Transcript Network Partners for Capacity Building and Knowledge Exchange in

Innovation System and Inequality:
The Experience of South Africa
Wits Innovation Symposium
Presentation 24 February 2010
Luci Abrahams, Wits LINK Centre & Thomas Pogue, IERI, TUT
ONE: TRENDS AND PATTERNS OF INEQUALITY
• Inequality has defined South Africa’s 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.
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Historical Patterns of Inequality
• 49.3 million people living in more than 12 million households,
South Africa’s 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 Africa’s 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).
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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
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Household 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.
•
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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
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Interregional Inequalities
• 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” (Abrahams, 2003).
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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.
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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.
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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 Africa’s rural provinces with respect to participation in
the local and global knowledge economy.
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Summative Remarks
• 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 cityregion 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.
• 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.
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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.
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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.
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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 valueadded. 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% growth good enough
– for whom?
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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 multidisciplinary 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!
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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.
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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 hightechnology 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.
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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.
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NR&D
survey
Table 1.4:
Provincial
split of R&D
2005/06*
Business
enterprise
Province
Government
Higher education
Not-for-profit
Science councils
Total
R 000
%
R 000
%
R 000
%
R 000
%
R 000
%
R 000
%
242,692
2.9
84,071
10
214,701
7.9
6,589
2.9
123,956
5.9
672,008
4.7
476,346
5.8
41,856
5
146,823
5.4
3,687
1.6
50,197
2.4
718,908
5.1
4,643,864
56.3
291,639
34.5
1,030,801
37.7
104,002
45.9
1,103,284
52.5
7,173,590
50.7
KZN
Limpopo
Mpumalanga
843,499
10.2
72,131
8.5
379,681
13.9
35,036
15.5
201,811
9.6
1,532,158
10.8
84,187
1
15,917
1.9
43,564
1.6
5,329
2.4
48,058
2.3
197,054
1.4
187,934
2.3
36,001
4.3
58,549
2.1
10,238
4.5
48,051
2.3
340,773
2.4
North-West
180,227
2.2
20,857
2.5
73,457
2.7
3,547
1.6
45,751
2.2
323,838
2.3
N Cape
14,691
0.2
42,539
5
15,263
0.6
1,650
0.7
64,284
3.1
138,426
1
W Cape
1,570,336
19
239,630
28.4
769,378
28.2
56,436
24.9
416,702
19.8
3,052,483
21.6
Total
8,243,776
100
844,640
100
2,732,215
100
226,514
100
2,102,094
100
14,149,239
100
E Cape
Free State
Gauteng
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Source: KwaZulu-Natal Department of Health, nd
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Knowledge Intensity/ Technology Intensity
Phase 2: Consolidation,
Complexity and Competitiveness
Maturity of institutions an
programmes, accompanied by
greater social and economic
complexity, based on higher
levels of knowledge intensity
Phase 1: Fusion and Infusion
Forming new institutions
and infusing existing
institutions with capacities
and resources
Current Phase: AgriIndustrial and
Services Phase
Knowledge Economy Building Blocks: Strategic Focus Areas and Mechanisms
ICTs for Network Development
Regional Innovation System
1960 - 2010
Social and Economic Inclusion
Trade in Value Added Goods and Services
2015
Knowledge and Business Ecosystem
Knowledge Intensive Human Capital
Knowledge Economy
2020 - 2030
Source: KwaZulu-Natal urban-rural innovation strategy:
Abrahams, 2009 in LINK Centre & Lindon Corporation, 2009
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Table 1: Magisterial Districts with the Largest Population (2001)
District
Population (2001)
% of Provincial Total
Sasolburg
114 450
3.85
Botshabelo
202 661
6.83
Welkom
264 781
8.92
Witsieshoek
348 781
11.75
Bloemfontein
377 968
12.73
Odendaalsrus
104 262
3.51
Source: Provincial Profile of the Free State, Development Bank of
Southern Africa, May 2003
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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 Africa’s 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…
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Figure 2 Composition of exports 2003-2007
Source: Calculations based on South African Revenue Service’s Trade Data following OECD guidelines (Hatzichronoglou, 1997).
