T h e J o u r n a l o f D e v e l o p i n g A r e a s Volume 49 No. 4 Fall 2015
THE DETERMINANTS OF VERTICAL INTRA-
INDUSTRY TRADE IN SITC 8: THE CASE OF
ASEAN-5 AND CHINA
MUI-YIN CHIN*
Tunku Abdul Rahman University College, Malaysia
CHEN-CHEN YONG University of Malaya, Malaysia
SIEW-YONG YEW
University of Malaya, Malaysia
ABSTRACT
Vertical intra-industry trade (VIIT) has become increasingly important in Asia resulting from the
rapid development of regional production network. China, endowed with abundance of labor has
emerged as the regional and global manufacturing powerhouse. The dynamic changes of trade
networking have reinforced ASEAN-5’s desire to boost the development of VIIT with China in
manufactured products. As such, the objective of this study is to identify the determinants for VIIT
between ASEAN-5 and China in miscellaneous manufacturing sector (SITC 8). After computing
VIIT indices using the decomposition type threshold method, the indices were subjected to panel
data analysis using spatial panel model. The econometric results show that trade openness is the
significant determinant of VIIT. The results also confirm the presence of spatial interaction effects
among ASEAN-5 countries as SVIIT (spillover effects of VIIT) is significant. These suggest that
ASEAN Economic Community and China-ASEAN Free Trade Area can be the appropriate
platform to promote VIIT in SITC 8.
JEL Classifications: F12, F14, C33, C43
Keywords: Vertical Intra-Industry Trade, Labor-Intensive Manufactured products, Spatial Panel
Model
Corresponding Author’s Email Address: [email protected]
INTRODUCTION
After the 1997 Asian Financial Crisis, the trade between ASEAN and Asia, particularly
China had increased and the dependency on trade with the United States (US) market was
diluted. During the nineties, China’s continuous open door policies, coupled with
abundant labor had attracted tremendous inflow of foreign direct investment (FDI)
(Eichengreen and Tong, 2006). The inflow of FDI into China had led to the increase in
two-way trade of intermediate and final goods in the same industries between China and
her neighbors leading to the formation of production networks in Asia as part of the
global production networks (Chantasasawat et al., 2004). China ascension to WTO in
December 2001 had further increased the reliability of China as a supplier to international
markets and reduced the risk premium of investment within China (Zhang, 2008). China
has now emerged as the regional and global manufacturing powerhouse. Vertical intra-
industry trade (VIIT1) in manufacturing products, which is attributable to production
fragmentation2, plays the pivotal role in bilateral trade between China and her trading
partners. Manufactured products contributed more than 80% to the total trade between
East Asia and China in 2006-2007 (Athukorala, 2011) while processing exports and
imports contributed 50-55% and 40-45% respectively to China’s total trade (Koopman et
al., 2008). Interestingly, China’s imports were mainly from Asian countries. Half of the
imported goods were intermediate goods for reprocessing and assembly, which were then
sold to foreign markets (The Economist, 2009).
Previous studies on bilateral intra-industry trade in Asia were focused mainly on
machinery and electrical products (Yong et al, 2013; Fukao, Ishito and Ito, 2003; Hurley,
2003; Ando, 2006, Tong and Lim, 2009 and Wong and Chan, 2003). Bilateral intra-
industry trade on traditional labor-intensive manufactured products is not widely studied.
Athukorala (2012) found the share of labor-intensive manufactured products has
increased strikingly in Asian regional trade and despite the onset of 2008 global
economic crisis, the exports of traditional labor-intensive manufactured products did not
decrease significantly (Athokorala, 2011). This reflects the sustainability of these
products. Chin et al. (2013) had earlier identified for each ASEAN-53 countries the niches
in SITC 8 using decomposition type threshold method.
This study, which does not stop at trade decomposition, aims to fill in the gap of
the current literature by identifying econometrically, the determinants of VIIT between
ASEAN-5 and China in the miscellaneous manufacturing sector (SITC 8) using spatial
panel model. SITC 8 is chosen as this manufacturing sub-sector encompasses most of the
traditional labor-intensive manufactured products, the trade of which appears sustainable.
ASEAN-5 is selected in this study instead of all ASEAN countries as there is limited data
availability for Brunei and CMLV4. This paper is organized as follows: Section 2
presents the analysis of bilateral trade between ASEAN-5 and China; Section 3 contains
the literature review on intra-industry trade; Section 4 describes the methodology used in
this study; Section 5 presents the empirical results and Section 6 concludes the paper.
