Patterns and determinants of chinas bilateral intra industry trade with japan and korea

Abstract This study investigates the patterns and determinants of China‟s intra-industry trade IIT with her major two trading partners in Northeast Asia, namely, Korea and Japan.. The em

Abstract

This study investigates the patterns and determinants of China‟s intra-industry trade

(IIT) with her major two trading partners in Northeast Asia, namely, Korea and Japan

Using numerical measures, we examine the evolution of trading characteristics of

these three countries and find that, due to high growth rate and rapid integration into

the world market, trade patterns of these countries are experiencing a great change

Although inter-industry trade still accounts for the majority, its importance relative to

intra-industry trade is declining significantly In addition, based on cross-industry

panel data from 1992 to 2003, we develop econometric models to test the specific

determinants of IIT between China and Japan and between China and Korea The

empirical results show that product differentiation, research intensity and inward

foreign direct investment played an important role in driving Chinese bilateral

intra-industry trade with Japan and Korea, while economies of scale, trade imbalance

and income inequality are negatively correlated with China‟s IIT Findings generally

conform to what we expected under the economic theory

Key Words: Intra-industry trade, Product differentiation, Economies of scale

1 Introduction

Since the introduction of the concept of intra-industry trade1 (IIT), i.e simultaneous exports and imports of commodities within the same „industry‟ or product category,

there have been extensive studies examining the phenomenon Studies on this topic

can be classified into three groups The first concerns the measurement as well as the

magnitude of intra-industry trade [e.g Grubel and Lloyd (1975), Greenaway (1983)

and Brulhart (1994)] The second category attempts to develop theoretical

explanations for its existence [e.g Krugman (1979), Lancaster (1980) and Falvey

(1981)], while the third is seeking to evaluate the determinants of intra-industry trade

in an econometric framework [e.g Balassa and Bauwens (1987), Greenaway et al

(1994) and Hu and Ma (1999)] The current study belongs to the third category for the

special case of China

Since the implementation of the “open door” policy in late 1970s, China has pursued

significant trade liberalization and rapid integration into the world market It is

observed that during the years 1979-2006, not only China‟s international trade volume

expanded greatly, its trade patterns also experienced a noticeable change, especially in

terms of the increasing share of intra-industry trade Although inter-industry trade still

accounts for the majority, its importance relative to intra-industry trade is declining

In this study, we focus on China‟s intra-industry trade with her major two trading

1

Balassa introduced the concept of intra-industry - as compared to inter-industry – trade in 1966

partners in Northeast Asia, namely, Japan and Korea The purpose is to investigate the

changing nature of China‟s trading patterns and the determinants of intra-industry

trade The paper is comprised of both descriptive and empirical analysis The

descriptive analysis will investigate the major trade characteristics of Northeast Asia

and the evolution of China's trade relation with Japan and Korea It will further

evaluate China‟s intra-industry trade pattern of various industries In the empirical

part, we will test several hypotheses regarding the determinants of IIT using

cross-industry panel data

By exploring the case of China, the present study will contribute to empirical works

on intra-industry trade in two ways First, most empirical studies concerning IIT focus

on industrial countries2 where IIT is more likely to occur Although trade in developing countries and newly industrializing countries has attracted increasing

academic interest since 1980s, intra-industry trade studies involving emerging

economies are still limited, empirical analysis concerning China‟s intra-industry trade

is even scarcer In fact, China has made great strides in manufacturing and has

become an important supplier of manufactured exports over the past three decades,

thus we can expect that China‟s IIT has also increased significantly Second, most

cross-industry studies only incorporate a limited set of industries or merely employ

one-year data in their estimations In contrast, we establish a rich data set, covering

2 See, for example, Loertscher and Wolter (1980), Caves (1981), Bergstrand (1983), Kol and Mennes (1983), Greenaway and Milner (1984), and Clark and Stanley (2003)

more than 3003 of four-digit SITC4 industries over a 12-year period This provides a unique opportunity to conduct quality cross-industry analysis

