4below shows GDP the growth rate for industry per ZFMgcawu the and municipalities District its local construction, trade, transport, finance and community industries. services output.agricultural //Khara Hais is largest the contributing municipality local manufacturing, inthe electricity, mostly inKai practised !Garib and //Khara Hais together which generated over cent 80per of district’s the total more cent than 90per of total the value of 2005and inboth mining 2015.Agricultural district inthe activity is Mining is largest the ZFMgcawu inthe industry with Tsantsabane District, and Kgatelopele accounting for recorded contractions of inall industries the in2015. mining in2015.//Khara Hais and Kai !Garib had largest the negative growth rates inagriculture. //Khara Hais recorded and also electricity trade contractions. of All municipalities the saw negative growth inagriculture and mining and construction; industries with these contracting by 8.1,5.4and cent 3.1per respectively, while The negativeeconomic growth in ZFMgcawube in2015 could attributed largeto contractions in agriculture, ZF Mgcawu in2005and 2015. Table 2.3below provides contributions the municipalities that local the made to economic the totals of industry ZF Mgcawu DM Kgatelopele LM Tsantsabane LM LM !Kheis //Khara Hais LM LM !Garib Kai LM Mier Table 2.3: Contributions by Local Municipalities to Economic Industry Totals for ZF Mcgawu District Municipality, 2005and 2015(Constant 2010Prices) Source: Global Insight, 2016[Version 933(2.5v)] Source: Global Insight, 2016[Version 933(2.5v)] ZF Mgcawu DM Kgatelopele LM Tsantsabane LM LM !Kheis //Khara Hais LM LM !Garib Kai LM Mier Table 2.4: Growth per Rate Industry for ZF Mgcawu District and itsLocal Municipalities, 2005and 2015(Constant 2010Prices) 2005 36.6% 44.7% 100% 27.0% Agriculture 2005 14.4% 17.3% 25.4% 29.8% 27.4% 22.0% 2.4% 5.9% 7.6% 2.9% Agriculture 2015 34.8% 47.9% 100% 2015 -8.1% 2.3% 6.5% 6.5% 2.1% -6.1% -4.7% -6.3% -9.2% -8.2% -5.7% -10.1% 2005 -11.7% 37.8% 53.4% 100% 2005 -9.8% -4.9% -4.7% -5.4% -7.5% 4.3% 2.8% 0.6% 1.1% Mining Mining 2015 32.0% 59.9% 100% 2015 -5.4% -4.4% -5.7% -6.2% -7.4% -6.4% -7.3% 3.9% 2.6% 0.5% 1.0% Manufacturing Manufacturing 2005 49.9% 27.6% 100% 18.8% 2005 17.8% 22.0% 20.0% 14.9% 5.4% 8.6% 5.9% 2.5% 6.5% 8.9% 2015 48.6% 30.2% 100% 2015 -2.0% -0.3% 4.7% 9.4% 5.2% 1.9% 0.5% 1.2% 4.1% 1.1% 4.8% 2005 11.9% 42.0% 24.7% 100% 17.1% 2005 18.2% 14.7% 18.4% 47.5% 6.3% 7.1% 8.1% Electricity 4.4% 4.6% Electricity 2015 11.9% 37.2% 28.6% 10.5% 100% 2015 -1.0% -3.0% -1.7% 5.8% 5.9% 1.2% 2.4% 1.4% 2.3% 2005 42.0% 32.5% 15.2% Construction 100% 2005 18.7% 14.6% 16.8% 12.1% Construction 9.9% 6.1% 3.5% 5.9% 3.7% 6.0% 2015 11.5% 40.2% 34.9% 100% 2015 -3.1% -0.9% -4.6% -1.2% -3.5% -0.4% 5.8% 2.6% 5.1% 0.7% 2005 11.2% 52.0% 29.5% 100% 2005 13.6% 11.7% -0.5% 6.9% 3.5% 2.3% 5.8% 2.0% 9.6% 7.1% Trade Trade 2015 50.1% 31.7% 100% 2015 -0.1% -1.3% 8.1% 3.4% 1.7% 5.1% 2.7% 3.6% 2.7% 0.0% 3.7% 2005 10.9% 10.8% 49.0% 27.4% 100% 2005 14.0% 10.6% 12.6% -1.2% 4.5% 2.3% 6.0% Transport 0.7% 7.7% Transport 2015 11.9% 46.9% 30.1% 100% 2015 -0.4% 1.1% 4.1% 1.7% 5.3% 3.9% 5.1% 3.5% 0.9% 4.8% 15.5% 2005 51.7% 28.0% 100% 2005 18.0% 14.5% 15.8% 11.9% 9.6% 3.7% 2.2% 4.9% 6.1% 7.3% Finance Finance 2015 10.0% 50.8% 29.6% 2015 100% -1.0% 0.0% 3.4% 1.7% 4.5% 1.7% 2.4% 2.7% 0.2% 2.8% 2005 11.6% 46.6% 28.0% 2005 11.5% 100% -2.7% -0.4% Community Community Community Community 8.2% 4.8% 3.3% 5.6% 7.5% 9.5% 5.1% Services Services 2015 13.4% 44.7% 30.1% 2015 100% -1.1% 0.4% 4.5% 2.5% 4.8% 2.5% 3.7% 2.8% 0.2% 4.5% Total Industries Total Total Industries Total 2005 2005 15.9% 13.1% 15.5% 10.8% 21.3% 13.3% 35.1% 23.3% 100% -8.9% -5.9% 6.5% 2.4% 4.5% 2015 2015 -2.2% 23.6% 11.4% 34.4% 24.7% 100% -3.1% -3.1% -2.2% -1.8% 0.8% 1.0% 2.0% 3.9% and smallest. 2015with the being !Kheis In tourism, //Khara Hais and Kai !Garib were largest the contributors to total the of in2005 bednights district the in agriculture, mining and construction. of All municipalities the saw adecline inagriculture and mining in2015. district’sthe GDP. The negativeeconomic growth inZFMgcawube in2015could attributed largeto contractions Hais and Kai !Garib are economic the hubs of ZF Mgcawu the together District, contributing more than of half evident This was thedistrict. contractions in in agricultural and mining output in2015.//Khara the district in andcountry commodity falling the prices; since agriculture and mining are major the economic inthe activities economyThe the ZFMgcawuof District Municipality was adversely affected the by drought that the hit entire 2.5 Conclusion //Khara Hais together contributed over cent 75per to total the of bednights ZFMgcawu years. inboth district contributor. contributor was !Kheis smallest the to total years. the of inboth bednights district the Kai !Garib and tobednights second the being largest in2015,only 0.2percentage points less than Kai !Garib, largest new the Mgcawu. //Khara Hais moved from largest the being contributor in2005by contributing cent 44.8per of total the There are slight changesthe contributions in that the local municipalities made thebednights to in ZF total refer to number the of nights that aperson spends away from home on asingle person trip. and international) inZFMgcawu are shown for 2005and 2015.According to Insight Global (2016),bednights In Table 2.5below, municipalities’ local the contributions to total the spent bednights by tourists domestic (both 2.4 Tourism Source: Global Insight, 2016 [Version 933(2.5v)] Kgatelopele LM Tsantsabane LM LM !Kheis //Khara Hais LM LM !Garib Kai LM Mier Table 2.5: Local Municipality Contributions to Total Bednights of ZF Mgcawu District Municipality, 2005and 2015 2005 44.8% 34.0% 3.8% 9.0% 3.2% 5.2% 2015 38.2% 38.0% 4.5% 6.7% 9.7% 2.8%