THE ANALYSIS OF BILATERAL TRADE BETWEEN ASEAN-5 AND CHINA
The US, European Union and Japan were the major trading partners of ASEAN in the
early nineties (Zhang and Hock, 1996). China’s share in ASEAN’s total trade then
remained insignificant and was only 2.06% and 2.15% in 1993 and 1994, respectively
(ASEAN Statistical Yearbook, 2003). China was an exporter of labor–intensive
manufactured products and competed strongly with ASEAN countries, which have
similar comparative advantage in similar types of commodities (Liu and Luo, 2004). The
similar comparative advantages between ASEAN and China also limit their mutual
absorptive capacity for each other’s products (Zhang and Hock, 1996).
The 1997 Asian Financial Crisis caused severe recession and trade contraction in
ASEAN. The export of ASEAN to her largest trading partner, the US, dropped by 7.7%
in 1998. On the other hand, China was willing to assist ASEAN during the crisis (Tong
and Lim, 2009). The total export of ASEAN to China surged by 0.4% from 1997 to 1998
(ASEAN Statistical Yearbook, 2003). Since then, ASEAN promoted intra-regional trade
vigorously and subsequently causing their bilateral trade to increase significantly in the
nineties. Following the ascension of China to WTO in December 2001, China has further
liberalized her trade, partly contributing to the drastic rise in the bilateral trade between
ASEAN and China in the 2000s. ASEAN-China trade rocketed to USD231 billion in
2008 from USD78 billion in 2003, at 24% annually (Hong Kong Trade Development
Council, 2010). Since 2009, China has become the largest trading partner of ASEAN
(ASEAN Statistical Yearbook, various years).
Trade between ASEAN-5 and China lean towards manufactured products, which
contributed the rise from 55.9%, 55.6%, 55.5%, 58.7% and 62.2% in 1993 to 46.4%,
73.4%, 75.9%, 85.4% and 75.6% in 2000 for Indonesia, Malaysia, Philippines and
Thailand respectively (UN COMTRADE database). With the exception of Singapore, the
trade share of manufactured products for the rest of ASEAN-5 countries (Indonesia,
Malaysia, Philippines and Thailand) further elevated to 60.3%, 82.6%, 82.8% and 82.6%
in 2012. For Singapore, the already high trade share dropped marginally to 84.9% (UN
COMTRADE database).
FIGURE 1. BILATERAL TRADE BETWEEN EACH ASEAN-5 COUNTRY AND
CHINA FOR SITC 8 DURING 1993-2012
Source: UN Comtrade Database
Figure 1 portrays the bilateral trade volume between each ASEAN-5 country and China
for SITC 8 from1993 to 2012. The growth rates of bilateral trade between ASEAN-5
countries and China in SITC 8 are in line with the rising trend of bilateral trade between
ASEAN-5 and China in manufactured products. The multi fold increases point towards
more prominent roles of SITC 8 products in their trade relations.
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
Million US Dollars
Year
Indonesia Malaysia Philippines
LITERATURE REVIEW ON INTRA-INDUSTRY TRADE
Ample empirical studies have shown that intra-industry trade has been expanding over
time (Grubel and Lloyd, 1971; Lancaster, 1980; Falvey, 1981; Krugman, 1981;
Greenaway and Milner, 1983; Balassa and Bauwens, 1987; Tharakan and Kerstens, 2005
Fontagne and Freudenberg, 1997; Hu and Watkins, 1999; Fontagne, Freudenberg and
Gaulier, 2005; Zhang, Witteloostuijn and Zhou, 2005; Turkcan, 2010; Ito and Okubo,
2011). Ando (2006) further pointed out that the equalization of the composition of
exported and imported goods has converged in the East Asian region, signalling the
increasing importance of intra-industry trade in this region. In light of the above, intra-
industry trade (IIT) had received increasing attention in trade liteerature as traditional
trade theories can no longer accommodate the new trade patterns that arose (Lancaster,
1980). Intra-industry trade can be further divided into horizontal intra-industry trade and
vertical intra-industry trade. According to Fukao, Ishido and Ito (2003), vertical intra-
industry trade dominated intra-industry trade in East Asia with the percentage of intra-
industry trade in some ASEAN countries, i.e. Malaysia, Singapore and the Philippines
higher than more developed countries such as Korea and Japan. In line with the findings
of Fukao, Ishido and Ito (2003), Hurley (2003) also found that intra-industry trade,
particularly vertical intra-industry trade have been growing and became crucial for
ASEAN.
The determinants for IIT have been widely studied (Lancaster, 1980; Krugman,
1979 and 1981; Helpman, 1981; Falvey, 1981; Caves, 1981; Balassa and Bauwens, 1987
and 1988; Bergstrand, 1990; Greenaway, Milner and Elliott, 1999; Hu and Ma, 1999;
Kimura and Ando, 2003; Schott, 2003; Fukao, Ishido and Ito, 2003; Ando, 2006; Xing,
2007; Turkcan, 2010; and Andresen, 2010). The impact of the determinants varies
depending on the nature of whether the intra-industry trade is horizontal or vertical.
