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Africa Region Working Paper Series No. 95
South Africa’s Export Performance:
Determinants of Export supply
by
Lawrence Edwards and Phil Alves
School of Economics
University of Cape Town
DECEMBER 2005
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Africa Region Working Paper Series No. 95
December 2005
Abstract
This paper is a result of a wider policy research and knowledge
work on growth and jobs issues in South Africa, which the Bank
promotes in collaboration with leading South African researchers.
The objective is to contribute to major economic and policy issues
facing South Africa as it embarks on the second decade of its
remarkable democratic transition. These issues include growth and
jobs, export competitiveness, service delivery, small and
medium-size enterprise development and investment climate,
industrial concentration, infrastructure and growth, municipal and
financial management, land reform, regional integration, trade and
poverty, HIV/AIDS, and––especially important––service delivery.
The paper provides three principal results. First, it evaluates
the extent to which the composition and level of manufacturing
exports have responded to reform initiatives in the 1990s and finds
that the successes of these policies in generating export growth
have been mixed; the inability to re-structure exports towards
dynamic, high-technology products is one explanation for the
relatively poor export performance of South African manufacturing
during the 1990s. Second, the paper investigates the determinants
of South African manufacturing export performance using estimated
export supply and demand functions; it shows that South African
manufacturers are on average price-takers in the international
market and that exports are predominantly supply driven. And third,
the paper finds that export growth is constrained by factors that
affect the profitability of exports; real effective exchange rate,
infrastructure costs, tariff rates and skilled labour are found to
be important determinants of export supply.
The Africa Region Working Paper Series expedites dissemination
of applied research and policy studies with potential for improving
economic performance and social conditions in Sub-Saharan Africa.
The series publishes papers at preliminary stages to stimulate
timely discussions within the Region and among client countries,
donors, and the policy research community. The editorial board for
the series consists of representatives from professional families
appointed by the Region’s Sector Directors. For additional
information, please contact Momar Gueye, (82220), Email:
[email protected] or visit the Web Site:
http://www.worldbank.org/afr/wps/index.htm.
The findings, interpretations, and conclusions in this paper are
those of the
authors. They do not necessarily represent the views of the
World Bank, its Executive Directors, or the countries that they
represent and should not be attributed to them.
mailto:[email protected]://www.worldbank.org/afr/wps/index.htm
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Authors’Affiliation and Sponsorship
Authors: (1) Lawrence Edwards, Professor of Economics, School of
Economics, Cape Town University, South Africa, Consultant, The
World Bank.
(2) Phil Alves, School of Economics, Cape Town University, South
Africa, Consultant, The World Bank.
Sponsor and Editor: Željko Bogetić, Lead Economist, AFTP1, The
World Bank. [email protected]
FOREWORD
This paper is a result of a wider policy research and knowledge
work on growth and jobs issues in South Africa, which the Bank
promotes in collaboration with leading South African researchers.
The objective is to contribute to major economic and policy issues
facing South Africa as it embarks on the second decade of its
remarkable democratic transition. These issues include growth and
jobs, export competitiveness, service delivery, small and
medium-size enterprise development and investment climate,
industrial concentration, infrastructure and growth, municipal and
financial management, land reform, regional integration, trade and
poverty, HIV/AIDS, and––especially important––service delivery. It
is hoped that dissemination of papers such as this will contribute
to a wider exchange of ideas on policy and development experiences
both within South Africa and across the African countries. Such
knowledge work is key to understanding complex development issues
and dilemmas confronting the policymakers. It is also a necessary
ingredient in promoting sound policies and economic growth in the
region.
Ritva Reinikka
Country Director
Botswana, Lesotho, Namibia, South Africa, Swaziland
The World Bank
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South Africa’s Export Performance:
Determinants of Export supply
By
Lawrence Edwards and Phil Alves*
1. Introduction
In 1994, the new democratically elected government inherited an
economic system characterised by declining economic and employment
growth. In response to these pressures, the government initiated a
number of policy reforms to stimulate growth, employment and
redistribution. The macroeconomic reforms were encapsulated in the
Growth, Employment and Redistribution macroeconomic policy (GEAR)
strategy. In addition to encouraging growth and employment, this
strategy aimed to transform South Africa into a “competitive,
outward orientated economy” (RSA, 1996). Measures to reduce unit
costs and an exchange rate policy to keep the real effective
exchange rate stable at a competitive level formed key components
of this strategy. To differentiate itself from the previous
protectionist government, the new government also embarked upon an
ambition trade liberalisation process that commenced with the
government’s formal Offer in the 1995 WTO (Bell, 1997). Numerous
other policy changes relating to labour markets and competition
have also been implemented.
This paper evaluates the extent to which the composition and
level of
manufacturing exports have responded to these initiatives in the
1990s. We find that the successes of these policies in generating
export growth have been mixed. Exports of manufactures have
increased but not by enough to generate an export-led growth boom
similar to those of East Asia and a few other resource-based export
economies. Moreover, South African manufactured exports remain
resource-based and the country has lagged others in diversifying
into new and fast growing export sectors. The inability to
re-structure exports towards these dynamic high technology products
is one explanation for the relatively poor export performance of
South African manufacturing during the 1990s.
* School of Economics, Cape Town University, South Africa. The
paper was edited by Željko Bogetić, Lead Economist, AFTP1, The
World Bank.
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The paper also investigates the determinants of South African
manufacturing export performance using estimated export supply and
demand functions. The analysis finds that South African
manufacturers are on average price-takers in the international
market and that exports are predominantly supply driven. Export
growth is therefore not predominantly dependent on the economic
prosperity of South Africa’s trading partners or on their ability
to compete in the export market on the basis of price.
Furthermore, the paper finds that many of the constraints to
export growth can be found in factors that negatively affect the
profitability of export supply. The real effective exchange rate,
infrastructure costs, tariff rates and skilled labour are found to
be important determinants of export supply.
Section 2 of the paper presents a very brief review of South
Africa’s trade regime, the increased openness in the 1990s, the
changing composition of South Africa’s exports, and its dynamic
export performance in comparative perspective. Section 3 develops
the export model used to identify the determinants of export
performance and then discusses the results. Section 4 contains
concluding remarks and some policy implications.
2. South African Trade regime and Trade Patterns During the
1990s
This section consists of three components. Progress made in
liberalising the
economy is first discussed. This is then followed by an analysis
of the changing patterns of South Africa’s exports from the 1970s.
Finally, South Africa’s dynamic export performance during the 1990s
is assessed relative to a range of developing and natural
resource-based economies.
Trade liberalisation in the 1990s The democratically elected
government in 1994 inherited a protectionist
trade regime characterised by high levels of protection, a wide
dispersion of tariffs, and a complicated array of tariff types
(Belli et al., 1993). The protective trade regime arose from a
policy of import substitution industrialisation that began in the
1920s with the substitution of imports of consumer goods by
domestic manufactures, but then shifted in the 1970s and 1980s
towards import replacement in downstream industries, particularly
the chemical and basic metals sub-sectors.
Although some initiatives had been made in opening the economy
from
the 1970s (Export Development Assistance scheme in 1970s,
General Export Incentive Scheme in 1990 and the relaxation of
quantitative restrictions), reform of the trade regime accelerated
with South Africa’s formal Offer in 1995 to the WTO. In this Offer
South Africa agreed to bind 98% of all tariff lines, reduce the
4
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number of tariff rates to six, to rationalise the over 12000
tariff lines and to replace quantitative restrictions on
agricultural products with tariffs.1
Substantial progress has been made in simplifying the tariff
structure of
the early 1990s, but further progress can be made. The total
number of HS8-digit tariff lines fell from over 11200 in 1994 to
6707 in 2004. The tariff structure has also been simplified with
the number of HS8-digit lines bearing formula, mixed or specific
duties declining from 3524 in 1994 (30% of total) to 205 in 2004
(3% of total), although almost half of this reduction took place
between 2003 and 2004. The number of ad valorem tariff rates also
remains high (37 in 2004 vs. 31 in 1994) and exceeds the 6 tariff
rates proposed in South Africa’s GATT/WTO Uruguay Round offer. If
non-ad valorem tariff rates are included, the number of different
rates in 2004 rises to 99.2 Therefore, there is further scope to
simplify the tariff structure as per the Offer to the WTO.
Average nominal and effective protection rates have also fallen.
The
simple average Most Favoured Nation (MFN) tariff rate, inclusive
of surcharges, fell from 22% in 1994 to 11.3% in 2003 (Figure 1),
although most of this decline occurred prior to 2000.3 4 Since
2000, tariff rates facing EU and SADC countries have also fallen in
accordance with the SA-EU Free Trade Agreement (2000) and the SADC
Free Trade Protocol (1996), reaching 9.7% and 5.1% in 2003,
respectively. Average effective rates of protection (ERP) have also
fallen, but remain high, particularly in manufacturing where they
averaged 25% in 2003 (Table 1).5 Further simplifications of the
tariff structure initiated in early 2004 have led to addition
reductions in average tariff rates facing MFN (8.3%), EU (7.1%) and
SADC (2.4%) countries.6
1 This is a very cursory overview of the liberalisation process,
which has been heavily debated in the South African context. For
more detailed discussions see Holden (1992), Belli et al. (1993),
Bell (1997), Jenkins et al. (1997), Fedderke and Vase (2001, 2004)
and Rangasamy and Harmse (2004).
2 The number of rates in 1990 and 1994 were 733 and 717,
respectively. 3 These rates include ad valorem equivalents of
formula, specific, compound and mixed duties and are
based on HS8-digit tariff lines. Duty collection rates are used
to calculate the ad valorem equivalents. See Edwards and van de
Winkel (2005) for further details.
