Africa Region Working Paper Series 2 3 6 6 9
Number 26
What Can Africa Expect From
Ito Traditional Exporto?
Fraricis Ng
Alexander Yeats
February 2002
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What Can Africa Expect From Its Traditional Exports?
February 2002
Africa Region Working Paper Series No. 26
Abstract
This study examines the implications of recent trade trends and long-terni price
projections for Sub-Saharan Africa's major exports. Its policy message for Afr'ica is 1wVo frid.
First, Africa must diversify away from traditional products or continue to experience scinotus
negative trade effects including; (i) declining or relatively low growth in global demand for the. se
goods, (ii) falling real prices for traditional products, (iii) very unstable prices arld expert
earnings, (iv) a continued marginalization in world trade, and (v) diminiished growtlh andi
industrialization prospects. However, there is no evidence that any general diversification is
occurring. Domestic and international policy initiates must assign a far greater importance to the
need for diversifying Africa's exports.
Second, it is unlikely that major shifts in the composition of expor-is can occur in tlie
short to medium-term. As such, the removal of general anti-export biases ill African counIrle;s
domestic policies, as well as initiatives to promote more competitive (low cost) pliccs Im-
traditional exports, still require immediate attention. Future markets lOr traditional product s w. I
be highly competitive and African countries failing to implement policies p.n littill prodll( tio}n
efficiencies and lower costs should expect to experience major competitive export Io,s ss ie
these key items.
Authors' Affiliation and Sponsorship
Francis Ng
Research Analyst, Trade Team, The World Bank
E-mail: Fng@worldbank.org
Alexander Yeats
Consultant, Trade Team and Africa Region, The World Banlk
E-mail: Ayeats(msn.com
THE WORKING PAPER SERIES
The Afrnica Region Working Paper Series expedites dissemination of applied research and polic y studies with
potential for improving economic performance and social conditions in Sub-Saharan Africa. Thle Series
publishes papers at preliminary stages to stimulate timely discussion within tile Regioxn and among client
countries, donors, and the policy research community. The editorial board for the Series collsists of
representatives from professional Families appointed by the Region's Sector Directors.
Editor in charge of the series: Antoine Waldburger, AFTM3, Email: awaldburger(�)worltd)anik.oig, who may
be contacted for hard copies.
For additional information visit the Web site htrp://www.worldbank.ora/wps/index.htn, where copies are
available in pdf forniat.
The findings, interpretations, and conclusions expressed in this paper are entirely those of the author(s).
They do not necessarily represent the views of the World Bank Group, its Executive Dir-ectors, or the
countries that they represent and should not be attributed to them.
What Can Africa Expect From Its Traditional Exports?
Francis Ng
Research Analyst, Trade Team, Development Research Group, The World Bank
E-mail: Fng@worldbank.org
Alexander Yeats
Consultant, Trade Team and Africa Region, The World Bank
E-mail: Ayeats@msn.com
February 2002
The findings, interpretations, and conclusions expressed in this paper are entirely those of the
author(s). They do not necessarily represent the views of the World Bank Group, its Executive
Directors, or the countries that they represent and should not be attributed to them.
The authors, wish to thank Larry Hinkle, Bernard Hoekmari and Ataman Aksoy for valuable
comments and supports during the preparation of this paper. Maria Kasilag provide helpful
assistance in the production the report. The views expressed in this paper are those of the
authors, and do not necessary reflect the views of The WVorld Bank Group, its Executive
Directors, or its member countries.
Table of Contents
Chapter Page
Table of Contents ....................................................................i
Executive Summary .................................................................... iii
A. General Trade Trends ................................................................... iv
B. Price Instability Problems ................................................................... iv
C. Implications of the Competitive Environment .................................................................... v
D. Growth Prospects for African Exports ................................... ................................ vi
I. INTRODUCTION .1
II. DATA AND METHODOLOGY ...................................................................4
A. Statistical Issues .....................................................................4
Key Observations ...................................................................4
B. Identifying "Traditional" Products . ................................................................... 6
Key Observations ....................................................................6
III. LONG TERM DEMAND PROSPECTS .............................. ...................................... 9
A. Global Trade Trends for Traditional Exports .................................................................... 9
Key Observations ....................................................................9
B. Prospects for Individual SSA Countries ........................................... ........................ 13
Key Observations .................................................................... 13
C. Implications of Recent Income Elasticity Estimates ............................................................ 16
Key Observations ................................................................... 16
D. Recent Changes in the Direction of Trade ................................................................... 27
Key Observations .................................................................... 27
IV. PRICE TRENDS AND PROSPECTS ................................................................... 33
A. Secular Price Trends ................................................................... 34
Key Observations ................................................................... 34
B. Recent Price Instability for Traditional Products .................................................................. 39
Key Observations ................................................................... 39
C. Price Formation for Primary and Processed Traditional Products ........................................ 44
Key Observations ................................................................... 44
D. The OutJook for Traditional Product Prices ................................................................... 47
Key Observations ................................................................... 47
E. Implications of the Competitive Situation ............................................................. ...... 48
Key Observations ................................................................... 48
V. OVERALL EXPORT PROSPECTS ....................... ............................................ 49
Key Observations ................................................................... 49
VI. POLICY IMPLICATIONS ................................................................... 54
Key Observations ................................................................... 54
References .................................................................... 58
Annex I ................................................................... 61
Traditional Products and the Export Prospects of the Smaller Sub-Saharan African Countries ... 61
Annex 2 ................................................................... 65
Prospects for the Petroleum Exporting Sub-Saharan African Countries ................ ....................... 65
Annex 3 ................................................................... 69
Elements of Traditional Product Commodity Processing Chains .................................................. 69
Boxes
1. Major Findings of a Companion Study of Sub-Saharan Africa's Supply Capacity .........3
2. Implications of the Demnise of Some African "Historical" Exports ............................8
3. Are There "Dynamic" African Exports? ........................................................ 23
4. Recent Trends in Non-Energy Commodity Prices .............................................. 38
5. Trade Restrictions Facing Primary and Processed Traditional Products .................... 55
Tables
Table 1. The Growth of World Trade in Sub-Saharan Africa's Traditional Exports (1990-99) .... 11
Table 2. The Growth of World Trade in Major Groups of Sub-Saharan Africa's Traditional
Exports (1990-99) ............................................................. 12
Table 3. Estimated Effects of Demand Changes on Large and Mid-Size African Countries'
Traditional Exports (1990-99) ............................................................. 15
Table 4. Estimates of Trade Income Changes and Income Elasticities of Demand in the EU (15),
Japan and United States for Major Groups of Traditional African ....................................... 19
Table 5. Probable Demand Growth Prospects for Individual Traditional Products .22
Table 6. Average Income Elasticities and Trade-Income Ratios for Individual African Country
Traditional Products .26
Table 7. The Geographic Pattern for Global Imports of Traditional Products .29
Table 8. The Origins of Global Exports of Traditional Products .31
Table 9. Average Prices for Major Groups of Primary Commodities in Selected Years (1990 =
100) .35
Table 10. Average Real Prices of African Traditional Exports in Selected Years .36
Table 11. Recent Prices for Major Groups of Traditional .37
Table 12. Estimates of Real Price Changes for African Traditional Products (1990 = 100) . 39
Table 13. Price Instability Indices for Individual Traditional Products .42
Table 14. Average Annual and Maximum Consecutive Year Changes in Traditional Product
Prices During 1990-99 .43
Table 15. Instability and Longer-Term Price Changes for Primary and Processes Traditional
Exports .46
Table 16. 1990 Constant and Projected Prices for Traditional .48
Table 17. The Trade Prospects Index For Three Groups of African Exports .51
Executive Summary
Conventional thinking alleges unfavorable demand characteristics for the raw
materials that constitute Sub-Saharan Africa's traditional exports jeopardize the region's
growth and industrialization prospects. Empirical evidence suggests that the income
elasticities of demand for these goods are generally well below unity. If true, this would
tend to diminish Africa's importance in world trade relative to exporters of high income
elasticity goods, like machinery, chemicals, and transporl equipment, and also adversely
influence the region's relative economic growth rate. Second, the level of demand, and
prices, for traditional products can be strongly affected by cyclical changes in global
economic activity. It has been alleged that these "induced" demand changes have bcen
an important cause of instability in commodity prices and revenues that, purportedly, had
serious adverse implications for development planning and industrialization.
Third, it has been argued that inherent weakness iin long-term demand will cause
real commodity prices to fall relative to those for manufactures which, in turn, would
cause the terms-of-trade for African countries to deteriorate. For some products, the
weakness in demand was thought to have been exacerbated by competition from
synthetics. As an example, exports of hard fibers, like Agave or Sisal, have been reduced
by competition from man-made fibers, just as the replaceiment of some metals by plastics
reduced global demand for metal ores. Finally, it has been asserted that trade barriers in
major importing markets may have an adverse impact on the level of demand for, and
structure of, some commodity exports. Would the removal of any post-Uruguay Round
trade barriers markedly improve expectations for Africa's traditional exports?
With regard to the policy discussion of these issues, it should be noted that many
key propositions were formulated on the basis of empirical evidence from the 1950s or
1960s. Important changes have since occurred in the global economy. UNCTAD reports
that less than 50 percent of world trade consisted of rmanufactures in the mid-1950s,
while the current share of these goods is about 75 percent. The present share of
commodities and raw materials (approximately 25 percent) is about one-half what it was
in the mid-1950s -- it would now be about 5 percentage points lower if crude petroleum
was excluded. One factor responsible for this shift in the composition of trade was the
conversion of many important commodity producing countries into exporters of
manufactures. This conversion started with the Asian NICs in the early 1970s, followed
by a group of "second tier" countries like Malaysia and Thailand in the late 1970s and
1980s. Today, more than 60 percent (by value) of the total exports of former largely
commodity producing countries like Brazil, China, India, Malaysia, Mauritius, Pakistan
and Thailand consist of manufactured goods. This major re-orientation of global
production and trade toward manufactures may have altered the prospects of the fewer
remaining commodity exporters, like those in Africa. I'hus, this study addresses a key
question. What can Africa expectfrom its traditional exports?
iii
A. General Trade Trends
Over the last decade, global trade in Africa's traditional exports grew at a rate of
1.9 percent, or about one-third the corresponding rate for all goods. This is a
continuation of trends observed for the 1980s. Furthermore, 1990-1999 trade growth
rates for over 40 percent of Africa's traditional products were actually negative. The last
half of the decade witnessed a major collapse in demand for many of these goods with
1995-99 global imports of several traditional products falling by more than ten percent
annually. These developments contributed to the further erosion of Africa's global trade
share which fell from 1.8 percent in 1990 to 1.3 percent in 1999.
Conceivably, considerable variation could occur in the recent trade performance
of individual African countries depending on their specific "basket" of traditional
exports. However, the data show no African country's traditional exports came close to
matching the 1990-99 rate of growth of world trade. Traditional exports of all African
countries, except for South Africa and Malawi, experienced negative global demand
growth during 1995-99, and in some cases the declines were dramatic. Growth rates for
Mali's traditional exports (largely cotton) fell by about 15 percentage points (from 6 to -
9.2 percent), while the declines in annual growth rates for Ethiopia, Uganda and Angola
were 16 percentage points or more. Exporters of traditional products seemingly are
vulnerable to important adverse demand and price shocks when global economic activity
weakens, as it did during the period of the East Asian financial crisis.
Over the last decade, world trade growth (5.7 percent) was roughly double that for
income, as measured by GDP. On average, our income elasticity estimate for Africa's
traditional exports is just over one-third (0.36). This implies that, if GDP expands at its
recent rate of 2.5 percent, global trade in traditional products should grow by under one
percent per year. As such, continued reliance on traditional exports will significantly
extend Africa's marginalization in world trade. This trend could be reversed, or the rate
of marginalization slowed, if Africa achieved major competitive gains for these products
to compensate for their relatively low demand growth. However, a recent analysis of
Africa's supply capacities found no evidence that these competitive gains were occurring.
The recent record provides no indication that the longer-term deterioration in
traditional product prices has reversed. Over 1990-99, average real prices for all
traditional products declined by about 24 percent. In a few cases, like coffee and lumber,
where some modest improvement occurred, real prices still remain well below their 1980
levels. In addition, long term price projections by the World Bank reinforce the basically
negative outlook for traditional products and most commodities.
B. Price Instability Problems
Traditional product price instability is a major problem for exporters. Average
annual price changes for these goods generally exceeded those for the all non-oil
commodity price index, while one-half the traditional products experienced average price
iv
changes that were at least 50 percent greater. However, annual data clearly understate
instability problems since traditional product prices often experienced sizable consecutive
year directional changes. Over a three year period, consistent directional price shocks as
high as 101 percent occurred, while changes of 150 percent were observed in four
consecutive year data. These major price swings are generally associated with a
"collapse" of traditional product prices as, over 80 percent of the time, they were in a
downward direction.
The question of whether shifting the composition of exports from unprocessed to
processed traditional products would reduce price and export earnings instability is
examined. This possibility exists if demand for processed traditional products like
chocolate, tobacco manufactures, or ferrous metals are relatively stable, or if
"administered" pricing is used for these goods. The supporting evidence for this
proposition is strongest for traditional products where further processing is normally
labor intensive, but no similar pattern occurs for foodstuffs and most metals. Over the
last decade there is little evidence that prices for processed traditional products were
rising faster, or falling less, than those for unprocessed products. However, prices for
processed traditional products often incorporate a substantial "mark up" over those
exported in raw form.
C. Implications of the Competitive Environment
Changes in Africa's ability to compete in global, markets have the potential to
substantially alter what the region should expect from its traditional products. If Africa's
global market shares for these products experienced substantial erosion this would make
the already poor demand and price expectations worse. However, the overall competitive
changes during the last decade were so small that their general influence was negligible.
However. for one or two individual traditional exports, like copper, a significant erosion
of market shares further worsened African expectations for these products.
While Africa generally maintained its ability to compete with other foreign
suppliers of most traditional goods, a related question concerns the importance of
government imposed trade restrictions which place Africa at a competitive disadvantage
vis-a-vis local producers. Available data suggest C)ECD protection facing most
traditional products is generally low, although several agricultural products, like sugar
and tobacco, are important exceptions. In these cases, industrial countries have the
opportunity to significantly improve market access conditions for specific traditional
products. However, trade barriers facing Africa's traditional products in many
developing countries are sufficiently high that their liberalization could improve the
outlook for these goods.
v
D. Growth Prospects for African Exports
An "export growth prospects" index is used to empirically assess what African
countries should expect from their traditional and non-traditional exports. The index
facilitates comparisons of prospects for any given exporter with those of other regional or
non-regional countries, or with the general growth in world trade. Numeric values for the
index show Africa should expect its traditional export's growth to fall well short of that
for world trade. The index also shows the growth prospects for Africa's non-traditional
exports are often more favorable. However, non-traditional exports probably could not
significantly improve the general short-term outlook for Africa's exports since they
normally constitute a very small share of most Africa countries' trade. Short to medium
term prospects can be strongly affected by the SSA countries ability to become relatively
low cost producers and to remove domestic anti-export biases.
This study's message for Africa is two fold. First, Africa must diversify away
from traditional products or continue to experience serious negative trade effects
including; (i) declining or relatively low growth in global demand for these goods, (ii)
falling real prices for traditional products, (iii) very unstable prices and export earnings,
(iv) a continued marginalization in world trade, and (v) diminished growth and
industrialization prospects. However, there is no evidence that any general
diversification is occurring. Domestic and international policy initiates must assign a far
greater importance to the need for diversifying Africa's exports.
Second, it is unlikely that major shifts in the composition of exports can occur in
the short to medium-term. As such, the removal of general anti-export biases in African
countries' domestic policies, as well as initiatives to promote more competitive (low cost)
prices for traditional exports, still require immediate attention. Future markets for
traditional products will be highly competitive and African countries failing to implement
policies promoting production efficiencies and lower costs should expect to experience
major competitive export losses for these key items.
vi
What Can Africa Expect From Its Traditional Exports?
Francis Ng and Alexander Yeats
I. INTRODUCTION
Conventional thinking alleges several unfavorable demnand characteristics for the primary
commodities and raw materials that constitute Sub-Saharan Africa's traditional exports may
jeopardize the region's growth and industrialization prospects.' First, empirical evidence
suggests the income elasticities of demand for these goods are generally well below unity (See
Stern et al 1976). If true, this would tend to diminish Africa's importance in world trade relative
to exporters of high income elasticity goods, like machinery, chemicals, and transport equipment,
and also adversely influence the region's relative economic growth rate. Second, the level of
demand and prices for primary products can be strongly are affected by cyclical changes in
economic activity in major importing countries. Some economists previously suggested these
'"induced" demand changes were an important cause of instability in commodity prices and
revenues that, purportedly, had serious adverse implications for development planning and
industrialization.2
Third, it has been argued that inherent weakness in long-term demand will cause real
commodity prices to fall relative to those for manufactures that, in turn, would cause the terms-
of-trade for African countries to deteriorate.3 For some products, the weakness in demand was
thought to be exacerbated by competition from synthetics. As an example, exports of hard
fibers, like Agave or Sisal, have been reduced by competition from man-made fibers, just as the
replacement of some metals by plastics has reduced global demand for metal ores. Finally, it has
been asserted that trade barriers in major importing markets imay have an adverse impact on the
level of demand for, and structure of, some commodity exports (For earlier statements on the
purported nature of this problem see Balassa 1968, Basevi 1966, or UNCTAD 1969, 1973).
Would the removal of any post-Uruguay Round trade barriers markedly improve expectations for
Africa's traditional exports?
With regard to the policy discussion of these issues, it should be noted that many key
propositions were formulated on the basis of empirical evidence pertaining to the 1950s and
1960s. Important changes have since occurred in the global economy. UNCTAD reports less
IAlthough, a few Sub-Saharan African countries progressed in shifting their exports toward manufactures, primary commodities
and raw materials are still of far greater relative importance. Ng and Yeats (2000., p. 19) show these latter goods constitute about
three-quarters (by value) of the total 1998 exports of the 14 largest African countries and about 87 percent of the exports of 13
mid-sized African countries.
2 See Cuddy (1978), MacBean (1966), Michaely (1962) or Lim (1976) for useful earlier discussions and empirical evidence on
these issues. To counter the effects of unstable demand for primary products UNCTAD(1 972)(1976) proposed the creation of a
"common fund" that would purchase, or sell, stocks of 18 "core" commodities in a counter-cyclical manner to stabilize prices.
However. several individuals subsequently observed that, if supply fluctuations vvere the source of instability, a common fund's
operation would further de-stabilize prices and export revenues.
3Chief advocates for this argument were Raul Prebish, former chairman of the UN Economic Commission for Latin America.
and Hans Singer. See Hogendom (1987), Findlay (1980) or Spraos (1980) for discussions of the issues and relevant empirical
information.
than 50 percent of world trade consisted of manufactures in the mid-1950s while their current
share is about 75 percent. The present share of commodities and raw materials (approximately
25 percent) is about one-half what it was in the mid-1950s -- it would now be about 20 percent if
crude petroleum is excluded. One factor responsible for this shift in the composition of trade
was the conversion of many important commodity producing countries into exporters of
manufactures. This conversion started with the Asian NICs in the late 1960s and early 1970s,
followed by a group of "second tier" countries, like Malaysia and Thailand, in the late 1970s and
1 980s. Today, more than 60 percent (by value) of the total exports of former largely commodity
producing countries like Brazil, China, India, Malaysia, Mauritius, Pakistan and Thailand consist
of manufactured goods.4 Has this major re-orientation of global production and trade toward
manufactures altered prospects of the fewer remaining commodity exporters, like those in
Africa?5
4 Some countries re-oriented production and trade toward manufactures at remarkable speed. In 1970, only 4.7 percent of
Thailand's exports were manufactures, yet these goods' share was 66 percent in 1990. Over this period, the share of
manufactures exports rose from 2 to 68 percent for Mauritius. In 1970, about three-quarters of Singapore's exports consisted of
commodities, yet their current share is only about 15 percent.
5 This might occur if the declining number of commodity exporters caused the global supply curve for these goods to shift
upward and to the left. However, productivity increases attributable to increased mechanization may limit, or reverse, the
magnitude of any such shifts. Alternatively, the impact of diminished reserves of some non-renewable commodities, like metal
ores, might have a negative impact on supply and exert upward pressure on prices. Such issues received little attention in the
earlier debates on prospects for commodity exporting countries.
2
Box 1. Major Findings of a Companion Study of Sub-Sahairan Africa's Supply Capacity
An earlier study undertaken for the World Bank's Africa Region examined production and supply
constraints of Sub-Saharan African countries (Ng and Yeats, 2000). Its major findings, which are also relevant to
the present investigation, were as follows;
During the last three decades global Sub-Saharan African exports either declined in absolute terms or
expanded at a slower pace than world trade. Sub-Saharan Africa accounted for 3.1 percent of world exports in the
late 1950s, yet by the mid-1990s this share fell to 1.2 percent. UN COMTRADE statistics show this reduction was
largely due to the erosion of Africa's competitive position in international markets. For the region's 30 most
important non-oil exports combined, Africa's import market share declined by over 11 percentage points (from 20.8
to 9.7 percent, which implied annual trade losses of about $11 billion. The value of these losses is about the same as
current OECD official development assistance (ODA) to Africa.
For the 14 largest African countries, as a group, manufactures share of all exports rose from 17 to 27
percent over the last decade. However, much of this increase was due to Mauritius, Madagascar and South Africa,
although several "unusual"' products, like precious stones. increased the share of manufactured exports from a few
other countries. No similar increase occurred for a group of 13 "mid-sized SSA countries where the share of
manufactures held constant at 13 percent.
No major expansion occurred in the diversity of products exported by most Sub-Saharan African
countries, although there were a few exceptions like Madagascar and Kenya. Indeed, the product concentration of
some African countries' exports became more concentrated over the last decade. Africa continues to be heavily
dependent on a relatively few commodities which have been the region's traditional exports.
An analysis of recent changes in Africa's exports indicates no general increase occurred in the number of
industries in which most countries have a "revealed" comparative advantage. This is consistent with statistics
showing Africa generally failed to diversify its export base and, in several countries, trade became more
concentrated. That is, a fewer number of products were being exported at the end of the decade than at the
beginning.
There is little evidence that the relative importance of exports of processed domestically produced
commodities increased, nor do the data indicate that intra-industry trade between Africa and other countries grew.
Although other studies suggest the rapidly growing international trade in parts and components has been a major
factor promoting interdependence and globalization little evidence was found that Africa was an important
participant in this activity.
Evidence was cited that strongly suggested the recent "lackluster" trade performance of African countries
was largely due to an unfavorable internal environment. Cross-country indices of the quality of African governance,
trade, fiscal, monetary and legal policies indicate major scope for improvement exists. The business climate in
Africa appears to be distinctly inferior to that in many countries which compete with the region for foreign
investment.
Source: Conclusions drawn from Ng and Yeats (1997)(2000)
This study examines recent empirical information relating to these points. It proposes
specific criteria for identifying Africa's "traditional products" and then determines how
important these items are in current regional exports. Next, the implications of price trends and
estimated income elasticities for traditional products over the last decade are examined in order
to assess what Africa might expect from these goods in the future. This section also analyzes
changes in the direction of trade for traditional products to determine whether the relative
importance of OECD markets has been changing, or whether important changes have occurred
3
in the countries originating these exports. Third, we attempt to determine whether expectations
for earnings growth and price stability might be improved if the composition of Africa's
traditional exports shifted from primary to processed forms of these goods. That is, would
expectations be significantly improved if Africa shifted exports from (say) raw cotton to cotton
thread or fabric? Fourth, the study assesses the importance of tariffs and nontariff barriers in
major markets and attempts to determine what effects their removal might have. The study
closes with the application of a new "trade growth prospects" index that numerically shows how
relatively favorable, or unfavorable, expectations should be for a country's traditional and
nontraditional products. The index allows an individual SSA country to assess its export growth
prospects relative to world trade, or to those of other African exporters. The study closes with a
discussion of the policy implications of the empirical findings.
II. DATA AND METHODOLOGY
The key question addressed in this study is what can Sub-Saharan Africa expect from its
traditional exports? As such, the analysis primarily focuses on the characteristics of global
demand for the types of goods Africa exports, and not on the export performance of the African
countries themselves. A central concern is whether specific demand characteristics for these
exports would produce below average rates of growth and extend the region's marginalization in
world trade.6 Given that most African traditional exports are primary commodities, the question
as to whether regional exports have demand characteristics that differ significantly from other
commodities is also addressed. This possibility exists since many African exports like cocoa and
coffee are tropical products that generally can only be produced by countries in southern
locations.
A. Statistical Issues
Key Observations
Given that this investigation focuses on global demand prospects for Africa's
traditional exports, it minimizes the problem of Sub-Saharan African countries widespread
failure to report their trade statistics to UN COMTRADE. Rather, demand prospects for these
goods can be analyzed from readily available UN import statistics for OECD and most
developing countries. These available countries account for about 90 percent of world trade.
For relevant empirical information needed to address the issues, import statistics
compiled by the United Nations and maintained in this organization's COMTRADE records
were utilized. At the time this investigation was initiated, annual UN COMTRADE trade
statistics through 1999 were available for over 70 developed and developing countries. These
records included all the original OECD members as well as most larger developing countries like
6 Earlier the authors examined the influence of supply or competitive problems on African exports (Ng and Yeats 1997 and
2000). See Box I for a summary of the major findings. One striking conclusion was that erosion of global market shares for the
SSA countries' 30 largest export products since the early 1960s caused annual revenue losses of approximately $11 billion - a
figure about equal to official development assistance to the region. Inappropriate anti-competitive domestic policies were cited
as the major reason for the erosion of Africa's ability to compete. The present study largely focuses on global demand
characteristics for Africa's major exports in order to determine whether they offset, or reinforce, the adverse supply effects.
4
China, India, and Indonesia. Our comparison of UN COMTRADE with the highly aggregate
IMF Direction of Trade Statistics indicates the countries available in COMTRADE account for
about 90 percent of world trade (see the notes to Table I for a listing of these countries). The
major gaps in the UN statistics were in data for most states of the former Soviet Union, and
many Sub-Saharan African countries, themselves, who chronically fail to report to the United
Nations. The lack of data for the latter should have a negligible effect on our analysis since
relatively little regional intra-trade appears to occur for Africa's traditional export (Yeats 1999).
Given this study's global focus, the required aggre'gation of many individual country
trade statistics, often at low levels of product detail, would have posed serious problems.
However, a trade data access and manipulation program developed within the Bank (named
WITS for World Integrated Trade System) facilitated this aspect of the analysis. WrrS could
both access UN COMTRADE records and aggregate trade statistics, across products and
countries, at both highly aggregate and low levels of prodluct detail. Since the UN records
contained matched annual trade value and quantity data, WITS could also compute unit value
(price) statistics back to the early 1960s, at least for revision I of the SITC system.7 However,
our analysis largely focuses on developments during the 1990s when many former large
commodity exporters, like China, Brazil and India, had largely shifted the their export profiles to
manufactures so we based our analysis on more detailed SITC Revision 2 statistics.
An additional point concerns the selection and treatment of the African countries whose
export prospects are to be assessed. Following the procedures employed in our earlier study (Ng
and Yeats 2000), we differentiate between 14 "larger" African exporters which had 1999 exports
of over $1 billion, and a second group of 14 mid-size countries with exports of over $250
million. This distinction is based on the fact that larger exporters like South Africa, Zimbabwe
and Kenya often have a more diversified export base than the mid-sized countries although, this
is not true for the large African oil exporters. Since, it has been asserted countries with a more
diversified trade base may experience less instability in their total export earnings, and also
experience less adverse terms-of-trade swings, we made the distinction between large and mid-
sized countries to evaluate this proposition.8 Finally, since the remaining "small" countries, with
exports of under $250 million, are generally dependent on relatively fewer commodity exports
we felt it more efficient to evaluate their trade prospects separately in an annex to this report.
7 While all import values are reported by UN COMTRADE in US dollars. and can be aggregated across countries, non-
standardized quantity reporting practices may make it impossible to compute a global unit value for a good. For example, the
United States may report quantity imports in terms of actual numbers while the EU may report imports of the same good in
kilograms. Division of the combined import values by the combined dissimilar quantity units would produce a nonsensical unit
value estimate. For this reason, our later analyses of price behavior may be based on statistics from the largest import markets
under the assumption that, with arbitrage, these will parallel global patterns.
8 These assertions originate from a debate in the 1960s and 1970s about the relationship between country size and trade
concentration. Khalaf (1974), for example, presents evidence that smaller countries may have more concentrated export profiles,
purportedly due to their more limited resource base or constraints associated with small domestic market size. This debate had
important economic and political implications in that it raised the question whether there is a minimum "viable" size for
independent countries. Most African countries attempted to offset constraints associated with small domestic markets by joining
regional trade arrangements.
5
B. Identifying "Traditional" Products
Key Observations
Previous empirical investigations that attempted to identify traditional or non-
traditional exports generally used an "export share criteria" to differentiate between these
types of goods. That is, a traditional export product has been defined as one that accounted
for at least three percent of a country's total exports. We utilize a procedure that accounts for
both the total value of a product and Africa's global market share for the good. The
traditional products defined using this criteria account for about 70 percent of total regional
exports.
An important question is how "traditional" products should be defined. One approach
could rank African exports by value and then select the largest items. There are several
attractions, and potential problems, with this procedure. The first problem is that the resulting
list is dominated by crude petroleum which accounts for about one-third of the region's total
exports. Any aggregation of petroleum and non-energy traditional products could make it
difficult to correctly identify underlying trends and prospects if market conditions for oil are
significantly different than those for other goods. Also, high export values need not necessarily
indicate the region has a comparative advantage in a good. Ng and Yeats (2000) show SSA
countries do not have a revealed comparative advantage in several items, like refined petroleum
products, that appear in a "high value" list. This suggests a more useful approach would be to
first define traditional products as those for which Africa has a relatively high share in global
markets (this would be consistent with the region having a revealed comparative advantage in the
good) which has been maintained over a number of years.9
For a first pass at defining traditional products, we compiled a list of 31 items in which
Africa had its highest global market shares which in all cases were over 10 percent. In other
words, these goods have production characteristics that allowed Africa to traditionally maintain a
strong export presence in global markets. The market share criteria was used to identify
products, like goat or sheep hides, which had relatively low global or regional export values, but
Africa was still a major factor in international markets for these goods. However, we recognize
that some high value products should be added to the "traditional" list if their share in SSA
exports was consistently above their share in world trade (this, essentially, is the definition of
revealed comparative advantage). Employing this "dual" criteria we added 7 items to the
traditional product list. Petroleum is classified as a traditional product, but we examine its
9 A literature search revealed several previous of attempts to define "nontraditional" and "traditional" exports which helped
clarify our thinking on this issue. Most empirical studies employed export share thresholds to distinguish between the two classes
of goods. In Labys and Lord (1990), for example, the dividing line between traditional and nontraditional exports is set at I
percent of total merchandise trade. Balassa (1977, p. 17) defined non-traditional primary products as those accounting for less
than 2 percent of total exports. In an earlier study involving all exports, nontraditional products were defined as those accounting
for less than 3 percent of all exports (Balassa 1971). Recently, in its World Development Indicators the World Bank (1997, p.
259) defined "traditional exports" as the ten largest three-digit commodity groups in a country's exports in a base year (1983-84).
unless the ten do not account for at least 75 percent of total expons. In this case more three-digit groups are added until at least
75 percent is reached. Nontraditional exports are, by implication, all of the rest. Our definition is essentially consistent with the
approach used by the Bank except that we work at a lower four-digit SITC level of detail and also introduce a market share
criterion.
6
prospects separately in an annex. Combined, our list of petroleum and non-energy traditional
products account for over 70 percent of Africa's current total exports.
Table I lists the 38 four-digit SITC (Rev. 2) traditional products, it reports the total
global value of trade in each item during 1990, 1995 and 1999, and also shows Africa's share of
world trade in each product at the beginning and end of the last decade. Altogether, these
traditional products accounted for about 55 percent of Sub-Saharan Africa's non-oil exports.10
Africa is a major factor in world trade in cocoa beans, manganese ore, uranium, and hard fibers
as the region has a global import share of more than 50 percent for each product. It should be
noted that the list in Table 1 is dominated by primary commodities as only one manufactured
good (ferrous alloys) satisfied our criteria for inclusion. Another notable point is that products
like palm oil, palm nuts and kernels, copra, groundnuts or vegetable oil cake, which historically
were important, are not included due to their greatly diminished role in current regional exports
(see Box 2).
An interesting question concerns the magnitude of iAfrican trade losses reflected in the
market share erosion for these products. If Africa maintained its 1960s market shares for these
items its current exports would now be $7.7 billion higher. C'ompetitive share losses for palm oil
are of major importance ($1.8 billion) and are about $1.1 billion for both alumina and unmilled
maize.
