2. Innovation System and Inequality: The Experience of South Africa Presentation 29 January 2010 Luci Abrahams, Wits LINK Centre & Thomas Pogue, IERI, TUT

3. Licensed under a Creative Commons Attribution NonCommercial NoDerivs 2.0 SA LicenceCreative Commons Attribution NonCommercial NoDerivs 2.0 SA Licence ONE: TRENDS AND PATTERNS OF INEQUALITY Inequality has defined South Africas political economy historically and continues to be an intractable reality, with race, class, gender and geographic dimensions. This paper traces trends in interpersonal and inter-regional inequality since the establishment of a democratic state in 1994. Reviews key aspects of the co-evolution of the innovation system, side by side with current and historical inequality in the SET workforce and inequality in the benefits of innovation output. Poverty and inequality can be examined from at least five perspectives, namely income, assets, services, infrastructure and knowledge: income, housing assets, health and education services and in knowledge infrastructure.

4. Licensed under a Creative Commons Attribution NonCommercial NoDerivs 2.0 SA LicenceCreative Commons Attribution NonCommercial NoDerivs 2.0 SA Licence SA Gini Coefficient by District Source: Craig Schwabe, HSRC, Census 2001 (2001) GINI Co-efficient measures level of inequality. Darkest districts are poorest

5. Licensed under a Creative Commons Attribution NonCommercial NoDerivs 2.0 SA LicenceCreative Commons Attribution NonCommercial NoDerivs 2.0 SA Licence Percentages of Households with Telephones Percentages of Households with Telephones (by district, 2003) Source: HSRC, 2006

6. Licensed under a Creative Commons Attribution NonCommercial NoDerivs 2.0 SA LicenceCreative Commons Attribution NonCommercial NoDerivs 2.0 SA Licence % of Households with Mobile Telephony % of Households with Mobile Telephony (by district, 2003) Source: Statistics South Africa Source: HSRC, 2006

7. Licensed under a Creative Commons Attribution NonCommercial NoDerivs 2.0 SA LicenceCreative Commons Attribution NonCommercial NoDerivs 2.0 SA Licence NR&D survey Table 1.4: Provincial split of R&D 2005/06* Business enterpriseGovernmentHigher educationNot-for-profitScience councilsTotal ProvinceR 000% % % % % % E Cape 242,6922.984,07110214,7017.96,5892.9123,9565.9672,0084.7 Free State 476,3465.841,8565146,8235.43,6871.650,1972.4718,9085.1 Gauteng 4,643,86456.3291,63934.51,030,80137.7104,00245.91,103,28452.57,173,59050.7 KZN 843,49910.272,1318.5379,68113.935,03615.5201,8119.61,532,15810.8 Limpopo 84,187115,9171.943,5641.65,3292.448,0582.3197,0541.4 Mpumalanga 187,9342.336,0014.358,5492.110,2384.548,0512.3340,7732.4 North-West180,2272.220,8572.573,4572.73,5471.645,7512.2323,8382.3 N Cape 14,6910.242,539515,2630.61,6500.764,2843.1138,4261 W Cape 1,570,33619239,63028.4769,37828.256,43624.9416,70219.83,052,48321.6 Total8,243,776100844,6401002,732,215100226,5141002,102,09410014,149,239100

8. Licensed under a Creative Commons Attribution NonCommercial NoDerivs 2.0 SA LicenceCreative Commons Attribution NonCommercial NoDerivs 2.0 SA Licence DistrictPopulation (2001)% of Provincial Total Sasolburg114 4503.85 Botshabelo202 6616.83 Welkom264 7818.92 Witsieshoek348 78111.75 Bloemfontein377 96812.73 Odendaalsrus104 2623.51 Table 1: Magisterial Districts with the Largest Population (2001) Source: Provincial Profile of the Free State, Development Bank of Southern Africa, May 2003

