Socio Economic - Transnet

Transnet - Swazi Rail Link – MsukaligwaLocal Municipality - Davel Stock YardSocio-economic impact analysisDraft

GlossaryCorridors: A corridor is a linear strip of land or area, connecting large activity nodes, traversing urbanor inter-urban areas, surrounding a major transport facility or facilities providing an appropriateregional level of mobility and accessibility to adjacent areas, and containing a high concentration ofpopulation and mixed land uses” and “… accommodate major linear transport routes like heavy andlight rail and/or freeways, large shopping concentrations etc., social, cultural and sporting facilities aswell as a large amount of residential accommodation”.Density: The number of units per unit of land area, e.g. dwelling units/ hectare. There are fivemeasures of density:i. population density: people / hectare.ii. gross dwelling unit density: dwelling units / total land area of a project or suburb including roads,public open space and non-residential land uses.iii. net dwelling unit density: dwelling units / land occupied by residential plots only.iv. building density: area of buildings / hectare.v. settlement density: (dwelling units / total land occupied by settlement) also known as average grossdwelling units density.Densification: Densification is the increased use of space both horizontally and vertically withinexisting areas/ properties and new developments, accompanied by an increased number of unitsand/or population threshold.Efficiency: Development that maximises development goals such as sustainability, integration,accessibility, affordability, and quality of living, relative to financial, environmental, and social costs,including on-going and future costs.Infill Development: Development of vacant or under-utilised land within existing settlements in orderto optimise the use of infrastructure, increase urban densities and promote integration.Integrated Development Plan: The strategic municipal development plan, reviewed on an annualbasis, required by the MSA (Act 32 of 2000) which guides municipal decisions and budgets.Land Use Management: Establishing or implementing any measure to regulate the use or a changein the form or function of land, and includes land development.Land Use Management System: A system used to regulate land use in a municipality, including atown planning or zoning scheme, or policies related to how land is used on a plot by plot basis.Nodes: Nodes are focused areas where a higher intensity of land uses and activities are supportedand promoted. Typically any given municipal area would accommodate a hierarchy of nodes thatindicates the relative intensity of development anticipated for the various nodes, their varying sizes,and their dominant nature.Spatial planning: planning of the way in which different activities, land uses and buildings are locatedin relation to each other, in terms of distance between them, proximity to each other and the way inwhich spatial considerations influence and are influenced by economic, social, political, infrastructuraland environmental considerations.Spatial Development Framework: A Spatial development Framework (SDF) is a core component ofa Municipality’s economic, sectoral, spatial, social, institutional, environmental vision. In other words itis a tool for moving towards a desired spatial form for the Municipality.Sector Plans: Municipal plans for different functions such as bio-diversity conservation, housing,transport, local economic development and disaster management. They may also be geographicallybased, for example a sub-region, settlement within a local Municipality or a component of thatsettlement.Stakeholders: Agencies, organisations, groups or individuals who have a direct or indirect interest ina development intervention or its evaluation.Town Planning Scheme or Zoning Scheme: A legal instrument for regulating the use of land interms of provincial or national legislation, see Land Use Management System.5 July 2013 Page 2

Urban Edge: The urban edge is defined as an indicative boundary within the municipality with the solepurpose of containing physical development and sprawl and re-directing growth towards a moreintegrated, compact and efficient urban form.AcronymsAUCMIPCRCDEAAnimal unitComprehensive Municipal Infrastructure PlanCapital Replacement CostDepartment of Environmental AffairsDFA Development Facilitation Act (Act 67 of 1995)DoHGVAIDPLEDLMLUMSDepartment of HealthGross value addedIntegrated Development PlanLocal Economic DevelopmentLocal MunicipalityLand Use Management SystemMSA Municipal Systems Act (Act 32 of 2000)MTREFMedium Term Revenue and Expenditure FrameworkNEMA National Environmental Management Act (Act 107 of 1998)NSDPPGDSSANParksSDFSEASWOTVIPNational Spatial Development PerspectiveProvincial Growth and Development StrategySouth African National ParksSpatial Development FrameworkStrategic Environmental AssessmentStrengths, Weaknesses, Opportunities, ThreatsVentilated Improved Pit LatrineWSA Water Services Act (Act 108 of 1997)5 July 2013 Page 3

Contents1 Introduction ....................................................................................................................................... 62 Regional Setting ............................................................................................................................... 62.1 Location ................................................................................................................................... 73 Socio Economic Profile .................................................................................................................... 73.1 Data and data sources ............................................................................................................ 73.2 Demographic consideration ..................................................................................................... 73.2.1 Size ...................................................................................................................................... 83.2.2 Population age distribution .................................................................................................. 83.2.3 Population growth rate ......................................................................................................... 93.2.4 Future expected growth ..................................................................................................... 103.2.5 Spatial aspects of the population ....................................................................................... 113.3 Labour and Economic Analysis ............................................................................................. 143.3.1 Description of the Msukaligwa Local Municipality Labour force ........................................ 143.3.2 Employment productivity ................................................................................................... 173.3.3 Economic structure and performance................................................................................ 204 Land Use ........................................................................................................................................ 254.1 Msukaligwa Local Municipality .............................................................................................. 254.1.1 Settlement Patterns ........................................................................................................... 254.1.2 Agriculture .......................................................................................................................... 264.1.3 Mining ................................................................................................................................ 264.1.4 Tourism .............................................................................................................................. 264.1.5 Forestry .............................................................................................................................. 265 Risks and Benefits .......................................................................................................................... 276 Works Cited .................................................................................................................................... 285 July 2013 Page 4