Some previous studies showed that FDI is the most important determinant of vertical
intra-industry trade (Balassa and Bauwens, 1987 and1988; Kimura and Ando, 2003;
Fukao, Ishido and Ito, 2003; Hurley, 2003; Zhang and Li, 2006; Ando, 2006; Xing, 2007;
Turkcan, 2010 and Turkcan and Ates, 2011). Other significant determinants of vertical
intra-industry trade include difference in market size, trade openness, GDP per capita,
distance, economics of scales and product differentiation.
METHODOLOGY
This study employs the decomposition-type threshold method developed by Fontagne and
Freudenberg (1997) to compute the VIIT indices between each ASEAN-5 country and
China. The computed VIIT indices were used as the dependent variable in the
econometric model. Based on this method, the intra-industry trade (IIT) indices in SITC 8
between each ASEAN-5 country and China are computed first in order to identify the
extent of trade overlap in each product of this manufacturing sub-sector. The trade of a
product is classified as intra-industry if the smaller trade value (either exports or imports)
of the product is at least 10% or more of its larger trade value (either exports or imports),
which serve as the evidence of significant simultaneous exports and imports. The
formula used to identify the presence of IIT for each product is as follows:
ACSit ACSit
ACSit ACsit (1)
where ACSit represents each ASEAN-5 country, A, exports of product S of SITC 8 to
China, C, at period t while MACSit represents each ASEAN-5 country, A, imports of
product S of SITC 8, from China, C, at period t. Furthermore, VIIT involved a substantial
gap between unit values of exports and imports (Fontagne and Freudenberg, 1997). As
such, unit values of exports and imports for each IIT product will be computed by
dividing trade value by the corresponding trade quantity. If the difference between the
unit values of exports and imports is greater than 25%, it is considered a VIIT product.
The following equations with dispersion factor of 25% are used to decompose IIT
products into VIIT products:
UVXACsit/UV
MACsit>1.25 (2)
UVXACsit/UV
MACsit<1/1.25 (3)
where UVXACsit represents unit value of product S of SITC 8, exported to China, C, by
each ASEAN-5 country, A, at time t and UVM
ACsit represents unit value of product S
of SITC 8, imported from China, C, by each ASEAN-5 country, A, at time t.
Based on the analysis above, the aggregate of the VIIT indices between each ASEAN-5
country and China in SITC 8 can be calculated for each year. The formula to compute
aggregate VIIT indices for each year is expressed as follows:
ACsit ACsit
ACsit ACsit
(4)
where
refers to VIIT index.
We adopted the spatial panel model to identify the determinants that enhanced the VIIT
relationship between ASEAN-5 countries and China in SITC 8. Spatial panel model is
appropriate for this study as intra ASEAN-5 trade have been increasing substantially after
the formation of AFTA in 1993 (ASEAN Statistical Yearbook, 2003). We strongly
believed that the existence of spillover effects among ASEAN-5 countries is present.
Fixed effects are used in this study as Xing (2007) noted that the estimators of fixed
effects are able to produce unbiased estimation if the unobserved variables are correlated
with the regressors. Furthermore, this study analyzes the VIIT between ASEAN-5 and
China, each cross sectional unit (each ASEAN-5 country) has its own fixed intercept
value, and therefore fixed effect is more appropriate than random effect.
The computed VIIT indices will serve as the dependent variable in the econometric
model. Meanwhile, ASEAN-5’s FDI in China (thereafter, FDI), differences in GDP
between each ASEAN-5 country and China (thereafter, DGDP), trade openness
(thereafter, TO) and spatial interaction effect of VIIT (thereafter, SVIIT) will serve as the
explanatory variables. The explanatory variables are taking on board in line with the
theoretical requirements of production fragmentation theories and the findings of
previous studies. Based on theoretical expectation, the coefficient of FDI will have a
positive sign if the motive of ASEAN-5’s FDI in China is efficiency seeking and the
processing trade attributable to production fragmentation is actively taking part (Xing,
2007; Turkcan, 2010 and Thorbecke and Smith, 2010). DGDP, which serve as the proxy
for the difference in market sizes between the trading partners, is expected to have a
negative sign (Grossman and Helpman, 2005). The production fragmentation theory
postulates that the production processes are divided into a few sequential stages in
different countries. Therefore, if the market size between the two trading partners is
similar and less divergent, trade coordination work can be carried out more smoothly,
thereby reducing the service linked cost (Kimura and Ando, 2005, Grossman and
Helpman, 2005). Besides, Carbaugh (2009, p.9) pointed out that trade openness serves as
an indicator on how important international trade is to a country’s economy while Xing
(2007) revealed that trade openness is the proxy of trade liberalization. Hence, it is
expected that VIIT can be stimulated if the trade between ASEAN-5 countries and China
is more liberalized (Falvey, 1981). On the other hand, according to Tran (2010), distance
is not considered as one of the important variables as geographic attributed as being
neighboring countries are assumed to be the primary reason for the establishment of
CAFTA (China –ASEAN Free Trade Area). Furthermore, Eicheengreen et al. (2004)
also revealed that distance is not powerful when explaining trade with neighboring
countries. Besides, Dees (2001) as cited by Agnes and Ahima, 2003) noted that only
ordinary trade is sensitive to exchange rate changes while Xing (2011) and Tharbecke
(2010) revealed that the impact of exchange rate has less impact on China’s processing
trade. In addition, our preliminary study found that exchange rate and GDP per capita are
not significant in this study. Therefore, distance, exchange rate and GDP per capita
which are prevalent in some trade models are not included in this study.
