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East Asia and Eastern EuropeTrade Linkages and Issues
Jocelyn Horne
247
A U S T R A L I A – J A P A N R E S E A R C H C E N T R E
PACIFIC ECONOMIC PAPERS
NO. 261, NOVEMBER 1996
East Asia and Eastern EuropeTrade Linkages and Issues
Jocelyn HorneMacquarie University
A U S T R A L I A – J A P A N R E S E A R C H C E N T R E
PACIFIC ECONOMIC PAPER NO. 261
NOVEMBER 1996
ii
© Australia–Japan Research Centre 1996
This work is copyright. Apart from those uses which may be permitted under the
Copyright Act 1968 as amended, no part may be reproduced by any process
without written permission.
Pacific Economic Papers are published under the direction of the Research
Committee of the Australia–Japan Research Centre. The opinions expressed are
those of the author(s) and do not necessarily reflect the views of the Centre.
The Australia–Japan Research Centre is part of the Economics Division of the
Research School of Pacific and Asian Studies, The Australian National Univer-
sity, Canberra.
ISSN 0728 8409
ISBN 0 86413 201 8
Australia–Japan Research Centre
Research School of Pacific and Asian Studies
The Australian National University
Canberra ACT 0200
Telephone: (61 6) 249 3780
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Edited by Gary Anson
Typeset by Minni Reis
iii
CONTENTS
List of tables and figures ................................................................................... iv
Introduction ........................................................................................................ 1
Background and issues ........................................................................................ 3
Stylised facts ..................................................................................................... 10
Concluding remarks .......................................................................................... 21
Appendix ........................................................................................................... 23
Notes ................................................................................................................. 25
References ......................................................................................................... 27
iv
TABLES
FIGURES
Figure 1 Relative endowments of natural resources, labour and capital,various economies, 1991 .................................................................. 9
Table 1 Summary measure of merchandise trade .......................................... 5
Table 2a Merchandise trade shares, 1979–96 ............................................... 12
Table 2b Northeast Asia trade matrices, 1985–91 ........................................ 15
Table 3 Trade intensity, complementarity and bias ..................................... 16
Table 4 Factor composition of total trade ................................................... 18
Table 5 Export specialisation indexes ......................................................... 19
Table 6 Revealed comparative advantage ................................................... 21
Table A1 Krause factor intensity classification .............................................. 23
Table A2 Murrell classification system .......................................................... 24
Table A3 Classification of transition economies by incomeand region, 1994 ............................................................................ 24
1
EAST ASIA AND EASTERN EUROPE
TRADE LINKAGES AND ISSUES
Economic integration of Eastern Europe and the former Soviet Union (FSU) has attracted
considerable interest in recent literature.1 The main focus has been on the welfare implications
of an enlarged European Union with little attention paid to evolving trade linkages between
Eastern Europe and the Asia Pacific region.2 The two issues, however, cannot be considered in
isolation given the increased importance of the Asia Pacific region in the world economy and
changing areas of comparative advantage as economies in these regions undergo economic
development and reform.
This study focuses on one aspect of these linkages or trade relations between ‘core’
(advanced industrialised) and ‘periphery’ (developing) countries in the trade blocs. In particu-
lar, it attempts to identify the main changes in merchandise trade pattern and structure between
Eastern Europe, the FSU and East Asia in the aftermath of systemic reforms in the former group
of countries. In examining these linkages, the scope of the study is restricted to merchandise
trade and an aggregated treatment of the FSU. The central themes that emerge need to be
interpreted within this context.
Drysdale (1991), writing prior to the breakup of the Soviet Union, stated that ‘The Soviet
economy is not yet, nor for many years can it be, central to Asia Pacific interests’. Despite the
major upheavals that have since taken place, this statement remains true. The share of East
Introduction
This paper examines the pattern and structure of trade between Eastern Europe,the former Soviet Union and East Asia with a particular focus on the post-1991reform period. The unexpected expansion in trade between Eastern Europe andEast Asia has been accompanied by increased trade complementarity between EastAsian and Eastern European transition economies. This trend is shown to reflecttwo concurrent developments; an intensification of pre-existing comparativeadvantage by Eastern Europe and changing comparative advantage by East Asianeconomies.
2
Asian trade by Eastern Europe and the FSU remains below 1 per cent. Rapid growth has
occurred, however, in East Asia’s share of Eastern Europe and FSU trade; that share has risen
from 8.4 per cent in 1980 to 16.6 per cent in 1995. Nevertheless, the dramatic collapse in intra-
trade among former members of the Council for Mutual Economic Assistance (CMEA) has
been mirrored largely in increased trade flows between Eastern and Western Europe.
The motivation for the present analysis requires further justification. It rests upon three
main grounds: the strategic importance of the FSU, the welfare effects of an enlarged European
Union, and the likelihood of increased global trade shares of Eastern Europe and the FSU.
First, the strategic influence of the Russian Federation in the world means that all
countries have a stake in successful reform in this region. This factor, combined with the
growing Asia Pacific share of global trade, means that trade and financial linkages bind the
sustainability of growth of the regions to each other. In addition, just as it is argued that Eastern
and Western Europe are ‘natural trading partners’ because of geographical proximity, so the
Central Asian republics are natural partners in trade to Northeast Asian economies, including
South Korea, Japan and China. Trade linkages may be expected to strengthen within regions
such as the Tumen River area.
A second motivation for the study arises from the question of Eastern Europe’s
comparative advantage and the welfare impact of an enlarged European Union. Resolution of
the question of comparative advantage in the transition and post-transition periods has a critical
bearing on predicting the distribution of the gains from inter-industry trade; ceteris paribus,
the greater the degree of complementarity in trade structures between Eastern and Western
Europe and East Asia, the greater the gains to member countries and the smaller the losses to
non-members. Conversely, insofar as East European economies compete in similar export
markets to Asian trading partners, the greater the potential trade diversion losses to the latter
that may arise from EU preferences to East European partners.
As confirmed in the present study, a distinctive pattern is apparent in the trade structure
of NIEs, with a shift in export specialisation away from unskilled labour and traditional
manufacturing towards human capital and high technology exports. This trade pattern is
consistent with recent theories of dynamic comparative advantage derived from models of
technology-led endogenous growth (see Grossman and Helpman 1991, 1992). In the transition
period, European central planning economies (CPEs) share certain similarities in economic
structure with developing economies, including trade and financial repression, soft budget
constraints and large macro imbalances. But there are also fundamental differences, such as a
3
higher share of industrial output and a more educated workforce. The question of their
comparative advantage is by no means clearcut in terms of such analogies.
Finally, as successful reform gathers momentum in Eastern Europe, the importance of this
region in the global economy should increase. Thus far, only a small group of countries (the
Czech Republic, Hungary, Poland and the Baltic states) have achieved positive output growth,
with significant shares of output originating in the private sector and private capital flows
exceeding 10 per cent of export earnings. Growth prospects for the remaining countries are
contingent upon their continued reliance on external assistance, making any projections highly
uncertain. Notwithstanding these uncertainties, trade interactions will be further strengthened
as the world economy becomes more integrated with successful implementation of the Uruguay
Round.
The remainder of the paper is organised as follows. The next section discusses the
background to recent trade reform initiatives in Eastern Europe and the associated issues. The
third section presents an analysis of the structure and composition of trade flows between East
Asia and Eastern Europe/FSU within a broad regional framework that includes the main trade
blocs — the European Union and APEC, as well as East Asia, North America and Australasia.
The final section brings together the main findings of the study and suggestions for further
research.
Background and issues
Trade reform issues in Eastern Europe and the FSU have already undergone a shift in emphasis
away from the earlier focus on rapid trade liberalisation towards present concerns with market
access, as reflected in the proliferation of regional trade agreements. A key question underpin-
ning the economic rationale for trade strategy is the likely effect of the opening up of these
economies on their trade volume, direction and structure. This question has been addressed in
recent literature. See, for example, CEPR (1990), Collins and Rodrick (1991), Murrell (1990),
Neven and Roller (1991), Wang and Winters (1993) and the Economic Commission for Europe
(1993).
As for trade volume, it is predicted that this will expand in the post-reform period due to
the widespread distortions under central planning, resulting from bureaucratic coordination of
production and trade as well as the asymmetric treatment of trade between CMEA and non-
CMEA trading partners.3 The dismantling of the CMEA in January 1991 was accompanied by
a comprehensive set of trade liberalisation measures (see Kenen 1991; and IMF 1992).
