Evolutionary perspective of international production networks
in the Asia-Pacific region1
(submitted for the 19th International Input-Output Conference, Alexandria, USA, 13-17 June 2011)
Satoshi Inomata, Institute of Developing Economies, JETRO
1. Introduction
The last few decades have witnessed the rapid development of vertical production
networks within the Asia-Pacific region. Production processes are fragmented into several stages and
countries specialize in each production stage according to their own comparative advantages.
In particular, as Pitigala (2009) points out, emerging economies in East Asia have
benefited considerably from the development of vertical production networks. These networks have
enabled them to join at the production stage that best corresponds to their level of technology, with
the result that they have enjoyed rapid trade and output growth.
2. Evolution of regional production networks
In order to investigate the backdrop to the rapid development of vertical production
networks, cross-border supply chains in the Asia-Pacific region will be evaluated from the
perspective of the ”strength” and ”length” of their linkages.
Figure 1 describes the evolution of regional networks over the last two decades. Arrows
represent selected supply chains among the countries of the region, with the direction of the arrows
corresponding to the flow of intermediate products. Each arrow has two features: thickness and
length. The thickness indicates the strength of linkages between industries, while the length, as
measured against the rings in the background, indicates the level of technological fragmentation of
that particular supply chain (see Appendix for the visualization method.)
In 1985, there were only four key players in the region: Indonesia (I), Japan (J), Malaysia
(M) and Singapore (S). The basic structure of the production network was that Japan built up supply
chains from resource-rich countries like Indonesia and Malaysia. In this initial phase of regional
development, Japan drew on a substantial amount of productive resources (natural resources) from
neighbouring countries to feed to its domestic industries.
By 1990 the number of key players had increased. In addition to the four countries already
mentioned, Japan had extended its supply chains for intermediate products to Korea (K), Taiwan (N)
1
This is a modified paper of Chapter VII from WTO and IDE-JETRO (2011).
and Thailand (T). While still relying on the productive resources of Indonesia and Malaysia, Japan
also started to supply products to other East Asian countries, especially to the country group known
as newly industrialized economies (NIEs). This is the phase when the relocation of Japanese
production bases to neighbouring countries, triggered by the Plaza Agreement in 1985, was
accelerating. It saw the building of strong linkages between core parts’ suppliers in Japan and their
foreign subsidiaries.
Then in 1995, the United States (U) came into the picture. It drew on two key supply
chains originating in Japan, one via Malaysia and the other via Singapore. These two countries came
to bridge the supply chains between East Asia and the US. Also to be noted is the length of the
arrows between Malaysia and Singapore. Compared to others, their shortness indicates that the
supply chains involve fewer production stages, suggesting that the degree of processing is relatively
low. It is considered that the product flows between these countries are distributional rather than
value-adding.
In 2000, on the eve of its accession to the WTO, China began to emerge as the third
economic giant. The country entered the arena with strong production linkages to its geographical
neighbours, Korea and Taiwan, and then gained access to Japanese supply chains through the latter.
The United States also brought a new supply chain from the Philippines (P). So the basic structure of
the tri-polar production network in the Asia-Pacific region was completed.2
The regional production networks thereafter showed dramatic development. By 2005, the
centre of the network had completely shifted to China, pushing the United States and Japan to the
periphery. China became the core market for intermediate products, from which final consumption
goods were produced for export to the US and European markets. Also of note is the nature of the
supply chains that China develops with others. The notable length of the arrows surrounding China
indicates that the supply chains towards China are characterized by a high degree of fragmentation
and sophistication, incorporating substantial amounts of value-added from each country involved.
The competitiveness of Chinese exports, therefore, is not only attributable to its cheap labour force,
but also stems from the sophisticated intermediate products it receives from other East Asian
countries, as embedded in goods labelled “Made in China”.
2
Interestingly, none of the poles, i.e. the USA, Japan and China, shows a direct linkage to either of the others.
Instead, they are mutually connected only through the supply chains of other East Asian countries. This feature
persisted even in 2005.
Figure 1: Evolution of regional production networks, 1985-2005
Source: Drawn by the author.
Figure 1: Evolution of regional production networks, 1985-2005 (continued)
Source: Drawn by the author.
3. Cross-border transfer of value-added in the Asia-Pacific region
The evolution of regional production networks as illustrated above has fostered a
distinctive structure of the production system in the Asia-Pacific region, i.e. the “tri-polar trade
through China” (Figure 2), whereby: (1) East Asian countries, except China, produce
sophisticated parts and components and export them to China, and (2) China assembles them
into final products, (3) these are further exported to the US markets for consumption.
Figure 2: “Tri-polar trade” through China
CHINA
Parts and
Components
Final
Consumption
Goods
Other
East
Asia
USA
Source: Drawn by the author.
