How can Africa Benefit
from Globalization?:
Global Governance ofTechnology and Africa’s
Global Exclusion

Banji Oyelaran-Oyeyinka

ATPS SPECIAL PAPER SERIES No. 17

ABOUT THE AFRICAN TECHNOLOGY POLICY STUDIES NETWORKThe African Technology Policy Studies Network (ATPS) is a multi-disciplinary network of researchers,
policy makers, actors in the private sector and other end users interested in generating, promoting
and strengthening innovative science and technology policies in Africa. With a regional secretariat in
Nairobi, the network operates through national chapters in 17 countries, with an expansion plan tocover the entire sub-Saharan Africa.
One of the objectives of the network is to disseminate research results to policy makers, legislators,
the organized private sector, civil society, mass media and farmers’ groups through publications,dialogue and advocacy. Among its range of publications are the Working Paper Series (WPS),
Research Paper Series (RPS), Special Paper Series (SPS) and the Technopolicy Briefs.
Papers published under the ATPS Special Paper Series are those commissioned as concept
papers, think pieces, leading conference papers and keynote addresses. In keeping with
our knowledge brokerage function, ATPS publishes, with permission of the author(s) or
journal editors, papers (published or unpublished) produced by distinguished academics/
researchers for a different purpose but judged by ATPS to be of excellent quality. Thesepapers address significant policy questions relevant to the work of ATPS and/or support
the Southern voice or an African perspective. We also consider theoretical papers that
advance our knowledge of science and technology policy issues.
ATPS is supported by a growing number of donors including the International Development ResearchCentre (IDRC), the Carnegie Corporation of New York, the Rockefeller Foundation, the World Bank,
the OPEC Fund, Ford Foundation, Coca-Cola Eastern Africa, the African Development Bank, InfoDev,
and the Royal Dutch Government.

List of Abbreviations and Acronyms
CI
DFI
FDI
GDP
ICTs
ILO
IMF
IPR
ISP
IUI
LDCs
NGOs
ODA
PC
PSTNs
PTOs
R&D
RDI
SAPs
SMEs
SSA
TRIMs
UN
UNCTAD
UNIDO
UNU
WTO

Competitiveness Indicator
Direct Foreign Investment
Foreign Direct Investment
Gross Domestic Product
Information and Communication Technologies
International Labour Organization
International Monetary FundIntellectual Property Rights
Internet Service Provider
Internet User Index
Least Developed Countries
Non Governmental Organizations
Official Development Assistance
Personal Computer
Public Switched Telecommunications Networks
Private Telecommunications Operators
Research and Development
Research and Development Institutions
Structural Adjustment Programmes
Small and Medium Enterprises
Sub-Saharan Africa
Trade Related Investment Measures
United Nations
United Nations Conference on Trade and Development
United Nations Industrial Development Organization
United Nations University
World Trade Organizations

Published by the African Technology Policy Studies Network, P.O. Box 10081, 00100
General Post Office, Nairobi, Kenya.

© 2004 African Technology Policy Studies Network (ATPS)

PUBLISHED BY ATPS COMMUNICATIONS DEPARTMENT
Printed by Newtec Concepts
P.O. Box 00800, Westlands
14180 Nairobi, Kenya
Tel: 4449849, Fax: 4450399
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ISBN: 9966-916-79-2

List of Tables, Figures and Diagrams

List of Tables
Table1:
Table 2a:Table 2b:
Table 2c:
Table 3:
Table 4:
Table 5:
Table 6:
Table 7:
Table 8:Composition of exports from sub-Saharan Africa
Implications of the demise of some African “Historical” exports
Recent prices for major groups of traditional products
Estimates of real price changes for African traditional products
Indicators of national efforts in S&T-Brazil, S. Korea, Japan, USA & SSA
Correlation matrix of human capital variables
Results of OLS regression for human capital variables
Information infrastructure for selected African countries (2000)
Correlation between IT infrastructure and network variables in SSA
Economic wealth and other determinants of the internet use in SSA (2000)

5
5
6
7
12
24
24
27
28
29

List of Figures
Figure 1:
Figure 2:
Figure 3:
Figure 4:

Performance variables in the system of innovation
Internet users and hosts in SSA (2000)
Internet users and PC density in SSA (2000)
Internet users and telephone density in SSA (2000)

13
31
31
31

List of Diagrams
Diagram 1: Gross enrollment ratios in Africa, 1960 to 1995
15
Diagram 2a: Primary education: Mean, standard deviation and coefficient of variation
16
Diagram 2b:Secondary education: Mean, standard deviation and coefficient of variation 16
Diagram 2c: Tertiary education: Mean, standard deviation and coefficient of variation
17
Diagram 2d:Tertiary education across regions
17
Diagram 3a: Average annual growth rates (%) in primary education
18
Diagram 3b:Average annual growth rates (%) in secondary education
18
Diagram 3c: Average annual growth rates (%) in tertiary education
18
Diagram 4a: Public expenditure on education as a % of GDP, 1970 to 1996
19
Diagram 4b:Public expenditure on education as a % of total government expenditure
20
Diagram 5a: Student/Teacher ratios in primary schools in Africa, 1980-1996
21
Diagram 5b:Student/Teacher ratios in secondary schools in Africa, 1980-1996
21
Diagram 6a: Government expenditure on primary education per student
22
Diagram 6b:Government expenditure on secondary education per student
22
Diagram 6c: Government expenditure on tertiary education per student
22

Table of Contents
List of Abbreviations and Acronyms
List of Tables, Figures and Diagrams
1.

Global, Technology and Development
1.1 Indicators of global exclusion

1
3

2.

Institutions and Innovation Systems in Africa
2.1 Constraints of institutional performance
2.2 Systems of innovation in Africa: the roots of exclusion from theglobal system

8
9

3.

Human Capital in African Development

14

4.

Technological and Physical Infrastructure
4.1 Telecommunications and information infrastructure

25
26

5.

Conclusion

32

11

Appendix

34

REFERENCES

36

1.

Globlalization, Technology and Development

Globalization itself is neither good nor bad. It has the power to do enormous good, and for countries
of East Asia, who have embraced globalization under their own terms, at their own pace, it has beenan enormous benefit, inspite of the setback of 1997 crisis. But in much of the world, it has not brought
comparable benefits. For many, it seems closer to an unmitigated disaster.
…the benefits of globalization have been less than its advocate claim, the price paid has been greater,as the environment has been destroyed, as political processes have been corrupted, and the rapid
pace of change has not allowed countries time for cultural adaptation. The crises that have brought intheir wake massive unemployment have, in turn, been followed by longer-term problems of social
dissolution…. (Joseph Stiglitz, Winner of the Nobel Prize for Economics 2001.)1

Globalization refers to the deep on-going socio-economic changes that started largely in the 1980s.
These changes have been associated with, and employed to explain the financial, market andtechnological competitiveness. It is also related to the increasing integration of national economies
with that of the rest of the world. Internationalization, which refers to the trade relations of the 1950s
has been revolutionized in part with the advent of information and communications technologies(ICTs). Nations of the world have always engaged in trade and other forms of exchanges. In the last
15 to 20 years there has been a major and qualitative change reflected in a high rise in capital
mobility and shifts in the structure and forms of Direct Foreign Investment (DFI)2. What constitutes
globalization is beginning to emerge but the precise ways in which they would affect individual
countries, region and economic blocks are not clear. This paper focuses on the implications of the
globalization process for Africa’s industrial competitiveness, manifested in part in the region’s inability
to produce and export manufactured goods.
Much of the global changes leading to the intense internationalization of trade and production arepartly driven by technological change particularly ICTs. The changes are highly interrelated and insome cases, causes and effects become difficult to separate. The key elements of globalization aresummarized below:

12Joseph Stiglitz (2002), Globalisation and its Discontents, Allen Lane.
OECD (1996), Globalisation and Competitiveness: relevant indicators, STI Working Papers 1996/5, Paris.

1

2

ATPS SPECIAL PAPER SERIES N O. 17• Technological change has led to new and diverse range of products and services that inturn promote specialization and new forms of exchanges including inter-industry trade.
• Tremendous improvements in transportation and communications and sharp reductions
in transactional costs have shortened economic distances for trade and manufacturing.
Improvements in production technologies have given rise to economies of scale making it
more attractive and efficient to produce far beyond the requirements of the domestic market;
increased plant sizes is a tacit incentive to explore foreign markets.
• Growth of world exports output especially in manufactures, for instance between 1965 and1990, share of exports to world Gross Domestic Product (GDP) increased from 11 to 20%.
• Rapid increases in Foreign Direct Investment (FDI). Economies in transition and somedeveloping economies have recently benefited greatly from inflows of DFI. According toUnited Nations Development Organization (UNIDO) (1996), more than 30% of total world
FDI compared to 20% in the mid-1980s goes to developing countries with most of it channeledinto manufactured exports.
• Widespread adoption of deregulation and liberalization policies.

This last element and the ways in which economic parameters and “conditionalities” have been
defined constitute the most contentious aspect of globalization. More controversial are the threemain institutions that govern globalization: the International Monetary Fund (IMF), the World Bankand the World Trade Organization (WTO). Some United Nations (UN) sister institutions, such as theUnited Nations Conference on Trade and Development (UNCTAD), the International Labour
Organization (ILO) and the United Nations University (UNU) provide countervailing views. However,
the influence of the first three institutions in defining global agenda is so pervasive as to generate astrong exclusionary effect. For instance, efforts to tie all investments issues to Trade Related
Investment Measures (TRIMS) has all but excluded substantive debates on the ways in whichdeveloping countries build up technological capabilities through technology investments. Yet, in its
fixation with trade, and less so with technological development, TRIMS has removed an important
plank upon which countries acquired technology by seeking to dilute or remove state intervention.
Global governance is evidently imperative in an era of globalization, in as much as the role of the UN
remains critical in fostering industrialization. However, global rules setting procedures and the same
rules tend to set little store on the objective conditions and institutional capacity of poor countries.3
There are other factors, but it is the dynamics of these elements, and not just their occurrence alone,that is giving rise to the new structures and patterns of global integration in trade, technology andmarkets.

