Deepening and Widening of Production - Am MIT spezialisierte KI-Forschung

Deepening and Widening of Production
Networks in ASEAN∗

Ayako Obashi
Toyo University and Keio University
5-28-20 Hakusan, Bunkyo-ku
Tokio 112-8606, Japan
obashi@toyo.jp

Fukunari Kimura
Keio University and Economic Research Institute

for ASEAN and East Asia (ERIA)

2-15-45 Mita, Minato-ku
Tokio 108-8345, Japan
fkimura@econ.keio.ac.jp

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Abstrakt
This paper assesses the recent widening and deepening of machinery production networks in ASEAN
by using highly disaggregated international trade data over 2007–13. Based on both traditional trade
value data analysis and a novel approach to the diversiﬁcation of exported products and destinations,
we conﬁrm the steady development of back-and-forth trade links, notably with East Asian partners,
centering on Singapore and Thailand. In addition to the ﬁve ASEAN forerunners, Vietnam is an in-
creasingly active player in such networking. Although their degree of participation is still limited, Nocken-
bodia, Lao PDR, and Myanmar also show signs of joining production networks.

1. Einführung

Cross-border fragmentation of the production process into geographically separated
Stufen, or global production sharing, has evolved into a network of back-and-forth trade
links in East Asia and other parts of the world. The development of such international
production networks is reﬂected in an expansion of international trade, especially in
trade of intermediate goods. To assess the extent and depth of these production networks,
previous studies have attempted to quantify the magnitude and reveal the patterns and
determinants of trade taking place within the networks (for an overview of the existing
approaches used to capture trade within the networks, see Athukorala 2011). In line with
this literature, we examine to what degree less-developed ASEAN countries have also

∗ We would like to thank Prema-chandra Athukorala, Fredrik Sj ¨oholm, Chalongphob Sussangkarn,
and other participants at the Asian Economic Panel Meeting in Tokyo, September 2015 for their
valuable comments and suggestions.

Asian Economic Papers 16:1

C(cid:3) 2017 by the Earth Institute at Columbia University and the Massachusetts

Institute of Technology

doi:10.1162/ASEP_a_00479

Deepening and Widening of Production Networks in ASEAN

started to become involved in international production networks. We also look at how
already-active players in production networks have deepened their participation, by mak-
ing full use of product-level trade data with a focus on the product and destination diver-
siﬁcation in each countries’ exports of intermediate goods.

Participation in production networks is crucial in the development strategies of ASEAN
Länder. ASEAN and surrounding East Asian countries entered an era of international
production/distribution networks (Ando and Kimura 2005), or the “second unbundling”
(Balduin 2011), in the mid-1980s. Unlike Japan, the Republic of Korea, and Taiwan in the
1950s to 1970s—when much more gradual industrialization with trade protection was at
the center of their development strategies—Southeast Asian countries and China can uti-
lize the mechanics of production fragmentation, particularly in the machinery industry, Zu
jump-start and upgrade industrialization. Although we can also observe the development
of production networks in other parts of the world, including Latin America and Eastern
Europa, ASEAN and East Asian countries are the most advanced in terms of geograph-
ical extension and the sophistication of their production networks. Jedoch, Weil
ASEAN countries have different historical backgrounds and economic systems, and are
at different stages of development, the degree of participation in production networks
differs widely across countries. Latecomers to ASEAN, such as Cambodia, Lao People’s
demokratische Republik (PDR) and Myanmar, are still in the initial stages of participating in
production networks. Vietnam, the Philippines and Indonesia are struggling for deeper
involvement in production networks, while Thailand, Malaysia, and Singapore are seek-
ing pathways toward more sophisticated means of utilizing production networks. In der Tat,
how to take full advantage of the mechanics of production networks is a central theme
of industrial development plans in each country and in ASEAN economic integration, als
presented in the ASEAN Economic Community Blueprint (ASEAN 2007) and the Master
Plan on ASEAN Connectivity (ASEAN 2010). In view of this, Kimura and Obashi (2010)
undertook a thorough survey of this issue using international trade data.