4 The decline in average nominal protection in South Africa has
been marginally higher than reductions in other developing
economies, but this has not significantly affected its ranking
(43-44 percentile) in terms of tariff levels.
5 ERP are calculated as ∑∑
−
−=
iij
iiijj
j a
tatERP
1 where tj is the tariff on outputs, ti is the tariff on
inputs
and aij is the quantity of intermediate input i used in the
production of one unit of j. The Balassa (1965) approach is
followed and services are given a zero output tariff. See Holden
and Holden (1975), Greenaway and Milner (1993) and Holden (2001)
for a critical evaluation of ERP.
6 These estimates are based on data obtained from the DTI and
use a different approach to calculate ad valorem equivalents. Using
this approach 2003 yields tariff rates of 10.7% for MFN, 9.6% for
EU and 5.1% for SADC. The weighted average (using import values)
nominal tariff in 1993 equals 10.1%.
5
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Figure 1: Evolution of nominal tariff protection
Evolution of nominal tariff protection
0.0
5.0
10.0
15.0
20.0
25.0
1994
1997
2000
2003
1994
1997
2000
2003
1994
1997
2000
2003
1994
1997
2000
2003
%
SurchargesTariffs
All Agriculture Mining Manufacturing
Note: The tariff rate for 2003 reflects the weighted average
(using import values) of MFN, EU and SADC rates.
All aggregate sectors experienced a decline in nominal and
effective protection between 1994 and 2003, but protection remains
high in some sectors (Table 1). Relatively strong declines in
nominal protection were experienced in textiles, footwear, wearing
apparel and communication equipment. Despite these declines,
nominal protection remains high in the textile, clothing and
footwear sectors where average tariffs exceed 20%. Other highly
protected sectors are tobacco (33%) furniture (17.4%) and motor
vehicles (15.2%). The structure of effective protection rates is
similar to nominal protection rates and therefore high ERP are also
found in the tobacco (257%), textiles (76%), clothing (94%),
footwear (51%), and furniture (46%) sectors.7 These rates are
substantially lower than in 1994 when ERP exceeded 100% for most of
these sectors.
Table 1: Measures of sectoral protection
Scheduled rates ERP Anti-export biasa
1994 2003 % Δb 1994 2003 1994 2003 All 21.9 10.6 -9.3 38.6 18.9
2.0 1.4 Agriculture 8.9 4.4 -4.1 7.3 3.8 1.2 1.1 Mining 2.8 0.6
-1.9 3.8 -1.2 1.1 1.0 Total Manufacturing 22.5 10.9 -9.5 48.4 24.3
2.2 1.5 Food 18.8 11.5 -6.2 55.3 38.3 3.1 1.9 Beverages 29.3 15.4
-10.8 51.9 28.4 2.0 1.4 Tobacco 41.7 32.9 -6.2 340.5 257.2 13.4 6.2
Textiles 41.3 20.3 -14.8 149.7 76.2 3.3 2.1 Wearing apparel 75.1
33.4 -23.8 218.4 94.1 4.2 2.2 Leather products 25.9 11.3 -11.5 59.7
18.8 6.1 2.0
7 The correlation between ERP and nominal protection rates
exceeds 0.79 in all cases.
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Footwear 48.0 22.7 -17.1 106.0 51.1 5.1 2.1 Wood products 14.5
8.5 -5.3 21.7 14.0 1.5 1.3 Paper products 11.3 6.2 -4.7 15.8 10.3
1.5 1.2 Printing & publishing 16.1 4.6 -9.9 22.2 4.5 1.4 1.1
Coke & petroleum 5.1 3.3 -1.8 10.0 8.2 1.2 1.1 Basic chemicals
8.1 1.6 -5.9 14.4 1.4 1.3 1.1 Other chemicals 16.2 4.4 -10.2 32.3
7.4 1.8 1.2 Rubber products 18.6 10.8 -6.5 46.6 31.7 1.9 1.5
Plastic products 19.8 9.8 -8.4 36.2 20.3 1.7 1.3 Glass products
17.2 7.2 -8.5 32.1 13.3 1.5 1.2 Non-metallic minerals 15.0 5.6 -8.2
29.9 10.8 1.4 1.2 Basic iron & steel 8.8 4.3 -4.2 20.1 11.0 1.4
1.2 Non-ferrous metals 10.8 2.1 -7.9 17.9 2.9 1.3 1.1 Metal
products 18.3 7.9 -8.8 36.7 16.1 1.7 1.3 Machinery & equipment
10.4 3.6 -6.2 11.9 2.9 1.4 1.1 Electrical machinery 18.3 7.1 -9.4
33.0 13.8 1.8 1.3 Communication equipment 24.2 2.9 -17.1 35.5 1.2
2.2 1.1 Professional & scientific 12.2 0.3 -10.6 9.5 -5.9 1.5
1.0 Motor vehicles 25.9 15.2 -8.5 45.1 32.3 2.4 1.6 Other transport
12.3 0.8 -10.2 14.9 -3.2 1.5 1.0 Furniture 32.1 17.4 -11.2 82.6
46.4 3.1 1.8 Other manufacturing 26.5 5.9 -16.2 96.5 17.5 3.0
1.3
Notes: a. To capture the duty free credit system implemented in
the clothing & textile and motor vehicle industries, zero
tariffs were imposed on textile inputs in the production of
clothing and textiles, and motor vehicles inputs used in the
production of vehicles. b. Calculated as ((t1-t0)/(1+t0)-1).
Tariffs include ad valorem equivalents for formula duties, specific
duties and mixed duties. The AVE are calculated using collection
rates. For formula duty and mixed duties the AVE are equal to the
collection rates if these exceed the ad valorem component of the
tariff. The average value for manufacturing is calculated as the
weighted average of the 3-digit SIC codes using real output between
1988-2002 as weights. The tariff rate for 2003 reflects the
weighted average (using import values) of MFN, EU and SADC rates.
The values for the scheduled tariffs are simple averages at the HS8
digit level.
The reduction in tariffs has also contributed significantly
towards raising the profitability of export production and reducing
the anti-export bias (AEB) (Table 1).8 Import taxes on intermediate
goods were equivalent to 38% of value added in aggregate
manufacturing in 1994 (not taking into account export subsidies),
but fell to 19% by 2003. The combined effect of a reduced tax on
intermediate goods and reduced effective protection was a reduction
in the anti-export bias in aggregate manufacturing from 2.2 to 1.5
over this period. However, much of the improvement in the AEB from
tariff liberalisation from 1994 to 1997 was offset by the removal
of export subsidies under the General Export Incentive Scheme. Kuhn
and Jansen (1997), for example, estimate that the removal of export
subsidies led to an increase in the anti-export bias between 1993
and 1996. 9
In conclusion, South Africa has made considerable progress in
reducing
tariff protection during the 1990s, but there is still scope for
further
8 The anti-export bias is calculated as (1+ERP)/(1-XRP) where
XRP is the implicit export tax of tariffs
calculated as ∑
∑−
=
iij
iiij
j a
taXRP
1.
9 The lack of export subsidy data prevented a similar analysis
in this paper.
7
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simplification of the tariff structure. Average nominal
protection is still higher than the average for developing
economies and high effective protection rates remain in many
manufacturing sectors. Nevertheless, tariff liberalisation has
raised the profitability of export supply, which will have enhanced
export growth during the 1990s.
Increased openness The reductions in tariffs, the re-integration
of South Africa into the
international arena and a real depreciation of the exchange rate
has raised exports and imports as a share of GDP. As shown in
Figure 2, merchandise exports as a share of GDP fell during the
1970s and the early 1980s in response to a decline in primary
sector exports, particularly gold exports. From the mid-1980s
manufactured export growth, spurred by a sizeable real depreciation
and recession driven ‘vent-for-surplus’ exports (Fallon and Pereira
da Silva, 1994), reversed this trend and total merchandise exports
rose as a share of GDP. The role of manufacturing exports in
driving this trend is reflected in the rise in its share of GDP
from 4% in 1985 to 9.8% in 1994 (Figure 2).
Manufacturing exports as a share of GDP continued to rise in the
1990s,
despite the modest recovery in output growth. By 2000,
manufactured exports as a share of GDP had risen to 15%. The rising
importance of exports in aggregate manufacturing is also shown by
the rise in export orientation (exports/gross output) from 12% in
1993 to 23% in 2000. This increased openness of manufacturing
during the 1990s has been broad based, with export orientation
rising in 25 of the 28 SIC 3-digit sectors analysed (Table 2).
Manufacturing firms have thus become firmly entrenched in the
international market and no longer export primarily on a
vent-for-surplus basis.
Figure 2: Indices of openness, 1970-2001
Merchandise trade to GDP
0%
5%
10%
15%
20%
25%
30%
1970
1973
1976
1979
1982
1985
1988
1991
1994
1997
2000
Merchandiseexports/GDP
Manufacturingexports/GDP
Merchandiseimports/GDP
8
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Growth in imports also recovered strongly in the 1990s in
response to the recovery in output growth and the reduction in
import barriers. Import growth had stagnated during the 1980s in
response to the depreciation in the mid-1980s, the imposition of
surcharges from 1988 and the onset of the domestic recession in
1989. However, from 1990 growth in merchandise imports recovered
raising its share of share of GDP from 13% in 1990 to 21% in 2000
(Figure 2). Import penetration in manufacturing rose from 17% to
28% over the same period. The rise in import penetration has also
been broad based, rising in 24 of the 28 SIC 3-digit sectors
between 1990 and 2000. Particularly strong increases occurred in
the textiles, apparel and footwear sectors as well as rubber
products, other transport equipment and furniture.