An instructive example cited by Stiglitz (2001) captures the contradictions inherent in rules setting and the interest of the poor:“Those who seek to prohibit the use of nets that harvest shrimps but also catch and endanger turtles are told by the WTO that such
regulation would be an unwarranted intrusion on free trade. They discover that trade considerations trump all others including theenvironment”.
3

H OW C AN AFRICA BENEFIT FROM GLOBALIZATION?

3

Several explanations have been advanced to explain Africa’s dismal economic growth performance.
These range from policy-related issues (World Bank 1981); structural and institutional factors (Easterly
and Levine 1997, Sachs and Warner 1997); the shortage of technological and managerial capabilities
that result in the failure to effectively transfer technology and the underutilization of human andphysical resources (Enos 1992; Lall 1992, 1993); and the long-term effects of historical factors(Engerman and Sokoff 2000). While these factors explain parts of Africa’s growth problems, a systemic
explanation of the nature of institutions in long-term development is still lacking. Africa is far fromhaving uniform conditions. There are wide regional variations in economic and political governancesystems leading to differentiated trajectories in development. Thus, cross-country analysis tends tohide the considerable intra-regional variations, particularly, the significant influences of specificnational innovation systems.

This paper explores the continuing exclusion of African countries from the benefits of global
technology exchange. We propose that institutions and the persistent inappropriate pattern of humancapital formation has conditioned the observed systems of innovation and effectively determined
Africa’s development trajectory. As Rodrik (1998: 5) observed, “the way to reverse the trend (pooreconomic growth) is not to target the region’s trade volume per se, but to raise overall growth rate”.
In this respect, the paper calls attention to the role of three broad factors supporting technologicaladvance in long-term industrialization. These three important factors impact the national system ofinnovation in very important respects. They include institutions, human capital, and technologicaland physical infrastructure. The rest of the paper discusses some indicators of global exclusion,
followed with a discussion of institutions and systems of innovation. Issues of human capital are
reviewed, while section four focuses on physical and technical infrastructure. The fifth section
addresses policy suggestions.
1.1

Indicators of Global Exclusion

African countries have not succeeded in acquiring technology effectively and subsequently havefailed to achieve sustainable industrialization. Subsequently, the region has suffered the loss ofcompetitiveness in traditional commodity exports. Loss of opportunities in global trade and technology
exchange has meant that African countries have marginally benefited from globalization. Two proxymeasures of globalization, FDI and export of traditional products and manufactures, are used toillustrate the point. For most sub-Saharan Africa (SSA) countries, manufactured exports, which
remain a small proportion of global exports, had declined over the years (see Appendix Table A1 andTable 1). While SSA has realized some increase in manufactured exports, this has been due to, inpart, the effects of reduction in the prices of commodities relative to manufactures in the last 20
years, UNCTAD (2001). Oil and non-oil commodities constitute more than 80% of Africa’s exports.
More disturbing is the decline in the exports of traditional exports. According to a recent study by Ng
and Yeats (2002) for the World Bank, in 1962, Africa’s exports of palm nuts and kernels accounted for
91% of $75 million world total. Exports fell to $3 million by 1999 while global market share was lessthan 10% of 1960s. Also, global market shares for groundnuts, palm kernel oil and palm oil was

4

ATPS SPECIAL PAPER SERIES N O. 17

between 51 to 83 % but have now fallen to only between 2 to 3 %, with the combined exports of theseproducts now much lower than it was four decades ago. If Africa had maintained its 1960 global
share of markets, current exports will be about $7.7 billion higher than current export value. According
to the World Bank, “competitive share losses for palm oil are of major importance ($1.8 billion) andare about $1.1 billion for both alumina and unmilled maize”, Table 2a.
Africa has not only lost market shares of products for what used to be “traditional exports”, it has notgained the promised competitive share of manufactures for which much pain was endured in theprocess of Structural Adjustment Programmes (SAPs). The transition to processed exports of socalled traditional exports did not materialize. In the years after independence more that 40 years ago,
Africa seemed destined to becoming a major exporter of various types of vegetable oils, tin, iron,bauxite and copper ore products. It was also easy to conjecture the export of sizeable global sharesof meat products, fish oils, maize and rice products, fruit jams, and animal feeds. This scenario has
not only failed to materialize, but the region has lost price competitiveness of traditional products.
Table 2b shows that only tropical beverage group recorded an overall positive change over the last
decade due to largely more than 20% increase in coffee prices. Country data is shown for selected
countries in Table 2c.
Diversification into manufactured exports was an important objective of economic reforms with theaim of reducing dependence on commodity exports, however, the effort has not been successful. In
an analysis of the international competitiveness of nine African countries over the 1980 and 1990
period, UNCTAD (2001) found that positive competitiveness indicator (CI) explained successful
export performance. CI is explained in terms of the evolution of unit labour costs in dollars that is
positively correlated with labour productivity, and real exchange rate but inversely related to real
wages. Labour productivity is the most permanent and significant predictor of manufactured exports.
Mauritius and Egypt that have displayed dynamic and stable export profiles for the last two decades
exhibited the most sustained productivity growths.4
FDI constitutes an important source of external finance. It has assumed greater significance in theface of the decline of other sources of private and official capital, far more than for instance,
commercial loans, portfolio investment, and official development assistance (ODA). The flow of FDI
is a measure of technology transfer through such mechanisms as imports of capital goods, licensing
and joint ventures. From low global flows in FDI of 15.2% between 1981 and 1985, developing
countries share increased to 36.1% in the early 1990s. During this period, the SSA share dropped
from 1.7 to 1.3%. By 2000, Africa’s share in the flow of FDI to developing countries had been reduced
to 5%, from 25% in the early 1970s. Regarding capital goods, East and South-East Asia, including

Mauritius sustained an average manufacturing productivity growth of 4.5% for 18 years, and Egypt an average 3.5%
productivity for 16 years inspite of real appreciation in real exchange rates, and without lowering wages. Most countries attempt
to achieve competitiveness through wage suppression and sharp currency depreciation. However, wage suppression often leadto social problems as well as impact negatively on long-term productivity growth.
45

H OW C AN AFRICA BENEFIT FROM GLOBALIZATION?

China, imported about 65% of total imports by developing countries in 1994. The share of SSA
dropped disappointingly from 11.1% in 1970 to a low 1.9% in 1994. This reflects the technologicaldynamism that characterized the East Asian countries and the near stagnation that SSA economies
continue to experience. However, significant intra-regional FDI particularly from South Africa andMauritius has begun to take place while FDI from developing Asian countries has accelerated (ECA
2002).
Table 1: Composition of Exports from Sub-Saharan Africa
1980

1990

1997

Crude Petroleum

75.6

61.3

54.7

Non-oilprimary commodities

19.7

22.8

26.6

Manufactures

4.0

15.5

18.4

Unclassified

0.7

0.4

0.3

Source:UNCTAD (2001)

Table 2a: Implications of the Demise of Some African “Historical” Exports
Share (%)
Commodity (SITC)*
Palm Nuts & Kernels (2213)
Groundnuts Green (2211)
Palm Kernel Oil (4224)
Palm Oil (4222)
Natural Abrasives (2752)
Fixed Vegetable Oils, nes (4229)
Alumina (5136)
Unmilled Maize (0440)
Fur Skins (2120)
Vegetable Oil Cake (0813)
Copper Ore & Concentrates (2831)
Fish Oil (4111)
Bovine & Equine Hides (2111)
Unwrought Tin (6871)
Meat Extracts (0133)
Tine Ores and Concentrates (2835)
Plywood (6312)
Glazed or Polished Rice (0422)
TOTAL OF ABOVE

African Exports ($000)

Africa’s World Trade

1962
75,061
184,279
8,941
36
13,247
8,555
25,60818,76237,85547,401
11,492
7,825
18,155
21,761
2,120
5,851
12,1496,346
505,444

1962
91.1
83.4
53.4153.1
50.9
27.6
16.0
13.8
13.2
12.3
10.9
8.7
7.6
8.0
7.8
7.6
6.0
5.2
3.5
13.9

1999
2,861
24,542
15,816
11,634
2,059
10,13160,33020,725757
49,264
44,633
1,453
24,627
267
759
9,139
48,659601
328,257

1999
9.9
3.2
2.2
1.0
0.2
1.3
0.7
0.2
0.1
0.8
0.9
0.4
0.9
0.0
0.6
0.5
0.6
0.0
1.0

* Since Revision 2 data were not available until mid-1970s, these statistics are based on the earlier Revision 1classification which first became available in 1962.
Source: African Region Working Paper Series No. 26, worldbank.org

ATPS SPECIAL PAPER SERIES N O. 17

6
Table 2b: Recent Prices for Major Groups of Traditional Products
Average Annual Prices (1990=100)
Change (%)
Traditional Product Group*
Tropical Beverage Products
Lumber and Products
Fresh and Preserved Seafood
Fibers & Agricultural Materials
Ferrous Metals and Ores
Minerals and Products
All Traditional Products
Other Foodstuffs
Gold and Diamonds
Non-Ferrous Metals and Ores
Hides and Leather Products
Memo Items
All Non-Oil Commodities
All Foods
All Raw Materials
Metals and Minerals
Source: Ng and Yeats (2002)

Percentage Price

1980
321.4
102.9
99.3
94.9
120.3
144.9
124.4
152.6
220.3
118.6
101.1

1990
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0

1998
135.7
85.4
99.2
94.1
91.4
80.9
78.0
87.0
73.6
69.4
56.9

1999
108.8
100.8
91.3
85.5
81.5
78.9
76.1
74.1
70.2
69.3
48.9

1980-99
-66.1
-2.0
-8.1
-9.9
-32.3
-45.5
-38.8
-51.4
-68.1
-41.6
-51.6

1990-99
8.8
0.8
-8.7
-14.5
-18.5
-21.1
-23.9
-25.9
-29.8
-30.7
-51.1

174.3
193.4
145.2
130.8

100.0
100.0
100.0
100.0

95.1
100.7
83.8
72.4

85.0
84.5
85.1
71.2

-51.2
-56.3
-41.1
-45.6

15.0
-14.5
-14.5
-28.8

7

H OW C AN AFRICA BENEFIT FROM GLOBALIZATION?
Table 2c: Estimates of Real Price Changes for African Traditional Products (1990=100)