10 We distinguish between non-oil and petroleum traditional products for several reasons (see Annex 2). Petroleum is produced in
a relatively few SSA countries and, unlike the other traditional products, most African countries are net oil importers. As such,
favorable price prospects for oil may have favorable implications for the relatively few producers, but have unfavorable
implications for most other African countries who are net oil importers. We intentionaliv excluded diamonds from our traditional
product list for several reasons. First, UN COMTRADE records generally do not report quantity units for diamond imports so
import unit values could not be calculated. Second, relatively large discrepancies in partner country statistics for unset diamonds
suggests false invoicing or smuggling probably imparts an important bias in trade data for these goods.
7
Box 2. Implications of the Demise of Some African "H1istorical" Exports!
If one attempted to tabulate a list of Africa's traditional exports on the basis of trade statistics for the 1960s
or 1970s, the items included undoubtedly would be quite different from those in Table 1. Four decades ago, Africa
was a major producer of several vegetable oil and oilseed products like palm oil or palm kernel oil, it had an
important position as an exporter of metaliferous ores including copper and tin, and also had a relatively high share
of world exports of foodstuffs like maize, rice, meat extracts, and fish oils. On the basis of actual world trade shares
in the 1960s, Africa appeared to be on the verge of becoming an important global exporter of products like:
preserved meat, preserved fruit, non-wheat flour and meal, fruit jams and jellies, improved or reconstituted wood,
and animal feeds. However, over the next four decades Africa experienced massive losses of global market shares
for these goods with the result that the value of the region's exports at the end of the century were often lower than
in the 1960s. As such, many of these products should not now be considered traditional exports, but should be
thought of as historical exports which do not now have an important influence on expectations for the region's
current trade performance.
The statistics shown below illustrate this point. As an example, in 1962 African exports of palm nuts and
kernels totaled $75 million, and the region accounted for 91 percent of world trade in this commodity. However, by
1999 exports fell to under $3 million and Africa's global market share was almost one-tenth of what it was in the
1960s. Similarly, Africa's 1962 global market shares for groundnuts, palm kernel oil, and palm oil ranged from 51
to 83 percent, but are now only about 2 to 3 percent, and the combined exports of these items are currently lower
than they were four decades ago. This major deterioration in export performance explains why some, possibly
expected, products have not been included in this study's list of traditional products.
African Exports ($000) Africa's World Trade Share (%)
Commodity (SITC)* 1962 1999 1962 1999
Palm Nuts & Kernels (2213) 75,061 2,861 91.1 9.9
Groundnuts Green (2211) 184,279 24,542 83.4 3.2
Palm Kernel Oil (4224) 8,941 15,816 53.1 2.2
Palm Oil (4222) 36 11,634 50.9 1.0
Natural Abrasives (2752) 13,247 2,059 27.6 0.2
Fixed Vegetable Oils, nes (4229) 8,555 10,131 16.0 1.3
Alumina (5136) 25,608 60,330 13.8 0.7
Unmilled Maize (0440) 18,762 20,725 13.2 0.2
Fur Skins (2120) 37,855 757 12.3 0.1
Vegetable Oil Cake (0813) 47,401 49,264 10.9 0.8
Copper Ore & Concentrates (2831) 11,492 44,633 8.7 0.9
Oils of Fish (4111) 7,825 1,453 8.6 0.4
Bovine & Equine Hides (211 1) 18,155 24,627 8.0 0.9
Unwrought Tin (6871) 21,761 267 7.8 0.0
Meat Extracts (0133) 2,120 759 7.6 0.6
Tin Ores and Concentrates (2835) 5,851 9,139 6.0 0.5
Plywood (6312) 12,149 48,659 5.2 0.6
Glazed or Polished Rice (0422) 6,346 601 3.5 0.0
TOTAL OF ABOVE 505,444 328,257 13.9 1.0
* Since Revision 2 data were not available until the mid-1970s, these statistics are based on the earlier Revision 1
classification which first became available in 1962.
III. LONG TERM DEMAND PROSPECTS
A key question relating to what Africa should expect from its traditional exports
concerns longer-term demand prospects for these goods. Several procedures could be employed
for addressing this issue. One could, for example, calculate the global import growth rate for
each traditional product and then compare these rates with those for other types of goods. Such
comparisons could help indicate whether there are some traditional products with relatively
favorable, or unfavorable, demand prospects. This constitutes a product specific approach
concerning what Africa might expect from traditional exports. Second, a country specific
approach could focus on prospects for the specific "basket" of goods a given African country
exports. The issue here is whether differetces in the composition of traditional exports from
individual SSA countries can produce significant differences in overall export prospects.
A. Global Trade Trends for Traditional Exports
Key Observations
Over the last decade, global trade in Africa's traditional exports grew at a rate of 1.9
percent, or about one-third the corresponding rate for all goods. This is a continuation of
trends which are observed in data for the 1980s. Furthermore, 1990-1999 trade growth rates
for over 40 percent of the traditional products were actually negative. The last half of the
decade witnessed a major collapse in demand for many of these goods with 1995-99 global
imports of several traditional products falling by more thanl ten percent. These developments
contributed to the further erosion of Africa's global trade share for all goods which fell from
1.8 percent in 1990 to 1.3 percent in 1999.
Table I provides empirical information on key global trade trends for Africa's traditional
exports over the last decade. The right-most column shows the annual growth rate of world trade
in each item, while similar growth rates are shown for the 1'990-95 and 1995-99 sub-intervals.'1
For comparison, the lower half of the table shows statistics on trade changes for several broad
product groups like all manufactures. These items have been included for use as a "benchmark"
for evaluating the relative growth in traditional products trade. Finally, the table also shows
Africa's world trade share for each product over the decade which, in the aggregate, were
relatively stable at over 1 3 percent.
The first impression from these statistics is that no really positive points are evident.
Over the decade, the average annual growth rate for all traditional products was 1.9 percent,
while the annual growth of world trade (5.7 percent) was 3 times higher. However, the disparity
is even greater if comparisons are made with all manufactures which grew at an annual rate close
to 7 percent. Furthermore, the last half of the decade witnessed a major collapse in demand for
" The first half of the last decade witnessed an impressive expansion in demand and prices for some primary commodities,
including a number of traditional products (Ng and Yeats 2000) or World Bank (2000). Prices and demand declined sharply
from about 1997 when global trade in traditional products fell at an annual rate exceeding 3 percent. The evidence suggests, see
Table 7 which follows, that the Asian financial crisis had a major adverse impact on demand and prices as regional imports of
some products, like cotton, experienced major contractions that had no parallel in .Europe or North America.
9
many of these goods with 1995-99 global imports of several products falling by more than ten
percent. These developments contributed to the further reduction of Africa's global trade share
from 1.8 percent in 1990 to 1.3 percent in 1999 (see Table 1).
A second negative point is that the annual global trade growth rates for over 40 percent
(17 of 38) of the traditional products was negative over the decade. Global demand for both
unwrought copper alloys and goat skins fell by more than 15 percent annually, while trade in
manganese ore and sheep skins declined at annual rates exceeding 5 percent. Major consecutive
year production surpluses caused a collapse in sugar prices which resulted in a 25 percent decline
in the value of trade over the decade, while trade in goat and sheep skins has been declining
since the mid-1970s. Several traditional products, like cottonseed and tobacco leaf parts, that
experienced relatively high growth rates are globally relatively unimportant with annual world
trade under $200 million. Limited global market size would seemingly restrict potential benefits
from African efforts to expand these goods exports.
Table 2 provides an overview of the global trade changes for traditional exports by
combining the individual product data into 10 groups with similar production characteristics or
end uses. For example, the tropical beverage group incorporates statistics for cocoa beans,
coffee beans, tea, and cocoa powder, while the ferrous ores and metals group consists of iron ore
and ferro-alloys (the notes to Table 2 indicate the product composition of each group). The table
shows global imports of each group and imports from Sub-Saharan Africa along with similar
trade statistics for all agricultural raw materials, and ores, minerals and metals. Since the product
composition of the traditional products is somewhat similar to these aggregate groups, it is of
interest to determine if recent trade changes for Africa's traditional exports differed substantially
from these groups of related products.
10
Table 1. The Growth of World Trade in Sub-Saharan Africa's Traditional Exports (1990-99)
Sub-Saharan Africa's Reported Global hinports Average Annual Global lImport
Global Trade Share % From All Countries (.$million)* Growth Rate Fromi All Contrities(%
Traditional Afriean Export Produict (SITC No.) 1990 1999 1990 199-5 1999 1990-95 1995-99 1990-99
Cocoa Beans (072. 1) 63.6 77.5 2,094 2,819 2,968 6.1 1.3 4.0
Manganese Ore (287.7) 56,3 57.2 914 696 517 -5.3 -7.2 -6.1
Uraniumi or Thoriumi Ore (286.0) 7.6 56.2 74 7 1 64 -0.8 -2.4 -1.5
Sisal or Agave Fibers (265.4) 42.2 52.5 58 54 43 -1.5 -5.6 -3.3
Industrial Diamonds (277. 1) 10.4 43.7 437 344 918 -4.7 27.8 8.6
Sesamie Seeds (222.5) 9.4 32.8 428 495 462 2.9 -1.7 0.9
Groundnut Oil (423.4) 41.4 30.8 365 334 227 -1.8 -9.1 -5.1
Tea (074.1) 27.1 30.7 1,657 1,695 1.800 0.5 1.5 0.9
Metals of the Platinum Group (681.2) 36.6 26.1 6,072 5.782 10.199 - 1.0 15.2 5.9
Other Nonferrous Ores (287.9) 19.9 22.7 2,658 3,241 2,116 4.1 -10.1 -2.5
Saw and Veneer Logs (247.2) 19.0 22.7 5,361 6,307 4,936 3.3 -5.9 -0.9
Parts of Tobacco Leaf orSterns (I121.3) 15.8 21.0 79 133 160 11.1 4.6 8.2
Sheep Skins Without Wool (211.7) 8.0 20.9 618 740 271 3.7 -22)2 -8.7
Products of Melted Metal Ores (278.6) 20,7 20.7 393 494 483 4.7 -0.6 2.3
Ferrous Alloys (671.6) 17.0 20.4 5,712 8.858 6.359 9.2 -8.0 1.2
Raw Cotton (263. 1) 14.9 20.1 7.816 10,304 5,706 5.7 -13.7 -3.4
Cocoa Butter and Paste (072.3) 16.4 20.1 1,614 2.065 2.172 5.1 1.3 3.4
Asbes,tos Simply Worked (278.4) 19.3 19.5 562 503 256 -2.2 -15.5 -8A4
Raw Goat and Kid Skins (211.4) 32.0 19.2 125 70 20 -11.1 -26.4 -18.2
Natural Gumis and Resinis (292.2) 31.0 19.1 256 380 277 8.2 -7.6 0.9
Raw Sugar (061.1) 18.8 19.0 4,385 5,383 3,317 4.2 -11.4 -3.1
Tobacco Stripped (1 21.2) 13.7 1 8.5 3,198 3.927 4,526 4.2 3.6 3.9
Cotton Seeds (222.3) 22.1 17.2 79 144 192 1 2.8 7.5 10.4
Chemical Wood Puilp (251.6) 13.9 15.6 1,025 1,320 918 5.2 -8.7 -1.2
Other Leathers (611.6) 7.3 15.6 1.602 1.640 1,1)89 0.5 -9.7 -4.2
- Beryllium and Titanium (689.9) 19.2 14.5 1,312 2,796 2,364 16.3 -4.1 6.8
- Non-Monetary Gold (971.0) 13.5 13.3 18,457 25,986 25,000 7.1 -1.0 3.4
Metaliferous Nonferrous Wastes (288. 1) 7.5 12.7 1.914 1,987 1,82(0 0.8 -2.2 -0.6
Coffee Green or Roasted (07 1.1) 16.4 12.5 7,880 15,047 11.014 13.8 -7.5 3.8
Natural Calcium Phosphates (271.3) 16.0 1 1.8 1.752 1,~364 1.381 -4.9 0.3 -2.6
Other Coal Not Agglomnerated (322.2) 7.5 10.1 18,411 20.303 18,302 2.0 -2.6 -0.1I
Iron Ore Not Agglomerated (281 .5) 9.7 9.2 7,77 1 8,502 7.429 1.8 -3.3 -0.5
Lumber Shaped Nonconifer (248.3) 8.4 7.8 6,067 8,895 8.613 8.0 -0,8 4.0
Fruit, Fresh or Dried (057.9) 5.5 7.8 5,997 7.775 8.790 8.2 0.9 4.9
Pr-epared or- Preserved Fish (037. 1) 5.8 6.2 3,652 5,406 5.610 5.3 3.1 4.3
Alumyinumn Alloys , Unwrought (684.1) 3.0 4.8 14,964 25,207 20,543 11.0 -5.0 3.6
Shellfish (0360) 4.6 4.6 11,788 17,920 17.101 8.7 -1.2 4.2
Copper Alloys, Ulnwrouight (682. 1) 19.1 4.2 12,197 17,082 11,704 7.0 -9.0 -0.5
ALL ABOVE PRODUCTS 13.5 13.2 159,744 216,069 189,667 6.2 -3.2 1.9
Global Trade in All Goods (0 through 9) 1.8 1.3 3,195,0129 4,713,653 5.262.729 8.1 2.8 5.7
All Goods less Petroleuin(O to 9 -3) 1.2 0.9 2,846,232 4,365,128 4.891,379 8.9 2.9 6.2
All Manufactures (5 through 8 - 68) *50.4 0.4 2,243.8 10 3.509.707 4,050,750 9.4 3.6 6.8
*The totals are the combined imiports of all original OECD miemibers pluis Algeria, Argentina, Bangladesh, Barbadosq, Belize, Bolivia, Brazil, Chile, China, Colombia. Costa Rica. Cypnms. Ectiador.,
Egypt, El Salvador, Greenland, Guatemiala. Honduras, Hong Kong (China). Hungary, India, Indonesia, Israel, Jamaica, Kenya. Rep. of Korea, Macau IClhina), Malaysia, Malta, Mauritius, Mexico,
Nepal, Nicaragua. Pakistan, Panaina, Paraguay. Peru. Philippines, Poland. Romania, Sinlgapore, SACU, Taiwan (China). Thailand, Trinidad & Tobago, Turkey, Tunisia, Uruguay anid Venezuela.
55This produICt was added on the basis of its overall size in SSA exports and the fact that trade data show the region hias a revealed comiparative advantage in its produiction.
Souirce. Based on the reported UN import statistics of the countries listed in the note,
Table 2. The Growth of World Trade in Major Groups of Sub-Saharan Africa's Traditional Exports (1990-99)
Reported Imports from Sub- Reported Global Imports Average Annual Global Import
Saharan Africa ($million) From All Countries ($million)* Growth Rate From All Countries (%)
Traditional Export Product Group* 1990 1999 1990 1995 1999 1990-95 1995-99 1990-99
Tropical Beverage & Related Products 3,337 4,664 13,245 21,626 17,954 10.1 -4.6 3.4
Non-Ferrous Metals and Ores 6,441 5,538 40.105 56,862 49,327 7.2 -3.5 2.3
Ferrous Metals and Ores 1,731 1,979 13,483 17,360 13,788 5.2 -5.6 0.2
Fresh and Preserved Seafood 738 1.230 15,440 23.326 22,711 8.6 -0.5 4.4
Other Foodstuffs 1,359 1,394 11.175 13,987 12,796 4.6 -2.3 1.5
Hides and Leather Products 206 231 2,345 2,450 1.380 0.9 -13.5 -5.7
Minerals and Products 1,843 2,155 21,118 22,664 20,422 1.4 -2.5 -0.4
Lumber and Products 1,750 1,988 12,709 16,902 14,744 5.9 -3.4 1.7
Fibers and Other Agricultural Materials 1,654 2,076 11,230 14,562 10,627 5.3 -7.6 -0.6
Gold and Industrial Diamonds 2,535 3,721 18,894 26,330 25,918 6.9 -0.4 3.6
TOTAL OF ABOVE PRODUCTS 21.594 24,976 159,744 216,069 189,667 6.2 -3.2 1.9
Total Excluding Gold and Diamonds 19,059 21,255 140,850 189,739 163,749 6.1 -3.6 1.7
MEMO ITEM
All Foods and Feeds 13,117 17,170 392,450 546,653 502,689 6.9 -2.1 2.8
All Agricultural Raw Materials 4,202 4,489 103,020 139,964 109,409 6.3 -6.0 0.7
All Ores, Minerals and Metals 9,530 8,708 132,036 176,955 158,645 6.0 -2.7 2.1
All Manufactured Goods** 9.474 16,034 2,243,810 3.509,707 4,050,750 9.4 3.6 6.8
ALLTRADEDGOODS 57,243 68,836 3,195,029 4,713,653 5,262,729 8.1 2.8 5.7
*The groups listed below are composed of the following traditional products; Tropical Beverage Products (cocoa beans, tea, cocoa butter and paste, and coffee); Non-Ferrous
Metals and Ores (manganese ore, uranium or thorium ore, metals of the platinum group, other nonferrous ores, beryllium and titanium, metaliferrous nonferrous waste,
unwrought aluminum alloys, unwrought copper alloys); Ferrous Ores and Metals (ferro-alloys, iron ore); Fresh and Preserved Seafood (shellfish, prepared or preserved fish);
Other Foodstuffs (sesame seeds, groundnut oil, raw beet and cane sugar, fresh or dried fruit); Hides and Leather Products (sheep skins without wool, raw goat and kid skins, other
leathers); Minerals and Products (simply worked asbestos, products of melted metal ore, natural calcium phosphates, other coal not agglomerated); Lumber and Products (saw and
veneer logs, natural resins and gums, chemical wood pulp, non-conifer shaped lumber); Fibers and Other Agricultural Materials (sisal or agave fibers, parts of tobacco leaf or stem,
raw cotton, tobacco stripped, cotton seed); Gold and Diamonds (non-monetary gold, industrial diamonds).
**What appears to be a fairly robust growth in imports of manufactures from Africa is something of an anomaly due to a relatively small number of unusual products. The rapid
expansion of diamonds, especially from Angola and the Democratic Republic of the Congo, account for about one-fifth the overall increase. While it might be argued that
diamonds are not a manufacture they are so classified due to a defect in the original SITC system which failed to distinguish between raw and cut diamonds. A case can be made
that the latter are in fact a manufactured good. Other unusual developments that had an importance influence on the 1999 manufactures total was the registration of flags of
convenience in Liberia (which is recorded as ships and boats in the SITC) and the leasing of aircraft by several African countries like Ghana. See Ng and Yeats (2000, p 16).
Source: Based on the reported UN import statistics of the countries listed in the notes to Table 1.
Three conclusions follow from these statistics;
Over the last decade, global trade growth for each traditional product group fell well
short of corresponding rate for world trade. Trade in the traditional hides and leather group fell
at an annual rate of almost 6 percent, due largely to a long term decline in global demand for raw
hides. Fresh and preserved seafood had the highest growth rate (4.4 percent) of any traditional
group, but this was still about one-quarter lower than the rate for world trade.
Whether or not gold and industrial diamonds are included has little influence on the
overall trade performance of all traditional products. If the former are excluded the traditional
product growth rate is reduced by only two-tenths of a percent. In part, this is due to the
relatively low share (13.7 percent) of gold and industrial diamonds in all traditional products. In
contrast, over one-quarter of all traditional product exports consist of non-ferrous ores and
metals.
For the decade, world trade in all traditional products grew at an annual rate (1.9
percent) which was below that for either the all foodstuffs, or ores, minerals and metals groups,
but higher than that for agricultural materials. The annual :1995-99 rate of global trade decline
for traditional products exceeded that for foodstuffs and ores, minerals and metals, but was less
than that for all agricultural materials. Broadly speaking, 1990-99 trade changes for traditional
products were basically in line with those for other commodities.
In short, these initial statistics suggest that 1990-99 global trade for all Africa's
traditional exports combined was essentially static. It also raises the question of whether there
are African non-traditional exports with more favorable trade prospects (see Box 3).
B. Prospects for Individual SSA Countries
Key Observations
Conceivably, considerable variation could occur in the recent trade performance of
individual African countries depending on their specific "basket" of traditional exports.
However, the data show no African country's traditional exports came close to matching the
1990-99 rate of growth of world trade. Traditional exports of all African countries, with the
exception of South Africa and Malawi, experienced negative global demand growth during
1995-99, and in some cases the declines were dramatic. Growth rates for Mali's traditional
exports (largely cotton) fell by about 15 percentage points (from 6 to -9.2 percent), while the
decline in annual growth rates for Ethiopia, Uganda and Angola were 16 percentage points or
more. Exporters of traditional products seemingly are vulnerable to important adverse
demand and price shocks when global economic activity weakens, as it did during the period
of the East Asian financial crisis.
The empirical information examined, thus far, provides a relatively pessimistic view of
prospects for most African traditional exports. Average annual growth rates for these products
were well below that for world trade, and also below rates for two broader groups of
13
commodities (foodstuffs and ores, minerals and metals). However, the fact that considerable
variation exists in growth rates for individual traditional products (see Table 1) may lead to
important differences in African export performance across countries, depending on the
particular basket of goods traded. Just how much can prospects of individual African countries
vary due to the specific traditional products they export is an important question?
A constant market share analysis can directly address this question. This approach
isolates the influence of changes in global demand for the specific goods an African country j
exports ( Dj) in the absence of any changes in the country's market shares, or diversification
into new product lines. Specifically, the projected impact of demand changes on traditional
exports is derived from,
(1) Dj = so0(Dti - D.i)
where soi is country j's global market share for traditional product i in period o, and Dti and Doi
represent global trade in product i in periods o and t. The right hand side of the equation is
summed over all traditional products to produce an aggregate demand change index for the
country. See Kravis (1970) for one of the earlier applications of this approach.
14
Table 3. Estimated Effects of Demand Changes on Large and Mid-Size African Countries' Traditional Exports (1990-99)
1990 Projected Demand Induced
Traditional Exports of Traditional Annual Rate of Growth in Projected
Exports Products ($ rnillion) Demand Induced Exports (%)
African Exporter (Smillion) 1995 1999 1990-95 1995-99 1990-99
LARGER COUNTRIES
Angola 10 18 15 12.3 -4.6 3.9
Cameroon 841 1.237 1,020 8.0 -3.8 2.2
Congo. Dem. Rep. 1.278 1,944 1,436 8.7 -5.9 1.3
Congo, Rep. 196 230 183 3.2 -4.4 -0.8
Cote d'lvoirc 1.833 2,565 2.410 6.9 -1.2 3.1
Gabon 552 553 428 0.0 -5.0 -2.8
Ghana 945 1.342 1,290 7.3 -0.8 3.5
Kenya 596 805 705 6.2 -2.6 1.9
Liberia 264 311 259 3.3 -3.6 -0.2
Mauritius 346 426 273 4.3 -8.5 -2.6
Nigeria 274 355 329 5.3 -1.5 2.1
SACU 9,124 11,016 11,353 3.8 0.6 2.5
Zambia 1.165 1,672 1,170 7.5 -6.9 0.0
Zimbabwe 703 932 781 5.8 -3.5 1.2
All Above Countries 18.127 23,406 21,652 5.2 -1.5 2.0
MID-SIZE COUNTRIES
Benin 53 74 57 6.7 -5.1 0.7
Ethiopia 200 343 237 11.4 -7.2 1.9
Guinea 50 70 55 7.1 -4.7 1.2
Madagascar 138 213 177 9.0 -3.6 2.8
Malawi 254 313 330 4.3 1.1 3.0
Mali 166 219 135 5.7 -9.2 -2.2
Mauritania 408 507 460 4.4 -1.9 1.3
Mozambique 137 178 142 5.4 -4.4 0.4
Senegal 357 408 356 2.7 -2.7 0.0
Sudan 343 445 275 5.3 -9.2 -2.5
Tanzania 264 393 288 8.2 -6.0 1.0
Togo 202 211 171 0.8 -4.1 -1.8
Uganda 200 359 263 12.4 -6.1 3.1
All Above Countries 2,772 3.733 2,946 6.1 -4.6 0.7
ALL SSA COUNTRIES 21,596 28,076 25,324 5.4 -2.0 1.8
MEMO ITEM:
(Global Trade Statistics)
ALL GOODS 3.195,029 4.713,653 5,262,729 8.1 2.8 5.7
Manufactures 2.243,810 3,509,707 4,050,750 9.4 3.6 6.8
Foods and Feeds 392,450 546,653 502,689 6.9 -2.1 2.8
Agricultural Material 103,020 139,964 109,409 6.3 -6.0 0.7
Ores, Minerals & Metals 132.036 176,955 158,645 6.0 -2.7 2.1
Source: Tabulations based on trade statistics reported to COMTRADE by countries listed in the notes to Table 1.
Table 3 summarizes the results when the constant market share analysis was applied to all
traditional products exported by each of the large and micl-size African countries (Appendix
Table 3 identifies each country's traditional exports and also reports their 1999 trade values).
Shown here are the 1990 values of each country's traditional exports, and 1995 and 1999
projected exports associated with global demand changes. To facilitate cross-country
comparisons, the projected growth rates are shown for the full decade and for two sub-intervals.
15
Finally, the table reports growth rates for global trade in all goods, and in four broad product
groups to provide standards for comparison.
The following points reflected in Table 3 should be noted:
No African country exports what could be called a really superior, or inferior,
combination of traditional products, although there are cross-country differences in the demand
induced growth rates. Angola (primarily an exporter of non-oil traditional products like shellfish
and coffee), Cote d'Ivoire (primarily cocoa beans, cocoa butter, and lumber), and Malawi
(stripped tobacco, tea and raw sugar) have projected 1990-99 demand induced export growth
rates exceeding 3 percent, while Gabon (saw logs, manganese ore, and shaped lumber),
Mauritius (raw sugar), Mali (raw cotton) and Sudan (sesame seeds, natural gums and resins, and
raw sugar) have the lowest projected negative growth rates, all under -2.8 percent.
No African country came close to matching the rate of growth of world trade. The
latter increased at an annual rate of 5.7 percent for the decade which was almost 2 percentage
points higher than that for Angola which had the highest projected traditional product growth
rate (3.9 percent). As a group, demand induced growth rates for the larger African countries (2
percent per year) was almost three times that for the mid-size exporters. The fact that several of
the latter are land-locked probably limits their ability to export some relatively high growth
traditional products like fish and crustaceans.
Traditional exports of all countries, with the exception of South Africa and Malawi,
experienced negative rates of demand induced growth during the 1995-99 period, and in some
cases the declines from the first half of the decade were dramatic. Growth rates for Mali's
traditional exports (largely cotton) fell by about 15 percent (from 5.7 to -9.2 percent), while the
change in annual growth rates for Ethiopia, Uganda and Angola was 16 percent or more. Very
few African countries appear to export a combination of traditional goods that guards against
excessive instability in periods of slowing world trade.
In short, the evidence suggests it is unlikely that a country could export some basket of
traditional products that would generate growth rates that parallel those for world trade. This is
not an impossibility, however, since Table I shows five traditional products, namely, platinum,
industrial diamonds, parts of tobacco leaf or stem, cotton seed, and miscellaneous base metals
grew at a 1990-99 pace that exceeded world trade growth.
C. Implications of Recent Income Elasticity Estimates
Key Observations
Over the last decade, world trade growth (5.7 percent) was roughly double that for
income, as measured by GDP. On average, our income elasticity estimate for Africa's
traditional exports is just over one-third (0.36). This implies that, if GDP continues to expand
at its recent rate of 2.5 percent, global trade in traditional products should grow by under one
percent per year. As such, continued reliance on traditional exports will significantly extend
16
Africa's marginalization in world trade. This trend could be reversed, or the rate of
marginalization slowed, if Africa achieved major compelitive gains for these products to
compensate for their relatively low demand growth. However, a recent analysis of Africa's
supply capacities found no evidence that competitive gains were occurring.
A useful way of assessing implications of the trade performance statistics previously
reported is to compare these data to changes in real income in major markets. Does the recent
evidence continue to support the assumption of low income elasticities of demand for the types
of products Africa exports, or have their prospects improved?. That is, have global real imports
of these goods grown at a pace that comes closer to matching growth rates for real GDP in the
major consuming countries? A related question is whether income elasticities for processed or
semi-processed traditional products (like plywood and veneers) are higher than those for raw
form item (like unworked or simply shaped timber)? If so, could Africa expect more from its
traditional exports by moving up commodity processing chains where such an adjustment is
economically feasible?12 The answers to such questions have an important bearing on Africa's
export prospects.
The income elasticity of demand for a given product j in country k (Ijk) is defined as the
percentage change in demand (imports) for the good attributable to a change in income of a
consuming country. That is, Ijk is defined as,
(2) Ijk = 1(Qjt - Qj0)/Qio] [(Ykt - Yko)/Yko
where Qjt and Qj3 represent the quantity of j consumed in period t and o, respectively, while Yk is
a measure of the level of income in country k. Some previous studies attempted to
"approximate" income elasticities by directly dividing percentage changes in the quantity of
imports of a specific good by percentage changes in real GDP in the importing country, that is,
through use of the ratio of changes in imports to those in incoine.
This approach, however, may provide potentially biased estimates for income elasticities
of demand in that it does not account for the potential effects any price changes which may have
occurred. It also does not account for any changes in the level of competition between domestic
and foreign producers, or changes in tariffs or NTBs facing foreign suppliers. However, for
many of Africa's traditional exports, particularly tropical prodlucts, competition between foreign
and domestic producers in industrial markets is likely to be smnall and unlikely to change quickly
over time.'3
12 Africa may not have a comparative advantage in processing some domestically produced commodities. The fabrication of ores
into metals is generally a capital intensive operation which normally would be undertaken in richer countries. However,
transformation of raw cotton, or wool, into fabric or clothing would seemingly be suitable for local processing. UNCTAD (1975)
discusses the potential benefits for developing countries in shifting the composition of exports to processed commodities. These
include; important job creation effects, it may increase trade contacts and provicLe benefits associated with "outward-oriented"
policies, there may be important linkages from processing industries to other sectors of the economy, it may reduce the instability
of export earnings, and it may produce an increase in export revenues and foreign exchange earnings. In contrast, Roemer (1979)
examines some of the problems may encounter in efforts to increase domestic processing.
17
A more reliable, and theoretically accurate, income elasticity estimate could be derived
by netting out the influence of price changes. Specifically, the projected change in imports due
to price changes is,
(3) (Qjt - Q) * = Qjo jk (Ujt- Ujo)-Uj.
where Uj is the import unit value for product j in the two time periods, and jk represents
published estimates for the price elasticity of demand for the good. The latter were drawn from
several sources such as Stem et. al. (1976). The import unit values used for these estimates were
computed from UN COMTRADE data. Since countries may report different quantity units for
imports our analysis was confined to major markets like the EU(15), Japan and United States
which reported on a common basis. This procedure made it possible to derive an estimate of
income elasticities (Ijk*) with the influence of price effects netted out. Specifically,
(4) Ijk* = [(Qjt - (Qjt - Qj.)* - Qjo)] (Ykt - Yko)/Yko
where Y measures the level of real income in the two time periods.
Table 4 utilized combined 1990 and 1999 import statistics of the EU(15), Japan and
United States to produce estimates for these countries' income elasticities for traditional exports.
The table shows the weighted average trade-income ratio changes and income elasticity
estimates for each traditional product group, as well as that for all products combined.'4 The
range in elasticity estimates within each group is reported, and the specific items with the highest
and lowest elasticities are identified. For example, Table 4 shows the average income elasticity
for fresh and preserved seafood is 1.35, the range in estimates for the underlying products is from
2.12 to 1.00. Prepared fish had the highest elasticity in this group (2.12), while shellfish had the
lowest (1.00).
13 Other factors besides income changes can influence consumption growth. Global trade in the traditional product simply
worked asbestos (SITC 2784) declined by almost 50 percent over the last decade due, in part, to health concerns involving this
item. Changes in demand for agricultural products, like sugar, are influenced by high tariffs and NTBs, just as excise and other
domestic taxes influence demand for tobacco. Technological factors, more efficient utilization of raw materials in production, or
the development of substitutes have had a negative impact on demand for some traditional products. Internal factors in the
exporting country may also influence the level of global trade. Ethiopia is one of the world's largest suppliers of sesame seeds
whose production and export was affected by the level of domestic hostilities. Although economic theory acknowledges the
possibility of a negative income elasticity (Henderson and Quandt, 1958, p. 26-28) these non-income factors probably generated
some of the negative estimates observed in our results.
14 Income elasticity estimates are sometimes generated within the context of multi-variable regression models that attempt to hold
both price and non-price factors constant. See, for example, Stem et. Al. (1976). Our approach focuses directly on price changes
and does not account for other factors that may influence import levels.
