SALIENT FEATURES OF TRADE PERFORMANCE
IN EASTERN AND SOUTHERN AFRICA
Africa Region Working Paper Series No.76
October 2004
Abstract
This paper reviews the main trends in growth, direction, and structure of intra- and extra-regional
trade in the eastern and southern Africa (ESA) region and its trading blocks (COMESA, SADC,
SACU and EAC). The region’s trade evolution over the 1990-2001 shows some troubling features.
Unlike other developing countries, the ESA region has increased its marginalization in world trade.
The declining share in world exports reflects export failure in some countries and growth failure in
others. The main impact of such marginalization has been either a slowdown in imports or an
increase in external debt. The share of intra-regional trade in region’s total trade increased only
marginally in all the trading blocks. Furthermore, such increase is concentrated mainly in two
countries: South Africa and Kenya, which have large and growing trade surpluses with other
countries in the region. Intra-regional trade is substantially lower in the ESA region than in other
regional trading blocks. The region’s export composition changed only marginally, unlike other
developing regions, which experienced an increase in manufactured exports. As a result, there has
been little change in the skill and technology intensity of exports in all trading blocks. Exports
remain concentrated in non-fuel primary commodities and resource based and labor-intensive
manufactures. The trading blocks’ exports are generally growing at a lower rate than world exports –
the share of dynamic products in the region is significantly low compared to other developing
countries. ESA’s challenge to reverse its increasing marginalization in world trade is to fully exploit
its comparative advantage in agriculture and minerals through trade facilitation policies while
diversifying also into other exports by gradually increasing the degree of primary good processing
and increasing manufactured exports. Policies to make the export sector competitive and profitable
need to be pursued relentlessly.
The Africa Region Working Paper Series expedites dissemination of applied research and policy studies
with potential for improving economic performance and social conditions in Sub-Saharan Africa. The
series publishes papers at preliminary stages to stimulate timely discussions within the Region and
among client countries, donors, and the policy research community. The editorial board for the series
consists of representatives from professional families appointed by the Region’s Sector Directors. For
additional information, please contact Momar Gueye, (82220), Email: mgueye@worldbank.org or visit
the Web Site: http://www.worldbank.org/afr/wps/index.htm.
The findings, interpretations, and conclusions in this paper are those of the authors. They do not
necessarily represent the views of the World Bank, its Executive Directors, or the countries that
they represent and should not be attributed to them.
AFRICA REGION
WORKING PAPER SERIES NO. 76
SALIENT FEATURES OF
TRADE PERFORMANCE
IN EASTERN AND
SOUTHERN AFRICA
Fahrettin Yagci
Enrique Aldaz-Carroll
October 2004
3
Authors’ Affiliations and Sponsorship
Enrique Aldaz-Carroll,
Young Professional, The World Bank
Email: Ealdazcarroll@worldbank.org
Fahrettin Yagci,
Lead Economist,
Email: Fyagci@worldbank.org
Lawrence E. Hinkle
Lead International Economist, AFTPM
Email: Lhinkle@worldbank.org
We would like to thank all those who provided very useful comments on the paper; particularly
Douglas Addison, Emmanuel Akpa, Manuel de la Rocha, Elwyn Grainger-Jones, Lawrence
Hinkle, Christos Kostopoulos, Lolette Kritzinger- Niekerk, Philippe Le Houerou, Jörg Mayer,
Peter Moll, Matthew Stern, Claire Michele Thirriot, and Jos Verbeek; and Momar Gueye who
provided logistical support.
-4-
TABLE OF CONTENTS
Page
EXECUTIVE SUMMARY ……………………………………………………….
5
INTRODUCTION …………………………………………………………………
9
GROWTH OF TRADE …………………………………………………………….
9
The Share of the Region in World Trade ………………………………….
Is the Region Under-trading? ……………………………………………...
What are the Causes of Marginalization of the Region in World Trade? …
Possible Economic Impact of Region’s Marginalization ……………….…
9
10
12
16
DIRECTION OF TRADE …………………………………………………………
17
STRUCTURAL CHANGE IN TRADE …………………………………………..
20
Change in Composition of Exports ………………………………………
Change in Revealed Comparative Advantage ……………………………..
Change in Skill and Technology Intensity of Exports ……………………
Dynamic Products …………………………………………………………
20
23
23
26
REGION’S TRADE PROSPECTS ………. …………. ..………………….……..
33
REFERENCES ……………………………………………………………………
35
ANNEXES ………………………………………………………………………...
37
Annex 1:
Annex 2:
Annex 3:
Annex 4:
Annex 5:
Annex 6:
Annex 7:
Annex 8:
Data Sources and Methodology ..……………………………...
Membership of Regional Trade Agreements (RIA)…………….
Under-trading and Overtrading of different regions …………
Under-trading and Overtrading of ESA Countries……………
Destination of Exports: Country Data………………………….
Composition of Exports: Country Data ……………………….
Revealed Comparative Advantage: Country Data …………….
Factor Intensity of Exports: Country Data …………………….
38
40
41
42
44
45
46
47
-5EXECUTIVE SUMMARY
i.
This paper reviews the main trends in growth, direction, and structure of intra- and extraregional trade in eastern and southern Africa (ESA) in the 1990-2001 period. It analyzes the main
determinants underlying these trends, examines some broader policy implications, and indicates
areas for further work. In particular, the paper addresses the following questions. What are the
causes of the region’s marginalization in the world economy? How the economies in the region
have reacted to marginalization? How has the direction and composition of trade changed in the
region in this period? Has the intra-regional trade increased and what accounts for such increase?
What is the skill and technology intensity of the region’s exports? What is the share of the region
in the export of dynamic products? How can the region reverse its marginalization in the world
economy?
ii.
The trade data are reviewed for all 25 countries of the region1. The data are aggregated
for the major regional trading blocks such as COMESA, SADC, SACU, EAC, and the
landlocked countries as a group. To simplify the presentation, the discussion in this paper
focuses primarily on broader trends in trade performance of the trading blocks and selected
countries. The annexes provide detailed country-level data that would be particularly useful for
country-level analysis to infer policy recommendations.
iii.
The main findings of the paper are summarized as follows:
a. Marginalization of the region in world trade. The share of the region in world
exports declined from 1.05 percent in 1990-92 to 0.97 percent in 1999-01, indicating
the failure of the region to take advantage of the trade opportunities created by rapid
globalization since the 1980s. The share of the region in world imports also declined
in the same period from 1.13 percent to 1.02 percent. Had the region maintained the
share of world exports it had in the early 1990s, its cumulative exports from 1990 to
2001 would be about $42 billion higher than its actual total exports over the period,
which may be compared to an increase of $43 billion in total external debt of the
region in the same period. The adverse effect of such revenue loss on growth and
poverty in the region is likely to be large. Only five countries in the region
(Botswana, Lesotho, Madagascar, South Africa, and Sudan) managed to increase their
shares in world exports. In the same period, the share of developing countries in
world exports and imports increased from 18.5 percent to 26.8 percent and from 18.7
percent to 25.3 percent, respectively.
b. Causes of marginalization. To understand the main causes of the region’s
marginalization in world trade, the cumulative revenue loss of $42 billion is
decomposed into three components: losses due to price effect (change in region’s
export prices relative to the world average), openness effect (change in region’s
export-to-GDP ratio relative to the world average), and growth effect (growth rate of
1
Angola, Botswana, Burundi, Comoros, Djibouti, DRC, Egypt, Eritreo, Ethiopía, Kenya, Lesotho, Madagascar,
Malawi, Mauritius, Mozambique, Namibia, Rwanda, Seychelles, South Africa, Sudan, Swaziland. Tanzania,
Uganda, Zambia, Zimbabwe. The data sources are given in Annex 1.
-6region’s GDP relative to the world average). The price effect is small and positive in
most countries. The contribution of openness and growth effects to revenue loss is
large and varies widely among countries and trading blocks, indicating that declining
share in world exports reflect export failure in some countries and growth failure in
others. One policy implication of this is that, for a reversal of marginalization, policy
reforms should focus more on trade policies and competitiveness in countries in the
former group and more on broader growth policies and accelerating investment in
countries in the latter group.
c. Impact of marginalization. The main impact of marginalization has been either a
growth slowdown or an increase in external debt depending on whether the countries
reacted to the revenue loss by reducing their imports and/or borrowing more to avoid
a reduction of imports. In the former case, a decline in imports has likely adversely
affected investment, growth and poverty given their strong dependence on foreign
technology and imported inputs, machinery and equipment, and food. In the latter
case, debt dependence has increased substantially as reflected in an increase of total
external debt of the region by $43 billion in this period, leading to heavy debt service
obligations.
d. Direction of trade. The direction of trade changed significantly in all countries. The
share of the EU, the largest trading partner of the region, fell considerably in region’s
exports (from 50.4 percent in the early nineties to 41.5 percent in the late nineties)
despite preferential access to the EU market under the Lome Convention. The EU’s
share in region’s imports also fell from 47.5 percent to 37.6 percent. The share of all
other major trading partners of the region (USA, East Asia, South Asia) as well as the
share of intra-regional trade increased in the same period. Causes and consequences
of these changes need to be further studied because they have implications for trade
policies and regional integration arrangements.
e. Intra-regional trade. The share of intra-regional trade in region’s total trade
increased marginally in all trading blocks. However, the increase concentrated in two
countries: South Africa and Kenya. While these two countries supply a large part of
total intra-regional exports they receive only a small proportion of intra-regional
imports. This asymmetric trend leads to large and growing trade surplus of South
Africa and Kenya with the region, and requires further analysis. In addition, intraregional trade is substantially lower in the ESA region (under 10 percent) compared
to regional trading blocks in other parts of the world. The low intra-block trade
reflects partly limited progress towards trade liberalization, elimination of transport
bottlenecks, and improvement in trade facilitation including customs administration
under regional agreements (World Bank 2000b). It may also be an indication of
limited trade potential among countries in the blocks particularly among the poorer
countries, because they have similar factor endowments and trade similar goods.
f. Alternative approaches to mainstreaming regionalism. Given limited success in
regional integration, the region should consider focusing more on regional
cooperation on joint infrastructure and trade facilitation projects and on policy
harmonization coupled with liberalizing its trade regime among themselves and on an
-7most-favored-nation (MFN) basis rather than moving towards more complex regional
preferential trade arrangements. Creating an economic space where investors can
produce for regional as well as global markets and paying more attention to
multilateral negotiations to influence the trading rules dismantling restrictive trade
practices that inhibit export expansion and diversification may provide small
economies of the region with better growth opportunities than focusing largely on
intraregional trade.
g. Export diversification. The composition of exports changed only marginally in the
region. In all trading blocks, the share of primary goods in total exports has fallen, but
primary goods still constitute almost three-quarters of total exports. There is a wide
difference in export composition between the region and other developing countries.
The share of primary goods in the exports of the ESA group is about twice compared
to the share of other developing countries (62 percent versus 31 percent in 1998-00),
while the share of manufacturing exports is about half compared to other developing
countries (36 percent versus 68 percent in the same period). This reflects that the
revealed comparative advantage of almost all countries in the region is in the primary
goods sector and it has changed little in this period. In addition, exports in most
countries are concentrated in one or two products.
h. Skill and technology mix of exports. The skill and technology intensity of exports is
very similar in all country groupings: exports are concentrated in non-fuel primary
commodities and resource-based and labor-intensive manufactures. These two
groups constitute over 50 percent of total non-fuel exports of all country-groupings.
The data also indicate very little change in factor intensity in the region, and that the
gap between the region and other developing countries is very large and increasing.
For example, the share of products in the top three skill/technology categories in
ESA’s exports increased from 12 to 15 percent from period 1990-92 to 1998-00. In
the same period, the share of the same category of products in other developing
countries increased from 25 to 42 percent.
i. Dynamic products. Dynamic products in world trade are defined as the products that
grow at a rate higher than the average growth rate of world exports. We identified 59
products (of the 225 products at the three-digit level) as dynamic products in world
trade for the 1990-2000 period. They constituted 47 percent of world non-fuel
exports in this period. The share of dynamic products in non-fuel exports in the ESA
region is significantly lower compared to other developing countries and varies
substantially among countries. The analysis show that there are dynamic products
within the group of primary commodities, and the resource-based and labor-intensive
manufactures -- the broad sectors that dominate exports of the ESA region. They
include: precious stones, knitted or crocheted fabrics, furniture, vegetable oil,
beverages, wood manufactures, margarine, food products, glass, spices, toys, paper
products, etc.
iv.
Region’s likely trade trajectory. Region’s resource endowment points to the path that its
trade would likely to follow in the future. As Wood and Mayer (2001) and Wood (2002) argue,
because it is natural resource-abundant, as are the Americas, Africa is likely to follow a
-8development trajectory in the direction of the Americas2. This means, the sectoral structure of an
increasingly prosperous ESA region is more likely to resemble those of Americas with a larger
primary sector and a smaller manufacturing sector than the natural resource-scarce regions of
Asia and Europe. The initial result of capital accumulation in the poor natural resource-abundant
countries in the region will be first strengthening the production of primary products and then
shifting from unprocessed to processed primary products (which are more capital-intensive). As
the capital/natural resource ratio rises to a level high enough, the comparative advantage would
shift from primary production to manufacturing.
v.
Consequently, the policy priorities in the natural resource-abundant countries in the
region will differ in some respects from those of a natural resource-scarce developing countries.
The former countries will need to focus more on applying technology and knowledge to nature,
strengthening government support for regional research and training in the natural resourcebased sectors, stimulating investment in these sectors, improving land-rights, eliminating urban
bias in economic policies, and promoting vigilance against livestock diseases. It is widely
acknowledged that the region has not yet benefited from a technological green revolution and its
accompanying intensification of water and fertilizer use, and the region’s primary sectors are
overly undercapitalized.
vi.
Reversing marginalization of the region in world trade. Given the region’s tiny and
fragmented economies and low per capita income, it is hard to imagine a successful growth drive
based solely on domestic markets. It is necessary therefore to anchor development strategy in
the region in export promotion and diversification to reverse the erosion of region’s share in
world trade. Policies to make the export sector competitive and profitable need to be pursued
relentlessly. The region has potential for sustained growth of exports. While fully exploiting its
comparative advantage in agriculture and minerals, the region needs to diversify into other laborintensive exports, including in agro-processing, manufacturing and services. Some countries in
the region (Mauritius, Botswana, Lesotho, Madagascar, Uganda, etc) have already began to
realize this potential. The challenge now is to sustain this momentum in some countries and to
initiate in others. This requires actions on several fronts, including strengthening the supply
response, providing a stable macroeconomic environment with competitive real exchange rates,
eliminating anti-export bias in the trade regime, and widening economic space through
mainstreaming regionalism in a new way.
2
Their analysis is related to sub-Saharan Africa (SSA) as a whole. Because the economic characteristics of the ESA
region is not significantly different from those of SSA, the analysis would also apply to the ESA region.
-91. INTRODUCTION
1.
This paper examines the evolution of eastern and southern Africa’s (ESA) trade in terms
of its growth, composition, direction, and skill and technology intensity in the 1990-2000
period. It analyzes the main determinants underlying these trends, examines some policy
implications, and highlights areas of further studies. It updates and extends previous
analysis of trade date in a number of areas concentrating on the ESA region. The paper is
prepared as part of a broader study of the causes of poor export performance of the ESA
region providing a quantitative background for the follow up policy analysis of the
regional trading blocks and individual countries studies.
2.
The rest of the paper is structured as follows. Section 2 reviews the main trends in the
growth of region’s trade and examines the main causes and the possible impact of
marginalization of the region in the world economy. Section 3 focuses on the changes in
the direction of trade considering both extra- and intra-regional trade and assesses the
results. Section 4 is devoted to the assessment of the structural change in exports. In
particular, it discusses the changes in the commodity composition, the revealed
comparative advantage, and the skill and technology of exports. It also analyses the share
of dynamic products in region’s exports. The final section reviews the main literature on
Africa’s comparative advantage and the likely trajectory the region’s production and
trade would follow.
2. GROWTH OF TRADE
The share of the region in world trade
3.
The share of the region in world exports declined from 1.05 percent in 1990-92 to 0.97
percent in 1999-01 (Table 1). The region’s share in world imports also declined in the
same period from 1.13 percent to 1.02 percent. This trend is unfavorably compared to
developing countries. In the same period, developing countries managed to increase their
share in both world exports and imports from 18.5 percent to 26.8 percent and from 18.7
percent to 25.3 percent, respectively. The disintegration of the region in world trade
indicates the failure of the region to take advantage of the trade opportunities created by
rapid globalization since the 1980s.
4.
There are important inter-country variations in trade performance in the region. The
share of 13 countries in world exports declined (Burundi, Comoros, DRC, Egypt,
Ethiopia, Kenya, Malawi, Mauritius, Mozambique, Rwanda, Swaziland, Zambia, and
Zimbabwe). Seven countries maintained their shares (Angola, Djibouti, Eritrea,
Namibia, Seychelles, Tanzania, and Uganda). Only five countries in the region managed
to increase their shares in world exports (Botswana, Lesotho, Madagascar, South Africa,
and Sudan).
5.
Regarding the country groupings in the region (see Annex 2 for the country membership
of the country groupings), the share of all groupings in world exports with the exception
of SACU declined. The largest decline took place in the case of landlocked countries (35
percent) followed by COMESA (25 percent). In the case of SACU, three of the five
- 10 members (South Africa, Botswana, and Lesotho) managed to strengthen their integration
with the world market (Table 1).
Table 1: Main Trends in Trade
Growth Rates 1990-2001 (%)
WORLD
Non-African DCs
ESA
COMESA
SADC
EAC
SACU
Landlocked
Rest of Africa
Angola
Botswana
Burundi
Comoros
Congo, D.R.
Djibouti
Egypt
Eritrea
Ethiopia
Kenya
Lesotho
Madagascar
Malawi
Mauritius
Mozambique
Namibia
Rwanda
Seychelles
South Africa
Sudan
Swaziland
Tanzania
Uganda
Zambia
Zimbabwe
Exports
6.44
10.75
5.58
3.16
6.11
5.88
7.80
1.98
4.41
Imports
6.37
9.97
5.43
4.17
5.84
4.60
7.91
1.31
3.29
GDP
3.32
4.66
3.00
5.04
0.67
6.15
0.57
1.42
1.34
6.18
12.93
-8.04
-3.69
-2.93
7.15
1.05
13.54
6.20
5.44
13.93
9.90
1.84
3.80
2.92
6.22
-5.17
8.13
7.83
12.73
-2.42
5.80
8.74
-5.53
1.72
4.00
1.28
-4.19
-2.03
-5.04
3.99
5.12
14.10
0.86
5.36
3.00
9.50
-0.33
5.29
3.63
10.34
-0.17
9.37
8.02
2.65
3.65
2.00
7.70
0.57
0.67
-0.03
3.11
-4.64
-1.73
-7.29
2.38
9.97
5.69
1.04
4.20
2.42
3.72
-0.22
5.54
6.61
2.46
-0.90
5.69
0.38
1.93
4.61
8.51
7.04
0.35
-0.92
Export to GDP
ratio (%)
1990-1992 1999-2001
15.45
19.97
17.98
30.64
15.08
18.65
17.18
14.77
16.80
26.48
12.68
13.28
13.55
24.60
15.81
16.25
30.30
39.83
40.58
7.76
10.42
11.30
19.48
20.47
13.15
0.33
5.10
17.11
9.59
13.63
22.35
45.65
16.79
14.95
7.15
27.33
13.49
4.29
45.18
10.17
5.57
40.52
20.77
80.96
20.12
8.64
10.81
22.76
32.26
6.10
1.89
7.31
21.46
23.65
22.71
26.06
39.34
12.61
21.98
4.13
31.37
24.87
13.14
24.47
8.59
6.10
22.98
25.77
Share in World
Exports (%)
1990-1992 1999-2001
100
100
18.45
26.75
1.05
0.97
0.56
0.42
0.81
0.78
0.06
0.06
0.50
0.55
0.14
0.09
1.62
1.34
0.108
0.009
0.003
0.001
0.049
0.003
0.152
0.000
0.009
0.040
0.002
0.011
0.012
0.035
0.011
0.012
0.004
0.003
0.463
0.013
0.012
0.013
0.006
0.038
0.047
0.108
0.017
0.001
0.000
0.021
0.003
0.095
0.000
0.008
0.037
0.003
0.015
0.008
0.028
0.008
0.012
0.001
0.003
0.507
0.025
0.005
0.013
0.006
0.013
0.031
Share in World
Imports (%)
1990-1992 1999-2001
100
100
18.68
25.30
1.13
1.02
0.71
0.57
0.64
0.59
0.10
0.08
0.37
0.42
0.14
0.09
1.48
1.14
0.05
0.01
0.00
0.00
0.03
0.01
0.34
0.00
0.03
0.05
0.00
0.01
0.02
0.04
0.02
0.00
0.01
0.00
0.36
0.03
0.00
0.03
0.01
0.02
0.04
0.04
0.00
0.00
0.00
0.01
0.01
0.30
0.00
0.02
0.05
0.00
0.01
0.01
0.03
0.02
0.01
0.00
0.01
0.40
0.02
0.00
0.02
0.01
0.01
0.02
Sources and notes can be found in Appendix 1. DCs=developing countries.
6.
Had the region maintained the share of world exports it had in the early 1990s, its
cumulative exports from 1990 to 2001 would be over $41.7 billion (7.3 percent) higher
than its actual total exports in the period. This revenue loss may be compared to the $43
billion increase in the combined foreign debt of the region in the same period. The
largest losers in export revenue are Egypt ($18.8 billion), DRC ($11.4 billion), Zambia
($9.1 billion), Angola ($8.1 billion), and Zimbabwe ($5.2 billion). The adverse impact of
such a large revenue loss on growth and poverty in the region is likely to be substantial.
Is the region under-trading?
7.
There are two competing views to explain why Africa has been marginalized in world
trade. The first view states that Africa has been marginalized because it under-trades; that
- 11 is, it trades below what would be expected by international norms once the income levels
and the size of its economies are taken into account3. The second view maintains that
Africa does not under-trade, and marginalization is explained by the continent’s poor
GDP growth performance4.
8.
The outcome of this debate has important policy implications for the region. If the undertrading hypothesis is confirmed, policy reforms would focus more on trade policy and on
further strengthening competition and opening up of the economies in the region5. If, on
the other hand, the alternative hypothesis is confirmed, the emphasis would be more on
broader economic policies and accelerating investment to achieve economic growth. One
should note however that these sets of policies are not mutually exclusive. What is
emphasized in these hypotheses is the relative weight to be given to various policies.
9.