Socio-Economic Impact Assessment1 IntroductionThe aim of this document is to provide a socio-demographic profile that captures the relevantcharacteristics of Davel and surrounding areas that will be affected by the Transnet-Swazi Rail Link.This baseline socio-economic profile of the study area will be developed through a desktop review ofavailable documentation and will address the following aspects:• The regional setting of the study area;• A socio-economic profile of the population residing in the study area;• Existing land uses and infrastructure in the vicinity of the project-related infrastructure andalong the proposed railway line routes; and• Possible risks and benefits regarding the proposed undertaking when considering the abovementioned aspects.2 Regional SettingThe study area of this project, as indicated in Map 1, relates to the areas directly affected by thealignment of the Transnet - Swazi Rail link as well as all associated infrastructure. The rail linktraverses the provinces of Mpumalanga and KwaZulu Natal, starting at the Davel Shunting Yard inMpumalanga. This will form the main focus of this study. The areas affected in the neighbouringcountry of Swaziland will be excluded from this study.Map 1: Swazi Rail Link Alignment5 July 2013 Page 6

2.1 LocationThe Davel Yard and its associated infrastructure and connections are proposed to be situated withinthe existing Davel Yard in Mpumalanga (indicated in Map 2), approximately 20km east Bethal andapproximately 33km west of the Ermelo, Mpumalanga.Due to its strategic location, a shunting yard situated at Davel will form a unique intersection betweenthe existing Coal Line (Webbsrus - Hamelfontein), the Eastern Mainline (Machadodorp - Breyten) aswell as the Central Basin (Trichardt). This shunting yard will facilitate the consolidation of loads intooptimised lengths for suitable for the new Swaziland Rail Link, and also possibly the de-consolidationof returning loads in the future.Map 2: Swazi Rail Link Alignment – Davel Shunting Yard3 Socio Economic Profile3.1 Data and data sourcesIn terms of the approach to the analysis the data was described at the local municipal level and in theconclusions trends and tendency as extrapolated to draw conclusions on the focus areas of theproject. Secondly, local economies and demographic areas are open and it is practically impossible toisolate a local or part of a local economy. The approach therefore was, where appropriate, to do theanalysis on a comparative basis by comparing the municipality with the profile of the DistrictMunicipality, the economy or demographics of Mpumalanga and also with the broader context of thenational economy.3.2 Demographic considerationThe population of a municipal area forms part of the ultimate objective of the development process, aswell as being a subject in the process, since the people provide labour and entrepreneurship forproduction and also consume the output of production. Demography does not form part of economicanalysis but needs to be taken into account as the population forms the basis of all economic activityin the area.5 July 2013 Page 7

3.2.1 SizeThe size of the population and in particular the number of households are some of the most importantdeterminants of the needs of the inhabitants. These needs are expressed in the demand forinfrastructural and social services and the potential on the extent of involvement in economicactivities. It also forms the basis from which all other calculations are made.Table 1: Population sizePopulation Group No. of people %Black African 8106 95.57%Coloured 67 0.79%Indian or Asian 11 0.13%White 287 3.38%Other 11 0.13%Total 8482 100%1% 3%96%Black AfricanColouredIndian or AsianWhiteOtherTable 1 shows the population composition of Davel, situated in the Msukaligwa local municipality.Black African is the majority population group, comprising over 88% of the municipality’s totalpopulation as estimated in 2011. The second largest group is the white population which accounts for3% while the coloured population makes up less than 1% of the total population and the Asian andother population 1% of the total population of the municipality. The household representation of thepopulation is indicated in Table 2, and shows a similar distribution as the overall population profile.Table 2: Households according to population groupPopulation Group No. of Households %Black African 2056 94.75%1% 4% Black AfricanColoured 11 0.51%Indian or Asian 7 0.32%White 89 4.10%Other 7 0.32%Total 2170 100%95%ColouredIndian or AsianWhiteOther3.2.2 Population age distributionPopulation 201180 - 8470 - 7460 - 6450 - 5440 - 4430 - 3420 - 2410 - 140 - 4-600 -400 -200 0 200 400 600Male FemaleFigure 1: Population PyramidA population pyramid graphicallydisplays a population’s age andgender composition by showingnumbers or proportions of males andfemales in each age group; thepyramid provides a clear picture of apopulation’s characteristics. Thesum total of all the age-gendergroups in the pyramid equals 100per cent of the population.The population pyramid of Davel(Figure 1) shows larger numbers inthe younger age groups, thisindicates rapid growth.5 July 2013 Page 8