Exporting Country
LARGER COUNTRIES
AngolaKenya
Cameroon
Ghana
Zimbabwe
Nigeria
Gabon
Liberia
SACU
Cote d’Ivoire
Congo, Republic
Congo, Democratic RepublicZambiaAll Larger Countries
MID-SIZE COUNTRIES
Ethiopia
Madagascar
UgandaGuineaMalawiTanzania
Mauritania
SenegalTogo
Mozambique
Sudan
Mali
Benin
All Mid-Size Countries
All Above Countries

Estimated Level of Real Prices (1990=100)
1980
1990
1998
1999

Percentage Change (%)
1980-1999 1990-1999

255.0
156.3
128.9
148.9
96.7
152.0
101.9
109.2
156.1
257.3
123.1
138.8
113.3
160.2

100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0

118.0
194.5
88.7
89.6
93.0
91.8
80.3
81.9
71.7
111.7
69.2
69.6
62.3
92.3

101.3
92.5
92.1
87.8
84.8
87.6
77.3
76.7
70.3
84.4
67.5
66.8
59.2
78.6

-60.3
-40.8
-28.6
-41.0
-12.3
-42.4
-4.1
-29.7
-55.0
-67.2
-45.2
-50.0
-47.7
-50.9

1.3
-7.5
-7.9
-12.2
-15.2
-12.4
-22.7
-23.3
-29.7
-15.6
-32.5
-33.2
-40.8
-21.4

369.7
284.9
214.8
186.1
93.9
111.4
117.8
125.1
194.5
113.8
156.1
157.4
105.5
171.6
165.7

100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0

144.4
122.2
115.3
98.1
94.5
92.7
92.3
90.6
92.8
79.3
77.8
76.2
56.2
94.8
93.5

118.7
104.0
99.4
87.3
86.2
84.0
82.8
79.2
77.6
73.5
64.1
62.2
49.5
77.1
77.9

-67.9
-63.5
-53.7
-53.1
-8.2
-24.6
-29.7
-36.7
-60.1
-35.4
-58.9
-60.5
-53.0
-55.1
-53.0

18.7
4.0
-0.6
-12.7
-13.8
-16.0
-17.2
-20.8
-22.4
-26.5
-35.9
-37.8
-50.5
-22.9
-22.1

2.

Institutions and Innovation Systems in Africa

Institutions are conceptualized narrowly or broadly6 but in both contexts, they take on the functions of
the management of uncertainty, the provision of information, the management of conflicts, and thepromotion of trust among groups (Edquist et. al. 1997; North 1989).7 For these reasons, institutions
are necessary for innovation for two reasons. The first one is the uncertainty that characterizeinnovative activities. Institutions act to provide stability, regulate the actions of agents and enforce
contractual obligations. Second, learning and knowledge creation, validation and distribution are
prerequisites of modern economic change mediated by such institutions as organization (R&D
laboratories, finance and investment institutions) and rules as intellectual property rights (IPRs) andpatent laws. In this study, we employ the broader concept of institutions in addition to locating
institutions within a historical context that admits the evolution of institutions themselves (David
1994; Zysman 1994). Coriat and Dosi (1998) called attention to another set of issues in understanding
institutional evolution. First is the origin of the institutions, the need to explain institutions that preceded
them and the mechanisms that led to the transition. Second is what is referred to as the degrees ofintentionality of institutional constructions. It explains whether an institution arose out of a selforganizational process or derived from a collective constitutional process. Third is the concern for
institutional efficiency. The point is whether institutions are merely “carriers of history” in the sense ofDavid (1994) and simply “path-dependently reproducing themselves well beyond the time of theirusefulness (if they ever had one)” (Coriat and Dosi 1998:7). Clark (2001) gave examples of Africa’s
higher institutions established for a purpose far different to what the current objectives of Africa’s
development presently demand. The founding initial objectives persist while the developmental
requirements have radically changed and this constrains organizational effectiveness.
Three institutionally induced phenomena are said to explain the observed development of the SI in
Africa. First is the pre-existing level and pattern of postcolonial education enrollment as a proxy ofhuman capital, a strong determinant of national technological capacity. Second is the factor
endowment that had been the starting point for wealth creation in other regions, may well be obstacles

In a narrow sense, institutions correspond to such organizations as universities, technological service organizations, while inbroad terms, it includes political context governed by constitutions and the rules regulating innovation activities.
7
Coriat and Dosi (1998) refer to the broad meaning of institutions as having three components which are: (a) formal organizations(ranging from firms to technical societies, trade unions, universities, and state agencies); (b) patterns of behaviours that arecollectively shared (from routines to social conventions to ethical codes); and (c) negative norms and constraints (from moral
prescriptions to formal laws).
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H OW C AN AFRICA BENEFIT FROM GLOBALIZATION?

9

to development.8 Factor endowments have strongly determined the course of investments andsubsequently the path of endogenous technical change. Conceived as the “rules, enforcement,characteristics of rules, and norms of behavior that structure repeated human interaction” (North etal. 1988), we suggest that institutions strongly influence the pattern of endogenous technicaldevelopment. In an increasingly interdependent global context, institutions may not necessarily beendogenous to regions and societies; they may be, and are often, imported.9
Financial markets are different because they are primarily concerned with information processing,a non-commodity factor that is bound to be more problematic for poor countries with poor intellectual
institutions. Since price is unable to coordinate markets in the absence of non-existing institutions,“government may thus have to assume a more active role in performing this function”, (Stiglitz 1996).
The coordination role becomes doubly difficult when institutions are absent and state capacity foraction is weak. Physical and human infrastructure including scientific and technological institutions,telecommunication and power are important prerequisites for transformation into modern economic
systems.
Aron (1996) has applied the concept of path-dependency to explain the growth or lack thereof of
African economies. Combining the notions of path-dependency and institutional evolution in Africa,
Aron suggests that policies that presc ribe piecemeal reform that fail to take account of the historicalcontext are unlikely to result in effective economic growth.
With path-dependent institutions, empirical growth models without comprehensive proxies for initial
institutional conditions, and shocks to institutions, may seriously underestimate the adjustment costs to
new higher growth equilibria (Aron 1996: 111).

We take industrialization as the systematic acquisition of technological capabilities within the national
systems of innovation. Our analysis is neither limited to technological artifacts nor to institutions asorganizations only, but includes the norms, codes and conventions that guide the behavior of
economic agents.
2.1 Constraints to Institutional Performance
A fundamental position of the evolutionary theory10 is that institutions, unlike what neoclassicaleconomics tell us, are not neutral, but are subject to x-efficiencies much in the same way as firms do
not always perform at optimal levels (Niosi 2002). The inefficiency of institutions stems from their
The term “resource curse” has been used to describe the lack of growth-generating effect of natural resources in developing
countries, see Mikesell (1997) and Aunty (1998).
9
For instance, the system of organized R&D within labouratories is an invention of the West. See Rosenberg and Birdzell (1986).
10
In broad terms, and in whatever discipline, evolutionary theories have properties by which they explain the processes of selftransformation, an issue central to our thesis. According to Witt (2002) an evolutionary theory is: (i) dynamic - such that the
dynamics of the processes, or some of their parts, can be represented; (ii) historical - in that it deals with historical processes which
are irrevocable and path-dependent; (iii) self-transformation explaining - in that it includes hypotheses relating to the source anddriving force of the self-transformation of the system.
8

ATPS SPECIAL PAPER SERIES N O. 17

10history and their connectedness to previous environment. Institutional evolution, therefore, is pathdependent and inefficiency could arise from any of the two sources. These are inter alia:• Rigidities in Organizations: This may stem from the founding ideals of organizations that
resist change in the face of new conditions and challenges. Clark (2001: 84) observed that,“in a world that is changing very rapidly (i.e. in one in whose systems parameters are shiftingalmost as fast as its variables) the pure scientific model inherited from the 19th Century is nolonger viable in itself as a core methodology.” Inertia may result from self-reinforcing
institutional networking that is now obsolete, or at best, needing radical reforms. Institutional
resistance may not be solely a result of poor judgment or lack of vision but of fear from theoutcomes of change. Innovation brings uncertainty and as Niosi (2002: 294) points out,
“Organizations tend to stick to their own obsolescence plans, particularly if they area uncertain
about the gains to be realized by the abandonment of existing technologies or organizations,and the adoption of the new ones. Sunk costs, in form of machinery and training of staff areanother reason why change becomes a difficult proposition.”•

Sub-optimal Knowledge Networks: Information asymmetry may lead to poor flows of
information and knowledge among critical economic agents within the system of innovation.
For instance, highly centralized knowledge “producing” institutions that include universities
and R&D laboratories, may be far removed from production systems. This has been observed
particularly in developing countries (Forbes and Wield 2000).

There are different types of organizational ineffectiveness that may manifest as system inefficiency(Niosi 2002). They are as follows:•

Institutional inadequacy that manifest as lack of rules of the game, poor enforcement ofcontractual laws and inadequate intellectual property laws that may constitute disincentives
to innovation and technological learning.

•

A possible lack of threshold in the number of such organizations as research institutions,private or public agents that assure quality, universities and vocational education centers. In
developing areas, it is not the number but the relevance of the institutions. Many havequestioned the role of government Research and Development Institutions (RDIs) that havelittle linkages with the productive sectors, and the relevance of universities that do not relatewith dominant actors in the economy, such as small and medium enterprises (SMEs).

•

Poor coordination of knowledge and economic production functions as cited above.
Examples include the demand and supply for skills at sectoral levels, the kinds and thequantity and quality mix required at different times.