With the exception of Subramanian and Tamirisa (2001), all earlier studies on the subject
were conducted for Sub-Saharan Africa (SSA) as a whole, overlooking the substantial
regional differences in SSA. Subramanian and Tamirisa disaggregated Africa into the
West and Central (Francophone) Africa and the Eastern and Southern (Anglophone)
Africa and compared their trade with developed and developing countries using a gravity
model for the 1980-97 period. They found that (a) the Francophone Africa was an undertrader and its under-trading was increasing, and (b) the Anglophone Africa was an
average trader but showed signs that it was not keeping pace with global integration.
10.
In this paper, we follow the Subramanian and Tamirisa route and further disaggregate the
Anglophone Africa into COMESA, SADC, EAC, SACU, and landlocked countries to test
the under-trading hypothesis. We used the methodology employed by Rodrik (1999) –
regressing the export-to-GDP ratio against population, land area, per capita income, and
dummies for regional groupings. We ran the regression for the first half and second half
of the 1990s to analyze the changes over time (See Annex 1b for an explanation of the
methodology and Annexes 3 and 4 for the regression results)6.
11.
The results show that 12 of the 22 countries in the sample are under-traders. This group
includes larger countries such as South Africa, Egypt, Sudan, and Mozambique as well as
smaller ones including Comoros, Lesotho, and Rwanda. For most of the under-traders,
the degree of under-trading has declined in the second period. Over-traders also
constitute a mixed group. They include larger countries (Kenya, Namibia), smaller ones
(Swaziland, Malawi), landlocked countries (Zambia, Zimbabwe), and island economies
(Madagascar, Mauritius). Note also that Botswana, Egypt, and Tanzania were overtrading in the first period. Their position changed to under-trading in the second period.
3
Sachs and Warner (1997), IMF (2001).
Foroutan and Pritchett (1993), Rodrik (1997, 1999), Coe and Hoffmaister (1999).
5
World Bank (2000b), Sachs (2000).
6
In each regression, a dummy variable is included for the particular region (or country) to check whether the
estimated coefficient is negative and statistically significant, as it would be if the region (country) were an underformer, or positive and statistically significant, as it would be if the region were an over-performer. Since our sample
covers most of the countries in the world, the regression coefficients are closer to being population values than
sample estimates. Therefore, we will focus on the sign of the coefficients without placing too much importance on
their significance.
4
- 12 Madagascar is the only country whose position changed from under-trading to overtrading7.
12.
Regarding country groupings, COMESA, EAC and landlocked countries under-trade,
while SACU and SADC over-trade.8 The results also show that the ESA group and subSaharan Africa as a whole are under-traders and that the degree of under-trading
increased in the second period. The latter results are broadly consistent with earlier
studies.
What are the causes of marginalization of the region in world trade?
13.
To examine the causes of the region’s marginalization in world trade, we decomposed the
loss of export revenue into its three components: losses due to price effect, openness
effect, and growth effect, defined by the differences between the region’s and the world’s
(a) export prices, (b) export-to-GDP ratios in constant prices, and (c) GDP growth rates,
respectively (see Annex 3 for the description of the methodology).
14.
According to this methodology, there are three possible causes of the region’s loss of
share in world exports: the region’s export prices have increased at a slower rate
compared to the world export prices, the region’s export-to-GDP ratio has increased at a
slower rate compared to the world export-to-GDP ratio, and the region’s GDP growth has
been slower than the growth of world income. The decomposition results are presented in
Table 39.
15.
Table 3 shows that price effect in 14 of the 25 countries in the ESA region is positive,
indicating that export prices in these countries increased faster than the world export
prices during the 1990-2001 (Figure 1). In terms of country groupings, the price effect
was positive for all country groupings with the exception of SACU and Landlocked
Countries indicating a $19 billion gain in export revenue for the ESA group, $20 billion
for COMESA, and $7 billion for SADC (Table 3).
16.
The openness and the growth effects vary widely among the countries and the country
groupings. For example, while the openness effect was negative for Egypt ($54 billion), it
was positive in the case of South Africa ($44 billion). This is explained by a declining
export-to-GDP ratio relative to the world in the case of Egypt, and an increasing exportto-GDP ratio relative to the world in the case of South Africa (Table 1). In contrast, the
growth effect was positive for Egypt ($15 billion), but negative for South Africa ($38
billion). This is a reflection of relative growth rates of GDP: while Egypt’s GDP grew
7
It is beyond the scope of this paper to explain the placing of countries in these groupings. For example,
Botswana’s under-trading in the second period may be explained by a fall-off in diamond sales in the late 1990s.
8
Note that the results for each country group are obtained incorporating a group dummy in the regression. The
group dummy takes value 1 for all its member countries. Consequently, all member countries have the same weight
in determining the coefficient of the group dummy. Group results are therefore not the trade weighted average of
country results. This explains why SACU over-trades in spite of South Africa’s under-trading (three of the five
SACU countries overtrade).
9
Note that the three effects do not add up to total revenue loss because we are reporting only the partial effects of
the three possible causes of marginalization, overlooking their joint effect. As in any non-linear relationship, the sum
of the marginal effect of each variable does not equal to their total effect.
- 13 faster (10.0 percent) compared to the world (3.3 percent), South Africa achieved a lower
growth rate (0.4 percent) in the prescribed period (Table 1).
17.
To recap, during the 1990-2001 period, while Egypt’s GDP grew faster compared to the
world average, its export-to-GDP ratio fell, indicating that the failure to maintain its
openness was the main cause of the loss of its share in world exports. South Africa, on
the other hand, managed to increase its exports-to-GDP ratio but realized very low GDP
growth rate compared to the world average. Therefore, inadequate GDP growth was a
key factor affecting its exports, with causality in both directions (low output reducing
exports and low exports reducing output).
- 14 Table 3. Breakdown of the difference between actual and potential export revenue (1990-2001)
(%)
Billion US $
Difference between actual and
Difference between
Difference Difference Difference
potential export revenue as
actual and potential
attributed attributed to attributed to
a percentage of period's
export revenue
to price
openness
growth
export revenue
over the period
effect
effect
effect
7.30
-41.7
19.1
-20.3
-20.3
ESA
21.81
-58.1
19.5
-66.7
1.7
COMESA
5.68
-25.4
6.9
14.0
-64.8
SADC
4.18
1.5
3.5
-0.7
1.2
EAC
4.96
15.1
-7.5
42.3
-37.7
SACU
27.26
-17.7
-5.5
-7.1
-10.1
Landlocked
South Africa
Sudan
Uganda
Madagascar
Botswana
Lesotho
Ethiopia
Eritrea
Kenya
Djibouti
Tanzania
6.01
18.14
30.41
13.96
14.37
27.35
5.00
88.96
0.34
2.67
0.03
17.2
1.6
1.4
1.1
0.8
0.4
0.3
0.1
0.1
0.0
0.0
-5.9
..
0.2
1.7
-0.8
0.0
1.2
0.0
2.3
..
0.7
44.2
3.2
0.6
1.1
0.9
0.4
1.0
0.1
1.3
0.1
-1.5
-37.9
-2.4
0.9
-0.1
-0.1
0.0
-1.0
0.0
-2.6
-0.1
0.9
Comoros
Seychelles
Burundi
Namibia
Rwanda
Malawi
Mozambique
Mauritius
Swaziland
Zimbabwe
Angola
Zambia
Congo, D.R.
Egypt
88.89
30.57
50.13
12.18
105.82
31.70
50.81
13.54
65.62
22.94
14.78
70.41
65.86
27.11
-0.2
-0.4
-0.6
-0.7
-1.3
-1.7
-2.1
-2.4
-2.6
-5.2
-8.1
-9.1
-11.4
-18.8
-0.1
0.2
-0.6
-0.1
0.2
-0.5
-0.6
0.5
0.6
-4.8
3.9
-3.0
0.8
6.9
-0.1
-0.6
0.0
-0.5
-0.5
-0.3
-2.6
-5.4
-3.3
1.3
14.0
-5.7
-0.2
-53.8
-0.1
0.1
-0.6
-0.2
-0.6
-1.6
0.2
2.0
0.3
-8.0
-35.0
-1.9
-11.2
14.7
Source: See Annex 1.
Note: Potential export revenue= export revenue obtained by the region (or country) had its world market share not changed over the period.
Countries are ordered according to the difference between potential and actual export revenue.
The difference between actual and potential export revenue as a percentage of the period's export revenue was calculated as the ratio
between the difference over the period and the sum of actual export revenue over the period.
An explanation of why the price, openness, and growth effects do not add to the total difference between potential and actual export
revenue over the period can be found in the Annex 1c).
- 15 -
Figure 1
Annual average growth of export prices relative to world export prices, 1990-2001*
-0.15
-0.1
-0.05
0
0.05
0.1
Angola
Rwanda
Congo, Dem. Rep.
Madagascar
COMESA
Ethiopia
Swaziland
Seychelles
Eritrea
Kenya
ECA
Egypt, Arab Rep.
Tanzania
ESA
SADC
Mauritius
Malawi
Namibia
South Africa
SACU
Lesotho
Uganda
Mozambique
Landlocked
Botswana
Zimbabwe
Comoros
Zambia
Burundi
Source: African Development Indicators 2002 and IMF Direction of Trade Statistics 2002.
* Export prices are export unit values. The annual average growth of export prices is the least squares growth rate for the period 1990-2001. The annual average growth of a country's export prices relative to that of the world
is calculated by subtracting the world annual average growth to the country's annual average growth. Due to missing data in Comoros and Congo D.R., the period is shortened in their case to 1990-99 and 1990-97,
respectively. Data for SADC & COMESA export unit values are calculated based on the average export unit values of their member countries weighted by their share in the region's total trade. The value for COMESA was
calculated excluding Comoros, Congo DR, Djibouti, Eritrea and Sudan because they do not report data for the entire 1990-2001 period.
18.
The decomposition and the cross-country regression results help identify the broad causes
of region’s marginalization in world trade. Compared to the world average, the poor
export growth in the case of Egypt and the poor GDP growth in the case of South Africa
seem to be the critical factors explaining the loss of their shares in the world export
market. In other words, its declining share in world exports reflects export failure in the
case of Egypt and growth failure in the case of South Africa. One implication of this
observation is that reforms should focus more on trade policy and further opening up of
the economy in the case of Egypt and more on broader economic policies and
accelerating investment and growth in the case of South Africa.
19.
To understand the possible causes of export failure and growth failure and draw specific
policy conclusions in a country context, this analysis would need to be extended in two
directions. First, the analysis should take into account all other relevant economic,
political, and geographical factors. Second, these quantitative findings need to be linked
to trade and behind the border policies explicitly and the interactions analyzed.
20.
Extending the interpretation of the results to other countries and the country groupings is
straightforward. For example, COMESA and SADC exhibit a pattern similar to Egypt
and South Africa. That is, their declining share in world exports reflect export failure in
the case of COMESA and growth failure in the case of SADC. Note that for the ESA
group as a whole, the openness effect which is negative and very large, is aggravated by
the negative growth effect. Because, the positive price effect is not large enough to offset
the combined negative effects of openness and growth, the ESA group ended up losing an
export revenue of $41.7 billion in the 1990-2001 period.
- 16 -
Possible economic impact of region’s marginalization
21.
The impact of the loss of export revenue on the economies in the region can be traced
through two main channels: a weakening of import capacity and/or an increase in aid and
debt dependence. In other words, a country can react to a loss of export revenue by
reducing its imports and/or borrowing more to avoid a reduction of imports. The data
indicate that the reaction of the countries in the region to the revenue loss varied widely.
22.
The shares of 12 countries in the region in world imports declined during the 1990-2001
period (Table 1). Given their strong dependence on foreign technology and imported
inputs, machinery and equipment, and food, a decline in import capacity has likely
affected investment, growth, and poverty adversely in these countries. The shares of ten
countries in world imports remained constant in this period. Seven of these ten have
experienced a loss in their share in world exports. Maintaining their share in world
imports while losing share in world exports is possible only by higher borrowing and/or
aid indicating increased debt and aid dependence.
23.
A proxy indicator to show whether the debt and aid dependence increased is the change
in the export-to-import ratio (the share of imports financed by export revenue) during the
1990-2001 period. In ten countries, the export-to-import ratio declined over time (Table
4) indicating that imports were reduced less than the fall in export revenue. This, in turn,
implies that import financing by borrowing or aid increased in this period enhancing aid
and debt dependence in these countries. Indeed, the regions total debt in this period
increased from $70 billion to $113 billion. In the case of 15 countries, the export-toimport ratio increased indicating an import reduction more than the fall in export revenue
and a possible fall in the share of aid and borrowing in financing imports. With regard to
country groupings, the export-to-import ratio declined only in COMESA and EAC.
- 17 Table 4: Share of Imports Financed by Export Revenue (%)
1990-92
75
128
89
96
57
123
1999-01
71
127
92
102
65
127
Angola
Botswana
Comoros
Congo, D. R.
Djibouti
Eritrea
Ethiopia
Kenya
Lesotho
Madagascar
Malawi
Namibia
Sudan
Tanzania
Zimbabwe
207
105
30
162
24
29
71
104
96
78
239
36
38
110
290
358
36
194
33
8
42
75
252
100
92
172
102
54
129
Burundi
Egypt
Mauritius
Mozambique
Rwanda
Seychelles
South Africa
Swaziland
Uganda
Zambia
69
43
94
44
77
63
124
633
47
161
46
31
80
39
38
50
122
343
47
90
COMESA
EAC
ESA
Landlocked
SACU
SADEC
Source: IMF Direction of Trade Statistics.
3. DIRECTION OF TRADE
24.
10
The main trend in the direction of trade is that the share of EU, the largest trading partner
of all country groupings, declined in the region’s trade10 (Table 5). For example, the EU’s
share in ESA’s exports fell from 50.4 percent in 1990-92 to 41.5 percent in 1999-01, and
in imports from 47.5 percent to 37.6 percent in the same period. In the case of SACU,
EU’s share in exports fell from 51.8 percent to 42.8 percent, and in imports from 54.8
percent to 42.5 percent. The EU’s share slightly increased only in the exports of
landlocked countries.
Only the analysis of data for the country groupings will be reported in the paper. The country-level data is
presented in the Annex 5.
- 18 -
Table 5: Destination of Exports and Sources of Imports (%)
Exports to
Imports from
1990-92 1999-01 1990-92 1999-01
ESA
SADC
Intra-Region
7.3
9.6
6.8
9.5
Intra-Region
Extra-Region
92.7
90.4
93.2
90.5
Extra-Region
Rest of Africa
0.9
1.7
1.1
1.0
Rest of Africa
USA
14.3
16.1
13.9
11.9
USA
EU
50.4
41.5
47.5
37.6
EU
East Asia & Pacific
13.6
18.6
15.7
19.5
East Asia & Pacific
South Asia
1.8
2.2
1.6
2.5
South Asia
Rest of World
11.7
10.4
13.3
18.0
Rest of World
World
100
100
100
100
World
COMESA
EAC
Intra-Region
4.1
5.2
2.7
3.6
Intra-Region
Extra-Region
95.9
94.8
97.3
96.4
Extra-Region
Rest of Africa
1.5
1.6
1.4
1.0
Rest of Africa
USA
17.6
20.2
13.9
12.7
USA
EU
49.7
40.8
45.0
35.6
EU
East Asia & Pacific
9.8
16.5
14.7
18.0
East Asia & Pacific
South Asia
2.8
2.4
2.2
3.1
South Asia
Rest of World
14.6
13.3
20.1
26.0
Rest of World
World
100
100
100
100
World
SACU
Landlocked
Intra-Region
Intra-Region
Extra-Region
100
100
100
100
Extra-Region
Rest of Africa
USA
EU
East Asia & Pacific
South Asia
Rest of World
World
0.2
10.8
51.8
16.7
0.5
20.0
100
1.8
13.1
42.8
20.2
1.6
20.6
100
0.3
15.8
54.8
16.9
0.3
12.0
100
1.1
12.2
42.5
21.8
1.5
20.9
100
Rest of Africa
USA
EU
East Asia & Pacific
South Asia
Rest of World
World
Exports to
1990-92
1999-01
Imports from
1990-92
1999-01
6.9
93.1
0.4
16.5
49.2
15.4
1.1
7.4
100
8.4
91.6
1.4
17.5
41.1
19.3
1.7
6.7
100
8.5
91.5
0.9
11.8
50.8
16.8
1.1
10.2
100
11.3
88.7
1.3
10.0
38.3
20.4
2.2
16.4
100
7.9
92.1
1.5
5.0
51.9
8.1
7.4
18.1
100
16.2
83.8
1.9
5.3
38.9
8.4
10.7
18.6
100
4.2
95.8
1.0
4.6
44.3
19.5
4.4
22.1
100
9.5
90.5
0.3
8.2
26.8
17.8
6.5
30.8
100
6.5
93.5
6.1
93.9
6.4
93.6
5.8
94.2
0.9
7.3
41.0
24.1
2.5
17.8
100
0.9
9.4
45.5
14.7
1.4
22.1
100
0.3
8.9
39.4
11.0
2.2
31.7
100
0.2
5.0
24.0
11.3
4.3
49.5
100
Source of data: IMF Direction of Trade Statistics.
25.
The share of all other major trading partners in region’s trade increased. Trade with East
Asia and Pacific increased in almost all country groupings except in landlocked
countries’ exports. The share of East Asia and Pacific in ESA’s exports increased from
13.6 percent in 1990-92 to 18.6 percent in 1999-01, and imports from 15.7 percent to
19.5 percent in the same period. East Asia and Pacific replaced the US as the second
largest trading partner of all country groupings except in COMESA’s exports.
26.
The share of intra-regional trade in total trade of the ESA group (both exports and
imports) increased from 1990 to 2001, but it remains very low. The share of intraregional exports in total exports were up from 7.3 percent to 9.6 percent, while the share
of intra-regional imports in total imports increased from 6.8 percent to 9.5 percent.
27.
Intra-regional trade increased in all country groupings in the region with EAC
experiencing the largest increase – from 7.9 percent to 16.2 percent in exports and from
4.2 percent to 9.5 percent in imports.
28.
The increase in intra-regional trade is concentrated in just a few countries. For example,
almost all increase in intra-regional imports was from Kenya in the case of COMESA,
and from South Africa in the case of SADC (Annex 5). Because these two countries do
not import much from the member countries, COMESA’s trade deficit with Kenya, and
SADC’s trade deficit with South Africa increased substantially in this period. South
- 19 Africa supplied 72 percent of total intra-regional exports, but received only 15 percent of
intra-regional imports in 1999-01. Over 30 percent of Kenya’s exports went to other
COMESA members, but Kenya received one percent of intra-COMESA imports in the
same period.
29.
Note that intra-block trade for all country groupings in the ESA region (and within
Africa) is substantially lower compared to other regional integration agreements (RIAs)
among middle income countries as well as RIAs among high income countries. The share
of member country exports that goes to other member countries is 62 percent for the EU,
47 percent for NAFTA, 25 percent for ASEAN, 23 percent for MERCOSUR, 9 percent
for ECOWAS and UEMOA, and 2 percent for EMCCAS11.
30.
Low intra-block trade reflects partly limited progress towards trade liberalization,
elimination of transport bottlenecks, and improvement in trade facilitation including
customs administration (World Bank 2000b). It may also be an indication of limited
trade potential among countries in the blocks, particularly, among the poorer countries,
because they have similar factor endowments and they therefore trade similar goods.
Similar factor endowments of countries does not necessarily mean that they have no
scope for trade. Trade among such countries is of intra-industry nature. The scope for
intra-industry trade varies according to the stage of development. Intra-industry trade is
dominant among industrialized countries in sectors producing technology- and skillintensive manufactures closely integrated through production networks, or consumer
goods for niche markets. Given the preponderance of primary goods in the production
and exports of the countries in the region, the potential for intra-industry trade within the
ESA region seems to be limited. The region has also failed to participate in the fast
growing global production chains, in which several countries complete different stages of
the fabrication of a manufactured good.
31.
When potential trade among neighboring countries is limited, alternative approaches may
be needed to mainstream regionalism12. The region should consider focusing more on
regional cooperation on joint infrastructure and trade facilitation projects and on policy
harmonization coupled with liberalizing its trade regime among themselves and on an
MFN basis rather than moving towards more complex regional preferential trade
arrangements. Creating an economic space where investors can produce for regional as
well as global markets and paying more attention to multilateral negotiations to influence
the rules and to dismantle restrictive trade practices that inhibit export diversification in
poor countries may provide small economies of the region with better growth
opportunities than focusing largely on intraregional trade.
11
12
World Bank (2000a, p.64).
McCarty (1999), World Bank (2000b).
- 20 -
4. STRUCTURAL CHANGE IN TRADE
Change in Composition of Exports
32.
The composition of exports has changed only marginally since 1990 in the region. In all
country groupings, the share of primary goods in total exports has fallen, but primary
goods still constitute almost three-quarters of total exports13. In the case of the ESA
group, the share of primary goods fell from 75.5 percent in 1990-92 to 62.4 percent in
1998-00, while the share of manufacturing increased from 23.5 percent to 36.2 percent
(Table 6). Within manufacturing, textiles and clothing is one of the largest sub-sectors
constituting over 20 percent of total manufacturing exports14. Among the RIAs in the
region SACU is the one with the lowest share of primary goods in total exports (53.5
percent) and the highest share of manufacturing (44.7 percent) reflecting the export
composition of South Africa and Botswana, the two most industrialized countries in the
region.
33.
Compared to other developing countries, exports of all country groupings in the ESA
region are dominated more by primary goods. The share of primary goods in the exports
of the ESA group is about twice compared to the share of other developing countries (62
percent versus 31 percent in 1998-00), while the share of manufacturing exports is about
half compared to other developing countries (36 percent versus 68 percent in the same
period).
34.
Inter-country variation is wide (Annex 6). On the one end, there are small economies
with limited natural resources such as Lesotho, Botswana, and Mauritius where the share
of primary goods is negligible and exports are dominated by one or two manufactures
benefiting from preferential trade arrangements. For example, the share of manufactures
is 99 percent in Lesotho (almost all textiles), and 72 percent in Mauritius (sugar and
textiles). On the other end, there are small and medium size countries where exports are
concentrated in one or two primary products such as Angola (oil), Burundi (coffee),
Malawi (tobacco), Zambia (Copper), and Seychelles (tuna). Export concentration is more
moderate in the medium-size and large countries. The key point coming out of the data is
that the composition of exports in all countries, with the exception of Mozambique, has
moved away from primary goods but only marginally. Mozambique is the only country
where the share of primary goods increased from 62 to 83 percent of total exports. This
is explained by substantial increase in the export of aluminum.
13
Only the analysis of data for the country groupings will be presented in the paper. Country-level data is presented
in the Annex.