The spatial panel model is divided into three types, namely spatial lag, spatial
error and spatial Durbin. Based on Elhorst (2010b), the model that involved spatially
lagged dependent variable and/or spatially lagged independent variables is known as
spatial lag model while spatial error model contains spatial autoregressive process in the
error term. The latest type of spatial panel model, advocated after 2007, is known as
spatial Durbin model (Elhorst, 2010a). Spatial Durbin model accounted for both spatially
lagged and spatially autocorrelated error terms. Prior to estimation, all of the variables
except VIIT and SVIIT are in the form of logarithms. The specification of the spatial lag,
spatial error and spatial Durbin models are formulated as follows:
(5)
(6)
(7)
where represents VIIT for cross sectional unit i (each ASEAN5 country) at time t
(i=1... to 5; t=1,...,17). Both and refer to spatial autocorrelation coefficient and the
coefficient of it respectively. represents 1xN vector of explanatory variables in the
form of X. X include FDI, DGDP and TO. On the other hand, M is the weight matrix,
which describes the arrangement of the spatial units and measures the spatial interaction
among ASEAN-5 countries. The weight matrix can be specified in several ways. This
study adopted row standardized contiguity matrix as all ASEAN-5 countries are treated
equally under AFTA. The row standardized contiguity matrix is expressed as follows:
(8)
where equals to 1 if i and
equals to 0 if i . Besides, is the i, jth
element of a prespecified nonnegative NxN spatial weights matrix and represents
constant term parameter. i and t represent the spatial specific effect, which control for
each space-specific time-invariant variable and the time-period specific effect, which
control for each time-specific spatial-invariant effects respectively. Nevertheless,
refers to potential heteroskedastic error term while represents the error term of unit ,
which is depends on the error terms of its neighboring unit j at time, t based on spatial
weights matrix and . from equation 7 refers to the coefficient of i t. Meanwhile,
both i i t and i it
denote the spatial interaction effect of each
explanatory variable (FDI, DGDP, TO) and dependent variable (VIIT) respectively,
among ASEAN-5 countries with China.
To normalize the difference of GDP between each ASEAN-5 country and China, the
following measurement is adopted:
(9)
where GDPc is the GDP of China while GDPA is the GDP of each ASEAN-5 country.
Besides, Carbaugh (2009, p.9) noted that the formula to compute TO is as follow:
TO=[Exportsc + Importsc]/GDPA (10)
where Exportsc and Importsc refer to each ASEAN-5 country’s exports to China and
imports from China in SITC 8, respectively.
A selection framework which is divided into two parts, namely specific to general
approach and general to specific approach will be carried out to determine whether
spatial lag, spatial error or spatial Durbin model is the most appropriate for the data using
classic LM test (Elhorst, 2010b). Based on this framework, if both approaches are in
favor of either spatial lag or spatial error model, the said model will be adopted to treat
the data. Otherwise, if the former approach is favorable to both spatial lag and spatial
errors model whereas the latter approach is in favorable to spatial Durbin model, then the
spatial Durbin model is deemed to be the most appropriate model in treating the data.
Definition and Source of Data
The GDP and FDI data are extracted from CEIC database. Meanwhile, the trade data of
SITC 8, with 4-digit code are derived from UN Comtrade Database, SITC Revision 3.
The number of products selected for Indonesia, Malaysia, Philippines, Singapore and
Thailand are 81, 59, 63, 53 and 98, respectively. All the data are annual statistic from
1993 to 2009.
EMPIRICAL RESULTS
The decomposition results revealed that VIIT indices exhibited a stable and increasing
trend between each ASEAN-5 country and China. From Table 1, the average VIIT
indices throughout the study period are 0.896, 0.879, 0.919, 0.728 and 0.791 for
Indonesia, Malaysia, Philippines, Thailand and Singapore, respectively.