•

Poor resource commitment for meeting organizational commitments, such as poor funding
and inadequate staffing may lead to x-ineffectiveness.

H OW C AN AFRICA BENEFIT FROM GLOBALIZATION?
2.2:

11

Systems of Innovation in Africa: The Roots of Exclusion from the Global System

In the 1960s, several African countries, in an attempt to achieve scientific and technological progress,
engaged in the wholesale imitation of industrialized countries’ model of institutionalization of science.
This involved the establishment of specialized R&D institutes to generate scientific knowledge andfrom which industry and agriculture would then draw when needed.11 Studies show that this great
experiment achieved very limited success, (Oyelaran-Oyeyinka 1996; Adeboye 1997). We suggestthat the two most important causes of this failure is the lack of an institutional base for innovation andsecondly, the shortage of the right kinds of human capital to build and sustain a technical foundation
for industry. Rather than aim to draw more on the underlying principles and processes that had
generated the diversity of past and present institutions, African countries tend to focus on building
organizations without much attention to institutions to sustain them. By this, we mean the evolutionary
process of innovative design and development that had fitted institutions to differing and changing
contexts, while usually embedding individual components within functionally coherent structures.
By simply imitating structures that work for the present context in the industrialized countries, Africancountries ignored the fact that these institutions were products of an organic process, rather thanmechanically given forms. The institutional forms were created, refined and adapted to given contexts
over a long historical period. As a result, problems of functional incoherence were designed into thestructure from the beginning. The present institutional structures observed in the industrializedcountries were radically different from what they were half a century ago.
It took decades for basic science to become an increasingly powerful force in the productive sector.
This was an evolutionary process following after the development of technological infrastructure
and rising incomes. Gradually, through technological learning based on imitation, the skill of theartisan and the genius of the lone inventor became increasingly subsumed in what Galbraith referred
to as the technostructure. Technostructure is the planning system that characterizes the modern
industrial corporation. As Marx perceptively noted, “Invention then becomes a business, and theapplication of science to direct production itself becomes a prospect, which determines and solicitsit” (Marx 1973:704). This leads to another important observation. The technical foundation of industry
had to be laid, after which the post scientific era found a secure anchorage. Without the endogenous
technical capability accumulated during the pre-scientific era, when metallurgy and machines tools
industries developed, it would have been near impossible to erect the present complex industrial
structures. This is a lesson easily missed by structural adjustment advocates and African policy
makers. Systems of innovation support production, while production systems take a long time tobuild. “Getting the price right” cannot possibly be a panacea, neither could it be a substitute for thefundamental evolutionary assignment of getting the institutions right.

The establishment of R&D organizations seemed to have been taken to represent a system of innovation.
This idea unfortunately persists in conception and practice. The so-called “linear model” of innovation has
had a profound influence on the thinking of African policy makers for decades. See Vitta (1990).
11

ATPS SPECIAL PAPER SERIES N O. 17

12

But these developments seem more like consequences than causes of the West’s unique institutional
invention: a large, highly organized body of scientists seeking explanation of all natural phenomena
by a common method based on observation, experiment and reason. This achievement can becredited to a large extent on the successful invention of an institutional form that suits the context ofthat particular environment. This unique characteristic of modern industry distinguishes it from the19th Century Industrial Revolution. Indeed, it is doubtful if the scientific-technical revolution of the 20th
Century could have been possible without it. Galbraith (1985) sums it up very succinctly:“The real accomplishment of modern science and technology is in taking ordinary men, informing
them narrowly and deeply and then, through appropriate organization, arranging to have theirknowledge combined with that of other specialized but ordinary men. This dispenses with the need of
genius” (ibid: 64).

The lessons for African policy makers seem complex yet simple. The role of institutions is sharply
illustrated by examples cited above but the context is as different as the past century is from thepresent one. What worked in the last 50 years may not be applicable now, and what worked forEurope may not be totally suitable for the present state in Africa. What seem important are theunderlying principles: the role of institutions and their path-dependence, and the importance ofinvestment in human capital at all levels from formal schooling to industry. In figure 1 we formalize
the narrative into a simple model, while Table 3 provides a comparative picture of the nature ofnational systems in SSA and in other regions.
Table 3: Indicators of national efforts in S&T-Brazil, South Korean, Japan, the United States and subSaharan Africa.
Indicators

BrazilScientists and Engineers
engaged in R&D per
million of population
Expenditure for R&D as
a percentage of GNP
Expenditure in R&D by
source of funds %Government
Productive enterprise
Other
Total patents field in the
US as a percentage of
total patents
Number of tertiary students
per 10,000 inhabitants

Japan

168
(1995)

South
Korea
2193
(1996)

Sub-Saharan Africa*

4909(1996)

UnitedStates3676(1993)

0.81(1996)

2.8(1996)

2.8(1996)

2.64(1996)

0.01(1997)

57.2(1996)
40.0(1996)
2.8(1996)
0.07(1998)

15.9(1994)
84(1994)
0.1(1994)
2.2(1998)

9.6(1995)
65.2(1995)
25.2(1995)
18.6(1998)

35.5(1995)
59.4(1995)
5.1(1995)
55.7(1998)-

5.0(1996/7)

3.5(1994/5)

14.0(1995/6)

Senegal
3 (1996)

Uganda6.6(1996)
2.2(1996)
90.3**

S. Africa
1,031(1993)
0.70(1993)
S. Africa
42.7(1993)
54.4(1993)
1.8(1993)

0.004(1998)
2.6(1996/7)

7.7(1994)13

H OW C AN AFRICA BENEFIT FROM GLOBALIZATION?

Source: Office for Patent and Trade Mark Information, USA; UNESCO Statistical Yearbook, various issues; OECD
Statistical Yearbook, various issues.
Notes:*Due to the difficulties in obtaining reliable aggregate statistics for the entire sub-Saharan region, the authors, in somecases, have chosen to use a range of values (from the lowest to the highest) to represent the statistics for the region.
** Funds from abroad.

Technical skills

Human Capital

Literacy

Per Capita
Income Level
Industrial Firm

Industry Capital
Research
Development
Capacity

Other
Knowledge Bases

Universities
Vocational andTechnical Centers

Figure 1: Performance Variables in the System of Innovation

3.

Human Capital in African Development

One of the key factors behind the phenomenal economic success of industrial latecomers, such as
the South-East Asian economies was their emphasis on forming human capital and a dynamic
system of innovation. These countries, employing a mix of selective and functional policies, developed
an education structure that effectively provided the requisite skills for their industrialization initiative.
Public spending was concentrated on primary and secondary education while the demand for
tertiary education was primarily financed by the private sector. Public spending at the tertiary levelfocused on science and technology education, while the humanities and social sciences wereprivately funded. The governments, to varying degrees, intervened in curriculum development toensure that it was compatible with the needs of their evolving industrial policy. To this end, they interalia encouraged private sector involvement in universities. Additionally, some countries, notably
Singapore, imported expatriate skills where domestic capabilities were limited ( Lall 1992; Page
1994).
By contrast, the current educational structure in Africa has been described as “unsuitable forindustrialization” (Lall 1992: 119). Several reasons have been advanced to explain this description.
First, some researchers argue that the present education system in Africa is a legacy of colonialism(Blakemore and Cooksey 1982). It seems that the missionaries, in concert with the metropolitan
powers, implemented a highly academic, subject-centered curriculum in Africa. This curriculum,with its focus on producing an academic elite, was largely irrelevant to Africa’s development needs.
African countries, partly influenced by the British and French colonial elite with their classicaleducation and lack of technical knowledge, viewed academic education as the sole means ofsocial and economic mobility. 12
Only a privileged minority benefited from this elite education. In 1960, the gross primary enrolment in
SSA was a mere 36%. This was roughly half the levels found in Latin America (73%) and Asia (67%)(World Bank 1988). It appears that the colonial governments, in an attempt at social control, deliberately
Western education also disrupted power relations in Africa’s traditional societies. In some cases, traditional leaders were more
unwilling than their subjects to send their sons to school. However, over the course of colonialism, the status hierarchy in Africachanged from the traditional ascriptive one based on lineage to the Western achievement one of education. Indeed, the mosteducated increasingly replaced the chiefs as the elite. Their education and occupational achievement gave them status in the eyesof the local population according to the emerging hierarchy of values. See Blakemore and Cooksey (1982: 42-44).
12

14

15

H OW C AN AFRICA BENEFIT FROM GLOBALIZATION?

limited access to education, particularly secondary education, among Africans. Lord Lugard, forexample, postulated that the expansion of missionary schools in southern Nigeria, “seems to haveproduced discontent, impatience of any control and an unjust assumption of self-importance in theindividual” (quoted in Blakemore and Cooksey 1982: 37). Indeed, academic education was conceived
not as a means of industrializing the countries but rather creating an elite supply of white-collar
African workers for the administration of the colonies.
African governments sought to remedy this situation in the post independence era. As Diagram 1
demonstrates, their performance has been impressive. Within two decades, the gross primaryenrolment ratio13 tripled from 39% in 1960 to an astounding 81% in 1980. This ratio subsequently
declined by 8% in 1999. However, gross secondary and tertiary enrolment steadily increased during
the period. Secondary enrolment ratios rose six-fold during 1960 to 1995, while tertiary enrolment
ratios increased seven-fold during 1960 to 1990.
Diagram 1: Gross Enrollment Ratios in Africa, 1960 to 1995
90
80
70
60
Primary

50

Secondary40

Tertiary

30
20
10
0
1960

1970

1975

1980

1985

1990

1995

Source: World Development Indicators (CD-ROM).