9. Historical Patterns of Inequality 49.3 million people living in more than 12 million households, South Africas economic production concentrated in six urban centres South Africa 129/182 countries; HDI of 0.683 (2007), lower country position for life expectancy at birth and stronger positioning on adult literacy, combined gross enrolment ratio and GDP per capita (UNDP, 2009). HIV/AIDS influencing population trends, est.5,2 million people living with the virus. Approximately 70% of South Africas population or 35 million people live outside the six metropolitan areas; predominant economic activity is community services. Western Cape, Eastern Cape and KwaZulu-Natal very large rural town and village populations: 6 million each KZN and Eastern Cape, living from agriculture, subsistence farming, informal tourism, social grants (StatsSA, 2009). Licensed under a Creative Commons Attribution NonCommercial NoDerivs 2.0 SA LicenceCreative Commons Attribution NonCommercial NoDerivs 2.0 SA Licence

10. Interpersonal Inequalities: income and consumption GDP ZAR2283.8bn; GDP per capita ZAR46800 Income inequality is extremely high at a ratio of 43:1 Income inequality has risen in the period post democracy, signalling the rise of a relatively large black middle class and a continued rise in unemployment arising from job losses in mining and agriculture; and by a shift in the sectoral earnings shares from manufacturing and trade to government, the FIRE and construction sectors, at lower average wage rates. Bhorat, van der Westhuizen & Jacobs (2009, p.57): increasing levels of wage inequality partly attributable to skill premium paid to highly skilled workers. Of total employment 13.3 million (June 2009), SA has a very small informal sector of around 2,1 million (excluding agriculture and domestic employment) or less than 16% of the total employed, significantly lower than either Brazil or India Licensed under a Creative Commons Attribution NonCommercial NoDerivs 2.0 SA LicenceCreative Commons Attribution NonCommercial NoDerivs 2.0 SA Licence

11. Innovation-focused S&T and R&D activities and outputs Services sector dominant, then manufacturing, mining in decline.. strengths and weaknesses of the provincial economy are apparent. The economic profile of Xhariep district is largely agricultural with further tourism potential to be exploited around the Gariep Dam and the Diamond and Wine Route. The Lejweleputswa district relies on gold mining with a contribution to GGP from agriculture and trade and a small contribution from manufacturing. Northern Free State has a largely manufacturing base, with the petrochemical hub at Sasolburg, a significant services sector and a contribution from agriculture. Motheo district relies largely on the services and government sectors, while the Thabo Mafutsantyana district has a high dependence on agriculture with a contribution from tourism that could be further exploited. Licensed under a Creative Commons Attribution NonCommercial NoDerivs 2.0 SA LicenceCreative Commons Attribution NonCommercial NoDerivs 2.0 SA Licence

12. Consumption patterns Most important asset class for SA majority is housing. In 2008, 73.5% of households lived in a formal dwelling, 10.5% in a traditional dwelling and 1,8 million h/h or 13.4% in informal settlements. (Government RSA, 2009, p.30). Significant demand for rental housing by individuals earning below R7500 per month (FFC, 2009 p. 59). Middle class chooses private schooling and healthcare, at a premium price, with innovation. Public sector provides economic and social infrastructure, as well as community and personal services, with extremely limited innovation. Demand for innovation in services visible across income levels. Public sector – most visible demand in health services (HIV/AIDS, tuberculosis, other), policing and crime reduction, public transport, energy and electronic communications with government. Private sector, demand most visible in banking, access to finance and mobile communications. Licensed under a Creative Commons Attribution NonCommercial NoDerivs 2.0 SA LicenceCreative Commons Attribution NonCommercial NoDerivs 2.0 SA Licence