TABLE 1. THE VIIT INDICES BETWEEN ASEAN-5 AND CHINA IN SITC 8
Year Indonesia Malaysia Philippines Singapore Thailand
VIIT VIIT VIIT VIIT VIIT
1993 1.000 0.569 1.000 1.000 0.823
1994 0.882 0.929 1.000 1.000 0.530
1995 0.949 0.909 1.000 0.780 0.936
1996 0.571 0.956 1.000 0.941 0.748
1997 1.000 0.967 0.978 0.719 0.851
1998 0.917 1.000 1.000 0.656 0.886
1999 0.940 0.985 1.000 0.777 0.645
2000 0.972 0.974 1.000 0.788 0.866
2001 0.879 1.000 1.000 0.974 0.437
2002 0.891 0.844 0.550 0.975 0.853
2003 0.794 0.822 1.000 1.000 0.830
2004 0.888 0.976 1.000 0.401 0.853
2005 0.814 0.720 1.000 0.197 0.820
2006 0.895 0.943 0.740 0.465 0.731
2007 0.909 0.918 0.784 0.800 0.950
2008 0.925 0.565 1.000 0.168 0.786
2009 1.000 0.861 0.578 0.727 0.901
Source: Authors’ Compilation
Note: The data above have been published by the authors in 2013 at Labuan Bulletin of
International Business & Finance 11: 42.
The decomposition result is consistent with the findings of Yong et. al. (2013), Zhao et
al. (2010), Kimura (2006), Fukao et. al. (2003) and Hurley (2003) as it confirms that IIT
between each ASEAN-5 country and China is prone to processing trade which is
attributable to VIIT. This signifies that VIIT is crucial in bilateral trade between each
ASEAN-5 country and China. As such, it is noteworthy to identify the determinants of
VIIT using spatial econometrics. The results of panel estimation are presented in Table 2
and Table 3.
TABLE 2: ESTIMATION RESULTS OF VIIT BETWEEN ASEAN-5
COUNTRIES AND CHINA USING PANEL DATA MODELS WITHOUT
SPATIAL INTERACTION EFFECTS
Determinants Pooled OLS
Spatial Fixed
Effects
Time-period Fixed
Effects
Spatial and Time-
period Fixed Effects
GDP -0.044(-0.519) 0.500(0.990) -0.040(-0.468) 0.902
FDI -0.061(-1.802) -0.073(-0.791) -0.059(-1.692) * -0.022(-0.210)
TO 0.071(4.722) *** 0.072(4.703) *** 0.071(4.025) *** 0.071(3.980) ***
Intercept -0.018(-0.042)
R2 0.327 0.342 0.45 0.481
Adjusted R2 0.3 0.278 0.287 0.28
LogL 51.839 52.761 59.909 62.24
LM spatial lag 26.134 27.361 35.975 38.467
LM spatial
error 463.774 535.255 135.295 141.964
Notes: Number of observations = 85. t-values are provided in parentheses. Asterisk ***, ** and
* denotes level of significance at 1%, 5% and 10% respectively. The critical value for LM test at
5% significance level is 7.815.
Table 2 shows the econometric results derived from specific to general approach. From
Table 2, the null hypothesis of no spatial lag and no spatial autoregressive process in the
error term must be rejected. This implies the presence of spatial interaction effects in the
model and therefore spatial Durbin model best describe the data. Besides, the test results
pointed to spatial and time-period fixed effects as the two determinants, R2 of 0.481 and
LogL of 62.64 are of the highest value in comparison with the other three specifications.
As such, spatial Durbin model with spatial and time-period fixed effects is adopted to
carry out the estimation. The econometric estimation results are shown in Table 3.
TABLE 3: ESTIMATION RESULTS OF VIIT BETWEEN ASEAN5 COUNTRIES
AND CHINA: SPATIAL DURBIN MODEL SPECIFICATION WITH SPATIAL
AND TIME-PERIOD FIXED EFFECTS
Determinants Spatial and Time-period Fixed Effects
DGDP -0.046(-0.331)
FDI(-1) 0.011(0.694)
SVIIT -2.251(-29.478)***
TO 0.021(4.338)***
R2 0.969
Adjusted R2 0.956
LogL 174.416
Wald test spatial error 1178.27(p=0.000)***
LR test spatial error 247.431(p=0.000)***
Notes: Number of observations = 85. t-values are provided in parentheses. Lags are chosen
Based on AIC and SC and Asterisk ***, ** and * denotes level of significance at 1%, 5% and 10%
respectively.
From Table 3, the high value of R2 and adjusted R
2, which are 0.969 and 0.956
respectively, indicate the appropriateness of the model specification. To further examine
whether spatial Durbin model can be simplified to spatial error model, both Wald test and
LR test (general to specific approach) are adopted. Both results of Wald test and LR test
simultaneously infer that the spatial Durbin model cannot be simplified to spatial error
model at 1% significance level. Hence, the null hypothesis of spatial Durbin model can
be simplified to spatial error model must be rejected. The results further ascertain that
the spatial Durbin model is appropriate for the estimation. This model generalizes both
spatially lagged dependent variable and spatially autocorrelated error terms.