Enrollment ratio is defined as the ratio of the number of persons enrolled in school to the population of the corresponding age groupby educational level.
13

ATPS SPECIAL PAPER SERIES N O. 17

16

Enrollment levels vary considerably at the three levels, with the largest variation found at the tertiarylevel and smallest at the primary level. Diagrams 2a-c shows the mean, standard deviation and thecoefficients of variation of the enrollment ratios at the primary, secondary and tertiary levels. The lastvariable, the coefficient of variation, is a relative measure of variation and can thus be expressed inpercentages or ratios. The analysis of the data for primary education reveals that the standard
deviation rose for the period 1960 to 1980, declined over the next 10 years before rising again, while
the coefficient of variation declined over 1960 to 1990, showing a tendency of a rising mean enrollment.
For both secondary and tertiary enrollment, standard deviation rose over the whole period, with thecoefficient of variation for secondary enrollment first declining sharply in the first ten years, then risingand assuming a steady but slight decline between 1970 to 1990, again showing a steady rise inmean enrolment. Changes at the tertiary level were not as significant.
Diagram 2a: Primary Education: Mean, Standard Deviation and Coefficient of Variation

100
80

Mean

60

SD

40
Coefficient of
Variation

20
01960 1970 1975 1980 1985 1990 1995

Diagram 2b: Secondary Education: Mean, Standard Deviation and Coefficient of Variation

140
120

Mean

100
80
60

SD

40

Coefficient of
Variation

20
01960 1970 1975 1980 1985 1990 1995

17

H OW C AN AFRICA BENEFIT FROM GLOBALIZATION?
Diagram 2c: Tertiary Education: Mean, Standard Deviation and Coefficient of Variation

140
120
100
80
60
40
20
0

Mean
SD
Coefficient of
Variation
1970

1975

1980

1985

1990

1995

Diagram 2d : Tertiary Education: Comparative Picture Across Regions

Further analysis reveals that the average annual growth rates in school enrollment vary widely among
different groups of African countries. The average annual growth rate in primary education declinedin the post 1990 period for only the middle-income, oil exporting countries as Angola and Cameroon,and the middle-income, oil importers including Botswana and Senegal. The former group saw
average annual growth rates slip from 19% in 1985 to 1990, to 0.1% in 1990 to 1996 (See Diagram
3a). Moreover, it was only these two groups that experienced a decline in the average annual growth
rates in secondary education. As Diagram 3b shows, the middle-income oil importers saw averageannual growth rates in secondary education decline from 7.2% in 1985 to 1990, to 5.2% in 1990 to
1996. However, all of these countries experienced sharp falls in the average annual growth rates oftertiary education. For example, in the low-income, semi arid countries, such as Kenya and Burkina
Faso, average annual growth rates in tertiary education were halved in the post 1990 period, from
6.5% in 1985 to 1990 to a mere 3.5% in 1990 to 1996 (See Diagram 3c). Diagram 2d shows acomparative picture across the regions and not surprisingly, SSA has the lowest tertiary enrolment.

ATPS SPECIAL PAPER SERIES N O. 17

18

Diagram 3a: Average Annual Growth Rates (%) in Primary Education
12

Low-income
other

10
8

Low-income
semiarid

6
4

Middleincome oil
0exporters
Middle1970-1980 1980-1985 1985-1990 1990-1996
Diagram 3b: Average Annual Growth Rate (%) in Secondary Education
income oil
2

Diagram 3b: Average Annual Growth Rate (%) in Secondary Education

14
12

Low-income
other

10
8

Low-income
semiarid

64
2
0
1970-1980 1980-1985

1985-1990 1990-1996

Middleincome oil
exporters
Middleincome oil
importers

Diagram 3c: Average Annual Growth Rate (%) in Tertiary Education
Low-income
other

25
20

Low-income
semiarid15
10
50
1970-1980 1980-1985 1985-1990

1990-1996

Source: ADEA, Statistical Profile of Education in Sub-Saharan African, 1999.

Middleincome oil
exporters
Middleincome oil
importers

19

H OW C AN AFRICA BENEFIT FROM GLOBALIZATION?

Notes:
Other Low-income include Benin, Burundi, Central African Republic, Comoros, the Democratic Republic of Congo,
Equatorial Guinea, Eritrea, Ethiopia, Ghana, Guinea, Guinea-Bissau, Kenya, Lesotho, Liberia, Madagascar, Malawi,
Mozambique, Nigeria, Rwanda, Sao Tome, Sierra Leone, Sudan, Tanzania, Togo, Uganda, Zambia.
Low-income, semi-arid countries include Burkina Faso, Chad, Gambia, Mali, Mauritania, Niger, Somalia.
Middle-income oil exporters include: Angola, Cameroon, Congo, Gabon.
Middle-income oil importers include Botswana, Cape Verde, Cote d’Ivoire, Djibouti, Mauritius, Namibia, Senegal,
Seychelles, South Africa, Swaziland, Zimbabwe.

This period also saw fluctuations in public expenditure on education. This variable slightly declined
during 1970 to 1975, recovered in 1980, but dropped dramatically to half of its 1970 value in 1996
(See Diagram 4a). Further analysis of the data on public education expenditure reveals wide variations
among African countries. For example, low-income countries, such as Benin, Ghana and Kenya
experienced the greatest decline in public expenditure on education: government expenditure on
education as a proportion of total expenditure precipitously fell in two decades from 16% in 1970 to
12% in 1990. It was only in 1995 that government spending on education was restored to 1970 levels(See Diagram 4b). Other groups of African countries also experienced fluctuations in public
expenditure on education. Most experienced steep declines in spending in 1985 with some recovery
in 1995 (See Diagram 4b).
Diagram 4a: Public Expenditure on Education as a percentage of GDP, 1970 to 1996
4
3.5
3
2.5
2
1.5
1
0.5
0
1970

1975

1980

1985

1990

Source: ADEA, Statistical Profile of Education in Sub-Saharan African, 1999.

1996

ATPS SPECIAL PAPER SERIES N O. 17

20

Diagram 4b: Public Expenditure on Education (as a percentage of total government expenditure)

Low-income
other

30
25

Low-income
semiarid

20
15
10
5
0
1970

1980

1985

1990

1995

Middleincome oil
exporters
Middleincome oil
importers

Source: ADEA, Statistical Profile of Education in Sub-Saharan African, 1999

Directly impacting industry is the product of higher education system, specifically engineering andscience graduates. There is a suggestion that tertiary institutions produce an inappropriate mix ofskills. For example, African institutions of higher education presently enroll 60% of students in thearts and humanities, and 40% in science and engineering. Enrollment in technical subjects presently
lags behind that of other regions. While in 1995, only 0.04% persons as a percentage of the population
were enrolled in technical subjects, such as engineering and mathematics, the figure for four AsianTigers was 1.34% (Lall, 2001). In a set of technical enrolment index constructed by HarbisonMyers14, while Norway ranked first with 73.52%, South Africa, the most industrialized country in SSA
had a total of 23.61%, Nigeria, 5.85% (less than 9% of the Norwegian figure) with most SSA ranged
from 1 to 5%. The colonial legacy of a limited emphasis on technical enrollment may have been
appropriate during early independence period when most African countries were faced with a paucityof administrative staff. However, this skill mix has remained unchanged for the past four decades
despite the declining demand for arts and humanities graduates, and the rising and unfulfilled
demand for science and engineering graduates (World Bank 1988; Fabayo 1996; Delano et al.
2000).
The situation is compounded by the quality of education offered in Africa, which is said to be well
below world standards. Education standards are increasingly becoming poor with the gap inachievement between African students and those in industrialized countries “widening to unbridgeable
proportions” (Clarke 2000: 82). Indeed, the student/teacher ratios at the primary and secondary
See Lall (2001). Technical enrolment index is tertiary enrolment (times 1000) plus tertiary enrolment in technical subjects (times5000), both as percentage of population.
14

21

H OW C AN AFRICA BENEFIT FROM GLOBALIZATION?

schools have steadily increased in the post 1990 period especially for low-income, semi arid countries,
such as Gambia and Chad, and the middle-income oil importers like Botswana and Zimbabwe(See Diagram 5a-b). In addition, there has been a drastic decline in the quality of physical inputs(e.g., African staff, especially at the senior levels, and learning resources and facilities) that are
essential for the successful operations of knowledge institutes. The declining quality of education islargely a result of constant budget cuts (since 1980) together with rapid increases in enrolment
rates. This has made the financing of education recurrent costs more difficult (World Bank 1988). As
diagrams 6a-c show, the expenditure per student at all levels has declined drastically since 1970.
This decline is more serious for secondary and tertiary education, with most low-income countries
experiencing the most severe declines. In Chad, Gambia and Niger, government expenditure persecondary student fell from US$ 536 in 1970 to a mere US$ 90 in 1995. Expenditure on tertiary
education fared no better: spending per student dropped from US$ 5,054 in 1980 to US$ 1,185 in
1990.
Diagram 5a: Student/Teacher Ratios in Primary Schools in Africa, 1980-1996
60
50
40
30
20
10
0
1980

1985

1990

1995

1996

Lowincomeother
Lowincomesemiarid
Middleincome oil
exporters
Middleincome oil
importers

Diagram 5b: Student/Teacher Ratios in Secondary Education in Africa, 1980-1996
Lowincome
other

35
30
25

Lowincomesemiarid

20
15

Middleincome oil
exporters

10
5
0
1980

1985

1990

1995

1996

Middleincome oil
importers

Source: ADEA, Statistical Profile of Education in Sub-Saharan African, 1999.

ATPS SPECIAL PAPER SERIES N O. 17

22

Diagram 6a: Government Expenditure on Primary Education per student (constant 1990 US$)

Low-income
other

300
250
200

Low-income
semiarid

150
100
50

Middleincome oil
importers

0
1970

1980

1985

1990

1995

Diagram 6b: Government Expenditure on Secondary Education per student (cost in constant 1990
US$)
Low-income
other

800
700
600
500
400
300
200
100
0

Low-income
semiarid

1970

1980

1985

1990

1995

Middleincome oil
importers

Diagram 6c: Government Expenditure on Tertiary Education per student (constant 1990US$)

6,000
Low-income
other

5,000
4,000
3,000

Low-income
semiarid

2,000
1,000
0
1970

1980

1985

1990

1995

Middle-income
oil importers

Source: ADEA, Statistical Profile of Education in Sub-Saharan African, 1999.