13. Interregional Inequalities SA economy dominated by Gauteng, consistent share of 1/3 of GDP 2002 – 2007 as compared to share of 1/5 of population Decline in output inequality attributed in part to relatively constant share of output relative to increase or decrease in population size eg Gauteng constant output share (34%) with increase in population share, Eastern Cape constant share of output (8%) but population share declined 1995 – 2007 Absolute exclusion of small towns from meaningful output, and innovation Gauteng & Western Cape consistently greater contributors to economic output relative to their population size. Five provinces: North-West, Free State, Limpopo, KZN, and Eastern Cape consistently generating less output relative to their population shares: explanation partly relatively higher concentration of urban populations for the former and rural populations for the latter provinces Licensed under a Creative Commons Attribution NonCommercial NoDerivs 2.0 SA LicenceCreative Commons Attribution NonCommercial NoDerivs 2.0 SA Licence

14. Class, Race, Gender and Inequality Inter-racial inequality historical and remains a factor for a large proportion of the population. However, decadal rates of change indicate that intra-racial inequality is also an increasingly important characteristic of income inequality – post-1994 intra-racial inequality increased for all populations – African, Indian, Coloured and White. Increases in class and gender inequality within these historically racial groups, as new opportunities in high-income jobs and business ventures began to determine the shape of inequality in South African society on a class and gender basis. Licensed under a Creative Commons Attribution NonCommercial NoDerivs 2.0 SA LicenceCreative Commons Attribution NonCommercial NoDerivs 2.0 SA Licence

15. Summative Remarks Public policy seeks to increase per capita income and to reduce unemployment. Requires innovation in redistributive mechanisms, capacity of society to move towards sustainable livelihoods through distributive means over the next two to three decades, productive capacities need to be geared towards making the benefits of science and technology more broadly available to society. A greater proportion of the benefits of investment in innovation must go to the 40% of the population with the lowest income. South African society requires political, business and community leadership to build sustained efforts to shift structural inequality as the only means of increasing income for the lowest quintile of the population and pushing the African mean income levels strongly towards the total mean income level. Licensed under a Creative Commons Attribution NonCommercial NoDerivs 2.0 SA LicenceCreative Commons Attribution NonCommercial NoDerivs 2.0 SA Licence

16. Summative Remarks Given the current shape and size of the South African economy and its relative positioning in the global economy, strategies to address structural inequality will require major shifts in economic policy, charting a direction away from reliance on low wage-labour resource mining towards medium-high technology production. Changing the history of centuries of dispossession and inequality will also require strategies to increase sustainable subsistence agriculture and to reposition South Africas rural provinces with respect to participation in the local and global knowledge economy. For each province, some potential for structural change exists. Though the change trajectory may occur over more than two decades, agendas can be set now eg Gauteng global city- region 2055 and KZN knowledge economy focus and ICT and electronics cluster. Comparative advantages of Limpopo, Free State and Eastern Cape in terms of their future positioning in the productive system must be assessed, theorised and strategised. The role of R&D and innovation in this strategic positioning must come under scrutiny. Licensed under a Creative Commons Attribution NonCommercial NoDerivs 2.0 SA LicenceCreative Commons Attribution NonCommercial NoDerivs 2.0 SA Licence

17. Summative Remarks Comparative advantages of Limpopo, Free State and Eastern Cape in terms of their future positioning in the productive system must be assessed, theorised and strategised. The role of R&D and innovation in this strategic positioning must come under scrutiny. Licensed under a Creative Commons Attribution NonCommercial NoDerivs 2.0 SA LicenceCreative Commons Attribution NonCommercial NoDerivs 2.0 SA Licence

18. TWO: CO-EVOLUTION OF INNOVATION SYSTEM AND INEQUALITY TWO: CO-EVOLUTION OF INNOVATION SYSTEM AND INEQUALITY Various elements of innovation in the production system and inequality mutually reinforce each other - private sector domination of R&D and unequal access to the global production network. Market driven trade and investment under globalization are briefly examined. Public sector orientation towards supporting SET innovation biased towards the production system for increased global competitiveness, limited but increasing ? support for research to support social objectives. Licensed under a Creative Commons Attribution NonCommercial NoDerivs 2.0 SA LicenceCreative Commons Attribution NonCommercial NoDerivs 2.0 SA Licence