Comparative Analysis for ZF Mgcawu District Municipality | 13 Comparative Analysis for ZF Mgcawu District Municipality | 14 percentage points) over same the period. and 2015are shown inTables 3.2and 3.3respectively. Table 3.4shows changes the unemployment inthe rate (in Employment and unemployment by raceand gender for ZFMgcawu and municipalities District its local for 2005 of under study. 13 538for period the cent20.3 per in2015.//Khara Hais recorded largest the increase working inthe age (15to 64years) population (2005to 2015)ZFMgcawudecade managed to its decrease unemployment rate from cent 22.2per in2005to unemployment rate in2015at cent, 32.3per was which asharp increase from cent 21.2per in2005.In past the municipalities inemployment that adecrease experienced 2005and between had 2015.!Kheis highest the Kai !Garib and //Khara Hais employed most the people2005and inboth 2015.Mier and are !Kheis only the unemployed people. andwilling actively looking for work and are who ages the between of 15and 64and thus includes employed and definitionstrict of unemployment. economically The active population the is people number of who are able, The unemployment ratepercentagethe is economicallythe of population active that are unemployedthe per as definition and are referred to as discouraged workseekers, forming part the of noteconomically population. active Insightpeople (2016).Thewho are not activelyseeking work (and would like to work) are excludedfrom this considering people are who all currently not working, but are actively looking for work as defined by Global Mgcawu and municipalities District its local for 2005and definition 2015.The strict of unemploymentused, is and economically active or not economically active). Table 3.1below shows labour characteristics for ZF the characteristicsLabour relates to an individual’s employment status instance (inthis employed or unemployed Status3.2 Labour employment for and eachindustry lastly employment distribution by industry. covers labour the characteristics, employment and unemployment by raceand gender, contributions to total is to create a more inclusive and more dynamic economy that create will more job opportunities. This chapter anbeing exception. One way of reducing unemployment according to National the Development Plan (NDP) encountering is still South Africa challenges levels with high of unemployment, with Northern the Cape not 3.1 Introduction Chapter 3:Labour Working population age (15-64 years) Not economicallyNot active Economically active Economically Unemployed Working population age (15-64 years) Employed economicallyNot active Economically active Economically Unemployed Employed Table 3.1: Labour Characteristics for ZF Mgcawu District and itsLocal Municipalities, 2005and 2015 Source: Global insight [Version 993 (2.5v)] 143 415

ZF Mgcawu DM 100.0% 55 314 88 102 19 528 68 574 2005 38.6% 61.4% 22.2% 77.8% 173 917 107 801

100.0% 66 116 21 857 85 943 2015 38.0% 62.0% 20.3% 79.7%

100.0% 2005 49.8% 50.2% 26.0% 5 158 74.0% 2 566 2 591 1 917 674 Mier LM

100.0% 2015 48.5% 51.5% 29.0% 4 791 71.0% 2 325 2 466 1 751 715

100.0% 42 408 13 317 29 091 25 012 Kai !GaribKai LM 2005 31.4% 68.6% 14.0% 86.0% 4 079

100.0% 48 714 15 666 33 048 28 906 2015 32.2% 67.8% 12.5% 87.5% 4 142

//Khara Hais LM //Khara Hais 100.0% 55 289 22 959 32 329 23 749 2005 41.5% 58.5% 26.5% 73.5% 8 580

100.0% 68 827 30 232 38 595 28 970 2015 43.9% 56.1% 24.9% 75.1% 9 624

100.0% 11 008 2005 43.3% 56.7% 21.2% 78.8% 4 772 6 236 1 320 4 916 !Kheis LM !Kheis

100.0% 10 850 2015 40.9% 59.1% 32.3% 67.7% 6 410 4 440 2 072 4 338

Tsantsabane LM Tsantsabane 100.0% 19 339 11 838 2005 38.8% 61.2% 28.3% 71.7% 7 501 3 353 8 485