18
Table 4. Estimates of Trade Income Changes and Income Elasticities of Demand in the EU (15), Japan and
United States for Major Groups of Traditional African
Group Range in Estimates High and Low Value Products
Traditional Product Group* Agjg2 High Low Hieh Low
TRADE-INCOME CHANGES
Tropical Beverage Products 0.45 1.67 -1.21 cocoa beans cocoa butter
Non-Ferrous Metals & Ores 0.49 3.70 -0.85 beryllium and titanium manganese ore
Ferrous Metals & Ores -0.17 2.19 -0.21 ferro-alloys iron ore
Fresh & Preserved Seafood 1.42 2.29 1.01 prepared fish shellfish
Other Foodstuffs 1.17 3.83 -0.87 prepared fruit groundnut oil
Hides & Leather Products 0.54 0.66 -3.82 other leather nes goat hides
Minerals and Products** 0.83 1.03 -2.97 coal asbestos
Lumber and Products 0.55 0.67 0.51 sharped lumber wood pulp
Fibers & Agricultural Materials -0.73 2.12 -1.68 tobacco leaf parts raw cotton
Gold and Diamonds*** -0.16 -0.16 -0.16 gold gold
All Above Products 0.55 3.83 -3.82 prepared fruit goat hides
INCOME ELASTICITY ESTIMATES
Tropical Beverage Products 0.70 1.67 -1.18 cocoa beans cocoa butter
Non-Ferrous Metals & Ores 0.24 3.76 -1.25 berllium and titanium manganese ore
Ferrous Metals & Ores -0.39 1.89 -0.43 ferro-alloys iron ore
Fresh & Preserved Seafood 1.35 2.12 1.00 prepared fish shellfish
Other Foodstuffs 0.76 3.62 -1.50 prepared fruit groundnut oil
Hides & Leather Products 0.21 0.33 -4.21 other leathers nes goat hides
Minerals and Products" 0.23 0.67 -3.06 coal asbestos
Lumber and Products 0.36 0.64 0.28 shaped lumber saw logs
Fibers & Agricultural Materials -0.96 1.81 -2.00 tobacco leaf parts raw cotton
Gold and Diamonds"' -1.21 -1.21 -1.21 gold gold
All Above Products 0.36 3.76 -4.21 beryllium and titanium goat hides
See the notes to Table 2 for a list of items in the product groups.
Since no quantity units were available for uranium ore and platinum these items are excluded from this group.
** Since no quantity units were available for industrial diamonds this item is excluded from the group.
Source: Tabulations based on trade statistics reported to COMTRADE by countries listed in the notes to Table I.
For all traditional products combined, both the average trade-income change ratio (0.55)
and income elasticity estimate (0.36) are well below unity, which is consistent with earlier
estimates (Stern et. al. 1976). However, the number of instances (8 of 10) where the lower range
of the elasticity estimates are negative is surprising. Negative values imply that demand for
these items is contracting in spite of rising real income levels. Average traditional product trade-
income ratios and income elasticities are negative for three of the ten product groups. Goat hides
registers the lowest income elasticity (-4.26) of any traditionall product followed by asbestos.
The statistics in Table 4 have important trade policy implications for Sub-Saharan
Africa. Over the last decade, the rate of growth in world trade (5.7 percent) was roughly double
that for income as measured by GDP. On average, the income elasticity for traditional products
is just over one-third (0.36). This implies that, if GDP continues to grow at its recent aninual
rate of 2.5 percent, global trade in traditional products should expand by under one percent per
year. As such, reliance on traditional exports will continue Africa's marginalization in world
trade. It appears the only way this trend could be reversed is for Africa to achieve major
competitive gains for these products which compensate for the relatively low rate of grow in
import demand. However, a recent analysis of Africa's supply capacities found no evidence that
such competitive gains were occurring (Ng and Yeats 2000).
19
Table 5 utilizes a "demand growth prospects" classification scheme to summarize
implications of the income elasticity estimates for individual traditional products. Although the
boundaries are by their nature arbitrary, six product classification groups were established which
incorporate a range of income elasticities. 5 Traditional products which clearly have
pronounced negative prospects (their income elasticities are below -1.5), like asbestos, are
classified in the "strong negative demand growth prospects group" while, at the other end of the
scale, products like ferro-alloys and prepared fish, where trade is growing considerably faster
than GDP, are classified in the "strong positive growth prospects" category. Between these two
extremes are three categories for likely static demand growth prospects products, and products
with probable positive, or negative, growth prospects. Within each group the products are listed
in terms of ascending income elasticities. For example, within the "strong negative growth
prospects" group goat skins has the lowest income elasticity and sheep skins has the highest.
The general message emerging from Table 5 reinforces the essentially pessimistic
impressions from the previous analyses. Twenty two (63 percent) of the traditional products
seemingly have either static or negative demand growth prospects. These "static or negative"
products accounted for about 30 percent of Africa's 1999 total non-oil exports, or about 60
percent of all traditional product exports. However, in contrast, to the essentially negative
prospects of most products, Table 5 suggests there are important items, like prepared fish, where
the outlook is for probable positive or strong demand growth. The 13 items classified in the
"positive growth" groups accounted for about 20 percent of SSA non-oil exports in 1999. In
terms of export values, the most important traditional products with favorable demand prospects
include;
Shellfish, crustacea and prepared fish. Exports of these products from Africa totaled
over $1.2 billion in 1999 and accounted for one percent or more of the total exports of 21
African countries. Recent statements in several trade journals suggest that prospects for seafood
and seafood products may be even more favorable than suggested by Table 5 due to the impact
of "mad cow" and "foot and mouth" disease, particularly in Europe. The favorable demand
outlook is enhanced by a slight recent increase in Africa's global market share (see Table 1).
Unwrought aluminum. Imports from Africa totaled about $1 billion in 1999 with about
98 percent of these shipments originating in South Africa, Cameroon and Ghana. Aluminum is
highly energy intensive in production so future demand and production prospects will be
influenced by changes in petroleum and other energy prices. The World Bank (2000, p. 80)
suggests the longer-term outlook is favorable and projects a 7 per cent real price rise over 1999-
2010. Over 1990-99, Africa's global market share for aluminum held constant (Table 1).
'5 The boundaries in Table 5 were established in recognition of the fact that other factors besides income changes may have
affected import levels. For example, imports of some agricultural products like sugar or groundnut oil may have been negatively
affected by the Uruguay Round "tariffication" of nontariff barriers facing these products. It has been suggested that tariffication
may have raised agricultural protection in cases. However, barriers were clearly lowered on most manufactures, agricultural raw
materials, and ores, minerals and metals. Our limits in Table 5 were set in an attempt to isolate the influence of income changes
as opposed to exogenous trade barrier changes.
20
Fresh or Prepared Fruit. Global imports of freshi and prepared fruit rose by over $3
billion over the last decade and now total about $8.8 billion. Africa has a geographic advantage
in many of these goods in that it is either an all season or off season producer. That is, when
African produce is ready for harvest winter conditions generally prevail in the major northern
hemisphere markets. Several trade journals suggest that Africa needs to further develop fast
reliable air service to deliver fresh produce to the major OECD and developing country markets.
The favorable demand outlook for these products is consicderably enhanced by an increase of
over 2 percentage points in Africa's global market share (Table 1).
Beryllium and Titanium. Global imports of these piroducts almost doubled over the last
decade, a point that is reflected in the group's relatively highi income elasticity. Beryllium is an
important additive to other metals making them stronger and lighter. Future prospects for
Beryllium are uncertain due to concerns that exposure to the product may pose lung and other
health hazards. Over the last decade, Africa experienced considerable erosion in its global
market share for these products.
21
Table 5. Probable Demand Growth Prospects for Individual Traditional Products
Growth Prospects Category (no. of items)* Traditional products**
Strong Negative Demand Growth Prospects (3) Raw Goat and Kid Skins
(Ijk* -1.5) Asbestos Simply Worked
Sheep Skins Without Wool
Probable Negative Demand Growth Prospects (8) Natural Calcium Phosphates
(-1.5 lIk* -0.5) Manganese Ore
Non-Monetary Gold
Cocoa Butter and Paste
Groundnut Oil
Other Nonferrous Ores, nes
Raw Beet and Cane Sugar
Groundnut Oil
Static Demand Growth Prospects (11) Raw Cotton***
(-0.5 ljk* 0.5) Metaliferous Nonferrous Waste
Iron Ore
Tea
Saw Logs
Other Leathers, nes
Other Coal Not Agglomerated
Natural Gums and Resins
Wood Pulp
Sesame Seeds
Unwrought Copper Alloys
Probable Positive Demand Growth Prospects (6) Shaped Lumber
(0.5 ljk* 1.5) Coffee Beans
Products of Melted Metal Ores
Shellfish and Crustacea
Cotton Seeds
Tobacco Stripped
Strong Positive Growth Prospects (7) Cocoa Beans
(ljk* 1.5) Parts of Tobacco Leaf or Stem
Ferro-Alloys
Prepared or Preserved Fish
Unwrought Aluminum Alloys
Prepared or Preserved Fruit
Beryllium and Titanium
* Prospects for export earnings will be determined both by changes in demand and supply. If global supply conditions are
expanding faster this could produce static or even declining export revenues
** Within each group the products are listed in terms of ascending income elasticity estimates. For example, within the "strong
negative growth prospects group" goat skins has the lowest income elasticity and sheep skins has the highest elasticity. We were
unable to compute income elasticities for uranium, platinum, and industrial diamonds due to a failure of most countries to report
quantities for imports.
*** Analysis of the underlying statistics lead us to shift raw cotton from the "strong negative prospects" group into the "static
growth prospects" category. The collapse of Asian markets for cotton due to the regional financial crisis had a major adverse
impact on overall demand for this good. In contrast, EU and North American imports of raw cotton were essentially static.
Source: Tabulations based on trade statistics reported to COMTRADE by countries listed in the notes to Table 1.
22
Box 3. Are There "Dynanic" African Exports?
An important question is whether there are "dynarnic" or relatively fast growing products that Africa may
export competitively. If so, how do the fast growing products compare with the regions' "traditional" products?
Are the dynamic products largely composed of non-oil primary commodities, or do manufactures, which historically
have had higher growth rates, appear among these items.
For an assessment, the following three-step procedure was employed. First, a list was compiled of all four-
digit SITC Rev. 2 products where 1999 global imports from Africa where at least $25 million. This "cut-off' was
established to distinguish between situations where regional trade might be the result of special "irregular"
circumstances, as opposed to where a permanent trade base was established. In order to provide further supportive
evidence on this last point, we next eliminated all products where SSA exports failed to exceed $1 million in each
year from 1995 to 1998. This procedure produced a list of 183 products for further analysis. Next, we calculated
1990-99 global import growth rates for these goods from both Africa and all exporting countries, and ranked the
products in descending order of the global trade growth rates. All products with above average global trade growth
rates were retained for further analysis. This procedure made it possible to differentiate between four different
groups of dynamic products.
Competitive-dynamic products. World trade in these items grew at above average rates while the rate
of growth of imports from Africa actually exceeded the global average. The 33 four-digit products listed below fall
in this category and accounted for $4.25 billion or 9.3 percent of Africa's 1999 non-oil exports. With the exception
of six products, all are classified as manufactured goods. Four textile and clothing products (with combined African
exports of $1.09 billion) appear in the list, as do six groups of "parts and components" of specific goods with a
combined African trade of $909 million. Trade in parts and components generally reflects international production
sharing, a fast growing global activity, in which various stages of the fabrication of a good are undertaken in
different countries.
1999 Global Imports ($ d1l.) 1990-99 Import Growth Rate
Export Product (SITC No.) From Africa World From Africa World
Radio-telegraphic equipment (7643) 31.2 43,648.4 50.0 22.6
Filtering machinery (7436) 404.5 9,378.8 47.6 8.5
Wineofgrapes(1121) 232.1 13,637.5 35.8 6.1
Insulated electric wire (7731) 73.0 32,167.7 33.9 11.4
Salts of metallic acids (5233) 50.3 2,186.7 33.0 8.7
Pneumatic tires (6251) 53.1 1l1,090.1 31.6 5.9
Chemical preparations (5989) 119.9 31,307.0 30.3 6.9
Industrial diamonds (2771)* 401.0 918.2 27.4 8.6
Chairs and parts (8211) 327.8 22,773.5 26.9 9.4
Cosmetics and perfumes (5530) 30.7 18,715.8 23.6 10.1
Other electric machinery (7788) 59.3 42,310.2 22.6 9.9
Ores of precious metals (2890) 294.2 2,896.4 19.9 8.0
Parts of office machinery (7599) 67.9 121,8324.5 19.7 13.1
Parts of motor vehicles (7849) 326.2 125,628.8 19.6 6.7
Medicaments (5417) 27.1 67,369.7 17.6 15.3
Electric switches & relays (7721) 35.3 55,711.8 17.0 9.0
Parts of power generators (7149) 33.0 23,596.6 16.8 7.2
Miscellaneous articles (8939) 38.6 41,456.9 15.7 8.6
Pepper and pimento (0751) 32.9 1,326.5 15.5 11.0
Parts of telecommunications (7649) 32.8 61,102.2 15.1 11.2
23
Box 3. Continued
1999 Global Imports ($mill.) 1990-99 Import Growth Rate
Export Product (SITC No.) From Africa World From Africa World
Specialized machinery (7284) 44.5 47,184.5 15.0 5.9
Trousers (8423) 330.1 16,303.2 14.4 7.4
Cotton under garments (8462) 382.1 23,443.1 13.6 13.3
Reaction engines (7144) 90.4 14,203.9 13.6 10.7
Other textile outer garments (8439) 196.2 23,123.5 13.2 6.1
Internal combustion engine parts (7139) 50.2 22,599.0 13.2 8.5
Zoo animals (9410) 41.4 504.3 12.7 6.9
Edible products nes (0980) 25.8 14,689.1 12.6 9.2
Parts of furniture (8219) l212 28,985.7 12.5 6.7
Parts of tobacco leaf or stem (1213)* 33.6 159.8 11.7 8.2
Builders carpentry products (6353) 58.4 7,497.6 9.2 8.3
Gas turbines nes (7148) 30.8 4,401.6 8.8 7.4
Men's shirts (8441) 181.0 10,644.6 8.1 6.0
Total of Above 4,257.3 943,287.2 19.1 11.0
*Also classified as a traditional export.
Dynanic Products. African exports of these goods grew faster than world trade, but slower than global
trade in the item. Although African import shares for these goods declined over the decade, their above average
growth rates worked against Africa's longer-term marginalization in world trade. Altogether, 3 four-digit products,
namely, knitted outer garments, cotton seed, and men's' jerseys with combined African exports of $517 million fell
in this category.'6
Static dynanuc products. Global trade in these products grew at an above average rate, yet imports
from Africa grew less rapidly than world trade. The four products falling in this category accounted for $3,042
million in trade or 6.6 percent of all African non-oil exports. Platinum dominates this group with 1999 African
exports of $2.7 billion. Other static-dynamic products include printing paper, miscellaneous base metals, and toys
and games.
Declining dynamic products. Global trade in these goods grew at an above average pace, yet the annual
rates of growth of imports from Africa were negative. In 1999, Africa's exports of the three products in the group
(palm oil, vegetable tanning extracts, and safety glass) totaled $105 million.
A point of interest concerns the recent African origins of the competitive-dynamic product exports. The
underlying data show that most of these goods originated in the southern cone of Africa. SACU accounted for 71
percent of all exports, foUowed by Mauritius (16 percent), and Madagascar and Zimbabwe (3 percent each).
However, all SSA countries , with the exception of Reunion and Rwanda recorded some competitive-dynamic
product exports. How Africa was able to establish an export base for such items is a question of considerable
imporance.
As was the case with our analysis of variations in global demand for a specific country's
products (Table 3), it was of interest to determine if significant differences exist in the SSA
countries average income elasticities. That is, are some SSA countries relatively fortunate in that
16 To test the sensitivity of the list of dynamic products to our 1999 $25 million trade cut-off, this value was reduced to $20
million and the resulting new product list examined. This lower limit only added five products to the "competitive-dynamic"
group, namely, electronic micro-circuits, tapes and valves for pipes, plastic polymers, wood manufactures for domestic use, and
bed linen. Only one item, corsets and brassieres, would have been added to the "dynamic" products list. The composition of the
two other groups was unchanged.
24
they export a "basket" of products with relatively high income elasticities, while others are
unfortunate in that their products elasticities are relatively low.
Table 6 provides evidence bearing on this point. Shown here are average trade weighted
and unweighted elasticity estimates for the large and mid-sized African countries. To help
identify the sources of cross-country variation in these statistics, the table also identifies the
largest traditional product exported by each country and shows its estimated income elasticity.
As an example, saw logs are the largest traditional product exported by Cameroon and 0.28 is
this items estimated income elasticity. Annex I provides similar statistics for a group of smaller
African countries.
Considerable variation occurs in the national averages as the income elasticities for four
countries, all of which are mid-sized exporters, are negative. This is consistent with our previous
finding (Table 3) of below average demand growth for the mid-size countries exports. The
collapse of East Asian markets for cotton in the late 1990s largely accounts for Benin, Mali, and
Togo's negative averages, while cotton, sugar, sheep and goat skins are responsible for Sudan's
negative elasticity. In contrast, there are several African countries, like Cote d'Ivoire, Ghana,
Guinea and Madagascar where the average income elasticities are close to, or exceed, unity.
Frequently, these results are attributable to a few products like fish, fruit, shellfish, and cocoa
beans. Zambia and the Democratic Republic of the Congo have average elasticities exceeding
unity almost entirely due to the high share of beryllium and titanium in their total exports.
However, It should again be noted that export revenue prospects may differ substantially from
demand prospects if major changes are occurring in competitive market shares.
Table 6 shows rather wide differences sometimes exist between the average trade-income
change ratio for individual large and mid-sized African exporters. The average ratio for all large
African countries (0.75) is more than four times that for mid-sized countries (0.16). Although
the discrepancy is smaller, the income elasticity for thie larger countries (0.63) is also
considerably higher. One possible explanation for the differences is that the mid-sized countries
typically export a smaller number of products on average (16 as opposed to 21 for the larger
exporters) and may, therefore, be more strongly affected by a few poorly performing items.
Second, four of the mid-sized countries (Ethiopia, Malawi, Mali and Uganda) are land-locked
which probably precludes exports of some relatively high growth products like shellfish and fish
preparations.
Differences in the average income elasticities for their traditional products could produce
significant differences in what African countries should expect from their exports of these goods.
Specifically, the expectations of the 27 large and mid-sized countries could be classified as
follows;
Negative traditional product export expectations (z4 countries). Included in this group
are; Benin, Mali, Sudan and Togo. Average traditional procluct income elasticities are negative
which implies significant reductions in real export earnings. However, future prospects will be
strongly influenced by a recovery in demand for cotton.
25
Positive slow growth expectations (17 countries). Average income elasticities are
positive, but below unity. This implies that traditional exports should grow, but at a rate lower
than income growth in major markets. The average income elasticity for these countries is about
0.5 which suggests their traditional exports should grow at a rate one-half that of income in
major consuming markets. If past trends persist, this implies an export growth rate about one-
quarter of that for world trade.
Favorable export expectations (6 countries). Average income elasticities for these
countries exceed unity, and range to over 2 in the case of Madagascar. About 65 percent of
Madagascar's 1999 exports consisted of shellfish, prepared fish, and fresh fruit which were all
high elasticity products. Zambia and the Democratic Republic of the Congo prospects depend
almost entirely on market developments for beryllium and titanium. Recent concerns have been
expressed about the potential cancer causing properties of this metal which could have a negative
impact on demand.
Table 6. Average Income Elasticities and Trade-Income Ratios for Individual African Country Traditional Products
Trade-Income Ratio Income Elasticity
Trade Trade Largest Export
African Exporter Weighted Unweighted Weighted Unweighted Product (Elasticity)
LARGER EXPORTERS
Angola 0.79 0.02 0.85 -0.02 Shellfish (1.00)
Cameroon 0.44 0.63 0.36 0.58 Saw Logs (0.28)
Congo, Dem. Rep. 1.36 0.83 1.36 0.66 Beryllium & Titanium (3.76)
Congo, Rep. 0.83 0.63 0.65 0.43 Saw Logs (0.28)
Cote d'lvoire 1.05 0.49 0.94 0.22 Cocoa Beans (1.67)
Gabon -0.85 -0.07 0.34 0.17 Saw Logs (0.28)
Ghana 1.53 1.47 1.13 1.07 Cocoa Beans (1.67)
Kenya 0.37 0.45 1.04 1.06 Tea (0.10)
Liberia 0.57 0.38 0.77 0.81 Saw Logs (0.28)
Mauritius -0.04 -0.56 0.59 0.00 Raw Sugar (-0.92)
Nigeria 1.00 0.92 0.41 0.28 Cocoa Beans (1.67)
SACU 0.76 0.70 0.32 0.49 Non-Monetary Gold (-1.21)
Zambia 1.33 0.34 1.27 0.71 Unwrought Copper (0.41)
Zimbabwe 0.66 0.50 0.48 0.23 Stripped Tobacco (1.10)
All Above Countries 0.75 0.69 0.63 0.50
MID-SIZE EXPORTERS
Benin -1.27 0.27 -1.55 0.17 Raw Cotton (-2.00)
Ethiopia 0.17 -0.22 0.41 -0.38 Coffee Beans (0.64)
Guinea 0.46 0.92 1.09 .1.32 Coffee Beans (0.64)
Madagascar 1.22 0.55 2.26 1.05 Shellfish (1.00)
Malawi 0.89 0.26 0.85 0.12 Stripped Tobacco (1.10)
Mali -1.62 0.00 -1.94 -0.22 Raw Cotton (-2.00)
Mauritania 0.28 0.40 0.14 0.29 Iron Ore (-0.43)
Mozambique 0.37 0.71 0.02 0.33 Shellfish (1.00)
Senegal 0.36 0.50 0.28 0.36 Shellfish (1.00)
Sudan -0.26 -0.30 -0.52 -0.59 Sesame Seeds (0.48)
Tanzania 0.31 0.68 0.38 0.58 Coffee Beans (0.64)
Togo -1.02 0.16 -1.06 0.15 Raw Cotton (-2.00)
Uganda 0.19 0.29 0.51 0.11 Coffee Beans (0.64)
All Above Countries 0.16 0.29 0.36 0.32
Source: Estimates based on the combined reported imports of the EU(15), North America and Japan.
26
D. Recent Changes in the Direction of Trade
Key Observations
Over the last decade the relative importance of developing countries as markets for
traditional products increased significantly. Although thle region's financial crisis had a
major negative impact on demand over 1997-99, East Asian imports of traditional products
had been growing faster than any other regional group. As global suppliers of traditional
products Sub-Saharan Africa ranks behind developing countries in Latin America and East
Asia in relative importance. This accents the needfor Sub-Saharan countries to implement
reforms that will enable thtem to remain globally competitive for these goods.
Expectations for Africa's traditional exports can be influenced by changes in the direction
of global trade in these goods. Are industrial countries still the major consumers of these
products, or have developing countries grown in relative importance? If shifts in the geographic
pattern of demand occurred do they have positive or negative implications for Africa. For
example, the liner conferences North-South routes generally link Africa to Europe, or to a lessor
extent with North America.'7 If the major growth in demand for traditional products is in other
regions, transport constraints could make it difficult for Africa to capitalize on the new
opportunities. Other important considerations are whether there are important differences in the
growth in demand for traditional products across markets (if so, why), is there evidence that
some markets may be under performing their potential, or are the origins of these exports
changing. ' 8
Table 7 provides empirical evidence bearing on these points. Shown here are global
imports of each traditional product group for selected years over 1990-99, as well as the share of
this exchange imported by specific countries or country groups. Similar statistics for all
traditional products combined are shown in the lower half ol the table along with data on global
imports of all non-oil primary products. The objective here is to determine if the geographic
pattern of trade in traditional products differs from that of most commodities.
Table 7 shows developed countries were of declining relative importance as markets for
traditional products over the decade. In 1990, 78 percent of all exports went to developed
countries, but by 1997 this share had declined by almost 12 percentage points. The 1998-99
statistics seemingly suggest a recovery in these markets, bul. the 4 percentage point increase (to
70.1 percent) is due largely to the impact of the regional financial crisis on East Asian demand.
7 However, the nature and directional effects of individual African countries transport constraints may vary. For example, a
recent World Bank (2001. p. 54) assessment of Ghana's export prospects noted " Ghanaian producers have good access to most
European and Middle Eastem markets and only indirect access to North/South American markets. Presently, only one small
ocean carrier and one air carrier provide infrequent direct freight service to the North American market. A second water carrier
has recently announced plans to offer direct service from the US East Coast to the West Coast of Africa, but the return trip to the
United States is a long haul through East Asia.
18 If one measures developed country imports on a per capita basis there are some relatively large differences between countries.
Japanese imports of traditional products per capita were $210 in 1999, while those in Europe were slightly lower ($200). In
North America and developed Oceania per capita imports were $120. The differences seem, at least in part, attributable to
differences in resource endowments rather than trade barriers. That is, North Arnerica has superior endowments of timber, ores,
minerals, and agricultural land than Europe or Japan so local production is competitive with many of the natural resource based
traditional products produced abroad.
27
From 1997 to 1999, East Asia's global market shares for gold and diamonds, as well for fibers
and agricultural materials, fell by more than 10 points while the other traditional product groups,
with the exception of hides and leather, also experienced reductions.'9
A comparison of the geographic import shares for the traditional and all non-oil
commodities suggests that no major dissimilarities exist between the two. Developed countries
accounted for 78 to 80 percent of global imports of the two groups in 1990. These markets then
declined in relative importance for both commodity groups although the reduction was somewhat
larger for traditional products. Conversely, in 1990 imports of developing countries accounted
for about 20 percent of world trade in both traditional and all non-oil products and these markets
grew in importance over the decade. In short, the relative importance and direction of changes in
demand for both product groups in developed and developing countries appears to be closely
related. These findings reinforce the previous conclusion that characteristics of traditional
products are basically similar to other non-oil commodities.
Question of interest also concern the origins of global trade in traditional products and
whether Africa was changing in relative importance as a global supplier of these goods. Table 8
provides relevant information for the last decade by reporting global export values and also
shows the share of global exports from different country groups. These groups differ somewhat
from those in Table 7 to more accurately reflect the importance of producer, as opposed to
consumer countries. As before, similar statistics for all non-oil primary commodities are
included for comparison.
19 The magnitude of the East Asian demand reduction is clearly evident in the underlying import value statistics. In 1997, East
Asia's imports of traditional products totaled $49.8 billion, yet by 1999 imports fell to $33.8 billion - a reduction of 32 percent in
only two years. During this period, East Asia's imports contracted in nine of the ten traditional product groups, but the largest
declines occurred for fibers and agricultural materials, and gold and diamonds.
28
Table 7. The Geographic Pattern for Global Imports of Traditional Products
World Share of Traditional Imports by Developed Countries (%) * Share of Traditional Imports by Other Countries (%)**
Imports North Other Latin Middle East South East
Traditional Product Group Year ($ mill.) Total Europe America Japan Oceania Total Europe America & Africa Asia Asia
Tropical Beverage 1990 13,362 90.5 58.7 24.5 6.1 1.2 9.5 0.9 0.8 3.4 1.4 3.1
Products 1995 21,828 88.8 59.6 21.3 6.5 1.4 11.2 3.0 1.3 2.6 0.9 3.4
1997 22,007 89.7 56.1 25.7 6.6 1.4 10.3 2.8 1.5 2.1 0.9 3.0
1998 21,530 89.0 55.9 25.1 6.4 1.5 11.0 3.1 1.4 2.3 1.3 2.9
1999 18,114 88.5 55.1 25.3 6.6 1.6 11.5 3.2 1.7 2.5 1.3 2.7
Non-Ferrous Metals & 1990 40,189 85.7 49.0 14.5 21.9 0.2 14.3 1.4 1.3 0.3 0.8 10.5
Ores 1995 56,956 73.7 40.1 16.6 16.6 0.4 26.3 1.6 2.2 0.4 1.1 21.1
1997 53,505 73.7 39.2 18.4 15.8 0.3 26.3 1.9 2.4 0.4 1.1 20.5
1998 49,647 76.9 40.6 22.1 13.9 0.3 23.1 1.9 2.9 0.5 0.7 17 0
1999 49,408 76.1 37.9 23.7 14.2 0.3 23.9 1.9 2.5 0.5 0.7 18.3
Ferrous Metals & Ores 1990 10,638 78.5 56.8 12.7 8.6 0.4 21.5 3.7 1.8 0.9 0.8 14.3
1995 14,631 72.5 50.5 11.5 10.2 0.4 27.5 3.6 1.6 (0.7 (0.7 20.8
1997 14.150 65.0 45.1 10.3 9.0 0.6 35.0 3.8 2.6 0.6 0.6 27.5
1998 13,522 67.0 48.8 10.5 7.4 0.4 33.0 4.2 2.9 0.9 0.4 24.6
1999 11,224 65.4 45.5 11.9 7.6 0.4 34.6 3.9 2.7 0.7 0.5 26.8
Fresh & Preserved 1990 15,709 92.2 35.4 20.9 34.5 1.4 7.8 0.2 0.7 0.6 ().0 6.4
Seafood 1995 23,657 89.2 31.3 19.1 37.6 1.2 10.8 0.3 1.2 0.5 0.0 8.8
1997 22,998 88.4 32.6 22.2 32.4 1.2 11.6 0.4 1.4 0.6 0.0 9.2
1998 22,443 89.7 37.3 23.4 27.7 1.3 10.3 0.4 1.6 0.6 0.0 7.6
1999 23,033 89.1 34.3 24.8 28.6 1.4 10.9 0.4 1.5 0.6 0.( 8.4
Other Foodsfuffs 1990 11,234 79.3 49.8 2(0.0) 8.6 0.9 20.7 1.2 2.7 2,3 0.4 14.1
1995 14,057 72.7 47.3 15.9 8.6 0.9 27.3 1.0 3.9 2.7 0.6 19.1
1997 14,222 74.3 47.1 19.2 7.3 0.8 25.7 1.0 3.6 3.0 1.7 16.4
1998 13,928 76.3 50.3 18.7 6.4 0.8 23.7 1.2 4.0 1.8 1.7 15.1
1999 12,887 78.8 50.8 20.4 6.7 0.9 21.2 1.2 3.6 1.8 1.9 12.6
Hides and Leather Products 1990 2,349 7(0.0) 56.7 8.0 4.7 0.6 30.0 3.1 1.7 1.5 1.4 22.3
1995 2,451 61.2 51 6 5.8 3.4 0.4 38.8 1().0 1.9 1.3 2.0 23.6
1997 2,190 59.2 49.9 4.9 4.0 0.4 40.8 9.6 3.1 1.2 1.5 25.5
1998 1,736 61.5 51.8 5.8 3.6 0.3 38.5 5.8 3.1 1.5 1.7 26.4
1999 1.381 58.6 46 5 6.4 5.2 0.4 41.4 5.5 3.3 1.7 2.1 28.9
Miierals and Products 1990 21,584 73.8 40.3 3.5 29.6 (1.5 26.2 3.2 4.2 0.7 3.5 14.6
1995 22,681 65.6 31.9 3.5 29.8 0.4 34.4 3 7 5.0 1.1 4.9 19.7
1997 24,594 60.4 28.8 3.9 28.1 0.4 39.6 5.4 5.5 2.6 5.4 2(0.7
1998 23,065 63.5 30.1 4.9 27.0 0.5 37.5 4.5 5.3 2.8 5.1 19.9
1999 20,442 62.9 30.0 5.2 27.2 0.5 37.1 3.2 5.3 2.6 6.0 19.9
Table 7. Continued
World Share of Traditional Imports by Developed Countries (%) * Share of Traditional Imports by Other Countries (%)**
Imports North Othcr Latin Middle East South East
Traditional Product Group Year ($ mill.) Total Europe America Japan Oceania Total Europe America & Africa Asia Asia
Lumber and Products 1990 12,774 73.8 44.8 6.0 21.9 1.0 26.2 1.0 1.2 1.8 2.6 19.6
1995 17,021 66.4 41.3 6.0 18.2 0.8 33.6 0.8 1.6 2.3 1.8 27.1
1997 15,810 64.0 38.2 7.8 17.2 0.8 36.0 1.1 2.1 2.3 2.9 27.6
1998 13,720 67.3 47.3 9.5 9.8 0.7 32.7 1.3 2.6 2.5 3.1 23.2
1999 14,868 64.4 42.2 9.8 10.5 0.8 36.6 1.2 2.3 2.3 3.0 27.9
Fibers & Agricultural 1990 11,301 56.4 38.4 3.3 14.1 0.6 43.6 3.5 3.7 2.1 1.1 33.1
Materials 1995 14,649 42.4 30.3 2.7 8.7 0.6 57.6 6.8 8.5 2.6 3.3 36.5
1997 15,384 43.1 29.8 5.6 7.2 0.5 56.9 9.6 12.2 1.9 2.1 31.1
1998 13,235 45.8 32.8 4.3 8.3 0.5 54.2 10.2 12.8 1.9 3.4 24.8
1999 10,703 52.0 35.8 6.7 9.0 0.5 48.0 9.7 10.8 2.1 6.4 19.0
Gold & Industrial 1990 18,908 68.7 38.4 9.3 19.1 1.9 31.3 0.3 0.2 0.9 0.2 29.7
Diamonds 1995 26,347 56.3 31.5 10.3 12.4 2.1 43.7 0.2 0.4 0.9 3.7 38.6
1997 32,625 40.6 22.1 12.5 4.2 1.8 59.4 0.2 0.7 0.9 11.4 46.2
1998 31,092 52.1 27.9 14.9 2.9 6.4 47.9 0.2 1.1 0.8 16.0 29.8
1999 25,935 49.0 25.7 14.3 4.0 5.0 51.0 0.2 1.8 0.9 20.8 27.4
All Traditional Products 1990 159,745 78.0 45.1 12.4 19.7 0.8 22.0 1.6 1.7 1.1 1.2 15.2
1995 216,068 70.4 39.6 12.8 17.1 0.9 29.6 2.1 2.5 1.2 1.8 21.2
1997 219,395 66.2 36.3 14.6 14.5 0.8 33.8 2.6 3.0 1.3 3.2 22.7
1998 205,692 70.0 39.6 16.2 12.6 1.6 30.0 2.5 3.3 1.3 3.9 18.0
0 1999 189,667 70.1 37.9 17.4 13.5 1.3 29.9 2.2 3.0 1.3 4.6 17.8
All Non-Oil Primary 1990 530,019 80.0 52.9 12.9 13.4 0.8 20.0 1.8 3.1 2.2 1.2 11.6
Commodities 1995 730,957 74.2 47.7 12.5 13.2 0.9 25.8 2.2 4.3 2.3 1.4 15.8
1997 719,294 72.7 45.5 14.3 12.1 0.9 27.3 2.5 5.2 2.2 1.5 15.8
1998 687.195 74.7 48.1 15.1 10.6 0.9 25.3 2.5 5.6 2.3 1.6 13.3
1999 668,749 75.1 46.5 16.2 11.4 0.9 24.9 2.2 5.1 2.2 1.8 13.6
*The country composition of the groups listed below is as follows; Developed Europe - all members of the EEC 12 plus Austria, Finland, Iceland, Norway, Sweden, Switzerland
and Greenland; North America - Canada and the United States; Oceania - Australia and New Zealand.