19. TWO: CO-EVOLUTION OF INNOVATION SYSTEM AND INEQUALITY TWO: CO-EVOLUTION OF INNOVATION SYSTEM AND INEQUALITY Dialectical relationship between relative strength and focus of the innovation system, and the state of inequality in South Africa: Low levels of R&D investment and the selective focus on innovation in manufactured goods over nearly three decades has contributed little to SME development, as the majority of SMEs operate in the broad services sector – economic development amongst historically disenfranchised communities has moved at a slow pace, despite the presence of democratic government. Policy emphasis (15 years), and also investment focus BEE model based largely in asset structuring and deal financing, rather than in promoting innovation in black-owned business, in small firms, in the informal sector or in social ventures. Inhibitors in education and health sectors poor progress towards fostering successive generations of researchers, knowledge workers and entrepreneurs. Licensed under a Creative Commons Attribution NonCommercial NoDerivs 2.0 SA LicenceCreative Commons Attribution NonCommercial NoDerivs 2.0 SA Licence

20. National System of Innovation and Production Dynamics National System of Innovation and Production Dynamics Large services sector 65% of sectoral value-added 1999 - 2006. FIRE and business services 30% of service sector value- added. Between 1999 and 2006 the sectoral value-added in services grew at a compound annual growth rate of 5.8%. During this period, agriculture accounted for three percent of value-added, the mining and quarrying sector was a further eight percent and manufacturing contributed 19%. Secondary industries which consist of manufacturing, utilities, and the construction sector accounted for 24% of national value-added during this period. Secondary industries grew at an annualized rate of 5.2%, less than that of services and the 5.5% annualized growth in the primary sectors of agriculture and mining. Does local manufacturing need a stronger innovation push? Does agriculture? And services – is 5.8% good enough – for who? Licensed under a Creative Commons Attribution NonCommercial NoDerivs 2.0 SA LicenceCreative Commons Attribution NonCommercial NoDerivs 2.0 SA Licence

21. Formalised R&D and innovation Formalised R&D and innovation CSIR, ARC, HSRC, AI - while a number of these agencies have initiatives in social innovation, there is no single agency focused on exploring R&D and innovation for social development; for services; for the second economy Six research-intensive universities have built a strong knowledge base in a wide range of disciplines and in multi- disciplinary areas feeding competitiveness and societal development – what about the others? Not even social research or local applications/ideas? R16,5 billion; total innovation expenditure including R&D around R27bn in 2004. Formalised R&D excludes the poor! Licensed under a Creative Commons Attribution NonCommercial NoDerivs 2.0 SA LicenceCreative Commons Attribution NonCommercial NoDerivs 2.0 SA Licence

22. Formalised R&D excludes the poor! Formalised R&D excludes the poor! 87% of expenditure to the natural sciences, engineering and technology; 12% to the social sciences and humanities. Engineering sciences, medical and health sciences, and the ICT sector each receive relatively high shares (between 13% and 20%); while the environmental, materials and marine sciences (less than 2%) of R&D expenditure. By socio-economic objective, 62% relates to economic development objectives including manufacturing, mineral resources and commercial services (each receiving a share between 8% and 13%); expenditure on R&D in key areas such as energy resources and supply, education and training, and environmental knowledge receive relatively low shares of total expenditure (5% or less in each case) (DST, 2007). The e-fields (energy, education, environment) – innovation in great demand yet investment consistently low over a long period. Licensed under a Creative Commons Attribution NonCommercial NoDerivs 2.0 SA LicenceCreative Commons Attribution NonCommercial NoDerivs 2.0 SA Licence