Table 2: South African exports by industry as a share total
manufactured exports and export orientation
1970 1980 1990 1994 2000 Manufacturing (Rmill, 1995 prices)
14,495 22,319 38,793 47,617 85,536
Manufactured exports/total merchandise trade 22% 29% 43% 47%
62%
Total Manufacturing 100% 100% 100% 100% 100% Food products 18%
13% 9% 8% 5% Textiles, apparel 4% 6% 5% 6% 3% Wood 0% 2% 2% 2% 2%
Paper and printing 9% 5% 7% 6% 6% Chemicals 17% 15% 15% 19% 20%
Non-metallic minerals 4% 3% 1% 2% 1% Base metals 13% 33% 32% 25%
22% Fab. metal and machinery 21% 12% 18% 21% 32% Other 13% 11% 11%
12% 9% Export orientation Manufacturing 8% 8% 12% 15% 23% Food
products 8% 6% 5% 6% 7% Textiles, apparel 5% 7% 9% 12% 14% Wood 1%
9% 12% 14% 18% Paper and printing 11% 7% 11% 12% 18% Chemicals 14%
10% 11% 15% 23% Non-metallic minerals 8% 7% 5% 8% 11% Base metals
12% 26% 44% 43% 44% Fab. metal and machinery 5% 3% 8% 12% 26% Other
18% 28% 18% 24% 29%
Source: Own calculations based on data obtained from Quantech
(2004). Export orientation is calculated as the share exports in
gross output. Calculations based on real values.
The composition of exports has also changed with
manufacturing
displacing mining as the dominant export sector. During the
1970s and early 1980s mining sector exports accounted for between
60% and 65% of total exports (including services exports). The bulk
of this was gold exports, which accounted for between 35% and 52%
of total merchandise exports from 1972-1985 (Bell et al, 1999:
Table
9
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2).10 With the collapse in the gold price in the 1980s and the
declining grade of ore, the share of mining exports in total
exports (gold in particular), fell dramatically, reaching 47% in
1990 and 29% in 2000. In contrast, in response to relatively strong
export growth, the share of manufacturing in total exports rose
from 25% in 1980 to 41% in 1994. During the 1990s, manufacturing
overtook mining as the most important export sector, accounting for
53% of total exports by 2000.
Figure 3: Skill bias of manufactured export growth
Skill bias of export growth, 1994-2002
y = 0.66x - 0.03R2 = 0.33
-0.25-0.20-0.15-0.10-0.050.000.050.100.150.20
0.00 0.05 0.10 0.15 0.20 0.25 0.30
Highly skilled/Less skilled ratio
Ave
rage
ann
ual g
row
th
Skill bias of export growth, 1990-94
y = -0.21x + 0.14R2 = 0.01
-0.10
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.00 0.05 0.10 0.15 0.20 0.25
Highly skilled/Less skilled ratio
Ave
rage
ann
ual g
row
th
Skill bias of export growth, 1980s
y = 0.65x + 0.02R2 = 0.13
-0.15
-0.10
-0.05
0.00
0.05
0.10
0.15
0.20
0.00 0.05 0.10 0.15 0.20
Highly skilled/Less skilled ratio
Ave
rage
ann
ual g
row
th
Skill bias of export growth, 1970s
y = -1.66x + 0.13R2 = 0.27
-0.10
-0.05
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14
Highly skilled/Less skilled ratio
Ave
rage
ann
ual g
row
th
Manufacturing exports have also diversified during the 1990s,
with
relatively strong export growth in skill-intensive sectors. This
is clearly shown in the scatter plots in Figure 3 where high export
growth was experienced from 1994 in relatively skill-intensive
sectors such as coke and refined petroleum products, other
chemicals, motor vehicles, parts & accessories and other
transport equipment. Particularly strong export growth was
experienced in motor vehicles and other transport equipment sectors
in response to the Motor Industry Development Programme (MIDP)
introduced in 1995. The share of these two sectors in total
manufacturing exports rose from 6% in 1990 to 19% in 2002. Poor
export growth, combined with strong import growth, occurred in
less-skill intensive sectors such as textiles, wearing apparel,
leather and footwear has also contributed towards the skill-bias of
export growth.11 12
10 Based on IDC (1995)—data in current prices. 11 Net exports
show similar trends. However, no consistent trend is found when
using the capital
intensity (machinery and equipment capital per worker) of
production within manufacturing sectors.
10
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South Africa’s Dynamic Export Performance: A Cross-country
Comparison
The ways in which export patterns change over time has
profound
implications for the relationship between trade on the one hand,
and industrialisation and economic growth on the other. “Success in
entering lines of production with significant potential for global
demand expansion, high value added and rapid productivity growth
widens the scope for the exploitation of increasing returns from
larger markets, and enhances the role of trade in economic growth”
UNCTAD (2002: 52). In contrast, a high concentration of exports in
sluggish global markets or activities with limited potential for
productivity growth endangers the growth process. Middle-income
countries like South Africa have additional reasons to urgently
address the issue of upgrading their export structures. The entry
of low wage labour abundant economies such as China and India into
the world market have challenged middle-income economies’
comparative advantage in low-skill manufactures. As argued by
(UNCTAD, 2002: 126):
“… it is imperative that middle-income countries upgrade rapidly
from low skill to more market-dynamic, technology-intensive
products with a view to successfully competing with industrialised
countries and the first-tier NICs. If not, they risk being squeezed
between the bottom and top ends of the markets for manufactured
exports”
This section, therefore, presents a cross-country analysis of
South Africa’s
dynamic export performance using two different dynamic
indicators. Following UNCTAD (2002), ‘dynamic’ products are defined
in terms of their global demand potential (market-dynamic products)
and productivity potential (supply-dynamic products). The former
classification identifies products that have a strong growth
potential in world markets, while the latter identifies products
characterised by strong productivity growth potential.13
Supply-dynamic products Performance in supply-dynamic products
is assessed using a technology-
based product classification, developed by Lall (2000), and used
in UNCTAD (2002) and UNIDO (2004). As shown in Table 3, exports are
classified into primary products (PP), resource based manufactures
(RB), low technology manufactures (LT), medium technology
manufactures (MT) and high technology manufactures (HT).
12 Turning to imports, South African imports are heavily
concentrated in capital and intermediate goods and reflect the high
import dependency of the capital-intensive basic metals and
chemicals sub-sectors. etailed discussion of import composition is
contained in the longer version of this paper available from the
author.
13 The data used in this sub-section differs in important ways
from that presented in the rest of the paper. First, data for other
countries is obtained from the UN Comtrade database and is
classified according to SITC (Revision 2). For South Africa, export
data at the 8-digit HS level are obtained from Customs & Excise
and converted to 3-digit SITC level using a concordance files
obtained from UN Comtrade. Secondly, to facilitate cross-country
comparisons, all data are expressed in current US dollars rather
than constant 1995 rands.
11
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Primary products and resource-based manufactures tend to be
unskilled-labour- and scale-intensive, and skill requirements tend
to rise with the degree of technological complexity (see Lall
(2000) for a complete description of each technology category).
“Since increased application of human capital and technology
tends to raise
labour productivity, such a classification can be expected to
provide a reasonably good guide to sectoral differences in the
potential for productivity growth” UNCTAD (2002:66). The ability of
a country to shift exports into high technology products therefore
has important implications for long run output growth, as
productivity growth becomes the primary source of output growth
(and income per capita) once underutilised labour and natural
resources are exhausted.
Table 3: The Technological Classification of Exports14
PRIMARY PRODUCTS Fresh fruit, meat, rice, cocoa, tea, coffee,
wood, coal, crude petroleum, gas, metals MANUFACTURED PRODUCTS
Resource based manufactures
RB1: Agro/forest-based products Prepared meats/fruits,
beverages, wood products, vegetable oils
RB2: Minerals-based products Ores & concentrates,
petroleum/rubber products, cement, cut gems, glass Low technology
manufactures
LT1: ‘Fashion cluster’ Textile fabrics, clothing, headgear,
footwear, leather manufactures, travel goods
LT2: Other low technology Pottery, simple metal
parts/structures, furniture, jewellery, toys, plastic products
Medium technology manufactures
MT1: Automotive products Passenger vehicles and parts,
commercial vehicles, motorcycles and parts
MT2: Process industries Synthetic fibres, chemicals and paints,
fertilisers, plastics, iron, pipes/tubes
MT3: Engineering industries Engines, motors, industrial
machinery, pumps, switchgears, ships, watches High technology
manufactures
HT1: Electronics and electrical products Office/data
processing/telecommunications equip, TVs, transistors, turbines,
power generating equipment
HT2: Other high technology Pharmaceuticals, aerospace,
optical/measuring instruments, cameras
“SPECIAL” TRANSACTIONS Electricity, cinema film, printed matter,
art, coins, pets, non-monetary gold Source: Lall (2000)
14 This study moves non-monetary gold (SITC 971) from “special
transactions” into the primary products category, and precious and
semi-precious stones (SITC 667) from resource-based manufactures to
primary products.
12
-
There are also good market-dynamic reasons for shifting exports
into high technology products as these products are the fastest
growing in world trade. As shown in Table 4, the average annual
export growth of high technology products (9.1%) between 1988 and
2002, was almost double that of low technology (5.6%), medium
technology (5.7%) and resource-based (4.9%) products. The share of
high technology products in world trade rose from 15.8% in 1988 to
23.6% in 2002. All other categories had a smaller share in world
trade in 2002 than they did in 1988, although the medium technology
group has regained some of its losses since 2000.