Migrant labour is not a factor in the municipality as there are about equal amounts of males andfemales in the municipal area. However, there are anomalies in some cohorts between 30 years and34 years. There is no apparent reason that explains this.Table 3: Population PercentageAge Groups Male % Male Female % Female0 - 4 518 12.33% 434 10.20%5 - 9 508 12.10% 450 10.58%10 - 14 450 10.71% 494 11.61%15 -19 447 10.64% 470 11.05%20 - 24 452 10.76% 399 9.38%25 - 29 372 8.86% 356 8.37%30 - 34 246 5.86% 290 6.82%35 - 39 255 6.07% 261 6.14%40 - 44 223 5.31% 208 4.89%45 - 49 167 3.98% 166 3.90%50 - 54 158 3.76% 174 4.09%55 - 59 136 3.24% 170 4.00%60 - 64 108 2.57% 136 3.20%65 - 69 62 1.48% 73 1.72%70 - 74 53 1.26% 80 1.88%75 - 79 30 0.71% 56 1.32%80 - 84 15 0.36% 37 0.87%Total 4,200 100.00% 4,254 100.00%M/F % 49.68% 50.32%3.2.3 Population growth rateThe population growth rate and future projections are of great importance for planning purposes. Anegative or below-average growth rate is indicative of an out-migration of people – normally due to alack of economic growth and the concomitant loss of job opportunities in the municipal area. Thereverse is true for an above-average growth rate.Figure 2 indicates the growth in population for the Msukaligwa LM between 1996 and 2011. From thisfigure it can be seen that the municipality is experiencing a positive growth.Population growth - Msukaligwa LM1600001400001200001000008000060000400002000001996 2001 2011Figure 2: Msukaligwa population growth (1996 – 2011)5 July 2013 Page 9

Based on the population size over the past years, the population growth rate of the Msukaligwa LMwas calculated to be 1.8% per annum. This is slightly lower than the Mkhondo LM but higher than theAlbert Luthuli LM has seen a decline in population size.This pattern revealed is mostly the same for both the province and the district. It should be noted thatthe growth in the five year period between 1996 and 2001 was the almost the same as for the periodbetween 2001 and 2011, indicating a slightly slower growth over the past few years. From 2001 to2008 the municipality’s growth rate has declined rapidly from about 4% to -2%. This decline is acharacteristic of modern rural municipalities in South Africa. This can show to large majorities ofpeople migrating to other areas in search of employment opportunities. However, since 2009 thegrowth rate has improved and in 2011 was calculated at about 1.8%.3.2.4 Future expected growthPopulation and household growth is one element that determines the long-term demand for goodsand services. Based on historical population figures from 2000 to 2011, a trend analysis was done forthe municipality. The trend analysis is based on historical data. This data was used to determine themunicipal growth rate and extrapolate the figures to give a projected growth for the municipality up to2025.Table 4: Municipal demographic projections2001 2011 2015 2020 2025Population 124,829 149,378 160,351 175,206 191,439Households 29,689 40,931 46,865 55,506 65,740HH size 4.2 3.6 3.4 3.2 2.9Average Pop Growth Rate (last 12 years) 1.8%Average HH Growth Rate (last 12 years) -0.09%Figure 3 indicates the forecasted population growth graphically, compared to the expected growth oftwo neighbouring LMs.250 000200 000150 000100 00050 000Forecasted Population Growth0201120122013201420152016201720182019202020212022202320242025MP301: Albert Luthuli MP302: Msukaligwa MP303: MkhondoFigure 3: Forecasted population growthIn terms of the projected population growth the following should be noted:• The growth rate was calculated at 1.8%.• This is similar to other rural municipalities in the country.5 July 2013 Page 10

• The general trend indicates that the municipality’s population will increase at a steady but slowpace.• The priorities, policies and decisions of the local and district municipality can alter the situation.This cannot necessarily be predicted.Household growth was projected in the same way as for population. The following should be noted:• The Household growth rate was calculated to be -0.09%• Household growth shows a steady decline over the next few yearsHousehold size is an important indicator for the demand for services since the number of people in ahousehold determines consumption demand for water, electricity, and waste disposal.The estimates in shown in Table 4 were derived from the population and households estimates in theprevious sections. Household sizes are averaged but is regarded as slightly little below average for arural environment. This is based on the assumption that there are no structural changes in population.However the higher levels of possible migrant workers can imply that more males are absorbed,which is not necessarily attached to an existing household. This implies more single-personhouseholds, which may lower the average household size.3.2.5 Spatial aspects of the populationThis section investigates how the population of the municipality is distributed and in what type ofareas people lives. This helps to visualise the data presented previously in this section. The tablebelow shows the population per Enumerator Area type in the municipality on ward level. The variouswards locality are indicated by the map below. The data shows that the municipality’s population islargely formal in nature with little informal and no traditional residential population. Davel is situated inWard 10, and consist primarily of formal residential buildings and farms.Table 5: Population per EA typeFormalresidentialInformalresidentialTraditionalresidentialFarmsParks andrecreationCollective livingquartersIndustrialSmall holdingsVacantCommercialWard 1 6100 0 0 0 0 0 0 0 0 0Ward 2 7906 986 0 0 0 0 0 0 0 0Ward 3 7034 1313 0 0 0 887 85 0 0 30Ward 4 4297 0 0 0 0 739 0 0 4 0Ward 5 2807 623 0 0 0 0 0 0 0 0Ward 6 3142 2162 0 0 0 0 0 0 0 0Ward 7 5275 0 0 0 0 32 125 0 0 180Ward 8 9175 1460 0 2710 0 155 6 0 92 0Ward 9 6386 881 0 2442 0 0 81 0 0 0Ward 10 4974 0 0 3508 0 0 0 0 0 0Ward 11 3397 0 0 3886 0 0 0 0 5 0Ward 12 302 1305 0 1408 0 0 260 0 0 0Ward 13 8295 299 0 359 0 0 0 0 0 0Ward 14 5578 174 0 619 0 0 0 0 0 0Ward 15 2965 1267 0 5870 0 0 0 0 0 0Ward 16 10299 4351 0 1013 0 0 25 0 32 0Ward 17 7154 0 0 0 0 0 0 0 0 0Ward 18 197 0 0 6052 207 0 0 0 0 05 July 2013 Page 11