4
Predictions of the magnitude of the expected expansion in trade vary according to the
methodology employed and the definition of the post-reform period (transition or post-
transition). Collins and Rodrick (1991) project a rise in Eastern Europe’s share of world trade
from 3.3 per cent in 1989 to 4.9 per cent (assuming full trade liberalisation and no growth catch-
up to industrialised economies) and to 12 per cent (assuming full catch-up). Comparable long-
run rises in trade volume are projected in Wang and Winters (1993) based upon a gravity trade
model.
Summary data given in Table 1 show that these predictions have as yet failed to
materialise. On the contrary, Eastern Europe’s share of world trade has fallen to below 2 per
cent.
The unexpectedly large fall in output in the first few years of reform, itself related to the
CMEA dismantling (principally the negative terms-of-trade shock for non-FSU members),
helps explain the above outcome, given the above assumptions. Nevertheless, this finding serves
as a warning of the sensitivity of projections about trade volume and, more generally, trade
developments to assumptions about growth and successful reform. This issue becomes even
more important in the post-1993 period in view of the diverse economic performance of former
European CPEs.
The second question concerns the predicted geographical composition of trade. The above
studies project a reversal of the trade pattern under central planning in which trade flows were
highly concentrated among CMEA members, accounting for 60–80 per cent of trade, with
dominance by the FSU. The Collins and Rodrick (1991) study adopts a 1928 trade matrix as
its base period that shows high trade flows between Eastern and Western Europe but a very
small share of FSU trade. They assume that European CPEs would have followed a similar trade
pattern to a group of comparator countries in the absence of socialism (after adjusting for factors
depressing FSU trade in the 1920s).4 Wang and Winters (1993) also project a large reorientation
of trade towards industrialised countries and especially to Western Europe based upon
estimates of the gravity model of trade.
Table 2a shows these predictions to be well supported. The share of the European Union
in East European exports (excluding the FSU) has more than doubled since 1980 while intra-
East European trade halved over the same period. There are, however, two features of these
findings that are unexpected; first, the speed of redirection of trade and, second, the unexpected
expansion of trade between Eastern Europe and East Asia.
5
Table 1 Summary measure of merchandise trade (in per cent)
1979–81 1982–84 1985–87 1988–90 1991–93 1994–95
Share of exports that is intra-regional:Intra-East Asiaa 34.8 34.4 32.9 38.4 43.1 46.3
Intra-NIESb 8.9 8.2 8.6 10.8 13.1 11.9Intra- ASEANc 18.1 22.6 18.7 18.6 20.6 23.7
Intra-EEC-12 54.8 54.0 56.4 59.8 59.8 56.8Intra-East Europe (excl. FSU)d 24.2 17.9 21.0 18.8 9.8 14.4Intra-North Americae 27.9 32.7 37.3 34.3 33.9 36.9Intra- Australasiaf 8.6 9.1 8.9 9.2 10.3 12.1Intra-APECg 58.0 62.5 67.5 68.4 69.2 72.3Share of world exports:East Asia 14.6 18.1 20.2 21.5 24.3 25.4
Japan 6.9 8.4 9.7 9.0 9.2 9.0NIES 4.1 5.5 6.6 8.1 9.5 9.5ASEAN 3.6 4.2 3.5 4.1 5.2 6.3China 1.0 1.3 1.6 1.8 2.3 3.0
EEC-12 35.0 33.7 37.4 38.7 37.8 36.0Eastern Europe (excl. FSU) 3.2 2.9 3.2 2.3 1.2 1.5FSU 2.3 2.5 2.3 1.7 na naNorth America 15.1 16.0 15.1 15.6 15.8 15.8Australasia 1.5 1.6 1.5 1.5 1.5 1.4APEC 32.2 37.1 37.9 39.6 42.7 44.4Export share of GDP:East Asia 17.0 18.0 16.3 16.5 17.0 –
Japan 11.8 12.9 11.0 9.5 9.1 –NIES 51.3 53.1 57.1 54.5 51.6 –ASEAN 37.7 31.6 31.5 41.6 44.6 –China 9.5 10.6 12.0 16.7 20.3 –
EEC-12 22.2 23.7 23.6 22.8 20.8 –Eastern Europe (excl. FSU) 125.9 38.3 10.2 9.2 11.1 –North America 9.2 7.7 7.0 8.4 8.9Australasia 14.7 13.8 14.4 14.0 15.6APEC 11.8 11.3 10.6 11.8 12.5Trade intensity index:East Asia 2.1 1.8 1.9 1.8 1.8 1.4
NIES 1.9 1.5 1.5 1.4 1.4 1.0ASEAN 5.4 5.3 5.9 4.5 3.7 2.2
EEC-12 1.5 1.6 1.6 1.6 1.6 1.1Eastern Europe (excl. FSU) 7.1 6.5 6.7 8.2 6.5 6.8North America 1.7 1.7 1.7 1.8 1.9 1.3Australasia 6.2 5.9 6.1 6.1 7.5 5.5APEC 1.7 1.7 1.7 1.7 1.6 1.4
Notes: a Country aggregate ‘East Asia’ includes Japan, Korea, China, Taiwan, Hong Kong, ASEAN (as definedin ‘c’), Laos and Cambodia.
b Country aggregate ‘NIES’ includes Korea, Taiwan, Hong Kong and Singapore.c Country aggregate ‘ASEAN’ includes Thailand, Malaysia, the Philippines, Indonesia, Brunei, Vietnam
and Singapore.d Eastern Europe excludes FSU and includes Albania, the German Democratic Republic (before 1990),
Romania, the Czech Republic, Slovakia, Bulgaria, Poland and Hungary.
6
The speed of change is surprising given that both methodologies assume full functioning
of markets and institutions as well as income catch-up with industrialised countries. One
explanation lies in the smaller-than-expected import surge in Eastern Europe in response to
price liberalisation and elimination of the monetary overhang. Undervalued (in other words,
depreciated) real exchange rates is one factor behind increased exports, at least for Poland,
Hungary and the Czech Republic. But, in any event, both approaches assume that trade takes
place between similar industrialised economies, in which case the gains for trade derive
primarily from intra-industry rather than inter-industry trade. Other evidence (see, for example,
the Economic Commission for Europe [1993]) shows intra-East European industry trade to be
low and to have fallen in the post-reform period. The point here is that neither of the above
methodologies offers a satisfactory explanation of the observed transitional rather than long-
run pattern of trade.
A second feature of observed post-reform trade patterns is the unexpected growth in trade
between Eastern Europe and East Asia. This development is not predicted in the above studies
because of the low share of East Asia in world trade in 1928 and the gravity model based upon
the hypothesis of ‘natural trading partners’, as determined by income, location and country size.
Again, it is not difficult to offer ad hoc explanations for the observed trade pattern, especially
based upon a ‘stages-of-development’ approach in which middle and lower-income countries
specialise in unskilled labour exports in return for imports of high-technology goods from more
advanced economies. To explain this phenomenon, we need to turn to the next issue — that of
comparative advantage of Eastern Europe.
The issue of East Europe’s future comparative advantage has attracted considerable
debate. This debate has arisen largely because of difficulties in drawing inferences about
comparative advantage from pre-reform data on factor endowments and trade patterns as well
as different assumptions about Eastern Europe’s growth prospects after reform. Two main
e Country aggregate ‘North America’ includes the United States and Canada.f Country aggregate ‘ Australasia’ includes Australia, New Zealand and PNG.g Country aggregate ‘APEC’ includes Australia, Brunei, Canada, Chile, China, Hong Kong, Indonesia,
Japan, Korea, Malaysia, Mexico, New Zealand, Papua New Guinea, the Philippines, Singapore, Taiwan,Thailand and the United States.‘Export share of GDP’ is calculated by summing exports(US$).
na—Not available.
Sources: IMF (1996); World Bank (1995); International Economic Databank, Australian National University.
7
approaches have been adopted; the first uses information on factor endowments to make
inferences about comparative advantage using the Heckscher–Ohlin theory of trade. The second
draws inferences about comparative advantage from actual trade patterns. The specific question
addressed here is whether a similar picture emerges from these different approaches.