23. However… However… The business sector is the dominant force in funding and performing R&D. This is a positive factor from a business perspective, but it would appear that research efforts have not yet resulted in the increased development of medium- to high- technology goods and knowledge-intensive services (NACI, 2008) The total number of researchers is 1,5 per thousand employed persons, comparable to Brazil and China, but low as compared to the Russian Federation at 6.8 per thousand Majority of research producing universities and scientific performing/funding agencies in Gauteng, historically due to science system developing around the attractive forces of economic demand and the seat of government, this clustering may today play a part in stagnation in the contribution of R&D to the local economies outside of Gauteng province. Licensed under a Creative Commons Attribution NonCommercial NoDerivs 2.0 SA LicenceCreative Commons Attribution NonCommercial NoDerivs 2.0 SA Licence

24. However… However… Provinces such as KZN and the Free State seeking to reinvent their economies as knowledge-based economies and are accordingly making the requisite infrastructure investments or considering new economic strategies: Innovation is not a quick fix, it needs sustained efforts (Lan Xue, 2009) – nor is it a trivial exercise. South Africa is generally an importer of know-how and technology As regards technological innovation and original manufacture or process development, the contribution of innovation to economy and society has remained at the level of adoption of complex technologies by business and industry, as compared to innovation in government or the not-for-profit sector, according to National Experimental Research and Development survey data for 2006/7. Licensed under a Creative Commons Attribution NonCommercial NoDerivs 2.0 SA LicenceCreative Commons Attribution NonCommercial NoDerivs 2.0 SA Licence

25. Licensed under a Creative Commons Attribution NonCommercial NoDerivs 2.0 SA LicenceCreative Commons Attribution NonCommercial NoDerivs 2.0 SA Licence

26. Licensed under a Creative Commons Attribution NonCommercial NoDerivs 2.0 SA LicenceCreative Commons Attribution NonCommercial NoDerivs 2.0 SA Licence

27. Licensed under a Creative Commons Attribution NonCommercial NoDerivs 2.0 SA LicenceCreative Commons Attribution NonCommercial NoDerivs 2.0 SA Licence And so… Historical competitiveness in the low-tech and medium-tech sectors slowly being enhanced by competitiveness in the medium-high tech sector, driven largely by a decade-long upward trend in the export of automotive components and fully built-up motor vehicles. However, mining is still South Africas largest export sector. Participation in the global high-technology production sector is minimal (3%) and static. Given the structure of the economy and employment in low and medium-low technology intensive sectors, the South African labour force has witnessed limited adoption of medium-high and high-technology tools and processes in the workplace But innovation funding focused in hi-tech and knowledge- intensive areas – is this the right choice? Innovation also needed in lo-tech & medium-lo-tech (mining, agriculture, SME), services, and society…

28. Licensed under a Creative Commons Attribution NonCommercial NoDerivs 2.0 SA LicenceCreative Commons Attribution NonCommercial NoDerivs 2.0 SA Licence Figure 2 Composition of exports 2003-2007 Source: Calculations based on South African Revenue Service s Trade Data following OECD guidelines (Hatzichronoglou, 1997).

29. Licensed under a Creative Commons Attribution NonCommercial NoDerivs 2.0 SA LicenceCreative Commons Attribution NonCommercial NoDerivs 2.0 SA Licence Access to Health and Education Quality of health and wellbeing of the general population and the level of participation in higher education are contributing factors to the capacity of people to engage in R&D and productive innovation and to grow the countrys knowledge base Why? low participation rate in higher education (15%) (NACI 2008, p.6) and post-graduate studies, creates a major barrier to the ability of the current and future generations to participate in the evolution of an innovative productive system with the potential to increase household income and per capita GDP Same applies with childhood poverty, including malnutrition and quality of education

30. Licensed under a Creative Commons Attribution NonCommercial NoDerivs 2.0 SA LicenceCreative Commons Attribution NonCommercial NoDerivs 2.0 SA Licence 20022003200420052006 Water in house or on site 61%68% 70% 20022003200420052006 Access to Electricity 76%79%80%81% 20022003200420052006 Toilet in dwelling 36%37% 38% Source: Table derived from Statistics SA s General Household Surveys. Table 5 Household amenities

