COFISA: Foresight
    for Provincial Innovation


         Western Cape
    A Baseline Data Snapshot
Lord Charles Hotel, S...
Data sources
• COFISA baseline data study
  – In progress for E Cape, W Cape and Gauteng (IsambuloAMI)
  – Meta-data for ~...
Topics

•   Population, Poverty and Basic Services
•   Education
•   Western Cape PGDS
•   Industry
•   Research and Devel...
Population, Poverty
and Basic Services
Western Cape
                                      population growth
                           6


                      ...
Population by age group




                               Western Cape




South Africa
Age distribution W Cape
Black African
                              Coloured




White                      Indian/Asian
Net loss or gain of people in each province
                through inter-provincial migration over the five
             ...
Urban and non-urban
distribution by province
%age urban:
W Cape and SA
Age Dependency
%age of households
with mains electricity
%age of households with
  access to piped water
%age of households
using bucket or no toilets
%age of households
with municipal refuse removal
Education
Percentage school
attendance of 7-15 year olds
University growth points:
                                    Publications

•   University of Cape Town                   ...
Western Cape
Provincial Growth and
  Development Plan
Provincial innovation
       systems in South Africa
“But what emerges from the work so far
suggests that regional or loca...
Western Cape
                  PGDS (and PAMTS)
• Emphasises
  –   All development is a function of knowledge
  –   Region...
Industry
Industrial
                                   specialisations
                             (Provincial share >20% of natio...
Farming operations
            (2001)
Gross agricultural
          income
Research &
Development (R&D)
Knowledge intensity
                         and innovation
• Industrial activity            • Patents: IOM
   – Agricultu...
Technology
                 Achievement Index (TAI)

The provincial TAIs ranking as follows:
• Top:
     Gauteng, Western ...
Summary
These data seem to indicate that:
• Other provinces’ most productive (& innovative?)
  people migrating to Western...
Thank
   You
bday@scientia.co.za
Formal sector employment
        growth 1999-2004
Age Dependency
Net in-migration
   to the WC
%age of households
with access to piped water
%age of households
with access to piped water
Educational attainment
      20+ years (2001)
•   Three provinces – Eastern Cape, Free State, and Northern Province – are not
    specialised in any economic activity w...
•   Provincial development authorities in the Eastern Cape pay a lot of attention to
    attracting new industrial investm...
Percentage of households
using electricity for lighting
Percentage of households
using electricity for cooking
Western  Cape  Baseline  Snapshot  November 2007
Western  Cape  Baseline  Snapshot  November 2007
Western  Cape  Baseline  Snapshot  November 2007
Western  Cape  Baseline  Snapshot  November 2007
Western  Cape  Baseline  Snapshot  November 2007
Western  Cape  Baseline  Snapshot  November 2007
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Western Cape Baseline Snapshot November 2007

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Cofisa - Western Cape Baseline Snapshot for Innovation - November 2007

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Western Cape Baseline Snapshot November 2007

