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

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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

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Aus

tral

asia

Res

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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

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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

References

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Kornai, Janos (1993) The Socialist System, Oxford: Clarendon.

Murrell, Peter (1990) The Nature of Socialist Economies Lessons from Eastern EuropeForeign Trade, Princeton: Princeton University Press.

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Petri, Peter A (1994) ‘The East Asian trading bloc: an analytical history’, in Ross Garnaut andPeter Drysdale (eds), Asia Pacific Regionalism: Readings in International EconomicPluralism, Sydney: Harper Educational, pp. 107–25.

28

Pomfret, Richard (1996) Asian Economies in Transition: Reforming Centrally PlannedEconomies, Cheltenham: Elgar.

Rollo, J. and A. Smith (1993) ‘Political economy of East European trade with the EuropeanCommunity’, Economic Policy, 16 (April), pp. 139–81.

Tyers, Rodney and Prue Phillips (1984) ‘Australia, ASEAN and Pacific Basin merchandisetrade: factor composition and performance in the 1970s’, Asian–Australia EconomicPaper, No. 13, ASEAN–Australia Joint Research Project, Kuala Lumpur and Can-berra.

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29

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