Ward 19 4284 2564 0 1602 0 0 0 0 11 0Total 99567 17385 0 29469 207 1813 582 0 144 210Map 3 below illustrates the various locations of the different wards with in the MsukaligwaMunicipality.Map 3: Msukaligwa Municipality - WardsMap 4 below presents the population data spatially. One can immediately see specific populationconcentrations. Ermelo shows the densest populated area in the municipality. The rest of thepopulation is spread throughout the municipal area show some densification close to naturalresources. It is interesting to note that the densification area is close to main access routes,emphasising the importance of accessibility in development. Due to the disparity of the population itcan be assumed that the alignment of the Mpumalanga section of the rail link will not have a directeffect on the location of the population.5 July 2013 Page 12

Map 4: Population distribution5 July 2013 Page 13

3.3 Labour and Economic AnalysisIn the analysis of the labour and employment situation in a municipal area, it is necessary to focusattention on the size and spatial distribution of the labour force. Secondly, the characteristics of thelabour market should be analysed. To this end, it is necessary to examine the supply of labour, whichis derived from figures on the economically active population in a municipal area. The demand forlabour, on the other hand, is an indication of employment opportunities, which are determined by theeconomic structure of an area along with the level and growth in economic activities. Unemployment,and in a sense transfrontier commuting, provides an indication of the difference between supply anddemand and implies that equilibrium in the labour market necessitates both expansion of economicactivity and the curtailment of population growth.Figure 4: Composition of the labour forceA third issue that should be addressed is involvement in the peripheral sector, as not all potentialworkers are active in the labour market. Finally, the quality of the labour force needs to be analysedas it provides information on the employability of the workers.The term labour force refers to those people who are available for employment in a certain area.Figure 4 illustrates the different components of the labour force and the relationship between them.3.3.1 Description of the Msukaligwa Local Municipality Labour forceTable 6: Msukaligwa Local Municipality Labour forceDescriptionNumberPopulation 126 687Economically active 64 560Formal and informal (Total) 36 971Formal 26 104Formal - Highly skilled 4 402Formal - Skilled 10 739Formal - Semi- and unskilled 10 963Informal 10 867Unemployed 3 033Unemployment rate (Percentage) 20.80 %Labour force participation rate (Percentage) 57.27 %Table 6 describes the labour force of the Msukaligwa LM. According to the 2011 data acquired fromthe Quantec database, Msukaligwa Local Municipality has 64,560 economically active persons.26,104 people in the municipality are employed in the formal sector while 10,867 people are active inthe informal sector of the economy and 3 033 are shown to be unemployed. The municipality has anunemployment rate of 20.80% and a labour force participation rate of 57.27%.5 July 2013 Page 14

The size of the informal sector includes subsistence agriculture (not necessarily applicable in themunicipal area), is difficult to establish with a reasonable degree of accuracy and can easily be underestimated.One reason for this is that people involved in informal activity often classify themselves asunemployed.Obtaining the participation rates, involves calculating the labour force or the economically activepopulation relative to the potential labour force, (i.e. the population in the age group 15 to 64 years).These rates reflect the percentages of the said population that are actually economically active.Formally employed refers to people who are selling their labour or who are self-employed in theformal sector of the economy, for pay or profit. Informally employed includes all people who areactive, for pay or profit, in the informal or unregistered sector of the economy. Unemployed arepersons actively looking for a job, but who are not in any type of paid employment.The following figures describe each of the most important elements over time. This is done toestablish patterns in the Labour force and to assess any changes that might have taken place.3.3.1.1 Economic active population390003800037000360003500034000330003200031000Figure 5: Change in economic active population (No. ofpeople)Includes the formally employed, theunemployed, and those persons active inthe informal/ unregistered sector. The terms‘supply of labour’ and the ‘labour force’ areused as synonyms for the economicallyactive population.The number of people in the economicallyactive population has shown an overalldecline over the study period as indicated inFigure 5. There has been quite a drasticdecrease in this figure between 2000 and2003, and again between 2007 and 2010.This however correlates to the economicdown turn experienced in 2008.3.3.1.2 Formal employment35000300002500020000150001000050000The formal employment sector follows asimilar trend to that of the economicallyactive population graph above, although thedifferences were less extreme. Since 2000there has been a decline in the number ofpeople that are formally employed in themunicipality. The graph does show that thisfigure has become more stable since 2009.Figure 6: Change in formal employment (No. of people)3.3.1.3 Informal employment5 July 2013 Page 15

120001000080006000400020000The informal employment graph, depictedin Figure 7, shows an increase in peopleemployed informally from 2001 to 2011.Figure 7: Change of informal employment (No. of People)3.3.1.4 Unemployment1000080006000400020000200020012002200320042005200620072008200920102011Figure 8: Change in unemployment (No. of people)The change in the unemployed section of thelabour force shows a steep fall from 2000 to2003/2004 and then an increase from thatperiod to 2008, followed by a decrease with theonset of the recession. The decline inemployment corresponds with the increase inemployment in both the formal and informalsectors but the impact of the economic decline isalso evident in the trend towards the end of theperiod. It can be expected that it will start toincrease as the current economic conditionsprevail.3.3.1.5 Unemployment Rate252015105The rate of changes in unemployment indicatesthe number of people unemployed as apercentage of the total economically activepopulation (labour force).The unemployment rate follows much the samepattern as the change in the unemployed. The2009 figure would suggest a rise in theunemployment rate. This can again beexplained by the economic recession.0Figure 9: Change in unemployment rate (%)3.3.1.6 Labour force participation rate5 July 2013 Page 16