100.0% 27 202 18 749 15 114 2015 31.1% 68.9% 19.4% 80.6% 8 453 3 635

Kgatelopele LM Kgatelopele 100.0% 10 215 2005 41.1% 58.9% 25.3% 74.7% 4 198 6 016 1 521 4 495

100.0% 13 533 2015 36.9% 63.1% 19.6% 80.4% 5 000 8 533 1 669 6 864 more work done to be to address gender the inequality labour inthe market. municipalities it in!Kheis local increased while by 8.5percentage points 2005and between 2015.There is still Coloured unemployment most the inKgatelopele. decreased The unemployment rate in of five decreased females Thelargest unemploymentthe in African decrease rate in seen canbe Tsantsabane, followed by //Khara Hais. municipalities of inall local males the 2005and inboth 2015. 10 percentage points. With exception the of unemployment Mier higher in 2015, females experienced rates than majorityin the municipalities, of local the difference the between male and unemploymentfemale wasthan less recorded lowest the unemployment rate at cent 4.8per and cent 4.9per in2005and 2015respectively. In 2015, unemployment municipalities rate local the of inall ZFMgcawu except inKgatelopele. In ZFMgcawu, Whites at cent 98.1per and cent 98.7per in2005and 2015respectively. In 2015,Coloureds recorded highest the Kai !Garib had highest the percentage of economically the active population inemployment amongst Africans Female Male Gender Asian Coloured White African Race African Race Female Table 3.3: Employment and Unemployment and by Race Gender for ZF Mgcawu District and itsLocal Municipalities, 2015 Table 3.2: Employment and Unemployment and by Race Gender for ZF Mgcawu District and itsLocal Municipalities, 2005 White Coloured Asian Male Gender Source: Global insight, 2016 [Version 993 (2.5v)] Source: Global insight, 2016 [Version 993 (2.5v)] White African Race Table 3.4: Changes in Unemployment and by Race Rate Gender for ZF Mgcawu District and itsLocal Municipalities, 2005-2015 Source: Global insight, 2016 [Version 993 (2.5v)] Female Male Gender Asian Coloured Employed Employed ZF Mgcawu DM ZF Mgcawu DM ZF Mgcawu DM 77.1% 81.5% 80.2% 71.5% 95.1% 87.5% 82.2% 73.1% 95.2% 71.1% 76.9% 81.3% Unemployed Unemployed 22.9% 18.5% 19.8% 28.5% 12.5% 17.8% 26.9% 28.9% 23.1% 18.7% 4.9% 4.8% -3.4% -0.4% -5.3% -4.0% -0.2% 0.1% Employed Employed 71.0% 71.0% 71.8% 66.2% 97.6% 93.4% 95.9% 65.9% 97.8% 70.4% 73.0% 79.1% Mier LM Mier LM Mier LM Unemployed Unemployed 29.0% 29.0% 28.2% 33.8% 34.1% 29.6% 27.0% 20.9% 2.4% 6.6% 4.1% 2.2% -5.1% 1.2% 4.1% 0.3% 2.5% 8.1% Employed Employed Kai !GaribKai LM !GaribKai LM Kai !GaribKai LM 86.9% 87.9% 75.6% 74.3% 96.1% 98.7% 98.1% 84.9% 95.6% 73.2% 66.8% 86.8% Unemployed Unemployed 13.1% 12.1% 24.4% 25.7% 15.1% 26.8% 33.2% 13.2% 3.9% 1.3% 1.9% 4.4% -8.9% -1.1% -0.6% -0.6% -2.0% -1.1% Employed Employed //Khara Hais LM //Khara Hais //Khara Hais LM //Khara Hais //Khara Hais LM //Khara Hais 73.6% 76.2% 77.2% 69.8% 94.5% 79.0% 68.8% 68.8% 95.6% 68.7% 73.0% 77.2% Unemployed Unemployed -10.2% 26.4% 23.8% 22.8% 30.2% 21.0% 31.2% 31.2% 31.3% 27.0% 22.8% -4.8% -4.2% -1.1% 5.5% 4.4% 1.0% 1.1% Employed Employed 62.9% 70.7% 83.6% 63.7% 92.2% 84.8% 88.3% 71.4% 95.3% 75.5% 89.7% 83.4% !Kheis LM !Kheis !Kheis LM !Kheis !Kheis LM !Kheis Unemployed Unemployed 37.1% 29.3% 16.4% 36.3% 15.2% 11.7% 28.6% 12.7% 11.9% 24.5% 10.3% 16.6% 7.8% 4.7% 3.1% 3.5% 8.5% 6.1% Employed Employed Tsantsabane LM Tsantsabane Tsantsabane LM Tsantsabane LM Tsantsabane 74.6% 84.2% 92.1% 75.6% 96.7% 80.8% 64.8% 60.7% 94.2% 71.6% 82.9% 78.8% Unemployed Unemployed -15.9% -13.9% -5.4% -9.2% -3.9% -2.5% 25.4% 15.8% 24.4% 19.2% 35.2% 39.3% 28.4% 17.1% 21.2% 7.9% 3.3% 5.8% Employed Employed Kgatelopele LM Kgatelopele Kgatelopele LM Kgatelopele LM Kgatelopele 73.9% 84.2% 85.5% 79.0% 93.6% 78.0% 64.0% 81.2% 71.4% 93.7% 68.1% 86.9% Unemployed Unemployed -10.9% -3.0% -6.6% -9.9% 26.1% 15.8% 14.5% 21.0% 22.0% 36.0% 18.8% 28.6% 31.9% 13.1% 0.2% 1.4% 6.4% 6.3%