Misallocation of resources under socialism means that inferences drawn from raw data
may be quite misleading. One way of addressing this problem is to examine historical trends
before socialism. For example, the CEPR (1990) study shows that in the pre-1914 period,
Russia specialised in exports of agricultural products and raw materials, a finding that is
consistent with its relative abundance in natural resources. It is also observed that Eastern
Europe (and especially the former Czechoslovakia) prior to the Second World War specialised
in labour-intensive goods and thereby resembled Japan in the 1950s and 1960s. However, it is
difficult to derive any clearcut inferences about post-reform trade patterns based on historical
trends given the different stage of development of the Soviet economy and Eastern Europe after
many decades of industrialisation under socialism.
Some support for the view that pre-socialist data may provide a useful insight into post-
reform trade patterns comes from a different source. While measured capital-to-labour ratios
and investment in terms of GDP in Eastern Europe and the FSU are very high, estimates by
Borensztein and Montiel (1992) show unproductive investment to be 50–75 per cent of total
investment in the former Czechoslovakia, Hungary and Poland. Once capital to labour ratios
are adjusted for ‘excess investment’, the ratios are very low. As a consequence, Eastern Europe
matches the characteristics of the earlier historical data, resembling middle-income developing
economies with low wages and an abundant labour force. The scarcity of capital and high
marginal productivity of capital at the start of recent reform also implies that fairly low
investment ratios may be sufficient to achieve growth convergence.5
The need to correct resource endowment data for factor quality is also of relevance when
using data on human capital skills. A broad range of human capital indicators (education
expenditure in terms of GDP, school enrolment ratios and R & D ratios) are presented in the
CEPR study cited above to show comparability between Eastern and Western Europe. On the
basis of this evidence, the authors conclude ‘these factor abundances suggest that among
manufactures, it is high-technology goods rather than labour-intensive goods that represent
Eastern Europe’s area of comparative advantage’ (CEPR 1990, p. 13). This conclusion is at
variance with other research using factor endowments and measures of revealed comparative
advantage, as discussed below.
8
A simplified treatment of the problem of measuring factor endowments is suggested in an
application by Anderson (1991) of the Leamer triangle examining comparative advantage of
groups of countries, including Eastern Europe.6 A three-factor model — natural resources,
unskilled labour and capital (human, physical and knowledge) — is assumed in Figure 1, which
is reproduced from Anderson.
In Figure 1, per capita income and per capita agricultural land are used as proxies for
capital-to-labour and resources-to-labour ratios, respectively. While measures of income per
capita in CPEs vary greatly, Anderson’s estimates (Eastern Europe’s per worker capital
endowment is 60 per cent of the world average) are broadly consistent with those of Borensztein
and Montiel (1992).
In the Leamer diagram, Eastern Europe (excluding the FSU) is located in the WLB zone
— that is, below the global average per worker endowments of capital — with a resulting
comparative disadvantage in skill and knowledge-intensive products. In contrast, West Euro-
pean economies lie in WCB, with a comparative advantage in capital-intensive goods but a
comparative disadvantage in primary products and unskilled labour-intensive goods.
Economic growth as modelled through an increase in the supply of capital relative to that
of other factors shifts an economy’s endowment point towards C and away from NL. As a result,
countries in WLB (as well as the FSU in WAN) shift towards WBC and in the process
strengthen their initial comparative advantage in labour-intensive products (Eastern Europe)
and resource-intensive products (FSU). As discussed more fully in Anderson (1991), the
direction and magnitude of predicted change in comparative advantage in response to growth
depend critically upon assumptions about labour mobility, sufficient capital inflows to finance
investment and enterprise restructuring in reforming countries. For example, large-scale labour
emigration from Eastern Europe shifts the endowment point towards the N corner, thereby
strengthening its comparative advantage in primary products.7
Alternative approaches to identifying comparative advantage in Eastern Europe using
measures of revealed comparative advantage (see Murrell 1990; and Collins and Rodrick 1991)
reach similar conclusions in regard to the pre-reform period. For example, Collins and Rodrick
show that while Eastern European economies were net importers of manufactures taken as a
whole, they are similar to middle-income developing countries with a comparative advantage
in standardised (low-skill items) in basic and miscellaneous manufactures. Based upon 1989
trade patterns, Collins and Rodrick (1991) conclude that ‘… Eastern Europe is likely to make
its entrance into the world economy, at least where manufactures are concerned, mainly as a
9
low-cost producer of relatively standardized commodities rather than as a producer of human
capital-intensive goods’ (p. 61).
Analysis of East–West trade flows by Murrell (1990) using measures of revealed
comparative advantage also shows that the comparative advantage of Eastern Europe under
central planning lies in so-called ‘Heckscher–Ohlin goods’ (that is, in goods characterised by
(Natural resources) N
0.1
1.25 ANZ1.5 SSA SU D
A 1.0 LA
W 3.2 CH NA 10 OEA EET SA EC
32 EF JA
(Labour time) L NIE C (Capital) 0.1 0.25 0.5 1.0 3.2 10 32
B
Notes: The distance along NL from N measures population per unit of agricultural land as a ratio of the worldaverage (1.07 people per hectare). The distance along LC from L measures per capita income as a ratioof the world average (US$3,400). Both scales are in logs. Along any ray from C to NL the population perunit of agricultural land is constant, and similarly for rays from the other two corners of the triangle. Wis the world’s endowment point. Countries are represented as follows: ANZ— Australia and NewZealand; CH — China; EC — the twelve EC member countries; EET — Eastern Europe; JA — Japan;LA — Latin America; NA — the United States and Canada; NIE — the Asian NIEs; OEA — other EastAsian market economies; SA — South Asia; SSA — Sub-Saharan Africa; SU — the Soviet Union. Theestimates used for per capita income for Eastern Europe and the Soviet Union are US$1,800 andUS$1,600 respectively, based on World Bank and other estimates reported in CEPR (1990, p. 33).
Source: Anderson (1991).
Figure 1 Relative endowments of natural resources, labour and capital, variouseconomies, 1991
10
standard manufacturing) while that of the FSU lies in ‘Ricardo goods’ (namely, in resource-
intensive goods).
Stylised facts
Methodology
The methodology adopted in this paper is ‘stylised fact’ analysis. The purpose is to identify
issues for research — that is, what needs to be explained.
Presentation of the stylised facts is intended to answer the following questions:
• What is the strength of trade linkages between East Asia, Eastern Europe and the
former Soviet Union?
• What is the structure of trade interactions among the above regions and how has
this structure altered over the past decade, especially since the major economic
reforms introduced by European CPEs in 1991?
• What is the comparative advantage of Eastern Europe based upon measures of export
specialisation (or revealed comparative advantage)?
Presentation of stylised facts is a highly selective process and this is particularly the case
in analysing trade data on Eastern Europe. There are three main problems: non-comparability
of trade data of former European CPEs and Western economies, classification of commodities,
and definition of region and country. The first issue has already been noted and arises from three
sources — distortions under socialism, non-convertibility of trade within the former CMEA,
and differences between UN and CMEA trade data classification.
To minimise data problems, the focus of the analysis is on trade flows between Eastern
Europe, the FSU and other trade regions rather than within Eastern Europe. A further solution
to the above problem is to use mirror statistics (see, for example, Murrell 1990). Exports
(imports) of Eastern European economies are derived by adding imports (exports) of major
industrialised trading partners. Sensitivity tests using the latter show that the broad trends in
trade patterns identified in this study do not appear to be altered appreciably by the use of mirror
statistics.
A second concern is the sensitivity of summary trade measures and interpretation of trade
patterns to the method used to classify factor intensity. This paper follows Tyers and Phillips
11
(1984), who adopt Krause’s methodology whereby production processes are assumed to
involve multiple factors, each classified by its factor used most intensively and/or location of
production. Trade of 187 commodities at the 3-digit SITC level are divided into five groups
according to their intensities in five factors: agricultural resources, mineral resources, unskilled
labour, technology and human capital (see Appendix Table A1.) The sensitivity of summary
measures and, in particular, measures of export specialisation to the classification system are
examined by comparing these results with those based upon an alternative classification system
as presented in Murrell (1990),8 details of which are given in Appendix Table A2.