**The country composition of the groups listed below is as follows: Other Europe - Cyprus, Hungary, Malta, Poland, Romania and Turkey; Latin America - Argentina. Barbados,
Belize, Bolivia, Brazil, Chile, Colombia, Costa Rica, Ecuador, El Salvador, Guatemala, Honduras, Jamaica, Mexico, Nicaragua, Panama. Paraguay, Peru, Trinidad and Tobago,
Uruguay and Venezuela; Middle East and Africa - Algeria, Egypt, Israel, Kenya, Mauritius, South Africa and Tunisia; South Asia - Bangladesh, India, Nepal and Pakistan: East
Asia - China, Hong Kong (China), Indonesia, Rep. of Korea, Macao (China), Malaysia, Philippines, Singapore, Taiwan (China) and Thailand.
Note: See the notes to Table 2 for the product composition of each traditional product groups.
Sour-ce: Tabulations based on trade statistics reported to COMTRADE by countries listed in the notes to Table 1.
I'able 8. The Origins of Global Exports of Traditional Products
World Developed Countries' Export Share (%) Developing: Countries' Export Share (%)
T'rade North Japan & SSA Middle Latin South East Other
Traditional Product Year ($ mill.) Total Europe America Oceania Total Countries East' America Asia Asia Countries
Tropical Beverage 1990 13,246 14.4 13.4 (.9 0.1 85.6 25.2 0.0 41.4 3.8 13.1 2.0
Products 1995 21,626 15.8 14.5 1.1 0.2 84.2 24.5 0.1 41.7 3.3 14.4 0.2
1997 21,795 15.4 14.1 1.2 0.1 84.6 22.2 0.1 44.5 3.6 14.0 0.3
1998 21,310 15.9 14.1 1.7 0.2 84.1 25.8 0.1 39,8 3.7 14.3 0.3
1999 17,954 17.4 15.3 2.0 0.2 83.6 26.0 ().1 37.6 3.7 14.8 0.4
Non-Ferrous Metals & 1990 40,105 52.8 26.5 16.8 9.5 47.2 16.1 2.0 15.4 0.4 3.2 10.1
Ores 1995 56,862 45.5 21.3 16.3 7.9 54.5 8.8 2.6 17.2 0.6 5.2 20.1
1997 53,423 43.9 20.7 14.6 8.6 56.1 10.8 2.5 17.1 0.6 4.9 20.2
1998 49,551 45.9 21.7 14.6 9.6 54.1 10.7 2.6 15.2 0.4 4.9 20.3
1999 49,327 43.6 20.8 13.5 9.3 56.4 11.2 2.5 14.6 0.6 5.0 22.5
Ferrous Metals & Ores 1990 13,483 43.1 19.6 4.8 18.6 56.9 12.8 0.6 27.4 5.4 3.3 7.4
1995 17,369 39.5 17.8 3.2 18.5 60.5 12.9 0.4 23.2 4.7 7.0 12.2
1997 17,024 41.3 15.9 3.4 21,9 58.7 12.6 0.3 24.7 4.8 5.8 10.5
1998 16,253 41.0 16.1 4.0 20.9 59.0 13.5 0.3 24.4 5.1 5.2 9.5
1999 13,787 40.2 14.1 3.4 22.7 59.8 14.4 0.3 25.5 5.1 5.1 9.4
Fresh & Pregerved 1990 15,441 33.5 17.8 10.4 5.3 66.5 4.8 3.6 10.6 5.0 38.3 4.2
Seafood 1995 23,326 29.8 14.6 10.4 4.8 70.2 5.3 3.6 12.6 6.2 37.5 4.9
1997 22,655 29.0 15.0 9.4 4.6 71.0 5.4 3.7 14.9 6.6 35.6 4.7
1998 22,116 29.3 16.0 9.1 4.2 70.7 5.8 3.7 15.8 6.3 34.7 4.5
1999 22,711 31.2 16.0 10.9 4.3 68.8 5.4 3.7 15.0 6.1 33.5 5.1
other Foodsfuffs 1990 11,175 44.6 26.4 6.9 11.3 55.4 12.2 2.5 23.9 1.3 13.0 2.6
1995 13,986 42.6 24.2 7.0 11.5 57.4 10.9 2.1 26.2 1.0 14.4 2.8
1997 14,131 42.6 24.6 6.9 1i.i 57.4 10.7 2.4 27.3 1.5 12.8 2.6
1998 13,844 43.7 26.5 6.8 10.4 56.3 11.6 2.6 27.2 1.6 10.6 2.8
1999 12,796 42.2 25.6 7.8 8.8 57.8 10.9 2.9 29.8 1.6 9.8 2.7
Hides and Leather 1990 2,345 38.9 22.1 2.6 14.2 61.1 8.8 6.7 4.0 14.1 2(0.3 7.1
Products 1995 2,450 36.4 21.8 2.3 12.3 63.6 12.7 10.5 2.3 13.6 19.5 5.0
1997 2,188 36.9 20.6 3.4 12.9 63.1 15.4 7.6 2.0 14.4 18.5 5.1
1998 1,734 35.5 22.1 3.8 9.5 64.5 15.6 5.9 2.6 16.0 19.4 5.0
1999 1.380 35.7 22.0 4.8 8.9 64.3 16.7 6.0 2.8 14.7 18.9 5.1
Minerals and Products 199( 21,118 68.2 4.9 36.3 27.0 31.8 8.7 4.9 2.5 0.0 3.3 12.3
1995 22,664 61.7 2.1 28.9 30.7 38.3 11.3 3.3 3.9 0.2 10.9 8.7
1997 24,574 59.7 1.8 25.0 32.8 40.3 10.8 3.9 4.7 0.2 12.2 8.6
1998 23,045 58.0 1.9 23.8 32.4 42.0 10.1 4.2 4.7 0.1 12.7 10.2
1999 20,422 56.4 2.0 20.3 34.1 43.6 10.6 4.1 5.8 0.1 14.6 8.5
Table 8. Continued
World Developed Countries' Export Shares (%) Developing Countrics' ExVort Shares (%)
Trade North Japan & SSA Middle Latin South East Other
Traditional Product Year ($ mill.) Total Europe America Oceania Total Countries East* America Asia Asia Countries
Lumberand Products 1990 12,709 30.8 13.8 16.6 0.3 69.2 13.8 0.1 3.5 0.4 46.1 5.4
1995 16,902 31.1 12.9 17.7 0.5 68.9 13.8 0.1 5.4 0.3 40.2 9.1
1997 15,706 34.1 12.7 20.7 0.8 65.9 14.4 0.1 5.7 0.3 36.8 8.5
1998 13,614 38.1 15.9 21.5 0.8 61.9 15.7 0.1 6.3 0.4 27.3 12.0
1999 14,745 37.9 16.4 20.6 0.8 62.1 13.5 0.1 5.4 0.3 31.3 11.5
Fibers&Agricultural 1990 11,230 49.8 6.0 38.7 5.1 50.2 14.7 2.6 15.3 8.2 4.0 5.4
Materials 1995 14,562 50.2 7.2 38.0 4.9 49.8 13.7 3.4 13.6 1.7 2.4 15.0
1997 15,295 45.3 7.6 31.1 6.5 54.7 16.1 3.9 13.3 4.1 2.8 12.6
1998 13,150 49.0 7.4 33.4 8.3 50.9 17.9 4.5 12.3 2.5 3.2 10.4
1999 10,626 45.4 10.6 27.7 7.1 54.6 19.5 4.6 12.9 1.9 5.0 10.6
Gold&lndustrial 1990 18,894 71.3 44.2 17.4 9.7 28.7 13.4 1.3 3.0 0.1 7.1 3.8
Diamonds 1995 26,330 66.3 34.1 19.2 13.0 33.7 16.0 0.5 4.2 0.1 9.8 3.2
1997 32,605 63.4 37.0 15.2 11.2 36.6 14.5 2.6 3.9 0.0 14.2 1.4
1998 31,073 64.4 36.6 16.7 11.1 35.6 11.6 1.7 4.2 (.1 16.0 1.9
1999 25,918 65.4 40.9 15.( 9.5 34.6 14.4 2.6 4.5 0.3 10.0 2.9
All Traditional 1990 158,745 48.4 20.7 17.1 10.6 51.6 13.5 2.2 14.4 2.3 12.3 6.9
Products 1995 216,068 43.5 17.7 15.6 10.2 56.5 12.4 2.0 15.9 1.9 14.2 10.1
1997 219,395 43.2 18.1 14.1 11.0 56.8 12.9 2.3 16.3 2.1 14.0 9.1
1998 205,692 44.2 18.9 14.2 11.1 55.8 12.9 2.3 15.7 2.0 13.5 9.3
1999 189,667 43.3 19.3 13.2 10.7 56.7 13.2 2.4 15.4 2.0 13.5 10.2
All Non-Oil Primary 1990 524,486 66.8 40.3 19.9 6.7 33.2 4.3 1.5 10.9 1.1 10.2 5.1
Commodities 1995 723,608 63.9 37.4 20.4 6.1 36.1 3.6 1.5 11.6 1.1 12.1 6.2
1997 711,434 62.7 35.9 20.0 6.8 37.3 3.9 1.5 13.0 1.4 11.7 5.9
1998 679,373 62.9 37.4 19.1 6.5 37.1 4.0 1.4 12.8 1.3 11.3 6.1
1999 661,334 62.7 36.9 19.1 6.6 37.3 3.9 1.5 12.5 1.3 11.6 6.5
* Also includes North Africa.
Source: Tabulations based on trade statistics reported to COMTRADE by countries listed in the notes to Table 1.
While the geographic patterns of import demand for traditional and all non-oil
commodities were very similar, Table 8 shows large differences sometimes occur in the origin of
these exports. Developing countries supply about 57 percent of world exports of traditional
products, but their share for all non-oil commodities is about :20 percentage points lower. In part,
the differences originate in the tropical beverages group, since the conditions required for their
production generally do not occur in OECD countries. However, non-African developing
countries also supply a disproportionately high share (over 50 percent) of other traditional
product groups including seafood, hides and leather, and lumber and wood products.
Finally, the export shares show Africa is not as relatively important a supplier of
traditional products as might be expected. -Africa originates about 13 percent of these goods
global exports, which is about the same as East Asia, but 2 percentage points lower than Latin
America's share.20 The traditional product shares for all three developing country regional
groups fall below those for the European Union or North Arnerica. However, the data do show
that Africa is far more dependent on the traditional products, as opposed to other non-oil
commodities, than any other regional group. For Africa, thie traditional product share is more
than three times higher than that for all non-oil commodities, yet for the other country groups the
differences are normally within several percentage points. These points have important policy
implications. Africa is not the major global supplier for most of the region's traditional exports.
As such, Africa's export prospects will be highly dependent on the region's capacity to remain
internationally competitive for these goods.
IV. PRICE TRENDS AND PROSPECTS
Although most forecasts and analyses of price trend[s for non-oil primary commodities
fail to include many of Africa's traditional products, some relevant data are available. The
World Bank (2000) published statistics on current and constant prices for about 40 primary
commodities, including 13 traditional products. UNCTAD (2000) also provides statistics on
prices for a somewhat larger number of commodities, although no price projections are included.
However, in cases where price data are not collected for a traditional product import unit values
derived from UN COMTRADE can be used as a proxy.21 These three sources allow one to
empirically address issues such as those relating to the general outlook for primary commodity
and traditional product prices, whether past trends and future prospects for traditional products
differ from those of other commodities, and whether price instability has become more, or less,
of a problem than in the past.
20 Under UNCTAD's auspices, major efforts were made to negotiate commodity agreements for specific products, like cocoa or
coffee, that would establish production controls, and also buy or sell the commodity from buffer stocks to dampen cyclical
changes in demand and prices. The relatively wide geographic dispersion of the origins of traditional products could make the
operation of such agreements more difficult, if they ever are concluded. Some regions (say Latin America) may experience
production shortfalls in a specific year due to climatic conditions, while others (say in Africa) generate a production surplus.
This could cause significant differences in opinions concerning appropriate actions of the buffer stock managers.
21 Price and unit value statistics may differ over time due if goods vary in their physical characteristics or quality standards.
Commodity price data compiled by the World Bank and UNCTAD attempt to hold product specifications constant. Also. import
unit values are generally expressed on a cost-insurance-freight basis while published commodity prices are normally in free-on-
bard terms. A major attraction of unit values is that they can be computed for a wide range of products, while the available
commodity price series have limited coverage.
33
A. Secular Price Trends
Key Observations
The recent record provides no indication that the longer-term deterioration in
traditional product prices have been reversed. Over 1990-99, average real prices for all
traditional products declined by about 24 percent. In a few cases, like coffee and lumber,
where some modest improvement occurred, real prices still remain well below their 1980
levels. In addition, long term price projections by the World Bank reinforce the basically
negative outlook for traditional products and most commodities. With the sole exception of
coffee, 2010 real prices for traditional products are projected to be lower, often substantially
so, than they were in 1990.
Table 9 provides information relevant to such questions by showing statistics on the level
of "real" prices in 1980, 1990, 1998 and 1999 for 12 broad commodity groups along with
aggregate information for Africa's traditional products. Real prices are derived by deflating
nominal prices in a specific year by the unit value index of manufactures (MUV) exported by
France, Germany, Japan and the United States. The data are expressed in terms of constant
1990 prices, and percentage changes over 1980-99 and 1990-99 are also reported. To facilitate
comparisons of trends, values of the MUV index are also shown.
Clearly there is little or no evidence in Table 9 that contradicts the general pessimistic
expectations many have for longer-term primary commodity prices. Over the last two decades
real prices for all non-oil commodities fell by more than 50 percent. Although approximately
two-thirds of the overall decline occurred during the 1980s, non-oil commodity prices fell, on
average, by 15 percent over the last decade. During 1990-99 three commodity groups, namely,
other foods (a group consisting of bananas, beef, oranges, shrimp and sugar), other raw materials
(cotton, rubber and tobacco), and metals and minerals experienced real price declines that were
almost double those for all non-energy commodities.22
22 These relatively large price declines were often attributable to one commodity in the group. The decline in the other raw
materials group is primarily due to cotton prices which, by end 1999, fell to about one-half their level in early 1997. Sugar
played a major role in the price decline for the other foods group. In commenting on the recent market environment for sugar the
World Bank (2000, p. 52) observed "Another year or surplus production adds to the sugar mountain and sends prices to 14 year
lows." Gold and copper had a major influence on falling prices for the minerals and metals group. Concerns about continued
central bank sales of gold stocks exerted downward pressure on prices, which fell by almost $100 per ounce from March 1997 to
March 1999.
34
Table 9. Average Prices for Major Groups of Primary Commodiities in Selected Years (1990 = 100)
Average Annual Real Prices (1990:= 1:00)* Percentage Price Change (%)
Commodity GrouD 1980 1990 1998 1999 1980-1999 1990-1999
All Non-Energy Commodities 174.3 100.0 95.1 85.0 -51.2 -15.0
Agriculture 191.8 100.0 103.5 89.6 -53.2 -10.4
Beverages 252.0 100.0 134.9 104.0 -58.7 4.0
Food 193.4 100.0 100.7 84.5 -56.3 -15.5
Fats and Oils 206.5 100.0 127.5 101.4 -50.9 1.4
Grains 186.5 100.0 87.2 83.4 -55.3 -16.6
Other Foods** 186.6 100.0 80.8 71.3 -61.8 -28.7
Raw Materials 145.2 100.0 83.8 85.5 -41.1 -14.5
Timber 109.7 100.0 87.3 107.9 -1.6 7.9
Other Raw Materials*** 169.5 100.0 81.4 70.2 -58.6 -29.8
Fertilizers 179.0 100.0 117.2 110.1 -38.5 10.1
Metals and Minerals 130.8 100.0 72.4 71.2 -45.6 -28.8
Memo Item
African Traditional Products 124.4 100.0 78.0 76.1 -38.8 -23.9
Manufactures Unit Value Index 72.0 100.0 104.2 103.6 43.9 3.6
* Real prices are derived by dividing nominal prices in a specific year by the unit value index of manufactures
exported by France, Germany, Japan. United Kingdom and the United States to developing countries.
** Items included in this group are; bananas, beef, oranges, shrimp and sugar.
* Items included in this group are; cotton, robber and tobacco.
Source: Based on World Bank (2000, p. 82) Price indices for the traditional products were computed by the
authors using the statistics reported in Table 10.
Two other points concerning Table 9 should be noted. First, over the last decade real
prices for African traditional products fell by 24 percent which was more than the 15 percentage
point decline in all non-energy commodity prices. However, over the full 1980-99 period prices
for the two groups fell by a roughly similar magnitude. Over this longer term the evidence
indicates no substantial differences between traditional product and other commodity price
trends. Second, Table 9 suggests a significant erosion occurred in the terms of trade for all
commodity groups occurred over the last two decades as the manufactures export unit value
(MUV) index increased by about 44 percent which was far greater than the change in nominal
prices for most commodities.
Are the average traditional product price changes reported in the memo item for Table 9
fairly representative, or are there important differences in trends for individual items? Table 10
addresses this point by showing statistics on the level of real prices for each traditional product,
and their percentage change, over the last two decades. The products are ranked in terms of the
descending order of their price changes during the 1990s, while similar information on all non-
energy commodity prices has also been included to providLe a standard for comparison. To
properly interpret these statistics, it should be noted that the 1990 numbers reflect actual nominal
prices for that year, while in all other years nominal prices were deflated by the MUV index on a
1990 base. As such, the statistics reflect real price changes relative to their 1990 level.
35
Table 10. Average Real Prices of African Traditional Exports in Selected Years
Average Real Prices Relative To 1990* Percentage Price Chancze (%)
Traditional Product 1980 1990 1998 1999 1980-1999 1990-1999
Products of Melted Metal Ores** 0.022 0.024 0.028 0.033 50.0 37.5
Coffee Green or Roasted** 450.6 118.2 174.9 143.8 -68.1 21.1
Sisal and Agave Fiber 1.04 0.69 0.79 0.80 -23.1 16.1
Lumber Shaped** 550.2 533.0 464.7 580.2 5.5 8.9
Natural Calcium Phosphates 64.9 40.5 41.3 42.5 -34.5 2.5
Parts of Tobacco Leaf or Stem** 0.72 0.64 0.62 0.64 -11.8 -0.5
Non-Monetary Gold 844.7 383.5 282.3 269.2 -68.1 -4.6
Tobacco Stripped** 3,161 3,392 3,204 2,922 1.4 -5.5
Shellfish 3.64 4.02 4.03 3.77 3.7 -6.1
Cocoa Butter and Powder 7.24 2.98 2.98 2.78 -61.6 -6.7
Cotton Seeds** 0.36 0:22 0.20 0.20 -43.9 -7.9
Asbestos Simply Worked 0.67 0.52 0.53 0.47 -29.1 -9.0
Iron Ore Not Agglomerated 39.0 32.5 29.8 26.6 -31.8 -10.7
Nonferrous Metal Wastes 1.51 1.01 0.78 0.88 41.3 -12.1
Groundnut Oil 1,193.0 963.7 872.8 760.6 -36.2 -12.9
Cocoa Beans** 361.7 126.7 160.9 109.6 -69.7 -13.5
Tea 230.5 205.8 196.4 177.6 -23.3 -13.7
Prepared or Preserved Fish** 4.14 3.48 3.37 2.98 -27.9 -14.3
Beryllium and Titanium** 15.56 6.33 5.27 5.37 -65.4 -15.0
ALL NON-OIL COMMODITIES 174.8 100.0 95.1 85.0 -51.2 -15.0
Chemical Wood Pulp 0.77 0.89 0.76 0.75 -3.2 -15.4
Aluminum, Unwrought** 2,023 1,639 1,303 1.341 -35.6 -20.5
Other Coal Not Agglomerated 59.88 41.67 33.00 32.03 -44.9 -20.8
Saw and Veneer Logs 349.7 343.5 274.9 260.9 -25.7 -24.3
Prepared or Preserved Fruit 1.32 1.24 1.06 0.93 -29.8 -25.3
Sesame Seeds 1.50 1.35 0.91 0.98 -34.4 -27.1
Other Nonferrous Ores 0.90 0.44 0.37 0.32 -64.7 -27.6
Ferrous Alloys** 1.25 0.96 0.87 0.68 -47.5 -31.6
Raw Beet or Cane Sugar 87.8 27.2 18.9 13.3 -78.5 -31.8
Natural Gums and Resins 2.65 2.25 1.46 1.42 -46.5 -36.9
Raw Cotton 286.5 181.9 138.7 113.1 -60.5 -37.8
Raw Goat and Kid Skins 12.18 5.85 4.34 3.54 -70.9 -39.4
Copper Unwrought 3,032 2,661 1,588 1,519 -49.9 -42.9
Sheep Skins Without Wool 5.68 5.90 5.36 3.35 -43.1 -45.2
Manganese Ore, Concentrated 0.10 0.14 0.09 0.07 -30.5 -50.0
Other Leathers 25.23 24.99 13.59 12.07 52.3 -51.7
* The data reported below show actual 1990 nominal prices for each traditional product, while in other years nominal prices have
been deflated by the MUV index.
** Estimates of income elasticities identified this product as having relatively favorable demand growth prospects (Table 5).
Source: Price data for coffee, tea, natural phosphates, sisal, shaped lumber, stripped tobacco, cocoa, iron ore, aluminum, cotton,
non-monetary gold, saw logs, copper alloys, manganese ore and sugar are from World Bank (2000) or UNCTAD (2000). Other
statistics are based on unit values computed from UN COMTRADE. Prices for cocoa, coffee and tea are expressed in US cents
per kilo, while those for groundnut oil, aluminum, copper and natural phosphates are in US$ per metric ton. Prices for saw logs
are in US$ per cubic meter, while gold is in US$ per troy ounce. All other prices are reported in US ($000) per ton.
Perhaps the most important point reflected in Table 10 is the fact that real prices for 30 of
the traditional products (86 percent of the group total) closed the last decade lower than they
were in 1990, while only 4 products (shaped lumber, sisal, coffee and products of melted metal
ores) experienced real price increases. Slag, which is widely used in agriculture as a soil
conditioner, is a major component of the latter group. Many traditional products experienced
what may be considered major declines during the 1990s, with prices for almost one half the
36
items falling by 20 percent or more. A basically negative picture also emerges for the extended
1980-99 period as prices declined for over 80 percent of the traditional products. The data
tentatively suggest that products previously identifies as having relatively favorable demand
growth prospects (see Table 5) generally experienced relatively smaller price declines. These
products are identified by an asterisk in the table.
Analysis of statistics for traditional product groups can provide another perspective on
recent real price changes for these goods. Table 11 shows that only the tropical beverage group
experienced an overall positive real price change over the last decade, which was largely due to a
23 percent increase in coffee prices. The data also show real prices for lumber essentially were
flat over the decade. The price decline for the hides and skins group (-48.3 percent) was by far
the steepest decline reflected in the table and was three tirnes that for all traditional products
average. Two components of this group, namely, goat and sheep skins, had previously been
classified as having "strong negative demand growth" prospects based on their estimated
negative income elasticities.
The memo item in Table 11 provides more aggregate information on commodity price
changes as these indices incorporate data on prices for both the traditional products and other
commodities. Again, they reinforce the impression that price changes for traditional products are
basically similar to the broader commodity indices. The index of all metal and mineral prices
declined by 29 percent over 1990-99, which was only slightly more than the decline registered
by the two traditional minerals and non-ferrous metals groups. The more aggregate raw
materials index, shown in the memo item, fell by 14 percent which was about the same
magnitude of decline reflected in the traditional lumber and fibers groups. Box 4 provides
graphic evidence on recent non-energy commodity current and constant price trends.
Table 11. Recent Prices for Major Groups of Traditional
Averaze Annual Prices (1990 = 100) Percentage Price Change (%)
Traditional Product Group* 1980 1990 1998 1999 1980-1999 1990-1999
Tropical Beverage Products 321.4 100.0 135.7 108.8 -66.1 8.8
Lumber and Products 102.9 100.0 85.4 100.8 -2.0 0.8
Fresh and Preserved Seafood 99.3 100.0 99.2 91.3 -8.1 -8.7
Fibers & Agricultural Materials 94.9 100.0 94.1 85.5 -9.9 -14.5
Ferrous Metals and Ores 120.3 100.0 91.4 81.5 -32.3 -18.5
Minerals and Products 144.9 100.0 80.9 78.9 -45.5 -21.1
ALL TRADITIONAL PRODUCTS 124.4 100.0 78.0 76.1 -38.8 -23.9
Other Foodstuffs 152.6 100.0 87.0 74.1 -51.4 -25.9
Gold and Diamonds 220.3 100.0 73.6 70.2 -68.1 -29.8
Non-Ferrous Metals and Ores 118.6 100.0 69.4 69.3 -41.6 -30.7
Hides and Leather Products 101.1 100.0 56.9 48.9 -51.6 -51.1
Memo Item
All Non-Oil Commodities 174.3 100.0 95.1 85.0 -51.2 15.0
All Foods 193.4 100.0 100.7 84.5 -56.3 -14.5
All Raw Materials 145.2 100.0 83.8 85.1 -41.1 -14.5
Metals and Minerals 130.8 100.0 72.4 71.2 -45.6 -28.8
* See the notes to Table 2 for a list of items in the product groups.
37
Source: Based on the statistics reported in Table 1 0.
Box 4. Recent Trends in Non-Energy Commodity Prices
The figure shown below is intended to provide graphic evidence relating to recent trends in
commodity prices over the last two decades. The intention here is to show how the more recent 1990-99 price
changes related to those for a longer interval. The figure establishes 1990 as a base period (1990=100) and
shows the level of current prices for all non-energy commodities in each year. In addition, constant prices for
these goods are also reported. Constant prices were derived by deflating current non-energy commodity prices
in each year by the unit value index of manufactures (MUV) exported by France, Germany, Japan, United
Kingdom and the United States. The MUV index is expressed in terms of US dollars and is derived by
converting prices of the first four countries exports into dollars at average annual exchange rates.
Non-Energy Commodity Price Index (USS)
i X
6 ,-
- 0 e - ----- ----- ---_ --- - -_
00I -- -- _ _ _ _ _ _ _ _ __ ___ _ __ I
Cirreni pr,ce - Consiant pnces
Two important trends are evident in the figure with the first relating to the importance of commodity
price instability. As shown, current non-energy commodity prices experienced three full cyclical swings over
the full interval, in 1982-86, 1987-91, and 1993-98. Average prices experienced their greatest variation in the
first period where the difference between the highest and lowest annual prices was about 50 percent.
Second, although the downward trend in constant prices continued in the last decade the figure
provides some indication that the rate of decline may have slowed. However, this may have been almost
exclusively due to the practice of expressing the MUV index in terms of US dollars, and the unusual strength
of the dollar against other currencies in the mid- to late 1990s.
When viewed from the perspective of individual African countries there is considerable
variation in the real prices they received for their traditional exports (Table 12). Three countries,
namely, Angola, Ethiopia and Madagascar saw real prices for their exports increase over the last
decade, although in 1999 they were still down sharply from 1980 levels. Mauritius was one of
38
the hardest hit countries due to sugar, which accounts for about 90 percent of traditional exports.
The 50 percent decline for Benin, the second largest in the table, is largely due to cotton.
Table 12. Estimates of Real Price Changes for African Traditional Products (1990 = 100)
Estimated Level of Real Prices (1990 = ]00) Percentage Change (%)
Exportine Country 1980 1990 1998 1999 1980-1999 1990-1999
LARGER COUNTRIES
Angola 255.0 100.0 118.0 101.3 -60.3 1.3
Kenya 156.3 100.0 194.5 92.5 -40.8 -7.5
Cameroon 128.9 100.0 88.7 92.1 -28.6 -7.9
Ghana 148.9 100.0 89.6 87.8 -41.0 -12.2
Nigeria 152.0 100.0 91.8 87.6 -42.4 -12.4
Zimbabwe 96.7 100.0 93.0 84.8 -12.3 -15.2
Coted'lvoire 257.3 100.0 111.7 84.4 -67.2 -15.6
Gabon 101.9 100.0 80.3 77.3 -24.1 -22.7
Liberia 109.2 100.0 81.9 76.7 -29.7 -23.3
SACU 156.1 100.0 71.7 70.3 -55.0 -29.7
Congo, Republic 123.1 100.0 69.2 67.5 -45.2 -32.5
Congo, Democratic Republic 138.8 100.0 69.6 66.8 -50.0 -33.2
Zambia 113.3 100.0 62.3 59.2 -47.7 -40.8
Mauritius 305.7 100.0 70.5 52.4 -82.8 -47.6
All Larger Countries 160.2 100.0 92.3 78.6 -50.9 -21.4
MID-SIZE COUNTRIES
Ethiopia 369.7 100.0 144.4 118.7 -67.9 18.7
Madagascar 284.9 100.0 122.2 104.0 -63.5 4.0
Uganda 214.8 100.0 115.3 99.4 -53.7 -0.6
Guinea 186.1 100.0 98.1 87.3 -53.1 -12.7
Malawi 93.9 100.0 94.5 86.2 -8.2 -13.8
Tanzania 111.4 100.0 92.7 84.0 -24.6 -16.0
Mauritania 117.8 100.0 92.3 82.8 -29.7 -17.2
Senegal 125.1 100.0 90.6 79.2 -36.7 -20.8
Togo 194.5 100.0 92.8 77.6 -60.1 -22.4
Mozambique 113.8 100.0 79.3 73.5 -35.4 -26.5
Sudan 156.1 100.0 77.8 64.1 -58.9 -35.9
Mali 157.4 100.0 76.2 62.2 -60.5 -37.8
Benin 105.5 100.0 56.2 49.5 -53.0 -50.5
All Mid-Size Countries 171.6 100.0 94.8 77.1 -55.1 -22.9
All Above Countries 165.7 100.0 93.5 77.9 -53.0 -22.1
Source: Based on World Bank (2000, p. 82)
B. Recent Price Instability for Traditional Products
Key Observations
Traditional product price instability appears to be a major problem for exporters.
Average annual price changes for these goods generally exceeded those for the all non-oil
commodity price index, while one-half the traditional products experienced average price
changes that were at least 50 percent greater. However, annual data clearly understate
instability problems since traditional product prices often experienced sizable consecutive year
directional changes. Over a three year period, consistent directional price shocks as high a
101 percent occurred, while changes of 150 percent were observed in the four consecutive year
39
data. These major price swings are generally associated with a "collapse" of traditional
product prices as, over 80 percent of the time, they were in a downward direction.