Comparative Analysis for ZF Mgcawu District Municipality | 15 Comparative Analysis for ZF Mgcawu District Municipality | 16 distributed among industries. the forgraph 2015.The shows howthe total formal employment theeachand district in local municipality is Figure 3.2 below shows employment the distribution by for industry ZF Mgcawu and District municipalities its local potentialthe to increase through expanding production demand. and local largestthe share to mining the industry’s employment Employment district. inthe agriculture inthe has industry electricity, construction, trade, transport, finance, and community industries. services Tsantsabane contributed agriculturethe and households industries, //Khara Hais while was largest the employer manufacturing, in the Mier, and !Kheis Kgatelopele eachcontributed less cent. than 10per Kai !Garib was largest the employer in //Khara Hais and Kai !Garib eachcontributed over cent 30per to total the employment ofwhile district, the Source: Global Insight, 2016[Version 933(2.5v)] Municipality,District 2015 Municipalities’ ContributionsFigure 3.1:Local to Total inZFMgcawu Industry Employment of Each ZFMgcawu inthe industry Municipality District in2015. Figure 3.1below shows how various municipalities the local contributed to total the formal employment of each 100% 10% 20% 30% 40% 50% 60% 70% 80% 90% 0% Local Municipalities' Contributions to Total Employment of Each Industry in ZF in Industry Each of Employment Total to Contributions Municipalities' Local MgcawuDistrict Municipality, 2015 Mier LM Mier LM !Garib Kai LM Hais //Khara LM !Kheis LM Tsantsabane LM Kgatelopele an increase. infivedecreased the local of municipalitiesbetween 2005 andthe 2015.!Kheis is only municipalitythat recorded labour market of region the it when comes to addressing gender equality, as unemployment the rate of females unemployment rate in2015 across municipalities of all local the except inKgatelopele. There was progressthe in demand the between and supply of In skills. terms of unemployment by race, Coloureds recorded highest the potentialthe to influencethelabour status are migration, educationandskills and ensuringthat there is a match fairly is still with an district the high unemployment rate of cent 20.3per in2015.Some of factors the that have unemployment inthe decrease rates of Kai !Garib, //Khara Hais, Tsantsabane and Kgatelopele, unemployment in and to create decent and sustainable jobs.Although unemployment the rate due district inthe to a decreased Thelabour characteristics showsthat more workbe done to needs inZF Mgcawu unemploymentto minimise 3.3 Conclusion ofjurisdiction //Khara Hais municipal together with local the offices. cent.per This is due to provincial government district offices and district municipal being offices situated in the municipalities. //Khara Hais had largest the share of people employed at community in industry the 30.4 services made industry an insignificantThe electricity contribution to employment less thanlocal percentwith the 1 all in was largest mining the the industry employer, employing 46.5and cent 45.0per respectively. employment agriculture inthe in ZFMgcawu industry cent was 27.7per in2015.In Tsantsabane and Kgatelopele, According to Kai !Garib’s IDP of 2015,most of commercial the farmers produce grapes region. inthe The overall Kgatelopelein 2015,while percentage had smallest the of people employed at industry cent. in this 5.1per The agriculture in industry Kai !Garibthelargest was employerthe in municipality employing per centover 50 Source: Global Insight, 2016[Version 933(2.5v)] Figure 3.2:Employment Municipalities, Distribution 2015 by for Industry and District its Local ZFMgcawu 100% 10% 20% 30% 40% 50% 60% 70% 80% 90% 0% ZF Mgcawu ZF DM Employment Distribution by Industry for ZF Mgcawu District and and District ZF Mgcawu for Industry by Distribution Employment Mier LM Mier Kai !Garib Kai LM its Local Municipalities, 2015 Municipalities, Local its Hais LM Hais //Khara !Kheis LM !Kheis Tsantsabane LM Kgatelopele LM Electricity Construction Trade Transport Finance services Community Agriculture Mining Manufacturing Households