H OW C AN AFRICA BENEFIT FROM GLOBALIZATION?

23

Worsening the skills dilemma in Africa, firm-level training that complements the education system isweak. Enterprises, with the exception of the major multinationals, invest very little in training. Moreover,
the apprenticeship system that exists in Africa is geared more to the development of traditional skills
that are of a very low level of technological sophistication (Lall 1995). Several countries have attempted
to bypass the formal education system by establishing non-formal training activities that are largely
funded by non-governmental organizations (NGOs). They involve such activities as literacy, agriculturalextension and vocational skills. However, it appears that the activities offered by the informal system
are vulnerable to disincentives and are of poor quality (Clark 2000).
The economic conditions in most African countries and declining employment prospects in the
public sector that historically, has been the largest employer, have resulted in growing levels of yment
and underemployment of graduates. A recent study conducted in Nigeria places the level of
unemployment among tertiary graduates at 22% (Delano et al. 2000). Further, studies point to theunderutilization of graduate skills. Indeed, it is a paradox that in a region that suffers from a shortageof graduates with relevant skills, there seems to be unemployed engineers or technically qualified
personnel operating in non-technical operations (Lall 1992; Fabayo 1996). Underemployment ofskills within firms persists due to slow growth of capita income, caused by low and stagnating growthof key productive sectors.
Tables 4 and 5 show correlation and OLS regression output for human capital variables. The
percentage of the population enrolled in technical subjects (including engineering and technicalsubjects) is a significant predictor of development, but the total R&D personnel was not significant.
This means that development is positively associated with the growth of technical personnel while
personnel in R&D make no contribution to income growth. This is intuitively correct as very little local
R&D is carried out in Africa. However, technical personnel may be fully engaged in production andmaintenance functions but not with R&D. Firms within the SI in Africa are engaged in imitative
product innovation that requires marginal investment in formal research other than quality assurance.
On industrial skills, we equally found statistical significance with industrial labour force but nonsignificance with agriculture labour force. The industrial labour variable is indicative of a country’slevel of development, but it is a surprising outcome given the low productivity of industry in Africa.
However, one may not read too much into this finding as the variable might have been subsumed byother skills factors, such as technical enrolment. It may also find consistency with the continuing
importance of agriculture that does not turn out significant in African economies. Read in conjunction
with the contribution of technical personnel, our interpretation is that the economies of SSA do
benefit from significant local but relatively low-level technological regime. Conversely, it may beargued that the lack of significance found for industrial R&D may be reflective of the immaturity of theregion’s industrialization initiatives that cannot yet fully use sophisticated technological products
and processes. This is symptomatic of the dissonance between the education system and the stageof industrialization in the region.

ATPS SPECIAL PAPER SERIES N O. 17

24
Table 4: Correlation Matrix of Human Capital variables
Log per
capitaPearson Log per
1,000
capita36
Agricultural.717**
Labour(.000)
35
Industrial.728
Labour(.000)
36
Technical.643
Enrolment(.000)
24
R&D-.122
personnel(.277)
30
Secondary.538
enrolment(.002)
75
29
Tertiary.336**
enrol(.047)
80
36** .01 level of significance (2-tailed)* .05 level of significance (2-tailed).
***enrol- enrolment

AgriclabourIndust.
labour

Tech.

R&D
Sec.
Personell enrol

Tertiary
enrol

35
-.231
(.128)
25-.151(.116)
25

1.000(.000)
40

1.000
38
-.868
(.000)
38-.521*(.003)
27.278(.085)
32-.720(.000)
30
348**(.000)
37

1.000
41
.303
(.054)
29-.209(.152)
35.697(.000)
30.108(.300)
40

1.00
29
-.175
(.196)
24.229**(.131)
22.543**(.002)
28

1000
30
.568
(.001)
30

Table 5: Results of OLS Regression for Human Capital variables
constant
Agriculture labour
Industrial Labour
Technical enrolment
R&D Personnel
Secondary School
Tertiary enrolment

Model I
3.728
(2.785)
1.121E-02(.791)
7.246E-02(2.326)17.241(2.809).203(.668)
8.253E-03(.396)-2.048E-03(-.013)

Sig.
.010
.426
.009
.001
.501
.534

Model II
3.727
(2.864)
1.122E-02(.812)
7.269E-02(2.899)17.190(3.749).203(.685)
8.040E-03(.632)

Sig.
.002
.531
.006
.001
.520

Model III
4.050
(3.434)8.111E-03(.638)
7.489E-02(3.060)16.639(3.750).190(.655)

Sig.
.000

.000
.000
.446

4.

Technological and Physical Infrastructure

An efficient infrastructure is important for two main reasons. First, lack of it compels optional provision
placing added financial and material burden on firms. Firms regard the cost of alternative utilities amajor impediment to new investments, as extra financial provision is required for major plant vintages
as well as for minor plant additions. Second, inadequate national infrastructure makes networking
among firms extremely difficult. For example, transaction costs are high where communication ishindered either by poor telecommunications or frequent power outages. In some cases linkage is
not only made difficult, but impossible. In most African countries, agricultural and industrial production
is constrained by inadequate backward linkage to exploit agricultural raw materials located within
inaccessible but rich rural communities. This maybe due to poor road networks, lack of informationand inadequate storage facilities15.
Frequent power outage compels firms to acquire standby power generating sets. Firms that are
unable to acquire private facilities either cut down production or in rare cases, share power withnearby firms with generating sets. There is the constant risk and realities of damages to sensitivemachinery resulting from unplanned power cuts. The perennial poor state of infrastructure leaves
manufacturers with little confidence in the ability of public enterprises to meet their supply
requirements.
The effect of poor infrastructure on routine production activities could be very significant. To theextent that there is greater propensity for technical change in a regime of continuous production, theavailability of infrastructure is critical to achieving competitive advantage. Planning becomes difficultand coordination among economic agents within the national economy and with international agents,
very problematic. Spontaneous inter-organizational linkages made possible by all-purpose
infrastructure are a prerequisite for ‘networking’ – that complex of backward and forward linkages taken for granted in dynamic industrial environments. We find that the constraints seem to redirect
the focus of firms in unprofitable direction. Rather than take a long-term perspective of ‘internal’
infrastructure as a component part of a firm’s strategic growth process (e.g. skill development, retraining to match new technologies etc.), firms are forced to deal with issues largely of public policy.

On a 1998 mission to some of Ethiopia ’s agricultural research station by road, the journey which on a good road should be no
more than one hour took three hours. The station had no functioning telephone.
15

25

ATPS SPECIAL PAPER SERIES N O. 17

26

Firms are being penalized for this public policy failure, through provision of alternative utilities.
Where such options are beyond firms’ capacity, the innovation investments tend to be the first casualty.
In sum, issues relating to infrastructural capacity and capability within firms in a SSA country shouldbe central to discussions on innovation as infrastructure significantly influences the path and processof inventive activities. It would be misleading to consider them as fixed factors of technical change.
4.1

Telecommunication and Information Infrastructure

ICT infrastructure may be divided broadly into three components: telecommunications, computing
and connectivity infrastructure. Historically, the key telecommunications actor had been the Public
Switched Telecommunications Networks (PSTNs). However, in the last two decades, privatizationand market liberalization led to public divestments as well as the entry of new private
telecommunications operators (PTOs) into the sector. Massive restructuring resulted but moreremain to be done to create truly competitive markets in the telecommunication sector in Africa.
While some progress has been made in improving connectivity infrastructure, there remains strong
reliance on the US Internet backbones for connectivity infrastructure. Skills, innovations and major
investments are concentrated in the triad of USA, Japan and Europe. While users have some form ofcontrol on the provision of private computing facilities, access to, and the quality, telecommunicationand connectivity available to a user depend on geographic space. In effect, the economic environmentis a determinant of the access, speed, and types of data and information and knowledge to whichusers have access.16
At the very basic level, countries have highly differentiated access to telephone and electricity services.
The quality of these basic engineering and physical infrastructure is important because information
coded in files travel through series of linked nodes within the ICT network. The slowest link in the
network node becomes the rate-determining step and thereby defines the overall speed of datatransmission (Dholakia, 1997).17 On the other hand, local and regional telecommunications
infrastructure, such as server connectors, local loop telecommunication lines, inter-nodal connections
and switching systems determine the cost and quality of access. Users in high-bandwidth
telecommunications environment are likely to have access to lower cost connections. Most developing
countries face capacity constraints, largely a result of thin-bandwidth and frequent power outages.
The combined effects of poor infrastructure result in high average cost of access to the Internet. Cost
components include charges for local calls, line rentals and costs due to Internet Service Provider(ISP) services. Historically, there has been a strong correlation between basic domestic and industrial
technological artefact adoptions, such as telephone, computers and levels of development.

Castell cites (Porat, 1972) and defines Information as simply : “data that have been organized and communicated”
For example, a 28.8kbps modem on a home computer may yield a transmission speed of no more than 24.6, a speed loss of
14.5% as a result of the quality of telephone lines.
16
17

27

H OW C AN AFRICA BENEFIT FROM GLOBALIZATION?