6050403020100Figure 10: Change in labour force participation rate (%)Labour force participation rate indicates thelabour force (economically active population) as apercentage of the population in the age group15– 64 yearsAn increase in the participation rate can be theresult of more women entering the labour marketor the outflow of the potential economically activepeople from a municipal area due to harsheconomic conditions, which would ‘artificially’increase the participation rate. A low participationrate in a municipal area can be ascribed to thelarge number of male migrant workers moving outof the municipal area or the proliferation ofperipheral activities in the municipal area. Thelatter does not seem to be the case in theMsukaligwa Municipality.3.3.2 Employment productivityEmployment is always a priority for the Council and it is obvious that development and growthstrategies will have to support job creation.3.3.2.1 Employment per sectorThe table below shows the employment per sector. The structure of employment and the extent of thelink between employment and the level of economic activity are important.Table 7: Employment per sectorAgriculture, forestryand fishingMining andquarryingManufacturingElectricity, gas andwaterConstructionWholesale and retailtrade, catering andaccommodationTransport, storageand communicationFinance, insurance,real estate andbusiness servicesCommunity, socialand personalservicesGeneral governmentTotal1995 14225 2929 2669 244 2478 6074 1543 2131 3504 3318 391141996 14155 2833 2850 224 2301 6183 1558 2213 3483 3425 392251997 14048 2687 2872 207 2149 6300 1516 2290 3633 3512 392151998 13816 2463 2832 205 1890 6571 1396 2316 3810 3535 388331999 13286 2249 2790 200 1563 6999 1316 2301 4008 3508 382212000 12543 2076 2741 188 1397 7143 1234 2309 4215 3461 373062001 10568 1970 2685 199 1349 7355 1224 2397 4134 3468 353502002 9491 1753 2689 185 1367 7894 1225 2512 4237 3542 348952003 8651 1614 2612 189 1225 7851 1355 2582 4319 3694 340922004 8107 1547 2665 211 1316 8351 1491 2641 4466 3858 346542005 7909 1511 2681 262 1572 9255 1667 2553 4651 4073 361342006 7711 1380 2621 320 1842 10025 1761 2700 4823 4289 374712007 6887 1434 2492 429 1906 10887 1863 2810 5141 4517 383652008 5482 1490 2237 543 1823 11537 2051 2858 5433 4794 382472009 4338 1524 1897 641 1731 11900 2033 2665 5602 5051 373842010 4162 1654 1722 644 1644 11707 2058 2536 5414 5203 367432011 3950 1689 1610 654 1701 11931 2133 2518 5293 5494 36971Avg.Change-7.5% -3.7% -3.0% 7.2% -2.9% 4.4% 2.2% 1.1% 2.7% 3.2% 3.8%5 July 2013 Page 17

The most noticeable is the differential growth rates in employment creation between the sectors.Agriculture has shown an average decrease of about 7.5% of the jobs between 2011 and 1995. Theimplication is important since these workers are jobless and have to leave farms. They usually end upin informal settlements on the urban fringes. This amounts to about 7886 people being affected or itimplies a need for about 2 500 new households to be provided with services. The primary andsecondary sectors are both shedding jobs while the tertiary sector is growing strongly andemphasising the role of the Msukaligwa Municipality.3.3.2.2 Changes in employmentTable 8 below presents the employment distribution per sector over the past 17 years. These figuresare expressed in terms of the distribution of employment across the sectors. One noticeable aspect isthat the largest economic sectors are not necessarily the biggest contributors to employment creation.Table 8: Employment distribution per sectorAgriculture, forestry andfishingMining and quarryingManufacturingElectricity, gas and waterConstructionWholesale and retail trade,catering andaccommodationTG: Transport, storage andcommunication [SIC: 7]TH: Finance, insurance, realestate and business services[SIC: 8]TI: Community, social andpersonal services [SIC: 92,95-6, 99, 0]TJ: General government[SIC: 91, 94]Total1995 36% 7% 7% 1% 6% 16% 4% 5% 9% 8% 100%1996 36% 7% 7% 1% 6% 16% 4% 6% 9% 9% 100%1997 36% 7% 7% 1% 5% 16% 4% 6% 9% 9% 100%1998 36% 6% 7% 1% 5% 17% 4% 6% 10% 9% 100%1999 35% 6% 7% 1% 4% 18% 3% 6% 10% 9% 100%2000 34% 6% 7% 1% 4% 19% 3% 6% 11% 9% 100%2001 30% 6% 8% 1% 4% 21% 3% 7% 12% 10% 100%2002 27% 5% 8% 1% 4% 23% 4% 7% 12% 10% 100%2003 25% 5% 8% 1% 4% 23% 4% 8% 13% 11% 100%2004 23% 4% 8% 1% 4% 24% 4% 8% 13% 11% 100%2005 22% 4% 7% 1% 4% 26% 5% 7% 13% 11% 100%2006 21% 4% 7% 1% 5% 27% 5% 7% 13% 11% 100%2007 18% 4% 6% 1% 5% 28% 5% 7% 13% 12% 100%2008 14% 4% 6% 1% 5% 30% 5% 7% 14% 13% 100%2009 12% 4% 5% 2% 5% 32% 5% 7% 15% 14% 100%2010 11% 5% 5% 2% 4% 32% 6% 7% 15% 14% 100%2011 11% 5% 4% 2% 5% 32% 6% 7% 14% 15% 100%From Table 8 it is confirmed that employment is not a static issue and changes in employment arevery important. Figure 11 below gives a comparison between the employment situation in 1995 and in2011.5 July 2013 Page 18