While the previous analysis strongly indicated Africa should have negative expectations
concerning trends in traditional product prices, a second important consideration is price
instability and its impact on economic variables such as the level of export earnings and the
terms of trade. Abrupt changes in the terms of trade may have an especially strong impact on the
macroeconomic performance and incomes of commodity exporting developing countries. In an
IMF report, Cashin and Patillo (2000) cite an example involving arabica coffee which is the
dominant export of Ethiopia. The slump in world coffee prices in 1986-87 resulted in a 40
percent fall in Ethiopia's terms of trade. Because imports were about 15 percent of Ethiopia's
national expenditure, this adverse movement in the terms of trade resulted in a decline of about 6
percent in real income.
This example raises an important question. What does the recent record reveal regarding
the stability of traditional product prices and how does it compare with that for other types of
goods? Relevant empirical information may be derived from three measures of price instability.
The first is the average absolute percentage change in prices, which is expressed as,
(5) I = [ ( Ut - Ut1 Ut1) N-1] 100
where U, is the unit value for the good in year t and N is the number of years used for the
calculation of the index. Absolute values are used to avoid the problem of positive and negative
changes canceling each other out. However, if prices were subject to a significant predictable
trend, say consistently rising, or falling, by 15 percent per year, equation (5) would overstate the
degree of "unexpected" instability. For this reason, a linear trend was fitted to the annual price
data and the coefficient of determination (R2) used as measure of "unanticipated" instability.
That is, the higher the coefficient the lower the level of unanticipated variation. Finally, the
percentage difference in prices at the beginning and end of the last decade is employed as a
measure of secular price instability.
Table 13 summarizes the 1990-99 results when these price instability indices were
computed for each traditional product. For comparison, similar statistics are shown for the all
non-oil commodities index and for the manufactures export unit value index. Two points are
evident from the data,
Compared to both the MUV and the all non-oil commodity index, many traditional
products experienced a relatively high degree of instability. Gold, coffee and nonferrous ores
had average annual price changes of over 20 percent, which was more than four times higher
than the MUV index. Even relative to the non-oil commodity index, traditional products
generally experienced a relatively high degree of instability. Twenty three (66 percent)
experienced a higher level of instability, and in 16 cases the average annual instability was more
than 50 percent greater.23
40
As evidenced by the R2 measure, few traditional products experienced "predictable"
price variation. More than one-half the products had an R2 of 0.10 or less, and a time trend
explained 50 percent or more of the annual variation in prices for only 6 traditional commodities
(saw logs, manganese ore, products of melted ores, sisal, fruit., and coal).
It could be argued that the annual indices reported in Table 13 may understate the true
magnitude of instability for a primary commodity. Consistent directional changes for a
commodity may occur over a period longer than a year, or start in (say) the middle of one year
and end in the middle of the next, and this would not be accurately reflected in annual data. For
this reason, Table 14 reports the maximum positive and negative percentage price change that
occurred for each traditional product over consecutive three and four year intervals during the
last decade. As an example, the average annual variation in prices for other nonferrous ores was
24.7 percent, but in one consecutive three year period (1990 to 1992) prices fell by more than
one-third. However, for the consecutive four year period from 1992 to 1995 prices rose by 150
percent. Price changes of these magnitudes clearly would constitute major terms of trade shocks.
23 This result was not entirely unexpected since, at any given point in time, prices for specific commodities included in the
general non-oil commodity index may be changing in different directions. This would tend to reduce the overall
fluctuations in the index. UNCTAD counted on a less than perfect co-variation in commodity prices to reduce
financial requirements of the common fund.
41
Table 13. Price Instability Indices for Individual Traditional Products
Range in 1990-99 Unit Values ($000 per ton) Price Instability Indices
Percent (%) Ave Annual
Traditional Product High Low Difference R2 % Change
Other Nonferrous Ores 0.55 0.22 150.0 0.06 24.7
Coffee Green or Roasted 3.68 1.57 134.4 0.34 22.5
Non-Monetary Gold 4.50 1.61 179.5 0.30 20.8
Sheep Skins Without Wool 7.83 3.35 133.7 0.00 16.1
Other Leathers 24.99 12.50 99.9 0.43 15.8
Ferrous Alloys 1.08 0.66 63.6 0.03 15.2
Raw Goat and Kid Skins 5.85 3.28 78.4 0.09 14.6
Groundnut Oil 1.12 0.74 51.4 0.00 14.2
Sesame Seeds 1.35 0.95 42.1 0.28 13.9
Raw Cotton 2.05 1.30 57.7 0.01 13.9
Saw and Veneer Logs 0.17 0.09 88.9 0.76 13.8
Copper Alloys Unwrought 2.92 1.60 82.5 0.31 13.6
Aluminum Alloys Unwrought 2.03 1.31 55.0 0.03 13.1
Manganese Ore, Concentrated 0.16 0.07 128.6 0.89 12.5
Natural Gums and Resins 3.12 1.47 112.2 0.26 12.4
Metaliferous Nonferrous Wastes 1.01 0.73 38.4 0.04 12.2
Products of Melted Metal Ores 0.05 0.03 66.7 0.67 10.3
Cotton Seeds 0.26 0.15 73.3 0.02 10.3
Sisal or Agave Fibers 0.74 0.47 57.4 0.53 10.0
Cocoa Beans, Raw or Roasted 1.65 1.15 43.4 0.30 9.6
Beryllium and Titanium 6.70 5.01 33.7 0.01 9.6
Chemical Wood Pulp 0.90 0.66 36.4 0.00 9.0
Cocoa Butter and Paste 3.28 2.42 35.5 0.14 8.3
All Non-Oil Commodities 112.1 78.9 42.0 0.01 8.1
Raw Beet and Cane Sugar 0.68 0.55 23.6 0.02 7.6
Shell Fish, Fresh or Frozen 4.58 3.59 27.6 0.08 7.2
Fruit, Fresh or Dried 1.24 0.96 29.2 0.56 7.2
Other Coal Not Agglomerated 0.05 0.04 25.0 0.69 7.1
Lumber Shaped Non-Conifer 0.80 0.61 31.1 0.02 6.8
Parts of Tobacco Leaf or Stems 5.85 3.28 78.4 0.00 6.7
Tobacco Stripped 5.55 4.42 25.6 0.28 6.7
Iron Ore Not Agglomerated 0.03 0.02 50.0 0.46 6.4
Prepared or Preserved Fish 3.57 3.09 15.5 0.08 6.2
Asbestos Simply Worked 0.60 0.49 22.4 0.10 6.1
Tea 1.12 0.74 12.8 0.14 5.3
Natural Calcium Phosphates 0.53 0.43 23.2 0.08 4.0
Memo Item*
Manufactures Export Unit Value 110.1 94.0 17.1 0.06 4.6
* UNCTAD reports that the MUV index rose from 97.6 in 1993 to 110.1 in 1995 (1990 = 100) and then fell from the 1995 level
to 94 in 1999.
Source: Based on import unit value statistics computed from COMTRADE data.
Two important points are evident in these statistics. First, the annual data clearly
understate the potential importance of secular price changes for traditional product. Over a three
year period, average maximum consecutive year price changes were almost 28 percent, for the
four year period they averaged 33 percent. The latter was about three times the variation in the
annual price data. Second, the statistics suggest that the shocks are more likely to be associated
42
with a collapse of traditional product prices as over 80 percent of the four year changes were in a
downward direction.
Table 14. Average Annual and Maximum Consecutive Year Changes in Traditional Product Prices During 1990-99
Average Maximum Consecutive Year
1990-99 Ranee in Unit Values Annual Price Change Over:
Percentage Price Three Four
Traditional Product High Low Difference Chan2e (%) Years Years
Other Nonferrous Ores 0.55 0.22 150.0 24.7 -34.1 150.0
Coffee Green or Roasted 3.68 1.57 134.4 22.5 -28.3 -37.8
Non-Monetary Gold 4.50 1.61 179.5 20.8 101.1 *
Sheep Skins Without Wool 7.83 3.35 133.7 16.1 22.3 *
Other Leathers 24.99 12.50 99.9 15.8 -35.5 -49.7
Ferrous Alloys 1.08 0.66 63.6 15.2 -27.5 -31.3
Raw Goat and Kid Skins 5.85 3.28 78.4 14.6 -23.6 -43.9
Groundnut Oil 1.12 0.74 51.4 14.2 -31.5 -19.2
Sesame Seeds 1.35 0.95 42.1 13.9 -26.9 -31.1
Raw Cotton 2.05 1.30 57.7 13.9 -29.7 -28.2
Saw and VeneerLogs 0.17 0.09 88.9 13.8 -20.0 -33.3
Copper Alloys Unwrought 2.92 1.60 82.5 13.6 -25.6 -32.8
Aluminum Alloys Unwrought 2.03 1.31 55.0 13.1 -23.6 -20.7
Manganese Ore, Concentrated 0.16 0.07 128.6 12.5 60.0 *
Natural Gums and Resins 3.12 1.47 112.2 12.4 -38.0 -48.1
Metaliferous Nonferrous Wastes 1.01 0.73 38.4 12.2 -17.8 -27.7
Products of Melted Metal Ores 0.05 0.03 66.7 10.3 50.0 66.7
Cotton Seeds 0.26 0.15 73.3 10.3 -19.2 -18.2
Sisal or Agave Fibers 0.74 0.47 57.4 10.0 34.0 48.0
Cocoa Beans. Raw or Roasted 1.65 1.15 43.4 9.6 36.5 *
Beryllium and Titanium 6.70 5.01 33.7 9.6 -15.3 -18.1
Chemical Wood Pulp 0.90 0.66 36.4 9.0 -21.3 -22.5
Cocoa Butter and Paste 3.28 2.42 35.5 8.3 35.5 -18.8
All Non-Oil Commodities 112.1 78.9 42.0 8.1 -33.2 -29.6
Raw Beet and Cane Sugar 0.68 0.55 23.6 7.6 20.8 31.3
Shell Fish. Fresh or Frozen 4.58 3.59 27.6 7.2 27.6 -10.7
Fruit, Fresh or Dried 1.24 0.96 29.2 7.2 -17.1 -17.7
Other Coal Not Agglomerated 0.05 0.04 25.0 7.1 -16.7 -20.0
Lumber Shaped Non-Conifer 0.80 0.61 31.1 6.8 -12.5 -20.0
Parts of Tobacco Leaf or Stems 5.85 3.28 78.4 6.7 27.9 *
Tobacco Stripped 5.55 4.42 25.6 6.7 -11.2 16.6
Iron Ore Not Agglomerated 0.03 0.02 50.0 6.4 -33.3 *
Prepared or Preserved Fish 3.57 3.09 15.5 6.2 -9.0 *
Asbestos Simply Worked 0.60 0.49 22.4 6.1 15.4 -16.9
Tea 1.12 0.74 12.8 5.3 9.2 *
Natural Calcium Phosphates 0.53 0.43 23.2 4.0 -10.4 -11.9
AVERAGE PRICE CHANGE** 11.2 27.7 33.0
Memo Item
Manufactures Export Unit Value 110.1 94.0 17.1 4.6 12.9 -14.6
* No consecutive yearly directional change occurred for this product over a four year period during 1990-1999.
** The averages shown in this row are only for traditional product prices.
Source: Based on import unit value statistics computed from COMTRADE data.
43
C. Price Formation for Primary and Processed Traditional Products
Key Observations
Shifting the composition of exports from unprocessed to processed traditional products
may reduce price and export earnings instability if demand for processed traditional products
like chocolate, tobacco manufactures, or ferrous metals is relatively stable, or if
"administered"pricing is usedfor these goods. The supporting evidence for this proposition is
strongest for traditional products where further processing is normally labor intensive, but no
similar pattern occurs for foodstuffs and most metals. Over the last decade there is little
evidence that prices for processed traditional products were rising faster, or falling less, than
those for unprocessed products. However, prices for processed traditional products often
incorporate a substantial "mark up" over those exported in raw form.
For countries who view the reduction of export price instability as an important objective,
a relevant question is whether this could be accomplished by further local processing of
traditional exports. The markets for some processed traditional products, like chocolate, coffee
extracts, plywood and veneers, or cotton thread and fabric may be more stable, particularly if
administrative pricing is employed, or the demand for these goods is less volatile. A related
question is whether major differences exist in longer term trends in primary and processed
traditional product prices. That is, does the evidence suggest the spread between primary and
processed traditional product prices is growing.
To derive relevant empirical information, a review of the SITC Revision 2 system was
undertaken with the objective of identifying groups that were primary or processed traditional
products. These efforts resulted in the identification of a primary and processed stage for 21
traditional commodities, and in several cases the S1TC also included an intermediate stage
product. As an example, cocoa beans and chocolate are the primary and final stages of the cocoa
processing chain, while cocoa powder and butter constitute intermediate stage products. Annex
3 provides details on the SITC based processing chains for traditional products.
Annual import statistics for the primary and processed stages of each chain were drawn
from UN COMTRADE for the last 1990-99 period and unit values were computed. Next, the
two measures of price instability (equation 5 and the R2 measure) were calculated along with the
percentage change in the primary and processed traditional product's prices over the last decade.
Table 15 reports statistics for these indices. Using plus and minus symbols the table has
been "coded" to quickly indicate where further processing of a traditional product leads to
greater stability or secular price increases (+), while a negative (-) symbol indicates prices have
fluctuated less (or risen more) for the unprocessed traditional product. For example, both the
average annual change and R2 measure indicates prices for jute fabrics, the final stage product in
the chain, are more stable than those for jute fibers. However, over the last decade the price
increase for fibers exceeded that for fabrics. These comparisons reveal three points,
First, the general association between further traditional product processing and
increased price stability does not appear to be as strong as might have been thought. Average
44
annual final stage price changes were lower for roughly one-half (11 of 21) of the processed
products, and the R2 measure suggests the price changes for 70 percent of the processed goods
was more predictable.
Second, the relationship between further processing and price stability appears
strongest within the paper, wood, leather and fibers groups where only one chain (sisal) recorded
a lower instability index for the primary as opposed to processed stage. Part of the explanation
for the stronger relationship in these sectors may be that the processing function for the final
stage good is labor intensive. With, relatively stable, wages accounting a high share of
production costs this may dampen pressures for frequent price changes.
Third, and quite unexpected, is the fact that secular 1990-99 changes in primary stage
prices fell less, or rose more, than their processed stage counterparts in 14 of the traditional
product chains. In several cases, the differences were sizable. For example, jute prices declined
by about 4 percent while prices for jute fabrics (the final stage item) fell by almost 13 percent.
One possible explanation for this general pattern is that the '1990s was a period of downward
pressure on both primary and processed traditional products. Primary commodities are typically
produced with low value added coefficients that may have little room for contraction before
production must halt. In contrast, there may be more scope for price reductions for processed
products with their relatively higher value added.24
24 Some evidence to this effect is reflected in the price margins between primary and processed traditional products. For iron,
manganese and aluminum the 1999 ratio of primary to final stage prices ranges between 0.02 and 0.05. For asbestos it is 0.07,
while the ratio for copper is 0.13. Price ratios for timber, wool and leather range between 0.07 and 0.11. Considerably high
primary-processed product price ratios are observed within the food products group.
45
Table 15. Instability and Longer-Term Price Changes for Primary and Processes Traditional Exports
Alternative Measures of Annual Price Instability
Average Annual Secular Price Changes
Percentaze Change (%)* The R2 Index 1988-89 to 1998-99 (%)
Stability Stability Trend Growth
Primary Final More (+) or Primary Final More (+) or Primary Final More (+) or
Processing Chain Stage Stage Less (-) Stage Stace Less (-) Stage Stage Less (-)
FOOD & TOBACCO
Fruit 7.56 7.58 - 0.01 0.37 + 6.5 -7.0
Fish 8.28 8.73 - 0.20 0.01 - 2.2 16.0 +
Shellfish 7.18 6.48 + 0.08 0.14 + 7.6 -4.6
Sugar 7.65 9.57 - 0.01 0.30 + -4.7 2.9 +
Cocoa 9.57 6.45 + 0.30 0.17 - 2.9 -1.2
Tobacco 5.54 6.67 - 0.23 0.28 + 15.6 -3.5
Cotton Seed 10.31 12.89 - 0.02 0.09 + 5.0 1.0
Groundnuts 6.49 14.20 - 0.30 0.00 - -1.2 -1.6
PAPER AND WOOD
Paper 10.41 8.58 + 0.34 0.47 + -15.5 -12.6 +
Lumber 13.79 6.75 + 0.76 0.77 + -37.8 -24.2 +
FIBERS AND LEATHER
Cotton 13.87 8.27 + 0.01 0.47 + -10.6 -13.9
Jute 9.28 8.08 . + 0.04 0.13 + -3.8 -12.7
Sisal 10.00 8.23 + 0.53 0.15 - 21.8 -11.0
Wool 17.69 11.63 + 0.19 0.67 + -43.2 -36.8 +
Leather 11.52 7.28 + 0.07 0.32 + -29.6 -7.4 +
MINERALS & METALS
ksbestos 6.10 6.15 - 0.10 0.25 + -0.3 -2.1
Iron 6.37 10.06 + 0.46 0.27 -3.6 -21.7
Copper 18.58 9.50 + 0.18 0.34 + -46.9 -27.6 +
Aluminum 7.41 8.92 - 0.21 0.34 + -9.0 -19.8
Manganese 12.46 13.55 - 0.89 0.31 - -36.1 -39.7
ENERGY PRODUCTS
Petroleum 16.29 12.65 + 0.30 0.22 - -25.4 -46.5
* In order to identify individual stages of a processing chain for traditional products, it was sometimes necessary to operate at a somewhat higher SITC level than that used for the
actual identification of these goods. For example, the primary stage of the fruit processing chain is SITC 057 (fresh fruit), while SITC 0579 is the (less aggregate) designation of
the traditional product. This was necessary because the four-digit SITC traditional product code could not be directly linked to a higher processed stage. Differences in SITC
levels cause of the unit values shown below to differ from those reported in Tables 13 and 14,
Souirce: Authors' estimates.
D. The Outlook for Traditional Product Prices
Key Observations
Long term price projections by the World Bank provide some indication of likely future
trends for traditional products. These price forecasts reinforce the basically negative outlook. With
the sole exception of coffee, 2010 real prices for traditional products are projected to be lower, often
substantially so, than they were in 1990. Even from a depressed 1999 base period, the Bank
anticipates a further deterioration in real prices for more than one half the traditional products,
which ranged up to 16 or 17 percent in the case of tobacco, groundnut oil and gold. This adverse
price outlook for most traditional products accents the need for Africa to adopt policies that would
allow the region to remain efficient low-cost su7ppliers of these goods.
The general impression from statistics on recent global demand and price changes for Africa's
traditional exports is clearly negative. Aggregate demand growth in major markets for almost two-
thirds of the products was essentially static or negative (Table 5), while real prices for most of these
goods were declining. This raises an important question. Is the future outlook for traditional products
basically for a continuation of past trends, or is there some reason why a more optimistic view is
warranted.
Longer term price projections by the World Bank (2000) provide some indication as to likely
future developments. Essentially, the Bank projected prices for about 50 primary commodities through
the year 2010 and also provided statistics on recent price trends for these goods. One problem,
however, is that the Bank's forecasts only cover 13 traditional products, and an additional 7
commodities that are also exported by Sub-Saharan Africa. Table 13 summarizes the Bank's forecasts
for real prices of these products through the current decade.25
Essentially, these price projections reinforce the general negative outlook for Africa's
traditional products. With the sole exception of coffee, 2010 real prices for all traditional products are
projected to be lower, often substantially so, than they were in 1990. Even from a depressed 1999 base
period, the Bank anticipates a further deterioration in prices for more than one half the traditional
products. These range upward to 16 or 17 percent in the case of tobacco, groundnut oil and gold. A
roughly similar pattern is projected for other African commodity exports where real prices for 5 of the
7 products in 2010 are projected to be lower than their level in either 1990 or 1999. In short, the
Bank's projections do not anticipate a reversal in the long term deterioration in traditional and other
commodity prices.
25 The World Bank (2000, p. 80) publishes related statistics that suggest considerable uncertainty is often associated with its projections.
For example, from a 1990 base of 100. cocoa prices in 2005 are forecast to be 125 with a 70 percent confidence interval (our italics)
ranging from 69 to 183. The width of this interval indicates that cocoa prices may be either substantially higher, or substantially lower,
than their level (109.6) in 1999.
47
Table 16. 1990 Constant and Projected Prices for Traditional
1990-2010
Prices in 1990 Dollars Proiected Prices Projected
Commodity price/unit 1980 1990 1999 2001 2005 2010 % Chanee
TRADITIONAL PRODUCITS
Coffee, Robusta cents/kilo 450.6 118.2 143.8 103.8 136.5 138.7 17.3
Cocoa cents/kilo 361.7 126.7 109.6 96.5 125.5 125.9 -0.1
Logs, Cameroon $/cum 349.7 343.5 260.0 284.9 284.5 310.9 -9.5
Aluminum $/mt 2.023 1,639 1,314 1,471 1.506 1,406 -14.2
Natural Phosphates $/mt 64.9 40.5 42.5 40.4 36.9 34.1 -15.8
Tea cents/kilo 230.5 205.8 177.6 171.9 163.2 155.5 -24.4
Iron Ore cents/dmtu 39.0 32.5 26.6 27.1 26.8 24.4 -24.9
Cotton cents/kilo 286.5 181.9 113.1 119.6 132.8 133.8 -26.4
Tobacco $/mt 3,162 3,392 2,922 2,849 2,719 2,443 -28.0
Copper $/mt 3,032 2,661 1,519 1,746 1,841 1,777 -33.2
Groundnut Oil $/mt 1,193.0 963.7 760.6 735.3 686.1 629.2 -34.7
Sugar cents/kilo 87.8 27.7 13.3 13.1 16.7 17.8 -35.8
Gold $/troy oz 844.7 383.5 269.2 257.4 230.1 222.1 -42.1
OTHER PRODUCTS
Coconut Oil $/mt 936.1 336.5 711.8 574.5 518.8 481.2 43.0
Palm Oil $/mt 810.9 289.8 421.0 321.7 355.6 340.5 17.5
Soybean Oil $/mt 830.2 447.3 412.6 376.8 384.9 388.6 -13.1
Tin cents/kilo 2,330.5 608.5 521.8 514.7 493.7 451.6 -25.8
Zinc cents/kilo 105.8 151.4 103.9 106.6 100.4 92.5 -38.9
Lead cents/kilo 125.8 81.1 48.5 48.3 50.2 47.4 -41.6
Nickel $/mt 9,056 8,864 5,805 7,353 5,021 5,034 -43.2
Memo Item
All Non-Energy Commodities 1990 dollars 174.3 100.0 85.0 86.7 90.1 86.3 -13.7
Manufactures Unit Value Index 1990 dollars 72.0 100.0 103.6 106.2 119.5 135.1 35.1
Source: Adapted from World Bank (2000).
E. Implications of the Competitive Situation
Key Observations
Changes in Africa*s ability to compete in global markets have the potential to substantially
alter what the region should expect from its traditional products. If Africa's global market shares
for these products experienced substantial erosion this would make the already poor demand and
price related expectations worse. However, the overall competitive changes that occurred over the
last decade were generally so sma1l that their general influence was negligible. This is not the case,
however, for one or two individual traditional products (like copper) where a significant erosion of
global market shares occurred.
The preceding analysis contained very little that was positive concerning recent trends and
future prospects for traditional products. Real prices for these goods fell by about 24 percent over the
last decade and were about 40 percent below their 1980 levels. Available World Bank forecasts are
also generally pessimistic with predicted real prices in 2010 generally lower than their, already
depressed, 1999 base. However, there is one factor, namely, changes in the African countries ability to
48
compete that could potentially alter expectations for traditional products. If Africa is generally losing
global market shares for these goods it could make the already dim outlook worse, just as increasing
market shares have the potential to improve the general outlook.
Relevant information concerning this point can be derived using an approach that quantifies the
effects of market share changes on exports. This "competitive effects index" for product j ( C]) is
expressed as,
(6) CG = (sa,t - Sa,o) Jg.t
where Sa,t and sa,o represent Africa's global market share for the good in base year o and end year t,
while Ig., represents global imports of the traditional product in year t. The index indicates the dollar
value of export gains or losses associated with a country, or group of countries, market share changes.
Summing equation (6) over all traditional products will indicate whether their competitive position
improved or worsened, and what was the magnitude of the associated change in the value of exports.
The values for the index can be computed for each traditional product using the statistics presented in
Table 1.
When these computations are made the overall the outlook is slightly negative. Competitive
share changes resulted in an overall decrease in 1999 exports of about $570 million, which is only
about a one-half a percentage point reduction in exports. Cormpetitive changes have the potential to
alter general expectations for traditional products, but they have not significantly done so in total.
However, this is not the case for several traditional products like copper, platinum, and groundnut oil
where substantial market share loses will further aggravate unfavorable price prospects if they
continue. In contrast, African prospects for a few products like cocoa, sisal and sesame seeds have
been enhanced by competitive share gains.
V. OVERALL EXPORT PROSPECTS
Key Observations
An "export growth prospects" index is used to empirically assess what African countries
should expect from their traditional and non-traditional exports. The index facilitates comparisons
of prospects for any given exporter with those of other regional or non-regional countries, or with
the general growth in world trade. Numeric values for the index show Africa should expect its
traditional exports growth to fall well short of that for world trade. The index also suggests the
growth prospects for Africa's non-traditional exports are ojften more favorable. However, non-
traditional exports probably could not significantly improve the general short-term outlook for
Africa's exports since they normally constitute a small share of most Africa countries' trade. Short
to medium-term prospects will be strongly affected by the SSAL countries ability to become relatively
low cost producers of traditional products and to remove any anti-export biases in their domestic
regulations.
A key question relating to rational expectations for future exports concerns how well the
current trade profile of a country positions it among relatively high growth products. The preceding
49
analysis showed that many African traditional exports had negative characteristics, such as low income
elasticities of demand and below average global trade growth rates. However, although traditional
products constitute a high share of most SSA countries total exports (see Appendix Table 2) variation
occurs across countries in their importance relative to non-traditional goods. This observation poses an
important question. Are the prospects for nontraditional products significantly different that they could
alter what African countries should expect from their total exports.
This point can be addressed through the use of an index that provides summary information on
a country's trade growth prospects. The index allows any African country to compare its export
prospects to those of other regional or non-regional exporters, or to the general growth in world trade.
The index also makes it possible to assess the likely influence of policy induced changes in the
"basket" of goods exported on trade growth rates. For example, it could help indicate what influence
a shift in exports from primary to processed commodities might have on export growth. Similarly, it
could help determine how efforts to increase trade in specific products like (say) those manufactures in
which the country has an established competitive export base, could influence exports.26
26 The simulations assume policy makers have some prior knowledge of what products could be competitively exported. This
information might come from a country's actual export experience with related products, or from specially designed surveys of
enterprises engaged in a country's commerce. See the World Bank (2001 b) for a useful application of this approach.
50
Table 17. The Trade Prospects Index For Three Groujps of African Exports
GROUP I GROUP II GROUP III DIFFERENCE
Current Export All Traditional Non-Traditional Group Ill Versus
African Exporter Structure* Products* Exports Onlv* Group If
LARGER COUNTRIES
Mauritius 1.18 0.53 1.41 0.88
Kenya 0.55 0.35 0.84 0.49
Ghana 0.62 0.50 0.91 0.41
Liberia 0.50 0.13 0.54 0.41
Gabon 0.46 0.45 0.77 0.32
Cameroon 0.46 0.44 0.65 0.21
Nigeria 0.62 0.60 0.78 0.18
SACU 0.81 0.76 0.94 0.18
Congo, Democratic Rep. 0.70 0.60 0.73 0.13
Cote d'lvoire 0.46 0.44 0.55 0.11
Angola 0.62 0.60 0.67 0.07
Zambia 0.64 0.64 0.66 0.02
Congo, Republic 0.57 0.58 0.55 -0.03
Zimbabwe 0.58 0.61 0.53 -0.08
Average of Above 0.63 0.52 0.75 0.23
MID-SIZE COUNTRIES
Mali 0.29 0.24 0.87 0.63
Madagascar 0.90 0.60 1.12 0.52
Uganda 0.42 0.36 0.80 0.44
Senegal 0.56 0.38 0.81 0.43
Ethiopia 0.40 0.35 0.73 0.38
Mauritania 0.56 0.52 0.88 0.36
Togo 0.19 0.15 0.50 0.35
Mozambique 0.57 0.47 0.73 0.26
Benin 0.47 0.45 0.68 0.23
Tanzania 0.57 0.47 0.66 0.19
Malawi 0.74 0.73 0.81 0.08
Guinea 0.39 0.44 0.38 -0.06
Sudan 0.50 0.63 0.11 -0.52
Average of Above 0.50 0.45 0.70 0.25
*Group I shows growth prospects index values computed using actual 1999 shares of all traditional and non-traditional
exports. Group 11 shows the growth prospects index for traditional products. while Group IIl reflects growth prospects for
non-traditional products.
Source: Authors' estimates.
The export growth prospects index first establishes a concordance between the share of each
four-digit SITC product (i) in an African country's (j's) exports,. and the recent world trade growth rate
for that product. That is, if Sij is the current shiare of product i in country j's total exports, and Ri is the
rate of growth of i in world trade, the export prospects index (Pj) is defined as,
(7) Pj = [ Sij Rj]/Rw
where Rw is the rate of growth of world trade in all products. It should be noted that the index only
reflects the influence of global demand growth and assumes no changes occur in a country's
competitive position. Countries with an index above unity may be thought of as having above average
export growth prospects, while the reverse is true for those with indices below unity. Furthermore,
because the index is measured relative to the growth rate of world trade it shows how relatively
51
favorable, or unfavorable, are a country's export prospects compared to world trade.27 For example,
an index value of 0.50 suggests a country's exports should grow at one-half the rate of world trade. An
index value of 1.50 suggests the exports should grow 50 percent faster.
Table 17 shows export growth prospects index values for the African countries computed for
three different groups of exports. Group I employs 1999 shares for all of a country's four-digit SITC
(Rev. 2) traditional and non-traditional exports and, therefore, shows what might be expected from its
complete export profile.28 The second group index is for traditional exports. Comparisons of these
results with those for Group I will show whether traditional products make a higher, or lower,
contribution than average to export growth. In preparation for this simulation, the current trade shares
for all traditional products were proportionately upward adjusted so their sum was one hundred
percent. Group III assumes that only non-traditional products (that is, all other products aside from the
traditional goods) are exported. Comparison of the results for Groups II and III will help indicate how
important are relative differences in the prospects for traditional and non-traditional products. For this
reason, a fourth column was included in Table 17 showing differences in the indices generated for
Groups II and III. Positive values indicate the growth prospects for nontraditional products are
superior to those for traditional exports. For policy purposes this information could be useful for
identifying products that might be targeted for export promotion.
In several ways the results could have been anticipated from the earlier analysis. Traditional
products (Group II) have growth prospects that are significantly lower than those for world trade. The
average index for the larger countries (0.52) suggests that their exports could grow at a rate slightly
higher than one-half that of world trade, while the mid-size countries face slightly lower growth
prospects. However, comparisons of the cross group results reflects several important points:
With the exception of only four countries, the growth prospects index for product Group III
is higher than that for Group II, and often substantially so. This implies that the established
nontraditional exports have more favorable growth prospects than traditional goods. For the larger
countries, growth prospects for non-traditional products are about 45 percent higher than those for
traditional exports while the spread is even greater for the mid-size countries.
Mauritius clearly differs from other SSA countries in that its development of non-traditional
exports affords the possibility of growth prospects that are far more favorable than other African
countries. Mauritius overall index of 1.18 (Group I) indicates its nontraditional exports more than
compensate for the relatively low growth prospects of its traditional products (largely sugar).
27 Several caveats should be noted. First, use of this measure is justified by correlations showing longer-term relative growth rates for
trade in most products are stable. As such, a basic assumption of the index is the continuation of past trends. As an example, rank
correlations between the 1980 to 1989 and 1990 to 1999 export growth rates of all four-digit SITC products were statistically significant
at the 99 confidence level. Second, information provided by the index differs from a measures based on the rate of growth in a country's
total exports over a given period. The latter may be biased by changes in the relative importance of products, while the growth prospects
index is based on the relevant importance of products in the most recent period. Third, the measure assumes no changes occur in the
level of trade. A policy induced shift in structure toward faster growing products may not be advantageous if the level of trade declines.
Finally, the index can provide information on the likely influence of a policy induced change in the composition of exports on trade
growth rates, but it provides no information concerning the costs, or feasibility, of implementing the trade changes.
28 Since price instability for some commodities may bias estimates of their share in a country's total exports in a given year, export data
for the 1997-1999 period have been pooled to limit the influence of any unusual annual fluctuations. Similarly, in the computation of
individual four-digit product world trade growth rates pooled 1987 to 1989 and 1997 to 1999 were employed.