Based on the estimation results, SVIIT is the most prominent determinant of
VIIT between ASEAN-5 countries and China in SITC 8. It is negative and statistically
significant at 1% significance level. This infers the presence of spillover effects of VIIT,
and there is intense competition among ASEAN-5 countries in relation to VIIT with
China in SITC 8. Such competition should be minimized in order that each ASEAN-5
country can sustain the bilateral VIIT with China in this manufacturing sub-sector.
Besides, the coefficient of TO has the expected theoretical sign and is significant
at 1% significance level. Trade openness reduces trading costs and service costs that were
needed to link up various locations. Therefore, trade openness provides greater
opportunity for production fragmentation and results in greater intensity of VIIT between
ASEAN-5 countries and China. This finding is consistent with Zhang and Li (2006) and
Yi (2003). With the estimated coefficient TO of 0.021, if trade is liberalized by 1%, the
VIIT between ASEAN-5 countries and China will be stimulated by 0.021%. Contrary to
the theoretical expectation, the results revealed that both DGDP and FDI are not
significant. These findings imply that both variables are not important in determining
VIIT between ASEAN5 countries and China in SITC 8 as the products under SITC 8 are
mainly traditional labor-intensive products which are less affected by the inflow of
foreign direct investment or the changes of market size between trading partners.
Additionally, the fragmentation of production processes has occurred to a large extent
and cross border FDI flows is no longer a necessity for vertical production integration
and networking.
CONCLUSIONS
This study aims to identify the determinants of VIIT between ASEAN-5 and China in the
miscellaneous manufacturing sector (SITC 8) using spatial panel model. This study
found that trade openness plays a significant role in VIIT between ASEAN-5 countries
and China. This implies that VIIT between ASEAN-5 countries and China can be
stimulated in SITC 8 if the trade in these two regions is further liberalized. As a result,
the full implementation of CAFTA since January 2010 might provide a platform to
expand the VIIT in SITC 8 between ASEAN-5 countries and China.
Furthermore, the econometric estimation confirms the presence of spatial
interaction effects among ASEAN-5 countries in relation to China’s trade. The negative
sign of SVIIT shows that ASEAN-5 countries are competing among each other to
undertake VIIT with China. To transform the competition into complementation among
ASEAN-5 countries, ASEAN Economic Community (AEC) can play a pivotal role. The
establishment of AEC with one single market for merchandise, services and factors of
production which is estimated to materialize in 2015 will be a good channel for each
ASEAN-5 country to leverage their comparative advantage respectively, and as a whole
sustain the bilateral trade with China in SITC 8. In light of the importance of AEC, close
supervision and monitoring of trade practices and processes are vital in order that the
enforcement and implementation of its programs can be carried out effectively.
ENDNOTES
*Acknowledgement
We would like to thank the anonymous reviewers for their invaluable comments and suggestions.
The remaining errors are our own.
1 VIIT refer to trade in ‘vertical differentiated’ products within the similar industry distinguished by
quality and price (OECD Glossary of of Statistic, 2007). 2 The production processes are divided into a few sequential stages in different countries depending
on the differences of factor costs among countries within the same production network. 3 ASEAN-5 is the common and widely accepted abbreviation for the 5 founder members of
ASEAN, namely Indonesia, Malaysia, Philippines, Singapore and Thailand. 4 CMLV consists of Cambodia, Myanmar Laos and Vietnam.
REFERENCES
Agnes, B. and Amina, Q., “Trade Linkages and Exchange Rates in Asia: The Role of
China”, 2003, CEPII Wprking Paper No 2003-21, C n r d’E ud s
Prosp c v s d’Informa ons In rna onal s, Paris.
Ando, M., “Fragmentation and Vertical Intra-industry Trade in East Asia”, North
American Journal of Economics and Finance, 2006, Vol. 17, pp .257-281.
Andresen, M. A., “A Cross-Industry Analysis of Intra-Industry Trade Measurement
Thresholds: Canada and the United States, 1988-1999”, Empirical Economics,
2010, Vol. 38, pp .793-808.
Athukorala, P., “Production Networks and Trade Patterns in East Asia: Regionalization
or Globalization?”, Asian Economic Papers, 2011, Vol. 10, pp. 65-95.
Athukorala, P., “Asian trade flows: Trends, patterns and prospects”, 2012, Japan and the
World Economy, Vol. 24, pp. 150-162.
Balassa, B. and Bauwens L., “Intra-Industry Specialization in A Multi-Country and
Multi-Industry Framework”, 1997, The Economy Journal, Vol. 97, No. 388, pp.
923-939.
Balassa, B. and Bauwens, L., “The Determinants of Intra-European Trade in
Manufactured Goods”, European Economic Review, 1988, Vol. 32, pp. 1421-
1437.