14
The data do not reflect the impact of the Africa Growth and Opportunity Act (AGOA) of the US which was
introduced in 2000.
- 21 -
Table 6: Composition of Exports (%)
1990-1992
1998-2000
ESA
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
75.50
18.60
5.85
51.06
23.49
0.68
1.20
5.83
62.43
17.96
4.45
40.02
36.18
0.91
1.41
7.28
COMESA
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
82.16
21.26
4.89
56.01
17.36
0.51
0.12
9.38
72.88
23.20
5.07
44.61
26.27
0.60
0.24
13.64
SADC
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
74.18
16.69
5.15
52.33
24.77
0.62
1.52
4.85
60.50
15.19
3.70
41.61
38.08
0.90
1.68
4.89
SACU
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
68.19
14.06
6.29
47.84
30.19
0.90
2.44
1.92
53.50
12.68
3.58
37.24
44.67
1.18
2.36
2.45
EAC
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
86.27
69.09
14.64
2.54
12.92
2.73
0.34
2.95
87.94
71.37
14.36
2.20
11.34
0.63
0.39
2.79
LANDLOCKED
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
86.22
39.76
4.85
41.61
13.60
0.56
0.14
3.11
78.30
51.14
8.96
18.20
20.94
1.25
0.39
5.60
NON-AFRICAN LDCs
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
48.93
14.47
4.30
30.16
50.12
3.15
1.71
13.32
30.95
9.65
2.49
18.81
67.82
3.25
1.76
12.32
WORLD
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
26.22
9.28
3.06
13.88
72.12
2.08
2.53
6.82
20.55
7.38
2.12
11.06
76.94
1.92
2.30
5.99
Note: Totals do not add up to 100 because the miscellaneous category is not included.
Source: See Appendix 1.
- 22 35.
The degree of export diversification is measured more formally by the Herfindahl index
(A fall in the index over time reflects greater diversification. When exports are evenly
distributed over a large number of products, the index approaches zero). As Table 7
shows, progress in export diversification in all country groupings and individual countries
has been limited since 1990. Concentration has actually increased in the case of Burundi,
DRC, Ethiopia, Mozambique, and Sudan. Export diversification has been largest in the
case of Zambia. The share of cooper in total exports declined from 93 percent to 73
percent in this period with substantial increase in the export of horticulture and
floriculture. This is partly explained by a fall in copper prices.
Table 7: Herfindahl Index of Concentration of Exports
1990-92
1999-01
ESA
0.04
0.03
COMESA
0.17
0.14
SADC
0.05
0.04
EAC
0.13
0.11
SACU
0.07
0.05
Landlocked
0.16
0.10
Angola
0.91
0.81
1
0.50
Botswana
Burundi
0.61
0.64
Comoros
0.51
0.33
Congo, D.R.
0.16
0.36
Djibouti
0.15
0.08
1
0.52
Egypt
1
0.06
Eritrea
2
0.39
0.43
Ethiopia
Kenya
0.15
0.14
1
0.24
Lesotho
Madagascar
0.11
0.08
Malawi
0.55
0.45
Mauritius
0.16
0.12
Mozambique
0.08
0.14
1
0.26
Namibia
Rwanda
0.50
0.41
Seychelles
0.60
0.51
South Africa
0.07
0.05
Sudan
0.28
0.36
1
0.15
Swaziland
Tanzania
0.11
0.10
Uganda
0.56
0.48
Zambia
0.70
0.26
Zimbabwe
0.13
0.12
Source: See Appendix 1.
Note: When a single export product produces all the revenues index=1
When export revenues are evenly distributed over a large number
of products, the index approaches 0.
A fall in the index represents greater diversification.
1
2
Value based on 2000 data.
The value on the third column is the 1995-1997 average.
- 23 -
Change in revealed comparative advantage
36.
This section reviews the change in the revealed comparative advantage (RCA) of all
countries in the region15. This review, together with the analysis of dynamic products in
region’s exports, will provide an important input in the discussion of the prospects for
region’s trade in Section 5.
37.
In terms of broad sectors, the revealed comparative advantage (RCA) of all countries in
the region (except Botswana and Lesotho) and in all country groupings is in the primary
goods category and it has changed very little since 1990 (Table 8 and Annex 7). The
highest RCA is in the fuels, ores and metals sub-sector (an average of 3.62 for the ESA
region). The data also indicate that the region’s RCA in the primary sector has increased
since 1990 (from 2.88 in 1990-92 to 3.04 in 1998-00).
38.
All countries in the ESA region have comparative disadvantage in all manufacturing subsectors with the exception of textiles and clothing (in Egypt, Lesotho, Madagascar,
Malawi, Mauritius, and Swaziland), leather, rubber and footwear (in Djibouti, Eritrea,
Ethiopia, and Sudan), wood and paper products (in South Africa), and iron and steel (in
South Africa). The degree of their disadvantage has fallen since 1990 but only to a
limited extent.
Change in skill and technology intensity of exports
39.
Following UNCTAD (2002), we divided exports, at the three-digit level, into the
following six categories according to their skill and technology intensity16: high skill and
technology manufactures, medium skill and technology manufactures, low skill and
technology manufactures, resource-based and labor intensive manufactures, non-fuel
primary commodities, and others (including fuel).
40.
The results are in line with the region’s factor endowments. The factor intensity of nonfuel exports of all country groupings in 1998-00 is very similar (Table 9): exports are
concentrated in non-fuel primary commodities and resource-based and labor intensive
manufactures (over 50 percent of total non-fuel exports). The share of products with high
and medium skill and technological intensity is very low but slightly higher in SACU
reflecting the influence of South Africa and Namibia.
41.
The data also indicate that the factor intensity of the region’s exports over 1990-2000
changed very little, and that the gap between the region and other developing countries is
very large and increasing. For example, the share of the top three categories of products
in ESA’s exports increased from 12 to 15 percent from period 1990-92 to 1998-00. In the
same period, the share of the same category of products in other developing countries
increased from 25 to 42 percent. Country level data is presented in Annex 8.
15
The RCA of a country in a product is measured as the ratio of that product’s share in the country’s exports to the
share in world exports. If the RCA is higher than one, the country is said to have revealed comparative advantage in
that product relative to the world.
16
UNCTAD (2002).
- 24 Table 8: Revealed Comparative Advantage
1990-1992
1998-2000
ESA
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
2.88
2.00
1.91
3.68
0.33
0.33
0.47
0.85
3.04
2.43
2.10
3.62
0.47
0.48
0.61
1.22
COMESA
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
3.13
2.29
1.60
4.03
0.24
0.24
0.05
1.38
3.55
3.14
2.40
4.03
0.34
0.31
0.11
2.27
SADC
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
2.83
1.80
1.68
3.77
0.34
0.30
0.60
0.71
2.94
2.06
1.75
3.76
0.49
0.47
0.73
0.81
SACU
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
2.60
1.52
2.06
3.45
0.42
0.43
0.96
0.28
2.60
1.72
1.69
3.37
0.58
0.61
1.03
0.41
EAC
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
3.29
7.45
4.78
0.18
0.18
1.32
0.14
0.43
4.28
9.67
6.79
0.20
0.15
0.33
0.17
0.47
LANDLOCKED
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
3.29
4.29
1.58
3.00
0.19
0.27
0.06
0.46
3.81
6.93
4.23
1.65
0.27
0.65
0.17
0.93
1.87
1.56
1.41
2.17
0.69
1.52
0.67
1.95
1.51
1.31
1.18
1.70
0.88
1.70
0.77
2.06
NON-AFRICAN LDCs
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
Source: See Appendix 1.
- 25 Table 9: Factor Intensity of Exports (%)
1990-1992
1998-2000
High manufactures
23.40
29.28
Medium manufactures
24.52
25.40
Low manufactures
6.38
5.77
Labor-intensive manufactures
14.88
13.84
Non-fuel primary commodities
15.66
12.38
Others
15.17
13.32
High manufactures
3.54
4.16
Medium manufactures
1.73
4.85
Low manufactures
6.47
6.02
Labor-intensive manufactures
9.54
15.83
Non-fuel primary commodities
43.20
36.62
Others
35.52
32.53
High manufactures
2.75
2.24
Medium manufactures
0.71
1.33
Low manufactures
2.11
1.90
Labor-intensive manufactures
11.35
19.82
Non-fuel primary commodities
39.24
33.74
Others
43.84
40.97
High manufactures
3.15
4.27
Medium manufactures
1.89
5.51
Low manufactures
7.77
7.10
Labor-intensive manufactures
9.16
15.07
Non-fuel primary commodities
44.77
35.70
Others
33.26
32.35
High manufactures
3.52
2.95
Medium manufactures
1.11
0.99
Low manufactures
0.21
0.24
WORLD
ESA
COMESA
SADC
EAC
Labor-intensive manufactures
7.74
6.64
Non-fuel primary commodities
85.04
87.24
Others
2.38
1.95
High manufactures
4.39
6.41
Medium manufactures
2.63
9.15
Low manufactures
10.13
10.62
Labor-intensive manufactures
8.01
12.17
Non-fuel primary commodities
45.66
38.90
Others
29.18
22.71
High manufactures
0.90
1.23
Medium manufactures
0.75
1.42
Low manufactures
6.72
5.21
Labor-intensive manufactures
4.87
11.94
Non-fuel primary commodities
84.43
76.57
Others
2.33
3.63
SACU
LANDLOCKED COUNTRIES
NON-AFRICAN LDCs
High manufactures
11.97
22.39
Medium manufactures
8.32
14.15
Low manufactures
4.44
5.32
Labor-intensive manufactures
23.40
23.83
Non-fuel primary commodities
23.77
16.50
Others
28.10
17.81
Source: See Appendix 1
Notes: Goods categories are those defined by UNCTAD 1996.
- 26 -
Dynamic products
42.
This section focuses on the dynamic products in world trade and the share of the region’s
exports in these products17. The dynamic products are defined as the products that grow
at a rate higher than the growth of world exports, which was 7 percent in the 1990-2000
period. Of the 225 products at the three-digit level, 59 were identified as dynamic
products for the 1990-2000 period18. The results are presented in the first two columns of
Table 10. The dynamic products constituted 47 percent of world non-fuel exports in this
period.
43.
The dynamic products appear in all six categories of products classified earlier according
to their skill and technology intensity (para 39). Of the 59 dynamic products, nine are in
the non-fuel primary commodities (category A in the third column of Table 10), ten in the
resource-based and labor intensive manufactures (B), seven in the low skill and
technology intensive manufactures (C), 13 in the medium skill and technology
manufactures (D), 18 in the high skill and technology intensive manufactures (E), and
two in the unclassified sectors. Note that as the skill and technology intensity of the
product increases so does the number of dynamic products within each category.
44.
The share of dynamic products in non-fuel exports in the ESA region is significantly
lower, and varies substantially among countries and country groupings. For example, it
is 4.7 percent in Malawi, 20.7 percent in Zambia, 40.8 percent in Mauritius, 41.1 percent
in South Africa, 21.1 percent in the landlocked countries, and 40.9 percent in SACU
(Table 10 and 11).
45.
It is also important to note that there are dynamic products within the primary
commodities and the resource-based and labor intensive manufactures, which dominate
exports of the ESA region. They include: precious stones, knitted or crocheted fabrics,
furniture, vegetable oil, beverages, wood manufactures, margarine, food products, glass,
spices, toys, paper products, etc (Table 10).
17
The methodology used to analyze the dynamic products is the same as the methodology used by Ng and Yeats
(2002), UNCTAD (2002), and Mayer, Butkevicius, Kadri, and Pizarro (2004).
18
They are very similar to those identified by UNCTAD for the period 1980-2000 (UNCTAD 2002).
- 27 -
Table 10: Dynamic Products' growth rates and shares in total non-fuel exports
1
2
1
1
1
1
1
1
2
2
1
1
2
1
2
1
1
1
1
1
2
1
2
2
1
1
1
2
1
1
2
1
2
1
1
1
2
1
2
1
1
1
2
1
1
2
1
1
2
2
1
2
2
1
1
1
1
1
1
28.77
17.20
26.52
23.50
19.92
19.06
14.94
35.12
29.47
21.83
17.27
9.41
9.31
14.43
5.23
22.89
42.25
22.87
20.21
20.92
29.12
20.09
12.92
-1.45
20.36
7.41
19.98
-3.49
20.48
13.56
3.84
139.75
26.00
3.82
16.25
18.60
15.13
2.37
3.97
22.20
11.70
15.59
9.70
8.12
9.59
7.51
40.04
17.06
0.10
9.44
26.71
12.43
18.16
19.54
24.73
7.92
4.07
18.75
26.73
1990
2000
0.008
0.022
0.023
0.056
0.074
0.064
0.082
0.032
0.002
0.104
0.299
0.979
0.085
0.074
13.486
0.024
0.001
0.011
0.008
0.033
0.025
0.125
0.146
1.520
0.105
0.187
0.463
0.098
0.009
0.158
0.009
0.000
0.019
0.064
0.023
0.036
0.009
0.058
0.249
4.156
0.028
0.011
0.139
0.018
0.082
0.119
0.139
0.127
0.053
0.033
0.006
0.068
0.010
0.006
0.028
0.076
1.638
0.004
0.027
0.041
0.065
0.146
0.377
0.176
0.339
0.138
0.331
0.057
0.380
1.123
1.096
0.100
0.175
12.195
0.186
0.016
0.059
0.048
0.094
0.068
0.172
0.279
0.598
0.383
0.332
1.372
0.023
0.055
0.325
0.014
0.084
0.141
0.056
0.089
0.152
0.016
0.065
0.224
13.330
0.057
0.023
0.118
0.024
0.105
0.126
2.284
0.310
0.031
0.036
0.116
0.118
0.028
0.042
0.210
0.168
1.318
0.014
0.089
1
1
1
1
1
1
1
1
1
1
1
1
1
1
2
1
1
1
1
1
1
1
1
2
1
1
1
2
1
1
2
1
1
2
1
1
1
2
2
1
1
1
1
1
1
1
1
1
2
1
1
1
1
1
1
1
2
1
1
19.07
8.56
14.74
4.58
26.45
17.72
10.10
3.64
42.58
3.01
14.51
-8.35
-9.35
6.99
-46.06
10.69
-25.67
9.09
3.99
32.50
80.78
16.10
3.08
3.18
19.60
-6.12
16.39
-3.73
7.59
9.57
-13.66
97.50
10.94
31.64
-2.52
9.14
-6.72
19.47
33.76
16.71
-11.42
52.54
-0.65
-7.09
-22.82
11.33
12.62
-4.77
8.53
-1.05
45.74
-7.31
21.86
15.24
12.90
21.12
-0.61
21.43
-12.50
1990
2000
0.003
0.104
0.029
0.214
0.028
0.027
0.168
0.008
0.001
0.023
0.020
0.242
0.009
0.033
0.080
0.007
0.001
0.006
0.001
0.002
0.000
0.008
0.024
0.128
0.015
0.477
0.018
0.011
0.000
0.184
0.000
0.000
0.003
0.002
0.016
0.099
0.055
0.037
0.000
1.268
0.027
0.000
1.052
0.017
0.027
0.165
0.005
0.380
0.008
0.027
0.002
0.173
0.000
0.002
0.006
0.006
0.018
0.000
0.008
0.009
0.283
0.049
0.270
0.129
0.074
0.168
0.007
0.013
0.054
0.004
0.084
0.003
0.057
0.000
0.026
0.000
0.009
0.002
0.005
0.004
0.024
0.027
0.260
0.120
0.090
0.048
0.006
0.000
0.270
0.000
0.008
0.009
0.022
0.015
0.277
0.013
0.066
0.001
3.214
0.005
0.001
0.601
0.034
0.020
0.202
0.012
0.150
0.030
0.014
0.042
0.081
0.001
0.006
0.017
0.024
0.037
0.005
0.001
Notes: Goods categories: A= Primary commodities, B= Labour-intensive and resource-based manufactures, C= Manufactures with low skill and technology intensity,
D= Manufactures with medium skill and technology intensity, E= Manufactures with high skill and technology intensity & F= Unclassified products.
Product types: 1=positive dynamic, 2=negative dynamic.
Average world growth rate = 7%.
Source: See Appendix 1.
1
1
1
2
1
1
1
2
1
2
1
2
2
2
2
1
2
1
2
1
1
1
2
2
1
2
1
2
1
1
2
1
1
1
2
1
2
1
1
1
2
1
2
2
2
1
1
2
1
2
1
2
1
1
1
1
2
1
2
1990
2000
47.80 0.001 0.018
24.29 0.105 0.438
14.37 0.089 0.187
28.55 0.038 0.403
20.95 0.085 0.194
20.15 0.064 0.301
16.12 0.083 0.134
20.70 0.008 0.096
25.52 0.003 0.024
47.75 0.183 3.244
17.61 0.326 1.252
13.59 0.018 0.110
70.00 0.104 0.112
35.38 0.040 0.273
5.26 16.957 13.731
24.66 0.026 0.205
19.60 0.009 0.016
17.72 0.115 0.282
23.98 0.010 0.045
21.20 0.040 0.106
37.44 0.097 0.614
21.15 0.138 0.190
15.62 0.129 0.292
3.29 0.596 0.306
21.14 0.005 0.056
12.51 0.099 0.328
10.60 0.228 0.263
-3.89 0.094 0.020
20.59 0.010 0.061
13.42 0.178 0.340
8.77 0.011 0.013
98.63 0.000 0.083
26.39 0.024 0.157
4.65 0.079 0.061
17.90 0.026 0.098
18.29 0.045 0.168
7.90 0.005 0.007
3.82 0.062 0.072
4.19 0.290 0.245
21.17 4.231 10.206
17.86 0.015 0.030
14.84 0.013 0.023
9.20 0.034 0.049
9.47 0.016 0.020
19.24 0.030 0.096
4.91 0.096 0.045
40.33 0.172 2.564
35.45 0.002 0.022
24.08 0.030 0.333
10.24 0.035 0.038
25.00 0.008 0.127
8.97 1.292 1.776
18.64 0.013 0.031
7.74 0.149 0.131
24.58 0.035 0.234
7.33 0.094 0.182
23.93 0.014 0.329
23.07 0.002 0.015
10.45 0.060 0.152
1990
2000
1
1
1
1
1
1
1
1
1
1
1
1
1
1
2
1
1
1
1
1
1
1
1
2
1
1
1
2
1
1
1
1
1
2
1
1
1
2
2
1
1
1
1
1
1
2
1
1
1
1
1
1
1
1
1
1
1
1
1
7.32
31.08
24.60
0.09
7.29
25.05
10.70
62.64
14.05
3.36
11.36
17.58
25.17
18.11
-24.18
57.45
10.86
30.84
23.13
36.70
-11.60
-11.86
17.52
3.11
7.78
17.23
20.15
-25.34
8.00
26.53
-7.75
77.70
20.39
18.60
3.14
46.92
6.56
55.74
0.86
9.99
16.22
63.85
37.71
8.24
19.15
-1.73
5.23
13.41
-5.81
20.02
25.81
14.67
-11.54
17.19
20.91
28.48
11.23
2.32
24.75
0.009
0.001
0.001
0.111
0.024
0.038
0.035
0.001
0.000
0.024
0.188
0.143
0.006
0.005
0.109
0.000
0.001
0.001
0.001
0.005
0.046
0.066
0.020
1.884
0.011
0.040
0.066
0.068
0.002
0.014
0.000
0.000
0.000
0.004
0.009
0.001
0.003
0.000
0.051
1.022
0.003
0.000
0.035
0.005
0.049
0.089
0.013
0.106
0.005
0.011
0.002
0.020
0.007
0.009
0.002
0.001
0.209
0.001
0.000
0.016
0.138
0.014
0.116
0.028
0.176
0.114
0.704
0.012
0.038
0.074
0.797
0.002
0.040
0.001
0.027
0.001
0.005
0.063
0.020
0.009
0.019
0.130
1.721
0.053
0.506
0.439
0.004
0.002
0.124
0.019
0.003
0.012
0.014
0.014
0.173
0.008
0.021
0.036
12.021
0.010
0.019
0.413
0.048
0.129
0.019
0.021
0.210
0.003
0.020
0.018
0.077
0.003
0.003
0.018
0.024
2.332
0.001
0.016
Share in total
non-fuel
exports (%)
Product type
0.015
0.117
0.031
0.217
0.051
0.411
0.097
0.229
0.005
0.067
0.149
4.355
0.005
0.085
0.002
0.048
0.004
0.101
0.024
0.017
0.006
0.060
0.111
0.899
0.334
0.853
0.475
0.011
0.019
0.119
0.008
0.244
0.013
0.013
0.050
0.255
0.007
0.034
0.037
11.788
0.287
0.009
1.608
0.057
0.908
0.144
0.165
0.297
0.072
0.206
0.071
0.166
0.002
0.010
0.089
0.081
4.797
0.092
0.010
Share in total
non-fuel exports
(%)
Product type
2000
0.014
0.055
0.015
0.145
0.037
0.058
0.081
0.028
0.000
0.061
0.154
2.338
0.006
0.021
0.046
0.027
0.000
0.009
0.001
0.007
0.018
0.034
0.102
2.054
0.024
0.367
0.106
0.057
0.005
0.070
0.000
0.023
0.003
0.005
0.024
0.024
0.014
0.025
0.020
1.649
0.025
0.001
1.400
0.013
0.375
0.235
0.150
0.218
0.098
0.277
0.001
0.105
0.003
0.004
0.009
0.005
3.305
0.041
0.003
Landlocked
Growth rate (%)
1990
9.46
6.82
17.28
9.52
12.69
23.67
10.59
11.77
-1.50
-0.42
8.98
12.14
6.83
20.85
-12.92
15.48
12.68
32.39
14.04
16.97
-6.30
8.41
4.37
-3.33
31.98
14.62
21.80
-9.47
17.09
12.86
-6.27
24.70
1.09
16.94
8.20
22.07
-1.04
11.36
6.13
22.23
34.35
27.33
1.83
14.09
15.03
2.52
19.09
9.25
0.13
2.42
19.95
7.15
-5.40
28.91
20.01
24.15
7.69
24.90
10.87
Share in total
non-fuel
exports (%)
Product type
0.40
6.08
0.72
4.04
2.87
1.96
4.09
0.74
0.25
1.93
0.07
0.62
0.64
1.74
0.41
0.38
0.06
0.45
0.23
0.78
0.14
1.28
0.95
0.07
1.21
0.86
1.20
0.13
0.08
0.29
0.02
0.07
0.41
0.27
0.57
0.27
0.33
0.64
0.36
1.13
0.36
0.06
0.05
0.21
0.30
1.12
0.72
1.44
0.19
0.13
0.21
0.46
0.14
0.16
0.72
0.44
0.99
0.10
0.16
SACU
Growth rate (%)
2000
Share in total
non-fuel exports
(%)
Growth rate (%)
0.13
2.35
0.38
1.98
1.69
1.19
2.65
0.49
0.22
1.36
0.05
0.45
0.51
1.28
0.30
0.28
0.04
0.34
0.18
0.63
0.12
1.13
0.81
0.07
0.99
0.75
1.03
0.14
0.07
0.25
0.02
0.09
0.37
0.25
0.51
0.24
0.27
0.59
0.32
0.95
0.32
0.06
0.04
0.19
0.27
1.00
0.67
1.34
0.18
0.13
0.20
0.42
0.14
0.16
0.73
0.43
0.92
0.09
0.16
EAC
Product type
18.16
17.25
14.83
14.13
13.50
12.46
12.24
11.76
10.55
10.45
10.39
10.39
10.32
10.23
10.15
10.15
9.96
9.83
9.67
9.51
9.45
9.29
9.21
9.13
9.04
8.74
8.73
8.71
8.69
8.69
8.66
8.61
8.46
8.42
8.42
8.37
8.35
8.26
8.23
8.22
8.16
8.05
8.00
8.00
7.93
7.87
7.85
7.85
7.83
7.82
7.74
7.55
7.53
7.46
7.45
7.34
7.32
7.24
7.22
Share in total
non-fuel
exports (%)
Growth rate (%)
1990
E
E
D
E
E
E
E
D
D
D
A
B
E
D
A
E
E
E
D
E
C
D
C
A
D
D
B
A
A
B
A
A
E
C
D
A
E
E
B
B
C
C
A
B
B
B
D
E
E
E
E
F
D
F
D
B
B
C
C
Share in total
non-fuel
exports (%)
SADC
Product type
Optical instruments and apparatus
Thermionic,cold & photo-cathode val
Electric power machinery and parts
Telecommunications equipment and parts
Parts of and accessories suitable f
Medicinal and pharmaceutical produc
Automatic data processing machines
Equipment for distributing electric
Road motor vehicles,n.e.s.