52
Mauritius is the only African country whose total exports appear to have the potential to grow faster
than world trade.
Although they have not yet had a major impact on overall trade prospects, Table 17 indicates
several African countries have developed some non-traditional exports that could potentially have a
important positive influence on export growth. Non-traditional exports of Madagascar have an average
trade prospects index exceeding unity, while the indices for Kenya, Mali and Uganda are well above
their "all product" averages (Group I). This raises two important questions. What non-traditional
products have these countries developed to improve their growth prospects, are there general
similarities in their production characteristics. Analysis of tlhese countries' 1999 export profiles
reveals the following points:
Mauritius. The development of an important non-traditional export base centered on textile
and clothing products which accounted for more than 60 percent of 1999 exports. This country's
textile and clothing export base continues to diversify and now covers 14 different four-digit SITC
product groups. Recently, non-traditional exports have expanded to include several "niche" products
like spectacle frames, clock movements and parts, and children's' toys.
Madagascar. The non-traditional product base has similarities to that of Madagascar. Textiles
and clothing accounted for 38 percent of all 1999 exports, and covered 11 different four digit SITC
groups. Another relatively high global growth non-traditional product, spices, accounted for 8 percent
of total 1999 exports.
Kenya. Textile and clothing products are of relatively minor importance as they account for
less than 4 percent of total 1999 exports. However, previous Multifiber Arrangement restrictions
placed on Kenya may have "frozen" textile and clothing exports at artificially low levels. Currently,
the most important high growth non-traditional export is "cut flowers" which accounts for about 11
percent of all exports. This one item is largely responsible for the relatively high Group III results.
Mali. The non-traditional trade base is very small, and cotton accounts for 83 percent of all
exports. However, a few textile and clothing products, works of African art, and microcircuits appear
in this country's non-traditional exports. Mali appears to have made some fledgling progress in
utilizing its relatively large domestic cotton production to move upstream into thread, fabric and
clothing exports. Given the importance of raw cotton and other fibers in many SSA countries exports,
an effort to determine what factors constrain further processing along these lines is warranted.
53
VI. POLICY IMPLICATIONS
Key Observations
This study's policy message for Africa is two fold. First, Africa must diversify away from
traditional products or continue to experience serious negative trade effects including; (i) declining
or relatively low growth in global demand for these goods, (ii) falling real prices for traditional
products, (iii) very unstable prices and export earnings, (iv) a continued marginalization in world
trade, and (v) diminished growth and industrialization prospects. However, there is no evidence that
any general diversification is occurring. Domestic and international policy inifiates must assign a
far greater importance to the needfor diversifying Africa's exports.
Second, it is unlikely that major shifts in the composition of exports can occur in the short to
medium-term. As such, the removal of general anti-export biases in African countries' domestic
policies, as well as initiatives to promote more competitive (low cost) prices for traditional exports,
still require immediate attention. Future markets for traditional products will be highly competitive
and African countries failing to implement policies promoting production efficiencies and lower
costs should expect to experience major competitive export losses for these key items.
If, at this point, we return to the question posed in the title of this study "What Can Africa
Expect from its Traditional Exports" the answers seemingly are quite clear. Africa can expect to
experience serious negative trade effects including; (i) declining or relatively low growth in global
-demand for these goods, (ii) falling real prices for traditional products and other similar commodities,
(iii) unstable prices and export revenues, (iv) a continual declining role in world trade, and (v)
diminished growth and industrialization prospects. The policy prescription for these problems is also
quite clear. Diversify away from traditional products. The importance of this policy prescription is
further strengthened by a recent World Bank study showing a strong positive relation exists between
export diversification and national growth rates (David de Ferranti et. al 2001).
Unfortunately, what is not clear are the appropriate policy measures that should be adopted to
implement this policy prescription. Available statistics show African countries have made little or no
recent progress in diversifying their exports. In fact, Ng and Yeats (2000, pp. 22-23) found that "no
major changes in the diversification of African exports occurred in the 1990s, indeed several statistical
indices suggest some African countries' exports became more concentrated". One approach that has
been suggested for diversification involves the further local processing of domestically produced
primary commodities (see UNCTAD 1975, Roemer 1979, Yeats 1981 or, more recently, de Ferranti et.
al. 2001). Although proposal advocating the use of these "natural resource based" industrialization and
diversification strategies date back to (at least) the early 1970s, Africa has clearly made little related
progress along these lines. African anti-competitive, anti-open, domestic policies were, no doubt, a
29~~~~~~~~~~~~~~~2
key reason for this failure (Ng and Yeats 1997). 2
29 An interesting question is whether World Bank policies might do more to promote diversification. Brownbridge and Harrigan (1996)
examined changes in the export profiles of African countries that were involved in World Bank structural adjustment programs (SAPs).
They observe (p. 419) that, over a decade, sixty percent of the recipients exported a smaller number of products at the end of the period
than at the beginning. The authors concluded that "The emphasis placed by structural adjustment programs on price reforms to boost
exports is likely to be of greater benefit to the traditional primary commodity exports than to non-traditional exports, since the latter often
54
While this study's objective was not to formulate a strategy for African export diversification, a
recent World Bank (2001b) report made such an initiative for Ghana. Several points regarding this
effort should be noted. First, the Bank report utilized surveys of local domestic and foreign firms
engaged in various export activities to identify specific types of non-traditional products Ghana might
export successfully. Second, the Bank study extended the survey approach to determine what were the
impediments facing these potential exports. These procedures appear to have considerable merit and,
if applied in other selected Sub-Saharan African countries could provide a useful overview of the
region's prospects and problems in diversifying exports.
Box 5. Trade Restrictions Facing Primary and Processed Traditional Products
The essentially negative conclusions concerning what should be expected from Africa's traditional exports might
be altered if there was a marked improvement in international demand for these goods. The key question, however, is what
factor(s) rmight produce such a significant positive demand increase? An acceleration of income growth in the major
consuming countries would likely have only modest effects, given the relatively low income elasticities for most of these
goods (see Table 4). It also seems unlikely that competition from synthetics will abate, thereby raising relative demand for
traditional products. However, there is the possibility that a lowering of government imposed trade barriers against
traditional products might have a positive impact on demand, particularly if these barriers occur frequently and are high.
Although recent analyses show OECD trade barriers facing Africa are generally low (Amjadi et. al., 1996), there
are specific situations where they are of major importance. For example., OECD tariff files show African, and other
developing countries, face import duties of 170 percent on sugar exports tc, Japan, and over 40 percent in the European
Union. Similarly, US tariffs on unprocessed, or partially processed, tobacco (another traditional product) range from 27 to
39 percent. Constraints associated with the Multifiber Arrangement and high escalating tariffs clearly have a negative
impact on the further processing of some African natural fibers, like cotton, inito thread, textiles and clothing. Identification
of these OECD trade barriers could have a positive impact on demand for some specific primary and processed African
traditional products.
As far as specific policy initiatives are concerned recent EU proposals for a general "blanket" liberalization of all
trade barriers facing least developed countries' exports is particularly attractive. This "Everything but Arms" proposal
would eliminate government imposed trade restrictions on all least developed countries (most of which are located in
Africa) exports with the exception of armaments. See UNCTAD and Commonwealth Secretariat (2001).
While most previous analyses of trade barriers facing developing countries focused on restrictions in developed
countries, there are several reasons why this practice should change. First, developing countries have been growing
steadily in relative importance, as evidenced by the fact that almost one-third of all traditional product exports went to these
markets in 1999 (see Table 7). Second, real income levels of many developing countries, particularly those in East Asia,
have grown faster than the original OECD members, while the global economic importance of OPEC countries has
increased dramatically since the first early 1970 petroleum price increase. Clearly, the current situation requires that the
face other severe constraints such as inadequate technological, managerial, technical and marketing skills, infrastructure, and lack of
finance. Remedying these constraints has not been addressed in most SAPs in Sub-Saharan Africa."
30 Just as trade barriers in non-regional markets may constrain some African exports, particularly those of textiles, clothing, and products
that compete with temperate zone agriculture, the Bank survey uncovered similar problems in regional markets. For example, the report
notes that "Several problems constrain Ghana's ability to take full advantage of regiDnal trade opportunities; (i) lack of implementation
of the ECOWAS trade agreements, which result in discriminatory treatment of Ghanaian exports; (ii) transport logistics including
innumerable check-points within neighboring countries; and (iii) an inefficient import regime, particularly regarding duty drawbacks.
Box 4 provides summary information on average tariffs least developed African countries face in industrial and developing countries
markets.
55
Box S Continued
more advanced non-OECD countries accept some responsibility for improving the trade and economic prospects of Sub-
Saharan Africa, as well as the highly indebted least developed countries in other geographic regions.31
As far as the opening of markets is concerned, the tariff averages shown below suggest other developing countries
may have considerably greater scope for improving market access conditions for Africa than do industrial nations. These
statistics reflect average tariffs facing exports of selected product groups from least developed countries, most of which are
located in Africa. As indicated, the average duties outside industrial countries are often set at relatively high levels. In
non-industrial markets, tariffs facing least developed country exports for 39 (56 percent) of the product groups exceed 10
percent, and they exceed 15 percent for almost one-quarter of the groups. On average, the average tariffs in the non-
industrial countries are roughly on a par with import duties in OECD countries prior to the conclusion of the 1968 Kennedy
Round of Multilateral Trade Negotiations.
Industrial East South Other Europe Middle East & Latin
Product Countries Asia Asia & Central Asia North Africa America
Agriculture & Fish 2.1 14.0 28.3 11.9 7.6 14.8
Crustaceans 0.7 9.4 16.4 14.3 15.1 30.0
Other fish 1.8 22.7 13.8 9.6 12.8 14.6
Fruit and Nuts 0.1 6.4 38.0 8.9 13.0 17.0
Coffee 0.0 0.9 35.0 7.4 16.3 12.7
Oil seeds & grains 0.4 14.1 33.4 5.8 8.1 11.2
Other agriculture 5.1 3.2 13.0 18.4 29.2 16.8
Minerals and Fuels 0.0 4.5 6.5 0.7 14.4 5.9
Metal ores 0.0 1.3 5.0 0.0 12.0 0.0
Petroleum 0.0 4.5 30.0 3.9 20.0 6.0
Manufactures 4.4 2.4 24.7 8.0 12.6 10.3
Rubber and leather 2.8 1.4 13.0 13.8 12.7 11.5
Wood and products 0.4 2.0 7.7 3.2 11.5 18.1
Cotton products 0.3 2.0 4.5 0.0 11.9 8.4
Given the relative size of these non-industrial country markets, and the magnitude of the tariffs which they impose
on imports, it is clear that a selective trade barrier liberalization could potentially generate an important stimulus to demand
for traditional products. What is not widely recognized, however, is that an appropriate instrument has been negotiated and
ratified by developing countries for implementing the required liberalization.
In the mid-1980s, developing countries negotiated and ratified, under the auspices of the United Nations
Conference on Trade and Development (UNCTAD), an agreement referred to as the "Global System of Trade Preferences"
(GSTP) among developing countries. The GSTP called for the exchange of trade preferences among all developing
countries to help correct a number of perceived trade problems including the concentration of many developing countries
exports and their inability to penetrate new markets. In spite of the fact that major financial, time and other resources were
devoted to the negotiations, surveys by World Bank staff failed to identify and developing country which has implemented
the GSTP.
31 The World Bank (2001a, pp. 192-193) classifies countries into four income categories depending on their level of GDP per capita.
This classification accents the magnitude of the gap that exists between many countries in Africa and others that are often called
"developing" countries. For example, 38 "low income" African countries like Kenya, Tanzania, Uganda and others has 1999 GDP per
capita levels under $755, while upper "middle income" countries like Saudi Arabia, Brazil, Chile, Mexico and others had per capita
income levels that ranged upward to $9,265. Non-original OECD countries like Hong Kong, Singapore and Taiwan (China), and 27
other countries had GDP per capita ratios in excess of $9,265. Clearly, these higher income countries are in a position to make some
contribution toward improvement of African trade and economic prospects.
56
Box 5. Continued
This situation presents UNCTAD with a unique opportunity to both oversee initial first steps in the actual
implementation of the GSTP, and also to accomplish a needed liberalization of trade barriers facing African and other least
developed countries' exports. Specifically, medium and high income non-industrial countries should now taken the lead
and unilaterally extend GSTP preferences to Africa, just as the OECD countries unilaterally extended GSP preferences to
developing countries in the early 1970s. Furthermore, this proposed initial step in implementing the GSTP might be
accompanied by an agreed timetable for broadening the preferences to include other developing countries.
Second, this report identified a number of "dynamic" non-traditional products that Africa has
been able to export competitively (see Box 3). Given the negative outlook for traditional exports, a
further inquiry as to how Africa has been able to establish a successful competitive presence for these
fast growing products clearly seems warranted.
The impediments to diversification of exports which the Bank's Ghana report identifies, and
areas where corrective reforms are required, are very broad and encompass a wide range of financial,
tax, customs, legal, transport, educational policies, all of which are aimed at improving the commercial
environment within Ghana. The report emphasis the development of export processing zones
processing zones as a preliminary first step toward export diversification (p. 68), and discusses the
types of tax and financial incentives needed to attract foreign investment to these zones. Third, the
reports focus strongly suggest that internal constraints and disincentives, which can only be corrected
by Ghanaian action, lie at the center of obstacles to successful export diversification efforts.32 This
focus is consistent with those of other recent investigations that improvements in the internal domestic
and commercial environment hold the key to improved African trade and economic performance. The
nature of these improvements are such that they can only be implemented by the African countries,
themselves, and not by outsiders.
32 The report (p. 37) accents the importance of Lome Convention preferences in the EU and opportunities recently extended under the
U.S. Africa Growth and Opportunity Act for Africa as improving Ghana's competitive position in these major markets.
57
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60
Annex 1
Traditional Products and the Export Prospects of the Smaller Sub-Saharan African Countries
Key Observation
Four products, namely, cotton, saw logs, fish and coffee account for three quarters of the
small African countries traditional product exports, and their trade performance will largely be
determined by these commodities. World Bank projections anticipate real prices for these
commodities, except for coffee, remaining below their 1990 level. Aggregate income elasticity
estimates suggest demand prospects for the small countries' exports fall below those of both the
large and mid-size exporters. With one or two exceptions the smaller countries do not appear to be
developing an export base in the types of non-traditional products thiat could improve growth
prospects.
While this report's main text examined the trade prospects of larger and mid-sized African
countries, there are several relatively small countries that may be disadvantaged by their size, and the
fact that many are either islands or land-locked. Total exports for these smaller countries are generally
under $250 million, but may be as low as $10 to $25 million in the case of Cape Verde, Eritrea, or Sao
Tome & Principe. These countries are treated separately since previous studies indicate a relationship
may exist between country size and trade concentration (Khalaf 1974).33 That is, smaller countries
might be expected, ceterus paribus, to be more heavily dependent on a relatively fewer exports than
larger ones.
Annex Table I provides summary statistics on the 15 smaller African countries 1999 non-oil
exports of traditional products.34 Excluding the three petroleum producers (Equatorial Guinea,
Guinea-Bissau and Niger) the relative importance of non-energy traditional products in their total
exports is apparent. Traditional products account for more than one-half the total exports of 7 of the
12 countries, and their share reaches 90 percent, or more, for Rwanda and Burundi. In several cases,
one traditional product dominates a country's total exports. For example, almost 60 percent of
Rwanda's exports consist of coffee, cotton accounts for 61 percent of Burkina Faso's exports, while
fish preparations comprise 69 percent of the Seychelles exports.
33 In general, this study's statistics support the proposition. South Africa, the largest SSA country measured by either trade or GDP,
exports all 38 traditional products (see Appendix Table 3), while very small countries like Cape Verde, Chad, or Sao Tome & Principe
export 5 or fewer items. On average, the large African countries export 21 traditional commodities as opposed to 16 for the mid-sized
countries, and under 9 for the smaller countries. Once countries reach a certain threshold of development, however, the relationship
between country size and trade concentration seems to weaken. This is evidenced by the fact that some relatively small countries, like
Singapore, have a relatively diversified export base.
34 In 1999, total exports of Equatorial Guinea and Niger exceeded the $250 million limit used to define "small" countries. They have
been included here since, for most of the last decade, their exports were under this value and only recently increased dramatically due to a
surge in petroleum exports.
61
Annex Table 1. The 1999 Traditional Product Export Profile of Smaller African Countries.
Traditional Exports
Share of All
Exporter Largest Traditional Exports (Share of Total Exports) Number Exports (%)*
Burkina Faso Raw Cotton (61), Raw Sugar (9) 14 87
Burundi Coffee Beans (69), Non-Monetary Gold (14) 12 95
Cape Verde Shellfish (2) 4 2
Cent. African Rep. Raw Cotton (7), Saw Logs (6) 14 22
Chad Raw Cotton (82), Natural Resins & Gums (13) 5 95
Djibouti Non-Monetary Gold (18), Sheep Skins (8) 10 38
Equatorial Guinea Saw Logs (14) 6 15 (90)
Eritrea Non-Monetary Gold (46), Natural Resins & Gums (6) 9 58
Gambia Shellfish (25) 11 26
Guinea-Bissau Shellfish (9), Raw Cotton (3) 8 15 (52)
Niger Raw-totton (1) 10 2 (58)
Rwanda Coffee Beans (59), Tea (17) 10 90
Sao Tome & Principe Cocoa Beans (31), Shellfish (8) 3 40 (51)
Seychelles Prepared Fish (68) 9 69
Somalia Natural Resins & Gums (21), Sesame Seeds (12) 9 56
8 Numbers in parentheses include petroleum exports.
Source: Tabulations based on trade statistics reported to COMTRADE by countiies listed in the notes to Table 1.
Annex Table 2 provides a different perspective on these countries exports. Shown here are the
combined total 1999 values of the 15 largest traditional products and the number of small countries
that export each item. Combined, these 15 products account for about 99 percent of all traditional
product exports, but five commodities, namely, cotton, saw logs, prepared fish, coffee, and shellfish
are of primary importance accounting for more than 80 percent of the small countries' total exports.
The relatively high shares for fish, shellfish and coffee has potentially favorable implications since the
previous analysis (Table 5) showed these items had relatively high income elasticities. On the
negative side, 47 percent of the combined exports of these countries consist of cotton and saw logs
which appeared to have static growth prospects.
Although the instability indices are not shown, traditional product price volatility is clearly a
potential problem for the smaller countries. Annex Table 2 indicates that 10 of their 15 major export
products experienced 1990-99 annual price changes that exceeded those for the all non-oil commodity
average. In addition, 9 of the 15 products experienced a three year consecutive directional price that
exceeded 25 percent, often by a considerable margin.
62
Annex Table 2. Major Traditional Product Exports of the Smaller African Countries in 1999
Number of Share of Traditional Cumulative Exports
Traditional Product Exporters Exports (%) Share (1 ($000)
2631 Raw Cotton* 7 29.6 29.6 191.119
2472 Saw Logs* 8 17.4 47.0 112,245
0371 Prepared Fish 2 16.0 63.0 103,181
0711 Coffee Beans* 10 13.3 76.3 85,680
0360 Shellfish 13 4.8 81.0 30.676
97 10 Non-Monetarv Gold* 7 4.3 85.3 27,669
2922 Natural Resins and Gums* 7 2.5 87.7 18,843
0741 Tea 7 2.2 90.0 14,390
0611 Raw Sugar* 1 2.1 92.1 13,811
2483 Shaped Lumber 7 1.8 93.9 11,552
0721 Cocoa Beans* 5 1.6 95.5 10.430
2225 Sesame Seeds* 6 1.6 97.1 10,339
2879 Other Nonferrous Ores* 3 0.8 98.0 5.396
6116 Ferro-Alloys* 5 0.8 98.7 4.903
2223 Cotton Seeds* 1 0.4 99.1 2,394
All Above Items 15 99.1 99.1 639,628
All Traditional Products 15 100.0 100.0 645,504
* During the last decade average annual price instability for this product exceeded that for the all non-oil commodity
price index.
Source: Tabulations based on trade statistics reported to COMTRADE by countries listed in the notes to Table 1.
Annex Table 3 employs the traditional product income elasticity estimates to compute trade
weighted and unweighted average elasticities for each country. Considerable variation is observed in
the aggregate price adjusted elasticities due to the specific traditional products exported. Prepared fish
has one of the highest income elasticities of any traditional product and this one commodity largely
accounts for the high (2.10) aggregate estimate for the Seychelles. In contrast, raw cotton dominates
Burkina Faso's exports and the depressed demand for cotton over the last decade largely explains the
negative aggregate elasticity for this country. Taken together, the aggregated weighted and
unweighted elasticity estimates suggest the outlook for the smaller countries as a group falls below that
for the large and mid-size exporters.
63
Annex Table 3. Average Income Elasticities for Traditional Products Exported by the Smaller African Countries
Price Adiusted Income Elasticity Estimates
Trade Weighted Average
Exporter All Traditional Exports Unweichted Average
Burkina Faso -1.49 -0.38
Burundi 0.28 -0.35
Cape Verde 0.97 0.52
Cent. African Rep. -0.26 -0.01
Chad -1.66 -0.80
Djibouti -0.69 0.33
Equatorial Guinea 0.34 0.81
Eritrea -1.00 0.03
Gambia 1.04 0.75
Guinea-Bissau 0.50 0.62
Niger 0.79 0.66
Rwanda 0.28 -0.35
Sao Tome & Principe 1.51 1.10
Seychelles 2.10 1.56
Somalia -0.44 -0.71
All Above Countries 0.15 0.25
Memo Item
Large African Countries 0.63 0.50
Mid-Size Countries 0.36 0.32
Source: Tabulations based on trade statistics reported to COMTRADE by countries
listed in the notes to Table 1.
Future prospects for the smaller countries will be influenced by two factors; trends in real
prices for the relatively few products that dominate their exports (mainly cotton and saw logs which
account for almost one-half of their traditional exports), and their capacity to expand into faster
growing non-traditional product lines. Regarding the first point, World Bank projections anticipate
real prices for these commodities remaining below their 1990 level. Second, the available evidence
does not indicate the smaller African countries have been any more successful in diversifying and
developing an export base in non-traditional products that could enhance growth prospects (see
Appendix Table 1). Cape Verde is the sole exception as almost 40 percent of its 1999 exports
consisted of footwear and clothing products..
64
Annex 2
Prospects for the Petroleum Exporting Sub-Saharan African Countries
Key Observation
Several characteristics of Africa's petroleum trade differs substantially from other traditional
products. About 95 percent of the region's oil exports originate in only six countries, while most
other African countries are net oil importers. As such, a positive price outlook would be beneficial
for the relatively few producers, but would have adverse consequences for most Sub-Saharan
African countries. Over the last decade the level of annual inst,ability in petroleum prices was about
double that for the all non-oil commodity index and constant dollar prices for oil were about 25
percent lower in 1999 than in 1990. World Bank forecasts call for a continued deterioration in real
petroleum prices through 2010.
For several reasons the main text focused on non-energy traditional products. Petroleum is
treated separately since oil exports are of major importance to a relatively few countries like Angola,
Republic of Congo, Gabon and Nigeria. Second, petroleum constituted about one-third of Sub-
Saharan Africa's exports in 1999 (as opposed to about 40 percent in 1990), so its inclusion with the
non-energy products would have made it difficult to properly assess prospects for the latter in
aggregate statistics. Third, petroleum also differs from the traditional products in that exports are
subject to some degree of control by a commodity cartel (OPEC) and its prospects depend on how
effectively the cartel functions. Perhaps the most important point, however, is that petroleum differs
significantly from most traditional products in that the majority of African countries are net oil
importers. As such, depressed global demand and prices for oil may have adverse implications for the
relatively few producer countries, but have favorable implications for the majority of energy importing
African countries.
Annex Table 4 provides empirical evidence relating to thie first of these four points, that is, the
very high concentration of regional oil exports from a relatively few SSA countries. Shown here are
both the 1995 and 1999 value and regional share of all petroleum exports by the major producer
countries. As indicated, Nigeria and Angola originated over 70 percent of all Sub-Saharan Africa's oil
exports in 1999, while four other countries (Gabon, Democratic Republic of the Congo, Cameroon,
and Equatorial Guinea) increase the regional export share to almost 95 percent.
65
Annex Table 4. Major African Exporters of Petroleum in 1995 and 1999
Value of Petroleum Exports ($million) Share of African Petroleum Exports (%)
Exporting Country 1995 1999 1995 1999
Nigeria 11,549 10,791 60.7 52.2
Angola 3,460 4,156 18.2 20.1
Gabon 1,920 1,859 10.4 9.0
Congo, Dem. Republic 905 1,504 4.8 7.2
Cameroon 586 711 0.1 3.4
Equatorial Guinea 31 516 0.1 2.5
All Above Countries 18,451 19,537 97.3 94.4
Source: UN COMTRADE import statistics as reported by the countries listed in the notes to Table 1.
In contrast, Annex Table 5 shows how important petroleum is in the import profiles of other
African countries. Shown here are the 1995 and 1999 values of oil imports for all countries that have
reported their recent trade statistics to UN COMTRADE, and the share of petroleum in total imports.35
While there is considerable variation in the data, in 1999 the share of petroleum in the total imports of
two-thirds of these countries exceeded 10 percent, and for over one-fifth of the countries it exceeded
20 percent. Given the nature of their foreign exchange constraints, higher petroleum prices would
have a negative impact on the capacity of these Sub-Saharan countries to import capital equipment
required for industrialization and growth.
35 While the trade statistics in this study are generally based on data reported to UN COMTRADE by the 72 countries listed in the notes
to Table 1, Annex Table 6 draw on statistics for all African countries that reported recent trade data to the United Nations. This
alternative data source was employed since, unlike most traditional products, there appears to be significant African intra-trade in oil and
this exchange would not be accurately reflected in the 72 partner countries' data.
66
Annex Table 5. Selected African Importers of Petroleum Products in 1995 and 1999
Petroleum Imports ($000) Oil Imports as a Percent of All Imports (%)
lmportinz Countrv 1995 1999 1995 1999
Benin 67,145 128.919 9.3 19.3
Central African Republic 22,755 15,297 8.5 8. 1
Cote d'lvoire 466.586 820,380 18.9 25.2
Cameroon 27.260 212,010 2.5 15.6
Cape Verde 39,890 10,921 12.2 5.0
Ethiopia 126,363 123,057 11.1 11.1
Ghana 353,639 466.070 6.0 15.5
Guinea 155,817 76,179 19.0 10.2
Kenya 408,150 432,393 14.5 15.5
Madagascar 76,495 121,986 13.9 24.1
Mali 119,471 162.197 15.4 20.7
Mozambique 58,741 82,256 8.0 7.1
Mauritania 96.948 138,953 21.3 28.2
Mauritius 121,909 141,455 6.0 6.2
Malawi 53.336 66.312 10.7 9.5
Niger 44,005 53,021 12.8 13.6
Sudan 162,244 127,180 13.7 10.1
Senegal 122,051 153,417 10.0 9.6
Togo 166,257 265.410 29.9 39.7
Tanzania 8.619 126,436 0.5 8.0
Uganda 17.917 124,480 1.7 12.3
South Africa 2,194,163 2.349,673 8.2 9.7
Zambia 88,664 102,475 12.5 12.5
Zimbabwe 234.012 241,733 8.8 11.4
Source: African countries import statistics as reported to UN COMTRADE. Data are for 1995 and 1999 or the closest years available.
The African countries listed above are those that reported recent trade statistics to UN COMTRADE.
Over the last decade, petroleum prices were characterized by a relatively high level of
instability. As reflected in import unit value statistics crude petroleum prices experienced average
annual price changes of about 17 percent during the 1990s which was more than twice the average (8.1
percent) for all non-oil commodities. During the decade quantity imports of crude petroleum by the
major OECD countries grew by about 18] percent less than real GDP due in part to conservation
efforts. The effects of these efforts, plus the introduction of new sources of supply, were factors in
World Bank forecasts for relatively flat current dollar, and declining 1990 constant dollar prices for
petroleum through 2010. (Annex Table 6).
67
Annex Table 6. Actual, Constant 1990 Dollar, and Projected Prices for Crude Petroleum
Actual or Constant Price Values Proiected Values or Prices
Price orPrice Measure* 1980 1990 1998 1999 2001 2005 2010
Current dollar spot crude price 36.87 22.88 13.07 18.07 21.00 18.00 19.00
Constant dollar spot crude price 51.22 22.88 12.54 17.45 19.30 15.06 14.06
Manufactures unit value index** 71.98 100.0 104.19 103.56 108.80 119.51 135.09
*Petroleum prices are in US$ per barrel. Constant prices are on a 1990 base of 100.
**The manufactures unit value (MUV) index measures the US dollar value of manufactured goods exported by France, Germany, Japan,
UK and US weighted proportionately by these countries' exports to developing countries.
Source: Authors' estimates.
68
Annex 3
Elements of Traditional Product Commodity Processing Chains
Annex Table 7 provides information on the 27 commodity processing chains utilized in
section IV of this study. In their construction, an attempt was made to identify a primary,
intermediate, and final stage for each chain. In addition, the table shows SITC Revision 2 number
to help identify the specific product in each stage. For example, the annex table shows the cocoa
chain has three stages with cocoa beans (SITC 0721) representing the primary stage product.
Cocoa powder (SITC 0722) and cocoa butter and paste (SITC 0723) experienced some processing
and are classified as intermediate stage products, while chocolate and other food preparations
containing cocoa (SITC 073) represent a higher level of processing activity.
Since the chains defined in the annex table are based on the established SITC system, they may
have certain associated limitations. Some of the stages may be at a relatively high level of aggregation
with the result that the underlying product composition in the group can vary. For example, the SITC
based primary and processed stages of the fruit and vegetable chains may contain different proportions
of (say) temperate and tropical products, so actual unit value data may not accurately price changes for
the same item at different levels of processing. A second potentlial problem concerns leakage from the
chains, in that a specific commodity can experience further fabrication, but this would not be recorded
if it were outside the main elements of the chain. For example, cotton fabric is classified as a higher
stage of processing than cotton yarn, but some yarn may be used as a direct input into other processed
products (like tires and other rubberized materials). This woulcd tend to understate the actual level of
further processing that was occurring. Similarly, some copper products may be lost from the analysis
if they are used in the manufacture of (say) electronic equipment. As a result, analysis of trade
changes in a SITC defined processing chain may understate the actual level and nature of processing
which is occurring. Finally, a given SITC group may contain products which are at different levels of
fabrication, but no distinction is made between them. As an example, most SITC vegetable oil groups
do not distinguish between crude and refined oil although different levels of processing are involved.
Several of the commodities listed in Annex Table 7 have end uses at the primary stage, and this
can cause complications. Vegetables, fruits, fish and shellfish are examples of commodities where the
primary stage item can be consumed directly. In fact, consumer preferences may favor the
unprocessed stage of this produce and be willing to pay a "premium" for these goods. For such
reasons relative price trends between primary and processed foodstuffs may differ from those observed
in other processing chains.
A final point is that the SITC did not always permit identification of a distinct primary,
intermediate, and final stage product so, in cases, no intermediate stage product is identified (see the
fruit and vegetable chains, for example). This contrasts with the a few other commodities (like
aluminum) where the level of detail in the SITC identifies a primary stage, two intermediate stages
(alumina and unwrought aluminum), and a final good. Similarly, in the lumber chain a distinction is
made between two intermediate stage goods, that is, sawn logs and plywood, which have clearly
experienced different levels of fabrication. As a result of these variations in detail, significant
differences may exist in the level of product processing and value added that occurs between primary
and final stage products in various processing chains.
69
Annex Table 7. Components of Specific Traditional Product Commodity Processing Chains and Their SITC Revision 2 Commodity Classifications
Processing Chairt Primary Stage Product Intermediate Stages Final Stage Goods
FOOI) & TOBACCO
Fruit 057 Fresh Fruit none identified 058 Preserved Fruit
Fish 0341 Fresh Fish none identified 0343 and 0344 Fish Fillets
Shellfish 036 Fresh Shellfish none identified 037 Prepared Shellfish
Sugar 0611 Raw Beet and Cane Sugar 0612 Refined Sugar 0620 Sugar Confection
Cocoa 0721 Cocoa Beans 0722 and 0723 Cocoa Powder and Butter 073 Chocolate and Food Preparations with Cocoa
Tobacco 1211 Tobacco Not Stripped 1212 Tobacco Stripped 122 Tobacco Manufactured
Cotton Seed 2223 Cotton Seeds none identified 4233 Cotton Seed Oil
Groundnuts 2221 Groundnuts none identified 4234 Groundnut Oil
PAPER, WOOD & RUBBER
Paper 251 Paper Pulp 641 Paper and Board (intermiediate stage 2) 642 Manufactures of Paper
Lumber 2472 Raw Nonconifer Logs 2483 Nonconifer Logs Sawn (intermnediate stage 1) 635 Manufactures of Wood
6341 Wood Sawn Lengthwise (intermediate stage 1) 82192 Furniture of Wood
6342 Plywood and Veneers (intermediate stage 2)
FIBERS AND LEATHER
Cotton 2631 Cotton Not Carded 6513 Cotton Yam (intermediate stage 1) 84232, 84242,84293 Men's Cotton Suits, Cotton
2634 Cotton Carded 652 Woven Cotton Fabrics (intermediate stage 2) Trousers and Jackets
84322, 84332, 84342,84351 Women's Cotton Outer
Garments, Cotton Suits, Dresses, Skirts and Blouses
Jute 2640 Jute Fibers none identified 6545 Fabrics of Jute
Sisal 2654 Sisal and Other Agave Fibers none identified 6542 Sisal and Agave Yams
Wool 2681 Wool Greasy 6512 Yam of Wool (intermediate stage 1) 84221,84231,84241.84292 Men's Wool Suits, Trousers.