The current paper concentrates on assessing the degree of involvement of ASEAN coun-
tries in international production networks in the machinery industry. To explore partici-
pation in production networks, we aim to quantify the magnitude of international trade
occurring within networks by utilizing highly disaggregated international trade data
for machinery parts and components at the Harmonized System (HS) six-digit product
Ebene. In so doing, we focus our attention on a key aspect of the increased involvement
in production networks: networks of back-and-forth trade links of machinery parts and
components, especially inside the East Asian region. In addition to Singapore, Malaysia,
Thailand, Indonesien, and the Philippines, Vietnam is an increasingly active player in such
production networks. Andererseits, Brunei, Kambodscha, Lao PDR, and Myanmar
are relatively limited in terms of their integration into production networks, although
these countries are expanding their formation of trade links for a wider range of products

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Deepening and Widening of Production Networks in ASEAN

with a wider range of trading partners. Konkret, departing from simply looking at the
value of exports, we count the number of products exported, the number of destination
market countries across products, and the number of product-destination pairs in sev-
eral informative ways, to reveal the patterns of diversiﬁcation of exported products and
destination markets.

From the perspective of export product and destination diversiﬁcation, we document
that ASEAN countries, centering on Singapore and Thailand, have widened the range
of products exported and the geographic scope of their respective destination markets.
Even more strikingly, Singapur, Thailand, and other already-active players have deep-
ened their participation in production networks by exporting already-exported products
to new destination countries to which these countries had not previously provided these
Produkte. Production networks are widening by involving more exporters of products,
and are also deepening by increasing the number of non-zeros in the product-level bilat-
eral trade matrix.

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The remainder of this paper proceeds as follows: Abschnitt 2 begins by comparing ASEAN
countries and other countries by using the proportion of machinery parts and compo-
nents in total exports and imports of manufactured goods. Abschnitt 3 examines the de-
gree of participation of ASEAN countries in international production networks in the
machinery industry, from the perspective of export product and destination diversiﬁ-
cation. To help us to understand the observed patterns of export product and destina-
tion diversiﬁcation, Abschnitt 4 offers a statistical analysis of the probability that a product
is exported from a particular origin country to a particular destination country, apply-
ing gravity logic to the incidence of zeros in terms of global production sharing. Endlich,
Abschnitt 5 concludes.

2. Preliminary analysis using trade value data

Given the fact that ASEAN countries and other East Asian countries are, and have been,
highly dependent on trade in machinery, we focus on the machinery industry to explore
the involvement of ASEAN countries in international production networks. In order to
assess the degree of involvement in machinery production networks, we aim to quantify
the magnitude of international trade occurring within these networks. Trade within these
networks encompasses the export of intermediate goods and semi-ﬁnished products, Und
also includes the export of ﬁnished products assembled or manufactured, using imported
intermediate inputs.

To quantify the magnitude of trade within production networks for less-developed
ASEAN countries, as well as the forerunners, we make full use of international trade
data from the UN Comtrade database, which is publically available for a wide range of

Asian Economic Papers

Deepening and Widening of Production Networks in ASEAN

Länder. From the standpoint of reliability, we use import statistics throughout the pa-
pro (even when we analyze a country’s exports). Import statistics are regarded as more
reliable because a country of origin is more closely veriﬁed because of tariff regulations,
and the ﬁnal destination may not be known at the time of export.1 To count the number
of products traded and the number of trading partner countries in a consistent manner (In
Abschnitte 3 Und 4), we try to avoid any issues arising from mergers or branching of product
codes due to classiﬁcation updates. We therefore construct a data set for bilateral trade
ﬂows at the six-digit level of the 1996 version of the HS product classiﬁcation for both
2007 Und 2013. The data set consists of 139 Länder, including all East Asian countries of
interest.2 Using the data set, we analyze all potential bilateral trade ﬂows, including zero
ﬂows, zwischen 19,182 (= 139 × 138) exporter–importer pairs at the product level.3

Based on the HS classiﬁcation, manufactured goods range from HS 28 to HS 92. Among
ihnen, machinery includes all goods classiﬁed as part of general machinery (HS 84), elektr-
tric machinery (HS 85), transport equipment (HS 86–89) and precision machinery (HS
90–92). We group respective HS product codes at the most disaggregated level into ma-
chinery parts and components, and ﬁnal products.4

Let us begin by comparing countries using the proportion of machinery, in particular ma-
chinery parts and components, in their total exports and imports of manufactured goods.
The higher the percentage of machinery parts and components in exports or imports, Die
more deeply a country is considered to be integrated into machinery production networks
relative to trade in other manufacturing sectors. In Abbildung 1, a pair of stacked bars shows
the percentages of machinery in a country’s manufacturing exports (left-hand bar) Zu, Und

1 By using import statistics, we avoid the need to tackle data issues such as the one emerging from
Hong Kong’s important role in re-exporting goods from China to the rest of the world (and in the
opposite direction).