Third, there is the question of regional definition. There is considerable diversity in
economic structure and development within each trade region and especially within East Asia
and European CPEs. A further breakdown based upon core and periphery economies has
therefore been adopted for East Asia. Within East Asia (excluding Japan), core economies are
defined to include the four NIEs (Singapore, South Korea, Hong Kong and Taiwan) with the
remainder — ASEAN, Laos, Cambodia and China classified as periphery economies. The close
proximity of Central Asian republics in the FSU to Northeast Asia is also of interest and some
limited data on trade linkages between the FSU and Northeast Asian economies is presented.
In regard to former European CPEs, there may be greater similarities between the more
advanced Eastern European economies and the Baltic states than within either Eastern Europe
or the former Soviet Union (see Appendix Table A3). The emphasis on European CPEs may also
be misplaced given the similarity in economic structure of some Central Asian republics which
specialise in cotton exports to developing Asian economies as well as complementarity (in terms
of mineral resources) to more developed Asian economies. This type of disaggregation within
the FSU would be highly desirable but is not possible using a consistent data set based upon UN
sources.9
Direction of trade
The outstanding feature highlighted by the direction of trade data (Table 2a) is the small size
of trade flows between East Asia and Eastern Europe, especially compared with the strength
of trade linkages between Eastern and Western Europe in the aftermath of reforms. Since 1990,
the share of the European Union in Eastern Europe’s trade has doubled to over 50 per cent, rising
from almost 20 per cent in 1980. In contrast, East Asia’s share of total FSU and East European
trade has risen from 8.4 to 16.6 per cent. The sharpest recorded growth has been between East
12
Tab
le 2
aM
erch
and
ise
trad
e sh
ares
, 19
79–9
6 (t
hre
e-ye
ar a
vera
ges
, ex
cep
t 19
94–9
5) (
in p
er c
ent)
Exp
ort s
hare
Eas
t Asi
aJa
pan
NIE
SA
SE
AN
Chi
naE
EC
-12
Eas
tern
Eur
ope
FS
UN
orth
Aus
tral
asia
AP
EC
(exc
l. F
SU
)A
mer
ica
Eas
t Asi
a19
79–8
134
.811
.014
.311
.32.
313
.80.
81.
424
.13.
062
.619
82–8
434
.49.
914
.112
.12.
711
.80.
51.
328
.83.
166
.719
85–8
732
.98.
314
.88.
44.
813
.20.
61.
134
.92.
670
.819
88–9
038
.48.
818
.410
.34.
815
.50.
40.
929
.82.
571
.219
91–9
343
.18.
020
.712
.56.
515
.40.
30.
725
.52.
071
.119
94–9
546
.38.
519
.615
.57.
814
.00.
40.
524
.92.
173
.5Ja
pan
1979
–81
25.6
–
14.9
9.9
3.6
13.5
0.6
2.2
27.1
3.4
57.3
1982
–84
24.1
–
13.8
9.8
3.4
12.7
0.4
2.1
32.7
3.8
61.2
1985
–87
23.9
–
14.7
6.4
5.1
14.4
0.3
1.4
40.2
3.2
67.9
1988
–90
28.6
–
19.3
9.7
2.9
18.0
0.3
1.1
35.6
3.1
68.1
1991
–93
34.0
–
21.7
12.7
3.7
17.2
0.2
0.5
31.0
2.5
68.6
1994
–95
38.7
–
21.8
17.1
5.0
15.2
0.2
0.3
31.2
2.5
73.3
NIE
S19
79–8
132
.611
.28.
912
.81.
815
.60.
20.
327
.53.
463
.919
82–8
433
.29.
78.
214
.03.
311
.70.
10.
333
.23.
069
.419
85–8
732
.810
.68.
69.
06.
712
.40.
10.
238
.72.
574
.119
88–9
039
.511
.910
.810
.28.
914
.30.
20.
131
.22.
373
.419
91–9
344
.29.
313
.112
.012
.214
.40.
30.
525
.21.
971
.419
94–9
548
.58.
911
.915
.215
.213
.00.
30.
622
.71.
972
.9A
SE
AN
1979
–81
54.4
28.5
14.9
18.1
0.9
12.3
0.5
1.3
16.8
3.0
74.1
1982
–84
56.9
26.0
16.5
22.6
0.9
9.9
0.3
1.0
17.2
2.9
77.0
1985
–87
51.9
22.6
16.1
18.7
1.8
12.3
0.4
0.8
20.9
2.6
75.3
1988
–90
50.1
18.8
17.5
18.6
2.2
14.2
0.4
0.8
21.0
2.5
73.6
1991
–93
51.1
16.6
20.2
20.6
2.1
15.0
0.5
0.7
19.9
2.3
72.9
1994
–95
52.4
14.7
19.3
23.7
2.7
14.4
0.5
0.5
20.6
2.2
74.2
EE
C-1
219
79–8
13.
51.
01.
21.
20.
454
.81.
91.
56.
80.
811
.819
82–8
43.
91.
11.
41.
40.
454
.01.
31.
68.
90.
914
.219
85–8
74.
61.
41.
61.
10.
856
.41.
31.
310
.40.
916
.319
88–9
05.
62.
02.
21.
30.
659
.81.
31.
28.
50.
815
.319
91–9
36.
41.
92.
61.
80.
759
.81.
91.
27.
60.
715
.219
94–9
57.
82.
13.
02.
41.
056
.82.
70.
68.
10.
817
.2
13
(Tab
le 2
a co
nti
nu
ed)
Eas
tern
Eu
rop
e (e
xcl.
FS
U)
1979
–81
2.9
0.5
0.2
0.6
1.6
19.5
24.2
21.8
2.2
0.1
5.1
1982
–84
2.9
0.6
0.2
0.6
1.7
21.4
17.9
22.3
2.4
0.1
5.4
1985
–87
3.2
0.5
0.2
0.5
2.1
18.1
21.0
28.0
2.3
0.1
5.4
1988
–90
4.3
0.9
0.8
0.9
2.0
25.5
18.8
24.6
2.5
0.2
7.0
1991
–93
4.7
0.9
1.4
1.1
1.4
47.4
9.4
9.4
3.8
0.2
7.5
1994
–95
3.4
0.5
1.2
1.0
0.7
51.7
––
3.2
0.2
6.5
FSU
1979
–81
5.5
4.6
0.2
0.2
0.5
33.1
33.5
–1.
60.
07.
219
82–8
44.
83.
40.
20.
31.
039
.428
.4 –
1.0
0.1
5.8
1985
–87
6.9
3.9
0.2
0.2
2.6
30.2
41.6
–1.
10.
08.
019
88–9
010
.75.
80.
50.
73.
934
.032
.4 –
1.9
0.1
12.8
1991
–93
15.6
5.2
2.8
1.7
6.4
38.6
14.6
–3.
30.
018
.619
94–9
513
.23.
72.
72.
25.
119
.7–
–6.
20.
019
.1N
ort
h A
mer
ica
1979
–81
17.1
8.5
5.2
3.1
1.3
22.1
0.9
1.3
27.9
2.0
52.7
1982
–84
18.7
9.0
6.0
3.6
1.3
19.5
0.4
1.4
32.7
2.0
57.5
1985
–87
19.1
9.5
6.4
2.9
1.4
18.7
0.3
0.8
37.3
2.2
63.2
1988
–90
22.5
10.6
8.5
3.5
1.4
20.0
0.2
0.9
34.3
2.1
64.4
1991
–93
22.6
9.4
9.0
4.4
1.6
19.1
0.3
0.9
33.9
1.8
65.4
1994
–95
22.9
9.3
8.7
5.2
1.7
16.7
0.3
0.5
36.9
1.8
68.9
Au
stra
lasi
a19
79–8
141
.525
.07.
87.
43.
316
.40.
93.
813
.78.
663
.919
82–8
442
.124
.210
.47.
72.
816
.10.
82.
812
.39.
163
.819
85–8
743
.324
.411
.06.
23.
816
.80.
72.
312
.98.
965
.319
88–9
047
.524
.814
.78.
72.
514
.80.
71.
612
.59.
269
.619
91–9
352
.323
.718
.411
.93.
012
.30.
20.
511
.010
.373
.919
94–9
553
.622
.717
.613
.74.
111
.60.
20.
49.
112
.175
.0A
PE
C19
79–8
126
.010
.39.
37.
01.
918
.00.
81.
526
.32.
758
.019
82–8
427
.010
.010
.07.
82.
015
.70.
51.
430
.82.
862
.519
85–8
727
.19.
410
.95.
93.
315
.80.
41.