2682 Wool Degreased 6542 Wool Fabrics (intermediate stage 2) Jackets and Outer Garments
2687 Wool Carded or Combed 84321. 84331, 84341 Women's Wool Suites, Dresses and
Skirts
l eather 211 Raw Hides and Skins (Except Furskins) 611 Leather 612 Manufactures of l_eather
MINERALS & METALS
Asbestos 2784 Asbestos none identified 6638 Manufactures of Asbestos
Iron 2815 Iron Ore 671 Pig Iron (intermediate stage 1) 673 Iron and Steel Bars and Shapes
672 Ingots and Primary Forms (intermediate stage 2) 674 Iron and Steel Plates
Copper 2871 Copper Ores 6821 Unwrought Copper 6822 Worked Copper and Copper Alloys
Annex Table 7. Continued
Processing Chain Primary Stage Product Intermediate Stages Final Stage Goods
Alumiiium 28731 Aluminum Ores 28732 Alumina (intermcdiate stage I) 6842 Worked Aluminum Alloys
6841 Unwrought Aluminum Alloys (intermediate stage 2)
Manganese 2877 Manganese Ores and Concentrates none identificd 6821 Manganese Unwrought
Platinum 28901 Precious Metal Ores (Excluding Gold) none identified 6812 Platinum Metals
ENERGY PRODUCTS
Petroleum 333 Crude Petroleum Oils none identified 334 Refined Petroleum Products
Source: Processing chain stages as identified in groups contained in Revision 2 of the Standard International Trade Classification System.
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~1~~~~~~~~~~~~~
Appendix Table 1. The Major Exports of Individual Sub-Saharan African Countries in 1999
Exports Export Cum. Exports Export Cum.
Country/SITC/Product ($000) Share (%) Share (%) Country/SITC Product ($000) Share (7o Share (%)
ANGOLA BENIN
3330 Petroleum Oils 4,069,077 85.2 85.2 2631 Raw Cotton 119,440 70.4 70.4
6672 Diamonds Unworked 551,130 11.5 96.7 2223 Cotton Seeds 19,019 11.2 81.7
3344 Fuel Oil, nes 70,009 1.5 98.2 0577 Edible Nuts 9,946 5.9 87.5
0360 Crustaceans 18,521 0.4 98.6 3330 Petroleum Oils 2,483 1.5 89.0
3413 Petroleum Gases 14,538 0.3 98.9 2483 Nonconifer Wood 1,669 1.0 90.0
3341 Motor Spirits 11.187 0.2 99.1 0813 Vegetable Oil Cake 1,453 0.9 90.8
9310 Unidentified Goods** 5,903 0.1 99.2 6521 Cotton Fabric 1,305 0.8 91.6
0711 Coffee Beans 5,511 0.1 99.3 0360 Crustaceans 1,303 0.8 92.4
0342 Fish Frozen 5,418 0.1 99.5 6522 Woven Cotton Fabric 1,045 0.6 93.0
7149 Engine Parts 2,931 0.1 99.5 2238 Oil Seeds, nes 984 0.6 93.6
BURKINA FASO BURUNDI
2631 Raw Cotton 91,474 61.1 61.1 0711 Coffee Beans 46.648 69.5 69.5
0611 Raw Sugar 13,811 9.2 70.4 9710 Nonmonetary Gold 9,632 14.3 838
2225 Sesame Seeds 8,887 5.9 76.3 0741 Tea 5,531 8.2 92.1
9710 Nonmonetary Gold 7,862 5.3 81.6 6673 Precious Stones 1,575 2.3 94.4
0545 Chilled Vegetables 5,171 3.5 85.0 2879 Other Nonferrous Ore 1,349 2.0 96.4
6116 Other Leather 4,518 3.0 88.0 7810 Passenger Cars* 411 0.6 97.0
6115 Sheep Leather 4,221 2.8 90.8 0341 Fresh Fish 233 0.3 97.4
2223 Cotton Seeds 2,394 1.6 92.4 0360 Crustaceans 151 0.2 97.6
8928 Printed Matter 1,084 0.7 93.2 8452 Knit Dresses 136 0.2 97.8
2924 Seeds For Perfume 637 0.4 93.6 2631 Raw Cotton 127 0.2 98.0
CAMEROON CAPE VERDE
3330 Petroleum Oils 669,519 34.0 34.0 6123 Parts of Footwear 5,121 23.2 23.2
2472 Saw Logs 300,942 15.3 49.3 7144 Reaction Engines* 4,384 19.8 43.0
2483 Nonconifer Wood 208,590 10.6 59.9 7148 Turbines* 3,787 17.1 60.2
0573 Bananas 172,058 8.7 68.7 8441 Men's Textile Shirts 2,084 9.4 69.6
0721 Cocoa Beans 122,445 6.2 74.9 8510 Footwear 1,387 6.2 75.8
6841 Unwrought Aluminum 99,468 5.1 80.0 0342 Fish Frozen 1.041 4.7 80.5
0711 Coffee Beans 96,936 4.9 84.9 7712 Electric Machine Parts 615 2.8 83.3
2631 Raw Cotton 79,725 4.1 89.0 0360 Crustaceans 489 2,2 85.5
0723 Cocoa Butter 38,758 2.0 90.9 0542 Beans and Lentils 365 1.7 87.2
2320 Natural Rubber 35,906 1.8 92.8 6793 Iron Forgings 362 1.6 88.8
CENT. AFRICAN REP. CHAD
6672 Diamonds Unworked 156,048 73.0 73.0 2631 Raw Cotton 80,440 82.2 82.2
2631 Raw Cotton 14,256 6.7 79.6 2922 Shellac and Resin 12,829 13.1 95.3
2472 Sawlogs 13,294 6.2 85.8 7924 Aircraft* 2,543 2.6 97.9
2483 Nonconifer Wood 10,598 5.0 90.8 7929 Parts of Aircraft* 765 0.8 98.7
0711 Coffee Beans 8,443 3.9 94.7 7169 Electric Plant Parts 212 0.2 98.9
1211 Tobacco Not Stripped 2,507 1.2 95.9 7923 Small Aircraft* 208 0.2 99.1
1222 Cigarettes 1,578 0.7 96.6 2923 Plaiting Material 88 0.1 99.2
9310 Unidentified Goods** 834 0.4 97.0 9310 Unidentified Goods" 87 0.1 99.3
7362 Metal Tuming Tools 689 0.3 97.4 5989 Chemicals, nes 68 0.1 99.4
2922 Shellac and Resins 601 0.3 97.6 7493 Transmission Shafts 56 0.1 99.4
COMOROS*** CONGO, DEM. REP.
0752 Spices 8,181 37.9 37.9 6672 Diamonds Unworked 833,373 69.8 69.8
5513 Essential Oils 4,539 21.0 59.0 3330 Petroleum Oils 110,368 9.2 79.1
7722 Printed Circuits 1,887 8.7 67.7 6899 Beryllium 81,585 6.8 85.9
7525 Peripheral Units 1,322 6.1 73.8 2879 Other Nonferrous Ore 53,995 4.5 90.4
7762 Electronic Valves 1,197 5.5 79.4 0711 Coffee Beans 41,234 3.5 93.9
7524 Digital Storage Units 580 2.7 82.1 6821 Unwrought Copper 19,307 1.6 95.5
7711 Transformers 504 2.3 84.4 2472 Sawlogs 13,881 1.2 96.6
7721 Fuses and Relays 309 1.4 85.8 2483 Nonconifer Wood 9,667 0.8 97.5
7763 Transistors 290 1.3 87.2 5169 Organic Chemicals, nes 2,607 0.2 97.7
7764 Microcircuits 276 1.3 88.5 2771 Industrial Diamonds 2,569 0.2 97.9
72
Appendix Table 1. Continued
Exports Export Cum. Exports Export Cu
Country/SITC/Product ($000) Share (%) Share h ) Country/SIT(' Product ($000) Share (%) Shar(
REPUBLIC OF CONGO COTE d'IVOIRE
3330 Petroleum Oils 1,420,935 77.9 77.9 0721 Cocoa 13eans 1,445,639 43.0 43
3344 Fuel Oil, nes 75.487 4.1 82.0 0723 Cocoa B3utter 309,902 9.2 52
2472 Sawlogs 74,477 4.1 86.1 2483 Nonconifer Wood 213.207 6.3 58
6672 Diamonds Unworked 62.168 3.4 89.5 0711 Coffee Beans 196,897 5.9 64
3413 Petroleum Gases 49,017 2.7 92.2 0579 Fresh Fruit 149,058 4.4 68
2483 Nonconiferous Wood 22.037 1.2 93.4 0573 Bananas 144,304 4.3 73
6899 Beryllium and Titanium 20,753 1.1 94.5 2631 Raw Cotton 142,444 4.2 77
6821 Unwrought Copper 13,942 0.8 95.3 0371 Prepared Fish 132,003 3.9 81
0611 Raw Sugar 13.932 08 96.0 2320 Natural Rubber 76,233 2.3 83
6341 Sawn Wood 10.410 0.6 96.6 6341 Sawn Wood 66,327 2.0 85
DJIBOUTI EQUATORIAL GUINEA
9710 Non-Monetary Gold 2.309 17.8 17.8 3330 Petroleum Oils 488,327 71.0 71
5530 Toilet Preparations 1.682 13.0 30.8 2472 Sawlogs 97,921 14.2 85
2117 Sheep Skins 1,086 8.4 39.2 0342 Fish Frozen 48,851 7.1 92
0571 Oranges 820 6.3 45.5 3345 Lubricating Oils 28,009 4.1 96
5156 Heterocyclic Items 581 4.5 50.0 6341 Sawn Wood 7,980 1.2 97
6841 Unwrought Aluminum 429 3.3 53.3 7239 Parts of Machinery 6,764 1.0 9E
0711 Coffee Beans 417 3.2 56.5 0721 Cocoa Beans 4.287 0.6 9S
6251 Tires 353 2.7 59.3 9310 Unidentified Goods*" 1,264 0.2 99
7436 Filtering Machines 349 2.7 62.0 3413 Petroleum Gases 1,123 0.2 9S
6115 Sheep Leather 331 2.6 64.5 0711 Coffee Beans 791 0.1 9S
ERITREA ETHIOPIA
9710 Non-Monetary Gold 5,066 46.0 46.0 0711 Coffee Beans 217.686 62.3 62
2933 Shellac 725 6.6 52.5 2225 Sesame Seeds 30,904 8.9 71
6il4OtherLeather 488 4.4 57.0 2117 SheepSkins 16.334 4.7 75
7234 Mining Machinery* 432 3.9 60.9 0542 Beans and Lentils 13.986 4.0 79
9310 Unidentified Goods** 416 3.8 64.7 7149 Engine Parts 9,189 2.6 82
2117 Sheep Skins 366 3.3 68.0 2238 Oil Seeds, nes 8,539 2.4 85
0343 Fish Fillets Fresh 348 3.2 71.1 0545 Other Vegetables 5,523 1.6 8t
0342 Fish Frozen 334 3.0 74.2 2631 Raw Cotton 4,990 1.4 88
0341 Fresh Fish 276 2.5 76.7 8741 Surve,ying Equip. 4,824 1.4 89
6130 Tanned Furskins 252 2.3 79.0 6116 Other Leathers 4,791 1.4 9C
GABON GAMBIA
3330 Petroleum Oils 1,846,709 69.9 69.9 6672 Diamonds Unworked 54.436 60.7 6C
2472 Sawlogs 450,180 17.0 87.0 0360 Crustaceans 22.054 24.6 85
2877 Manganese Ore 150,370 5.7 92.6 0545 Other Vegetables 3,075 3.4 88
7938 Floating Structures* 61,798 2.3 95.0 0342 Fish Frozen 1,799 2.0 9C
5241 Zinc Oxide 22.071 0.8 95.8 0344 Fish Fillets Frozen 1,282 1.4 92
6341 Sawn Wood 16,779 0.6 96.5 0577 Edible Nuts 827 0.9 9'
6342 Inlaid Wood 16,307 0.6 97.1 0579 Fresh Fruit 808 0.9 95
2483 Nonconifer Wood 13,370 0.5 97.6 8928 Printed Marter 568 0.6 94
0360Crustaceans 13,135 0.5 98.1 0350DriedFish 533 0.6 g9
3342 Kerosene 12.329 0.5 98.5 0372 Crustaceans 347 0.4 9'
GHANA GUINEA
0721 Cocoa Beans 473,633 31.3 31.3 2873 Aluminum Ore 365,172 56.1 5(
6672 Diamonds Unworked 208,173 13.7 45.0 6672 Diamonds Unworked 139,757 21.5 77
6841 Unwrought Aluminum 132,573 8.8 53.8 3330 Petroleum Oils 44,744 6.9 84
2483 Nonconifer Wood 119,786 7.9 61.7 0711 Coffee Beans 14,672 2.3 86
7924 Aircraft* 116,498 7.7 69.4 2472 Sawlogs 11,224 1.7 8E
0371 Prepared Fish 74,425 4.9 74.3 2631 Raw Cotton 9.557 1.5 8'
6341 Sawn Wood 57,878 3.8 78.1 0342 Fish Frozen 8.182 1.3 91
0723 Cocoa Butter 57,679 3.8 81.9 0360 Crustaceans 7,041 1.1 92
3344 Fuel Oil, nes 27,379 1.8 83.7 0341 Freshi Fish 6,882 1.1 93
0579 Fresh Fruit 24,286 1.6 85.3 5225 Inorganic Bases 5.703 0.9 94
73
Appendix Table 1. Continued
Exports Export Cum. Exports Export Cun
Countrv/SITC/Product ($O(Q) Share (%) Share (%) CountrvI/SITC Product ($000) Share (1 Share
GUINEA-BISSAU KENYA
0577 Edible Nuts 19,910 39.3 39.3 0741 Tea 392,740 28.8 28.:
3330 Petroleum Oils 18,449 36.5 75.8 071 1 Coffee Beans 187,568 13.8 42.1
0360 Crustaceans 4.520 8.9 84.7 2927 Cut Flowers 145,182 10.6 53.~
0342 Fish Frozen 2,483 4.9 89.6 0545 Other Vegetables 115,022 8.4 61i
2631 Raw Cotton 1,315 2.6 92.2 0589 Prepared Fruit, nes 52.030 3.8 65.:
6672 Diamonds Unworked 1,289 2.5 94.8 0344 Fish Fillets Frozen 42,096 3.1 68.:'
0721 Cocoa Beans 871 1.7 96.5 0565 Prepared Vegetables. nes 24,809 1.8 70..
2472 Sawlogs 436 0.9 97.4 5232 Metallic Salts 21,414 1.6 71.1
07 11 Coffee Beans 199 0.4 97.8 0579 Fresh Fruiit, net 19.169 1.4 73.:
7764 Microcircuits 153 0.3 98.1 8439 Other Outer Garments 18.954 1.4 74.'
LIBERIA MADAGASCAR
6672 Diamonds Unworked 309,372 48.0 48.0 0360 Crustaceans 102,604 13.6 13.t
7932 Ships and Boats 193,412 30.0 78.0 8451 Pullovers 102,591 13.6 27.:
2320 Natural Rubber 46,525 7.2 85.2 0752 Spices 60,021 8.0 35.:'
2472 Sawlogs 35.480 5.5 90.7 0711 Coffee Beans 55,743 7.4 42.(
3330 Petroleum Oils 13.473 2.1 92.8 8423 Trousers 47,282 6.3 48.:
5982 Antiknock Preps. 10.437 1.6 94.4 0579 Fresh Fruit 42,333 5.6 54..
3343 Gas Oils 6,704 1.0 95.5 8439 Other Outer Garments 35,632 4.7 59.:
3341 Motor Spirits 5,418 0.8 96.3 8462 Knitted Under Garments 31,219 4.1 63.1
3343 Kerosene 4,649 0.7 97.0 0371 Prepared Fish 30,494 4.0 67.;
8960 Works of Art 2,690 0.4 97.5 8441 Men's Textile Shirts 16,554 2.2 69..
MALAWI MALI
1212 Tobacco Stripped 273,870 58.6 58.6 2631 Raw Cotton 200,643 83.0 83.(
121 1 Tobacco Not Stripped 37,729 8.1 66.6 7764 Microcircuits 6,184 2.6 85.i
0741 Tea 37,437 8.0 74.6 6672 Diamonds Unworked 4,734 2.0 87..
0611 Raw Sugar 18,696 4.0 78.6 8960 Works of Art 4,291 1.8 89.:
6584 Bed Linens 13.148 2.8 81.4 2634 Combed Cotton 2,107 0.9 90.:
8462 Knit Undergarments 11,633 2.5 83.9 6116 Other Leather 1,870 0.8 91.1
8441 Men's Textile Shirts 10,773 2.3 86.2 61 15 Sheep Leather 1,601 0.7 91.1
071 1 Coffee Beans 9,753 2.1 88.3 8462 Knit Undergarmnents 1,590 0.7 92..
8423 TrouseTs 9.484 2.0 90.3 9310 Unidentified Goods** 1,539 0.6 92.1
1213 Parts of Tobacco 5,056 1.1 91.4 0548 Roots and Tubers 1,249 0.5 93.,
MAURITANIA MAURITIUS
2815 Iron Ore 250,679 50.2 50.2 0611 Raw Sugar 301,916 19.0 19.1
0360 Crustaceans 166,593 33.3 83.5 8462 Knit Undergarnents 283.868 17.9 36.1
0342 Fish Frozen 25.581 5.1 88.6 8451 Pullovers 197,975 12.5 49..
0341 Fresh Fish 20,988 4.2 92.8 8423 Trousers 150,509 9.5 58.1
7955 Office Machine Parts 9.250 1.9 94.7 8441 Men's Textile Shirts 120.5 10 7.6 66..
2816 Concenitrated Iron Ore 8.67 1 1.7 96.4 8439 Other Outer Garmnents 88,829 5.6 72.
0344 Fish Fillets Frozen 2,844 0.6 97.0 8459 Knit Outergarrnents 49,656 3.1 74.!
0814 Fitsh Meal 2,012 0.4 97.4 8973 Jewelry 43,622 2.7 78.'
0350 Dried Fish 1,677 0.3 97.7 0371 Prepared Fish 42,956 2.7 80;'
0343 Fish Fillets Fresh 1,381 0.3 98.0 0342 Fish Frozen 39,479 2.5 83.
MOZAMBIQUE NIGER
0360 Crustaceans 83,718 31.7 31.7 3330 Petroleum Oils 151,880 51.2 51.:
0577 Edible Nuts 38,033 14.4 46.1 5241 Radio-Isotopes 117,168 39.5 90:1
2631 Raw Cotton 30,121 11.4 57.5 3344 Fuel Oil, nes 7,794 2.6 93.
2472 Sawlogs 10,277 3.9 61.4 7929 Aircraft* 3,819 1.3 94.1
7234 Mining Machines, nes 9.378 3.5 64.9 2631 Raw Cotton 3,329 1.1 95.
2231 Copra 8,419 3.2 68.1 0224 Preserved Mfilk 1,222 0.4 96:
2731 Building Stone 6,918 2.6 70.7 9310 Unidentified Goods"* 844 0.3 96..
2483 Nonconifer Wood 3,363 1.3 72.0 0548 Roots and Tubers 633 0.2 96:'
0422 Rice 3,309 1.3 73.2 7764 Microcircuits 551 0.2 96.:
6716 Ferro-Alloys 3,275 1.2 74.5 7649 Telecom Parts 462 0.2 97.'
74
Appendix Table I. Continued
Exports Expoyt Cum. Exports Export CuD
Country/SITC/Product ($000) Share (%) Share (%) Countrv/SITC /Product ($000) Share 1%) Share
NIGERIA RWANDA
3330 Petroleum Oils 10,221,208 86.9 86.9 0711 Coffee Beans 28.933 58.7 58.
3345 Lubricating Oils 249,478 2.1 89.0 0741 Tea 8,573 17.4 76.
3344 Fuel Oil, nes 216,103 1.8 90.8 2879 Other Nonferrous Ore 4,046 8.2 84.
3413 Petroleum Gasses 211.147 1.8 92.6 9710 Nonmonetary Gold 2,586 5.2 89.
0721 Cocoa Beans 209.895 1.8 94.4 2876 Tin Ore 1.223 2.5 92.
3341 Motor Spirits 72,395 0.6 95.0 2929 Vegetable Material 541 1.1 93.
2472 Sawlogs 58,890 0.5 95.5 5629 Fertilizers, nes 462 0.9 94.
2483 Nonconifer Wood 49.752 0.4 96.0 2927 Cut Flowers 404 0.8 94.
0360 Crustaceans 49,641 0.4 96.4 2111 Bovine Hides 369 0.7 95.
6115 Sheep Leather 43,014 0.4 96.7 2926 Bulbs and Tubers 304 0.6 96.
SAO TOME & PRINCIPE SENEGAL
0721 Cocoa Beans 4,809 30.8 30.8 0360 Crustaceans 144,678 25.7 25.
0342 Fish Frozen 4,082 26.1 56.9 5222 Inorganic Bases 77,860 13.9 39.
3344 Fuel Oil, nes 1,766 11.3 68.2 4234 Groundnut Oil 62,651 11.1 50.
0360 Crustaceans 1.288 8.2 76.4 0341 Fresh Fish 52,284 9.3 60.
7244 Textile Machinery 611 3.9 80.3 2713 Natural Phosphate 33,577 6.0 66
8743 Hydraulic Equipment 305 1.9 82.3 0371 Prepared Fish 29.109 5.2 71.
7943 Transmission Shafts 160 1.0 83.3 0344 Fish F'illets Frozen 25,594 4.6 75.
8422 Men's Suits 154 1.0 84.3 0545 Other Vegetables 11,763 2.1 77.
0711 Coffee Beans 132 0.8 85.1 0343 Fish F'illets Fresh 11,363 2.0 79.
8424 Jackets 124 0.8 85.9 0813 Vegetable Oil Cake 10,469 1.9 81.
SEYCHELLES SIERRA LEONE
0371 Prepared Fish 103.078 68.0 68.0 6672 Diamonds Unworked 34,343 39.6 39.
0342 Fish Frozen 19,452 12.8 80.8 7810 Passenger Cars* 20,123 23.2 62.
0344 Fish Fillets Frozen 4.513 3.0 83.8 8510 Footwear 2.828 3.3 66.
8720 Medical Instruments 3,316 2.2 86.0 0721 Cocoa Beans 2,601 3.0 69.
0343 Fish Fillets Fresh 2,995 2.0 88.0 7431 Air Pumps 2,163 2.5 71.
0341 Fresh Fish 2,931 1.9 89.9 0711 Coffee Beans 1,796 2.1 73.
6353 Works of Carpentry 2.450 1.6 91.5 2879 Other Nonferrous Ore 1,721 2.0 75.
0360 Crustaceans 1,943 1.3 92.8 6652 Glassware 1.274 1.5 77.
0814 Fish Meal 1,112 0.7 93.5 8211 Chairs and Parts 901 1.0 78.
8748 Measuring Equipment 815 0.5 94.1 2784 Asbestos 744 0.9 79.
SOMALIA SOUTH AFRICA
2922 Shellac and Resins 1.571 21.4 21.4 9710 Nonmonetary Gold 3,207,359 12.2 12.
2225 Sesame Seeds 888 12.1 33.5 6812 Platirium 2,664,459 10.1 22.
2114 Goat Skins 589 8.0 41.5 3222 Other Coal 1,839,625 7.0 29.
2472 Sawlogs 516 7.0 48.6 6672 Diamronds Unworked 1,267,026 4.8 34.
8748 Measuring Equipment 472 6.4 55.0 6716 Ferro-Alloys 1.132,155 4.3 38
5112 Cyclic Hydrocarbons 416 5.7 60.7 7810 Passenger Cars 745.834 2.8 41.
2117 Sheep Skins 391 5.3 66.0 6841 Unwirought Aluminum 732,552 2.8 44.
7525 Peripheral Units 390 5.3 71.3 9310 Unidentified Goods** 547,779 2.1 46.
0342 Fish Frozen 287 3.9 75.2 2815 Iron Ore 432,948 1.6 47.
2119 Hides, nes 145 2.0 77.2 7436 Centrifuges 400,347 1.5 49.
SUDAN TANZANIA
3330 Petroleum Oils 210,652 41.4 41.4 0577 Edible Nuts 118,136 21.6 21.
2225 Sesame Seeds 68.471 13.7 55.1 0711 Coffee Beans 93,334 17.1 38.
2631 Raw Cotton 58,477 11.5 66.6 1212 Tobacco Striped 51.628 9.4 48
0548 Roots and Tubers 24,343 4.8 71.4 0344 Fish Fillets Frozen 36,147 6.6 54
2922 Shellac and Resins 22,958 4.5 75.9 2631 Raw Cotton 24,116 4.4 59.
0459 Millet or Sorghum 22,815 4.5 80.4 6673 Precious Stones 24,030 4.4 63.
9410 Zoo Animals 13,579 2.7 83.0 0741 Tea 13,937 2.6 66.
2924 Plant Seeds for Perfume 10,814 2.1 85.2 2927 Cut Flowers 12,700 2.3 68
0611 Raw Sugar 10,552 2.1 87.3 2225 Sesame Seeds 12,524 2.3 70
0615 Molasses 10.460 2.1 89.3 0360 Crustaceans 12,415 2.3 73.
75
Appendix Table 1. Continued
Exports Export Cum. Exports Export Cut
Countrv/SITC/Product ($000) Share (%) Share (%) Country/SITC Product ($000) Share (%) Share
TOGO UGANDA
2631 Raw Cotton 68,403 31.2 31.2 0711 Coffee Beans 290,280 71.1 71.
2713 Natural Phosphates 63,300 28.9 60.0 0344 Fish Fillets Frozen 19,285 4.7 75.
0711 Coffee Beans 22,109 10.1 70.1 2631 Raw Cotton 15,997 3.9 79.
6672 Diamonds Unworked 15,646 7.1 77.2 1212 Tobacco Stripped 14,258 3.5 83.
0721 Cocoa Beans 12,456 5.7 82.9 0343 Fish Fillets Fresh 13,256 3.2 86
5622 Phosphatic Fertilizer 6,670 3.0 86.0 2927 Cut Flowers 9,511 2.3 88.
2223 Cotton Seeds 4.887 2.2 88.2 t211 Tobacco Not Stripped 5,781 1.4 90.
0360 Crustaceans 3,477 1.6 89.8 9710 Nonmonetary Gold 4,227 1.0 91.
8999 Misc. Manufactures, nes 2,587 1.2 90 9 2111 Bovine Hides 3,054 0.7 92.
0813 Vegetable Oil Cake 1,874 0.9 91.8 0545 Other Vegetables 3,008 0.7 92.
ZAMBIA ZIMBABWE
6821 Refined Copper 241,620 40.5 40.5 1212 Tobacco Stripped 451,211 27.7 27
6899 Beryllium 129,609 21 7 62.2 6716 Ferro-Alloys 156,849 9.6 37
2879 OtherNon-Ferrous Ore 41,685 7.0 69.2 2631 Raw Cotton 110,112 6.8 44
6513 Cotton Yam 29,631 5.0 74.2 6831 Nickel Alloys 89,947 5.5 49
2631 Raw Cotton 19,178 3.2 77.4 1211 Tobacco Not Stripped 86,576 5.3 54
2927 Cut Flowers 18,348 3.1 80.5 2927 Cut Flowers 62.280 3.8 58
6822 Worked Copper 18,328 3.1 83.5 9710 Nonmonetary Gold 50,571 3.1 61
2871 Copper Ore 14,211 2.4 85.9 0611 Raw Sugar 43,109 2.6 64
1212 Tobacco Stripped 10.659 1.8 87.7 2784 Asbestos 33.180 2.0 66
6673 Precious Stones 10,447 1.8 89.4 0111 Bovine Meat 29,395 1.8 68
* The African country seemingly has no, or limited, domestic production capacity for this item. Trade values shown may reflect sales of used equipment or. in
the case of aircraft, leasing of goods that were produced elsewhere.
** In cases where reporting trade values for a specific good would identify the specific exporter or importer UN regulations conceming confidentially allow
these transactions to be classified as "unidentified goods." Some countries appear to have also used this category to conceal arms trade.
*** We excluded the Comoros from Annex I since this country's trade statistics appear to be significantly biased by shipments into, and out of, French
military bases.
Source: UN COMTRADE statistics as reported by the countries listed in the notes to Table 1.
76
Appendix Table 2. Major African Suppliers of Individual Traditional Export Products in 1999
Product /(No. of Exoorters)/Exp9rter* Exports ($000) Share To Pouct /(lNo. of Exporters)Exporter'* Exponrs($000t Share(9
0360 Crustasceans & Shellfish (39) 0371 Prepared & Preserved Fish (18)
All Sub-Saharan Africa 792.706 100.0 All Sub-Saharan Africa 436,962 100.0
Angola 18,521 2.3 Cote d'Lvoire 132,003 30.2
Benin 1,303 0.2 Ghana 74,425 17.0
Cote dIlvoire 8,563 1.1 Kenya 11.874 2.7
Cameroon 6,780 0.9 Madagascar 30.494 7.0
Gabon 13.135 1.7 Mauritius 42.956 9.8
Ghana 18,152 2.3 Senegal 29,109 6.7
Guinea 7,041 0.9 Seychelles 103.078 23.6
Gambia 22,054 2.8 South Africa 12.608 2.9
Guirnea-Bissau 4.520 0.6 Others 415 0.1
Kenya 7.709 1 .0
Madagascar 102,604 12.9 0579 Fresh or Dried Fruit (39)
Mozambique 83,718 10.6 All Sub-Saharan Africa 541,034 100.0
Mauritania 166,593 20.9 Benin 465 0.1
Mauritius 453 0.1 Burkina Faso 502 0.1
Nigeria 49.641 6.3 Cote d'lvoire 149.058 27.6
Senegal 144.678 18.2 Cameroon 4.330 0.9
Sao Tome & Principe 1.288 0.2 Ghana 24.286 4.5
Seychelles 1,943 0.2 Guinea 2,270 0.4
Togo 3.477 0.4 Gambia 808 0.1
Tanlzania 12,415 1.6 Kna1,6 .