Bergstrand, J. H., “The Heckscher-Ohlin-Samuelson Model, The Linder Hyupothesis and
the Determinatns of Bilateral Intra-Industry Trade”, The Economic Journal,
1990, Vol. 100, No. 403, pp. 1216-1229.
Carbaugh, R. J., International Economics (12th
ed.), 2009, The United States of America:
South-Western Cengage Learning.
Caves, R. E., “Intra-Industry Trade and Market Structure in the Industrial Countries”,
Oxford Economic Papers, 1981, Vol. 33, No. 2, pp. 203-223.
Chantasasawat, B., Fung, K. C., Iizaka, H., and Siu, A., “Foreign Direct Investment in
China and East Asia”, In Third Annual Conference on China Economic Policy
Reform, 2004, Stanford Center for International Development (SCID), Stanford
University, U.S.
Chin, M. Y., Yong, C. C. and Yew, S. Y., “Vertical Intra-Industry Trade between
ASEAN-5 and China in SITC 8”, Labuan Bulletin of International Business and
Finance, 2013, Vol. 11, pp. 30-45.
Eichengreen, B., Rhee, Y. and Tong, H., “The Impact of China on the Exports of Other
Asian Countries”, 2004, Working Paper No 10768, National Bureau of
Economic Research.
Eichengreen, B. and Tong, H., “How China is Reorganizing the World Economy”, Asian
Economic Policy Review, 2006, Vol. 1, pp. 73-97.
Elhorst, J. P, “Applied Spatial Econometrics: Raising the Bar”, Spatial Economic
Analysis, 2010a, Vol. 5, No. 1, pp. 9-28.
Elhorst, J. P., “Matlab Software for Spatial Panels”, In the IVth Conference of the Spatial
Econometrics Association (SEA), 2010b, Chicago, The United States.
Falvey, R., “Commercial Policies and Intra-Industry Trade”, Journal of International
Economics, 1981, Vol. 11, No. 4, pp. 495-511.
Fontagne, L. and Freudenberg, M., “Intra-Industry trade: Methodological Issues
Reconsidered”1997, CEPII Working Paper 97/02, Centre d’Etudes Prospectives
et d’Informations Internationales, Paris.
Fontagne, L., Freudenberg, M. and Gaulier, G., “Disentagling Horizontal and Vertical
Intra-Industry Trade”, 2005, CEPII Working Paper No 2005-10, Centre
d’Etudes Prospectives et d’Informations Internationales, Paris.
Fukao, K., Ishido, H., and Ito, K., “Vertical Intra-industry Trade and Foreign Direct
Investment in East Asia”, 2003, Discussion Paper Series A No.434, The
Institute of Economic Research, Hitotsubashi University, Kunitachi, Tokyo.
Greenaway, D., Milner, C. and Elliott, R. J. R., “UK Intra-Industry Trade with the EU
North and South”, Oxford Bulletin of Economics and Statistics, 1999, Vol. 61,
No. 3, pp. 365-383.
Grossman, G. M. and Helpman, E., “Outsourcing in a Global Economy”, Review of
Economic Studies, 2005, Vol. 72, pp. 135-159.
Grubel, H. G. and Lloyd, P. J., “The Empirical Measurement of Intra-Industry Trade”,
Economic Record, 1971, Vol. 47, No. 4, pp. 494-517.
Helpman, E., “International Trade in the Presence of Product Differentiation, Economies
of Scale and Monopolistic Competition. A Chamberlin-Heckscher-Ohlin
Approach”, Journal of International Economics, 1981, Vol. 11, pp. 305-340.
Hong Kong Trade Development Council, China-ASEAN Free Trade Area (CAFTA)-
mpl ca ons for Hong Kong’s m rchand s xpor s, 2010, Retrieved March, 20,
2011, from http://www.hktdc.com/info/mi/a/ef/en/1X06OJ4B/1/
Hu, X. and Ma, Y., “International Intra-Industry Trade of China”, Welwirtchaftiliches
Archiv, 1999, Vol. 135, pp. 82-101.
Hu, X. and Watkins, D., “The Evolution of Trade Relationships between China and the
EU since the 1980s”, European Business Review, 1999, Vol. 99, No. 3, pp. 154-
161.
Hurley, D. T, “Horizontal and vertical intra-industry trade: The case of ASEAN trade in
manufactures” International Economic Journal, 2003, Vol. 17, No. 4, pp. 1-14.
Ito, T. and Okubo, T., “New aspects of intra-industry trade: Evidence from EU-15
countries”, 2011, Discussion Paper Series RIEB, Kobe University.
Kimura, F., “International Production and Distribution Networks in East Asia: Eighteen
Facts, Mechanics and Policy Implications”, Asian Economic Policy Review,
2006, Vol. 1, pp. 326-344.