Comparative Analysis for ZF Mgcawu District Municipality | 17 Comparative Analysis for ZF Mgcawu District Municipality | 18 resource allocation for poverty alleviation. area. assistsalso This with identifying areaswhere resources shouldbe directed to ensure effective and efficient It is imperative that poverty the indicators region are inorder inevery assessed to gauge level the of poverty inthe (percentage of people inpoverty) and poverty the gap rate. line and is expressed as apercentage of upper the bound poverty line. The coveranalysispovertywill theboth rate an indicator to measure depth the of poverty. It measures average the distance of population the from poverty the and varies according to sizeof the that household. According to Insight Global poverty (2016),the gap as is used poverty income, where poverty isthe defined minimumas monthly incomethat to is sustainneeded a household people inpoverty is thusthe defined as number peopleof living ina householdthat have an incomethan less the For of study, this purpose the definition the from Global Insight to define (2016) is used poverty. The number of without sacrificing one forthe other. as level the of consumption at individualswhich are able to purchase sufficient both food and non-food items someindividuals sacrifice itemsfood in order to obtainthe non-food items. The linepoverty upper is defined theis defined levelas of consumptionthat includes both and essential food non-food items, but requiresthat individuals are unable to purchase sufficient tofood provide them with an adequate diet. The lower line poverty line and an upper poverty line. Statspoverty linethethe SAdefines level as food of consumptionbelow which of money, therefore it changes year. every Stats SAdistinguishes poverty line, afood alower between poverty minimum standard of living is by determined Statistics (Stats on South Africa inflation SA)based timeand value appropriate assistance. social The acceptable minimum standard of livingknown is povertythe as line. The andfood water security, and social including, are ifthey unable to support themselves and dependents, their According to Constitution, South the African Act 108of has right 1996,everyone the to have access to sufficient 4.2 Poverty Indicators able be to redirect will hence resources they district; this where are most. they the needed governmentand local in a better be position to will challenges understand by faced social the municipalities in people have progressed or regressed. By analysing variables these for aspecific area or district, provincial, district Index to enable(HDI) and government access to services to gauge development the whether and conditions of the It is important studying when human development to consider variables of poverty levels, Human the Development 4.1 Introduction Chapter 4:Human Development ZF Mgcawu and municipalities District its local for 2005 and 2015. 1, with 0indicating no development 1indicates development. while perfect The figure below depicts the HDI of and standard the of living dimension is measured by gross national income capita. per The HDI rangesfrom 0 to schooling for adults aged 25years and older years and of expected schooling for children of schoolentering age; dimensionhealth at by is assessed education the birth; life expectancy dimension is measured by mean of years of human development: along and healthy life, knowledgeable being and having adecent standard of living. The The United Nations (UN) definesmeasure HDI asa summary of average achievement inkey dimensions of 4.3.1 Human Development Index ZFMgcawuin the Municipality District as well municipalities. as inits local The development indicatorsthat arebelow analysed arethe HDI theand income distribution peoplethe of living 4.3 Development Indicators cent more on average to get to poverty the line in2015. grants.access to The social impoverishedpeoplethe ZFMgcawu in per whole earn 24.1 to as a District needed a reduction poverty inthe gap rate; some of factors these are an increase inemployment or an improvement in cent to having lowest the in2015at cent, 22.8per together with There !Kheis. are many factorsthat can lead to was //Khara Hais at cent. 24.4per Mier improved from having highest the poverty gap rate in2005at 31.8per povertythe gap rate. Tsantsabane had highest the poverty gap rate in2015at cent, 25.6per second the highest The percentagereductionthe in peopleof livingpoverty accompanied in also in2015was by a reduction in at cent. 35.2per less cent than 40per in2015.In 2015,Kai !Garib had highest the poverty rate at cent 37.8per followed by !Kheis municipalitiesAll saw asignificant decline in povertyits ratesbetween 2005 and 2015, recordingpoverty rates of and 2015. Mier followed by had!Kheis highest the poverty rates at 63.1 and cent 61.6per respectively in 2005. municipality with apoverty rate of below cent 50per in2005and recorded lowest the poverty rate 2005 inboth povertythe rate of province the was which at 55.8in2005and cent 38.6per in2015.Kgatelopele was only the The district municipalitypoverty had a rate per centof 53.0 in2005 per centand 34.0 in2015.Thisbelow is 2015. Table 4.1below shows poverty the indicators for ZFMgcawu the and municipalities District its local for 2005and Source: Global Insight, 2016, [Version 993(2.5v)] ZF Mgcawu DM ZF Mgcawu LM Kgatelopele LM Tsantsabane LM !Kheis LM Hais //Khara LM !Garib Kai LM Mier Municipalities 4.1: PovertyTable ZF2015 for Indicators 2005and District Municipalities, itsLocal Mgcawu and % of People in in People of % Poverty 53.0% 44.0% 51.5% 61.6% 52.1% 53.3% 63.1% 2005 Poverty Gap Rate 30.6% 30.0% 30.8% 31.2% 30.6% 30.1% 31.8% % of People in in People of % Poverty 34.0% 26.7% 30.0% 35.2% 34.4% 37.8% 30.4% 2015 Poverty Gap 24.1% 24.3% 25.6% 22.8% 24.4% 23.4% 22.8% Rate

Comparative Analysis for ZF Mgcawu District Municipality | 19 Comparative Analysis for ZF Mgcawu District Municipality | 20 of ZFMgcawu Municipality District and municipalities its local for 2005and 2015. populationin the earning income, earns else nothing. everyone whilst The figure below shows the Gini-Coefficient distributed manner equal 1means while that inaperfectly income is completely inequitable, with one individual The is measureGini-Coefficient a of incomeinequality. Itvaries from 0 to1,with 0 indicating that incomes are 4.3.2.1 Gini-Coefficient of Gini-Coefficient the as the as well income distribution between households. exploressection This the extent of distribution of income inZFMgcawu. be throughdone will This the analysis a developmental inSouth Africa. trajectory that sustainable economic growth increases income and productivity are which unarguably key components for The NDP identifies needthe to economic increase growth and expand employment. Thenotion behind this is 4.3.2 Income Distribution The HDI for was 0.66in2015. the district 2005andbetween 2015.In 2015,Kgatelopele and Tsantsabane had highest the HDIs at 0.69and 0.68respectively. evidentThis was forpoverty all the rates of decreased municipalities experienced all as and an increased HDI developed and are who presented with opportunities to better lives their is associated with alower poverty rate. is an inverse relationship HDI the and between poverty the rate, an increase number inthe of people getting below 0.5.Kgatelopele followed by //Khara Hais had highest the HDIs at 0.59and 0.58respectively in2005.There municipality was!Kheis only the local that district inthe was not in2005,with an semi-developed HDI rating of Source: Global Insight, 2016,[Version 993(2.5v)] Figure 4.1:Human Municipalities, Development 2005and 2015 Index for and District its Local ZFMgcawu 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 2015 2005 Mier LM Mier Human Development Index for ZF Mgcawu District and its Local Municipalities, Municipalities, Local its and District Mgcawu ZF for Index Development Human 0.64 0.50 Kai !Garib LM !Garib Kai 0.63 0.52 //Khara Hais //Khara 0.67 0.58 LM 2005 and 2015 2005 and !Kheis LM !Kheis 0.61 0.49 Tsantsabane 0.68 0.55 LM Kgatelopele 0.69 0.59 LM ZF Mgcawu ZF 0.66 0.55 DM households ZFMgcawu inthe and municipalities District its local is analysed for table 2015inthe below. In order to determine how income was distributed among households, annual the income distribution of 4.3.2.2 Annual Income Distribution lowestthe was with !Kheis aGini Coefficient of0.559. in2015.Tsantsabanedecreased again had highest the Gini-Coefficient the while at0.6in2015 municipality with at 0.587.Income inequality improved over years the as Gini-Coefficient under the review theall for municipalities unequal income distribution with aGini-Coefficient while of0.624, Kai !Garibleast the had unequal distribution In 2005,income for high municipalities the inequality all was Tsantsabane very district. inthe was leading in Source: Global Insight, 2016,[Version 993(2.5v)] 2005Local and2015 Municipalities, Figure District 4.2:Gini-Coefficient and its for ZFMgcawu Source: Global Insight, 2016, [Version 993(2.5v)] 2400000+ 1200000-2400000 600000-1200000 360000-600000 192000-360000 132000-192000 96000-132000 72000-96000 54000-72000 42000-54000 30000-42000 18000-30000 12000-18000 6000-12000 2400-6000 0-2400 Income Category Table 4.2: Annual Income Distribution for ZF Mgcawu District and itsLocal Municipalities, 2015 //Khara Hais LM Hais //Khara ZF Mgcawu DM Mgcawu ZF Tsantsabane LM Tsantsabane Kgatelopele LM Kgatelopele Kai !Garib LM !Garib Kai 2005 2015 !Kheis LM !Kheis Mier LM Mier Mier LM Mier Gini 0.616 0.574 0.520 - Coefficient forZFMgcawu District anditsLocal Municipalities,2005 and 2015 Z F Mgcawu DM Kai !Garib LM !Garib Kai 0.587 0.563 0.540 3 107 5 099 8 650 7 925 7 085 7 870 7 810 6 548 5 768 3 839 1 714 1 158 169 900 165 17 //Khara Hais LM Hais //Khara Mier LM 0.609 0.573 271 248 196 160 100 132 215 244 271 44 37 25 75 0.560 5 4 0 Kai !GaribKai 1 830 1 907 2 252 2 367 2 468 2 123 1 745 LM 166 588 975 968 362 214 !Kheis LM !Kheis 28 24 2 0.616 0.559 0.580 //Khara Hais //Khara Hais 3 695 3 179 1 298 2 159 3 077 2 914 2 878 2 378 2 101 1 464 Tsantsabane LM Tsantsabane LM 336 665 454 52 63 6 0.624 0.600 !Kheis LM !Kheis 0.600 136 256 451 532 612 628 588 460 370 234 103 44 74 9 7 0 Kgatelopele LM Kgatelopele 0.610 0.595 Tsantsabane Tsantsabane 0.620 1 019 1 607 1 339 1 214 1 088 1 032 LM 205 651 901 934 755 389 273 45 50 ZF Mgcawu DM Mgcawu ZF 7 Kgatelopele Kgatelopele 0.613 0.581 0.640 LM 123 360 558 852 725 659 602 596 489 457 152 105 319 29 17 2