Electrical machinery and apparatus,
Ores & concentrates of precious met
Under garments,knitted or crocheted
Organo-inorganic and heterocyclic c
Elect.app.such as switches,relays,f
Silver,platinum & oth.metals of the
Perfumery,cosmetics and toilet prep
Meters and counters,n.e.s.
Medical instruments and appliances
Articles of rubber,n.e.s.
Nitrogen-function compounds
Railway vehicles & associated equip
Internal combustion piston engines
Manufactures of base metal,n.e.s.
Miscell.non-ferrous base metals emp
Articles of materials described in
Engines & motors,non-electric
Furniture and parts thereof
Other fixed vegetable oils,fluid or
Non alcoholic beverages,n.e.s.
Wood manufactures,n.e.s.
Margarine and shortening
Rice
Pigments,paints,varnishes & related
Nails,screws,nuts,bolts etc.of iron
Rotating electric plant and parts
Edible products and preparations n.
Photographic apparatus and equipmen
Condensation,polycondensation & pol
Glass
Pearls,precious& semi-prec.stones,u
Sanitary,plumbing,heating,lighting
Iron & steel castings,forgings & st
Spices
Knitted or crocheted fabrics
Made-up articles,wholly/chiefly of
Baby carriages,toys,games and sport
Pumps & compressors,fans & blowers,
Measuring,checking,analysing instru
Optical goods,n.e.s.
Essential oils,perfume and flavour
Soap,cleansing and polishing prepar
Other miscellaneous manufactured articles
Materials of rubber(e.g.,pastes,pla
Office and stationery supplies,n.e.
Heating & cooling equipment and par
Paper and paperboard,cut to size or
Outer garments and other articles,k
Cutlery
Trailers & other vehicles,not motor
Growth rate (%)
871
776
771
764
759
541
752
773
783
778
289
846
515
772
681
553
873
872
628
514
791
713
699
689
893
714
821
424
111
635
091
042
533
694
716
098
881
582
664
667
812
679
075
655
658
894
743
874
884
551
554
899
621
895
741
642
845
696
786
Commodity
Good category
SITC
Rev 2
COMESA
Growth rate (%)
WORLD
Dynamic products
1
1
1
2
1
1
1
1
1
2
1
1
1
1
2
1
1
1
1
1
2
2
1
2
1
1
1
2
1
1
2
1
1
1
2
1
2
1
2
1
1
1
1
1
1
2
2
1
2
1
1
1
2
1
1
1
1
2
1
- 28 -
46.
The dynamic and non-dynamic products are further divided into two types of products
depending on their positive or negative contribution to increasing the region’s share in
world exports. This more detailed categorization helps identify the sectors which may be
targeted by the region to promote exports and reverse its marginalization in world trade
(Figure 2)19. In Figure 2, g Rj is the growth of region R’s exports of commodity j from
1990 to 2000, gWj is the growth of world exports of commodity j, and gW . is the average
growth of world exports of all commodities.
Figure 2: Type of Products in Regional Exports
Positive:
g Rj > gW .
Negative:
gW . > g Rj
Positive:
g Rj > gW .
Negative:
g W . > g Rj
Dynamic product
g Wj > g W .
Types
of
Products
Non-dynamic product
gWj < g W .
47.
19
A positive product (dynamic and non-dynamic) is a product where the region has a
growth rate higher than the average growth rate of world exports. It is labeled “positive”
because its export contributes to an increase in the region’s share in the world market. A
negative product (dynamic and non-dynamic) is a product where the region has a growth
rate lower than the average growth rate of world exports. It is labeled “negative” because
its exports do not increase the region’s share in the world market.
Ng and Yeats (2002).
29
Table 11: Dynamic Products' growth rates and shares in total non-fuel exports for selected countries
1990
2000
1990
2000
1990
2000
1
-17.12
0.000
0.000
2
6.51
0.06
0.04
2
55.88
0.000
0.001
1
37.45
0.004
0.049
1
33.85
0.000
0.003
1
-11.43
0.000
0.002
2
-9.37
0.000
0.000
2
-2.15
0.000
0.000
2
6.61
0.022
0.039
0.019
1
37.93
0.008
0.007
1
-13.42
0.10
0.02
2
24.54
0.002
0.171
1
22.71
0.021
0.058
1
-6.87
0.003
0.007
2
57.49
0.000
0.000
1
37.98
0.000
0.001
1
123.18
0.000
0.000
1
-11.94
0.001
0.002
2
771
Electric power machinery and parts
3.57
0.024
0.024
2
10.83
0.001
0.011
1
-35.65
0.002
0.000
2
-3.33
0.01
0.01
2
76.47
0.000
0.010
1
28.38
0.030
0.189
1
21.85
0.000
0.057
1
18.06
0.056
0.099
1
86.18
0.000
0.048
1
2.10
0.000
0.005
2
11.48
0.002
0.003
1
1
0.468
1
764
5.47
0.319
0.426
2
20.96
0.007
0.022
28.49
0.046
0.048
0.051
2
7.99
0.019
0.045
1
1.61
0.103
0.115
2
0.044
0.221
1
42.90
0.000
0.003
1
-5.65
0.022
0.005
2
-11.99
0.03
0.01
2
10.94
0.003
0.018
1
20.92
0.102
0.226
1
-1.32
0.011
0.004
2
36.09
0.001
0.012
1
11.85
0.005
0.008
1
-2.58
0.011
0.010
2
4.81
0.046
0.051
2
14.87
0.037
0.071
1
-11.62
0.010
0.001
2
134.82
0.000
0.085
1
-25.42
0.08
0.01
2
26.84
0.001
0.009
1
20.00
0.077
0.344
1
18.60
0.028
0.072
1
120.80
0.000
0.055
1
40.52
0.034
0.121
1
32.70
0.002
0.061
1
28.83
0.094
0.291
1
752
Automatic data processing machines
773
Equipment for distributing electric
783
Road motor vehicles,n.e.s.
778
Electrical machinery and apparatus,
7.15
0.037
289
Ores & concentrates of precious met
-22.05
0.005
846
Under garments,knitted or crocheted
-21.92
515
Organo-inorganic and heterocyclic c
-22.65
0.014
0.002
2
20.20
0.000
0.000
1
0.00
0.000
0.000
2
-8.21
0.00
772
Elect.app.such as switches,relays,f
1.38
0.050
0.057
2
71.53
0.014
0.314
1
24.97
0.000
0.001
1
13.26
0.02
681
Silver,platinum & oth.metals of the
10.04
0.010
0.000
1
10.33
0.000
0.000
1
-21.41
0.001
0.000
2
67.65
0.00
0.00
553
Perfumery,cosmetics and toilet prep
2
-11.93
873
Meters and counters,n.e.s.
872
Medical instruments and appliances
628
Articles of rubber,n.e.s.
2
1
6.21
0.155
1
11.02
0.021
0.253
1
19.24
0.010
0.106
1
43.57
0.004
0.109
1
8.42
0.008
0.632
1
2.19
0.081
0.036
2
0.000
2
8.15
0.000
0.000
1
18.50
0.00
0.00
1
11.38
0.002
0.037
1
35.35
0.048
0.319
1
-8.62
0.025
0.078
2
36.13
0.000
0.001
1
23.32
0.004
0.002
1
130.19
0.000
0.797
1
36.50
0.001
0.297
1
1
-34.85
0.000
0.000
2
-3.55
0.00
0.00
2
113.43
0.000
0.051
1
49.35
0.003
0.071
1
-33.43
0.001
0.000
2
136.00
0.000
0.039
1
112.53
0.000
0.012
1
67.32
0.000
0.027
1
10.58
0.001
0.020
0.069
2
-10.74
0.020
0.006
2
-5.98
0.007
0.005
2
-13.07
0.22
0.05
2
-0.61
0.023
0.083
2
24.04
0.126
0.491
1
3.07
0.001
0.028
2
28.81
0.002
0.027
1
30.16
0.000
0.049
1
-2.27
0.002
0.007
2
2.03
0.055
0.043
2
0.000
2
0.00
0.000
0.000
2
3.68
0.000
0.000
2
0.71
0.08
0.05
2
-4.17
0.000
0.000
2
17.61
0.392
1.471
1
0.00
0.000
0.000
2
-3.13
0.036
0.000
2
-6.36
0.058
0.029
2
5.43
0.025
0.106
2
7.97
0.480
0.163
1
8.47
11.86
18.72
1
42.46
0.177
0.460
1
13.87
0.134
0.219
1
34.37
0.000
0.012
1
-3.14
0.804
0.252
2
-47.80
0.013
0.000
2
-35.87
0.004
0.001
2
-5.19
0.356
0.158
2
0.00
2
-29.87
0.066
0.007
2
9.49
0.125
0.132
1
9.35
0.000
0.000
1
13.89
0.000
0.000
1
77.82
0.000
0.015
1
13.17
0.000
0.000
1
5.50
0.015
0.000
0.10
1
34.49
0.003
0.033
1
14.34
0.107
0.219
1
11.23
0.005
0.039
1
25.16
0.011
0.007
1
64.66
0.000
0.157
1
26.81
0.001
0.105
1
2.17
0.012
0.018
2
1
0.00
0.000
0.000
2
5.26
20.405 16.131
2
35.63
0.000
0.000
1
-65.03
0.282
0.000
2
21.29
0.017
0.000
1
-27.26
0.251
0.005
2
-25.56
0.027
0.000
2
0.000
0.019
0.000
0.018
0.000
0.008
1
87.02
0.000
0.009
1
86.52
0.000
0.052
1
6.77
0.012
0.035
2
1
-18.87
2
34.09
0.032
0.239
1
36.07
1
55.84
1
106.72
0.001
0.000
2
-3.29
0.000
0.000
2
22.66
0.000
0.002
1
-7.74
0.00
0.00
2
-12.53
0.019
0.001
2
47.67
0.001
0.020
1
-14.77
0.001
0.000
2
-16.04
0.000
0.001
2
-13.72
0.005
0.000
2
15.99
0.000
0.000
1
6.28
0.000
0.000
2
0.010
0.014
1
-11.55
0.000
0.000
2
5.48
0.001
0.003
2
-5.50
0.04
0.02
2
10.32
0.000
0.001
1
21.17
0.013
0.048
1
20.77
0.002
0.035
1
58.52
0.000
0.003
1
36.33
0.000
0.003
1
36.77
0.000
0.007
1
35.61
0.002
0.008
1
1
39.40
1
-13.08
2
-18.38
2
14.85
1
22.14
0.012
0.053
2
15.62
0.000
0.007
1
11.90
0.000
0.000
1
-12.60
0.000
0.000
2
17.79
0.01
0.00
1
-7.17
0.000
0.000
2
21.05
0.048
0.121
1
25.49
0.000
0.000
1
-7.70
0.007
0.001
2
40.16
0.000
0.004
1
17.43
0.000
0.000
1
9.63
0.013
0.000
1
0.000
0.000
1
2.87
0.000
0.000
2
-5.84
0.000
0.000
2
6.53
0.00
0.00
2
23.35
0.000
0.001
1
34.42
0.024
0.086
1
43.12
0.000
0.006
1
67.41
0.000
0.014
1
0.00
0.000
0.000
2
42.99
0.000
0.011
1
-11.60
0.126
0.022
2
713
Internal combustion piston engines
25.60
0.006
0.037
1
6.44
0.008
0.003
2
1
21.13
0.166
0.223
1
22.45
0.002
0.013
1
3.03
0.017
0.008
2
29.63
0.000
0.007
1
-8.01
0.005
0.005
2
-14.24
0.176
0.041
2
699
Manufactures of base metal,n.e.s.
2.94
0.038
0.038
2
46.32
0.001
0.018
1
22.95
0.001
0.002
1
-3.95
0.06
0.05
2
13.83
0.102
0.065
1
15.50
0.155
0.335
1
6.45
0.021
0.004
2
20.76
0.002
0.008
1
13.75
0.000
0.024
1
9.86
0.018
0.257
1
26.79
0.031
0.196
1
689
Miscell.non-ferrous base metals emp
13.12
0.002
0.004
1
0.00
0.000
0.000
2
-27.87
0.000
0.000
2
34.73
0.00
0.00
1
-33.45
0.006
0.000
2
3.29
0.718
0.359
2
-5.53
0.037
0.019
2
-2.24
0.500
0.398
2
112.80
0.000
0.960
1
2.69
4.816
14.052
2
13.97
0.005
0.015
1
893
Articles of materials described in
10.96
0.022
0.049
1
14.75
0.026
0.021
1
37.75
0.001
0.019
1
19.12
0.03
0.09
1
38.31
0.004
0.015
1
20.57
0.153
0.475
1
9.68
0.001
0.015
1
71.70
0.005
0.304
1
34.68
0.000
0.029
1
42.65
0.001
0.016
1
5.77
0.026
0.111
2
714
Engines & motors,non-electric
2.80
0.278
0.158
2
-29.94
0.041
0.001
2
-45.13
0.030
0.000
2
19.48
0.00
0.23
1
120.95
0.000
0.359
1
12.39
0.119
0.377
1
-7.77
0.783
0.773
2
-29.72
1.206
0.004
2
-12.79
0.007
0.001
2
-22.60
0.021
0.847
2
6.32
0.067
0.110
2
0.00
0.01
1
46.75
43.58
0.000
0.091
0.002
0.014
1
23.95
0.002
0.000
0.000
0.000
1
31.57
0.001
0.003
1
20.01
0.002
0.165
1
Furniture and parts thereof
1
20.46
1
12.29
0.042
0.032
1
14.94
0.02
0.06
1
10.67
0.006
0.047
1
1.734
1
-33.79
0.006
0.000
2
13.82
0.013
0.042
1
6.60
0.003
0.005
2
27.26
0.002
0.007
1
19.35
0.167
0.968
1
Other fixed vegetable oils,fluid or
-7.59
0.017
0.010
2
-21.69
0.359
0.021
2
-12.53
0.000
0.000
2
-38.58
0.00
0.00
2
55.06
0.143
0.267
1
-3.90
0.113
0.023
2
0.00
0.000
0.000
2
40.44
0.000
0.000
1
15.35
0.000
0.000
1
-11.88
0.014
0.000
2
-38.12
0.172
0.010
2
Non alcoholic beverages,n.e.s.
-11.06
0.001
0.000
2
0.71
0.000
0.000
2
-2.89
0.000
0.000
2
95.28
0.00
0.01
1
47.39
0.000
0.000
1
20.42
0.012
0.070
1
38.12
0.000
0.001
1
25.46
0.000
0.001
1
21.52
0.000
0.000
1
0.22
0.000
0.000
2
14.81
0.007
0.003
1
1
2
-8.76
13.70
0.065
0.159
1
48.85
0.000
0.006
1
10.77
0.005
0.036
1
33.28
0.016
0.297
091
Margarine and shortening
-13.66
0.000
0.000
2
0.00
0.000
0.000
2
0.63
0.000
0.000
2
-14.73
0.00
0.00
2
11.33
0.000
0.000
1
8.76
0.013
0.015
1
0.00
0.000
0.000
2
0.00
0.000
0.000
2
0.00
0.000
0.000
2
0.00
0.000
0.000
2
-7.75
0.000
0.053
042
Rice
-20.19
0.000
0.000
2
124.08
0.000
0.020
1
29.73
0.000
0.000
1
21.98
0.00
0.00
1
212.10
0.000
1.074
1
92.32
0.000
0.097
1
24.03
0.000
0.000
1
133.69
0.000
0.011
1
74.12
0.000
0.035
1
0.00
0.000
0.000
2
3.34
0.000
0.000
2
533
Pigments,paints,varnishes & related
13.18
0.003
0.014
1
17.35
0.000
0.001
1
-6.67
0.000
0.000
2
14.53
0.00
0.00
1
4.31
0.000
0.000
2
26.39
0.028
0.184
1
22.64
0.000
0.033
1
8.41
0.004
0.005
1
17.03
0.000
0.000
1
5.90
0.000
0.003
2
42.92
0.000
0.027
1
694
0.274
0.397
1
28.07
0.089
0.225
1
5.55
0.048
0.061
0.14
0.04
2
51.70
0.004
0.310
1
13.40
0.680
0.003
111
8.93
20.04
0.000
424
Wood manufactures,n.e.s.
0.096
22.61
1
821
635
0.101
2
0.00
24.63
64.19
0.001
0.00
1
17.75
0.001
0.000
0.002
Nitrogen-function compounds
-8.26
0.001
0.000
Railway vehicles & associated equip
0.062
0.000
0.01
791
0.024
0.004
0.04
514
17.49
0.004
0.000
2
8.73
0.001
0.002
1
-21.38
2.72
0.002
0.100
0.093
0.000
0.001
16.06
0.216
0.000
19.29
1
-6.69
0.000
1
0.108
2
5.90
1.971
0.001
0.063
11.16
0.116
38.12
0.011
2
36.26
2
0.70
2
1
0.09
-2.16
0.011
4.228
0.11
1
0.000
0.057
0.040
0.185
0.013
71.27
0.005
0.035
0.002
2
18.84
28.09
0.11
0.020
1
1
-20.95
0.058
0.004
0.07
2
26.22
0.007
0.01
2000
Parts of and accessories suitable f
11.32
16.50
1990
Telecommunications equipment and parts
1
2
2000
Medicinal and pharmaceutical produc
0.215
0.033
1990
Share in total
non-fuel
exports (%)
541
0.270
0.196
2000
Share in total
non-fuel exports
(%)
759
8.33
-4.52
1990
Share in total
non-fuel
exports (%)
Product type
2000
0.002
0.006
Share in total
non-fuel exports
(%)
Growth rate (%)
1990
0.000
34.50
Share in total
non-fuel
exports (%)
Product type
2000
36.96
1
Share in total
non-fuel exports
(%)
Product type
1990
1
0.504
Share in total
non-fuel
exports (%)
Growth rate (%)
2000
0.015
0.170
Share in total
non-fuel
exports (%)
Product type
1990
0.004
8.12
Share in total
non-fuel
exports (%)
Growth rate (%)
2000
22.29
Thermionic,cold & photo-cathode val
Share in total
non-fuel exports
(%)
Product type
1990
Optical instruments and apparatus
776
Commodity
Share in total
non-fuel
exports (%)
Growth rate (%)
2000
871
SITC
Rev 2
Growth rate (%)
1990
Product type
ZIMBABWE
Growth rate (%)
ZAMBIA
Product type
UGANDA
Growth rate (%)
TANZANIA
Growth rate (%)
SUDAN
Product type
SOUTH AFRICA
Product type
MOZAMBIQUE
Growth rate (%)
MAURITIUS
Product type
MALAWI
Growth rate (%)
MADAGASCAR
Product type
KENYA
Growth rate (%)
Dynamic products
0.214
0.398
1
-0.31
0.001
0.005
2
Nails,screws,nuts,bolts etc.of iron
31.75
0.004
0.037
1
4.43
0.000
0.000
2
7.35
0.000
0.000
1
35.59
0.00
0.00
1
-34.33
0.003
0.009
2
4.58
0.096
0.071
2
20.32
0.000
0.000
1
1
30.58
716
Rotating electric plant and parts
-4.37
0.019
0.023
2
26.16
0.002
0.003
1
-12.64
0.006
0.001
2
11.64
0.00
0.00
1
36.15
0.003
0.085
1
17.83
0.031
0.113
1
21.57
0.015
0.080
1
6.22
0.012
0.007
2
10.47
0.007
0.001
1
16.57
0.001
0.044
1
-3.16
0.018
0.009
2
098
Edible products and preparations n.