40%35%30%25%20%15%10%5%0%Changes in employment sector between 1995 and 201119952011Figure 11: Comparative employment situation in 1995 and 2011 (Employment per sector)From Figure 11 an overall decline in primary and secondary employment is evident, with the onlyexception of a slight increase in the utilities industry. Also, despite the large decrease in agriculturalemployment, the agriculture sector remains one of the larger employers in the LM. The tertiary sectorhas however shown an overall increase, especially in the wholesale industry.3.3.2.3 Labour outputTable 9 and Figure 12 below shows the Gross Value Added (GVA) output per labour unit between1995 and 2011.8 0007 0006 0005 0004 0003 0002 0001 000019951996199719981999200020012002200320042005200620072008200920102011Primary sectorMining and quarryingManufacturingConstructionWholesale and retail trade, catering and accommodationFinance, insurance, real estate and business servicesGeneral governmentAgriculture, forestry and fishingSecondary sectorElectricity, gas and waterTertiary sectorTransport, storage and communicationTI: Community, social and personal servicesFigure 12: GVA output per labour unit 1995 to 2011 (Rand)It is not possible to draw any specific conclusion regarding labour productivity. The interplay betweenlabour and capital is not assessed. All labour units, with the exception of the mining industry showedan increase in GVA output since 1995. The tertiary sector shows a significant contributing of 60%. Ifone assumes that these labour units show significant opportunities for substituting labour with capital,then one might conclude that there was an overall increase in labour productivity over the assessmentperiod.5 July 2013 Page 19

Table 9: GVA output per labour unit (R’million)Primary sectorAgriculture, forestry and fishingMining and quarryingSecondary sectorManufacturingElectricity, gas and waterConstruction1995 969 157 812 373 237 97 40 1,531 319 345 388 166 314 2,8731996 982 211 771 390 252 100 38 1,601 325 363 420 169 324 2,9721997 975 195 780 408 272 97 39 1,614 323 379 423 168 322 2,9981998 946 203 743 388 268 81 38 1,626 321 391 416 177 321 2,9601999 969 222 748 370 265 69 36 1,670 341 403 419 183 324 3,0092000 952 226 726 382 285 71 26 1,675 359 415 381 190 329 3,0092001 885 192 693 395 299 66 30 1,708 371 426 387 195 329 2,9882002 861 230 630 447 340 75 32 1,743 387 451 374 201 330 3,0512003 831 223 609 448 323 91 35 1,835 396 501 374 213 351 3,1142004 788 223 564 496 342 116 38 1,944 434 536 395 219 359 3,2272005 716 208 508 552 363 145 45 2,063 478 577 409 226 372 3,3312006 647 186 461 614 379 184 51 2,222 533 622 439 242 387 3,4842007 617 186 431 685 401 223 61 2,355 582 675 439 256 402 3,6582008 607 215 392 735 415 250 70 2,465 614 731 441 266 413 3,8072009 563 212 351 784 424 282 78 2,483 640 740 419 259 425 3,8302010 574 213 361 787 445 265 77 2,499 643 749 417 257 433 3,8602011 560 212 348 802 467 258 77 2,583 669 785 419 263 446 3,945Tertiary sectorWholesale and retail trade,catering and accommodationTransport, storage andcommunicationFinance, insurance, real estateand business servicesTI: Community, social andpersonal servicesGeneral governmentTotalAverage 791 207 584 533 340 145 48 1,977 455 535 409 215 364 3,301Average %contribution 24% 6% 18% 16% 10% 4% 1% 60% 14% 16% 12% 7% 11% 100%% growthpa -2.48% 2.05% -3.36% 6.78% 5.73% 9.85% 5.56% 4.04% 6.46% 7.50% 0.47% 3.46% 2.48% 2.19%3.3.2.4 Migrant labourTo calculate both the size of the migrant labour force and the spatial distribution of their areas oforigin, male absenteeism ratios are utilised. In the process, it is firstly assumed that only males in the15 to 64 year age group will migrate, meaning work on a contract basis in another area and returnhome at least once a year on average. This assumption is patently invalid as substantial numbers offemales also migrate, but it is the only plausible way of establishing a minimum level of male migrantworkers. Indications are that migrant labour does not play a role in the Msukaligwa local municipalitysince the male to female ratio is almost a 50/50 split.3.3.3 Economic structure and performance3.3.3.1 Gross value addedEconomic performance of a municipal area’s economic system in terms of, factors such as productionactivity can be measured by the Gross Value Added (GVA). The analysis will focus on the GVAproduced by the primary, secondary and tertiary economic sectors over time; the GVA produced by5 July 2013 Page 20