035
.72.
667
.519
88–9
031
.810
.114
.07.
33.
317
.30.
40.
931
.62.
568
.419
91–9
334
.98.
91
5.8
9.1
4.4
16.6
0.3
0.7
29.2
2.2
69.2
1994
–95
36.5
8.9
14.9
11.1
5.2
14.6
0.3
0.5
30.9
2.2
72.3
Sou
rces
:IIM
F (1
996)
; Int
erna
tiona
l Eco
nom
ic D
atab
ank,
Aus
tral
ian
Nat
iona
l Uni
vers
ity.
14
Asia (excluding Japan) and the FSU, from less than 1 to 9.5 per cent, while the share of East
Asia in East European trade has remained at between 2 to 4 per cent. The total share of Eastern
Europe and FSU in exports of the major regional trading blocs has remained very small at less
than 1 per cent (APEC and East Asia) and 3 per cent for the European Union. Decomposition
of trade flows between developed and developing East Asia economies reveals some distinct
patterns. First, within East Asia (excluding Japan) there has been a sharp reduction in trade
among NIEs. At the same time, trade has strengthened between core and periphery East Asian
countries and between core East Asian and Eastern European/FSU economies. The fastest
growth has been the increased NIE share of FSU trade, rising from 0.2 to 0.5 per cent (1980–
90) to 2.7 per cent in 1995. Somewhat slower growth (from 0.7–2.2 per cent) is observed for
ASEAN shares of FSU exports. A similar pattern is observed for NIE and ASEAN shares of
East European exports.
The above regional trade data do not capture the trade linkages associated with the
geographical proximity of the FSU with Northeast Asia, specifically the Tumen River area.10
Northeast Asia is defined to include South and North Korea, Japan, China, the FSU and
Mongolia. Even within a relatively short period (1985–91), some changes have already
occurred, reflecting FSU economic reforms and the increased importance of South Korea (Table
2b).11 Trade within this region remains dominated by Japan. However, trade flows have shifted
from Japan–China (45.8 per cent) and Japan–South Korea (28.4 per cent) in 1985 to dominance
by Japan–South Korea (47.0 per cent) in 1991. Some redirection of FSU trade away from former
trading partners, Mongolia and North Korea, towards South Korea (from zero in 1985 to 6.6
per cent in 1991) is also observed and is consistent with the strengthening of trade linkages
between the FSU and NIEs shown in Table 2a.
Trade intensity, complementarity and bias
Measures of trade intensity and their decomposition into trade complementarity and bias
provide further insight into the structure of trade relationships between Eastern Europe and East
Asia. The trade intensity index measures the share of trade of a given region with another region
expressed as a proportion of that region’s share of world trade. This measure has been further
decomposed into the joint product of two indexes: trade complementarity (a measure of the
degree of similarity between the commodity composition of one region’s exports and imports
of its trading partners) and trade bias (a measure of the relative strength of trade resistances).12
15
Table 2b Northeast Asia trade matrices, 1985–91
Importer South Korea North Korea Japan China FSU Mongolia
1985 trade matrix (in per cent of total regional trade)
ExporterSouth Korea 0 11.0 0 0 0North Korea 0 0.2 0.5 1.2 naJapan 17.4 0.5 30.8 6.9 –China 0.9 0.5 15.0 2.7 –FSU 0 1.9 3.2 2.2 3.5Mongolia 0 na – – 1.2
1990 trade matrix (in per cent of total regional trade)
ExporterSouth Korea 19.5 0.9 0.8 –North Korea – 0.5 0.2 1.5 naJapan 26.8 0.3 9.4 4.0 –China 3.9 0.6 13.9 9.4 3.4 –FSU 0.5 2.3 4.8 2.9 2.6Mongolia – na – – 1.1 2.6
1991 trade matrix (in per cent of total regional trade)
ExporterSouth Korea – 18.2 1.6 1.0 –North Korea 0.1 0.4 0.1 0.3 naJapan 29.4 0.3 12.6 3.1 –China 5.1 0.7 15.1 2.6 –FSU 0.7 0.3 4.5 2.8 0.4Mongolia – na – – 0.3
Note: na: Not available.
Source: Pomfret (1996, Table 10.1, p. 132).
Movement in trade intensity indexes (i in Table 3) are broadly similar to trends in bilateral
trade discussed above.13 Trade intensity indexes for East Asia have risen over the past fifteen
years while those for Eastern Europe have fallen sharply since 1991. Despite the high level of
aggregation across countries and commodities, a pattern of changing regional trade structure is
identifiable, especially if the NIEs are shown separately.
The trend over the entire sample period has been towards greater regional complementarity
between Eastern Europe and core East Asian economies, with an acceleration after 1991. For
example, the trade complementarity index (Table 3) for trade flows between the NIEs and
Eastern Europe (based upon exports by NIEs to Eastern Europe) doubled from 0.5 to 1.0 from
16
Tab
le 3
Tra
de
inte
nsi
ty,
com
ple
men
tari
ty a
nd
bia
s
Exp
orts
from
:
Exp
orts
to:
AP
EC
Eas
tern
Eur
ope
FS
UE
ast A
sia
NIE
sE
urop
ean
(exc
l. F
SU
)(e
xcl.
Jap
an)
Uni
on
ic
bi
cb
ic
bi
cb
ic
bi
cb
AP
EC
1980
1.2
1.1
1.1
0.2
0.7
0.2
0.3
1.0
0.4
1.5
1.2
1.3
1.4
1.2
1.2
0.3
1.0
0.3
1985
1.0
1.2
0.8
0.2
0.8
0.1
0.3
1.1
0.3
1.0
1.1
0.9
1.1
1.1
0.9
0.3
1.0
0.3
1990
1.0
1.1
0.9
0.1
0.9
0.1
0.3
1.0
0.3
1.1
1.1
1.0
1.2
1.2
1.0
0.3
1.0
0.3
1994
0.8
1.1
0.7
0.1
1.0
0.1
0.3
0.9
0.3
0.9
1.2
0.7
1.0
1.2
0.8
0.2
1.0
0.2
Eas
tern
Eur
ope
1980
0.1
0.5
0.2
6.6
0.7
10.0
10.5
0.9
11.4
0.2
0.6
0.4
–0.
40.
10.
50.
60.
8(e
xcl.
FS
U)
1985
0.1
0.9
0.2
9.1
1.3
7.1
10.8
1.4
7.8
0.2
1.0
0.2
–0.
7–
0.6
0.9
0.6
1990
0.1
0.9
0.2
12.7
1.4
9.2
16.5
1.6
10.2
0.2
1.0
0.2
0.1
0.9
0.1
0.7
1.0
0.7
1994
0.2
0.9
0.2
4.7
1.0
4.8
7.0
1.1
6.4
0.3
1.0
0.3
0.2
1.0
0.2
1.6
1.0
1.5
FS
U19
800.
80.
80.
211
.30.
715
.4–
––
–0.
5–
–0.
40.
10.
80.
81.
019
851.
10.
80.
112
.01.
210
.3–
––
–0.
20.
2–
0.1
0.3
1.1
1.0
1.1
1990
1.0
1.0
0.3
16.5
1.9
8.6
––
–0.
10.
60.
20.
10.
50.
11.
00.
91.
119
941.
40.
90.
48.
61.
08.
9–
––
0.3
0.8
0.4
0.4
0.8
0.4
1.4
0.9
1.6
Eas
t Asi
a19
802.
01.
11.
80.
20.
40.
60.
20.
60.
42.
21.
22.
42.
51.
22.
00.
41.
00.
4(e
xcl.
Japa
n)19
851.
71.
11.
50.
10.
70.
20.
20.
70.
22.
31.
21.
92.
21.
41.
60.
31.
00.
319
901.
71.
11.
50.
30.
80.
30.
10.
80.
12.
21.
21.
82.
41.
31.
80.
31.
00.
319
941.
41.
11.
20.
21.
00.
20.
30.
90.
31.
81.
21.
52.
01.
41.
50.
31.
00.
4
NIE
s19
801.
81.
01.
9–
0.3
0.1
–0.
3–
1.8
1.1
1.7
1.8
1.3
1.4
0.5
1.1
0.5
1985
1.7
1.1
1.5
–0.
5–
–0.
30.
11.
41.
41.
01.
41.
70.
80.
30.
90.
419
901.
71.
11.
60.
10.