An important feature of the changing pattern of world trade in
the 1990s,
is the rapid growth in developing country exports, particularly
within high and medium technology products (Figure 4). Total
developing country as a share of world trade rose from 19.1% in
1988 to 30.5% in 2002. Its share in high technology products
doubled from 14.8% to 34.3% over the same period. By 2002, the
value of developing country exports of medium and high technology
products together exceeded the combined value of primary products,
resource-based and low technology manufactures. In contrast, in
1988 medium and high technology exports equalled approximately half
the value of the remaining categories.
Figure 4: Developing country market share gains in total
exports, by broad technology category, 1988 & 2002 (%)15
0
5
10
15
20
25
30
35
40
45
50
Total exports Primary products Resource-basedmanufactures
Low techmanufactures
Medium techmanufactures
High techmanufactures
0
5
10
15
20
25
Share 88 Share 02 Gain Developing country growth rate World
growth rate
Source: as above Note: Share gains expressed simply in
percentage points. Growth rates are annual averages.
15 Country groupings follow World Bank definitions. “Developing
countries” include the four mature Tiger economies of East Asia
(Hong Kong, Korea, Singapore and Taiwan).
13
-
In comparison to developing countries, however, South Africa’s
total export growth during the 1990s (2% per annum) has been
relatively poor. South African export growth has also lagged the
average for the world (6%), developed countries (5%), and a
selection of countries with similar shares of resource intensive
products in total exports to South Africa, the Resource Group
(6.1%) (Table 4).16 An important source of this relatively poor
growth is the negative growth in primary product exports (-1.1%)
during this period. As a result of the poor export performance,
South Africa’s share of world exports declined 0.89% to 0.52%
between 1988 and 2002.
Table 4: Annual average growth rates by broad technology
category, 1988-2002 (%)17
World Developed countries Developingcountries
South Africa
Resources Group
Total exports 6.02 4.96 9.58 2.02 6.14 Primary products 3.59
2.79 4.95 -1.14 4.18 Total manufactures 6.32 5.13 10.63 6.91 7.72
Resource-based 4.89 4.09 7.89 4.26 5.63 Pure manufactures 6.59 5.33
11.13 8.57 9.52 Low technology 5.63 4.37 7.94 5.57 8.57 Medium
technology 5.67 4.77 11.07 9.67 8.51 High technology 9.10 7.14
15.83 11.53 14.95 Source: as above. As described in Appendix C,
South African data sources comprise the following: Customs and
Excise, the Minerals Production and Sales Statistics database, the
South African Reserve Bank (SARB), and the South African Department
of Trade and industry (DTI).
Within aggregate manufacturing, exports have grown marginally
more
quickly than the global average, but still slower than other
developing countries and the Resource Group.18 The growth
performance vis-à-vis developing countries is relatively poor in
all technology categories and is particularly weak in high
technology products. South African exports also lag that of the
Resource Group in all but the medium technology category. The
relatively strong growth in Medium technology exports can be
attributed to the very strong growth in motor vehicle exports under
the MIDP programme.
16 The Resource Group consists of twenty-five countries, listed
in Appendix A, selected on the basis of having similar levels of
natural resource dependent products (primary products +
resource-based manufactures) in total exports in the late 1980s.
That is, on the basis of having broadly similar export structures.
Most of the countries are low- and middle-income countries from
Latin America and Sub-Saharan Africa, but also included were
Australia, New Zealand, Norway and Indonesia.
17 Country groupings follow World Bank definitions. “Developing
countries” include the four mature Tiger economies of East Asia
(Hong Kong, Korea, Singapore and Taiwan).
18 There is substantial variation in export performance amongst
the members of the Resource Group. The OECD economies, Australia,
New Zealand and Norway, have growth rates more in line with
developed economies. Indonesia, on the other hand, experienced very
high growth rates, especially in high technology products. The
growth rates of these ‘outliers’, however, tend to cancel each out,
leading to similar growth rates for the group as a whole to those
calculated when these four ‘outliers’ are excluded.
14
-
The relatively poor export growth has resulted in little or no
gains to South Africa’s share of world manufacturing exports. This
is shown in Table 5 which presents world market shares by region
and technology sub-category. South Africa’s share of world exports
of manufactures rose marginally from 0.3% to 0.32% between 1988 and
2002, while its share of pure manufactures (non-resource based
manufactures) rose from 0.2% to 0.26%.19 As can be seen, South
Africa’s faster growth vis-à-vis the world in MT exports has been
due to very strong performances in MT1 (automotive), whose world
market share (WMS) increased seven-fold from 0.05% to 0.36%, and
MT3 (engineering), whose WMS roughly tripled. In high-technology
products, South Africa has seen a small rise in its 1988 share of
HT1 (electronics), and no change at all in HT2 (other). The
relatively poor performance is in stark contrast to the pattern in
East Asia, whose share of manufacturing exports rose from 12% to
18%, and share high technology exports rose from 13% to 27% over
this period.
Table 5: South Africa’s changing share of developing country,
Resource Group and world exports, 1988-2002 (%)
Developing Countries Resource Group World
1988 2002 % change 1988 2002 %
change 1988 2002 %
changeTotal manufactures 1.7 1.1 -38.0 12.8 11.5 -10.0 0.30 0.32
6.7
Resource based 4.3 2.6 -38.1 11.0 9.1 -16.7 0.76 0.7 -7.9
RB1: Agro-based 2.8 2.0 -26.8 7.9 7.0 -11.9 0.50 0.54 8.0
RB2: Minerals-based 6.6 3.5 -46.1 14.6 12.3 -15.8 1.16 0.94
-19.0
Low technology 0.9 0.7 -26.7 12.8 8.7 -32.4 0.28 0.28 0.0
LT1: Fashion cluster 0.3 0.3 -7.2 5.4 3.9 -26.9 0.15 0.18
20.0
LT2: Other 1.9 1.1 -42.7 23.1 15.5 -32.9 0.39 0.36 -7.7
Medium technology 2.1 1.8 -16.3 18.2 21.1 16.0 0.23 0.39
69.6
MT1: Automotive 0.9 2.4 151.6 14.4 34.6 140.0 0.05 0.36
620.0
MT2: Process 4.6 2.6 -43.6 26.7 23.7 -11.1 0.74 0.73 -1.4
MT3: Engineering 0.7 1.0 50.3 7.6 13.6 80.6 0.08 0.24 200.0
High technology 0.3 0.2 -41.1 6.6 4.3 -34.5 0.04 0.06 50.0
HT1: Electronic 0.2 0.1 -32.4 6.0 4.1 -32.2 0.03 0.05 66.7
HT2: Other 1.3 0.8 -41.8 7.4 4.8 -35.3 0.07 0.07 0.0 Source: as
above. Note: Percentage changes calculated as
(share02-share88)/share88*100.
South Africa’s share of developing country and Resource
Group
manufactured exports fell. The share of developing country
exports fell from 1.7% to 1.1% and those of the Resource Group from
12.8% to 11.5% between 1988 and
19 South Africa’s share for world market share for total exports
dropped alarmingly (0.89% to 0.52%), but again this is due to the
abnormal influence of gold on South Africa’s market share in
primary products.
15
-
2002.20 Loss in share occurred in all technology categories
apart from MT1 (automotive) and MT3 (engineering).
Although overall export growth has been comparatively low,
some
progress has been made in diversifying manufacturing exports
towards medium and high technology products. This diversification
is mainly due to the strong growth in motor vehicle related exports
(medium technology), with some minor diversification towards high
technology products (Figure 5). The Resource Group also diversified
its manufacturing exports, but this diversification was more evenly
spread across high technology, medium technology and low technology
products. The strongest restructuring towards high technology
sectors occurred within the East Asian and Pacific region where the
share of these sectors in total exports rose from 21% to 41% during
the 1990s.
Figure 5: Manufactured export structures, 1988-90 and
2000-02
17 14 18 13 13 9
4433
4938
2119
38
2740
26
20
16
21
22
4339
27
28
25
24
34
46
25
27
1928
1732
21
41
3 5 513
0%
20%
40%
60%
80%
100%
1988-90 2000-02 1988-90 2000-02 1988-90 2000-02 1988-90 2000-02
1988-90 2000-02
World Developingcountries
EAP South Africa Resources Group
Resource-based Low tech Medium tech High tech
Market-dynamic products
The second indicator of South Africa’s dynamic export
performance is its
positioning in demand/market-dynamic products. Performance in
market-dynamic products is measured by the change of a country’s
world market share in products that are becoming steadily more
important to global trade. Countries that are able to shift
20 Interestingly, the share reduction is almost twice as large
if one removes the four mature Tiger economies are removed from the
developing country group. This reflects the emergence during the
1990s of Mexico and China as manufacturing giants, but also Hong
Kong’s (and to a lesser extent Singapore and Korea’s)
de-industrialisation and shift into tertiary sector activities
(Lall & Kraemer-Mbula, 2005).
16
-
export production towards products with a strong global demand
potential will reduce the risk of declining export growth and
declining terms of trade.
Previous analyses have noted weaknesses in South Africa’s
export
performance from the market positioning perspective (Van
Seventer and Gibson (2004; Tsikata, 1999).21 In this section, we
extend these analyses and compare South Africa’s performance with
East Asia’s and the Resource Group’s. The approach used here is
similar to that of Tsikata (1999) and Van Seventer and Gibson
(2004), but anchors the analysis around those products that
contributed the most to South African export growth during the
1990s. Firstly, products (at 3-digit SITC level) are identified as
dynamic products if world export growth exceeds the average for all
products (i.e. the share of the product is rising in world trade).