The development of “tri-polar trade through China” has significantly enhanced China’s
presence in the region, as demonstrated in Figure 3. The figure shows cross-border transfers of
value-added for the years 1985 and 2005 (see the technical notes for the calculation method.) The
vertical axis indicates the degree of value-added that each country is able to obtain from a given
level of final demands of other countries in the region (the value-added gain potential). The
horizontal axis shows the degree of value-added that each country can “give out” to others in the
same fashion (the value-added give-out potential). It is apparent from the figure that China’s
presence has dramatically increased over the last two decades, while the influence of the United
States and Japan shows a sharp decline.
Figure 3: Cross-border transfer of value-added in the Asia-Pacific region, 1985 and 2005
VA Gain Potential
5.0
1985
2000
4.5
4.0
3.5
3.0
China
Japan
2.5
2.0
1.5
USA
1.0
0.5
0.0
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0
VA Give-out Potential
Sources: The Asian International Input-Output Table, 1985 and 2005 (preliminary), IDE-JETRO
Due to their relative size, other economies in the region are less significant players in
terms of shaping the structure of value-added distribution. Nevertheless, if we look more closely at
the cluster by origin (Figure 4), it turns out that most of them have advanced in at least one of the
two “potentials”, indicating that they have become more involved in regional production networks
over the decades. It is considered that these emerging economies, as a group, now have a significant
influence on the distribution of regional value-added.
Figure 4: Cross-border transfer of value-added in the Asia-Pacific region, 1985 and 2005,
Small economies
VA Gain Potential
1.0
1985
2000
0.9
Korea
0.8
0.7
Taiwan
0.6
China 1985
0.5
Malaysia
Indonesia
0.4
Thailand
0.3
0.2
Singapore
Philippines
0.1
0.0
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
VA Give-out Potential
Sources: The Asian International Input-Output Table, 1985 and 2005 (preliminary), IDE-JETRO
4. Conclusion
This paper investigated the evolution of the production networks in the Asia-Pacific region
using the Asian International Input-Output Tables constructed by the Institute of Developing
Economies, JETRO.
Firstly, the vertical production network was evaluated from the perspective of the
“strength” and “length” of linkages. Two-dimensional visualisation of regional supply chains
showed the expansion of networks among increasing number of key players, as well as an
incremental shift of the regional core towards China over the last two decades. It is also revealed that
the supply chains in East Asia are characterised with a high degree of fragmentation and
sophistication, incorporating substantial amounts of value-added from the countries involved. The
formation of the “tri-polar trade” structure is envisaged therein.
In order to verify the emergence of the “tri-polar trade” structure, cross-border transfer of
value-added within the region is calculated for the year 1985 and 2005, and the result clearly
elucidated the growing presence of China and a relative decline of the USA and Japan. It is also
shown that other emerging East Asian economies have significantly increased the degree of
integration into the regional production system, contributing to the deepening economic
interdependency in the Asia-Pacific region.
References
Dietzenbacher, E., L. Romero, N.S. Bosma, 2005, “Using Average Propagation Lengths to Identify
Production Chains in the Andalusian Economy,” in Estudios de Economia Aplicada, 23.
Pitigala. N., 2009, ‘Global Economic Crisis and Vertical Specialization in Developing
Countries’, Prem Notes No.133, World Bank.
WTO and IDE-JETRO, 2011, From Trade in Goods to Trade in Tasks: Regional Networks in Global
Supply Chains, WTO, IDE-JETRO
Technical note: Cross-border transfer of value-added
Transfer of value-added from country s to country r can be defined as follows.
ˆ r  L  ys
TVA rs  u'V
where V̂
r
is a diagonal matrix with value-added coefficients of country r in its corresponding
diagonal elements and zeros elsewhere, L is the Leontief inverse of the entire region, and ys is a final
demand vector of country s, and u is a summation vector. The calculated results are then
standardised by taking a deviation of each country’s total figure from the regional grand average, to
give indices of value-added gain potentials and give-out potentials.
Appendix: Visualisation of supply chains
The conventional approach to this kind of problem-settings is the linkage analysis, which
generally concerns to measure the “strength” of interconnectedness among industries. The
magnitude of backward and/or forward linkages is calculated between countries, using a
Leontief/Ghosh Inverse matrix of an international input-output table. In this paper, however, a new
perspective for the evaluation of cross-border production networks has been introduced in addition
to the above-mentioned traditional apparatus, by employing the input-output model of Average
Propagation Length (Dietzenbacher et al. 2005).
Average Propagation Lengths (APL) is defined as:
vij = 1*aij /(lij – δij ) + 2*[A2]ij /(lij – δij ) + 3*[A3]ij /(lij – δij ) + ...
   A  



  k A k
k 1 

k
ij
ij
k 1
where A is an input coefficient matrix, aij is its element, lij is a Leontief Inverse coefficient, δij is a
Kronecker delta which is δij =1 if i=j and δij =0 otherwise, and k is a number of production stages
along the path. We also define vij =0 when (lij – δij ) =0.