70.
1–
0.8
–1.
71.
31.
41.
51.
41.
10.
41.
00.
419
941.
51.
11.
40.
31.
00.
30.
40.
90.
41.
71.
31.
31.
41.
41.
10.
41.
00.
4
Eur
opea
nU
nion
1980
0.2
0.9
0.2
0.3
0.7
0.5
0.4
0.9
0.4
0.2
1.0
0.2
0.2
1.0
0.2
0.9
1.2
0.8
1985
0.3
1.0
0.3
0.4
0.9
0.4
0.4
1.0
0.4
0.2
1.0
0.2
0.2
0.9
0.2
1.0
1.1
0.9
1990
0.2
1.0
0.2
0.5
0.9
0.5
0.4
1.1
0.3
0.2
1.0
0.2
0.2
1.0
0.2
0.9
1.1
0.8
1994
0.2
1.0
0.3
1.0
1.1
1.0
0.9
1.2
0.7
0.2
1.0
0.2
0.2
0.9
0.2
1.0
1.1
0.9
Sou
rces
:In
tern
atio
nal E
cono
mic
Dat
aban
k, A
ustr
alia
n N
atio
nal U
nive
rsity
; UN
trad
e da
ta, J
une
1995
.
17
1985 to 1993. Over this period, the complementarity index fell from 1.9 to 1.0 within the former
CMEA (based upon FSU exports to Eastern Europe). In contrast, trade complementarity
between Western and Eastern Europe remained stable, based upon EU exports to Eastern
Europe. Trade complementarity among the NIEs has also remained strong despite a decline in
the index since the mid-1980s.
Commodity composition of trade
Shifts in commodity composition of trade based upon the Krause factor classification scheme
(see Appendix Table A1) are shown in Table 4. In terms of overall export structure, Eastern
Europe presents the most diversified picture, especially compared to the FSU. FSU export
structure is highly specialised in mineral-intensive products whose share of total exports has
remained stable at around two-thirds. In contrast, export shares in Eastern Europe are fairly
evenly distributed among agriculture, unskilled labour, technology and human-capital intensive
goods. However, a noticeable shift has taken place away from technology-intensive goods
towards agricultural and unskilled-labour intensive products. The export structure of East Asia
lies in predominantly unskilled-labour and technology-intensive goods, with the latter showing
the most dramatic rise in export share from 11 to 28 per cent. Examination of core and periphery
economies also shows significant differences within East Asia. The NIEs specialise in
technology-intensive and human capital exports while developing Asian economies specialise
in unskilled-labour goods. APEC and EU export structures are dominated by human and
technology-intensive goods in contrast to Australasia, where agriculture and resource-intensive
goods dominate.
Smaller differences in the regional commodity composition of trade arise in regard to
imports. Import structure in all regions, including Eastern Europe and the FSU, is predominantly
technological (with a small share of unskilled-labour imports). A similar but far more
pronounced pattern is apparent for East Asia, whose share of technological imports (36 per cent)
is well above that of the other regions (ranging around one-third).
Export specialisation
Trends in export specialisation are given in Table 5. Export specialisation is defined as the share
of each commodity group in an economy’s total exports relative to that commodity group’s share
of world exports.14
18
Table 4 Factor composition of total trade (per cent)
Agriculture Human-capital Resource Technology Unskilled- Intensive intensive intensive intensive labour intensive
X M X M X M X M X M
APEC1979–81 20.1 15.6 24.7 19.9 16.5 35.4 27.8 21.4 10.8 7.71992–94 11.9 11.8 26.6 24.6 8.2 14.3 37.7 35.5 15.6 13.9ASEAN1979–81 31.8 14.1 4.9 19.7 47.9 28.2 9.9 31.8 5.5 6.31992–94 19.0 9.2 17.0 22.0 15.9 12.5 33.3 48.7 14.9 7.6China1979–81 27.0 33.0 7.7 24.5 26.0 4.1 8.2 30.1 31.1 8.41992–94 10.0 11.1 16.9 27.5 5.2 7.4 12.5 40.3 55.3 13.6East Asia1979–81 12.8 20.9 32.9 11.2 15.2 41.2 20.7 20.1 18.5 6.71992–94 7.8 14.9 27.9 19.0 5.9 16.6 36.2 36.1 22.2 13.4Eastern Europe1979–81 11.0 16.4 17.5 22.4 12.8 14.5 27.2 26.3 11.2 4.11992–94 18.1 13.6 14.1 22.0 20.7 18.4 21.2 33.2 21.9 12.1EU1979–81 14.4 18.3 26.5 18.0 14.4 30.6 32.9 22.9 11.8 10.31992–94 13.8 15.6 28.1 25.3 7.8 13.2 37.6 32.4 12.8 13.5Japan1979–81 2.5 22.9 53.1 3.1 2.6 59.2 31.1 10.3 10.8 4.41992–94 1.2 26.1 40.8 10.8 2.2 29.1 48.8 21.6 7.0 12.4NIEs1979–81 12.9 18.6 22.6 16.4 9.7 27.4 15.3 27.1 39.5 10.51992–94 6.3 10.5 23.3 20.7 5.5 12.7 40.1 39.8 24.8 16.3North America1979–81 24.4 11.6 19.8 26.4 13.1 33.9 37.9 19.8 4.9 8.31992–94 16.2 8.4 25.8 30.4 8.4 12.7 43.0 33.8 6.6 14.7Australasia1979–81 53.6 8.9 6.3 25.2 27.5 17.9 10.3 35.0 2.3 12.91992–94 42.0 8.2 9.0 29.3 34.3 8.6 11.6 41.0 3.2 12.9Rest of Asia1979–81 62.0 28.7 2.9 38.6 19.4 4.4 0.4 28.3 15.4 –1992–94 26.7 40.4 0.3 3.4 21.2 11.7 0.0 43.9 51.8 0.5Rest of the world1979–81 11.2 18.3 15.3 19.1 59.0 31.2 10.2 24.4 4.3 6.91992–94 10.2 19.0 26.0 21.0 25.7 17.3 30.4 30.4 7.8 12.3FSU1979–81 10.1 33.7 6.3 21.3 71.6 3.7 11.0 27.9 1.0 13.41992–94 12.6 29.0 21.9 19.8 67.4 3.2 9.6 36.1 11.9 12.0Western Europe1979–81 14.3 17.3 26.6 18.5 14.8 29.8 32.4 23.7 11.9 10.71992–94 13.2 14.9 28.4 25.5 8.7 13.0 37.1 32.6 12.6 13.9World1979–81 16.2 17.0 28.4 20.1 29.6 29.6 24.3 24.2 9.5 9.11992–94 13.4 13.7 25.4 24.9 13.1 13.6 34.2 34.1 13.9 13.7
Sources: International Economic Databank, Australian National University; UN trade data.
19
Tab
le 5
Exp
ort
sp
ecia
lisat
ion
in
dex
es
AP
EC
AS
EA
N C
hina
Eas
tern
Eas
tern
EE
C-1
2 J
apan
Nor
thN
IEs
Aus
tral
asia
Res
t of
FS
UW
este
rnE
urop
eA
sia
Am
eric
aW
orl
dE
urop
e
Ag
ricu
ltu
re in
ten
sive
1979
–81
1.26
1.93
1.68
0.70
0.80
0.90
0.16
1.52
0.80
3.28
0.82
0.58
0.89
1982
–84
1.11
1.69
1.51
0.77
0.67
0.92
0.13
1.45
0.60
3.06
0.85
0.46
0.90
1985
–87
0.98
1.90
1.43
0.79
0.62
0.95
0.11
1.24
0.54
3.21
0.97
0.57
0.92
1988
–90
0.98
1.76
1.07
0.89
0.62
0.95
0.10
1.26
0.51
2.95
0.95
0.77
0.92
1991
–93
0.91
1.48
0.80
1.46
0.59
1.02
0.09
1.20
0.49
2.86
0.88
0.81
0.98
1994
0.87
1.34
0.75
1.31
0.59
1.02
0.09
1.17
0.45
2.70
0.94
–0.