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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 country’s 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
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Table 5 Household amenities
2002
2003
2004
2005
2006
61%
68%
68%
68%
70%
2002
2003
2004
2005
2006
76%
79%
80%
81%
81%
2002
2003
2004
2005
2006
36%
37%
37%
37%
38%
Water in house or on site
Access to Electricity
Toilet in dwelling
Source: Table derived from Statistics SA’s General Household Surveys.
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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 women’s participation was
marred by the low proportion of African, Coloured and Indian
women in universities (30%) and science councils (33%).
In particular, women’s 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).
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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, women’s 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).
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Access to Finance for R&D
Table 11 - Funders and Performers of R&D, 2006/07 (USD 000s at PPP)
PERFORMER

SOURCE 
Own funds
Government
Grants
Contracts
Agency funding
Business
Other
South
African sources
Higher education
Not for profit
Individual
donations
Foreign
Parent Company
Foundations
All sources
Total
BUSINESS
1,540,531
439,418
323,554
115,863
N/A
56,889
GOVERNMENT
DEPARTMENTS
136,946
96,405
88,690
7,715
N/A
3,254
HIGHER
EDUCATION
438,185
141,364
N/A
N/A
141,364
169,968
NOTFORPROFIT
3,729
7,425
4,321
3,104
N/A
6,061
SCIENCE
COUNCILS
76,101
455,589
285,447
170,142
N/A
66,105
TOTAL
2,195,492
1,140,201
702,013
296,824
141,364
302,277
21,744
413
4,542
4,887
2,329
65
2,608
1,311
1,090
6,160
678
4,757
5,840
145
5,690
41,239
4,876
16,143
16,789
243,333
84,155
1
159,177
2,301,915
2,493
12,865
N/A
N/A
12,865
254,358
207
69,409
N/A
N/A
69,409
821,534
726
29,554
N/A
N/A
29,554
52,930
5
79,909
N/A
N/A
79,909
683,544
20,220
435,071
84,155
1
159,177
4,114,281
Source: http://www.hsrc.ac.za/CCUP-58.phtml and Kahn, M (2009)
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Final thoughts…
Issues which require the attention of policy-makers and
decision-makers in various spheres are:
• Promoting stronger articulation between innovation
strategy and economic and social strategy directions
– with respect to the services sector, in the secondary and
primary industries and with respect to the SME and informal
sectors. Innovation in areas of consumption spending eg
major asset categories such as public housing; categories
such as education, engineering and environment; and
process innovation – anti-corruption and public management
of resources (service delivery).
• 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.
•
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Final thoughts…
Issues 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 finance and reducing the costs of
technology adoption, particularly for promoting
technology usage and related innovation in the small
business and the informal sectors.
•
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Final thoughts…
Frontiers for research and innovation policy and practice:
• Address inter-regional inequality in participation in the
R&D and innovation system:
Inter-regional inequality cannot be addressed by re-balancing
existing levels of GERD input across provinces, as this would
have the negative effect of reducing the value-creating
capacity of the major research producers. Rather, the policy
approach of promoting the provincial sub-systems, which is
currently being undertaken by the Department of Science and
Technology, requires the attention of all provincial
governments and of the metropolitan and district
municipalities.
Innovation system building in provincial sub-systems should seek
strong linkages between investment in innovation
infrastructure/resources and economic development strategies,
as future economic development is unlikely to progress at the
desired levels on the basis of the current historical path.
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Final thoughts…
Frontiers for research and innovation policy and practice:
• Gender participation in the innovation system
As a medium-sized economy, South Africa needs all its human
resources
• Innovation in the SMME and informal sectors of the
economy
Given the history and structural nature of inequality in South
Africa, the production and innovation systems are strongly
influenced by inequality, in particular with respect to the
availability of current and future R&D capacity. This is a
challenge for advancing the competitiveness of the country
and its ability to sustain economic growth through a
combination of export orientation, import substitution and
development of frontier sectors such as the SMME and
informal sectors. These modes of economic development
require higher levels of and different thinking about innovative
capacity than the status quo.
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Thank you…
…questions????
http://link.wits.ac.za
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