Comparative Analysis for ZF Mgcawu District Municipality | 21 Comparative Analysis for ZF Mgcawu District Municipality | 22 and 2015. Figure 4.3below depicts formal the dwelling for backlog ZFMgcawu and municipalities District its local for 2005 4.4.2 Housing people with Grade 0-6at 10 062people. population as well district as highest inthe the level of economic activity. Kai !Garib had largest the number of categories except for Grade the 0-6category. as //Khara Thispartly expected was Haisthelargest had share the of respectively Mier number had smallest the while at 367.//Khara Hais had largest the number of the people inall In 2015, //Khara Hais and Kai !Garib had largest the and number 3 128 of people with no schooling at 3 590 by individuals ZFMgcawu inthe and municipalities District its local in2015. at children which may leave Table schoolinSouth Africa. 4.3below shows highest the level of education attained This indicator representsthe number peopleof eachat level educationof aged 15 or older. Agethe 15 legal ageis 4.4.1 Education 4.4 Access to Services R192 000 and annum. R360 000per Thelargest and R72 000. number of households in//Khara Hais, Tsantsabane and Kgatelopelebetween earned respectively earning above R2.4million. Thelargest number of households in Kaibetween R54 000 !Garibearned and only 5and 9 households andhad 271 and R96 000 628 households respectively R72 000 earning between R0 and R2 400, Kai while !Garib and Kgatelopele had 2 households income each in this category. Mier and !Kheis 169 households earning above district inthe R2.4million. Mier and had !Kheis zero households earning between Thelargest number of householdsbetween R192 000earned the district in and R360 000there while in2015 were Source: Global Insight, 2016, [Version 993(2.5v)] ZF Mgcawu DM Kgatelopele LM Tsantsabane LM LM !Kheis //Khara Hais LM LM !Garib Kai LM Mier Municipalities Table 4.3: Education Attained in ZF Mgcawu District and itsLocal Municipalities, 2015 No schoolingNo 12 084 1 259 2 659 1 083 3 590 3 128 367 Grade 0-6 27 725 10 062 2 523 9 163 1 718 3 282 977 Grade 7-11 76 382 29 992 23 311 11 075 4 615 2 326 5 062 Certificate / Certificate diploma diploma without without matric 430 184 100 14 86 14 32 Matric only Matric 37 378 17 319 3 374 1 455 7 640 6 891 700 certificate / certificate Matric & Matric diploma 1 376 6 808 2 802 1 243 210 307 870 Bachelors Matric & Matric degree 3 948 2 166 616 151 615 337 63 Matric & Matric Postgrad degree 1 443 251 724 223 153 63 28 municipalities for 2005and 2015. Table 4.4 below shows number the of households by of type dwelling in ZFMgcawu and District its local 4.5.1 Type of Dwelling of right the to dignity enshrined Constitution. inthe removalthat and roads. These areservices be mustbasic provided to communities they areas essential components that governmentThe core local services provides are water,clean drinking sanitation, electricity, shelter, waste 4.5 Access to Basic Services recorded respective intheir adecrease formal dwelling backlogs. population. ashad smallest Mierthe also is expected Kai !Garib and Mier where only the two municipalities that followed by Kai !Garib. Mier municipality formal had smallest the dwelling in2005and both backlog 2015,which largest formal dwelling followed backlog by Tsantsabane, in2015Tsantsabane while had second the largest backlog //Khara Hais had largest the formal dwelling 2005and inboth backlog 2015.In 2005,Kai !Garib had second the Source: Global Insight, 2016[Version 993(2.5v)] Municipalities, 2005and 2015 forFigure and District 4.3:Formal its Local ZFMgcawu Backlog Dwelling Source: Global Insight, 2016, [Version 993(2.5v)] ZF Mgcawu DM Kgatelopele LM Tsantsabane LM LM !Kheis //Khara Hais LM LM !Garib Kai LM Mier Municipalities Table 4.4: Number of Households by Type of Dwelling Unit for ZF Mgcawu District and itsLocal Municipalities, 2005and 2015 //Khara Hais LM Hais //Khara ZF Mgcawu DM Mgcawu ZF Tsantsabane LM Tsantsabane Kgatelopele LM Kgatelopele Kai !Garib LM !Garib Kai !Kheis LM !Kheis Mier LM Mier FormalDwelling Backlog for ZFMgcawu District anditsLocal Municipalities,2005 and 2015 0 Formal Very Very 21 848 2 468 3 132 9 098 5 713 492 947 2 000 Formal 27 640 10 524 1 381 1 260 3 344 2 689 8 441 Informal 4 000 2005 6 364 1 285 3 066 158 384 715 755 Traditional 2015 6 000 726 130 202 275 21 47 53 2005 Dwelling Dwelling Other Other Type 2 304 1 801 190 185 90 23 15 8 000 Formal Very Very 33 191 14 838 4 419 5 383 7 205 763 584 10 000 Formal 22 385 3 419 2 296 6 118 8 392 1 274 885 Informal 12 000 2015 10 284 2 245 1 344 5 033 1 035 595 31 Traditional 14 000 694 190 255 128 14 58 49 Dwelling Dwelling Other Other Type 2 269 1 131 131 272 602 43 91