The correlation matrix in Table 7 shows the indivisibility of the various “wired” facilities particularlyelectrical power and telephone on the one hand, and networks variables comprising personal
computers (PCs), modems, and other telecommunication facilities on the other. Internet use andInternet hosts display high correlations among themselves. The correlation derives from a group of
42 African countries but this propensity equally holds for other highly developed countries and regions(Hargittai 1999).
Table 8 shows further differentiation of SSA into low and high-income countries. Not surprisingly,
most of Africa’s Least Developed Countries (LDCs) fall into the low-income group as well as the low
access, poor connectivity category. This confirms what we already know about the correlation ofincome with Internet access. For instance the 33 LDCs share of Africa’s GDP was only 16.5%, about
one-quarter of SSA 46 countries that was 59.5% of Africa’s GDP. In Table 8, we have constructed an
Internet User index (IUI) for all countries. The country with the highest per capita IUI, Mauritius, has
the maximum value 1.0 and is one thousand times the value for the least, Ethiopia. Evidently there ishigher correlation between IUI and the variables for the relatively higher income countries. South
Africa has the next best while the African LDCs like Burundi and Eritrea with low per capita income
also have low IUI. The general conclusion is that while low income is correlated with low access,some countries with the same economic structures may display different patterns Internet connectivity.
Figures 2, 3, and 4 show the correlations in graphical forms. The main reasons for this may be well
be historical, but may also result from policy and institutional building approaches.
Table 6: Information Infrastructure for selected African Countries (2000)
Country

TelephoneInternet
Interband
mainlines
Hosts perwidth
per 1,000
10,000outgoing
peopleInhabitants(Kbps) 2001
Algeria
57
0.01
2048
Tunisia
90
0.03
41500
South Africa 114
42.95
300,000
Namibia
63
18.51
3072
Mauritius
235
27.44
4096
Kenya
10
0.53
6144
Zimbabwe
18
2.16
5120
Egypt
86
0.35
112,500
Angola50.01
14000
Guinea8
0.25
128
Ethiopia40.01
512Lesotho
100.47
512Mauritania
7
0.45
384
Niger
2
0.16
192
Nigeria
4
0.07
9216
Rwanda2
0.47
128
Uganda3
0.08
2048
Zambia
8
0.86
3072
Ghana
12
0.25
4096
Source: UNDP, Human Development Report, 2001

Waiting
time(years)
5.4
0.9
1.1
0.7
1.0
8.1
10.0
1.9
8.5
0.1
7.8
10.0
10.0
1.1
1.4
4.0
3.6
6.7
1.5

Mobilephonesper 1,000
people
3
6
190
47
151
4
17
21
2
5
0
10
3
0
0
5
8
9
6

PC’s per1,000
peopleInternet
users

6.5
22.9
61.8
34.2
100.5
4.9
11.9
22.1
1.1
3.7
0.9

50
100
2,400
30
87
200
50
450
30
8
10
4
5
5
200
5
40
20
30

9.4
0.5
6.6
2.7
6.7
3.0

ATPS SPECIAL PAPER SERIES N O. 17

28

Table 7: Correlation between IT Infrastructure and Network Variables in SSA
VariableElectrical power

Electrical Power

1.000(.000)
Main Telephone 0.641(.002)
Internet use/capital 0.599(.000)
Internet
0.838(.000)
PC use/capita.329(.091)

Main telephone

Internet use

Internet Hosts

PC use0.641(.002)
1.000(.000)
0.965(.000)
0.947(.000)
0.826(.000)

0.599(.004)
0.965(.000)
1.000(.000)
0.902(.000)
0.709(.073)

0.838(.000)
0.947(.000)
0.902(.000)
1.000(.000)
0.727(.000)

0.329(.091)
0.826(.000)
0.709(.000)
0.729(.000)
1.000(.000)** .01 level of significance (2-tailed)* .05 level of significance (2-tailed).

The results also show that investments in telecommunication infrastructure and existing telephonedensity are important determinant of Internet hosts that in turn influences use of the Internet. Thesefinding are not surprising and support the findings of earlier studies (Hargittai 1999; Kelly and Petrazzini1997).The study demonstrates the significant role played by economic wealth in stimulating the
diffusion of the Internet. Similar results have been found by almost all the studies that have examined
the predictive role of GDP per capita. The role of economic wealth becomes more relevant in thecase of ICTs because governments need significant investment capital for a reliable and efficient
communication network to experience a faster diffusion of these technologies. National and global
communication network is not possible without sufficient economic wealth. In one of the chapters in
his seminal book, Landes (1999) cited Gerschenkron (1962) proposal on the levels and sources offinance available for backward countries. The countries we explore are economically backward, forwhich Gerschenkron (1962) recommended three levels of investment capital. The three levels are:• a country with lots of private wealth, well funded merchant banks which can financesmall loans• a poorer country with fewer and smaller private fortunes to finance industry through thecreation of investment banks• a poorer country still, where private wealth was not sufficient, and only the state could
provide sufficient finance., (cited in Landes 1999, p.275)
Much of the African LDCs will be hard put to tap into any of these sources for capital. Yet, “You needmoney to make money”, as Landes aptly title the chapter.

29

H OW C AN AFRICA BENEFIT FROM GLOBALIZATION?
Table 8: Economic wealth and other determinants of the Internet use in SSA (2000)
Country

GDP (USD)
at 1995

IU density(per 10,000)

IU
INDEX

IH density(per 10,000)

PC density(per 1,000)

density(1,000Low Income
Ethiopia
115.88Burundi140.70
Sierra Leone
147.39Eritrea
155.05Malawi
168.63
Tanzania
190.49Niger
202.80Guinea-Bissau
209.76
Chad217.84
Rwanda241.77
Madagascar
245.80Burkina Faso
252.05
Nigeria
253.60Mali
287.74
Sudan
319.08Togo
326.61
Kenya
328.20Central African Rcp. 338.57
Uganda347.95

1.58
7.47

0.001
0.009

0.01

0.945
..

3.23

13.05
14.51
32.75
3.73
24.97
3.92
6.47
18.82
8.38
17.57
16.74
9.65
86.41
65.21
4.15
18.01

0.017
0.019
0.044
0.004
0.033
0.005
0.008
0.025
0.011
0.023
0.022
0.012
0.118
0.089
0.005
0.024

0.05
0.01
0.23
0.16
0.17
0.01
0.47
0.34
0.32
0.07
0.08
0.21
0.34
0.53
0.02
0.08

1.608
1.161
2.847
0.466
..
1.341
..
2.195
1.257
6.587
1.157
3.216
21.603
4.891
1.660
2.701

8.09
3.86
4.87
1.86

Gambia, The
ZambiaGhana
Benin
Comoros
Mauritania
AngolaGuineaSenegalZimbabwe
Cote d’Ivoire
Djibouti
Congo, Rep.
Equatorial Guinea
Namibia
BotswanaSouth Africa
Gabon
Mauritius

92.11
19.19
14.84
24.6
21.61
18.87
22.84
10.12
42
37.08
27.05
21.94
1.75
15.45
170.78154.13549.38122.35728.91

0.12
0.86
0.01
0.415
0.58
0.45
0.01
0.25
1.93
2.16
0.41
0.064
0.02
0.13
18.51
14.53
42.95
0.28
27.44

11.514
6.717
2.969
1.640
4.323
9.434
1.142
3.669
16.80011.8676.087
10.1883.492
2.264
34.15736.99161.8059.788
100.539

24.42
9.20
9.93
8.05
10.27
7.17
8.39
8.16
20.71
27.08
17.01
14.09
7.68

1.46
3.43
4.35
3.84
3.36
11.15
9.22
10.88
2.80
2.87

High Income
370.48392.38413.25414.17435.79495.68506.07603.40609.24620.70742.52783.07841.421598.60
2407.60
3951.103985.104378.00
4429.00

0.126
0.026
0.020
0.033
0.029
0.025
0.031
0.013
0.057
0.050
0.036
0.029
0.002
0.020
0.234
0.211
0.754
0.167
1.000

Internet User Index = {X j,i - Min (Xj,i)}/ {Max (Xj,i) - Min (Xj,i)}
Data Source: World Development Indicators, The World Bank (2002), and ITU (2002).
Data for GDP per capita in US Dollars at constant price (at 1995) have been taken from WDI (2002).

68.35
89.93
33.63
32.28
257.85

ATPS SPECIAL PAPER SERIES N O. 17

30

The paper also shows a strong causal relationship between the diffusion of the Internet and telephonedensity. In sum, high levels of GDP, strong presence of Internet hosts, an effective network of telephone
are indispensable to the diffusion of the Internet and by extension to all innovations. However, network
capacity without an educated citizenry may not lead to the required transformation into the network
society. Our study has showed that education is a major factor in development. Internet diffusion iscertainly more pervasive in the relatively high-income category of African countries even if
comparatively these countries are poor relative to other developing countries.
What then should poor countries do to improve access to the Internet and in the end, bridge thedigital inequality? There are two divides in broad terms, the global divide between Africa and theindustrialized countries and the divide within the region. Evidently African countries need greater
investment flows, since huge investments are a prerequisite to building effective communications
networks. African countries have recorded improvements in literacy levels at the primary, secondary
and tertiary levels since after independence. However, they are still far behind the rapidly industrializing
developing countries. Even then, basic literacy is not enough, digital literacy is required and explicit
investment will have to be made by African countries for individuals to become computer literate.
There are other factors that have are significant predictors, such as institutions, telecommunications
regulation, and forms of government. However, the major policy implication that has emerged fromthis paper is that the countries need to reorient their telecommunication and economic policies topromote public and private investments in ICTs that in turn might further boost economic growth(Roller and Waverman 2001). Future studies might consider the role of technological and otherinstitutions that support effective use of the Internet. Further research is needed to examine the roleof such institutions in the diffusion of ICTs in general and the Internet in particular.
Definition of income groups
GDP <= 360 USD
GDP >360 USD

Low income
High income

31

H OW C AN AFRICA BENEFIT FROM GLOBALIZATION?

High Income

Low Income
0.140
0.100

IU Index

IU Index

0.120
0.080
0.060
0.040
0.020
0.000
0

0.2
0.4
Internet Hosts

1.400
1.200
1.000
0.800
0.600
0.400
0.200
0.000

0.6

0

10

20
30
Internet Hosts

40

50

Figure 2: Internet users and hosts in SSA (2000High Income
1.200

0.120
0.100

1.000
IU Index

IU Index

Low Income
0.140

0.080
0.060
0.040
0.020

0.800
0.600
0.400
0.200

0.000

0.000
0

5

10
PC Density

15

20

0

50
100
PC Density

150

Figure 3: Internet users and PC density in SSA (2000)

High Income

Low Income

1.400

0.140

1.200

0.100

IU Index

IU Index

0.120
0.080
0.060

1.000
0.800
0.600

0.040

0.400

0.020

0.200

0.000

0.000
0

5
10
Tele Density

15

Figure 4: Internet users and telephone density in SSA (2000)

0

100
200
Tele Density

300

5.