Secondly, South Africa’s top 20 products (at 3-digit SITC level)
are then identified and their world market share (WMS) is
calculated.22 To assess whether these products are positioned
optimally in terms of global demand, South Africa’s world market
share (WMS) in each of them is compared to world export growth.
We postulate that South Africa is positioned optimally in terms
of global
demand if its WMS in these products is rising and they are
experiencing higher than average world export growth. This
relationship is more clearly shown in Figure 6, which plots South
Africa’s changing WMS of its top 20 export growth products against
world export growth. The size of the bubble reflects South Africa’s
export value of each product in 2002. The horizontal dotted line in
the figure represents average world growth for all products (6.02%
per year). Optimal market positioning occurs if a large proportion
of the 20 products are situated in the top right hand ‘quadrant’
(above the dotted line and to the right of the vertical axis), i.e.
South Africa’s WMS is rising in products experiencing above average
growth in world demand. Using Tsikata’s (1999) terminology, these
are ‘rising stars’.
Poor market positioning occurs if a product’s WMS is rising in
stagnating
(in terms of world share) world markets (bottom right quadrant),
or its WMS is falling in dynamic world markets (top left). The
bottom left quadrant below average world growth reflects products
in which the economy is rapidly retreating from stagnating world
markets.
21 Van Seventer and Gibson (2004) find a low share of South
African exports in the top 40 demand-dynamic products identified by
UNCTAD (2002). Tsikata (1999) finds that relative to a range of
middle-income economies (Korea, Mexico, Taiwan, Malaysia, Thailand,
Brazil), South Africa exports a relatively high proportion of
products for which world markets are not growing very fast.
22 The top 20 export growth products accounted for 53% of South
Africa’s total exports in 2002.
17
-
Figure 6: The market positioning of South Africa’s top 20
exports
784 - car parts
112 - alcoholic bev.
713 - engines
057 - fruit & nuts
672 - iron ingots
034 - fish
667 - precious stones (diamonds)
641 - paper & paperboard
782 - special purpose vehicles
684 - aluminium
281 - iron ore
781 - passenger cars
667 - silver & platinum
289 - precious metal ores
784 - furniture and parts
322 - coal & lignite
522 inorganic chemicals
246 - pulpwood
743 - pumps & compressors
671 - pig iron
0
1
2
3
4
5
6
7
8
9
10
-15 -10 -5 0 5 10 15
Change in South Africa's world market share (WMS)
Glo
bal g
row
th ra
te, (
%)
Global total export
growth rate
Note: Dotted line is world growth for all products. WMS changes
expressed as percentage points.
As can be seen, the market positioning of South African exports
is poor:
The majority of its top 20 exports during the 1990s are in
stagnating world markets (below the dotted line). These sectors in
the diagram alone account for 43% of total South African exports in
2002. Very few of South Africa’s most important exports are found
in the top right hand ‘quadrant’. The major sectors that do fall
into this category are passenger cars (SITC 781), pumps &
compressors (SITC 743), furniture (SITC 784) and precious metals
(SITC 289). Together these sectors only account for 13% of total
South African exports.
The contrast in performance with East Asia is clearly shown in
Figure 7,
where 16 of the top 20 exports are in dynamic world markets.
Thirteen of these fall in the top right hand quadrant. In other
words, most of East Asia’s top exports are in markets growing
faster than the global average, and it is gaining world market
share in them.
18
-
Figure 7: The great market positioning of East Asia’s top 20
exports
771 - elec. power mach.
759 - computer parts
776 - transistors & semiconductors
752 - computers
763 - sound rec. equip.
793 - ships583 - polymerization
products
775 - household equip.
845 - knitted garments
341 - natural & manuf. gas
894 - baby carriages
843 - women's outer garments
781 - passenger cars 749 - non-elec. parts
893 - articles of plastic
821 - furniture
778 - elec. machinery
772 - switches & relays
655 - knitted fabrics
764 - telecomms. equip.
0
2
4
6
8
10
12
14
-15 -10 -5 0 5 10 15 20 25 30 35 40
Change in EAP's world market share (WMS)
Glo
bal g
row
th ra
te (%
)
Global total export
growth rate
Note: Dotted line is world growth for all products. WMS changes
expressed as percentage points.
The market positioning of the Resource Group also poor with a
high
proportion of the group’s top export performers located in the
lower right quadrant (Figure 8). There is therefore some similarity
in performance between South Africa and the Resource Group. A high
concentration of exports in primary and natural resource-based
products has negatively affected export growth for resource based
economies similar to South Africa during the 1990s. Further, these
economies have also been unable to restructure significantly into
dynamic world markets.
This similarity between South Africa and the Resource Group
suggests
that natural resource endowments are an important determinant of
export performance and the ability to diversify. The ability of
these economies to diversify into high technology products is
constrained by the comparative advantage in resource-based products
that the rich natural resource endowments provides them with.
However, there are also important differences in export growth and
diversification amongst countries within the Resource Group. These
differences may highlight the role of country specific effects such
as trade policy, infrastructure, skills, etc. The importance of
many of these supply side determinants is assessed in Section
3.
19
-
Figure 8: The market positioning of the Resource Group’s top 20
exports
641 - paper
057 - fruit & nuts
081 - animal feed
041 - wheat
022 - milk287 - base metal
ores
322 - coal & lignite034 - fish
424 - veg. oils
843 - women's outer garments
821 - furniture
759 - computer parts
764 - telecomms. equip.541 - pharma.
341 - natural & manuf. gas
781 - passenger cars
011 - edible meat
682 - copper
971 - gold
112 - alcoholic bev.
-2
0
2
4
6
8
10
12
14
16
-20 -15 -10 -5 0 5 10 15 20
Change in Resources Group's meorld market share (WMS)
Glo
bal g
row
th ra
te (%
) Global total export
growth rate
Note: Dotted line is world growth for all products. WMS changes
expressed as percentage points.
Concluding points The data analysis in this section highlights a
number of important
features of South African export performance since the late
1980s:
• Significant progress has been made in liberalising South
Africa’s trade,
although there is scope for further simplification of the tariff
structure.
• Manufacturing export growth has increased, but has been poor
relative to the average for developing countries and a range of
economies that had similar export structures to South Africa in the
early 1990s. South Africa’s manufactured exports are being
“squeezed” at both ends of the technology spectrum, and not only by
better performing countries in East Asia.
• The structure of manufacturing exports is highly concentrated
in natural resource-based products, but there has been some
diversification into skill-intensive and medium technology products
through increased exports of vehicles, chemicals and engineering
products. However, South Africa lags other economies (including
similar resource-based exporters) in its restructuring of exports
towards high technology products.
• The concentration of South African manufacturing (and total)
exports in products with relatively weak world export growth has
contributed towards the relatively poor performance of South
African exports.
20
-
The evidence therefore indicates that while manufacturing export
growth
increased, it has not been sufficient to generate an export-led
boom as has been experienced in many economies, particularly within
East Asia. The question is why? One of the reasons for the
relatively poor export growth appears to be the concentration of
exports in natural-resource-based products, which experienced
relative low growth in world markets. However, South Africa’s
export performance was weak even in natural resource-based
products. Further, export growth and diversification into high
technology products was poor compared to a range of similar
resource-based exporters. This suggests that there were important
domestic constraints to export growth during the 1990s. In the
following section we draw upon various techniques, including
econometric estimations of export supply and demand function, to
investigate the various determinants South African manufacturing
export performance.
3. Determinants of South African Manufacturing Export
Performance
There is a diverse and growing empirical literature on the
determinants
of South Africa’s export performance. This literature includes
cost or price competitiveness analyses through the use of real
effective exchange rates (IMF, 1998, Kahn, 1998, Walters and de
Beer, 1999, and Golub, 2000); Revealed Comparative Advantage
studies (Valentine and Krasnik, 2000); shift-share analyses of the
composition of exports (Nordas, 1996; Bell et al. 1999. Edwards and
Schoer, 2002); market positioning studies (Edwards and Schoer,
2002; Van Seventer and Gibson, 2004); and econometric estimates of
export supply and demand functions (Smal, 1996; Tsikata, 1999;
Edwards and Wilcox, 2003; Edwards and Golub, 2004).
To investigate the determinants of South African manufacturing
export
performance, this section estimates export demand and supply
relationships using a panel of industry data from 1970-2002. The
analysis extends existing empirical work in South Africa in two
ways. Firstly, a fuller specification of the export supply
relationship is estimated. Secondly, the endogeneity of export
volumes and export prices is taken care of.
Specifying the Export Demand and Supply Relationships We use a
variant of the imperfect substitution model outlined in
Goldstein
and Kahn (1985) and discussed further in Edwards and Wilcox
(2003). 23 This model is represented as a system of equations for
export supply (Xs) and export demand (Xd), which simultaneously
determine the export price and the export
23 The model is an imperfect substitutes model where imperfect
substitutability between domestic and export products enables
domestic and export prices to differ from one another (Goldstein
and Kahn, 1985).