98H
um
an-c
apit
al in
ten
sive
1979
–81
1.23
0.24
0.38
0.88
1.63
1.31
2.65
0.99
1.11
0.31
0.73
0.29
1.32
1982
–84
1.20
0.24
0.36
0.92
1.52
1.20
2.46
1.02
1.04
0.24
0.89
0.22
1.22
1985
–87
1.15
0.31
0.36
0.84
1.39
1.09
2.10
0.98
0.98
0.20
1.05
0.31
1.11
1988
–90
1.05
0.51
0.62
0.84
1.25
1.12
1.83
0.90
1.01
0.23
0.98
0.35
1.14
1991
–93
1.05
0.62
0.67
0.87
1.14
1.11
1.70
0.97
0.93
0.31
0.99
0.24
1.12
1994
1.03
0.71
0.70
0.97
1.06
1.11
1.50
1.03
0.92
0.33
0.95
–1.
13M
iner
al-r
eso
urc
e in
ten
sive
1979
–81
0.56
1.60
0.88
0.44
0.52
0.49
0.09
0.45
0.33
0.92
1.94
2.25
0.51
1982
–84
0.64
1.75
1.01
0.63
0.55
0.55
0.08
0.48
0.38
1.34
1.80
2.92
0.57
1985
–87
0.67
1.80
1.02
0.77
0.49
0.58
0.10
0.61
0.37
1.93
1.83
3.93
0.62
1988
–90
0.67
1.54
0.67
0.83
0.47
0.57
0.13
0.65
0.40
1.99
1.99
4.32
0.63
1991
–93
0.65
1.35
0.44
1.10
0.47
0.57
0.15
0.65
0.44
2.37
2.02
5.06
0.65
1994
0.60
1.08
0.40
1.10
0.44
0.62
0.18
0.61
0.42
2.21
1.96
–0.
69T
ech
no
log
y in
ten
sive
1979
–81
1.16
0.40
0.34
1.15
0.86
1.37
1.30
1.58
0.63
0.42
0.42
0.42
1.35
1982
–84
1.09
0.50
0.29
1.36
0.87
1.29
1.29
1.48
0.67
0.37
0.54
0.31
1.27
1985
–87
1.03
0.64
0.25
1.28
0.90
1.18
1.26
1.32
0.71
0.31
0.70
0.36
1.17
1988
–90
1.06
0.78
0.30
1.18
0.99
1.13
1.39
1.26
0.89
0.20
0.78
0.37
1.12
1991
–93
1.09
0.90
0.34
0.66
1.03
1.11
1.40
1.28
1.10
0.29
0.82
0.26
1.10
1994
1.11
1.04
0.40
0.62
1.10
1.09
1.47
1.21
1.26
0.30
0.89
–1.
08U
nsk
illed
-lab
ou
r in
ten
sive
1979
–81
1.15
0.57
3.29
1.21
1.95
1.25
1.15
0.52
4.16
0.24
0.44
0.09
1.27
1982
–84
1.15
0.58
3.41
1.25
1.92
1.12
1.03
0.46
3.90
0.19
0.51
0.05
1.14
1985
–87
1.08
0.76
3.68
1.05
1.71
1.06
0.63
0.37
3.32
0.18
0.51
0.08
1.06
1988
–90
1.07
1.00
3.98
1.05
1.66
1.03
0.49
0.40
2.64
0.17
0.49
0.13
1.01
1991
–93
1.12
1.13
4.07
1.50
1.64
0.94
0.51
0.45
2.02
0.19
0.52
0.12
0.93
1994
1.11
1.00
3.98
1.50
1.57
0.91
0.51
0.49
1.63
0.21
0.56
–0.
89
Not
es:
See
App
endi
x T
able
A1
for t
he c
omm
odity
cla
ssifi
catio
n up
on w
hich
the
fact
ors
grou
ps a
re b
ased
is d
eriv
ed. T
he e
xpor
t spe
cial
isat
ion
inde
x is
def
ined
as th
e ra
tio o
f the
sha
re o
f a c
omm
odity
gro
up in
tota
l exp
orts
for a
cou
ntry
or g
roup
of c
ount
ries
to th
at c
omm
odity
gro
up’s
sha
re o
f wor
ld e
xpor
ts.
Sou
rces
:In
tern
atio
nal E
cono
mic
Dat
aban
k, A
ustr
alia
n N
atio
nal U
nive
rsity
; UN
trad
e da
ta.
20
Summarising the results in Table 5, three trends are apparent:
First, based upon export specialisation indexes, the present comparative advantage of
Eastern Europe (excluding the FSU) appears to lie in agricultural and unskilled labour-intensive
goods. The comparative advantage of the FSU lies unambiguously in mineral-intensive goods.
In the post-reform period, the comparative advantage of Eastern Europe has intensified in the
above areas and shifted away from technological goods. The comparative advantage of the FSU
has remained fairly stable.
Second, the comparative advantage of older, industrialised economies in human capital
and technological goods has been stable over the past fifteen years. The most striking change
is observed in advanced (core) East Asian economies (excluding Japan) with a shift away from
labour-intensive towards technology-intensive goods.15
Third, the export specialisation indexes for both pre-reform and post-reform data do not
lend strong support to the hypothesis that the comparative advantage of Eastern Europe lies in
human capital goods, at least in the transition period. However, specialisation indexes for
human capital goods in Eastern Europe are comparable to those of NIEs and lie well above those
of developing Asian economies including China.
It is of interest to compare the above findings with RCAs derived using the data set and
methodology adopted in Murrell (1990), which have been re-estimated and extended to include
the post-reform period. Murrell’s data set are based upon mirror statistics drawn from trade data
of a sample of 44 countries representing 80 per cent of world trade. No separate category is
included for Europe or East Asia and almost all older industrialised countries including the NIEs
are classified within the region identified as ‘market economies’. Goods are classified according
to whether they are Ricardo (natural resources) goods, Heckscher–Ohlin (goods produced using
a standard technology under constant-returns-to-scale) and product cycle (high technology)
goods.16
The results given in Table 5 match those obtained by Murrell (Table 6), which show that
the comparative advantage of Eastern Europe in the pre-reform period lies in Heckscher–Ohlin
goods. (In the Soviet Union, comparative advantage lies in Ricardo goods.) Since 1990, the
comparative advantage in Heckscher–Ohlin goods has intensified while comparative disadvan-
tage in technological goods has also increased. Comparative advantage of the FSU in resource-
intensive goods has been retained. In contrast, market economies show little evidence of any
change in RCAs.
21
Table 6 Revealed comparative advantagea
1975 1980 1985 1990 1993
Eastern Europe 6b
Ricardo goods 1.1 0.8 0.9 1.3 1.1Heckscher–Ohlin goods 1.0 1.2 1.0 1.1 1.4Product-cycle goods 0.9 0.8 0.8 0.7 0.6Eastern Europe 9c
Ricardo goods 1.4 1.3 1.5 2.1 2.0Heckscher–Ohlin goods 0.7 0.6 0.6 0.8 0.9Product-cycle goods 0.7 0.6 0.5 0.5 0.4Market economiesd
Ricardo goods 0.8 0.9 0.9 0.9 0.9Heckscher–Ohlin goods 1.1 1.1 1.1 1.0 0.9Product-cycle goods 1.1 1.1 1.1 1.1 1.1
Notes: a Based upon Murrell’s (1990) classification system. See Appendix Table A2.b Eastern Europe 6 excludes the former FSU, the former Yugoslavia and Albania.c Eastern Europe 9 includes Bulgaria, Poland, Hungary, Romania, Czechoslavakia and East Germany
(Till 1990).d Market economies include the OECD members plus South Korea, Singapore and Hong Kong.
Source: UN trade data.
Concluding remarks
The purpose of this study has been to examine changes in trade flows and structure with a
specific focus on Eastern Europe, the former Soviet Union and East Asia. It has sought to give
a factual basis to explaining the unexpected expansion in trade between these regions in the
aftermath of reform as well as to provide input into the present debate on Eastern Europe’s
comparative advantage.
Increased trade flows between the above regions, viewed within the framework of
changing regional trade structure, appear to reflect two concurrent developments: trade
liberalisation within Eastern Europe and the FSU that has enabled former CPEs to fully exploit
their existing areas of comparative advantage and changing comparative advantage of more
advanced and developing Asian economies. The outcome of both forces is an observed
acceleration of trade complementarity between the two regions. Behind these trends, similarity
in trade structure and a shift towards technology-intensive exports by advanced East Asian
22
economies as well as trade barriers imposed by the European Union has forced more developed
Asian countries to seek new markets from both periphery or less developed Asian economies
and Eastern Europe/FSU economies.