9.08
0.163
0.487
1
1.97
0.004
0.002
2
90.34
0.000
0.015
1
150.18
0.00
0.01
1
11.16
0.005
0.004
1
17.54
0.054
0.171
1
82.65
0.000
0.020
1
38.93
0.000
0.003
1
-3.17
0.000
0.016
2
84.21
0.000
0.011
1
32.60
0.002
0.043
1
881
Photographic apparatus and equipmen
-14.47
0.081
0.009
2
-9.59
0.000
0.000
2
-4.82
0.000
0.000
2
-12.57
0.00
0.00
2
6.80
0.001
0.003
2
19.60
0.011
2
10.06
0.020
0.028
1
71.90
0.000
0.001
1
20.94
0.000
0.008
1
-4.66
0.008
0.014
2
582
Condensation,polycondensation & pol
19.92
0.060
0.117
1
-9.44
0.000
0.000
2
-1.84
0.000
0.000
2
-38.33
0.13
0.00
2
0.02
0.009
0.002
2
3.68
0.075
0.082
2
15.83
0.001
0.009
1
7.91
0.000
0.000
1
18.87
0.000
0.002
1
2.84
0.000
0.000
2
66.64
0.000
0.019
1
664
Glass
55.02
0.000
0.001
1
25.32
0.001
0.000
1
11.29
0.000
0.000
1
38.57
0.00
0.03
1
-35.74
0.362
0.001
2
4.18
0.349
0.288
2
-21.60
0.000
0.000
2
5.94
0.000
0.000
2
11.18
0.000
0.000
1
70.84
0.000
0.000
1
0.50
0.141
0.095
667
Pearls,precious& semi-prec.stones,u
-3.07
1.021
0.533
2
-1.12
1.517
0.543
2
11.66
0.016
0.031
1
25.53
0.32
2.74
1
-17.80
0.082
0.335
2
20.01
5.092
9.713
1
2.85
0.000
0.000
2
29.71
2.535
10.054
1
84.23
0.000
0.006
1
-5.36
2.221
3.172
2
-9.23
0.397
0.191
2
812
Sanitary,plumbing,heating,lighting
12.48
0.003
0.007
1
11.58
0.003
0.020
1
-16.37
0.000
0.000
2
-0.71
0.01
0.00
2
15.97
0.001
0.023
1
12.51
0.038
0.074
1
-13.17
0.003
0.001
2
-37.65
0.097
0.002
2
8.74
0.001
0.000
1
13.80
0.000
0.010
1
16.92
0.007
0.022
1
679
Iron & steel castings,forgings & st
52.18
0.000
0.001
1
79.58
0.000
0.000
1
-7.57
0.000
0.000
2
37.41
0.00
0.00
1
-30.01
0.007
0.002
2
14.82
0.016
24.45
0.000
0.000
1
11.35
0.000
0.000
1
-1.97
0.000
0.000
2
24.38
0.000
0.002
1
62.69
0.001
0.049
1
075
Spices
21.31
0.011
0.056
1
0.44
27.448
18.108
2
11.88
0.249
0.345
1
6.15
0.04
0.05
2
7.67
0.002
0.009
1
9.20
0.041
0.058
1
13.12
0.007
0.349
1
-5.89
4.088
1.514
2
41.14
0.024
0.884
1
29.64
0.011
0.229
1
58.12
0.013
0.778
655
Knitted or crocheted fabrics
0.22
0.020
0.060
2
72.13
0.000
0.004
1
123.98
0.000
0.057
1
2.86
0.05
0.01
2
9.17
0.000
0.001
1
9.45
0.019
0.024
1
13.84
0.000
0.000
1
-55.77
0.019
0.000
2
10.50
0.000
0.000
1
-51.89
0.014
0.000
2
47.66
0.000
0.113
1
658
Made-up articles,wholly/chiefly of
-20.90
0.018
0.017
2
13.62
0.231
0.210
1
137.05
0.001
0.782
1
-16.46
0.66
0.07
2
26.77
0.004
0.034
1
19.23
0.036
0.112
1
53.63
0.124
0.154
1
-30.24
0.063
0.033
2
10.87
0.001
0.003
1
-5.98
0.000
0.008
2
-0.89
0.135
0.154
2
Baby carriages,toys,games and sport
10.64
14.67
0.000
894
0.301
0.235
0.431
2
17.15
1
-36.99
0.005
0.000
1
15.06
0.012
0.023
1
2
1
1
20.11
1
-22.17
0.063
0.006
2
-3.25
0.97
0.48
2
4.03
0.001
0.051
0.131
1
1
20.05
1
13.94
0.000
0.002
1
0.14
0.220
0.028
2
0.002
2
70.18
0.000
0.012
1
16.60
0.014
0.004
1
7.88
0.01
0.01
1
23.15
0.001
0.177
1
40.32
0.207
3.010
1
10.31
0.000
0.017
1
24.34
0.001
0.038
1
20.68
0.000
0.002
1
-21.66
0.019
0.002
2
18.26
0.011
0.028
1
0.209
2
1.51
0.161
0.030
2
-1.46
0.021
0.009
2
34.99
0.04
0.86
1
35.73
0.030
0.466
1
17.71
0.138
0.331
1
-10.67
0.096
0.136
2
5.30
0.220
0.045
2
30.39
0.056
0.132
1
-3.73
0.016
0.028
2
-9.79
0.256
0.064
884
Optical goods,n.e.s.
8.86
0.014
0.050
1
208.10
0.000
0.051
1
-28.72
0.000
0.000
2
-1.30
0.66
0.50
2
8.05
0.001
0.006
1
9.92
0.008
0.010
1
4.99
0.000
0.000
2
13.35
0.000
0.005
1
32.50
0.000
0.003
1
2.82
0.000
0.000
2
-14.58
0.013
0.004
2
551
Essential oils,perfume and flavour
10.17
0.001
0.005
1
8.41
1.541
0.916
1
-27.24
0.001
0.000
2
-2.34
0.02
0.00
2
6.72
0.000
0.000
2
10.07
0.042
0.043
1
60.21
0.000
0.002
1
-0.78
0.106
0.039
2
11.28
0.000
0.001
1
1.82
0.000
0.000
2
14.55
0.029
0.026
1
554
Soap,cleansing and polishing prepar
36.58
0.003
0.041
1
-23.44
0.003
0.002
2
3.56
0.000
0.000
2
145.54
0.00
0.04
1
47.45
0.000
0.013
1
24.99
0.009
0.149
1
94.62
0.000
0.029
1
74.39
0.000
0.001
1
90.69
0.000
0.128
1
49.53
0.000
0.006
1
19.55
0.006
0.020
1
899
Other miscellaneous manufactured articles
-11.74
0.276
0.108
2
29.48
0.134
0.807
1
-4.56
0.003
0.005
2
1.37
0.31
0.29
2
37.69
0.000
0.019
1
15.47
0.065
0.124
1
-8.17
0.000
0.002
2
21.78
0.017
0.063
1
12.63
0.007
0.018
1
10.80
0.002
0.011
1
9.16
0.047
0.039
1
621
Materials of rubber(e.g.,pastes,pla
40.58
0.000
0.001
1
-28.29
0.004
0.003
2
-14.77
0.000
0.000
2
8.40
0.00
0.00
1
34.08
0.000
0.010
1
18.61
0.016
0.036
1
34.70
0.000
0.004
1
1.35
0.000
0.000
2
-1.27
0.002
0.000
2
24.36
0.000
0.000
1
40.85
0.000
0.003
1
895
Office and stationery supplies,n.e.
14.95
0.004
0.010
1
2.37
0.003
0.017
2
2.04
0.000
0.000
2
54.88
0.00
0.01
1
29.37
0.000
0.001
1
20.13
0.006
0.055
1
63.83
0.000
0.000
1
67.67
0.000
0.002
1
21.55
0.000
0.000
1
13.43
0.000
0.000
1
13.07
0.023
0.002
1
62.40
Heating & cooling equipment and par
0.03
0.010
0.026
2
19.95
0.001
0.002
1
59.16
0.000
0.012
1
13.67
0.01
1
143.21
0.002
0.127
1
24.54
0.042
1
10.46
Paper and paperboard,cut to size or
17.58
0.010
0.030
1
22.87
0.013
0.051
1
35.43
0.003
0.034
1
31.93
0.01
0.08
1
-21.79
0.016
0.016
2
7.32
0.113
0.213
1
0.56
0.000
0.003
2
79.62
0.000
0.024
1
18.82
0.000
0.002
1
47.12
0.000
0.000
1
29.02
0.002
0.050
1
845
Outer garments and other articles,k
-1.89
0.030
0.059
2
44.08
0.971
19.513
1
-5.39
1.236
1.163
2
0.57
20.20
15.93
2
-23.25
0.878
0.004
2
14.30
0.222
0.428
1
43.86
0.000
0.001
1
33.48
0.000
0.011
1
14.78
0.000
0.004
1
-19.58
0.004
0.000
2
0.11
0.235
0.168
2
696
Cutlery
21.57
0.000
0.010
1
-3.36
0.001
0.001
2
-10.20
0.000
0.000
2
-24.14
0.00
0.00
2
75.55
0.000
0.017
1
23.04
0.003
0.018
1
3.39
0.000
0.000
2
24.76
0.000
0.000
1
0.00
0.000
0.000
2
-12.26
0.000
0.000
2
-0.76
0.002
0.001
2
786
Trailers & other vehicles,not motor
-18.25
0.013
0.000
2
6.11
0.006
0.000
2
3.37
0.000
0.000
2
38.00
0.00
0.00
1
68.32
0.002
0.087
1
27.52
0.040
0.113
1
6.47
0.000
0.000
2
-0.93
0.001
0.000
2
9.33
0.000
0.001
1
61.57
0.000
0.076
1
25.30
0.001
0.016
1
Product types: 1=positive dynamic, 2=negative dynamic. Average world growth rate = 7%.
0.009
1
83.59
0.000
0.001
1
7.47
0.003
0.002
0.004
0.005
2
642
Source: See Appendix 1.
Notes: Goods categories: A= Primary commodities, B= Labour-intensive and resource-based manufactures, C= Manufactures with low skill and technology intensity, D= Manufactures with medium skill and technology intensity, E= Manufactures with high skill and , B= Labour-intensive and resource-based manufac
0.000
0.000
0.003
0.008
1
0.000
0.000
0.518
0.025
18.32
59.24
-0.01
0.000
1
1
-8.69
50.12
0.112
0.001
Pumps & compressors,fans & blowers,
1
0.004
0.000
Measuring,checking,analysing instru
0.273
0.006
0.004
874
0.00
0.002
0.027
1
0.000
743
741
0.268
0.019
51.52
2
1
30
48.
Note that a positive non-dynamic product may be the result of a surge in the world
demand or in the regional demand for that product that is exported largely by the region,
or it can also emerge when previously competing countries leave a vacuum in the market
in the process of export upgrading that is filled by the region.
49.
Because the export of positive dynamic and positive non-dynamic products contribute to
an increase in the regions’ share in the world market, we will focus particularly on these
products in assessing structural change in exports. Positive dynamic products, which are
labeled ‘1’ in the product type column, are shown in Table 10 for country groupings and
in Table 11 for selected countries. The positive non-dynamic products in COMESA and
SADC exports are listed in Tables 12 and 13, respectively.
50.
In the case of COMESA, of the 59 dynamic products, 38 are positive dynamic and 19 are
negative dynamic; and of the 162 non-dynamic products, 89 are positive non-dynamic
products. Of the positive dynamic products exported by COMESA, four are primary
commodities, eight are resource-based and labor-intensive manufactures, five are
manufactures with low skill and technology intensity, ten are manufactures with medium
skill and technology intensity, and 12 are manufactures with high skill and technology
intensity (Table 10). The product with highest share in total exports in the positive
dynamic category is “pearls, precious and semi-precious stones” (11.8 percent) followed
by “outer garments and other articles” (4.8 percent) and “under garments” (4.4 percent).
51.
In the case of SADC, of the 59 dynamic products, 50 are positive dynamic and 9 are
negative dynamic; and of the 162 non-dynamic products, 99 are positive non-dynamic
products. Of the positive dynamic products exported by SADC, five are primary
commodities, eight are resource-based and labor-intensive manufactures, six are
manufactures with low skill and technology intensity, 13 are manufactures with medium
skill and technology intensity, and 16 are manufactures with high skill and technology
intensity (Table 10). The product with highest share in total exports in the positive
dynamic category is “pearls, precious and semi-precious stones, unworked or worked”
(13.3 percent), followed by “silver, platinum and other metals” (12.2 percent) and
“pumps and compressors, fans and blowers” (2.3 percent).
52.
Note that in world exports as well as exports from COMESA and SADC, the fastest
growing products are those products with higher skill and technological intensity, a result
consistent with the findings of UNCTAD (2002) and Mayer, Butkevicius, Kadri, and
Pizarro (204).
- 31 Table 12. COMESA's positive non-dynamic exports
Share in COMESA's
non-fuel exports (%)
SITC
Description of
COMESA
World
Rev 2
commodity
growth rate (%)
growth rate (%)
1990
2000
524
Radio-active and associated materia
64.49
1.18
0.000
0.456
677
Iron/steel wire,wheth/not coated,bu
49.30
4.50
0.000
0.031
012
Meat & edible offals,salted,in brin
45.81
0.35
0.000
0.002
264
Jute & other textile bast fibres,ne
42.73
-1.37
0.000
0.000
584
Regenerated cellulose;cellulose nit
41.55
2.82
0.000
0.006
725
Paper & pulp mill mach.,mach for ma
41.44
1.48
0.000
0.017
662
Clay construct.materials & refracto
41.38
4.29
0.002
0.054
522
Inorganic chemical elements,oxides
39.14
5.16
0.006
0.469
641
Paper and paperboard
38.99
4.96
0.007
0.118
245
Fuel wood (excluding wood waste) an
29.70
5.29
0.001
0.017
659
29.69
0.71
0.086
0.814
Floor coverings,etc.
223
28.86
5.13
0.016
0.057
Oils seeds and oleaginous fruit, wh
613
Furskins,tanned/dressed,pieces/cutt
28.46
0.73
0.001
0.002
793
28.04
1.56
0.197
0.124
Ships,boats and floating structures
625
27.52
5.91
0.013
0.066
Rubber tyres,tyre cases,etc.for whe
727
Food processing machines and parts
26.10
1.27
0.002
0.010
037
25.24
5.24
0.239
1.657
Fish,crustaceans and molluscs,prepa
656
Tulle,lace,embroidery,ribbons,& oth
23.53
6.08
0.003
0.015
583
22.95
6.87
0.019
0.121
Polymerization and copolymerization
585
Other artificial resins and plastic
22.64
3.45
0.001
0.001
273
21.56
4.41
0.164
0.746
Stone,sand and gravel
282
21.24
3.83
0.043
0.139
Waste and scrap metal of iron or st
411
Animal oils and fats
21.21
3.52
0.004
0.008
112
21.09
5.33
0.012
0.040
Alcoholic beverages
665
19.89
4.45
0.014
0.113
Glassware
941
19.72
7.08
0.049
0.224
Animals,live,n.e.s.,incl. zoo-anima
025
Eggs and yolks,fresh,dried or other
19.47
0.75
0.000
0.007
774
Electric apparatus for medical purp
18.63
6.74
0.006
0.024
266
Synthetic fibres suitable for spinn
18.49
3.14
0.002
0.006
251
Pulp and waste paper
18.49
3.27
0.005
0.211
431
Animal & vegetable oils and fats,pr
18.48
6.19
0.006
0.016
721
Agricultural machinery and parts
18.45
4.77
0.003
0.015
653
18.41
2.27
0.047
0.252
Fabrics,woven,of man-made fibres
212
Furskins,raw (includ.astrakhan,cara
18.10
2.41
0.001
0.019
666
18.03
2.60
0.013
0.056
Pottery
222
16.79
5.26
0.587
1.152
Oil seeds and oleaginous fruit,whol
676
Rails and railway track constructio
16.51
3.29
0.000
0.001
047
Other cereal meals and flours
16.45
2.58
0.002
0.000
742
16.11
6.68
0.015
0.029
Pumps for liquids,liq.elevators and
744
15.49
6.32
0.039
0.087
Mechanical handling equip.and parts
892
15.33
4.49
0.066
0.091
Printed matter
749
15.29
6.98
0.019
0.071
Non-electric parts and accessories
691
15.03
5.26
0.013
0.056
Structures & parts of struc.;iron,s
562
14.03
3.17
0.123
0.745
Fertilizers,manufactured
897
13.96
5.55
0.271
0.491
Jewellery,goldsmiths and other art.
233
Synth.rubb.lat.;synth.rubb.& reclai
13.75
5.40
0.006
0.006
896
13.59
0.75
0.086
0.210
Works of art,collectors pieces & an
842
13.33
5.98
1.383
3.144
Outer garments,men's,of textile fab
036
13.02
4.25
0.563
1.438
Crustaceans and molluscs,fresh,chil
728
12.81
7.09
0.039
0.068
Mach.& equipment specialized for pa
513
Carboxylic acids,& their anhydrides
12.44
6.34
0.007
0.005
722
Tractors fitted or not with power t
12.30
4.29
0.002
0.002
711
Steam & other vapour generating boi
12.12
4.82
0.000
0.001
011
11.99
2.00
0.089
0.627
Meat,edible meat offals, fresh, chi
697
11.93
6.63
0.034
0.106
Household equipment of base metal,n
041
11.85
1.99
0.114
0.001
Wheat (including spelt) and meslin,
692
Metal containers for storage and tr
11.57
4.12
0.008
0.012
736
11.48
5.22
0.038
0.046
Mach.tools for working metal or met
663
11.38
6.30
0.018
0.042
Mineral manufactures,n.e.s
657
11.18
5.77
0.025
0.053
Special textile fabrics and related
287
11.16
1.83
0.641
1.343
Ores and concentrates of base metal
843
11.10
4.70
1.559
2.756
Outer garments,women's,of textile f
572
Explosives and pyrotechnic products
10.70
3.06
0.001
0.003
898
10.66
5.97
0.014
0.022
Musical instruments,parts and acces
057
10.61
3.32
0.694
1.269
Fruit & nuts(not includ. oil nuts),
784
10.49
7.08
0.021
0.046
Parts & accessories of 722--,781--,
035
10.48
2.01
0.055
0.146
Fish,dried,salted or in brine ; smo
693
10.27
3.41
0.015
0.050
Wire products and fencing grills
023
10.19
1.24
0.011
0.000
Butter
056
10.10
2.70
0.216
0.335
Vegetab.,roots & tubers,prepared/pr
763
Gramophones,dictating,sound recorde
10.04
6.46
0.007
0.008
781
9.73
6.92
0.021
0.051
Passenger motor cars,for transport
633
Cork manufactures
9.69
5.76
0.000
0.002
762
Radio-broadcast receivers
9.68
3.95
0.008
0.006
723
9.66
4.78
0.047
0.076
Civil engineering & contractors pla
844
9.63
5.31
1.147
1.717
Under garments of textile fabrics
043
Barley,unmilled
9.58
2.44
0.000
0.000
048
9.38
6.59
0.039
0.054
Cereal prepar. & preps. of flour of
044
9.34
2.35
0.373
0.039
Maize (corn),unmilled
745
Other non-electrical mach.tools,app
9.27
4.95
0.008
0.021
726
9.04
3.47
0.012
0.011
Printing & bookbinding mach.and par
054
8.97
3.47
1.826
2.182
Vegetab.,fresh,chilled,frozen/pres.
511
Hydrocarbons nes,& their halogen.&
8.07
6.75
0.009
0.015
122
8.01
5.11
0.014
0.022
Tobacco manufactured
661
7.88
4.26
0.126
0.259
Lime,cement,and fabricated construc
288
7.69
5.39
0.303
0.535
Non-ferrous base metal waste and sc
695
7.58
6.06
0.027
0.035
Tools for use in hand or in machine
724
7.27
-0.95
0.017
0.051
Textile & leather machinery and par
292
7.26
3.36
2.362
3.110
Crude vegetable materials, n.e.s.
Source: Appendix 1.
Notes: Positive non-dynamic commodities are those where the region's export growth is higher than the growth rate of total world exports.
Growth rate of total world exports = 7%.
Those products in bold have a share in COMESA's non-fuel exports larger than 0.01%.
- 32 Table 13. SADC's positive non-dynamic exports
SITC
Rev 2
264
633
043
762
511
012
781
951
266
572
782
041
122
612
001
112
282
761
737
233
625
727
793
684
722
024
598
584
882
046
591
892
749
785
663
562
742
723
269
692
513
411
784
666
512
656
037
431
744
775
246
745
763
034
661
736
774
265
223
022
659
851
751
592
941
585
523
693
691
531
676
665
728
897
695
516
277
726
842
697
653
292
831
898
583
724
522
677
045
274
048
654
036
222
035
672
245
883
725
Description of
commodity
Jute & other textile bast fibres,ne
Cork manufactures
Barley,unmilled
Radio-broadcast receivers
Hydrocarbons nes,& their halogen.&
Meat & edible offals,salted,in brin
Passenger motor cars,for transport
Armoured fighting vehicles,arms of
Synthetic fibres suitable for spinn
Explosives and pyrotechnic products
Motor vehicles for transport of goo
Wheat (including spelt) and meslin,
Tobacco manufactured
Manufactures of leather/of composit
Live animals chiefly for food
Alcoholic beverages
Waste and scrap metal of iron or st
Television receivers
Metal working machinery and parts
Synth.rubb.lat.;synth.rubb.& reclai
Rubber tyres,tyre cases,etc.for whe
Food processing machines and parts
Ships,boats and floating structures
Aluminium
Tractors fitted or not with power t
Cheese and curd
Miscellaneous chemical products,n.e
Regenerated cellulose;cellulose nit
Photographic & cinematographic supp
Meal and flour of wheat and flour o
Disinfectants,insecticides,fungicid
Printed matter
Non-electric parts and accessories
Motorcycles,motor scooters,invalid
Mineral manufactures,n.e.s
Fertilizers,manufactured
Pumps for liquids,liq.elevators and
Civil engineering & contractors pla
Old clothing and other old textile
Metal containers for storage and tr
Carboxylic acids,& their anhydrides
Animal oils and fats
Parts & accessories of 722--,781--,
Pottery
Alcohols,phenols,phenol-alcohols,&
Tulle,lace,embroidery,ribbons,& oth
Fish,crustaceans and molluscs,prepa
Animal & vegetable oils and fats,pr
Mechanical handling equip.and parts
Household type,elect.& non-electric
Pulpwood (including chips and wood
Other non-electrical mach.tools,app
Gramophones,dictating,sound recorde
Fish,fresh (live or dead),chilled o
Lime,cement,and fabricated construc
Mach.tools for working metal or met
Electric apparatus for medical purp
Vegetable textile fibres and waste
Oils seeds and oleaginous fruit, wh
Milk and cream
Floor coverings,etc.
Footwear
Office machines
Starches,inulin & wheat gluten;albu
Animals,live,n.e.s.,incl. zoo-anima
Other artificial resins and plastic
Other inorganic chemicals
Wire products and fencing grills
Structures & parts of struc.;iron,s
Synth.org.dyestuffs,etc.nat.indigo
Rails and railway track constructio
Glassware
Mach.& equipment specialized for pa
Jewellery,goldsmiths and other art.
Tools for use in hand or in machine
Other organic chemicals
Natural abrasives,n.e.s (incl.indus
Printing & bookbinding mach.and par
Outer garments,men's,of textile fab
Household equipment of base metal,n
Fabrics,woven,of man-made fibres
Crude vegetable materials, n.e.s.