The paper proceeds as follows Chapter 2 reviews the relevant literature Chapter 3

provides an overview of China‟s total trade and the development patterns of China‟s

bilateral trade with Japan and Korea Chapter 4 presents the methodology and the

hypotheses to be tested in econometric models and Chapter 5 discusses model

estimation procedures and reports the empirical results Chapter 6 offers some

2 Review of the literature

2.1 Theoretical Literature Review

The 1960s witnessed a revolution in international trade theory as new trade patterns

represented by intra-industry trade emerged The traditional trade theories such as

comparative advantage theory and factor endowments theory set out by David

Ricardo and Heckscher-Ohlin provided no explanation towards intra-industry trade5

as intra-industry trade suggests that a country has a comparative advantage and

disadvantage in the same product (since it both exports and imports the product)

Hence, considerable academic attention has been devoted to providing proper

interpretation of the phenomenon over the past four decades The evolution of

intra-industry trade theories can be divided into three stages

2.1.1 Early Hypotheses

According to Toh‟s (1982) summarization, in the early 1970s, there were several

hypotheses concerning intra-industry trade The representatives include seasonal

variation, border trade, and entrepot trade

Seasonal trade is mainly applied to agricultural products, such as Chinese apple,

5

Krugman & Obstfeld (1991)

which can be exported all around the world during a particularly good apple growing

season, but imported during a poor one Border trade is induced by taking transport

costs into account Although certain goods already produces domestically, the

existence of long common borders of two adjoining countries may find it less costly

to trade with a neighboring country, thus intra-industry trade occurs Entrepot trade is

a special kind of re-exportation, it is the export without further processing or

transformation of a good that has been imported Entrepot trade often happens in large

ports such as Rotterdam in Netherland and Singapore that charges lower or no tariffs

and act as holding places for goods which are then sold on

However, starting from Pomfret (1976) and Lipsey (1976), it has been argued that

intra-industry trade is a statistical artifact arising from improper aggregation of trade

data Because defining industries as “the same” is a matter of classification,

intra-industry trade would disappear at the finest level of disaggregation As a result,

how to establish meaningful industry categories became the center of the debate

However, as Finger (1978) recognized, categorical aggregation is not a significant

reason of intra-industry trade Sufficient empirical evidence have emerged to suggest

that there exists intra-industry trade even if industries are disaggregated into

extremely fine levels [e.g Gray (1979) and Bergstrand (1983)] and moreover, instead

of a higher level of disaggregation, a neither too fine nor too broad industry category

could be a scientific way for the meaningful analysis of IIT [Menon and Dixon

(1996)] With these considerations in mind, we adopt four digit Standard International

Trade Classification data in our estimation6

2.1.2 Early Theoretical Explanations

As a possible solution to the famous Leontief paradox, which rejected empirically the

traditional factor proportions theory, Linder (1961) proposed an alternative theory that

was consistent with Leontief's findings Linder‟s Theory focuses on the role of

demand, rather than supply, on trade patterns and relates trade to a country's

development level and domestic demand composition Linder hypothesized that

consumers‟ tastes depend on their income levels and countries with similar

preferences would develop similar industries With similar demand, these countries

would then trade back and forth in similar but differentiated products Accordingly,

the closer are the income levels per consumer, the higher are the level of

intra-industry trade Dreze (1961) further postulated that larger countries have better

abilities to produce differentiated goods than smaller ones and, on the other hand,

larger markets can accommodate a larger demand for different varieties, so market

size also contribute to intra-industry trade

Meanwhile, international economists also attempted to explain IIT by reference to

dynamic extensions of the traditional static factor proportion model Posner (1961)

proposed the “technological gap” theory which claims that changes in international

6

Toh (1982) has shown that at the four-digit level of disaggregation bias ought to be of lesser significance

trade are reflected by the relative technological sophistication of countries The most

highly industrialized nations export new high-technology products to other nations

Foreign firms take times to acquire the new technology after which they can reduce

imports and even occupy markets abroad While the technological gap model

emphasizes the time lag in the imitation process, the product cycle model propounded

by Vernon (1966) stresses the standardization process The theory suggests that early

in a product's life-cycle this product is produced and consumed only in the area where

it was invented After the mass-production techniques are developed and the product

becomes widely adopted and used in the world markets, through imitation and

technology transfer, the location of production gradually moves to developing

countries, where they can enjoy a lower cost These developing countries then export

the relative older versions of product to the original countries, simultaneously import

the latest versions in the same product category

2.1.3 Synthetical Research

Since late 1970s, many new models have been designed to analyze IIT in a synthetical

way The most comprehensive and widely accepted explanation is Paul Krugman's

new trade theory which emphasizes the role of economies of scale Krugman reveals

that, with increasing returns to scale, each producer within any particular industry will