The main finding is that in the short but dramatic post-reform period, the comparative
advantage of Eastern Europe appears to have intensified in pre-existing areas — namely,
agriculture and unskilled-labour intensive goods. At the same time, the comparative advantage
of less developed East Asian economies has strengthened in unskilled-labour intensive goods.
As a result, the two groups ... Eastern Europe and developing East Asian economies ... are in
direct competition for export markets of more advanced economies as well as posing a threat
to import-competing industries of older industrialised countries in North America, Australasia
and the European Union.
The study is preliminary and offers, due to its methodological, data and time period
limitations, ample scope for further research and refinement. The data set are subject to all the
limitations common to work on Eastern Europe and the FSU. In particular, a breakdown of the
FSU into the Central Asian republics as well as an extended coverage of trade linkages with
Northeast Asia would provide considerable insight into the scope for further trade between the
FSU and developing Asia. The very short period since the initiation of major economic reforms
in Europe limits the observed phenomena to a study of the transition rather than long-run
equilibrium trade flows and structure. With a lengthening of the transition period, disparities
between European transition economies are likely to increase, at least initially, and will be
influenced by the pace of structural reform. Further research is needed into the interaction
between structural reform, differential rates of regional growth and their influence on trade
flows and comparative advantage.
23
AppendixTable A1 Krause factor intensity classification
Commodity SITC, Commodity SITC,revised revised
Agricultural resource-intensive goods Human capital-intensive goodsFood and live animals 0 Dyes, tanning, colour products 53Beverages and tobacco 1 Perfume, cleaning, etc. products 55Hides, skins, furs undressed 21 Rubber manufactures nes 62Oil seeds, nuts, kernels 22 Paper, paperboard manufactures 64Crude and synthetic rubber 23 Steel 672Wood lumber and cork 24 Metal manufactures nes 69Pulp and waste paper 25 Telecommunications equipment 724cTextile fibres 26 Domestic electric equipment 725Crude animal and vegetable 29 Railway vehicles 731matter nes 4 Road motor vehicles 732Animal, vegetable oil, fat 61 Road vehicles, non-motor 733Leather, dressed fur, etc. 63 Watches and clocks 864Wood, cork manufactures nes 63 Sound recorders, producers 891
Printed matter 892Mineral resource-intensive goods Works of art, etc. 896Crude fertiliser, minerals nes 27 Gold, silverware, jewellery 897Metalliferous ores, scrap 28
Technology-intensive goodsMinerals, fuels, etc. 3 Chemical elements compounds 51Non-metal mineral Coal, petroleum, etc. chemicals 52manufactures 661 Medicinal, etc. products 54Pearl, precious and semi- Fertilisers, manufactured 56precious stones 667 Explosives, pyrotechnical products 57Pig iron, etc. 671 Plastic materials, etc. 58Non-ferrous metals 68 Chemicals nes 59
Machinery, non-electric 71aUnskilled labour-intensive goods Electric power machinery switchgear 722Textile yarn, fabric, etc. 65 Electric distributing machinery 723Glass 664 Electro-medical, x-ray equipment 726Ships and boats 735 Electrical machinery nes 729bPlumbing, heating, lighting Aircraft 734equipment 81 Instruments, apparatus 861Furniture 82 Photo, cinema supplies 862Travel goods, handbags 83 Developed cinema film 863Clothing 84Footwear 85Articles of plastic nes 893Toys, sporting goods, etc 894Office supplies nes 895Other manufactured goods, 899war, firearms, ammunition 951
Note: Physical capital classification aggregates human-capital and technology-intensive goods.
Source: Tyers and Phillips (1984, Appendix 1, Table A1).
24
Table A2 Murrell classification system
Good Production Type of goods SITC codescharacteristic
1. Ricardo goods Natural resources Food, minerals 011-3, 022-5, 041-0, 051-5, 061,071-2, -74-5, 121, 242-3, 251,261-3, 271,274, 281, 283,285,321, 331,341,411, 421-2,431, 668,681-7, 689
2. Heckscher– Standard technology Beverages, cement, 111-2, 122, 273, 533, 551, 553-Ohlin goods and constant returns- domestic appliances, 4,611-3, 621, 629, 651-7, 661-2,
to-scale cars, ships, 664-6, 671-9, 691-8, 724-75,furniture, clothing 731-3,812, 821, 831, 841-2, 851,
892-5, 887
3. Product cycle High technology Chemicals, plastics, 512-5, 521, 541,581, 532,561,goods aircraft, fertilisers, 571, 711-2, 714-5, 717-8,722-3,
machinery,instruments, 726, 729,734, 861-2,864, 951munitions
Source: Murrell (1990, Table 4.2, pp. 93–4)
Table A3 Classification of transition economies by income and region, 1994a
Income group Asia Europe and Central Asia
Low income ChinaLaos PDRMyanmarVietnamTajikistan
Lower-middle income Mongolia Albania, Armenia, Azerbaijan, Bosnia and Herzegovina,Bulgaria, Croatia, Czech Rep;, Georgia, Kazakhstan,Kyrgyz rep., Latvia, Lithuania, Macedonia NR, Moldova,Poland, Romania, Russian Federation, Slovak Rep,Turkmenistan, Ukraine, Uzbekistan, Yugoslavia, Fed.Republic of (Serbia) Montenegro
Upper-middle income Belarus, Estonia, Hungary, Slovenia
Note: a 1992 GNP per capita: low income: US$675 or less; lower-middle income, US$676–2,695; upper-middle income, US$2,696–$8,355.
Source: World Bank (1994, Table 1).
25
Notes
* I am grateful to the two anonymous referees for their comments.
1 See, for example, CEPR (1990), Collins and Rodrick (1991), Anderson (1991), Rolloand Smith (1993) and the Economic Commission for Europe (1993).
2 For exceptions, however, refer to Horne and Huang (1996) and Yang, Duncan andLawson (1996).
3 A detailed discussion of trade arrangements under central planning is given in Kornai(1992, Ch. 4).
4 The share of the Soviet Union in world trade was depressed in the 1920s; its share in1914 was 3.9 per cent (CEPR 1990, p. 1).
5 The projections by Borensztein and Montiel appear quite optimistic; 6–7 per cent percapita growth in Poland and Hungary (1993–97) and 3.25 per cent for the formerCzechoslavakia.
6 The question is also addressed in a further paper by Anderson (1993), with a particularfocus on the issue of agricultural reform.
7 This possibility is discounted in the CEPR (1990) study, which envisages EasternEuropean membership of the European Union with restricted migration and CAPmembership.
8 A detailed discussion of the properties and usefulness of measures of revealedcomparative advantage is provided in Murrell (1990, Ch. 2, pp. 32–7 and Appendix A).
9 A detailed analysis of trade structure of Central Asian republics within a broadframework of Asian transition economies is presented in Pomfret (1996).
10 A discussion of trade patterns and developments in Northeast Asia is given in Pomfret(1996).
11 The data in Table 2b are not comparable with the data presented in other tables.
12 More precisely, the index of complementarity in bilateral trade (Cij) measures theextent to which country or region i’s exports to country or region j are relatively largebecause the commodity composition of i’s exports matches that of j’s imports moreclosely than it matches the commodity composition of world trade.
13 Note that trade intensity (and bilateral trade) in Tables 1 and 2a are measured using IMFdata while measures given in Table 4 are based on UN data. Differences arise becauseof differing treatment of re-exports.
14 A discussion of the properties of RCAs (export specialisation indexes) is given inMurrell (1990). In their simplest interpretation (and the one adopted here), the RCAs
26
indicate whether a country has a comparative advantage in a particular good, based upona comparison with its RCAs for other goods. Inferences drawn from comparing RCAsof other countries require more stringent conditions, as shown in Murrell (1990,Appendix A). Further, in the presence of intra-industry trade, the benchmark of unityneed not indicate comparative advantage or disadvantage but merely high or low percapita income.
15 Tyers and Phillips (1984) show that the RCA for technological goods rose from 0.1 to0.4 for ASEAN countries over the period 1970–80.
16 A more comprehensive classification system using 26 categories is also included inMurrell (1990, Table 4.2, pp. 93–9).
27
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28
Pomfret, Richard (1996) Asian Economies in Transition: Reforming Centrally PlannedEconomies, Cheltenham: Elgar.
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29
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