Travel goods,handbags,brief-cases,p
Musical instruments,parts and acces
Polymerization and copolymerization
Textile & leather machinery and par
Inorganic chemical elements,oxides
Iron/steel wire,wheth/not coated,bu
Cereals,unmilled ( no wheat,rice,ba
Sulphur and unroasted iron pyrites
Cereal prepar. & preps. of flour of
Textil.fabrics,woven,oth.than cotto
Crustaceans and molluscs,fresh,chil
Oil seeds and oleaginous fruit,whol
Fish,dried,salted or in brine ; smo
Ingots and other primary forms,of i
Fuel wood (excluding wood waste) an
Cinematograph film,exposed-develope
Paper & pulp mill mach.,mach for ma
SADC
growth rate (%)
World
growth rate (%)
113.40
59.62
59.48
53.51
49.96
48.79
46.29
45.18
43.91
43.74
43.37
42.29
38.41
35.81
34.19
33.97
32.22
32.11
30.79
29.83
29.68
29.28
29.01
28.31
27.14
26.95
26.77
26.59
24.32
24.30
23.48
23.06
22.47
21.94
21.42
21.27
21.08
20.96
20.44
20.19
20.16
20.15
19.62
19.33
19.06
18.97
18.90
18.31
17.98
17.53
17.28
17.13
17.12
16.29
16.16
16.02
15.90
15.83
15.20
14.94
14.64
14.56
14.54
14.50
14.48
13.88
13.85
13.37
12.97
12.82
12.08
12.04
11.64
11.54
11.18
10.47
10.36
10.35
9.96
9.72
9.32
9.25
9.24
9.13
9.08
8.96
8.90
8.77
8.60
8.50
8.46
8.41
8.35
8.26
8.09
7.68
7.61
7.57
7.17
-1.37
5.76
2.44
3.95
6.75
0.35
6.92
-2.66
3.14
3.06
6.27
1.99
5.11
6.05
0.66
5.33
3.83
4.30
5.47
5.40
5.91
1.27
1.56
6.65
4.29
3.11
7.12
2.82
3.43
0.68
5.78
4.49
6.98
6.05
6.30
3.17
6.68
4.78
5.76
4.12
6.34
3.52
7.08
2.60
7.04
6.08
5.24
6.19
6.32
5.73
3.31
4.95
6.46
3.86
4.26
5.22
6.74
4.07
5.13
4.29
0.71
5.13
1.91
6.10
7.08
3.45
4.93
3.41
5.26
2.83
3.29
4.45
7.09
5.55
6.06
6.68
1.58
3.47
5.98
6.63
2.27
3.36
7.05
5.97
6.87
-0.95
5.16
4.50
0.26
-4.25
6.59
0.42
4.25
5.26
2.01
5.27
5.29
0.30
1.48
Share in SADC's
non-fuel exports (%)
1990
2000
0.000
0.000
0.000
0.007
0.032
0.000
0.150
0.000
0.006
0.002
0.040
0.129
0.004
0.007
0.002
0.102
0.030
0.004
0.010
0.016
0.048
0.006
0.170
0.815
0.003
0.000
0.087
0.001
0.003
0.006
0.039
0.032
0.085
0.004
0.023
0.112
0.025
0.038
0.002
0.016
0.017
0.004
0.364
0.003
0.175
0.015
0.186
0.008
0.090
0.015
0.261
0.046
0.007
1.082
0.056
0.054
0.007
0.018
0.015
0.015
0.037
0.022
0.005
0.019
0.032
0.001
0.217
0.055
0.083
0.008
0.003
0.012
0.300
0.242
0.112
0.231
0.175
0.017
0.739
0.043
0.037
0.484
0.043
0.024
0.174
0.030
0.957
0.125
0.012
0.000
0.034
0.010
0.683
0.168
0.039
0.798
0.054
0.004
0.007
Source: Appendix 1.
Notes: Positive non-dynamic commodities are those where the region's export growth is higher than the growth rate of total world exports.
Growth rate of total world exports = 7%.
Those products in bold have a share in SADC's non-fuel exports larger than 0.01%.
0.000
0.005
0.000
0.068
0.421
0.001
2.893
0.085
0.052
0.040
0.462
0.011
0.088
0.048
0.041
0.930
0.322
0.138
0.070
0.046
0.372
0.030
0.560
2.882
0.014
0.015
0.409
0.005
0.016
0.033
0.206
0.306
0.350
0.021
0.113
0.260
0.104
0.164
0.008
0.100
0.036
0.009
1.051
0.017
0.309
0.047
0.579
0.035
0.240
0.083
0.662
0.183
0.019
2.154
0.264
0.070
0.026
0.021
0.022
0.157
0.076
0.137
0.020
0.042
0.069
0.000
0.390
0.130
0.244
0.014
0.015
0.028
0.343
0.292
0.160
0.319
0.035
0.026
0.962
0.100
0.068
0.533
0.041
0.044
0.253
0.048
0.790
0.162
0.075
0.000
0.091
0.014
0.827
0.151
0.054
1.486
0.060
0.007
0.009
- 33 53.
Note that growth rates are sensitive to the initial value of exports – a small increase in
exports of a product which was hardly exported in 1990 would show a very high growth
rate. To avoid this anomaly in calculation of the share of positive-dynamic and positivenon dynamic products, we consider those products with an initial share in total exports
larger than 0.1 percent in 1990. These two types of products increase region’s share in
the world market. The export of positive dynamic products that satisfy this condition
constituted 24 percent of total exports in COMESA and 22 percent in SADC in 2000.
The exports of positive non-dynamic products satisfying this condition constituted 23
percent of total exports in COMESA and 19 percent in SADC.
5. REGION’S TRADE PROSPECTS
54.
This section explores the region’s likely trade trajectory in the long-run by reviewing the
ongoing debate on Africa’s comparative advantage and diversification potential20.
55.
Africa’s likely trade trajectory in the longer run. While it is generally recognized that the
region’s concentration of exports on primary products is caused largely by its factor
endowment (a combination of abundant natural resources and low level of education),
there is no agreement on where the region’s comparative advantage lies, and what
direction the composition of exports would follow in future to support faster growth and
development.
56.
Bloom and Sachs (1998), who argue that Africa’s agriculture suffers from tropical
climate, diseases and pests, claim that its true comparative advantage is in manufactures
and services.
Collier (1998a, 1998b) maintains that with better policies and
infrastructure, the share of manufactured exports in most of Africa could match those of
Asian countries (about 70 percent of total exports) because Africa’s low growth has
reduced wages in the region below those in Asia.
57.
Wood and Mayer (2001) dispute these conclusions. They argue that: (a) the handicaps of
agriculture do not give the region a comparative advantage in manufacturing because
technologies are available for Africa which can overcome most of these obstacles
(technological green revolution and its accompanying intensification of the use of highyielding variety seeds, water, and fertilizer); (b) tropical climates have not prevented the
achievement of far higher levels of agricultural output and exports in much of Latin
America and in Southeast Asia, to which Africa has lost world market shares in tropical
products; (c) manufacturing exports could be realized only in Africa’s coastal regions,
since transport costs in the interior are too high; (d) it is not clear that wages in African
manufacturing are currently lower; (e) comparative advantage depends not on the price of
any single factor, such as labor, but relative factor prices; and, (f) low wages tend to
make a country more competitive in all sectors, not only in manufacturing.
58.
Their own view is that the structure of Africa’s exports may just reflect the region’s
comparative advantage determined largely by the region’s combination of abundant
natural resources and low level of education. Poor policies and infrastructure are a
20
The following debate is related to Sub-Saharan Africa (SSA) as a whole. Because the economic characteristics of
the ESA region is not significantly different from those of SSA, the analysis would also apply to the ESA region.
- 34 second-order influence, rather than the main cause. They argue that Africa’s relative
position in factor endowment has not changed much over the past 30 years, and will
probably not change radically over the next 30 years, either. The implication of this is
that while, in some African countries, the share of manufactures in exports could be
raised by improving infrastructure and policies, for most of Africa, sectors based on
natural resources will continue to dominate exports, following a development path more
like that of land-abundant Americas than of land-scarce Asia. They claim that the longterm model for African development is not Japan but the United States, and that Africa’s
medium-term trajectory should take it in the direction not of East Asian NICs, but of
Latin America.
59.
Wood (2002) shows that, in terms of land/labor ratios, Africa as a region is much more
similar to the Americas than it is to Europe and Asia. He then argues that the higher
land/labor ratio in Africa will cause it to have distinctive sectoral structure at a high level
of development. The sectoral structure of an increasingly prosperous Africa will be more
like those of Americas. Because it is land-abundant, as is America, Africa will always
have a larger primary sector and a smaller manufacturing sector than the land-scarce
regions of Asia and Europe.
60.
He contrasts the differing evolution of sectoral structures in land-abundant and landscarce countries in the process of economic development. The initial result of capital
accumulation in a poor land-abundant country will be mainly a shift from unprocessed to
processed primary products (which are more capital intensive), whereas in a poor landscarce country at this stage the shift will be mainly from unprocessed primary products to
labor-intensive manufactures (which are also more capital intensive, but less landintensive). As capital accumulation proceeds further, both sorts of countries will shift
towards the production of even more capital-intensive manufactures. However, landabundant countries will remain net exporters of primary products for longer than landscarce countries (and perhaps for ever)21.
61.
What are the policy implications of this development trajectory of Africa? Faster
accumulation of capital is vital in the development of every country regardless of their
factor endowment. This will require political and macroeconomic stability, better
institutions, improvements in governance, and increased spending on health, education
and infrastructure. This policy agenda is similar in many respects to those which are
needed to raise living standards in low income land-scarce countries. However, the
policy priorities in the natural resource-abundant countries in the region will differ in
some respects from those of a natural resource-scarce developing countries. The former
countries will need to focus more on applying technology and knowledge to nature. It is
widely acknowledged that Africa has not yet benefited from a technological green
revolution and its accompanying intensification of water and fertilizer use, and policies
and institutions in African agriculture are less favorable than in other regions. Therefore,
in the natural resource-abundant countries of the region, policy priority will need to be
placed on application of new technology and strengthening government support for
regional research and training in the natural resource-based sectors.
21
Wood (2002:7).
- 35 62.
Wood and Mayer (2001) also argue that slow growth in world demand for primary
products is unlikely to constrain the expansion of Africa’s exports for three reasons.
First, Africa’s current share of the world market for all but a few products is so small that
growth of its exports could greatly exceed growth of world demand without much
disruption of other producers. Second, demand for many agricultural products (meat,
seafood, vegetable oils, fruits and vegetables, etc) has grown rapidly, and will continue to
do so, even though demand for traditional agricultural products (tea, coffee, etc) has
grown slowly – note that in our analysis a large number of primary products are
identified as dynamic products. Third, the rapid growth of natural-resource-poor Asian
countries is likely to keep the demand for primary products high.
REFERENCES
Bloom, D. and J. Sachs, “Geography, Demography, and Economic Growth in Africa”, Brookings
Papers in Economic Activity, 1998, No. 2.
Coe, D. and A. W. Hoffmaister. “North-South Trade: Is Africa Unusual? IMF Working Paper
98/94, 1999. Washington, DC: IMF.
Collier, P. “Globalization: Implications for Africa” in Iqbal and Khan (eds), Trade Reform and
Regional Integration in Africa, 1998. Washington, DC: IMF.
Collier, P. Comments, Brookings Papers in Economic Activity, 1998, No. 2.
IMF, World Economic Outlook, May 2001. Washington, DC: IMF.
Mayer, J., A. Butkevicius, A. Kadri, and J. Pizarro. “Dynamic Products in World Exports”,
Review of World Economics, v. 139, No. 4, 2004.
McCarty, C. “Regional Integration in Sub-Saharan Africa: Past, Present, and Future”, in Oyejide,
A. et al, Regional Integration and Trade Liberalization in Sub-Saharan Africa, v. 1-4. London:
Macmillan, 1999.
Oyejide, A. et al, Regional Integration and Trade Liberalization in Sub-Saharan Africa, v. 1-4.
London: Macmillan, 1999.
Ng, F. and A. Yeats, “What Can Africa Expects From Its Traditional Exports?”, Africa Region
Working Paper Series: No. 26, 2002. Washington, DC: World Bank.
Rodrik, D. “Trade Policy and Economic Performance in Sub-Saharan Africa”, 1997. Boston:
Harvard University.
Rodrik, D. The New Global Economy and Developing Countries: Making Openness Work,
1999. Washington DC: Overseas Development Council.
- 36 Sachs, J. “Tropical Underdevelopment”, Paper presented to the Economic History Association,
2000.
Subramanian, A. and N. Tamirisa, “Africa’s Trade Revisited”, IMF Working Paper 01/33, 2001.
Washington, DC: IMF.
UNCTAD, Trade and Development Report, 2002. New York: United Nations.
Wood, A. and J. Mayer, “Africa’s Export Structure in a Comparative Perspective”, Cambridge
Journal of Economics, 2001, v. 25, No. 3.
Wood, A. “Could Africa be Like America?”, World Bank, Annual Bank Conference on
Development Economics, April 2002.
World Bank, Trade Blocks. New York: Oxford University Press, 2000a.
World Bank, Can Africa Claim the 21st Century? Washington, DC, 2000b.
- 37 -
ANNEXES
- 38 Annex 1: Data sources and methodology
(A) Text Figures and Tables
Title
Figure 1
Table 1
Annual
average
growth of
export prices
relative to
world export
prices, 19902001
Source
Notes
African
Development
Indicators 2002
and IMF Direction
of Trade Statistics
2002
Export prices are export unit values. The annual average growth of export prices is the
least squares growth rate for the period 1990-2001. The annual average growth of a
country's export prices relative to those of the world is calculated by subtracting the
world annual average export price growth to the country's annual average export price
growth. Due to missing data in Comoros and Congo D.R., the period is shortened in
their case to 1990-99 and 1990-97, respectively. Data for SADC & COMESA export
unit values are calculated based on the average export unit values of their member
countries weighted by their share in the region's total trade. The value for COMESA
was calculated excluding Comoros, Congo DR, Djibouti, Eritrea and Sudan because
they do not report data for the entire 1990-2001 period.
Trade data: IMF
Direction of Trade
Statistics.
Trade data for SADC and COMESA countries and for Rest of Africa is that reported by
partner countries in the defined world. World is defined as = all countries in IMF
database except Reunion, Aruba, Guadeloupe, Guiana, Martinique and Reunion, which
do not report data. Botswana, Lesotho, Namibia and Swaziland are included in this
world definition. Since these four countries do not report data, a country’s trade with
these 4 countries cannot be estimated with mirror data so it is estimated with data
reported by the own country. South Africa, which is also included in the world
definition, does not report data from 1990 to 1997. Therefore, a country’s trade with
South Africa over that period is estimated with data reported by the own country rather
than by South Africa. Trade data for EAC and SACU is calculated adding the estimated
values of its members. Rest of Africa is constituted by those non-COMESA and nonSADC African countries in the IMF Direction of Trade database, except Reunion
(which does not report data continuously). Trade data for Developing Countries
includes the 152 countries considered by the WDI database as lower-middle-income
economies, low-income economies and upper-middle income economies. Missing
values for one or two years are replaced by estimates based on exponential growth rates.
Unlike other regions, trade data for USA, EU and East & Pacific is reported by the own
region rather than by mirror data due to their better quality data. The World trade values
are calculated based on the values of all countries in the IMF Direction of Trade
Statistics database except Aruba, Guadeloupe, Guiana, Martinique, and Reunion (which
do not report data continuously) plus the trade values for South Africa during 1990-97
reported by her partner countries (South Africa does not report data during that period).
Eritrea gained independence from Ethiopia in 1993. Export, import and GDP data
cannot be estimated before 1994, 1993 and 1992, respectively. The 1994 Eritrean
export to GDP ratio and the 1994 share in world exports replaces the 1990 value.
Ethiopia data before 1993 includes Eritrea.
______________________________________________________________________
Main trends
in trade
_______________
GDP data: World
Bank GDF & WDI
2002.
The countries included in the country groupings are the same as those in trade data.
GDP data for COMESA and SADC is calculated adding the values of its members.
Since GDP data for Eritrea for 1990 & 1991, Congo and Lesotho for 1999, 2000 &
2001, Namibia for 2000, and Uganda for 2001 are not available, they are replaced for
the value of the previous year. GDP data for EAC and SACU is calculated adding the
estimated values of its members. The GDP value for Developing Countries does not
include Liberia, Libya, and Somalia, which do not report data. The world GDP value is
based on the values of the same countries as in the trade calculation except American
Samoa, Bosnia and Herzegovina, Cuba, Faeroe Islands, Greenland, Guam, Iraq, Kyrgyz
Republic, Liberia, Libya, Mongolia, Myanmar, Netherlands Antilles, Korea, Dem. Rep.,
Somalia, and Yugoslavia, which do not report data for more than two years. Missing
values for less than two continuous years are replaced using the exponential growth
rate. Missing values for 1990 were replaced by 1991 values. GDP value for Congo
D.R. in 2000 is based on 1998 value. GDP value for Eritrea in 1990 is based on 1992
value. GDP value for Seychelles in 2001 is based on value for 2000.
- 39 -
Table 2
Table 3
Table 4
Table 5
Regression
results – Is
the region
undertrading?
World Bank GDF
& WDI 2002.
Regions’ undertrading or overtrading is evaluated running cross-country regressions
over all the countries in the world for which data was available: 162 countries in the
1996-2000 period and 148 in the 1990-1994 period. The regressions relate observed
shares of exports in GDP to levels of national income per capita in PPP terms and two
different measures that capture a country’s size: population and land area. The
dependent variable is the log of the average export to GDP ratio over the respective
period. The independent variables are expressed in logs and measured with a lag to
minimize the potential problem of reverse causality: 1989 for the 1990-1994 period and
1995 for the 1996-2000 period. In each regression dummy variables are included for
different regions to check whether the estimated coefficient is negative and statistically
significant, as it would be if the region were an underperformer, or positive and
statistically significant, as it would be if the region were an overperformer. The
regressions were submitted to tests of functional form (RESET test), heterocedasticity
(Brausch-Pagan test) and normality (Shapiro-Wilk test). Since the regressions did not
satisfy the normality test, dummies are included for the largest outliers till the normality
test was satisfied so that the estimated coefficients have the required statistical
properties. In all the regressions French Polynesia and New Caledonia behave as
outliers, as they trade less than what would be predicted by their income per capita and
their size. Seychelles, Congo Dem. Rep. and Ethiopia are not included in the sample for
lack of data. There is no data for Djibouti, Eritrea and Sudan for 1990-1994.
Breakdown
of the
difference
between
actual and
potential
export
revenue
(1990-2001)
Export unit values:
Africa Region
Sima, except for
world price, which
comes from IMF
International
Financial
Statistics.
Exports: Direction
of Trade Statistics,
IMF.
GDP data: World
Bank GDF & WDI
2002.
The cumulative loss as percent of export revenue was calculated as the ratio between
the change in export revenue and the actual cumulative exports for the period. See
Annex 1c) Decomposition of Export Revenue Loss for an explanation of the
methodology used.
Direction of Trade
Statistics, IMF.
The trade data was estimated as in Table 1.
Direction of Trade
Statistics, IMF.
The trade data was estimated based on mirror data reported by the partner countries, as
in Table 1.
Share of
imports
financed by
export
revenue
Destination
of exports
and sources
of imports
Table 6
Composition
of exports
Table 7
Herfindahl
index of
concentration
of exports
Table 8
Revealed
comparative
advantage
Table 9
Factor
intensity of
exports
Table 10
Dynamic
Products'
growth rates
and shares in
total non-fuel
exports
World Integrated
Trade Solution
(COMTRADE
data).
World Integrated
Trade Solution
(COMTRADE
data).
World Integrated
Trade Solution
(COMTRADE
data).
World Integrated
Trade Solution
(COMTRADE
data).
World Integrated
Trade Solution
(COMTRADE
data).
Data reported by the Rest of the World, as defined by Ng and Yeats (2002). Categories
constructed based on 3 digit commodities, SITC Revision 2.
Data reported by the Rest of the World, as defined by Ng and Yeats (2002). Categories
constructed based on 3 digit commodities, SITC Revision 2.
Data reported by the Rest of the World, as defined by Ng and Yeats (2002). Categories
constructed based on 3 digit commodities, SITC Revision 2.
Data reported by the Rest of the World, as defined by Ng and Yeats (2002). Goods
categories are those defined by UNCTAD 1996. Period value based on arithmetic
average. SACU data from 1990 to 1999 is calculated based on trade with South Africa
reported by Rest of the World, which is in fact trade with South Africa and the BLNS
countries. SACU data for 2000 is calculated by aggregating trade with Botswana,
Lesotho, Namibia, Swaziland, and South Africa reported by Rest of the World (the
South Africa 2000 data reported by the Rest of the World only includes trade with
South Africa not with the BLNS countries).
3 digit commodities, SITC Revision 2. Growth rates are calculated as least squares
growth rates.
- 40 -
Table 11
Dynamic
Products'
growth rates
and shares in
total non-fuel
exports for
selected
countries
Table 12
COMESA's
positive nondynamic
exports
Table 13
SADC's
positive nondynamic
exports
World Integrated
Trade Solution
(COMTRADE
data).
World Integrated
Trade Solution
(COMTRADE
data).
World Integrated
Trade Solution
(COMTRADE
data).
3 digit commodities, SITC Revision 2. Growth rates are calculated as least squares
growth rates.
3 digit commodities, SITC Revision 2. Growth rates are calculated as least squares
growth rates.
3 digit commodities, SITC Revision 2. Growth rates are calculated as least squares
growth rates.
(b) Annex Tables
Annex 3
Title
Source
Notes
Undertrading
and
overtrading
of different
regions
World Bank GDF & WDI.
Congo Dem. Rep., Ethiopia, Namibia, and Seychelles are not included
in the regressions for lack of data.
Annex 4
Undertrading
and
overtrading
of ESA
countries
World Bank GDF & WDI.
Annex 5
Destination
of Exports
and Sources
of Imports
IMF Direction of Trade Statistics.
Annex 6
Annex 7
Annex 8
ESA
countries'
export
composition.
Revealed
Comparative
Advantage
Factor
Intensity of
Exports
World Integrated Trade Solution
(COMTRADE data).
World Integrated Trade Solution
(COMTRADE data).
World Integrated Trade Solution
(COMTRADE data).
Each country coefficient is obtained running a regression of the logged
export to GDP ratio over the logged gdp per capita, logged land, a
Latin American dummy, an East Asian and Pacific dummy, and
dummies for three outliers: French Polynesia, New Caledonia and
Japan. Congo Dem. Rep., Ethiopia, Namibia, and Seychelles are not
included in the regressions for lack of data. A positive coefficient
indicates the country is overtrading and a negative coefficient
indicates the country is undertrading.