2 East Asia here is deﬁned as the so-called ASEAN+6, nämlich, ASEAN member countries, the Peo-
ple Republic of China (Jenseits, China), Japan, the Republic of Korea, Australia, Neuseeland
(Jenseits, NZ) and India. Because the statistical territory of China’s external trade statistics co-
incides with its customs territory that does not cover separate customs territories of Hong Kong
and Macau, the UN Comtrade database (our source of data) practically treats mainland China and
those Special Administrative Regions separately. We include only mainland China as “China” and
exclude the Special Administrative Regions from our data set.

3 For the details of the construction of our data set, see Obashi and Kimura (2016). The total value of
bilateral trade covered by our data set accounts for more than 90 percent of annual total imports to
all reporter countries available in the UN Comtrade database from all partner countries for which
International Standards Organization (ISO) 3166-1 alpha-3 country codes are assigned, both for
2007 Und 2013.

4 See Kimura and Obashi (2010) for the list of machinery parts and components at the HS four- Und
six-digit level for different versions of the HS classiﬁcation. Because some parts and components
used in the machinery industry that ranges from HS 84 to HS 92 are classiﬁed under the HS codes
other than the machinery industry (z.B., chemical and basic metal products), we would understate
the magnitude and diversity of machinery parts and components.

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Deepening and Widening of Production Networks in ASEAN

Figur 1. Machinery shares in total manufactures exports to and imports from the world

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Quelle: UN Comtrade database (import statistics, based on the HS 1996 classiﬁcation, at the six-digit level).

Notiz: We use import statistics to construct a data set for bilateral trade ﬂows at the HS six-digit level, consisting of 139 Länder, with a

few exceptions. Machinery industries are deﬁned as HS 84–92. Product groupings (z.B., P&C vs FP) follow Kimura and Obashi (2010). Sehen

text for more details on the data set construction.

Asian Economic Papers

Deepening and Widening of Production Networks in ASEAN

imports (right-hand bar) aus, the rest of the world, jeweils. The dark gray portions
represent the percentages accounted for by parts and components (labelled as P&C), Und
the light gray portions represent ﬁnal products (FP). The bars are in descending order,
from left to right, in terms of machinery parts and components shares in exports. In ad-
dition to ASEAN countries, we include other East Asian countries, selected Central and
Eastern European countries, Costa Rica, Mexiko, and the average ﬁgures for the Union of
South American Nations member countries, as a reference.5

In both years of interest, 2007 Und 2013, Malaysia, die Phillipinen, and Singapore all had
strikingly high percentages of machinery parts and components, reaching almost 40 pro-
cent or even higher, not only in total manufacturing exports but also in imports. Solch
high percentages of machinery parts and components, both for the export and import
sides, appear to reﬂect these countries’ active participation in back-and-forth transactions
of intermediate goods across borders within machinery production networks. Im Gegensatz,
for Costa Rica, the percentages of machinery parts and components reached 70–85 percent
for the export side, whereas the corresponding percentages were below 30 percent for the
import side.

Thailand is also highly dependent on the machinery trade, but shows a different trend:
In 2013, Zum Beispiel, the percentage of machinery parts and components was below
25 percent for the export side, whereas the corresponding percentage reached almost
30 percent for the import side. Gleichzeitig, the percentage of machinery ﬁnal prod-
ucts in exports was relatively high, compared with parts and components, exceeding
35 Prozent. Such a pattern of dependence on the machinery trade is also observed for
China, Mexiko, and Slovakia, and can be considered as indicating these countries’ role
as the world’s factory in machinery production networks, in the sense that they import
a large number of intermediate goods for assembly or for manufacturing products to be
exported back to the countries of origin, or to the rest of the world.

Vietnam, Kambodscha, and Lao PDR experienced noticeable increases in the relative im-
portance of the machinery trade in the period 2007–13. For Vietnam, the percentage of
machinery ﬁnal products in exports more than tripled, aus 10 Prozent zu 35 Prozent,
and the percentage of machinery parts and components in imports almost doubled, aus
18 Prozent zu 33 percent.6 As of 2013, the shape of Vietnam’s stacked bars resembles those
for China, Mexiko, Slovakia, and Thailand, suggesting that Vietnam now performs a simi-
lar role to those four countries, as the world’s factory.

5 The Union of South American Nations includes Argentina, Bolivia, Brasilien, Chile, Kolumbien,

Ecuador, Guyana, Paraguay, Peru, Suriname, Uruguay, and Venezuela.

6 The increasing importance of machinery ﬁnal products in Vietnam’s exports is due largely to
increases in exports of printers by Canon, communication devices by Samsung Electronics,
and others.