21
-
quantity. The long run export demand (Xd) and supply (Xs)
relationships are given by the following log-linear structures:
0,43210 >+++−=∗∗
iXd YPePX δδδδδδ (1)
and
0,3210 >Ψ+−−+= iXs ZCPPX ααααα (2)
where (all variables in logs):
X = volume of exports Y* = real foreign income P* = foreign
domestic price Px = domestic price of exports e = domestic to
foreign currency exchange rate P = domestic price C = nominal
variable cost Z = vector of other variables that influence the
supply of exports
Export demand is positively affected by foreign income (Y*) and
the price
of competing foreign goods (P*), but is negatively affected by
the foreign price of domestic exports (Px*= Px/e).24 The quantity
of exports supplied is specified as a positive function of its own
price and a negative function of the domestic price index and
variable costs.25 As export sales become profitably relative to
domestic sales (Px/P rises) firms shift production towards the
export market. Other supply side variables include tariff rates,
import penetration, infrastructure costs, capacity utilisation and
trend income.26
Following Fallon and Pereira da Silva (1994), Tsikata (1999),
Behar and
Edwards (2003) and Edwards and Golub (2004), capacity
utilisation is included to test the “vent-for-surplus” hypothesis.
A negative coefficient is expected. Tariff liberalisation reduces
the anti-export bias of production and thus positively affects
export production. Trend income is included as a proxy for
non-price improvements in competitiveness (infrastructure, total
factor productivity, export supply networks, learning by doing)
arising from increased economic activity. Finally, infrastructure
constraints are expected to negatively affect export supply.
24 Normally it is assumed that the demand function is homogenous
of degree zero in prices and the restriction -δ1(=δ2)+δ3 = 0 is
imposed, i.e. Px/eP* is included on the right hand side.
25 Homogeneity on the supply function requires the restriction
that α1+α2+α3=0. Alternatively, the supply function can be
specified in terms of real variable costs and the relative price of
exports to domestic prices (Px/P).
26 We also tested two concentration indices, the Gini
coefficient and Rosenbluth index, obtained from Fedderke and
Szalontai (1995). These variables were only available till 1996,
thus restricting our sample size considerably. The coefficients
were also mostly insignificant, although when significant they were
positive. The specifications presented in this study therefore
exclude the concentration indices.
22
-
An important consideration in estimating the export supply and
demand functions is that Px and X are endogenous variables. Failure
to account for this endogeneity will give rise to simultaneous
equation bias when estimating either equation.27 However, this is
less of a problem in small price-taking economies where the export
price is exogenous and the demand for exports is infinite. As
export prices are no longer endogenous, the export supply function
can be estimated independently of the demand equation.
Two approaches to the estimation of the export demand and
export
supply functions are followed in this study. Firstly, we first
estimate the export demand function and test whether the small
country assumption holds in the case of South Africa. Following
Riedel (1988) export demand (equation 1) is normalised on Px to
obtain
∗∗ +++−= YPeXPx d1
4
1
3
1
2
11
0 1δδ
δδ
δδ
δδδ
. (3)
In a small price taking country, the export price elasticity of
demand (δ1) tends towards negative infinity and the coefficient on
Xd and Y* therefore tend towards zero.28 Equation (3) then becomes
the standard PPP relationship in which export prices, measured in
domestic currency, equal foreign prices multiplied by exchange
rate. If price homogeneity holds, the coefficients on the exchange
rate and foreign prices equal one, i.e. δ2/δ1 = δ3/δ1 = 1.
Secondly, we estimate the reduced form function for export
volumes.29
Imposing the homogeneity assumptions and expressing the export
demand and supply functions in terms of relative prices (i.e.
δ1=δ2=δ3=δp and α1 = α2 = αp) and real unit labour costs (RC), the
reduced form equation for exports is expressed as:
( )[ ] 0,1
154320
1
>+−+−+++
= ∗∗ iZRCYPPeX λλλλλλλ (4)
where
Ψ=====+= 5341
41312
1
11
1
0100 ,,,,, λαλδ
δαλαλ
δα
λδδα
αλ .
27 This arises because the export volume and price in the demand
and supply relationship are correlated with the error terms.
Domestic prices, wages and the exchange rate may also be
endogenous. Export growth can affect the exchange rate, which in
turn affects inflation and wages. This problem may be particularly
problematic for South Africa during the 1970s and 1980s when the
gold price rose and then fell.
28 However, rising world demand for a particular product will
affect export supply through its impact on world prices.
29 Initial estimates of the export supply function (2) gave a
negative instead of positive coefficient for the relative price of
exports to domestic products (PX/P); a result also found by Fallon
and da Silva (1994). It was thus decided to concentrate on the
reduced form results.
23
-
(e+P*-P) is Real Effective Exchange rate measuring the price of
foreign products relative to South African products, valued in a
common currency. A real depreciation (e+P*-P rises) positively
affects exports. Note that in a small price-taking economy, the
reduced form equation effectively becomes the export supply
equation (2).
We draw on various data sources to construct a panel of data for
28
manufacturing sectors over the period 1970-2002. The data are
mostly obtained from Quantec (2004), the World Development
Indicators, the UNIDO INSTAT database, Statistics South Africa and
the IMF International Financial Statistics. Further details are
presented in the data Appendix.
To capture the short-run dynamics, the long-run relationships
(equations
(2, 3 and 4) are embodied in an autoregressive distributed lag
(ARDL) model. To capture the influence on exports of industry
specific variables that are constant over time, sector specific
effects (ηi) are included.
The export functions are estimated using two estimators: A
dynamic fixed
effects (DFE) estimator and the “system” General Methods of
Moments (GMM) estimator developed by Arrelano and Bover (1995) and
Blundell and Bond (1998).30 When using the GMM estimator, export
volumes, prices and the exchange rate are treated as endogenous
variables. In estimating the functions, the data are pooled and
homogeneity is imposed for all parameters other than the sector
fixed effects (ηi).
A potential limitation arising from the pooling of the data is
that it
imposes common long-run relationships and short run dynamics
across all sectors, which can give rise to misleading estimates of
the coefficients (Pesaran and Smith, 1995).31 To deal with the
possible biases arising from parameter heterogeneity, export
functions were estimated for a number of broadly defined
manufacturing sub-sectors: Beneficiated, natural resource-based,
metal and labour-intensive products.32
Empirical Results
Export demand
To test the sensitivity of the export demand function to the
selection of foreign prices two data sources are used: (a) US
import prices, obtained from the
30 See Pesaran and Smith (1995) for a discussion of the DFE and
other estimators. 31 Alternative estimators are the Mean Group
estimator of Pesaran and Smith (1995: 80) and the Pooled
Mean Group Estimator of Pesaran, Shin and Smith (1999). The
former allows for heterogeneity in short and long run coefficients,
while the latter constrains the long run coefficients to be the
same for each sector, but allows for short-run heterogeneity across
sectors.
32 Beneficiated consists of iron & steel, chemicals and
non-ferrous metals. Natural-resource based includes beneficiated
products, paper products and food products (food, beverages &
tobacco). Metal products include metal products, machinery &
equipment, electrical machinery, motor vehicles and other
transportation equipment. Labour-intensive products include
textiles, wearing apparel, footwear, leather and furniture.
24
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Bureau of Labour Statistics, and (b) a weighted average output
deflator for developed countries, constructed from the UNIDO INSTAT
(2001) database. The estimations using the foreign output price
deflators are estimated over the periods 1970-99 and 1980-99 to
enable comparisons with the results using the US import prices.
Table 6 presents the estimated long-run average coefficients for
the full sample of manufacturing industries and Table 6 to Tables
7-9 present the results for the sub-groupings.
Table 6: Long-run average export demand coefficients for
manufacturing
Using US Import Price Using Foreign output deflator
DFE GMM DFE GMM DFE GMM
1982-99 1970-99 1980-99
Export 0.084 ns 0.000 ns -0.103 ** -0.048 * -0.021 ns -0.008
ns
Exchange rate 1.000 *** 1.077 *** 1.205 *** 1.414 *** 0.916 ***
1.081 ***
Foreign price 0.934 ** 0.435 * 0.948 *** 0.941 *** 1.186 ***
0.259 *
Foreign output -0.005 ns 0.077 ns 0.455 *** 0.581 *** -0.136 ns
0.035 ns
Adjustment term -0.104 *** -0.109 *** -0.173 *** -0.048 ***
-0.123 *** -0.152 ***
Tests (H0)
Exchange rate = 1 ns ns ** *** ns ns
Foreign price =1 ns ** Ns ns ns ***
Erate=Pfor ns ns Ns ns ns ***
R2 0.57 0.40 0.54
F 16.06 *** 20239 *** 13.61 *** 33138 *** 16.70 *** 11685
***
Obs 428 428 812 560
AR(1) *** *** ***
AR(2) ns ns ns Note: lag limit set to 10 for GMM estimations,
except for the period 1970-99 where it is set to 5 (to solve
problem of autocorrelation).
The estimation results present supportive evidence for the
“small
country” hypothesis for total manufacturing when the sample is
restricted to the 1980s and 1990s. The coefficient on export
volumes and foreign output during this period is insignificantly
different from zero and the result is robust to changes in the
foreign price variable or the estimator (DFE or GMM). The results
are less robust when the sample is extended to include the 1970s.
The long-run average coefficients on exports and foreign output
estimated using the DFE are significantly different from zero and
imply a price elasticity of export demand of -10 and an income
elasticity of export demand of 4, respectively. However, the GMM
estimator suggests that when the endogeneity of export volumes and
the nominal effective exchange rate are accounted, the export
volume coefficient is only significant at the 10% level.33 Thus the
small country hypothesis holds once endogeneity problems are dealt
with.
There is also strong evidence that the long run average
coefficients on the
nominal effective exchange rate and the foreign price variable
are insignificantly
33 The implied price elasticity of demand and income elasticity
of demand are -21 and 12, respectively.