Conclusion

In this paper we advanced a set of propositions on the exclusion of African countries from thebenefits of globalization. The first is that this development could be explained by the lack of dynamismof the region’s SI, institutions that underlie the adoption, diffusion and adaptation of innovation.
Second, institutions possess path-dependent characteristics influencing the growth rate of per capita
incomes and the proxy for development. Third, we conjecture that these path-dependent variables,
codified loosely into the concept of systems of innovation, have institutional origins that havepersistently impact the evolution of African development. These variables include human capital,
R&D system and industrial capacity. Fourth, we showed that human capital formation represented
by schools enrolment and industrial skills capability acquisition has been inadequate in the newcompetitive global economy. Last, we showed that new kinds of infrastructure represented by ICT
has revolutionized technology and trade exchanges. However, Africa lags far behind other regions in
adopting ICTS and putting in place the necessary infrastructure, such as electrical power to support
their optimal utilization. For these reasons, the nature of the state and its institutions (which are‘carriers of history’) determine whether dynamic or non-dynamic learning systems of innovation
emerge. We suggest that the combined impact of pattern of schools enrollment at the primary,secondary and tertiary levels combined with the commodity-based system of trade, rather thanfactory-based R&D supported system of industry, gave form to the current low technological base of
African industry.
However, considerable work remains to be done in understanding the systemic origin of Africa’s nondynamic innovation systems and research may take several forms. First, we need to understandmore specifically which are the key elements of the system of innovation that are the most influential
and how much they contribute to building the SI. Second, we should understand the nature ofinteractions, not only within the narrow domain specified for firms and industry, but at a wider socioeconomic level. For instance, how to intensify interactions of economic actors to make them more
effective? Third, research should explore the specific ways in which the institutional origins of the SI
influence development and what policies can mitigate the negative impacts that persist. Last, in a
global economy, research and policies must understand the disruptive influences of global agreements
while accommodating latecomer countries in SSA. Global governance institutions have made shortshrift of the challenges facing the region, to paraphrase Stiglitz. African countries face the dilemmaof the imperative integration into a world economy of the 21st Century with states and institutions thathave changed little over time. Institutions developing human capital for industry and the bureaucracyneed to be transformed to fulfill the needs of modernizing economies. The SI approach suggests

32

H OW C AN AFRICA BENEFIT FROM GLOBALIZATION?

33

that the skills and knowledge bases of seemingly unrelated components can be fruitfully brought
together to promote development. Capacities outside the productive firm, for instance, may well be
as crucial for firm growth as the capacities within. As institutions and policies demonstrate persistentcharacteristics, African policy makers need to take a long-term view. Getting the institutions right ismore crucial than getting the prices right.

Appendix
Table A1: SSA Manufacturing Export Performance and Foreign Direct Investment
Countries

AngolaBenin
Botswana
Burkina Faso
BurundiCameroon
Cape Verde
C. African Rep.
Chad
Comoros
DRC
Congo, Rep.
Cote d’Ivoire
E. Guinea
Eritrea
Ethiopia
Gabon
GambiaGhana
GuineaGuinea-Bissau
Kenya
LesothoLiberia
Madagascar
MalawiMali
Mauritania
Mauritius
MayotteMozambique
Namibia

Manufacturing Export% of total export
1998 1999
2000

0.18
6.3

0.3
4.8

0.5

33.8

7.6

8.2

Manufacturing export % of
GDP
1998
1999
2000
6.3
3.2
2.9
8.8
8.9
9.1
4.8
5
5
15.9
13.1
12.2
7.9
8.7
10.7
10.9
10.9
8.9
8.9
9.1
9.4
9
9.3
12.7
12
11.2
4.2
4.2
4.2

19.1

21.4

14.5

7
19.7

5.5
19.9

3.4
18.7

6.8

6.7

9.8

5.2
15.0

20.4

14.7
30.2

23.6

22.2

20.8

14.1
7
4.9
5.7
9
4.4
9.3
11.1
17.5

14.9
7
5.2
5.6
9
4.2
10.2
12.3
16.4

7
4.2
5.3
9
4.2
9.9
13.1
16

13.8
4.3
9.4
24.7

14
4.1
10
24.9

13.8
4
9
24.5

12
12.2

12.2
11.4

12.6

3.4

36.2

72.6

49.8

74.7
10.1

80.8

34

Foreign direct% of GDP
1998
1999
17.3
39.9
1.7
1.7
1.9
0.7
0.4
0.5
0.2
0
0.6
0.4
1.7
2.6
0.5
1.2
0.9
1
0.9
0.4
0.2
3.3
5.3
4.7
4
3.1
3.1
0.7
0.5

2000
19.2
1.4
0.6
0.5
1.7
0.4
1.8
0.5
1

0.2
2.9
13.8
5.6
1.4
-3.6
3.2
0.8
1.8
1.3
0.13
17.9

0.4
1.1
8.9
5.8
0.8
3
3.3
2.1
2.1

0.3

1.6
3.3
0.7
0.8
1.2

2.1
2.7
3.3
0.5
6

5.5

9.6

3.7

29.8
0.5
4
0.7

1
13.1

35

H OW C AN AFRICA BENEFIT FROM GLOBALIZATION?
Countries

Manufacturing Export% of total export
1998 1999
2000

Niger
1.8
Nigeria
2.5
0.6
0.2
RwandaS T. & Principe
Senegal
52.8
56.6
30.4
Seycchelles
Sierra Leone
SomaliaSouth Africa
53.7
55
54.3
Sudan
2.7
Swaziland
Tanzania
21
15.5
Togo
12.2
17.7
30.8
Uganda5.0
3.4
6
ZambiaZimbabwe27
28.1
Source: World development indicators 2002

Manufacturing export % of
GDP
1998
1999
2000

Foreign direct% of GDP
1998
1999

6.2
5.2
13
4.6
16
13.9
3.9

6.5
4.9
12.3
4.5
16.7
14.9
4.3

6.8
4.1
11.5
4.5
17.8
12.5
4.7

0.4
3.3
0.3

2.9
0.1

1.5
9.1
0.7

3.3
9.8
0.1

0.8
2.6
0.8
21.5
2.4
9.1
0.2

19.3
5.2
34.4
7.4
9.4
8.9
13
16.6

18.8
7.7
33.5
7.4
8.6
8.7
12.2
16.6

18.8
8.8
33.1
7.5
9.7
9
12.7
15.8

0.4
3.6
12.5
2
2.1
3.1
6.1
7

1.2
3.7
6.6
2.2
3
3.5
5.3
1.1

0.8
3.4
-3
2.1
2.5
3.6
6.9
1.1

Table A2: Data Sources of Descriptive Statistics
Variables

Source of Data

LOGPCAP
PRI60
PRI70
PRI75
SEC60
SEC70
TERT70TELCAP96

UNDP, Human Development Report, various issues
UNESCO, Statistical Yearbook, various issues
Ditto
Ditto
Ditto
Ditto
Ditto
UNDP, Human Development Report, various issues andWorld Bank 2001, African Development Indicators
Ditto
Ditto
Ditto
Ditto
Ditto
UNESCO, Statistical Yearbook 1999, estimates
Gale Research Group (1998); UNESCO, Statistical
Yearbook 1999; UNESCO, World Science Report 1998.

ELCETCAPROADS96
MVA99
AGL90
ILA90
TECHSUB
RD96

2000

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Other Publications in the ATPS Special Paper SeriesSpecial Paper Series 1
Globalization and Technology: Africa’s Participation and Perspectives: Concept Paper and Research Agenda by Melvin Ayogu &Osita Ogbu (2002)
Special Paper Series 2
Globalization, Markets for Technology and the Relevance of Innovation Policies in Developing
Economies by Sunil Mani (2002)
Special Paper Series 3
Biotechnology in sub-Saharan Africa: Towards a Policy Research Agenda byJohn Mugabe (2000)
Special Paper Series 4
The Impact of Globalization in sub-Saharan Africa Countries by Mwindaace N. Siamwiza (2002)
Special Paper Series 5
A Blueprint for Developing National ICT Policy in Africa by Clement Dzidonu2002
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Impact of Foreign Direct Investment (FDI) on Technology Transfer in Africa by Moses M. Ikiara(2002)
Special Paper Series 7
Pursuing Technology Policy Research in sub-Saharan Africa: Reflections on the Dimensions,Applications and Implications of a Methodological Framework by M.H. Khalil-Tammy (2002)
Special Paper Series 8
African Response to the Information Communication Technology Revolution by G. Olalere Ajayi(2002)
Special Paper Series 9
Information and Communication Technologies (ICTs): Poverty Alleviation and Universal AccessPolicies by Andrew Dymond & Sonja Oestmann (2002)
Special Paper Series 10
ICT Human Resource Development in Africa: Challenges, Strategies and Options by T.M. Waema(2002).
Special Paper Series 11
Applications of ICTs in Africa: Development of Knowledge Workers in Centres of Learning by John

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Special Paper Series 12
State of Science and Technology Capacity in sub-Saharan Africa by Khalil-Timamy (2002).
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Strengthening National Information and Cmmunication Technology Policy in Africa: Governance,
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Special Paper Series 14
A Science Agenda from An Afrian Perspective by Turner T. Isoun
Special Paper Series 15
International Trends in Modern Bio-technology: Entry by and Implications for African Countries byJohn Mugabe
Special Paper Series 16
Foreign Direct Investment (FDI), technology Transfer and Poverty Alleviation: Africa’s Hopes andDilemma by Moses IkiaraBanji Oyelaran-Oyeyinka is a senior researcher and professor of Technology Management at theUnited Nations University/Institute for New Technologies, (UNU/INTECH) Maastricht, The
Netherlands.