each economic sector in the municipality and compare the GVA of the Municipality to the GertSibande DM, the Mpumalanga province and the country as a whole.The primary sector of the economy involves changing natural resources into primary products. Mostproducts from this sector are considered raw materials for other industries. Major businesses in thissector normally include agriculture, agribusiness, fishing, forestry and all mining and quarryingindustries.The secondary sector generally takes the output of the primary sector and manufactures finishedgoods or where they are suitable for use by other businesses, for export, or sale to domesticconsumers. This sector is often divided into light industry and heavy industry. The sector is made upof manufacturing, electricity, gas and water, and construction.The tertiary or services sector consists of the "soft" parts of the economy, i.e. activities where peopleoffer their knowledge and time to improve productivity, performance, potential, and sustainability. Thebasic characteristic of this sector is the production of services instead of end products. Businesses inthis sector include wholesale and retail trade, catering and accommodation, transport, storage,communication, finance, insurance, real estate, business services, community, social and personalservices, and general government.Sectoral GVA contributions - Msakaligwa LM3 0002 5002 0001 5001 00050001995199619971998GVA Contribution (R'million)1999200020012002200320042005200620072008200920102011Figure 13: GVS per economic sector (R'million)Primary sector Secondary sector Tertiary sectorFigure 13 indicates the largest and strongest growing sector in Msukaligwa’s economy is the tertiarysector. This means its economy is dominated by the service sector. The secondary sector has shownsome increase in recent years. The primary sector is getting smaller and does not contribute a lot tothe economy in terms of GVA.Going further and analysing the sub sectors in the economy (see Figure 14), it is clear thatMsukaligwa is experiencing strong growth in all industries with the exception of the mining industry. Italso becomes apparent why Msukaligwa’s tertiary economic sector is so strong. The economy isdriven by manufacturing activities with the finance, insurance, real estate and business servicesshowing strong growth. General government is also a sector that is improving and contributing to theeconomy more at a steady increasing pace.5 July 2013 Page 21

9008007006005004003002001000GVA output per industry - Msakaligwa LM1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011Agriculture, forestry and fishingMining and quarryingManufacturingElectricity, gas and waterConstructionWholesale and retail trade, catering and accommodationTransport, storage and communicationFinance, insurance, real estate and business servicesTI: Community, social and personal servicesGeneral governmentFigure 14: Economic sub sectors (R’million)3.3.3.2 Diversification and concentration in the economyThe level of diversification or concentration of a municipal area’s economy is measured by a tressindex. A tress index of zero represents a totally diversified economy. On the other hand, the higherthe index (closer to 100), the more concentrated or vulnerable the municipal area’s economy toexogenous variables, such as adverse climatic conditions, commodity price fluctuations, etc.50Tress Index - Msukaligwa LM40302010019951996199719981999200020012002200320042005200620072008200920102011Figure 15: Tress index (10 industries)The comparative tress index displayed in Figure 15 shows that Msukaligwa LMs economy isdiversifying. Not only is the municipality’s economy less vulnerable/diversified than it was in 1995, butit is also showing higher diversification than the Mpumalanga province and South Africa.3.3.3.3 Location coefficientSouth Africa Mpumalanga Msukaligwa Local MunicipalityBasic/Non-Basic ratios are calculated in order to determine the drivers of an economy. The ratio isexpressed as the employment in a sector in the local economy divided by the total employment in the5 July 2013 Page 22

local economy. This is in turn divided by the same ratio for the district, provincial or national economy.A ratio greater than one, implies that there is relatively more employment in this sector than in thecorresponding economy it is compared to. It therefore generates more than what can locally beconsumed and the sector is thus a net exporting sector. This implies that it generates income for thelocal economy. The opposite is then true for ratios smaller than one.Table 10: Location coefficient: South AfricaMsukaligwa LocalMunicipalityAgriculture, forestry andfishingMining and quarryingManufacturingElectricity, gas and waterConstructionWholesale and retailtrade, catering andaccommodationTransport, storage andcommunicationFinance, insurance, realestate and businessservicesCommunity, social andpersonal services2.19 1.50 0.69 3.19 0.57 1.22 1.95 0.45 1.09 0.74General governmentWhen compared at a national level Utility services shows the best performance, followed by transport,agriculture, and mining. It is interesting to note the strong mining position the LM still has on nationallevel despite the decrease in mining production in the LM over the past years.Table 11: Location coefficient: MpumalangaMsukaligwa LocalMunicipalityAgriculture, forestry andfishingMining and quarryingManufacturingElectricity, gas and waterConstructionWholesale and retailtrade, catering andaccommodationTransport, storage andcommunicationFinance, insurance, realestate and businessservicesCommunity, social andpersonal services1.57 0.48 0.57 1.44 0.80 1.50 2.06 0.80 1.16 1.09General governmentIn the provincial context transport services and agriculture are highlighted as the most importanteconomic activities, followed by trade and utilities. This shows the importance of the municipality inthe province and the role it plays as a service centre starts to emerge.Table 12: Location coefficient: DistrictMsukaligwa LocalMunicipalityAgriculture, forestry andfishingMining and quarryingManufacturingElectricity, gas and waterConstructionWholesale and retailtrade, catering andaccommodationTransport, storage andcommunicationFinance, insurance, realestate and businessservicesCommunity, social andpersonal services1.05 0.43 0.53 1.45 0.85 1.09 2.46 0.99 1.79 1.59General government5 July 2013 Page 23

When economic sectors are analysed in terms of how well it functions at district level, some importantaspects emerges. In Msukaligwa the tertiary services are the strongest sector and this emphasisesthe role the municipality plays as an important service centre for the people in the municipality andthose surrounding Msukaligwa.5 July 2013 Page 24