specialize in a limited variety of production in order to reap the advantages of

economies of scale Grubel and Lloyd (1975) made another contribution to the theory

of intra-industry trade as they divided intra-industry trade into horizontal and vertical

types The horizontal intra-industry trade (HIIT) is trade in differentiated product with

similar quality but different attributes, while vertical intra-industry trade (VIIT)

involves vertically differentiated goods that are distinguished by quality This

classification was then proved to be important in theoretical research because the two

types are driven by different or even contradictory forces

The theoretical work which had attempted to explain intra-industry trade using

models of monopolistic competition with increasing returns to scale mainly

concentrated on horizontal differentiation Following Dixit and Stiglitz (1977), the

“love of variety” approach, and Lancaster (1979), the “ideal variety” approach,

Krugman (1979) first developed models highlighting the key role of scale economies

and product differentiation in determining IIT As noted above, this approach became

the foundation of the following relevant literature Helpman (1981) and Helpman and

Krugman (1985) subsequently refined and synthesized the previous models into an

unifying one incorporating factor endowments, decreasing costs and product

differentiation This so-called Chamberlin–Heckscher–Ohlin (CHOS) model shows

how the share of intra-industry trade in total trade is related to consumer patterns and

factor endowments As a result, a theoretical framework associating different

country-specific characters with intra-industry trade was popularized By extending

the previous theoretical work, Bergstrand (1990) further rationalized relationships

between the share of intra-industry trade and the average levels of and inequalities

between their economic size, per capita incomes, capital-labor endowment ratios, and

tariffs He established a unified theoretical framework which includes all those

particular variables and analyzed how each of those determinants specifically affects

the share of intra-industry trade in a given commodity group

Studies of vertical IIT are derived from the seminal paper of Falvey (1981) that

pointed out goods under the same statistical category but of different quality may be

produced using different combination of factor inputs, so that the differences in factor

endowments may have a large impact on IIT Falvey (1981) and Falvey and

Kierzkowski (1987) constructed models assuming that goods are distinguished by the

perceived quality By associating the product quality with capital intensity, they both

indicated that goods with high capital intensity tend to have high quality They also

showed that the relatively high-income and capital-abundant countries will specialize

in and export capital-intensive products of high quality, whilst the relatively

low-income and labor-abundant countries export low quality labor intensive products

In addition, on the basis of the traditional comparative advantage theory, Flam and

Helpman (1987) emphasizes the role of technology, they claimed that technological

differences are the main source of different varieties Since market structure was

ignored in the above studies, a complementary work with a “natural oligopoly”

context was done by Shaked and Sutton (1984) They assumed that, R&D input,

which is considered as a kind of fixed cost, plays an important role in determining

product quality Thus, with entry barriers, only the best firms bearing big advantage of

scale economies can afford a constant larger expense for R&D and survive in the

world market Hence, Vertical IIT will occur when remaining firms are located in

different nations

2.2 Empirical Literature Review

The development of intra-industry trade theory has stimulated the pertinent empirical

analyses which seek to identify the determinants of such trade Intra-industry trade

enhances the gains from trade through increasing returns to scale and product

differentiation as it forces firms to concentrate on a narrow range of products, and

thus helps reduce fixed costs So it is crucial to find out what determines IIT Pertinent

empirical models can be traced to mid-1970s and most of them tend to categorize the

determinants into two groups: country-specific factors and industry-specific factors

The country characteristics such as per capita income, economic size, transactions

costs are originated from Helpman and Krugman‟s theoretical work in 1985 Three

closely related works are Balassa (1986), Helpman (1987), Bergstrand (1990)

Using trade data for the year 1971, Balassa (1986) tested the hypotheses7 derived from the theory of intra-industry trade in a cross-country (38 countries) framework

OLS method as well as non-linear least square method utilizing a logistic function are