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Deepening and Widening of Production Networks in ASEAN

Although Cambodia and Lao PDR, as well as Myanmar, seem still to be far behind other
countries in the sample in terms of their machinery parts and components shares in ex-
ports and imports, they are increasingly dependent on the machinery trade. For Cam-
bodia, the machinery share in exports quadrupled, driven by a surge in machinery parts
and components exports in the period 2007–13, although it remained below 10 Prozent.
For Lao PDR, the percentage of machinery parts and components in imports doubled,
aus 13 Prozent zu 27 Prozent, although the overall machinery share for the export side
remained negligible over the period. These countries reﬂect the so-called “Thailand plus
one” operation between a mother factory in Thailand and a satellite factory in Cambodia
or Lao PDR.

3. Diversiﬁcation of export products and destinations

A key aspect of increased involvement in international production networks is the forma-
tion of trade links for a wider range of products with a wider range of trading partners. In
what follows, departing from simply looking at the value of trade, we turn our attention
to the diversity of exported products and destination market countries in quantifying the
magnitude of trade occurring within production networks. In so doing, we admit that we
miss other important aspects of increased involvement in these networks, such as the vol-
ume of exports through newly formed links relative to long-standing ones. Trotzdem,
we conﬁne the paper’s scope to the diversiﬁcation of exported products and destination
countries because the formation of trade links is of ﬁrst-order importance, especially for
the less-developed ASEAN countries included in our analysis.

From the perspective of the diversiﬁcation of exported products and destination coun-
versucht, the rest of the paper is devoted exclusively to a detailed examination of exports of
machinery parts and components. Although trade within production networks includes
exports of ﬁnished products made from imported inputs as well, we leave an analysis
of exports of machinery ﬁnished products in relation to imports of machinery parts and
components to future research.

Focusing on exports of machinery parts and components, we count the number of prod-
ucts traded and the number of trading partners across products, and analyze patterns
of export product and destination diversiﬁcation. Konkret, we study: (ich) how many
products a country exports to how many destination market countries; (ii) how many of
potential export ﬂows (d.h., product-destination pairs) a country is actually involved in;
(iii) how a country’s export product diversiﬁcation varies across destination countries;
(iv) how a product–destination mix in a country’s exports changes over time; Und
(v) what factors are correlated with the export product and destination diversiﬁcation.

The number of products classiﬁed under machinery parts and components at the six-digit
level of the HS 1996 classiﬁcation is 445, and our data set includes 139 Länder. Wir sind

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Deepening and Widening of Production Networks in ASEAN

interested in how many products, out of the maximum possible number of 445, a country
exports to how many destination countries, out of the maximum number of 138.7

In addition to merely counting the numbers of products exported and destination coun-
versucht, we examine how many potential export ﬂows a country is actually involved in. Fol-
lowing Baldwin and Harrigan (2011), we deﬁne a zero as a country’s export ﬂow (d.h., A
product–destination pair) that could have occurred but did not. Naturally, auf dem anderen
Hand, actually occurring export ﬂows are referred to as non-zeros. Das ist, a zero occurs
when a country exports a certain product at the HS six-digit level to at least one coun-
try but not to all countries. By so doing, zero export ﬂows consist only of goods actually
produced in the country of origin. Außerdem, in identifying a zero export ﬂow, we re-
strict attention to destination countries to which the country of interest exports at least
one product classiﬁed under machinery parts and components. Mit anderen Worten, we ex-
clude exporter–importer pairs with no trade in machinery parts and components at all
from our analyses in this and the following sections.

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3.1 Number of export products and destinations

Tisch 1 provides an initial overview of exports of machinery parts and components to
die Welt, by country. The values of exports in 2007 Und 2013, and the growth rates of
export values between the two years, are reported on the left part of the table. The num-
bers of products exported, the numbers of destination market countries, the numbers of
non-zero product-destination pairs, and the proportions of non-zero to potential product-
destination pairs in 2007 Und 2013, are shown on the right part of the table. The ﬁgures for
ASEAN countries are compared with other East Asian countries.

First and foremost, non-zero export ﬂows occurred only in a limited portion of potential
product–destination pairs of ASEAN countries’ machinery parts and components exports,
even at the HS six-digit level.8 The percentages of non-zero product–destination pairs
ranged from 3.6 Prozent (calculated for Myanmar) Zu 31.6 Prozent (Thailand) In 2013, In-
dicating that zeros made up more than the two-thirds of potential export ﬂows (even for
Thailand), and was more than 96 percent for Myanmar. The predominance of zeros was

7 In the literature on the extensive and intensive margins of trade, there are discussions over

whether to use a ﬁxed cutoff of US$ 0 or alternative cutoffs varying across countries as a mea- sure of traded-ness—that is, whether a product is traded or not in a particular period (Kehoe and Ruhl 2013). As the current paper does not examine margins of trade growth but focuses on count- ing the number of products traded and the number of trading partners, we simply use a cutoff of US$ 0.