Comparative Analysis for ZF Mgcawu District Municipality | 23 Comparative Analysis for ZF Mgcawu District Municipality | 24 municipalities for 2005and 2015. Table 4.6below depicts number the of households by level of access to water inZFMgcawu and District its local 4.5.3 Access to Water only municipality that had an increase number inthe of households with no access to toilets. system toilet municipalities inall except for //Khara Hais where there was aslight increase. Tsantsabane was the pit (VIP)toilets and pit toilets. There was asignificant decreasethe in number of households using the bucket toilets in2005and both municipalities 2015.All had an district inthe increase inaccess to ventilation improved in 2005to 54 234 in2015.//Khara Hais followed by Kai !Garib had largest the number of households using flush The district’slargest increase waswiththe households having access to flush increased fromthey as toilets, 47 111 municipalities for 2005and 2015. Table 4.5below provides number the of households by of type toilet ZFMgcawu inthe and District its local 4.5.2 Access to Sanitation atsmallest 14. Kai !Garib had largest the number of households living intraditional dwellings at Kgatelopele 255while had the !Garib had largest the number of households formal living dwellings invery 2005and inboth 2015.In 2015, formal and traditional dwellings for decreased municipalities all except for Tsantsabane. //Khara Hais and Kai except for and !Kheis, informal dwellings increased for municipalities all except for Mier. Households living in 2005and number 2015the Between of households formal living dwellings invery municipalities increased inall Source: Global Insight, 2016, [Version 993(2.5v)] ZF Mgcawu DM Kgatelopele LM Tsantsabane LM LM !Kheis //Khara Hais LM LM !Garib Kai LM Mier Municipalities Table 4.6: Number of Householdsto Water by of Access for Level ZF Mgcawu District and itsLocal Municipalities, 2005and 2015 Source: Global Insight, 2016, [Version 993(2.5v)] ZF Mgcawu DM Kgatelopele LM Tsantsabane LM LM !Kheis //Khara Hais LM LM !Garib Kai LM Mier Municipalities Table 4.5: Number of Households by Type of Toilet for ZF Mgcawu District and itsLocal Municipalities, 2005and 2015 Piped water water Piped Flush Toilet dwelling 28 345 11 226 inside inside 2 749 4 068 1 342 8 240 47 111 17 578 15 066 4 006 6 191 2 969 1 302 721 Piped water water Piped in yard 26 109 Improved Pit Pit Improved 8 696 1 214 1 467 3 238 2 616 8 878 Ventilation Ventilation dwelling RDP- (At 2 028 (VIP) Communal piped piped Communal water: less than water: less 143 339 523 800 199 24 200m from 2005 2005 level) 1 211 Pit Toilet 382 166 157 439 35 32 1 176 236 709 more than 200m 85 97 43 5 from dwelling (Below RDP) piped water: water: piped Communal Communal System Bucket Bucket 783 354 182 127 3 427 1 619 18 22 81 169 616 131 657 234 piped water piped No formalNo No Toilet No 2 434 1 383 335 111 243 309 5 140 1 036 1 834 53 119 863 969 320 Piped water water Piped Flush Toilet dwelling 35 647 15 666 inside inside 4 912 5 621 8 109 678 660 22 507 13 834 54 243 5 794 8 483 2 663 962 Piped water water Piped in yard 21 041 8 531 1 220 2 497 3 712 4 117 Improved Pit Pit Improved 964 Ventilation Ventilation Communal piped piped Communal water: less than water: less (VIP) 3 261 192 509 938 902 687 dwelling (At 33 RDP-level) 200m from 2015 2015 Pit Toilet 1 145 2 914 306 473 963 18 3 305 1 165 1 381 9 243 389 Communal piped piped Communal 39 88 dwelling (Below dwelling (Below than 200m from water: more more water: System Bucket Bucket 2 568 1 740 RDP) 1 103 266 316 167 160 680 74 80 92 86 6 4 No Toilet No No formalNo 5 446 2 324 1 586 aer wate 1 210 piped piped 8 118 1 021 4 743 105 850 369 211 117 880 146 local municipalitieslocal for 2005and 2015. Table 4.8below shows number the of households by access to refuse removal ZFMgcawu inthe and District its 4.5.5 Access to Refuse Removal respectively. municipalities All recorded number inthe adecrease of households not using electricity. forelectricity lighting in2015 and and increasing 9 782 in2005to other 24 143 and purpose from 5 363 16 267 //Khara Hais period. this followed by Tsantsabane had largest the increase number in the of households using municipalitiesincrease in all number inthe of households using for electricity lighting and over other purposes only 2005and between 2015,with Kai !Garib followed by //Khara Hais having largest the decrease. There was an asignificant the in decreased experienced The district number of households using electricity for lighting purposes municipalities for 2005and 2015. Table 4.7below shows number the of households by usage ZFMgcawu electricity inthe and District its local 4.5.4 Access to Electricity households with no formal piped water in2015. piped water more than 200mfrom dwelling (below RDP). municipalities All had an increase number inthe of RDP level. In there district the was an increase number in the of households accessing water from communal recorded adecline inhouseholds accessing water from communal piped water: less than 200mfrom dwelling at water yard inthe except for Mier and Tsantsabane. Kgatelopele and Mier were only the two municipalities that dwellingthe for 2005and both municipalities 2015.All recorded adecline inhouseholds with access to piped //Khara Hais followed by Kai !Garib had largest the number of households with access to piped water inside Source: Global Insight, 2016, [Version 993(2.5v)] ZF Mgcawu DM Kgatelopele LM Tsantsabane LM LM !Kheis //Khara Hais LM LM !Garib Kai LM Mier Municipalities Table 4.8: Number Removal for of Households to Refuse ZF by Access Mgcawu District and itsLocal Municipalities, 2005and 2015 Source: Global Insight, 2016, [Version 993(2.5v)] ZF Mgcawu DM Kgatelopele LM Tsantsabane LM LM !Kheis //Khara Hais LM LM !Garib Kai LM Mier Municipalities Table 4.7: Number of Households by Electricity for Usage ZF Mgcawu District and its Local Municipalities, 2005and 2015 Weekly byWeekly Removed Removed Authority 43 272 18 624 10 970 3 936 5 881 2 906 955 Lighting Only for Electricity Removed Less Often Than Than Often Weekly byWeekly Authority 5 684 1 422 1 952 1 792 384 937 473 515 153 161 450 922 82 24 Removed byRemoved Lighting and other other and Lighting Community Community Members 2005 Electricity for Electricity 2 121 1 342 2005 137 174 372 17 79 Purposes Removal (own 42 194 16 267 13 666 3 470 5 363 2 568 861 Personal dump) 9 576 1 102 1 416 4 935 1 228 163 732 No Refuse Removal Electricity Not UsingNot 2 121 171 335 328 897 335 11 004 54 1 597 1 464 3 302 3 449 469 723 Weekly byWeekly Removed Removed Authority 50 368 23 805 11 142 1 179 2 799 5 656 5 786 Lighting Only for Electricity Removed Less Often Than Than Often 2 472 Weekly byWeekly Authority 117 527 186 548 852 243 1 768 263 525 781 58 45 96 Lighting and other other and Lighting Removed byRemoved 2015 Electricity for Electricity Community Community Members 2015 Purposes 2 207 1 372 120 622 59 434 24 143 15 416 20 66 7 5 607 9 782 3 038 1 449 Removal (own Personal 11 082 dump) 1 714 4 440 3 322 368 266 974 Electricity Not UsingNot No Refuse Removal 6 917 1 199 1 280 2 028 1 751 3 397 1 033 321 337 198 556 607 932 72