7 The hypotheses put forward to explain the extend of IIT pertain to the level of economic development, the size

of domestic market, transportation costs, common boarders with trading partners, the level of trade restrictions, and participation in integration arrangements

used IIT is calculated based on the 4-digit categories of United States Standard

Industrial Classification (SIC) Different from other studies which choose country

set somewhat arbitrarily, this paper select 38 countries whose manufactured exports

account for at least 18 percent of their total exports in the year 1979 This criterion

avoids spurious correlations through the inclusion of countries with low share of

manufactured exports The regression results significantly show that intra-industry

specialization is positively associated with the level of economic development, the

size of domestic markets, the existence of trading partners with common borders and

geographical proximity Openness of national economies and being an entrepot such

as Singapore further contribute to intra-industry trade

This paper was also one of the earliest studies that consider intra-industry trade

among developing countries The author made separate estimates for developed and

developing economy subgroups by taking their 1973 per capita GNP as the

benchmark Such separation of the countries made no difference as far as the overall

explanatory power of the regression is concerned Test for the developing countries

even reported better results However, increased intercorrelation among the

explanatory variables and the smaller heterogeneity of the observations reduced the

statistical significance of the individual regression coefficients, in particular for the

developed country group

Helpman (1987) captured the relation between the intra-industry trade share and both

the difference in income level and relative country size The intra-industry trade share

was calculated on the basis of 4-digit SITC data Since the hypotheses concerning the

determinants of intra-industry trade was derived from theoretical models in which all

industries have been accounted for, both manufacturing and nonmanufacturing sectors

were included Results generated from cross-section data which comprised 14

industrial countries supported the hypotheses that countries with similar incomes per

capita have larger share of intra-industry trade in bilateral trade In addition, He tested

within-group trade flows applying to time series data from 1970 to 1981 Since time

series analysis was not appeared in previous studies, Helpman‟s attempt was

undoubtedly a meaningful one However, the results is somewhat interesting and

deserves further investigation as it shows that contribution of differences in factor

composition to the share of intra-industry trade has declined over time

By restricting that intra-industry trade involves only horizontally differentiated

products, Bergstrand conducted an empirical test regarding relationships between the

share of intra-industry trade and the average levels of and differences between their

national incomes, per capita incomes, capital-labor endowment ratios, and trade

barrier The sample comprised 14 major industrialized countries for the year 1975 and

3-digit SITC bilateral intra-industry trade indexes within the sector SITC78 were used

as the dependent variable The regressions are estimated using weighted least squares

in order to avoid heteroskedasticity generated from OLS estimation Compared with

8

Machinery and transport equipment

the previous studies, two new variables which are the average of and inequality

between capital-labor endowment ratios were introduced for the purpose of

distinguishing between the demand and supply influences of per capita income It was

found that the inclusion of the two variables has significantly changes the coefficient

estimates of the average of and inequality between per capita incomes in an

economically meaningful way9

Paralleled with country-specific determinants analysis, it is noted that whatever the

country characteristics are, the level of IIT can vary significantly across industries

depending on whether the certain industry characteristics discourage IIT or promote

IIT Hence, a number of studies have also tested for industry-specific influences on

intra-industry trade10 and have shown that share of IIT in total trade is systematically related to imperfect competition, product differentiation, and scale economies

David Greenaway and Chris Milner‟s work (1984) plays a prominent role in the

empirical trade literature examining the industry-specific determinants of

intra-industry trade It explores the impacts of inter-industry differences on

intra-industry trade for the United Kingdom by reference to various industry structure

variables Intra-industry trade level is measured at third digit of the SITC and the U.K

SIC (Bj) Besides, an adjusted index (Cj), which is a weighted average of all the

9

The coefficient estimate for the inequality between per capita incomes becomes smaller and the average per capita income coefficient estimate changes from a statistically significant negative value to a positive value after addition of the two new variables

10

See, for example, Bergstrand (1983), Falvey and Kierzkowski (1987), Clark (1993) and Hughes (1993)

indices at the 4th digit level in each 3rd digit grouping, is introduced for the purpose

of making an allowance for possible categorical aggregation problem OLS

methodology is adopted in estimation using linear and loglinear specifications

In their paper, a variety of explanatory variables are included, such as product

differentiation, jointness of production, advertising/sales ratio, effect of research

intensity, five firm sales concentration ratio as well as cost advantage of large firms

over small firm within each industry, and also the overlapping demands Notably, the

market structure factors were most emphasized since they capture both supply based

and demand based features On the supply side the five firm sales concentration ratio

as well as cost advantage of large firms over small firm within each industry appears

to be inversely related to level of intra-industry trade On the demand side

advertising/sales ratio, and product differentiation indicate a positive relation to

intra-industry trade Although there is some inconclusiveness, this study still offers

more support for the role of industry-specific determinants than most of the other

studies

Other than investigating country-specific and industry-specific determinants

separately, some literature also tried to explore them all together The representatives

include Bela Balassa & Luc Bauwens (1987), and Don P Clark & Denise L Stanley

(2003)