The data for the country is that reported by the partner countries or
regions. However, since Botswana, Lesotho, Namibia and Swaziland
do not report data, their data is that reported by the country. South
Africa does not report data from 1990 to 1997, so the data is that
reported by the country.
Data reported by the Rest of the World, as defined by Ng and Yeats
(2002). Categories constructed based on 3 digit commodities, SITC
Revision 2.
Data reported by the Rest of the World, as defined by Ng and Yeats
(2002). Categories constructed based on 3 digit commodities, SITC
Revision 2.
Data reported by the Rest of the World, as defined by Ng and Yeats
(2002). Goods categories are those defined by UNCTAD 1996. Period
value based on arithmetic average.
- 41 c) Methodology of Decomposition of Export Revenue Loss
Country i’s share in world exports in year t can be expressed as
xti
X ti
Pt i GDPt i GDPt i
=
X tW PtW xtW GDPtW
GDPtW
[1]
Where X are nominal exports, x are real exports and GDP is real GDP. Taking logs on the lhs
and the rhs of the identity above and differentiating, proportional changes in a country’s share in
world exports can be expressed as a function of the country’s relative change in prices, its
relative change in openness and its relative change in GDP:
∧ ∧
∧
 xi
i
i
 X   P   GDP i
 X W  =  P W  +  xW
  t

 
 GDPW
t

∧

  GDP i 
t
+
W 
  GDPt 


[2]
where ^ denotes proportional changes.
Hence the changes in export revenue over the period caused by changes in world market share
can be decomposed into changes in export revenue caused by price differentials, changes in
export revenue caused by changes in the country’s relative openness, and changes in revenue
caused by the country’s differential GDP growth.
Note that the sum of the three effects in Table 3 do not add up to 100 because of two possible
reasons. First, in estimating the counterfactual export revenue, we used the average values of all
variables for 1990-92 rather than the actual for 1990. This is likely to affect the estimated
results. Second, we are reporting only the partial effects of the three possible causes of
marginalization, overlooking their joint effect.
- 42 Annex 2. Groupings of countries
Countries
ESA
COMESA
Angola
x
x
Botswana
x
Burundi
x
x
Comoros
x
x
Congo, D.R.
x
x
Djibouti
x
x
Egypt
x
x
Eritrea
x
x
Ethiopia
x
x
Kenya
x
x
Lesotho
x
Madagascar
x
x
Malawi
x
x
Mauritius
x
x
Mozambique
x
Namibia
x
x
Rwanda
x
x
Seychelles
x
x
South Africa
x
Sudan
x
x
Swaziland
x
x
Tanzania
x
Uganda
x
x
Zambia
x
x
Zimbabwe
x
x
SADC
x
x
EAC
SACU
Landlocked
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
43
Annex 3. Undertrading and overtrading of different regions, 1990-1994 & 1996-2000
Independent variables
Dummy Sub-Saharan Africa
(1)
-0.06
(2)
Dependent variable: log of average export to GDP ratio
period 1990 to 1994
period 1996 to 2000
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
(11)
(12)
-0.21 *
[0.13]
Dummy ESA
(1
[0.12]
-0.03
-0.21 *
[0.13]
Dummy COMESA
[0.12]
-0.45 **
[0.19]
Dummy SADC
0
-0.11
[0.16]
0.27 *
[0.22]
Dummy OVERLAP
-0.54 ***
[0.15]
[0.15]
1.01 ***
-0.17
[0.13]
-0.28
0.15
[0.21]
[0.15]
1.14 ***
[0.34]
[0.31]
Dummy EAC
-0.01
Dummy SACU
-0.
[0.29]
[0.
0.11
0.0
[0.25]
Dummy LANDLOCK
[0.
-0.23
[0.17]
Dummy East Asia & Pacific
Dummy Latin America
ln GDP per capita PPP
1
ln land
0.29 **
0.29 **
0.29 **
[0.13]
[0.13]
[0.12]
-0.14
-0.14
-0.13
[0.11]
[0.11]
[0.10]
0.21 ***
0.22 ***
0.33 ***
0.37 ***
0.28 **
0.32 ***
0.32 **
0.31 ***
0.33 ***
0.36 ***
[0.12]
[0.12]
[0.12]
[0.12]
[0.12]
[0.12]
[0.12]
[0.12]
[0.12]
-0.13
-0.09
-0.12
-0.15
[0.11]
[0.11]
[0.11]
[0.10]
0.22 ***
0.23 ***
0.23 ***
0.2 ***
-0.28 ***
-0.28 ***
-0.27 ***
-0.26 **
-0.22 **
[0.10]
[0.10]
[0.10]
[0.10]
[0.
0.16 ***
0.14 ***
0.16 ***
0.18 ***
0.
[0.04]
[0.04]
[0.04]
[0.04]
[0.04]
[0.04]
[0.04]
[0.04]
[0.04]
[0.04]
[0.04]
-0.02
-0.03
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
-0.03
-0.02
-0.02
[0.03]
Dummy French Polynesia
-3.78 ***
Dummy New Caledonia
-1.87 ***
[0.03]
[0.52]
[0.52]
[0.03]
-0.15 ***
[0.03]
-3.79 ***
[0.52]
-1.87 ***
[0.52]
[0.03]
-0.13 ***
[0.03]
-3.72 ***
[0.50]
-1.79 ***
[0.50]
[0.03]
-0.15 ***
[0.03]
-3.79 ***
[0.52]
-1.88 ***
[0.52]
[0.03]
-0.14 ***
[0.03]
-3.79 ***
[0.51]
-1.87 ***
[0.52]
Dummy Japan
[0.03]
-0.14 ***
[0.03]
-3.84 ***
[0.51]
-1.92 ***
[0.51]
[0.03]
-0.15 ***
[0.03]
-3.77 ***
[0.51]
-1.85 ***
[0.52]
[0.03]
-0.14 ***
[0.03]
-3.15 ***
[0.50]
-2.00 ***
[0.50]
[0.03]
-0.14 ***
[0.03]
-3.15 ***
[0.50]
-2.00 ***
[0.50]
[0.02]
-0.12 ***
[0.03]
-3.10 ***
[0.48]
-1.93 ***
[0.48]
[0.03]
-0.14 ***
[0.03]
-3.16 ***
[0.50]
-2.00 ***
[0.50]
[0.03]
-0.13 ***
[0.03]
-3.17 ***
[0.50]
-2.01 ***
[0.50]
-1.39 ***
Adjusted-R-Squared
Sample size
[0.
-0.0
[0.
-0.
[0.
-3.2
[0.
-2.0
[0.
-1.5
[0.51]
Constant
[0.
-0.2
[0.10]
[0.04]
-0.15 ***
0.4
0.16 ***
-0.02
1
ln population
0.2 ***
0.3 **
[0.
4.24 ***
4.21 ***
4.28 ***
4.17 ***
4.01 ***
3.95 ***
4.34 ***
4.72 ***
4.73 ***
4.81 ***
4.66 ***
4.41 ***
4.2
[0.50]
[0.50]
[0.48]
[0.50]
[0.48]
[0.48]
[0.49]
[0.48]
[0.48]
[0.46]
[0.48]
[0.46]
[0.
0.46
148
0.46
148
0.50
148
0.46
148
0.47
148
0.48
148
0.46
148
0.41
162
0.41
162
0.46
162
0.41
162
0.41
162
0.4
16
Diagnostic tests satisfied?
Functional form
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Heteroscedasticity
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Normality
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Source: GDF & WDI 2002.
Notes: * significant at 10%, ** significant at 5%, *** significant at 1%. Logs are natural logarithms. Y=yes, N=No. Standard errors in brackets.
OVERLAP: countries that are in SADC and COMESA; namely: Angola, Congo DR, Malawi, Mauritius, Namibia, Seychelles, Swaziland, Zambia, and Zimbabwe.
1
year is 1995 for the 1996-2000 regressions and 1989 for the 1990-1994 regressions.
See Annex 1 for more details.
44
Annex 4. Undertrading and overtrading of ESA countries, 1990-1994 & 1996-2000
Angola
1990-1994
0.93 *
1996-2000
1.17 **
[0.48]
Burundi
Botswana
-0.83 *
[0.46]
-1.12 **
[0.49]
[0.47]
0.30
-0.04
[0.49]
[0.48]
Djibouti
0.07
[0.47]
Egypt
0.33
[0.49]
Eritrea
-0.26
[0.47]
-0.24
[0.47]
Kenya
0.67
0.30
[0.49]
[0.47]
Lesotho
-0.36
-0.26
[0.49]
[0.47]
Madagascar
-0.02
0.05
[0.49]
[0.47]
-0.27
-0.52
Mozambique
[0.49]
[0.47]
Mauritius
0.35
0.22
[0.49]
[0.47]
Malawi
0.34
0.18
[0.49]
Rwanda
-1.32 ***
[0.48]
Sudan
[0.47]
-1.37 ***
[0.46]
-0.87 *
[0.47]
Swaziland
Tanzania
0.64
0.49
[0.49]
[0.47]
0.08
-0.14
[0.49]
[0.47]
Uganda
-0.79
-0.67
[0.49]
[0.47]
South Africa
-0.37
-0.11
[0.35]
[0.33]
Zambia
0.63
0.15
[0.49]
[0.47]
Zimbabwe
0.19
0.36
[0.49]
[0.47]
Comoros
-0.73
-0.70
[0.49]
[0.47]
0.30
0.20
[0.50]
[0.48]
Namibia
Source: GDF & WDI 2002.
Notes: * significant at 10%, ** significant at 5%, *** significant at 1%.
Standard errors in brackets. See Annex 1 for more details.
45
Annex 5: Destination of Exports and Sources of Imports (%)
Exports to
1990-92
1999-01
Imports from
1990-92
Exports to
1999-01
Angola
1990-92
1999-01
Imports from
1990-92
Exports to
1999-01
Djibouti
1990-92
1999-01
Imports from
1990-92
Exports to
1999-01
Lesotho
1990-92
1999-01
Imports from
1990-92
Exports to
1999-01
Namibia
1990-92
1999-01
Imports from
1990-92
1999-01
Swaziland
COMESA Intra-Region
0.0
0.0
0.6
0.2
COMESA Intra-Region
29.7
4.2
8.3
10.8
COMESA Intra-Region
1.2
0.7
2.7
1.4
COMESA Intra-Region
0.4
1.0
3.1
3.8
COMESA Intra-Region
6.3
7.1
1.8
1.2
SADC Intra-Region
0.0
0.3
2.4
11.9
SADC Intra-Region
0.1
0.2
0.1
0.9
SADC Intra-Region
1.3
0.7
2.7
1.6
SADC Intra-Region
0.6
1.5
3.1
3.8
SADC Intra-Region
9.6
15.8
1.8
3.9
Rest of Africa
0.4
0.2
1.1
2.3
Rest of Africa
29.0
48.9
0.5
1.2
Rest of Africa
1.1
1.9
0.7
0.4
Rest of Africa
1.9
1.3
0.0
0.1
Rest of Africa
1.0
0.5
0.0
1.0
USA
56.5
48.6
9.0
10.8
USA
0.0
0.2
2.5
3.3
USA
52.7
79.3
5.0
0.8
USA
7.9
5.5
21.5
39.0
USA
7.7
16.5
8.3
11.8
EU
33.8
20.2
70.9
43.5
EU
5.5
19.9
42.0
32.7
EU
35.6
9.6
59.2
10.5
EU
51.5
81.2
68.5
36.2
EU
41.1
39.1
8.3
11.8
East Asia & Pacific
0.8
22.3
7.4
19.1
East Asia & Pacific
1.1
0.9
26.1
23.6
East Asia & Pacific
1.1
0.4
19.2
51.9
East Asia & Pacific
0.7
2.3
1.6
9.6
East Asia & Pacific
22.9
18.6
23.9
56.0
South Asia
0.0
0.0
0.3
0.6
South Asia
0.1
0.5
3.2
2.4
South Asia
2.3
0.0
5.3
1.2
South Asia
0.0
0.0
0.4
0.8
South Asia
0.8
5.7
22.7
3.6
Botswana
Egypt
Madagascar
Rwanda
Tanzania
COMESA Intra-Region
19.8
6.9
28.7
16.6
COMESA Intra-Region
1.2
1.0
0.5
0.9
COMESA Intra-Region
9.4
3.7
2.6
8.9
COMESA Intra-Region
1.0
3.7
18.3
34.0
COMESA Intra-Region
11.4
18.1
11.4
18.1
SADC Intra-Region
20.0
7.0
28.9
16.6
SADC Intra-Region
0.5
0.4
0.1
0.3
SADC Intra-Region
9.7
3.8
6.2
13.8
SADC Intra-Region
0.3
7.4
13.6
10.9
SADC Intra-Region
2.7
8.3
2.7
8.3
Rest of Africa
0.2
0.0
0.3
0.0
Rest of Africa
2.8
3.0
0.6
0.6
Rest of Africa
0.8
0.9
0.9
0.3
Rest of Africa
0.1
0.2
0.1
0.0
Rest of Africa
0.6
0.6
0.6
0.6
USA
4.4
3.2
11.2
12.6
USA
6.9
14.3
21.8
18.2
USA
12.3
18.2
2.6
1.6
USA
10.2
7.4
0.9
13.6
USA
3.1
4.4
3.1
4.4
35.6
EU
33.6
79.3
70.9
43.5
EU
57.1
50.1
43.0
38.9
EU
55.3
59.5
61.4
40.5
EU
76.8
52.9
49.9
28.2
EU
47.8
35.6
47.8
East Asia & Pacific
7.0
0.3
12.2
13.8
East Asia & Pacific
5.1
9.8
13.7
18.3
East Asia & Pacific
14.3
14.2
17.9
25.1
East Asia & Pacific
3.4
15.1
11.3
6.9
East Asia & Pacific
16.6
16.7
16.6
16.7
South Asia
0.1
0.0
2.2
1.3
South Asia
4.3
4.2
2.2
1.8
South Asia
0.6
0.1
0.7
2.3
South Asia
6.6
9.5
2.0
3.9
South Asia
10.9
17.8
10.9
17.8
COMESA Intra-Region
5.2
10.1
10.4
9.6
COMESA Intra-Region
8.3
3.0
COMESA Intra-Region
3.7
5.6
11.6
21.7
COMESA Intra-Region
1.3
0.4
4.3
2.6
COMESA Intra-Region
3.3
1.3
23.9
44.0
SADC Intra-Region
2.7
0.8
8.5
13.3
SADC Intra-Region
3.0
0.6
SADC Intra-Region
11.4
14.8
51.2
70.1
SADC Intra-Region
1.2
2.1
18.7
10.3
SADC Intra-Region
0.6
2.2
2.1
9.6
Rest of Africa
0.4
0.2
0.3
0.0
Rest of Africa
0.1
0.1
Rest of Africa
0.8
0.6
0.0
0.0
Rest of Africa
0.4
0.6
0.0
0.3
Rest of Africa
1.4
3.0
0.6
0.1
USA
7.5
9.2
2.5
2.5
USA
1.8
9.2
USA
14.8
15.8
4.9
2.5
USA
0.8
6.0
1.3
13.9
USA
8.5
6.7
4.2
3.5
EU
79.2
56.9
63.5
51.4
EU
64.7
58.9
EU
46.1
37.0
27.5
12.5
EU
50.9
78.4
35.8
36.6
EU
74.3
60.9
41.3
22.2
East Asia & Pacific
2.1
6.1
14.6
5.2
East Asia & Pacific
12.2
12.9
East Asia & Pacific
18.2
12.0
13.3
6.2
East Asia & Pacific
31.7
12.1
26.2
14.1
East Asia & Pacific
6.3
9.4
15.6
9.0
South Asia
3.1
4.0
1.0
3.0
South Asia
0.0
0.0
South Asia
1.3
0.7
1.0
3.9
South Asia
0.4
0.0
1.0
2.6
South Asia
1.0
0.7
6.4
7.2
COMESA Intra-Region
0.6
0.2
5.6
8.7
COMESA Intra-Region
6.3
15.5
3.4
3.6
COMESA Intra-Region
1.3
2.3
1.4
1.5
COMESA Intra-Region
7.5
8.8
1.5
1.7
COMESA Intra-Region
3.8
15.4
8.1
7.5
SADC Intra-Region
0.1
0.0
5.8
18.0
SADC Intra-Region
0.0
0.8
0.1
1.3
SADC Intra-Region
1.4
5.5
14.0
15.5
SADC Intra-Region
7.8
9.4
1.5
1.9
SADC Intra-Region
3.5
18.0
32.6
69.4
Burundi
Eritrea
Comoros
Malawi
Ethiopia
Seychelles
Mauritius
Uganda
South Africa
Zambia
Rest of Africa
0.5
0.1
0.4
0.5
Rest of Africa
0.3
2.2
0.8
0.2
Rest of Africa
0.5
0.3
1.0
0.8
Rest of Africa
0.2
1.9
0.3
1.1
Rest of Africa
0.3
0.7
0.1
0.3
USA
28.4
20.4
0.2
1.2
USA
6.8
7.3
19.6
8.2
USA
11.6
17.2
1.2
1.4
USA
10.9
13.1
15.9
11.7
USA
3.6
3.2
6.5
2.2
12.7
EU
64.5
53.2
76.8
43.2
EU
46.0
39.9
45.5
37.5
EU
81.4
68.6
36.6
36.1
EU
52.6
40.8
55.1
42.8
EU
27.7
24.3
38.7
East Asia & Pacific
4.8
23.2
10.7
17.6
East Asia & Pacific
18.37
15.81
8.79
16.35
East Asia & Pacific
2.1
4.6
31.1
26.1
East Asia & Pacific
17.2
21.4
17.1
21.9
East Asia & Pacific
49.1
28.1
10.8
6.5
South Asia
0.1
0.4
1.4
4.9
South Asia
0.0
0.9
1.1
8.6
South Asia
0.1
0.3
5.5
9.4
South Asia
0.5
1.7
0.1
1.5
South Asia
6.2
3.0
4.1
2.2
COMESA Intra-Region
2.5
3.3
2.7
6.9
COMESA Intra-Region
20.4
30.7
2.7
1.2
COMESA Intra-Region
2.3
14.4
7.4
4.2
COMESA Intra-Region
4.5
3.8
3.9
5.7
COMESA Intra-Region
10.2
7.8
8.1
7.5
SADC Intra-Region
2.0
2.9
8.1
21.5
SADC Intra-Region
6.2
7.5
3.1
8.9
SADC Intra-Region
4.5
20.3
15.2
61.5
SADC Intra-Region
0.0
3.3
0.6
1.0
SADC Intra-Region
24.1
20.8
32.6
69.4
Congo DR
Kenya
Mozambique
Sudan
Zimbabwe
Rest of Africa
0.6
0.3
7.1
21.2
Rest of Africa
1.9
2.2
0.3
0.5
Rest of Africa
0.7
0.0
2.1
0.0
Rest of Africa
1.7
0.6
13.6
0.4
Rest of Africa
1.6
0.8
0.1
0.3
USA
17.6
16.9
6.1
2.6
USA
5.1
5.3
5.6
11.3
USA
6.6
4.0
10.9
3.4
USA
3.4
0.1
5.0
0.9
USA
6.5
6.3
6.5
2.2
EU
66.0
73.5
52.8
34.6
EU
50.2
36.3
46.6
29.6
EU
25.8
54.1
35.4
17.2
EU
34.4
13.8
37.9
33.2
EU
40.7
39.0
38.7
12.7
East Asia & Pacific
5.8
1.7
19.5
7.7
East Asia & Pacific
5.5
5.5
19.5
16.8
East Asia & Pacific
54.7
12.6
20.0
12.2
East Asia & Pacific
29.9
58.3
13.9
29.9
East Asia & Pacific
16.7
20.0
10.8
6.5
South Asia
3.8
3.8
0.5
4.3
South Asia
7.2
10.0
3.4
5.9
South Asia
0.9
6.2
1.7
1.5
South Asia
1.3
0.9
2.5
4.8
South Asia
1.0
0.9
4.1
2.2
Source of data: IMF Direction of Trade Statistics.
Notes: See Annex 1. Botswana's exports to Norway averaged 31% during 1990-92. Shares do not add to 100 because trade with the rest of the world is not reported and because nince countries are members of both COMESA and SADC.
46
Annex 6: ESA countries' export composition.