25
-
different from each other and are equal to 1. The null
hypothesis of equality of coefficients is only rejected in the GMM
estimator results when using foreign output deflators over the
period 1980-1999. In most cases it is also not possible to reject
the hypothesis that the long-run coefficient on the exchange rate
or foreign price equals 1. This provides strong evidence that
domestic exporters are price-takers in the international market and
hence that export prices rise by the full increase in foreign
prices or the depreciation of the exchange rate.34 These results
are consistent with those found by Edwards and Wilcox (2003) for
aggregate non-gold merchandise exports.
Although some variation is found, the results for the sub-groups
are
broadly consistent with those for total manufacturing.35 There
is strong evidence that the metal product and labour-intensive
industries are price-takers in the international market and
therefore face an infinite demand for their products. In both these
sub-groupings, the coefficient on export volumes is mostly
insignificant. Amongst natural resource based industries, a
significant negative coefficient on export volumes is found during
the 1970-99 period (giving an implied price elasticity of export
demand of -4 to -10), but this becomes insignificant once the
endogeneity of export volumes and the exchange rate are dealt with
and the sample is restricted to the 1980s and 1990s (see the GMM
results). Similarly, in most cases the equality of the exchange
rate and foreign price coefficients cannot be rejected. In cases
where they diverge (mainly metal products) export prices are
generally found to be more strongly affected by the exchange rate
(equal to or greater than 1) than foreign prices.
Overall, therefore, the results provide strong evidence that
South African
industries are price-takers in the international market. On
average, export prices rise by the full depreciation of the rand
and the increase in the foreign price.
Various implications arise from these results.
• Firstly, export growth is not predominantly dependent on the
economic prosperity of South Africa’s trading partners or on their
ability to compete in the export market on the basis of price.
• Secondly, this implies that export volumes are determined by
the profitability of export supply. Factors that raise the output
price received by exporter and reduce their cost of production will
therefore enhance export performance.
• Thirdly, exchange rate depreciations on average positively
affect export performance by raising the profitability of export
supply, and not by increasing the cost competitiveness of South
African products. Exporters
34 The adjustment lag is relatively slow, suggesting that export
prices adjust to correct 10% to 17% of the disequilibrium in the
long-run equilibrium each year. However, the short-run coefficients
suggest that between 21% and over 100% of the adjustment takes
place within the same year, implying a relatively quick adjustment
period.
35 The results for beneficiated products have been omitted as
they are similar to that of natural resource based products.
26
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raise their prices by the depreciation rate and do not, on
average, lower the foreign currency price of their products in
order to capture market share.36
These implications do not imply that world demand and foreign
market
access are unimportant. While world demand does not directly
affect export performance via the demand relationship, it affects
export supply via its impact on world prices. Similarly,
preferential reductions in foreign tariffs and market access will
improve export performance if they raise the price received by
exporters.
Table 7: Long-run average export demand coefficients for natural
resource products
Using US Import Price Using Foreign output deflator
DFE GMM DFE GMM DFE GMM
1982-99 1970-99 1980-99
Export -0.262 * -0.040 * -0.250 ** -0.097 *** -0.278 ** -0.048
ns
Exchange rate 0.440 ns 0.575 ** 0.809 *** 0.964 *** 0.421 ns
0.797 ***
Foreign price 1.227 *** 0.936 *** 0.763 *** 0.838 *** 1.275 ***
0.640 **
Foreign output 1.513 * 1.060 ** 1.314 *** 1.140 *** 1.280 *
0.622 **
Adjustment term -0.129 *** -0.111 *** -0.137 *** -0.109 ***
-0.129 *** -0.129 ***
Tests (H0)
Exchange rate = 1 ** ns ns ns ** ns
Foreign price =1 ns ns ns ns ns ns
Erate=Pfor ns ns ns ns ns ns
R2 0.57 0.44 0.55
F 11.57 *** 61.78 *** 11.40 *** 99 *** 12.87 *** 773 ***
Obs 177 177 319.00 220.00
AR(1) ** *** ***
AR(2) ns ns ns
Table 8: Long-run average export demand coefficients for metal
products
Using US Import Price Using Foreign output deflator
DFE GMM DFE GMM DFE GMM
1982-99 1970-99 1980-99
Export 0.073 ns 0.055 *** -0.106 ns 0.038 ns 0.074 ns 0.029
ns
Exchange rate 1.398 *** 1.279 *** 1.096 *** 0.716 *** 0.935 ***
1.325 ***
Foreign price -0.394 ns -0.537 * 1.066 *** 1.270 *** 0.742 ns
-0.792 ns
Foreign output -0.837 ns -0.549 ns 0.551 *** 0.967 *** -0.079 ns
-0.699 *
Adjustment term -0.209 *** -0.195 *** -0.409 *** -0.219 ***
-0.231 *** -0.220 ***
Tests (H0)
Exchange rate = 1 ns ns ns ** ns ns
Foreign price =1 ** *** ns ns ns ***
Erate=Pfor ** ns ns ** ns ***
36 A further implication of this point is that a depreciation of
the currency will improve (or rather will not worsen) the trade
balance.
27
-
R2 0.62 0.50 0.58
F 11.38 *** 11.96 *** 10.81 *** 22 *** 10.74 *** 5 **
Obs 126 126 203.00 140.00
AR(1) ** ** **
AR(2) ns * **
Table 9: Long-run average export demand coefficients for
labour-intensive products
Using US Import Price Using Foreign output deflator
DFE GMM DFE GMM DFE GMM
1982-99 1970-99 1980-99
Export -0.012 ns 0.027 ns -0.158 *** -0.042 * -0.019 ns -0.004
ns
Exchange rate 1.620 *** 1.384 *** 1.163 *** 1.027 *** 1.215 ***
1.293 ***
Foreign price -0.119 ns -0.072 ns 2.771 *** 1.232 *** 1.342 *
0.205 ns
Foreign output -0.137 ns -0.323 ns 0.254 ns -0.234 ns -0.332 ns
-0.256 **
Adjustment term -0.230 ** -0.266 *** -0.587 *** -0.423 ***
-0.378 *** -0.493 ***
Tests (H0)
Exchange rate = 1 * ns * ns ns **
Foreign price =1 ns ns *** ** ns **
Erate=Pfor ns ns ns ns ns **
R2 0.58 0.48 0.61
F 7.23 *** 5.42 * 8.29 *** 22 *** 10.28 *** 3 ns
Obs 72 72 145.00 100.00
AR(1) * ** **
AR(2) ns ns ns
Export supply
The export demand analysis identifies the importance of
analysing factors that affect export supply. Some of the most
important results arising from the estimation of the reduced form
equation are presented here. Table 10 presents the results for
total manufacturing, while Table 11 presents those for the industry
sub-groupings. Only the reduced form results using the foreign
output deflator over the period 1970-99 are presented for the
sub-groups, as the results using US import prices are similar.
Table 10: Reduced form average coefficients for
manufacturing
Using US import
prices Using foreign output deflators 1982-1999 1970-1999
1980-1999 Coef. Coef. Coef.Long run Relative price 2.05 *** 2.45
*** 1.81 *** Foreign output 1.38 *** 1.20 *** 1.61 *** ULC 0.37 ns
-0.51 ns 0.11 ns
28
-
Output 0.54 ns 0.33 ns 0.57 ** Output deviation -0.77 ns -0.28
ns -0.75 ns Import penetration 0.37 ** 0.23 ns 0.55 *** Rail
capacity 2.05 * 1.95 * 2.34 *** Fuel P -1.38 *** 0.20 ns -1.17 ***
Adjustment term -0.20 *** -0.19 *** -0.25 *** Short run Relative
price 0.37 *** 0.77 *** 0.32 *** Foreign output 1.22 *** ULC -0.19
* Output 0.80 ** Import penetration 0.42 *** 0.42 *** 0.50 ***
Output deviation -0.61 *** -0.47 ** -0.68 *** Rail capacity 1.10
*** 1.78 *** 1.29 *** Other K/L -0.07 ns -0.76 ** -0.40 ns
Skill/Unskill 2.00 *** 3.02 *** 1.98 *** Sanctions -0.06 * -0.02 ns
-0.09 *** Adj R-squared 0.27 0.24 0.30 F( 41, 410) 5.05 *** 5.91
*** 6.35 *** Number of obs 452 784 560
Note: The error correction parameterization of the ARDL model is
estimated. Dummy variables are included for each sector, the MIDP
programme (1995-2002), political turmoil in 1976 and the debt
crisis (1984-86). Insignificant short run coefficients have been
eliminated
Table 11: Reduced form average coefficients for sector
groupings, 1970-99 using foreign output deflators
Beneficiated Natural resource Metal products
Labour-intensive
Coef. Coef. Coef. Coef. Long run Relative price 2.33 *** 1.51
*** 0.79 ns 4.13 *** Foreign output 1.01 ns 1.48 * -0.14 ns 2.27
*** ULC -0.18 ns -0.16 ns 0.03 ns -1.00 ns Output 0.28 ns 0.48 ns
0.62 * 0.57 ns Output deviation -0.47 ns 0.23 ns -1.27 *** -0.63
*** Import penetration 0.46 ns 0.31 ns 0.90 ns 0.98 ns Rail
capacity 0.61 ns 0.92 ns -0.79 ns 5.74 ** Fuel P 0.69 ns -0.26 ns
-0.98 ** 2.06 *** Adjustment term -0.20 *** -0.24 *** -0.36 ***
-0.36 *** Short run Relative price 0.99 *** 0.66 *** 0.24 ns 1.39
*** Foreign output 1.08 *** 1.18 *** 1.00 *** 1.20 ns ULC -0.14 ns
-0.12 ns 0.00 ns -0.63 * Output 0.70 ns 0.45 ns 1.42 ** -0.19 ns
Import penetration 0.32 *** 0.27 *** 0.79 *** 0.61 *** Output
deviation -0.54 * -0.51 ns -0.79 ** 0.08 ns Rail capacity 1.81 ***
1.59 *** 1.36 *** 1.87 ** Fuel P -0.10 ns -0.09 ns -0.01 ns 0.22 ns
Other K/L -0.82 ** -0.71 * -3.35 ns -23.62 ns Skill/unskill 2.98 **
2.58 ** 5.39 *** 10.25 * Sanctions -0.03 ns -0.04 ns 0.02 ns -0.08
ns Adj. R2 0.32 0.20 0.42 0.38 F-statistic 4.21 *** 3.38 *** 5.82
*** 4.33 *** Obs 196 308 196 140
29
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Resource endowments and comparative advantage As shown earlier,
the dependence on natural resource-based products and
the failure to diversify sufficiently into products with growing
world markets is an important source of South Africa’s poor
aggregate manufacturing export performance during the 1990s.