31. Licensed under a Creative Commons Attribution NonCommercial NoDerivs 2.0 SA LicenceCreative Commons Attribution NonCommercial NoDerivs 2.0 SA Licence Current and Future R&D Capacity Major factors: race and gender OR gender and race: While the proportion of female academic staff in universities increased for the period 1992 – 2001 and the proportion of female R&D staff in science councils increased in the period 1996 – 2001, both groups tended to be less qualified than their male counterparts, especially at the Doctoral level (DST & NACI 2004, pp. 20 - 23). Furthermore, the upward trend in womens participation was marred by the low proportion of African, Coloured and Indian women in universities (30%) and science councils (33%). In particular, womens participation in the natural sciences and engineering was very low, from around 9% for instruction staff and 14% for research staff in engineering and engineering technology to around 35% and 29% respectively in the mathematical sciences. Only computer science and data processing showed reasonable levels of participation at 46% and 40% respectively (ibid., p.26 - 27).

32. Licensed under a Creative Commons Attribution NonCommercial NoDerivs 2.0 SA LicenceCreative Commons Attribution NonCommercial NoDerivs 2.0 SA Licence Current and Future R&D Capacity Female students constituted the greater proportion of all university enrolments and graduations for the period 1992 – 2001, and while the percentage of female postgraduate enrolments increased in the same period, womens participation at the upper postgraduate (Masters and Doctoral) levels remained below the 50% mark (NACI SET4W 2005, pp.8 - 19). These observed trends appear to be changing with respect to the future SET workforce. Data for the period 2000 – 2005 (NACI SET4W, 2009) indicates that women are approaching 50% of enrolments and graduations at the upper post-graduate level: When viewed by broad field of study the proportion of female doctoral graduates increased most substantially in the Engineering Sciences and Applied Technologies (from 12% to 19%); in Humanities (from 30% to 38%); and in the Social Sciences (from 49% to 53%). In the Health Sciences, the female share of doctoral graduates declined from 60% in 2001 to 57% in 2005 (ibid., 2009, p.16).

33. Licensed under a Creative Commons Attribution NonCommercial NoDerivs 2.0 SA LicenceCreative Commons Attribution NonCommercial NoDerivs 2.0 SA Licence Access to Financial Infrastructure

34. Licensed under a Creative Commons Attribution NonCommercial NoDerivs 2.0 SA LicenceCreative Commons Attribution NonCommercial NoDerivs 2.0 SA Licence Final thoughts… A few key features which require the attention of policy- makers and decision-makers in various spheres are: Promoting stronger articulation between innovation strategy on the one hand, and economic and social strategy directions on the other hand – with respect to the services sector, in the secondary and primary industries and with respect to the SME and informal sectors. Supporting current and future R&D capacity in the higher education sector and science councils as far as the fiscus will reasonably stretch, while encouraging business to increase R&D and innovation spend, as an investment in future economic growth and competitiveness.

35. Licensed under a Creative Commons Attribution NonCommercial NoDerivs 2.0 SA LicenceCreative Commons Attribution NonCommercial NoDerivs 2.0 SA Licence Final thoughts… A few key features which require the attention of policy-makers and decision-makers in various spheres are: Enhancing access to educational resources and improving the quality of the primary through tertiary education experience, particularly with respect to maths, science, technology and language capabilities; and with due attention to closing the race, class and gender divides. Promoting access to financial infrastructure and reducing the costs of technology adoption, particularly for promoting technology usage and related innovation in the small business and the informal sectors.

36. Licensed under a Creative Commons Attribution NonCommercial NoDerivs 2.0 SA LicenceCreative Commons Attribution NonCommercial NoDerivs 2.0 SA Licence Thank you… …questions???? http://link.wits.ac.za