Kimura, F. and Ando, M., “Fragmentation and Agglomeration Matter: Japanese
Multinationals in Latin America and East Asia”, North American Journal of
Economics and Finance, 2003, Vol. 14, pp. 287-317.
Koopman, R., Wang, Z. and Wei, S. J., “How Much of Chinese Exports is Really Made
in China? Assessing Domestic Value-Added when Processing Trade is
Pervasive”, 2008, NBER Working Paper Series 14109.
Krugman, P. R., “Increasing Returns, Monopolistic Competition, and International
Trade”, Journal of International Economics, 1979, Vol. 9, pp. 469-479.
Krugman, P. R., “Intraindustry Specialization and the Gains from Trade”, The Journal of
Political Economy, 1981, Vol. 89, No. 5, pp. 959-973.
Lancaster, K., “Intra-Industry Trade under Perfect Monopolistic Competition”, Journal of
International Economics, 1980, Vol.10, pp. 151-175.
Liu, Y. and Luo, H., “Impact of Globalization on International Trade between ASEAN-5
and China: Opportunities and Challenges”, Global Economy Journal, 2004, Vol.
4, Article 6.
Schott, P. K., “Across-Product versus Within-Product Specialization in International
Trade”, 2003, Yale School of Management and NBER.
Tharakan, P. K. M. and Kerstens, B., “Does North-South Horizontal Intra-Industry Trade
Really Exist? An Analysis of the Toy Industry”, Review of World Economics,
1995, Vol. 131, pp. 86-105.
The Economists, Asian Economies crouching tigers, stirring dragons, the Asian
economies are likely to be the first to pull out of the global recession, 2009,
Retrieved July 1, 2013, from http://www.economist.com/node/13649520/print
Thorbecke, W. and Smith, G., “How Would an Appreciation of the RMB and Other East
Asian Currencies Affect China’s Exports?”, Review of International Economics,
2010, Vol. 18, No. 1, pp. 95-108.
Tong, S. Y. and Lim, T. S., “SINO-ASEAN economic integration and its impact on intra-
ASEAN trade”, 2009, EAI Working Paper No.144.
Tran, V. H. , “ Impact of the WTO Membership , Regional Economic Integration and
Structural Change on China’s Trade and Growth”, Review of Development
Economics, 2010, Vol. 14, No. 3, pp.577-591.
Turkcan, K., “Vertical Intra-Industry Trade and Production fragmentation in the Auto-
Parts Industry”, Journal of Industry, Competition and Trade, 2010, Vol. 11, No.
2, pp. 149-186.
Turkcan, K. and Ates, A., “Vertical Intra-Industry Trade and Fragmentation: An
Empirical Examination of the US Auto-Parts Industry”, The World Economy,
2011, Vol. 34, pp. 154-172.
Wong, J. and Chan, S., “China-ASEAN Free Trade Agreement, Shaping Future
Economic Relations”, Asian Survey, 2003, Vol. 43, No. 3, pp .507-526.
Xing, Y., “Foreign Direct Investment and China’s Bilateral Intra-industry Trade with
Japan and the US”, Journal of Asia Economics, 2007, Vol. 18, pp. 675-700.
Xing, Y., “Processing Trade, Exchange Rates, and the People’s Republic of China
Bilateral Trade Balances”, 2011, ADBI Working Paper Series, No. 270. Yi, K. M., “Can Vertical Specialization Explain the Growth of World Trade?”, Journal
of Political Economy, 2003, Vol. 1, No. 111, pp. 52-102.
Yong, C. C., Chin, M. Y. and Yew, S. Y., “Value Added Intra-industry Trade between
ASEAN5 and China”, Actual Problems of Economics, 2013, Vol. 10, No. 148,
pp 540-551.
Zhang, J., Wittheloostuijn, A. V., and Zhou, C., “Chinese Bilateral Intra-industry Trade:
A panel Data Study for 50 Countries in the 1992-2001 Period”, Review of World
Economics, 2005, Vol. 141, No. 3, pp .510-540.
Zhang, Z., “Can Demand from China Shield East Asian Economies from Global
Slowdown?”2008, Working Paper: 19, Hong Kong Monetary Authority.
Zhang, Z. and Hock, O. C., “Trade Interdependence and Direct Foreign Investment
between ASEAN and China”, World Development, 1996, Vol. 24, pp. 155-170.
Zhang, Z. and Li, C., “Country-Specific Factors and the Pattern of Intra-Industry Trade in
China’s Manufacturing”, Journal of International Development, 2006, Vol. 18,
pp. 1137-1149.
Zhao, Y., Fu, W., Wei, W., and Chen, L., “The Impact of Financial Crisis on Textile
Trade between China and ASEAN”, International Economic Studies, 2010, Vol.
36, pp. 1-8.