Balassa and Bauwens (1987) is one of the earliest studies that analyze the

cross-country and the cross-industry determinants of intra-industry trade

simultaneously in a multilateral framework It is an extension of Balassa‟s previous

work (1986) by including industry-specific factors An adjusted logistic function of

IIT is constructed to prevent the predicted values lying outside the 0-1 range Apart

from the country-specific determinants discussed in the previous work, various

industry characteristics determinants as well as some new country characteristics

variables are introduced Estimations were made for bilateral intra-industry trade

flows among all the countries concerned, among 18 developed countries, among 20

developing countries, as well as between developed and developing countries Most

of the regression coefficients including the newly-introduced variable such as

language dummy and offshore procurement have the expected sign and are generally

statistically significant Regression equation of Intra-industry trade among developed

countries has the greatest explanatory power due to homogeneous economic structure

By contrast, the explanatory power of the regressions for intra-industry trade among

developing countries, and between developed and developing countries were reduced

by the heterogeneity of the sample and the relatively large proportion of zero

observations

Being the earliest attempt, their research is also proved to be a good work The

authors make a comparison of the results between the combined estimation of both

country and industry characteristics and the decomposed estimation which contains

only country or industry characteristics The former regression does show more

satisfactory results over the latter

Similarly, Clark and Stanley (2003) jointly investigate a variety of country and

industry-level determinants of intra-industry trade using a multi-country

multi-commodity framework The analysis is based on bilateral trade of U.S with 22

industrial nations Over 300 four-digit U.S SIC industries are included and all data

used pertain to 1992, which is much more recent than previous research Another

remarkable progress is that far more observations and a much lower level of industry

aggregation are used than most relevant studies Furthermore, a new distinctive

estimation approach is used in this paper Most previous studies apply a logistic

transformation to the dependent variable and drop observations with zero value In

contrast, the authors emphasize the importance of observations with zero because they

represent complete inter-industry trade Thus, they make an improvement in the

estimation procedure by using limited dependent variable techniques (Tobit Model

and Probit Model)

Table 1 provides a summary of the estimation results in the relevant literatures

Stimulated by the theoretical work that suggest intra-industry trade in horizontally and

vertically differentiated goods may have different determinants Abd-el-Rahman

(1991) empirically disentangled total IIT into horizontal and vertical IIT on the

assumption that price reflects product quality and can be represented by unit values

This prevailing methodology runs as follows: If the relative unit values of exports and

imports of a particular product falls in a range of ±15%（or a spread of ±25 %）, it

is categorized as horizontal intra-industry trade, or else it is considered to be vertical

intra-industry trade Following the two alternative criteria, Greenaway, Hine and

Milner (1994, 1995, 1996) test respectively how country- and industry-specific and

both factors affect vertical and horizontal IIT between UK and its partner countries

The results from this set of studies support the view that determinants of horizontal

and vertical IIT differ but sometimes in unexpected ways

Table 1 Determinants of Intra-Industry Trade

(1986b)

Bergstrand (1990)

Inequality of tariff levels -*

Participation in regional

integration schemes

+***

Table 1 Continued

(1986b)

Bergstrand (1990)

Country-specific variables

insignificant) Differences in skilled

1 *, **, *** denote statistical significance in t-tests at the 10%, 5%, and 1% levels, respectively

2 All estimates use intra-industry trade indices as the dependant variable

Undoubtedly it is a good challenge to distinguish between vertical and horizontal IIT

and test their determinants separately in the empirical study, but it is not practicable in

most cases due to the data availability Since our analysis covers almost all the

industries and especially in a relatively disaggregate level, we will not make such

distinction

Empirical investigations of the determinants of IIT in China are extremely limited Hu

and Ma (1999) develop two different regression models to detect the influence of

country characteristics and industry characteristics separately The first one considers

the intra-industry trade of China across all the major 45 trading partners using

country-specific variables while the other one concerns bilateral intra-industry trade

with UK across industries using industry-specific variables The study clearly shows

that intra-industry trade is an important component of China‟s total trade, and it takes

place not only between China and developing countries with similar income level, but

also between China and developed countries with different factor endowments and

consumer tastes It is also found that China's intra-industry trade generally follows the

similar patterns of those in industrialized countries despite some different features