1990-1992
Angola
Primary goods
99.03
All foods
0.38
Agricultural materials
0.01
Fuels, Ores and Metals
98.63
Manufactures
0.82
of which: Leather, rubber and footwear
0.00
Wood and paper
0.00
Textiles and Clothing
0.01
Botswana
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
1998-2000
93.06
0.78
0.03
92.25
6.77
0.00
0.01
0.00
Kenya
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
2000
18.26
6.40
0.03
11.83
77.72
0.55
0.00
3.40
Lesotho
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
1990-1992
1998-2000
84.24
71.05
10.49
2.70
14.78
4.14
0.29
1.94
86.22
68.74
15.68
1.80
13.16
0.88
0.56
3.78
South Africa
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
2000
0.85
0.74
0.04
0.07
99.05
0.07
0.04
86.56
Sudan
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
1990-1992
1998-2000
2000
49.42
9.91
3.13
36.38
48.43
1.21
2.40
2.00
96.22
21.98
72.10
2.14
3.28
0.41
0.02
0.56
93.65
31.50
18.66
43.49
4.77
1.98
0.04
1.56
2000
64.38
52.15
10.68
1.55
35.44
0.09
0.20
18.18
Burundi
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
96.35
86.82
5.14
4.39
3.15
0.24
0.05
0.72
96.46
93.10
0.91
2.45
3.38
0.07
0.11
0.21
Madagascar
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
84.17
70.49
4.61
9.06
15.59
0.65
0.13
10.22
55.83
46.85
5.18
3.79
43.01
0.20
0.31
38.41
Swaziland
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
Comoros
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
64.76
64.11
0.52
0.12
34.47
0.01
0.43
1.09
51.99
49.20
0.38
2.41
47.82
0.01
1.60
0.46
Malawi
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
95.06
92.14
2.82
0.10
4.80
0.03
0.20
3.36
87.91
85.76
2.07
0.09
11.94
0.02
0.30
11.02
Tanzania
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
85.93
55.85
26.82
3.27
13.35
0.39
0.66
6.98
86.17
67.20
14.73
4.24
12.95
0.17
0.23
2.34
Congo DR
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
89.41
13.26
7.97
68.17
10.33
0.01
0.60
0.06
46.82
6.98
5.70
34.13
51.61
0.01
0.28
0.02
Mauritius
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
32.94
32.24
0.56
0.14
66.72
0.04
0.12
57.46
26.98
26.25
0.50
0.23
72.03
0.08
0.12
61.31
Uganda
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
97.54
85.03
12.21
0.30
2.38
0.12
0.01
0.15
96.53
86.64
9.26
0.64
2.60
0.43
0.01
0.03
Djibouti
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
60.80
7.56
34.81
18.43
33.97
0.69
0.76
2.89
42.11
17.38
10.69
14.04
54.79
9.51
1.47
1.13
Mozambique
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
61.90
35.96
6.40
19.54
37.72
0.47
1.07
2.12
83.23
55.31
17.01
10.92
16.47
1.14
0.20
2.90
Zambia
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
95.80
1.60
1.05
93.15
4.05
0.07
0.01
1.04
87.16
7.44
6.72
73.00
10.75
0.16
0.04
5.29
Egypt
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
75.96
4.14
2.84
68.98
23.10
0.22
0.05
12.69
60.57
6.05
4.98
49.54
37.81
0.82
0.32
23.44
Namibia
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
2000
68.08
58.13
1.07
8.88
31.26
1.89
0.08
0.12
Zimbabwe
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
70.74
43.63
7.63
19.48
29.05
1.30
0.26
5.89
74.43
45.81
13.93
14.70
25.31
1.71
0.83
4.28
49.27
28.88
13.89
6.50
47.97
16.12
0.31
2.22
Rwanda
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
Eritrea
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
97.11
83.86
7.79
5.46
2.72
0.33
0.13
0.07
96.55
75.51
6.38
14.66
3.00
0.13
0.16
0.24
- 47 Annex 7: Revealed Comparative Advantage
1990-1992 1998-2000
Angola
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
3.78
0.04
0.00
7.10
0.01
0.00
0.00
0.00
Botswana
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
1990-1992 1998-2000
4.53
0.11
0.01
8.34
0.09
0.00
0.00
0.00
Kenya
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
2000
0.89
0.87
0.02
1.07
1.01
0.29
0.00
0.57
Lesotho
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
3.21
7.66
3.43
0.19
0.20
1.99
0.11
0.29
4.20
9.32
7.41
0.16
0.17
0.46
0.25
0.63
South Africa
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
2000
0.04
0.10
0.02
0.01
1.29
0.04
0.02
14.44
Sudan
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
1990-1992 1998-2000
2000
2.40
1.34
1.48
3.29
0.63
0.63
1.05
0.33
3.67
2.37
23.56
0.15
0.05
0.20
0.01
0.08
4.56
4.27
8.82
3.93
0.06
1.03
0.02
0.26
2000
3.13
7.07
5.05
0.14
0.46
0.04
0.09
3.03
Burundi
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
3.67
9.36
1.68
0.32
0.04
0.12
0.02
0.10
4.69
12.62
0.43
0.22
0.04
0.04
0.05
0.04
Madagascar
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
3.21
7.60
1.51
0.65
0.22
0.31
0.05
1.50
2.72
6.35
2.45
0.34
0.56
0.10
0.13
6.41
Swaziland
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
Comoros
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
2.47
6.91
0.17
0.01
0.48
0.00
0.17
0.16
2.53
6.67
0.18
0.22
0.62
0.00
0.70
0.08
Malawi
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
3.63
9.93
0.92
0.01
0.07
0.01
0.08
0.49
4.28
11.62
0.98
0.01
0.16
0.01
0.13
1.84
Tanzania
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
3.28
6.02
8.76
0.24
0.19
0.19
0.26
1.02
4.19
9.11
6.96
0.38
0.17
0.09
0.10
0.39
Congo DR
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
3.41
1.43
2.60
4.91
0.14
0.00
0.24
0.01
2.28
0.95
2.69
3.09
0.67
0.00
0.12
0.00
Mauritius
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
1.26
3.47
0.18
0.01
0.93
0.02
0.05
8.43
1.31
3.56
0.24
0.02
0.94
0.04
0.05
10.23
Uganda
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
3.72
9.17
3.99
0.02
0.03
0.06
0.00
0.02
4.70
11.74
4.37
0.06
0.03
0.22
0.00
0.00
Djibouti
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
2.32
0.81
11.38
1.33
0.47
0.33
0.30
0.42
2.05
2.36
5.05
1.27
0.71
4.96
0.64
0.19
Mozambique
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
2.36
3.88
2.09
1.41
0.52
0.23
0.42
0.31
4.05
7.50
8.03
0.99
0.21
0.60
0.09
0.48
Zambia
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
3.65
0.17
0.34
6.71
0.06
0.03
0.00
0.15
4.24
1.01
3.17
6.60
0.14
0.08
0.02
0.88
Egypt
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
2.90
0.45
0.93
4.97
0.32
0.11
0.02
1.86
2.95
0.82
2.35
4.48
0.49
0.43
0.14
3.91
Namibia
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
2000
3.31
7.88
0.50
0.80
0.41
0.98
0.03
0.02
Zimbabwe
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Manufactures
of which: Leather, rubber and footwear
Wood and paper
Textiles and Clothing
2.70
4.70
2.49
1.40
0.40
0.63
0.10
0.86
3.62
6.21
6.58
1.33
0.33
0.89
0.36
0.71
2.40
3.91
6.56
0.59
Rwanda
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
Eritrea
Primary goods
All foods
Agricultural materials
Fuels, Ores and Metals
3.70
9.04
2.55
0.39
4.70
10.23
3.01
1.33
48
Annex 8. Factor Intensity of Exports (%)
1990-1992
1998-2000
ANGOLA
1990-1992
1998-2000
DJIBOUTI
High manufactures
0.13
0.07
High manufactures
Medium manufactures
0.08
0.18
Low manufactures
0.01
0.03
Labor-intensive manufactures
0.59
6.48
1990-1992
LESOTHO
5.97
16.19
Medium manufactures
7.86
Low manufactures
7.69
Labor-intensive manufactures
4.59
1998-2000
2000
NAMIBIA
2000
High manufactures
0.52
High manufactures
11.37
12.84
Medium manufactures
0.66
Medium manufactures
1.39
6.22
Low manufactures
0.27
Low manufactures
0.29
9.89
Labor-intensive manufactures
97.56
Labor-intensive manufactures
18.03
Non-fuel primary commodities
0.44
0.88
Non-fuel primary commodities
52.93
30.15
Non-fuel primary commodities
0.81
Non-fuel primary commodities
64.57
Others
98.76
92.36
Others
20.95
24.71
Others
0.17
Others
4.36
BOTSWANA
2000
EGYPT
MADAGASCAR
RWANDA
High manufactures
0.21
High manufactures
6.00
4.48
High manufactures
1.68
1.28
High manufactures
1.23
0.96
Medium manufactures
3.62
Medium manufactures
1.25
3.36
Medium manufactures
0.33
0.36
Medium manufactures
0.40
1.00
Low manufactures
0.01
Low manufactures
1.97
3.11
Low manufactures
0.14
0.14
Low manufactures
0.38
0.28
Labor-intensive manufactures
73.33
Labor-intensive manufactures
13.50
25.08
Labor-intensive manufactures
13.03
40.06
Labor-intensive manufactures
0.46
0.60
Non-fuel primary commodities
18.26
Non-fuel primary commodities
10.99
15.53
Non-fuel primary commodities
83.26
53.70
Non-fuel primary commodities
97.03 94.57
Others
4.58
Others
66.28
48.45
Others
1.56
4.46
Others
0.49
BURUNDI
ERITREA
1994-1996
MALAWI
2.60
SEYCHELLES
High manufactures
0.42
0.49
High manufactures
9.23
9.65
High manufactures
0.36
0.27
High manufactures
3.41
4.62
Medium manufactures
0.76
0.52
Medium manufactures
4.10
6.64
Medium manufactures
0.70
0.20
Medium manufactures
3.89
1.11
Low manufactures
0.16
0.06
Low manufactures
0.18
0.31
Low manufactures
0.06
0.06
Low manufactures
0.20
0.13
Labor-intensive manufactures
1.69
2.03
Labor-intensive manufactures
8.35
12.01
Labor-intensive manufactures
3.66
11.35
Labor-intensive manufactures
0.49
1.74
Non-fuel primary commodities
96.13
91.13
Non-fuel primary commodities
49.83
30.18
Non-fuel primary commodities
95.05
87.89
Non-fuel primary commodities
90.87 90.93
Others
0.84
5.78
Others
28.32
41.22
Others
0.17
0.24
Others
1.14
COMOROS
ETHIOPIA
1994-1996
MAURITIUS
SOUTH AFRICA
1.47
2000
High manufactures
31.60
35.19
High manufactures
3.35
2.48
High manufactures
3.90
3.27
High manufactures
6.50
Medium manufactures
0.56
9.18
Medium manufactures
5.64
2.99
Medium manufactures
0.52
0.72
Medium manufactures
11.60
10.55
Low manufactures
0.06
0.58
Low manufactures
0.04
0.17
Low manufactures
0.63
0.33
Low manufactures
Labor-intensive manufactures
1.88
2.67
Labor-intensive manufactures
9.32
5.10
Labor-intensive manufactures
59.39
64.44
Labor-intensive manufactures
14.08
Non-fuel primary commodities
64.65
51.94
Non-fuel primary commodities
80.99
88.83
Non-fuel primary commodities
32.93
26.96
Non-fuel primary commodities
37.15
Others
1.25
0.44
Others
0.65
0.42
Others
2.64
4.28
Others
20.12
CONGO DR
KENYA
MOZAMBIQUE
SUDAN
High manufactures
0.37
1.07
High manufactures
4.82
4.34
High manufactures
1.96
2.32
High manufactures
0.79
0.49
Medium manufactures
0.14
0.14
Medium manufactures
0.84
0.96
Medium manufactures
3.64
8.30
Medium manufactures
1.23
0.59
Low manufactures
0.43
0.15
Low manufactures
0.23
0.29
Low manufactures
28.17
1.62
Low manufactures
0.14
0.08
Labor-intensive manufactures
9.51
50.13
Labor-intensive manufactures
8.45
6.98
Labor-intensive manufactures
3.94
3.49
Labor-intensive manufactures
1.00
3.52
Non-fuel primary commodities
69.65
32.09
Non-fuel primary commodities
82.56
85.40
Non-fuel primary commodities
58.97
80.97
Non-fuel primary commodities
93.58 52.37
Others
19.89
16.42
Others
3.11
2.03
Others
3.32
3.31
Others
3.26
Source: See Annex 1.
Note: Data presented is for the 1990-1992 and 1998-2000 periods unless otherwise stated using a shaded box.
The period stated in a shaded box applies only to that particular country.
42.95
49
Series #
ARWPS 1
Africa Region Working Paper Series
Title
Date
January 1999
Progress in Public Expenditure Management in
Africa: Evidence from World Bank Surveys
Author
C. Kostopoulos
ARWPS 2
Toward Inclusive and Sustainable Development in
the Democratic Republic of the Congo
March 1999
Markus Kostner
ARWPS 3
Business Taxation in a Low-Revenue Economy: A
Study on Uganda in Comparison with Neighboring
Countries
June 1999
Ritva Reinikka
Duanjie Chen
ARWPS 4
Pensions and Social Security in Sub-Saharan Africa: October 1999
Issues and Options
ARWPS 5
Forest Taxes, Government Revenues and the
Sustainable Exploitation of Tropical Forests
January 2000
Luca Barbone
Juan Zalduendo
ARWPS 6
The Cost of Doing Business: Firms’ Experience
with Corruption in Uganda
June 2000
Jacob Svensson
ARWPS 7
On the Recent Trade Performance of Sub-Saharan
African Countries: Cause for Hope or More of the
Same
August 2000
Francis Ng and
Alexander J. Yeats
ARWPS 8
Foreign Direct Investment in Africa: Old Tales and
New Evidence
November 2000
Miria Pigato
ARWPS 9
The Macro Implications of HIV/AIDS in South
Africa: A Preliminary Assessment
November 2000
Channing Arndt
Jeffrey D. Lewis
ARWPS 10 Revisiting Growth and Convergence: Is Africa
Catching Up?
December 2000
C. G. Tsangarides
ARWPS 11 Spending on Safety Nets for the Poor: How Much,
for
How Many? The Case of Malawi
January 2001
William J. Smith
ARWPS 12 Tourism in Africa
February 2001
Iain T. Christie
D. E. Crompton
ARWPS 13 Conflict Diamonds
February 2001
Louis Goreux
ARWPS 14 Reform and Opportunity: The Changing Role and
Patterns of Trade in South Africa and SADC
March 2001
Jeffrey D. Lewis
Luca Barbone
Luis-A. Sanchez B.
- 50 Africa Region Working Paper Series
Title
Series #
Date
March 2001
ARWPS 15 The Foreign Direct Investment Environment in
Africa
Author
Miria Pigato
ARWPS 16 Choice of Exchange Rate Regimes for Developing
Countries
April 2001
Fahrettin Yagci
ARWPS 18 Rural Infrastructure in Africa: Policy Directions
June 2001
Robert Fishbein
ARWPS 19 Changes in Poverty in Madagascar: 1993-1999
July 2001
S. Paternostro
J. Razafindravonona
David Stifel
ARWPS 20 Information and Communication Technology,
Poverty, and Development in sub-Saharan Africa
and South Asia
August 2001
Miria Pigato
ARWPS 21 Handling Hierarchy in Decentralized Settings:
Governance Underpinnings of School Performance
in Tikur Inchini, West Shewa Zone, Oromia Region
September 2001
Navin Girishankar A.
Alemayehu
Yusuf Ahmad
ARWPS 22 Child Malnutrition in Ethiopia: Can Maternal
Knowledge Augment The Role of Income?
October 2001
Luc Christiaensen
Harold Alderman
ARWPS 23 Child Soldiers: Preventing, Demobilizing and
Reintegrating
November 2001
Beth Verhey
ARWPS 24 The Budget and Medium-Term Expenditure
Framework in Uganda
December 2001
David L. Bevan
ARWPS 25 Design and Implementation of Financial
Management Systems: An African Perspective
January 2002
Guenter Heidenhof H.
Grandvoinnet
Daryoush Kianpour B.
Rezaian
ARWPS 26 What Can Africa Expect From Its Traditional
Exports?
February 2002
Francis Ng
Alexander Yeats
ARWPS 27 Free Trade Agreements and the SADC Economies
February 2002
Jeffrey D. Lewis
Sherman Robinson
Karen Thierfelder
ARWPS 28 Medium Term Expenditure Frameworks: From
Concept to Practice. Preliminary Lessons from
Africa
February 2002
P. Le Houerou Robert
Taliercio
- 51 -
Series #
Africa Region Working Paper Series
Title
Date
Author
ARWPS 29 The Changing Distribution of Public Education
Expenditure in Malawi
February 2002
Samer Al-Samarrai
Hassan Zaman
ARWPS 30 Post-Conflict Recovery in Africa: An Agenda for
the Africa Region
April 2002
ARWPS 31 Efficiency of Public Expenditure Distribution and
Beyond: A report on Ghana’s 2000 Public
Expenditure Tracking Survey in the Sectors of
Primary Health and Education
ARWPS 33 Addressing Gender Issues in Demobilization and
Reintegration Programs
May 2002
Serge Michailof
Markus Kostner
Xavier Devictor
Xiao Ye
S. Canagaraja
August 2002
N. de Watteville
ARWPS 34 Putting Welfare on the Map in Madagascar
August 2002
Johan A. Mistiaen
Berk Soler
T. Razafimanantena
J. Razafindravonona
ARWPS 35 A Review of the Rural Firewood Market Strategy in
West Africa
August 2002
Gerald Foley
Paul Kerkhof
Djibrilla Madougou
ARWPS 36 Patterns of Governance in Africa
September 2002
Brian D. Levy
ARWPS 37 Obstacles and Opportunities for Senegal’s
International Competitiveness: Case Studies of the
Peanut Oil, Fishing and Textile Industries
September 2002
Stephen Golub
Ahmadou Aly Mbaye
ARWPS 38 A Macroeconomic Framework for Poverty
Reduction Strategy Papers : With an Application to
Zambia
ARWPS 39 The Impact of Cash Budgets on Poverty Reduction
in Zambia: A Case Study of the Conflict between
Well Intentioned Macroeconomic Policy and
Service Delivery to the Poor
October 2002
S. Devarajan
Delfin S. Go
November 2002
Hinh T. Dinh
Abebe Adugna
Bernard Myers
ARWPS 40 Decentralization in Africa: A Stocktaking Survey
November 2002
Stephen N. Ndegwa
ARWPS 41 An Industry Level Analysis of Manufacturing
Productivity in Senegal
December 2002
Professor A. Mbaye
ARWPS 42 Tanzania’s Cotton Sector: Constraints and
Challenges in a Global Environment
December 2002
John Baffes
- 52 -
Series #
Africa Region Working Paper Series
Title
Date
Author
ARWPS 43 Analyzing Financial and Private Sector Linkages in
Africa
January 2003
Abayomi Alawode
ARWPS 44 Modernizing Africa’s Agro-Food System:
Analytical Framework and Implications for
Operations
February 2003
ARWPS 45 Public Expenditure Performance in Rwanda
March 2003
Steven Jaffee
Ron Kopicki
Patrick Labaste
Iain Christie
Hippolyte Fofack
C. Obidegwu
Robert Ngong
ARWPS 46 Senegal Tourism Sector Study
March 2003
Elizabeth Crompton
Iain T. Christie
ARWPS 47 Reforming the Cotton Sector in SSA
March 2003
Louis Goreux
John Macrae
ARWPS 48 HIV/AIDS, Human Capital, and Economic Growth
Prospects for Mozambique
April 2003
Channing Arndt
ARWPS 49 Rural and Micro Finance Regulation in Ghana:
Implications for Development and Performance of
the Industry
June 2003
William F. Steel
David O. Andah
ARWPS 50 Microfinance Regulation in Benin: Implications of
the PARMEC LAW for Development and
Performance of the Industry
June 2003
K. Ouattara
ARWPS 51 Microfinance Regulation in Tanzania: Implications
for Development and Performance of the Industry
June 2003
Bikki Randhawa
Joselito Gallardo
ARWPS 52 Regional Integration in Central Africa: Key Issues
June 2003
Ali Zafar
Keiko Kubota
ARWPS 53 Evaluating Banking Supervision in Africa
June 2003
Abayomi Alawode
ARWPS 54 Microfinance Institutions’ Response in Conflict
Environments: Eritrea- Savings and Micro Credit
Program; West Bank and Gaza – Palestine for
Credit and Development; Haiti – Micro Credit
National, S.A.
June 2003
Marilyn S. Manalo
June 2003
Steven Jaffee
AWPS 55
Malawi’s Tobacco Sector: Standing on One Strong
- 53 -
Series #
Africa Region Working Paper Series
Title
Date
leg is Better than on None
Author
AWPS 56
Tanzania’s Coffee Sector: Constraints and
Challenges in a Global Environment
June 2003
John Baffes
AWPS 57
The New Southern African Customs Union
Agreement
June 2003
Robert Kirk
Matthew Stern
AWPS 58a
How Far Did Africa’s First Generation Trade
Reforms Go? An Intermediate Methodology for
Comparative Analysis of Trade Policies
How Far Did Africa’s First Generation Trade
Reforms Go? An Intermediate Methodology for
Comparative Analysis of Trade Policies
June 2003
Lawrence Hinkle
A. Herrou-Aragon
Keiko Kubota
Lawrence Hinkle
A. Herrou-Aragon
Keiko Kubota
AWPS 59
Rwanda: The Search for Post-Conflict SocioEconomic Change, 1995-2001
October 2003
C. Obidegwu
AWPS 60
Linking Farmers to Markets: Exporting Malian
Mangoes to Europe
October 2003
Morgane Danielou
Patrick Labaste
J-M. Voisard
AWPS 61
Evolution of Poverty and Welfare in Ghana in the
1990s: Achievements and Challenges
October 2003
S. Canagarajah
Claus C. Pörtner
AWPS 62
Reforming The Cotton Sector in Sub-Saharan
Africa: SECOND EDITION
November 2003
Louis Goreux
AWPS 63
(E)
Republic of Madagascar: Tourism Sector Study
November 2003
Iain T. Christie
D. E. Crompton
AWPS 63
(F)
République de Madagascar: Etude du Secteur
Tourisme
November 2003
Iain T. Christie
D. E. Crompton
AWPS 64
Migrant Labor Remittances in Africa: Reducing
Obstacles to Development Contributions
Novembre 2003
Cerstin Sander
Samuel M. Maimbo
AWPS 65
Government Revenues and Expenditures in GuineaBissau: Casualty and Cointegration
January 2004
Francisco G. Carneiro
Joao R. Faria
Boubacar S. Barry
AWPS 66
How will we know Development Results when we
see them? Building a Results-Based Monitoring and
Evaluation System to Give us the Answer
June 2004
Jody Zall Kusek
Ray C. Rist
Elizabeth M. White
AWPS 58b
June 2003
- 54 -
Series #
Africa Region Working Paper Series
Title
Date
Author
AWPS 67
An Analysis of the Trade Regime in Senegal (2001)
and UEMOA’s Common External Trade Policies
June 2004
Alberto Herrou-Arago
Keiko Kubota
AWPS 68
Bottom-Up Administrative Reform: Designing
Indicators for a Local Governance Scorecard in
Nigeria
June 2004
Talib Esmail
Nick Manning
Jana Orac
Galia Schechter
AWPS 69
Tanzania’s Tea Sector: Constraints and Challenges
June 2004
John Baffes
AWPS 70
Tanzania’s Cashew Sector: Constraints and
Challenges in a Global Environment
June 2004
Donald Mitchell
AWPS 71
An Analysis of Chile’s Trade Regime in 1998 and
2001: A Good Practice Trade Policy Benchmark
July 2004
Francesca Castellani
A. Herrou-Arago
Lawrence E. Hinkle
AWPS 72
Regional Trade Integration in East Africa: Trade
and Revenue Impacts of the Planned East African
Community Customs Union
Post-Conflict Peace Building in Africa: The
Challenges of Socio-Economic Recovery and
Development
An Analysis of the Trade Regime in Bolivia in2001:
A Trade Policy Benchmark for low Income
Countries
Remittances to Comoros- Volumes, Trends, Impact
and Implications
August 2004
Lucio Castro
Christiane Kraus
Manuel de la Rocha
Chukwuma Obidegwu
AWPS 73
AWPS 74
AWPS 75
AWPS 76
Salient Features of Trade Performance in Eastern
and Southern Africa
August 2004
August 2004
October 2004
October 2004
Francesca Castellani
Alberto Herrou-Aragon
Lawrence E. Hinkle
Vincent da Cruz
Wolfgang Fendler
Adam Schwartzman
Fahrettin Yagci
Enrique Aldaz-Carroll