Resource-based products are declining as a share of world trade.
These products are also characterised by a long term decline in
prices relative to other products, although the world economy is
currently experiencing a commodity price boom. The net effect of
the existing trade structure and the inability to diversify
sufficiently is that South Africa’s share of developing economy
exports declined dramatically from 1.73% in 1988 to 1.07% in
2002.
The dominance of natural resource-based products in South
African
exports and the failure to diversify significantly during the
1990s in part reflect South Africa’s rich endowment of natural
resources, rather than a failure of policy. Wood and Mayer (2001),
for example, show that Africa’s land abundance per worker, combined
with its low level of skills, is an important determinant of its
high share of primary products in total exports. Dependence on
primary and natural resource-based exports also inhibits
diversification as it can lead to a ‘Dutch Disease’ effect (Wood
and Mayer, 2001), and results in volatile exchange rate movements
(Sachs and Warner, 1997; Collier, 2001).37 This volatility is
detrimental to manufacturing and agricultural processing, which
have a low share of factor costs in total costs and are therefore
unable to absorb the negative impact of large price decreases
(Collier, 2001). With its large natural resource endowments, South
Africa is not immune from these effects.
The entry of highly populated, low-income economies into the
world
market from the mid-1980s has also inhibited the diversification
of middle-income countries such as South Africa into
labour-intensive exports. UNCTAD (2002: 126) estimates that the
share of low-skilled labour (adults with schooling up to secondary
level) in world trade rose from 64% to 68% due to the participation
of these economies in the world market. In addition, rapid skills
accumulation in the Newly Industrialised Economies (NIEs) and the
abundance of skilled labour in developed economies has reduced
options for diversification into skill-intensive exports. South
Africa’s natural resource endowment has thus led to a squeeze in
competitiveness by both developed and NIEs and labour abundant
developing economies.
While natural resource endowments may inhibit diversification,
the
availability of skilled labour is shown to be an important
determinant of diversification into manufacturing. The econometric
estimates in Table 10 and Table 11 show a strong positive
relationship between the skill-intensity of production
37 The rents generated by primary commodities have also been
associated with poor governance and substantially higher risk of
civil war, both of which negatively affect economic growth (Sachs
and Warner, 1997)
30
-
and export performance, with coefficients for aggregate
manufacturing in excess of 2. The coefficient on the
skill-unskilled ratio for metal products, which fall in the high
technology group of products, is a high 5.4. The ability to
diversify into high technology sectors is therefore strongly
influenced by the availability of well educated labour. The
importance of skilled labour for the diversification of exports
into manufacturing within Africa has also been shown by Wood and
Mayer (2001).
Relative prices and competitiveness of manufacturing Foreign
prices, domestic prices and the exchange rate have a strong
impact on manufacturing export performance in South Africa. This
is shown by the positive and significant coefficient on the
relative price variable (the real effective exchange rate) in the
reduced form results presented in Table 10 as well as Figure 938 39
A 1% increase in the relative price of exports is estimated to
raise average manufacturing export volumes by 1.8% to 2.5% in the
long-run. The very elastic response of export volumes to changes in
relative prices found in these estimates is much larger than the
estimate (0.63) by Fallon and da Silva (1994), but is similar to
the results (1.6 to 2.8) of Edwards and Golub (2004).
Support for the vent-for-surplus hypothesis is also found, but
its
importance in determining export growth is diminishing. Declines
in output from the long-run trend are found to positively affect
aggregate manufacturing exports, at least in the short run. As
shown in Table 10, the short-run coefficients on the output
deviations variable range from -0.47 to -0.68. The vent-for-surplus
relationship helps to explain why export growth continued during
the late 1980s (see Figure 9), despite the real appreciation of the
currency. The rapid growth in exports from the early 1990s reflects
a diminished importance of vent-for-surplus exports, as well as a
once-off adjustment to the ending of sanctions and the
re-integration of South Africa into the world economy.40
38 Note that in this specification, price homogeneity is imposed
and foreign prices (P*), domestic prices (P) and the exchange rate
(e) are combined into a single relative price variable (eP*/P). In
many cases, but not all, the restriction of homogeneity could not
be rejected.
39 The use of the real effective exchange rate as a measure of
South African export competitiveness is widespread in South African
empirical analysis (IMF, 1998, Kahn, 1998, Walters and de Beer,
1999, and Golub, 2000). Despite the sensitivity of this measure to
the choice of price indices and weights, most estimates suggest
that South Africa’s competitiveness improved from the mid 1990s.
The recent appreciation of the Rand, however, has reversed much of
this gain.
40 The coefficient on the sanctions dummy (1986-92) is
significant and negative for aggregate manufacturing when the
period is restricted to the 1980s and 1990s (Table 10).
31
-
Figure 9: Real effective exchange rate and exports in aggregate
manufacturing
Aggregate manufacturing
0.00
0.05
0.10
0.15
0.20
0.2519
75
1977
1979
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
2001
Expo
rt or
ient
atio
n
020406080100120140
REE
R (e
P*/P
, 199
5=10
0)
Export orientation REER
Note: The REER is constructed using the weighted average foreign
output price deflators, the weighted average nominal exchange rate
and the domestic producer price index. Export orientation is the
value of exports in gross output valued in 1995 prices.
The highly elastic response to relative prices for aggregate
manufacturing
is also found within all sub-groups apart from metal products
(Figure 10).41 The long-run coefficient on relative prices in the
reduced form results for beneficiated and natural-resource based
products range from 1.5 to 2.3 (Table 11). Much of this appears to
be driven by the positive impact of exchange rate depreciations on
exports of these products. Labour-intensive products appear to be
particularly sensitive to relative prices in the long-run
(4.13).
In contrast, exports of metal products are not sensitive to
changes in
relative prices. This is most clearly shown in Figure 10 during
the period 1987 to 1995 when the REER fell, but export orientation
rose very strongly. Three factors may explain the insensitivity of
metal product exports to relative prices.
• Firstly, exports of these products are very sensitive to
domestic demand
conditions. The level of exports is weakly correlated with the
level of output (the long-run coefficient of 0.67 is significant at
the 10% level) and is very strongly affected by business cycles. A
decline in output below its long-run trend raises exports by 1.3%
in the long-run. The correlation with output growth
41 We also find strong evidence that the sectoral composition of
exports is determined by relative prices across sectors. This
provides support for the argument of Bell et al. (1999) that
commodity price booms raise the share of natural resource-based
products in total exports.
32
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may reflect the development of technological capabilities
required for the production of these products prior to entering the
export market.42
• Secondly, exports of metal products are strongly biased
towards the regional market and reflect advantages arising from
regional proximity and the ability to offer after sale service
(repair, operator training and engineering support) rather than
cost competitiveness in production.43 44 Thus, many of the regional
exports contain little domestic content as is reflect in the very
high import content of these products (60% for machinery and over
80% for scientific and professional and communication equipment).
Additional evidence of this effect is shown by the high positive
short run coefficient on import penetration (0.79) for metal
products in Table 11.
• Thirdly, export performance within the motor vehicle industry
during the 1990s has largely been driven by industrial policies
such as the MIDP, rather than adjustments in response to
international price movements.
Figure 10: Export performance and the Real Effective Exchange
Rate by sub-group
Beneficiated products
0.000.050.100.150.200.250.300.35
1975
1977
1979
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
2001
Expo
rt or
ient
atio
n
020406080100120140
REE
R (e
P*/P
, 199
5=10
0)
Export orientation REER
Metal products
0.00
0.05
0.10
0.15
0.20
0.25
0.30
1975
1977
1979
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
2001
Expo
rt or
ient
atio
n
020406080100120140160
REE
R (e
P*/P
, 199
5=10
0)
Export orientation REER
Natural resource-based products
0.00
0.05
0.10
0.15
0.20
0.25
1975
1977
1979
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
2001
Expo
rt or
ient
atio
n
020406080100120140
REE
R (e
P*/P
, 199
5=10
0)
Export orientation REER
Labour-intensive products
0.00
0.05
0.10
0.15
0.20
1975
1977
1979
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
2001
Expo
rt or
ient
atio
n
020406080100120140
REE
R (e
P*/P
, 199
5=10
0)
Export orientation REER
42 Goldstein and Kahn (1985:1060) note that, “secular changes in
the level of aggregate real output will be accompanied by advances
in factor supplies, infrastructure, and total factor productivity
that will lead to an increase in export supply at any given level
of export prices.”
43 Africa accounts for 31% of total exports of these products,
but only 18% of total SA manufacturing exports.
44 After sale service has become an important competitive tool
involving repair, operator training, and engineering support
(Gourevitch et al., 2000).
33
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Firm