Zhang et al (2005) investigate the features and determinants of Chinese intra-industry

trade during the 1992–2001 period for 50 of China‟s trade partners They include a

much broader range of explanatory variables (15 totally) in the estimation equation

and disentangle intra-industry trade into vertical and horizontal intra-industry trade

The results confirm that most underlying determinants work the expected way

However, the analysis only included country-specific factors, and it might be

improved by incorporating industry characteristics

3 Patterns and Recent Trends in Intra-Industry Trade

This chapter is a descriptive analysis of the historical evolution of China‟s trading

patterns and trends on China‟s intra-industry trade with Japan and Korea The purpose

is to deliver an overall impression of China‟s trade pattern rather than proving the

trends statistically or econometrically It serves as the fundamental to the main

discussion in the following chapters

3.1 The Measurement of Intra-Industry Trade

A variety of measurements have been designed to estimate IIT in the sixties The most

important one at that time was proposed by Balassa (1966) in the following form:

M X n

Where X i and M i stand for exports and imports in industry i respectively and n is the

number of industries taken into consideration It is an unweighted average of trade

overlap for each industry and E measures the degree of a country‟s inter-industry

specialization Accordingly, the lower the value of this index, the larger the share of

intra-industry trade

However, Grubel and Lloyd (1971) criticized Balassa‟s index because it is a simple

arithmetic mean of each industry‟s index and thus fails to reflect the different weight

of each industry11 By a simple modification, Grubel and Lloyd (1971) have introduced the so-called Grubel–Lloyd (G–L) index, which is perhaps the most widely

used index of IIT to date It is generally defined as:

i i i i i

This index takes the minimum value of zero when either X i = 0 or M i = 0, signifying

complete inter-industry trade, and the maximum value of 100 when X i = Mi, indicating

that all trade is intra-industry To calculate the overall level of IIT across industries at

a given level of aggregation, Grubel and Lloyd (1975) further suggested the following

weighted IIT index, using the relative size of exports and imports of a particular

ij

i

Where j = 1, 2…n, denotes the sub-industry category within industry i and n is the

number of industries at this certain level of aggregation

Nevertheless, Index (2) and (3) are influenced by the size of the trade imbalance As

Grubel and Lloyd stressed (1975), in the presence of a trade imbalance, both indices

are downward biased measures of IIT and are likely to underestimate the intensity of

IIT The greater the imbalances, the smaller the share of IIT Therefore, they proposed

an alternative way to overcome this bias by incorporating trade imbalance into the

11

See Vona (1991)

initial equation as follows

)(

i

n

i

i i n

i

i i

M X M

X

M X M

X

Comparing equation (4) with equation (2) and (3), we can observe that the

denominator in equation (4) has been reduced by subtracting the total trade imbalance

from the total trade volume Such treatment makes IIT represent the share of total

balanced trade instead of overlap trade in total trade and thus mitigate the effect of

trade imbalance on the level of IIT

Aquino (1978) and Bergstrand (1983) argued that the GL correction failed to adjust

for an imbalance in a country‟s overall trade, because each industry rather than the

weighted average of overall trade should be corrected for the trade imbalance Hence,

they both proposed more complicated measures to address the problem However, as

Clark (1993) pointed out, they paid too much attention to deal with the trade

imbalance and overlooked the role of trade pattern The assumption behind their

formula that trade imbalance is evenly distributed across industries could induce a

more serious bias This is precisely the reason that most recent empirical studies tend

not to use the adjusted measures (e.g., Clark, 1993; Greenaway et al 1994; and Kim

et al., 2001) Accordingly, we also prefer the unadjusted GL index But instead,

following Clark and Stanley (1999), we will include a measure of the relative trade

imbalance as an explanatory variable in our estimation

3.2 Trade Growth and Close Trading relationships with Japan and Korea

Thirty years ago, China was an insignificant player in the world economy However,

since the policy of openness and reform program initiated by Deng Xiaoping in 1978,