4 Land UseThis section will provide a general discussion of settlement patterns and major land uses in theMsukaligwa Local Municipality.Map 5: Land Cover4.1 Msukaligwa Local Municipality4.1.1 Settlement PatternsThe Local Municipality has a large agricultural sector with strong service centre Ermelo. Thesettlement pattern in this area has developed in orientation to the resource base and economicpotential of the area. The agricultural sector, petrochemical industries and mining activities in the areahave led to the distribution of service centres varying in size and function throughout the area.Informal settlements are also found scattered in this local municipality.The Mpumalanga Land Use Management Plan (Gert Sibande Development Planners, 2005est.)identified the following important settlements in the Gert Sibande district:Settlement Type Town/City Development DirectiveMajor Urban Centre • Bethal;• Carolina;• Embalenhle;• Ermelo;• Evander;• Piet Retief;• Secunda;Aim of centres is to retain the currentengineering, social, economic andinstitutional infrastructure and tostrengthen and diversify the economyin order to achieve growth, prosperityand sustainability. The followingindustrial clustering opportunities5 July 2013 Page 25

Settlement Type Town/City Development DirectiveRural settlement hubs• Standerton;• Volksrust.A total of 39 rural settlement hubswere identified.should be explored: agriculture,chemical, forestry, and mining.Hubs should fulfill a rural supportfunction. Each hub must accommodatethe primary range of social andeconomic services. The hubs mustprovide accessibility to the hinterland,not only in the form of roads but alsopublic transport facilities.It is important to note that the major urban centre within Msukaligwa LM, is Ermelo and is in closeproximity to the new rail line in question.4.1.2 AgricultureThe Gert Sibande area has a strong agricultural sector that produces maize, sunflower, grain,sorghum, beef, dairy, wool, sheep and wheat. Other types of crops produced in the area incorporatepotatoes, oil, seeds, maize and soybeans.The area between Carolina, Bethal and Ermelo is one of the largest wool-producing areas in thecountry. The Standerton area is known for its large dairy industry and maize agriculture. The area ofOgies shows high soil potential for irrigation farming.The district has an estimate of 1,750 commercial farmers, 2,300 emerging, and 5,300 subsistencefarmers (MDALA, 2007b).4.1.3 MiningThe Gert Sibande area has rich coal and mineral deposits and has some of the largest coal mines inSouth Africa. The major areas for coal in Gert Sibande District are concentrated around Bethal,Secunda, Standerton and Carolina. Linked with these coal mines are some of the world’s largest coalfired power stations, such as Majuba and Tutuka, both situated in the Gert Sibande District. The areais however confronted by the tension between the agricultural activities in the sense that valuableagricultural land is being sterilised by mining activities (CSIR, 2007). Despite the strong miningpresence that remains in the Msukaligwa LM it is noted that the mining activities have declineddrastically since 1995.4.1.4 TourismThere is potential to expand small-scale eco-tourism activities in the vicinity of Chrissiesmeer,because of the unique grassland habitats and the bird life associated with the grassland and wetlandareas. The establishment of stop-over facilities linked to the development of the bird watch tourismcluster adds value to the tourism potential of the Gert Sibande District (CSIR, 2007).4.1.5 ForestryThe forestry activities in the Gert Sibande area relate to pine, eucalyptus and wattle plantations, whichare concentrated in the eastern parts of the region stretching from Carolina, Lothair, and Amsterdamdown to Piet Retief in the south. Mondi has a manufacturing facility in Gert Sibande, namely the PietRetief mill.There exists tension between agriculture and forestry activities over the use of land (CSIR, 2007).5 July 2013 Page 26

5 Identified Risks and BenefitsDue to its strategic location, the shunting yard will be situated at Davel which forms a uniqueintersection between the existing Coal Line (Webbsrus - Hamelfontein), the Eastern Mainline(Machadodorp - Breyten) as well as the Central Basin (Trichardt). This shunting yard will facilitate theconsolidation of loads into optimised lengths for suitable for the new Swaziland Rail Link, and alsopossibly the de-consolidation of returning loads in the future. The location of the rail line can be notedas a transportation spine, crossing the centre section of the Msukaligwa Local Municipality. The spinedoes not directly affect any known environmental concerns.Taken into account the various land uses that may be affected by the Transnet - Swazi Rail link, therisk on a sector does exist but the possibility of it having a great impact on the MsukaligwaMunicipality as an entire body is very slim.Risks may be that of the current unemployment percentage within the LM, and how the Transnet -Swazi Rail link may bring relief to this high percentage. The new line will generate more trips on thelines and result in change in local movement patterns, movement being the movement of pedestrianscrossing the line. This is a risk that must be taken into consideration as the most frequent usedtransport mode for both work trips and education trips originating in Mpumalanga Province is walking(31.5% and 80.3% of work and education trips respectively). Other prominent modes were privatecars, buses, and minibus-taxis. Trains contributed only 0.1% of all working trips originating in theprovince (Department of Transport, 2008).The Msukaligwa Local Municipality will benefit from the Transnet - Swazi rail link greatly. The risksand benefits weight the reward of the Transnet - Swazi Rail link will be superior.5 July 2013 Page 27

6 Works CitedCSIR, 2007. Integrated Spatial Framework Update, 2005, Part I & II (First Edition). MpumalangaProvincial Department, Office of the Premier. Nelspruit, South Africa.Sisonke Development Planners, 2005est. Mpumalanga Land Use Management Plan. MpumalangaProvincial Government, Department of Agriculture and Land Administration. Nelspruit, South Africa.MDLALA( Mpumalanga Provincial Government, Department of Agriculture and Land Administration),2007b. 2007/08 – 2009/10 Strategic Plan. Nelspruit, South Africa.Department of Transport. (2008). National Transport Master Plan 2050 .Mpumalanga Department of Agriculture and Land Administration. (2005). Integrated ResourceInformation Report.5 July 2013 Page 28