South Africa 116.782 14.7 Madagascar 42,333 7.8
Others 1,336 0.1 Mali 1,140 0.2
Mauritius 1.740 0.3
0611 Raw Beet & Cane Sugar (13) Sudan 1.263 0.2
All Sub-Saharan Africa 630,872 100.0 Senegal 1.677 0.3
Burkina Faso 13.811 2.2 Togo 684 0.1
Cote dIlvoire 5,399 0.9 South Africa 284.375 52.6
Madagascar 6,446 1.0 Zimbabwe 5,965 1.1
Mauritius 301.916 47.9 Others 969 0.2
Malawi 18,696 3.0 0711 Green or Roasted Coffee (35)
Sudan 10,552 1.7 All Sub-Saharani Africa 1.373,624 100.0
Tanzania 7,136 1.1 Angola 5.511 0.4
South Africa 208.379 33.0 Burundi 46.648 3.4
Zambia 1.469 0.2 Central African Republic 8,443 0.6
Zimbabwe 43,109 6.8 Cote dIlvoire 196.897 14.3
Others 13,959 2.2 Cameroon 96,936 7.1
Congo, Republ ic 10,292 0.7
0721 Cocoa Beans (21) Ethiopia 217,686 15.8
All Sub-Saharan Africa 2,300.667 100.0 Ghana 6,034 0.4
Cote d'lvoire 1,445.639 62.8 Guinea 14.672 1.1
Cameroon 122,445 5.3 Equatorial Guiniea 791 0 1
Ghana 473,633 20.7 Kenya 187,568 13.7
Guinea 5,009 0.2 Liberia 1,018 0.1
Equatorial Guinea 4,287 0.2 Madagascar 55,743 4.1
Liberia 2.203 0.1 Malawi 9.753 0.7
Madagascar 6,360 0.3 Nigeria 751 0.1
Nigeria 209.895 9.1 Rwanda 28.933 2.1
Sierra Leone 2.601 0.1 Sierra Leone 1,796 0.1
Sao Tome & Principe 4.809 0.2 Togo 22,109 1.6
Togo 12.456 0.5 Tanzania 93.334 6.8
Tanzania 2.887 0.1 Uganda 290,820 21.2
Uganda 2.368 0.1 South Africa 4.794 0.3
South Africa 2.5 13 0.1 Congo. Democratic Republic 41,234 3.0
Others 3,562 0.2 Zambia 8,429 0.6
0723 Cocoa Butter and Paste (7) Zimbabwe 22.358 1 6
All Sub-Saharan Africa 436.411 100.0 Others 1.074 0.1
Cote dIlvoire 309.902 71.0 0741 Tea
Cameroon 38.75 8 8.9 All Sub-Saharan Africa 5 52.752 100.0
Ghana 57,679 13.2 Burundi 5,531 1.0
Nigeria 29,695 6.8 Ghana 369 0.1
South Africa 345 0.1 Kenya 392.740 71.0
Others 32 -- Mauritius 351 0.1
1212 Tobacco Stripped (18) Malawi 37.437 6.7
All Sub-Saharan Africa 837.173 100.0 Rwanda 8.573 1.6
Kenya 9,578 1.1 Sierra Leone 236 0.1
Mozambique 2,728 0.3 Tanzania 13.937 2.5
Malawi 273.870 32.7 Uganda 1,738 0.3
Tanzania 51.628 6.2 South Africa 79.987 14.4
77
Appendix Table 2. Continued
Product /(No. of Exporters)IExnorter Exports ($000) Share (% Product /(o. of Exporters)ExoLorter Exports ($000) Share(9
Tobacco Stripped (Continued) Tea (Continued)
Uganda 14,258 1.7 Zimbabwe 10.939 2.0
South Africa 21,502 2.6 Others 914 0.2
Zambia 10,659 1.3
Zimbabwe 451,211 53.9 2117 Sheep Skins (15)
Others 1,739 0.2 All Sub-Saharan Africa 56,565 100.0
Burundi 52 0.1
1213 Parts of Tobacco Leaf (9) Burkina Faso 156 0.3
All Sub-Saharan Africa 33.595 100.0 Djibouti 1,086 1.9
Kenya 837 2.5 Eritrea 366 0.6
Malawi 5,056 15.1 Ethiopia 16,334 28.9
Tanzania 3,010 9.0 Kenya 301 0.5
Uganda 453 1.3 Mali 177 0.3
South Africa 2,267 6.7 Nigeria 1,919 3.5
Zambia 187 0.6 Sudan 1.409 2.5
Zimbabwe 21,770 64.8 Senegal 7 1 0.1
Others 1 5 -- Somalia 391 0.7
Uganda 77 0.1
2114 Goat and Kid Skins South Africa 34,203 60.5
All Sub-Saharan Africa 3.929 100.0 Others 23 -
Burundi 19 0.5
Cote d'Ivoire 2 1 0.5 2223 Cotton Seed (13)
Djibouti 237 6.0 All Sub-Saharan Africa 33,086 100.0
Eritrea 32 0.8 Benin 19,019 57.5
CGuinea 15 0.4 Burkina Faso 2,394 7.2
Kenya 124 3.2 Cote dIroire 344 1.0
Mali 311 7.9 Ghana 2,018 6.1
Mauritania 35 0.9 Guinea 2,130 6.4
Malawi 288 7.3 Mozambique 349 1.1
Nigeria 269 6.8 Malawi 56 0.2
Rwanda 37 0.9 Senegal 56 0.2
Sudan 863 22.0 Togo 4,887 14.8
Senegal 140 3.7 South Africa 120 0.4
Somalia 589 15.0 Zambia 1,069 3.2
Tanzania 9624 Zimnbabwe 638 1.9
Uganda 273 6.9 Others 6 -
South Africa 485 12.3 2225 Sesame Seeds (20)
Zimbabwe 93 2.4 All Sub-Saharan Africa 151,770 100.0
Others 2 0.1 Burkina Faso 8,887 5.9
2472 Saw Logs (29) Cote d'lvoire 271 0.2
All Sub-Saharan Africa 1,120,560 100.0 Djibouti 29t 0.2
Angola 1.335 0.1 Ethiopia 30,904 20.3
Central African Republic 13,294 1.2 Ghana 1,268 0.8
Cote d'Ivoire 23,969 211 Gambia 241 0.2
Cameroon 300,942 26.9 Mali 328 0.2
Congo, Republic of 74,477 6.6 Mozambique 254 0.2
Gabon 450,180 40.2 Nigeria 22,847 15.1
Ghana 3,168 0.3 Sudan 69,471 45.7
Guinea t11,224 1.0 Senegal 260 0.2
Equatorial Guinea 97,921 8.7 Somalia 888 0.6
Liberia 35,480 3.2 Tanzania 12,524 8.3
Madagascar 1,010 0.1 Uganda 1,992 1.3
Mozambique 10,277 0.9 South Africa 1,276 0.8
Mauritania 1,258 0.1 Others 68 -
Nigeria 58.890 5.3
Togo 888 0.1 2483 Lumber Shaped (34 670,440 100.
Tanzania 1,057 0.1 All Sub-Saharan Africa1690.
South Africa 19,940 1.8 Benin16902
Congo, Democratic Republic 13811.2 Central African Republic 10,598 1.6
Others 13,3690. Cote d lvoir-e 2 13,270 31.8
1,369 0.1 Cameroon 208,590 31.1
2631 Raw Cotton (31) Congo, Republic 22.037 3.3
All Sub-Saharan Africa 1,149,313 100.0 Gabon 13,370 2.0
Benin 119,440 10.4 Ghana 119,786 17.9
Burkina Faso 91,474 8.0 Guinea 1,473 0.2
Central African Republic 14,256 1.2 Equatorial Guinea 577 0.1
Cote d'lvoire 142,444 12.4 Liberia 439 0.1
Cameroon 79,725 6.9 Madagascar 3,363 0.5
Ethiopia 4,990 0.4 Mozambique 49,752 7.4
Ghana 3,276 0.3 Nigeria 4,5 .
Guinea 9,557 0.8 Tanzania 2,026 0.3
78
Appendix Table 2. Continued
Product /(No. of Exporters)/Exporter' Exports ($000) Share (%) Product /(No. of Exporters)Exo2orter Exports ($0001 Share
Raw Cotton (Continued) Lumber Shaped (Conitinued)
Guinea-Bissau 1,315 0.1 South Africa 8.015 1.2
Kenya 1,157 0.1 Congo. Democratic Republic 9,887 1.4
Madagascar 12.230 1.1 Zambia 416 0.1
Mali 200.643 17.5 Zimbabwe 1,048 0.2
Mozambique 30.121 2.6 Others 1,031 0.1
Nfauritius 587 0.1
Malawi 2,775 0.2 2516 Chemiical Woodpulp (1)
Niger 3.329 0.3 All Sub-Saharari Africa 143,526 100.0
Nigefia 9,268 0.8 South Africa 143,526 100.0
Sudan 58.477 5.1
Senegal 9,746 OX 2654 Sisal and Agave (5)
Chad 80,440 7.0 All Sub-Saharani Africa 22.596 100.0
Togo 68,40-3 6.0 Kenya 8.558 37.9
Tanzania 24,116 2.1 Madagascar 4.917 21.8
Uganda 15,997 1.4 Tanzania 8.763 38.8
South Affica 35.749 3.1 South Africa 358 1.5
Zambia 19,178 1.7 Others
Zimbabwe 110,112 9.6
Others 508 - 2713 Natural Plhosphates (6)
All Sub-Saharani Africa 162,867 100.0
2784 Asbestos (5) Senegal 33.577 20.6
All Sub-Saharan Africa 50,042 100.0 Togo 63,300 38.9
Sierra Leone 744 1.5 Tanzania 230 0.1
South Africa 16,049 32.1 South Africa 65,755 40.4
Zambia 59 0.1 Others 5 -
Zimbabwe 33,180 66.3
Others 10 -- 2771 Industriail Diamnonds (15)
All Sub-Saharan Africa 401.015 100.0
2786 Products of Melted Metal Ore (S) Congo, Republic Of 1,931 0.5
All Sub-Saharan Africa 100,098 100.0 Ghana 6.909 1.7
South Africa 100,085 100.0 Guinea 4,315 1.1
Others 13 -- Tanzania 3,881 1.0
South Africa 381,058 95.0
2815 Iron Ore (6) Congo, Democratic Republic 2,569 0.6
All Sub-Saharan Africa 683.904 100.0 Others 352 0.1
Mvauritania 250.679 36.7
South Africa 432,948 63.3 2879 Other Nonferrous Ores (25)
Others 277 -- All Sub-SaharaLn Africa 481,238 100.0
Burundi 1,349 0.3
2860 Uranium and Thorium (1) Congo. Republic of 6,126 1.3
All Sub-Saharan Africa 36,101 100.0 Ethiopia 3,330 0.7
South Africa 36,101 100.0 Madagascar 2,505 0.5
Nigeria 8,087 1.7
2877 Manganese Ore (3) Rwanda 4,046 0.8
All Sub-Saharan Africa 295.358 100.0 Sudan 2,464 0.5
Gabon 150,370 50.9 Sierra L-eone 1.721 0.4
Ghana 18,457 6.3 Uganda 898 0.2
South Africa 126,531 42.8 South Africa 354,493 73.6
Congo. Democratic Republic 53,995 11.2
2881 Nonferrous Metal Waste (13) Zambia 41,685 8.7
All Sub-Saharan Africa 231,984 100.0 Zimbabwe 276 0.1
Cote d'lvoire 170 0.1 Others 263 -
Congo, Republic of 218 0.1
Keny-a 158 0.1 2922 Natural Gum and Resins (20)
Mauritius 173 0.1 All Sub-Saharan Africa 52,821 100.0
Nigeria 697 0.3 Central African Republic 601 1.1
Togo 126 0.1 Cameroon 831 1.6
South Africa 223.888 96.4 Eritrea 725 1.4
Zambia 3,440 1.5 Ethiopia 1,973 3.7
Zimbabwe 2,939 1.3 Kenya 928 1.8
Others 175 -- Mali 212 0.4
Niger 93 0.2
3222 Other Coal (4) Nigeria 6,563 12.4
All Sub-Saharan Africa 1.842,310 100.0 Sudan 22.958 43.5
Mozambique 2.517 0.1 Senegal 2,341 4.4
South Africa 1,839,625 99.9 Somalia 1,571 3.0
Others 168 _ Chad 12,829 24.3
Tanzania 389 0.7
4234 Groundnut Oil (5) South Africa 119 0.2
All Sub-Saharan Africa 70,053 100.0 Zimbabwe 585 1.1
Sudan 1,991 2.8 Others 103 0.2
79
Appendix Table 2. Continued
Product /(No. of ExportersOExporter* Exports (5000) Share (%) Product /(No. of Exposters)Exporter Exports ($000) Share (%)
Groundnut Oil (Continued) 6716 Ferro-Alloys (12)
Senegal 62,651 89.5 All Sub-Saharan Africa 1,295,162 100.0
South Africa 5.388 7.7 Mozambique 3,275 0.3
Others 23 -- South Africa 1,132,155 87.4
Zambia 2,231 0.2
6116 Other Leathers (27) Zimbabwe 156,849 12.1
All Sub-Saharan Africa 170,116 100.0 Others 652 --
Benin 573 0.3
Burkina Faso 4,518 2.7 6812 Platinum (9)
Cote d'lvoire 187 0.1 All Sub-Saharan Africa 2.666,308 100.0
Comoros 396 0.2 South Africa 2,664,459 99.9
Djibouti 95 0.1 Others 1,849 0.1
Eritrea 171 0.1
Ethiopia 4.791 2.8 6821 Copper Alloys (12)
Kenya 3,056 1.8 All Sub-Saharan Africa 495,539 100.0
Mali 1,870 1.1 Congo, Republic of 13,942 2.8
Nigeria 40,761 23.9 Kenya 336 0.1
Sudan 1,320 0.8 Mozambique 2,199 0.4
Senegal 975 0.6 Tanzania 9,569 1.9
Somalia 118 0.1 South Africa 194,725 39.3
Uganda 126 0.1 Congo, Democratic Republic 19,307 3.9
South Africa 100.413 58.9 Zambia 241,620 48.8
Zambia 258 0.2 Zimbabwe 13,517 2.7
Zimbabwe 10,327 6.1 Othess 324 0.1
Others 161 0.1
6841 Unwrought Aluminum (9)
9710 Non-Monetary Gold (29) All Sub-Saharan Africa 990,300 100.0
All Sub-Saharan Africa 3,320,456 100.0 Cameroon 99,468 10.0
Burundi 9.632 0.3 Ghana 132,573 13.4
Burkina Faso 7,862 0.2 Nigeria 24,388 2.5
Cote d'lvoire 20,765 0.6 South Africa 732,553 74.0
Congo. Republicof 3,518 0.1 Others 1,318 0.1
Djibouti 2,309 0.1
Eritrea 5,066 0.2 6899 Beryllium and Titanium (10)
-Rwanda 2,586 0.1 All Sub-Saharan Africa 341,821 100.0
Uganda 4,227 0.1 Congo, Republic of 20,753 6.1
South Africa 3,207,359 96.6 Tanzania 1,569 0.5
Congo, Democratic Republic 1,992 0.1 Uganda 337 0.1
Zimbabwe 50,571 1.5 South Africa 107,498 31.4
Others 4,569 0.1 Congo, Democratic Republic 81,585 23.9
Zambia 129,609 37.9
Zimbabwe 374 0.1
Others 96 --
* Figures in parenthese show the total number of Sub-Saharan African countries who exported the traditional product in 1999. Individual country exports of
the product are not listed unless their exports acounted for at least one-tenth of one percent of the product total.
Source: UN COMTRADE statistics as reported by the countries listed in the notes to Table 1.
80
Appendix Table 3. The 1999 Value of Individual African Countries Traditional Exports and Their Share of All Goods Exporte
Exports Share of All Exports Share of A
Exporter (No. of Products)/Product* (S000) Exports (%) Exporter /(No. of Products)/Product' ($000) Expons(3
Angola (6) Congo Democratic Republic (14)
0360 Shellfish 18,521 0.4 0711 Coffee Beans 41,234 3.5
071] Coffee Beans 5.561 0.1 0721 Cocoa Beans 2,513 0.2
All Traditional Products 25,511 0.5 2472 Saw Logs 13,881 1.2
Benin (12) 2483 Shaped Lumber 9,667 0.8
0360 Shellfish 1.303 0.8 2771 Industrial Diamonds 2.569 0.2
0579 Fresh or Dried Fruit 465 0.3 2879 Other Nonferrous Ores 53,995 4.5
2223 Cotton Seeds 19,019 11.2 6821 Copper Alloys Unwrought 19,307 1.6
2472 Saw Logs 214 0.1 6899 Base Metals nes 81,585 6.8
2483 Shaped Lumber 1,669 1.0 9710 Non-Monetary Gold 1,992 0.2
2631 Raw Cotton 119.440 70.4 All Traditional Products 227,137 19.0
6116 Other Leathers 573 0-3 Congo Republic (14)
All Traditional Products 142,771 84.2 0611 Raw Sugar 13,932 0.8
Burkina Faso (14) 0711 Coffee Beans 10,292 0.6
0579 Fresh or Dried Fruit 502 0.3 0721 Cocoa Beans 1,069 0.1
0611 Raw Sugar 13,811 9.2 2472 Saw Logs 74.477 4.1
2117 Sheep Skins Without Wool 156 0.1 2483 Shaped Lumber 22.037 1.2
2223 Cotton Seeds 2,394 1.6 2771 Industria]l Diamonds 1,931 0.1
2225 Sesame Seeds 8,887 5.5 2879 Other Nonferrous Ores 6.126 0.3
2631 Raw Cotton 91.474 61.1 6821 Copper Alloys Unwrought 13,942 0.8
6116 Other Leathers 4.518 3.0 6899 Base Meltals nes 20,753 1.1
6812 Platinum 220 0.2 9710 Non-Monetary Gold 3,518 0.2
9710 Non-Monetary Gold 7,862 5.3 All Traditional Products 168,445 9 2
All Traditional Products 129,641 86.8 Cote d'lvoire (24)
Burundi (12) 0360 Shellfish 8,563 0.3
0360 Shellfish 151 0.2 0371 Preserved Fish 132,003 3.9
0711 Coffee Beans 46,648 69 5 0579 Fresh Fruit 149,058 4.4
0741 Tea 5,531 8.2 0611 Raw Sugar 5,399 0.2
2631 Raw Cotton 127 0.2 0711 Coffee B3eans 196,897 5.9
2879 Other Nonferrous Ores 1,349 2.0 0721 Cocoa Beans 1.445,639 43.0
9710 Non-Monetary Gold 9,632 14.4 0723 Cocoa Butter and Paste 309,902 9.2
Al] Traditional Products 63,558 94.7 2472 Saw Logs 23,969 0.7
2483 Lumber Shaped 213,207 6.3
Cameroon (14) 2631 Raw Cotton 142,444 4.2
0360 Shellfish 6.780 0.3 9710 Non-Monetary Gold 20,765 0.6
0579 Fresh or Dried Fruit 4,330 0.2 All Traditional Products 2,648,940 78 8
0711 Coffee Beans 96,936 4.9
0721 Cocoa Beans 122,445 6. 2 Djibouti (10)
0723 Cocoa Butter 38,758 2.0 0360 Shellfisht 30 0.2
2472 Saw Logs 300.942 15.3 0579 Fresh Fruit 84 0.7
2483 Lumber Shaped 208.590 10.6 0711 Coffee Beans 417 3.2
2631 Raw Cotton 79,725 4.1 2114 Goat and Kid Skins 237 1.8
All Traditional Products 860,533 43.8 2117 Sheep Skins 1,086 8.4
2225 Sesame Seeds 291 2.3
Cape Verde (4) 6116 Other Leathers 95 0.7
0360 Shellfish 489 2.2 6716 Ferro-Alloys 52 0.4
All Traditional Products 508 2.3 6841 Aluminum Alloys Unwrought 429 3.3
Central African Republic (14) 9710 Non-Monetary Gold 2,309 17.8
0711 Coffee Beans 8.443 4.0 All Traditonal Products 5,029 38.8
2472 Saw Logs 13.294 6.2
2483 Lumber Shaped 10,598 5.0 Equatorial Guinea (6)
2631 Raw Cotton 14,256 67 0711 Coffee Beans 791 0.1
2922 Natural Gums and Resins 601 0.3 0721 Cocoa Beans 4,287 0.6
6841 Aluminum Alloys Unwrought 378 0.2 2472 Saw Logs 97,291 14.2
All Traditional Products 48.023 22.5 All Traditional Products 103.814 15.1
Chad (5) Eritrea (8)
2631 Raw Cotton 80,550 82.2 0360 Shellfish 28 0.3
2922 Natural Gums and Resins 12,829 13.1 0579 Fresh Fruit 37 0.3
All Traditional Products 93,326 95.4 2114 Goat and Kid Skins 32 0.3
2117 Sheep Skins 366 3.3
Comoros (2) 81 0.4 2922 Natural Gums and Resins 725 6.6
0360 Shellfish 66 03 6116Otherleathers 171 1.6
071 1 Coffee Beans 147 0.7 9710 Non-Monetary Gold 5,066 46.0
All Traditional Products All Tradibonal Products 6,425 58.3
Ethiopia (12)
0711 Coffee Beans 217.686 62.4
81
Appendix Table 3. Continued
Exports Share of All Exports Share of A'
Exporter /(No. of Products)/Product* ($000) Exports (%) Exporter /(No. of Productsl/Product* ($000) Exports(
Gabon (12) Ethiopia (Continued)
0360 Shellfish 13,135 0.5 2117 Sheep Skins 16,334 4.7
2472 Saw Logs 450,180 17.0 2225 Sesame Seeds 30,904 8.9
2483 Shaped Lumber 12,370 0.5 2631 Raw Cotton 4,990 1.4
Manganese Ore 150,370 5.7 2879 Other Nonferrous Ores 3,330 1.0
All Traditional Products 627,875 23.8 2922 Natural Gums and Resins 1,973 0.6
Gambia (11) 6116 Other Leathers 4,791 1.4
Shellfish 22,054 24.6 All Traditional Products 280,252 80.3
0579 Fresh Fruit 808 0.9 Malawi (13)
2225 Sesame Seeds 241 0.3 0611 Raw Sugar 18,696 4.0
2483 Shaped Lumber 175 0.2 0711 Coffee Beans 9,753 2.1
2631 Raw Cotton 178 0.2 0741 Tea 37,437 8.0
All Traditional Products 23,553 26.3 1212 Tobacco Stripped 273,870 58.6
Ghana (24) 1213 Parts of Tobacco Leaf or Stem 5,056 1.1
0360 Shellfish 18,152 1.2 2631 Raw Cotton 2,775 0.6
0371 Prepared Fish 74.425 4.9 All Traditional Products 348,269 74.5
0579 Fresh Fruit 24,286 1.6 Mali (13)
0721 Cocoa Beans 473,633 31.3 0579 Fresh Fruit 1,140 0.4
0723 Cocoa Butter and Paste 57,679 3.8 2114 Goat and Kid Skins 311 0.1
2223 Cotton Seeds 2,018 0.1 2225 Sesame Seeds 328 0.1
2472 Saw Logs 3,168 0.2 2631 Raw Cotton 200,643 83.0
2483 Lumber Shaped 119,786 7.9 6116 Other Leathers 1,870 0.8
2631 Raw Cotton 3,276 0.2 9710 Non-Monetary Gold 600 0.3
2771 Industrial Diamonds 6,909 0.5 All Traditional Products 205,312 85.0
6841 Aluminum Alloys Unwrought 132,573 1.2 Mauritania (16)
All Traditional Products 943,559 8.8 0360 Shellfish 166,593 33.3
Guinea (16) 2472 Saw Logs 1,258 0.3
0360 Shellfish 7,041 1.1 2815 Iron Ore 250,679 50.2
0579 Fresh Fruit 2,270 0.4 All Traditional Products 418,687 83.8
0711 Coffee Beans 14,672 2.3 Mauritius (16)
0721 Cocoa Beans 5,009 0.8 0371 Prepared Fish 42,956 2.7
2223 Cotton Seeds 2,130 0.3 0611 Raw Sugar 301.916 19.0
2472 Saw Logs 11,224 1.7 All Traditional Products 350,613 22.1
2483 Lumber Shaped 1,473 0.2
2631 Raw Cotton 9,557 1.5 Mozambique (19)
2771 Industrial Diamonds 4,315 0.7 0360 Shellfish 83,718 31.7
All Traditional Products 57,948 8.9 1212 Tobacco Stripped 2,728 1.0
2223 Cotton Seeds 349 0.1
Guinea-Bissau (8) 4,520 8.9 2225 Sesame Seeds 254 0.1
0360 Shellfish 103 0.2 2472 Saw Logs 10,277 3.9
0371 Prepared Ftsh 199 0.4 2483 Shaped Lumber 3,363 1.3
o711 Coffee Beans 871 1.7 2631 Raw Cotton 30,121 11.4
0721 Cocoa Beans 436 0.9 3222 Other Coal 2,517 1.0
2472 Lumber Shaped 87 0.2 6716 Ferro-Alloys 3,275 1.2
2631 Raw Cotton 1,315 2.6 6821 Copper Alloys Unwrought 2,199 0 8
All Traditional Products 7,535 14.9 All Traditional Products 139,002 52.6
Kenya (2) Niger (10)
0360 Shellfish 7,709 0.6 0721 Cocoa Beans 408 0.1
0371 Prepared Fish 11,874 0.9 2631 Raw Cotton 3,329 1.1
0579 Fresh Fruit 19,169 1.4 6841 Aluminum Alloys Unwrought 320 0.1
0711 Coffee Beans 187,568 13.8 All Traditional Products 4,443 1.5
0741 Tea 392,740 28.8 Nigeria (22)
1212 Tobacco Stripped 9,578 0.7 0360 Shellfish 49,641 0.4
1213 Parts of Tobacco Leaf or Stem 837 0.1 0721 Cocoa Beans 209,895 1.8
2654 Sisal and Agave Fibers 8,558 0.6 0723 Cocoa Butter and Paste 29,695 0.3
6116 Other Leathers 3,056 0.22 2225 Sesame Seeds 22,847 0.2
All Traditional Products 644,224 47.2 2472 Saw Logs 58,890 0.5
Liberia (13) 2483 Shaped Lumber 49,752 0.4
0711 Coffee Beans 1,018 0.2 6116 OtherLeathers 40,761 0.4
0721 Cocoa Beans 2,203 0.3 6841 Aluminium Alloys Unwrought 24,388 0.2
2472 Saw Logs 35,480 5.5 All Traditional Products 51,647 4.4
All Traditional Products 39,470 6.1 Rwanda (10)
Madagascar (19) 0711 Coffee Beans 28,933 58.7
0360 Shellfish 102,604 13.6 0741 Tea 8,573 17.4
0371 Prepared Fish 30,494 4.0
82
Appendix Table 3. Continued
Exports Share of All Exports Share of All
Exporter-!(Ng. of ProductsV/Product'* ($000) Exports (% Exoorter /(No. of Products)/Product'*"U, Exports (%)
Madagascar (Continued) Rwanda (Continued)
0579 Fresh Fruit 42,333 5.6 2483 Shaped Lumber 90 0.2
061 1 Raw Sugar 6.446 0.9 2879 Other Nonferrous Ores 4,046 8.2
0711 Coffee Beans 55.743 7.4 9710 Non-Monetaryv Gold 2.586 5.3
0721 Cocoa Beans 6,350 0.8 All Traditional Products 44.324 89.9
2472 Saw Logs 1,010 0.1 South Africa (38)
2483 Shaped Lumber 3,093 0.4 0360 Shellfish 116,782 0.4
2631 Raw Cotton 12,230 1.6 0579 Fresh Fruit 284,375 1.1
2654 Sisal and Agave Fibers 4.9 17 0.7 0611 Raw Sugar 208,379 0.8
2879 Other Nonferrous Ores 2,505 0.3 0741 Tea 79.987 0.3
All Traditional Products 268.569 35.6 221 17 Sheep Skins 34,203 0.1
Sao Tome and Principe (3) 2472 Saw Logs 19,940 0.1
0360 Shellfish 1,288 8.2 2516 Wood Pulp 143,526 0.6
0711 Coffee Beans 132 0.8 2631 Raw Cotton 35.749 0.1
0721 Cocoa Beans 4,809 30.8 2713 Natural Phiosphates 65,755 0 3
All Traditional Products 6.229 39.9 2771 industrial Diamonds 381,058 1.5
Senegal (18) 2786 Products of Melted Metal Ores 100,085 0.4
0360 Shellfish 144.678 2p5. 7 2815 Iron Ore 432.948 1.7
0371 Prepared Fish 29,109 5.2 2860 Uranium and Thorium 36,101 0.1
0579 Fresh Fruit 1,677 0.3 2877 Manganese Ore 126,531 0.5
2631 Raw Cotton 9,746 1.7 2879 Other Noniferrous Ores 354,493 1.4
2713 Natural Phosphates 33.577 6.0 2881 Metalifenrous Nonferrous Waste 223,888 0.9
2922 Natural Gums and Resins 2.341 0.4 3222 Other Co;sl 1.839,625 7.0
4234 Groundnut Oil 62,651 11.1 6116 Other Leathers 100,413 0.4
6116 Other Leathers 975 0.2 6716 Ferro-Alloys 1,132,155 4.3
All Traditional Products 285,617 50.8 6812 Platinum 2.664,459 10 I
6821 Copper Alloys Unwroughr 194.725 0.7
Seychelles (7) 6841 Aluminium Alloys Unwrought 732.552 2.8
0360 Shellfish 1,943 1.3 6899 Base Metals net 107,498 0 4
0371 Prepared Fish 103,078 68.0 971 0 Non-Monetary Gold 3,207,359 12.2
All Traditional Products 105,082 69.3 All Traditional Products 12,696,537 48.3
Sierra Leone (15) Sudan (13)
0711 Coffee Beans 1.796 2.1 0579 Fresh Fniit 1.263 0.3
0721 Cocoa Beans 2,601 3.0 0611 Raw Sugar 10,552 2.1
0741 Tea 286 0.3 2 1 4 Goat Skins 863 0.2
1212 Parts of Tobacco Leaf or Stem 213 0.3 2117 Sheep Skins 1.409 0.3
2483 Shaped Lumber 88 0.1 2225 Sesame Seeds 69.471 12.7
2771 Industrial Diamonds 162 0.2 2631 Raw Cotton 58,477 11.5
2784 Asbestos 744 0.9 2879 Other Nonferrous Ores 2,464 0.5
2879 Other Nonferrous Ores 1,721 2.0 2922 Natural Gums and Resins 22.958 4.5
6716 Ferro-Alloys 366 0.4 4234 Groundnut Oil 1,991 0.4
All Traditional Products 8.045 9.3 6116 Other Leathers 1,320 0.3
Somalia (9) All Traditional Products 170,861 33.6
0360 Shellfish 17 0.2 Tanzania (26)
2114 Goat and Kid Skins 589 8.0 0360 Shellfish 12.415 2.3
2117 Sheep Skins 391 5.3 0611 Raw Sugar 7.136 1.3
2225 Sesame Seeds 888 12.1 0711 Coffee Beans 93,334 17.1
2472 Saw Logs 516 7.0 0721 Cocoa Beans 2,887 0.5
2922 Natural Gums and Resins 1,571 21.4 0741 Tea 13,937 2.6
6116 Other Leathers 118 1.6 1212 Tobacco Stripped 51,628 9.5
All Traditional Products 4.091 55.8 1213 Parts of Tobacco Leaf or Stem 3.010 0.6
Togo (12) 2225 Sesame Seeds 12.524 2.3
0360 Shellfish 3,477 1.6 2472 Saw Logs 1,057 0.2
0579 Fresh Fruit 684 0.3 2483 Shaped Lumber 2,026 0.4
0711 Coffee Beans 22,109 10.1 2631 Raw Cotton 24.116 4.4
0721 Cocoa Beans 12.456 5.7 2654 Sisal and Agave Fibers 8,763 1.6
2223 Cotton Seeds 4,887 2.2 2771 Industrial Diamonds 3,881 0.7
2472 Saw Logs 888 0.4 6821 Copper Alloys Unwrought 9,569 1.8
2483 Shaped Lumber 276 0.1 6899 Base Metals nes 1,569 0.3
2631 Raw Cotton 68,403 31.2 All Traditional Products 248,945 45.6
2713 Natural Phosphates 63,300 28.9 Uganda (20)
All Traditional Products 176.786 80.6 0711 Coffee Beans 290,820 71.1
Zambia (23) 0721 Cocoa Beans 2,368 0.6
0611 Raw Sugar 1,469 0.3 0741 Tea 1,738 0.4
0711 Coffee Beans 8,429 1.4 1212 Tobacco Stripped 14,258 3.5
1213 Parts of Tobacco Leaf or Stem 453 0.1
2225 Sessame Seeds 1922 0.5
83
Appendix Table 3. Continued
Exports Share of All Exports Share of A
Exporter /(No. of Products)/Product* ($000 Exports (%1 Exporter /(No, of Products)/Product* ($000) Exports (i
Zambia (Continued) Uganda (Continued)
1212 Tobacco Stripped 10,659 1.8 2631 Raw Cotton 15,997 3.9
2223 Cotton Seeds 1,069 0.2 2879 Other Nonferrous Ores 898 0.2
2631 Raw Cotton 19,178 3.2 9710 Nonmonetary Gold 4,227 1.0
2879 Other Nonferrous Ores 41,685 7.0 All Traditional Products 334,206 81.8
2881 Metalifferous Nonferrous Waste 3,440 0.6
6716 Ferro-Alloys 2,231 0.4
6821 Copper Alloys Unwrought 241,620 40.5
6899 Base Metals nes 129,609 21.7
Al] Traditional Products 460,874 77.2
Zimbabwe (26)
0579 Fresh Fruit 5,965 0.4
0611 Raw Sugar 43,109 2.7
0711 Coffee Beans 22,358 1.4
0741 Tea 10,939 0.7
1212 Tobacco Stripped 451,211 27.7
1213 Parts of Tobacco Leaf or Stem 21,770 1.3
2631 Raw Cotton 110,112 6.8
2784 Asbestos 33,180 2.0
2881 Metalifferous Nonferrous Waste 2,939 0.2
6116 Other Leathers 10,327 0.6
6716 Ferro-Alloys 156,849 9.6
6821 Copper Alloys Unwrought 13,517 0.8
9710 Non-Monetary Gold 50.571 3.1
All Traditional Products 936,028 57.5
* Traditional products are not listed below unless they account for at least one-tenth of one percent of total exports.
Source: UN COMTRADE statistics as reported by the countries listed in the notes to Table 1.
84
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