China has moved out of its isolation and has embarked on a gradual switch from a

closed, central-planned and agricultural-based economy to an open, market-oriented

and manufacturing-based economy Over the past three decades, China‟s trade and

economic relations with foreign countries have undergone tremendous development

The sustained rapid economic growth and the simultaneous rise in people‟s living

standards, together with the robust demand of the international market have provided

strong propulsion for China‟s exports and imports Figure 1 is a clear demonstration

of China‟s trade expansion The total trade volume of China was only 21 billion US

dollars in 1978, ranked 32nd in world trade By the end of 2006, the total nominal

trade volume has jumped to 1760 billion US dollars, over 80 times the figure 28 years

ago, making China surpassed Japan as the world trade's third largest participant12

Figure 1 China’s International Trade Development

12

Rankings are from Ministry of Commerce of China

China's International Trade Development

1200.00 Trade Volume (Billion US$)

Imports/GDP Exports/GDP Exports Imports

Source: Trade data are from WTO: international trade statistics database

GDP data are from IMF: World Economic Outlook Database, October 2007

China‟s astounding growth has significant implications for the East Asian economies,

especially for Japan and South Korea, China‟s two nearest neighbors and the most

important economies in Asia as well In the past two decades, China's trade relations

with Japan and Korea have beengreatly enhanced The bilateral economic and trade

ties with Japan and Korea has been rapidly developing in relative importance

According to Japan External Trade Organization (JETRO), bilateral trade between

China (excluding Hong Kong) and Japan amounted to 236.6 billion US dollars in

2007 China accounted for 17.7 percent of Japan's total trade and replaced U.S

(16.1%) as the biggest trading partner of Japan while Japan remains the 3rd place of China‟s largest trading partner, only behind the EU and the U.S Meanwhile, in

accordance with the report by Korea's Ministry of Commerce, Industry and Energy,

China maintained the largest trade partner and export destination of Korea in 2007,

with the bilateral trade volume climbed up to 140.5 billion US dollars On the other

hand, statistics from China indicated that Korea ranked 6th among China‟s trading

partners and export markets, and 3rd among import sources

Additionally, it is observed that China‟ trade expansion with Japan and Korea has

been along with intensive increase of foreign direct investment (FDI) from the two

partner countries In fact, foreign invested firms are the major forces boosting China's

trade growth In 2001, the exports of foreign invested firms in China amounted to

$133.23 billion, more than fifty percent of China‟s total exports13

In particular,

according to the report of Ministry of Commerce of China, there were 28,401

Japanese-invested enterprises and 27,128 South Korean-invested enterprises in China

by the end of 2003, accounting for 6.1 percent and 5.8 percent of the total foreign

companies in China Japan became the second largest investor in China, with a

cumulative contractual investment value of US$57.5 billion (6.1%) and actual

investment of US$41.4 billion (8.25%), while Korea ranked as the fifth largest FDI

source of China, with a cumulative contractual investment value of US$36.7 billion

(3.88%) and actual investment of US$19.7 billion (3.93%) As pertinent literature

shows14, those foreign invested firms are seeking to maximize production efficiency and use China as an export-processing base According to a survey of JETRO (2003),

there are about two thirds of Japanese-invested firms in China exporting at least 70

percent of their products, and on average15, more than 50 percent of the exports headed for Japan Although we don‟t have specific data for Korea, Park and Lee

(2003) showed that from 1993-1995, Korean affiliated manufacturers in machinery,

electrical and chemical industries in China sold on average 91.2 percent of their

products to overseas markets including Korea Since most of the products exported

back to Japan and Korea belong to the product categories which comprise China's

major imports from those two countries16, we can expect that this kind of “reverse imports” contribute to the growth of China‟s intra-industry trade with Japan and

Korea

Table 2 shows trade patterns of China, Japan and Korea It can be seen that their

trading structures differed in many ways 30 years ago, but the disparities have

reduced gradually over the past three decades Japan and Korea are both well-known

for being resource-poor countries, and because of the shortage of farmland and the

higher degree of industrialization, they are highly dependent on imports of agriculture

products and raw materials, especially energy resources Imports of fuels and mining

products accounted for 60% and 36% of Japan and Korea‟s total imports respectively

in 1980 Although both declining to 36%, the figures for imports of fuels and mining

products still rank top ones among all the imports in 2006, On the other hand,

manufactured goods make up most of Japan's commodity exports throughout the

15

Specifically, 90 percent of electrical product, 80 percent of textile, 70 percent of metal product, over 60 percent

of machinery and 45 percent of transport product are export back to Japan

16

E.g precision instrument, machinery and metal products are China‟s major imports from Japan, while electrical and chemical products are major imports form South Korea