The first term in the right-hand side of the upper equation shows that the impact delivered
through one-step paths (k=1), i.e. direct impact, amounts to an aij / (lij – δij) share of the total impact
given by the Leontief Inverse coefficient (less unity for diagonal elements). Similarly, two-step paths
(k=2) contribute an [A2]ij / (lij – δij ) share, and three-step paths (k=3) an [A3]ij / (lij – δij ) share of the
total impact. This is evident from L = I + A + A2 + A3 + ... (L: the Leontief Inverse matrix) which is
rearranged as L – I = A + A2 + A3 + ..., and hence (L – I) ij = Aij + [A2]ij + [A3]ij + ....
As an illustrative example, consider the following hypothetical supply chain.
Figure A1: Calculation of Average Propagation Lengths
Industry A
→Industry E
lae = 0.20 (100%)
Ind D
Ind C
(2)
Ind E
l(2) =0.10 (50%)
Ind E
l(4) =0.02 (10%)
Ind E
l(3) =0.06 (30%)
Ind E
l(4) =0.02 (10%)
(1)
Ind A
(1)
Ind B
(2)
Ind C
(3)
Ind D
(4)
(1)
Ind B
Ind D
(2)
Ind C
(3)
(3)
Ind D
(4)
Source: Drawn by the author.
When the share of an impact for each path is calculated as given at the ends of the branches, the APL
between Industry A and Industry E is derived as:
vea = 1 x 0% + 2 x 50% + 3 x 30% + 4 x (10+10)% + 5 x 0% + …= 2.7.
That is, APL is formulated as a weighted average of the number of production stages which an
impact from industry j goes through until it ultimately reaches industry i, using the share of an
impact at each stage as a weight. It represents the average number of production blocks lining up in
every branch of all the production chains, or, in short, an industry’s level of fragmentation.
Using these two types of information, namely, the “length” and “strength” of linkages, the
supply chains can be visualised in the following manner. Table A1 shows the cross-national APL of
Asia-Pacific region in 1985, by country of origin (the left column) and country of destination (the
top row). The values of APL have been first calculated at the level of seven industrial sectors
classification, and then aggregated into one sector per one country by taking weighted averages with
output shares as weights.
Table A1: Average Propagation Lengths in the Asia-Pacific region, 1985
China
Indonesia
Japan
Korea
Malaysia
Taiwan
Philippines
Singapore
Thailand
USA
China
Indonesia Japan
Korea
Malaysia
Taiwan
Philippines Singapore Thailand
USA
1.8674
3.4504
3.2107
4.5588
3.0997
4.5971
2.8015
2.7277
2.9738
3.2772
3.3393
1.5864
3.2786
3.2314
3.0524
3.3527
2.6780
2.6759
3.1936
3.2678
3.8466
3.4879
1.9692
3.7480
3.3585
3.9038
3.5763
3.3932
3.5235
3.7607
5.2438
3.1869
3.3571
1.8375
3.0942
3.6302
3.0966
3.0196
3.3535
3.4505
3.4133
3.1973
3.3019
3.2717
1.5866
3.3001
2.5959
2.4819
2.8529
3.2000
3.7009
3.1685
3.3291
3.6398
3.1440
1.9199
3.2786
3.0062
3.2946
3.3756
3.3918
3.0556
3.4123
3.3396
2.8393
3.4527
1.6927
2.8753
3.0280
3.2244
3.3371
2.4422
3.1020
3.1589
2.6082
3.2849
2.9755
1.5075
2.8025
3.0902
3.4312
2.9161
3.4696
3.4831
2.7493
3.4509
3.0413
2.7434
1.7218
3.1804
3.8256
3.2629
3.7400
3.6222
3.4416
3.6820
3.4055
3.3424
3.3078
1.8417
Source: The Asian International Input-Output Table, 1985, IDE-JETRO
Then, we refer to the “strength” of linkages, as defined as a simple element-to-element
average of Leontief inverse coefficients (less unity for diagonals) and Ghosh inverse coefficients
(less unity for diagonals). If the strength of linkage is less than 0.018, this particular supply chain is
omitted from the picture (=> a blank cell in the APL table). If, on the other hand, the strength
registers more than 0.025, this supply chain is considered as a cardinal path (=> a bold number in the
APL table). The result of the operation gives the following new APL table. Note that we only
consider cross-national linkages (= off-diagonals), and that the values have been rounded up into
integers.
Table A2: Screened-out Average Propagation Lengths in the Asia-Pacific region, 1985
China
China
Indonesia
Japan
Korea
Malaysia
Taiwan
Philippines
Singapore
Thailand
USA
Indonesia
Japan
Korea
Malaysia
Taiwan
Philippines Singapore
3
Thailand
USA
3
2
3
3
Source: The Asian International Input-Output Table, 1985, IDE-JETRO
The information given in Table A2 is mapped into the diagram in Figure 1, for the supply
chains among Indonesia, Japan, Malaysia and Singapore in the case of the year 1985.