Comparative Analysis for ZF Mgcawu District Municipality | 25 Comparative Analysis for ZF Mgcawu District Municipality | 26 an increase number inthe of households refuse was removed whose by community members. lighting and over Tsantsabane other purposes period. this was only the municipality to experience district in the piped water in2015.There was an increaseall in municipalitiesthe in number of households usingfor electricity where there was aslight increase. municipalities All had an increase number inthe of households with no formal was asignificantthe in decrease number of households usingthe bucket system toilet except for //Khara Hais householdswhile living informal, traditional and other 2005and dwelling between 2015.There decreased types In number the district. in the district, the of households formal living and invery informal dwellings increased and acertificate or diploma and matric bachelor’sand a improved degree. services The basic of delivery overall people werethese in //Khara Hais and Kai !Garib. //Khara Hais had largest the also number of people with matric in 2015.With regards people with no schooling in2015.The majority to education, had 12 084 district the of Thelargest number of households thewere district in earning withinthe R192 000 to R360 000 incomecategory and district, in the measures have will put to be inplace inorder to gap the lessen richand the between poor. resulted improving district in the from 0.55 in 2005 to 0.66 in 2015. There is an unequal distribution of income cent34.0 per of population the lived still inpoverty in2015.The HDIs all of municipalities increased,which Even though progress remained poverty still made poverty district, inalleviating inthe achallenge has been as 4.6 Conclusion municipalities 2005and between 2015. households respectively in2015.The number 3 322 of householdswith no refuse removalthe all increased in !Garib followed by Tsantsabane had largest the number of households removing and own their refuse at 4 440 an increaseexperience number inthe of households refuse was removed whose by community members. Kai where refuse was removed weekly by authorities. Tsantsabane was only the municipality to district inthe basis by authorities in 2005 and both 2015. and!Kheis Tsantsabane had a decline number in the of households //Khara Hais followed by Kai !Garib had largest the number of households that had refuse removed on aweekly , Tel: 053, Tel: 839 2900 SwifPrint

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