  1. 1. COFISA: Foresight for Provincial Innovation Western Cape A Baseline Data Snapshot Lord Charles Hotel, Somerset West, 13th November 2007 Peter Greenwood & Bob Day Non-Zero-Sum Development
  2. 2. Data sources • COFISA baseline data study – In progress for E Cape, W Cape and Gauteng (IsambuloAMI) – Meta-data for ~800 datasets, at different degrees of disaggregation – CeSTII innovation data disaggregated to provincial level by December • Western Cape baseline data – Only ~180 datasets currently (freely) available with data that is disaggregated down to the province or finer – Our sources for Western Cape: • Human Sciences Research Council • Statistics South Africa • Western Cape Provincial Government
  3. 3. Topics • Population, Poverty and Basic Services • Education • Western Cape PGDS • Industry • Research and Development
  4. 4. Population, Poverty and Basic Services
  5. 5. Western Cape population growth 6 5 WC Population (millions) 4 3 2 1 0 1996 2001 2007 Year
  6. 6. Population by age group Western Cape South Africa
  7. 7. Age distribution W Cape Black African Coloured White Indian/Asian
  8. 8. Net loss or gain of people in each province through inter-provincial migration over the five years preceding October 2001 500000 400000 300000 Population 200000 100000 0 -100000 -200000 -300000 EC LP FS KZN MP NC NW WC GP -400000 Province Source: Statistics South Africa, Census 2001
  9. 9. Urban and non-urban distribution by province
  10. 10. %age urban: W Cape and SA
  11. 11. Age Dependency
  12. 12. %age of households with mains electricity
  13. 13. %age of households with access to piped water
  14. 14. %age of households using bucket or no toilets
  15. 15. %age of households with municipal refuse removal
  16. 16. Education
  17. 17. Percentage school attendance of 7-15 year olds
  18. 18. University growth points: Publications • University of Cape Town • University of Stellenbosch – Earth Sciences – Chemical Sciences – Mechanical and Industrial Engineering – Biological Sciences – Civil Engineering – Physical Sciences – Architecture and Urban Environment – Agricultural, Veterinary and Environmental – Human Movement and Sport Science Sciences – Public Health and Health Services – Industrial Biotechnology and Food – Immunology Sciences – Economics and Business – Medicine – Medical Physiology – Medical Biochemistry and Clinical Chemistry – Pharmacology and Pharmaceutical • University of the Western Cape Sciences – Chemical Sciences – Immunology – Biological Sciences – Economics and Business – Mechanical and Industrial Engineering – Biomedical Engineering (incl. Biomedical Technology) – Information, Computing and Communication Sciences
  19. 19. Western Cape Provincial Growth and Development Plan
  20. 20. Provincial innovation systems in South Africa “But what emerges from the work so far suggests that regional or local innovation systems exist, if at all, only in Gauteng and Western Cape, and possibly in KZN, but nowhere else.” REGIONAL AND LOCAL INNOVATION SYSTEMS A study on behalf of NACI March 2007 (unpublished) So: an innovation system probably exists in the Western Cape, but only just!
  21. 21. Western Cape PGDS (and PAMTS) • Emphasises – All development is a function of knowledge – Regional innovation system; – University - industry linkages – Sectoral programmes; horizontal strategies • But – More work required to establish how and where provincial competences in knowledge-intensive activities can combine in support of innovation
  22. 22. Industry
  23. 23. Industrial specialisations (Provincial share >20% of national total) • Gauteng • Western Cape – Manufacturing – Agriculture, forestry and • Metals, metal products, fishing machinery, equipment – Food, beverages and • Other non-metal mineral tobacco products – Textiles, clothing and • Electrical machinery and leather goods apparatus – Finance and business • Radio, TV, instruments, services watches, clocks • Furniture and other manufacturing – Construction • Eastern Cape – Wholesale and retail trade, – Transport equipment catering and accommodation – Finance and business services
  24. 24. Farming operations (2001)
  25. 25. Gross agricultural income
  26. 26. Research & Development (R&D)
  27. 27. Knowledge intensity and innovation • Industrial activity • Patents: IOM – Agriculture, forestry and – Agriculture, hunting, and fishing related service activities • Patents: SOU – Growing of vegetables, horticultural specialties and • R&D investments nursery products – Growing of crops; market – Growing of fruit, nuts, gardening; horticulture beverage and spice crops – Forestry, logging and related service activities
  28. 28. Technology Achievement Index (TAI) The provincial TAIs ranking as follows: • Top: Gauteng, Western Cape, and KwaZulu-Natal • Average: Mpumalanga, Free State, and North West • Bottom: Eastern Cape, Northern Cape, and Limpopo (DST 2005, 28)
  29. 29. Summary These data seem to indicate that: • Other provinces’ most productive (& innovative?) people migrating to Western Cape (& Gauteng) • Origin of poverty rural – urban poverty inherited • W Cape has lowest levels of poverty in RSA • Many growth areas in HEIs, but how relevant to needs of RSA (poverty and exports)? • More work needed to turn (many?) provincial knowledge-intensive competencies into innovation • 90% urban population, few farming units, yet most productive agricultural sector in RSA (high exports) • R&D focus on agriculture, forestry and fishing. Is more diversity needed?
  30. 30. Thank You bday@scientia.co.za
  31. 31. Formal sector employment growth 1999-2004
  32. 32. Age Dependency
  33. 33. Net in-migration to the WC
  34. 34. %age of households with access to piped water
  35. 35. %age of households with access to piped water
  36. 36. Educational attainment 20+ years (2001)
  37. 37. • Three provinces – Eastern Cape, Free State, and Northern Province – are not specialised in any economic activity where the provincial share in the national total reaches 20 per cent. Even if the threshold had been set at ten per cent, they would hardly show up, with the exception of community, social and personal services in the Eastern Cape and mining in the Northern Cape. Another three provinces – Mpumalanga, Limpopo, and North West – are specialised in one and the same activity, namely mining. The Western Cape is specialised in agriculture, forestry, and fishing, and in finance and business services. KwaZulu Natal has three specialisations and Gauteng four. These two provinces are the only ones with specialisations in manufacturing (see Figure 1). • When secondary activities are disaggregated, Eastern Cape and Western Cape contribute with specialisations in transport equipment, reflecting the automobile industry around East London and Port Elizabeth, and food and beverages as well as textiles in the Cape. Mainstays of KZN manufacturing with national importance are food, beverages, and tobacco; textiles, clothing, and leather goods; wood and paper; publishing and printing; and furniture. Gauteng is the only province with high-tech manufacturing; next to non-metal mineral products, metals and metal products, and furniture, it is specialised in electrical machinery and instruments.
  38. 38. • Provincial development authorities in the Eastern Cape pay a lot of attention to attracting new industrial investments, especially FDI, but there is a lot less focus – or maybe none – on retaining accumulated absorptive capacities in the form of multinational firms who for whatever reason extricate movable capital equipment and strategic assets such as group-internal core competences but who leave skills and also a fair amount of tacit production and process knowledge behind. In the context of the automotive industry – indisputably the primary technological and organisational core of economic upgrading in the region – this suggests at best a lucky midterm horizon with a high risk of running foul of events beyond the control of provincial or even national policymakers, namely the fickleness of the key players in global automotive assembly. In other words, local development strategies with enough foresight would accompany the justified courting of DCSA with at least some brainstorming in conjunction with industry and other stakeholders about a possible post-DC world. At numerous component supplier plants, this is certainly of interest to management and employees. It is not clear that public stakeholders in the Eastern Cape appreciate this, let alone guide attendant soul-searching. This implies that what may endanger the future of the regional economy is not so much local capabilities per se, but a failure to coordinate the setting of priorities, identification of linkages, and selection of public interventions within a larger vision for local development in the face of global change. In other words, it is the very absence of a regional innovation system that makes for trouble.
  39. 39. Percentage of households using electricity for lighting
  40. 40. Percentage of households using electricity for cooking
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