8 The predominance of zeros at the HS six-digit level understates the number of zeros at the ﬁrm

level because each HS six-digit code possibly contains products of different ﬁrms that might export
only to a subset of the overall destination mix of the HS six-digit code.

Asian Economic Papers

Deepening and Widening of Production Networks in ASEAN

Tisch 1. Number of products and destinations in machinery parts and components exports
to the world

Exporter
country

Export value
(millions US $)
2013
2007

Growth,
%

N. von
Produkte
2007

2013

N. von
destinations
2013
2007

Shares of
N. of non-zero
non-zero
product-
destination pairs pairs, %
2007

2007

2013

ASEAN member countries
Malaysia
Singapur
Thailand
Philippinen
Vietnam
Indonesien
Kambodscha
Myanmar
Lao PDR
Brunei

72,585
46,939
34,986
43,025
3,361
13,295
4
31
10
7

228,266
241,098
140,333

Northeast Asian countries
China
Japan
Korea
Other East Asian countries
Indien
Australia
NZ

10,565
5,219
1,078

86,462
43,918
38,764
30,266
14,715
12,405
206
52
33
26

344,601
229,652
193,299

16,540
4,820
1,017

19.1
−6.4
10.8
−29.7
337.8
−6.7
4,981.5
66.1
221.3
253.2

51.0
−4.7
37.7

56.6
−7.6
−5.7

439
442
439
421
399
434
157
118
124
151

445
444
438

441
436
419

430
435
428
408
402
422
214
181
139
184

439
437
431

434
427
412

133
134
134
121
113
134
58
41
37
42

136
137
133

135
132
125

132
136
135
129
126
136
71
55
42
46

138
138
137

137
135
128

14,802
17,272
16,036
7,715
4,638
10,129
297
203
181
268

38,623
31,913
23,746

21,231
15,291
6,647

16,836
17,875
18,243
9,404
8,461
12,185
582
359
256
427

43,410
31,141
25,342

25,129
15,934
7,569

25.4
29.2
27.3
15.1
10.3
17.4
3.3
4.2
3.9
4.2

63.8
52.5
40.8

35.7
26.6
12.7

29.7
30.2
31.6
17.9
16.7
21.2
3.8
3.6
4.4
5.0

71.7
51.6
42.9

42.3
27.6
14.4

Quelle: UN Comtrade database (import statistics, based on the HS 1996 classiﬁcation, at the six-digit level), IMF IFS database

(US CPI).

Notiz: We basically use import statistics to construct a dataset for bilateral trade ﬂows at the HS six-digit level, consisting of 139

Länder, with a few exceptions. Machinery industries are deﬁned as HS 84-92, and among them we identify parts and components,

following Kimura and Obashi (2010). Countries are listed in descending order of the total value of machinery parts and components

exports to the world in 2013, by the country group. Export values are deﬂated by the consumer price index (CPI) in the US to obtain

a constant dollar series, and are rounded off to the million. All ﬁgures expressed in percentage terms are rounded off to the tenth.

In our dataset, the maximum possible number of products is 445 and that of destinations is 138. See the text for more details on the

dataset construction.

also common among other East Asian countries, with the exception of China, for which
the incidence of zeros was surprisingly low, bei 28 percent.9

Gesamt, the number of products exported, as well as the number of destination coun-
versucht, varied less from country to country than the value of exports. Erste, Brunei, Cambo-
dia, Lao PDR, and Myanmar are relatively far behind other countries in terms of export
Werte, but are much closer in terms of both the number of products and the number of

9 The predominance of zeros is not special to ASEAN countries’ machinery parts and components
export ﬂows. Zum Beispiel, Haveman and Hummels (2004) found that 27 percent of bilateral im-
port ﬂows (that contain products exported by at least one country in the world) were zeros at
the SITC four-digit level in 1990. Baldwin and Harrigan (2011) document that 82 percent and 93
percent of the United States’ potential export and import ﬂows are zeros, jeweils, at the HS
ten-digit level in 2005. In Baldwin and Harrigan’s method, a zero occurs when a country exports
(imports) a product to (aus) at least one country but not all. At the aggregate country level, In-
stead of the country-product level, Helpman, Melitz, and Rubinstein (2008) found that about half
of the country pairs in their sample covering 158 countries did not trade with each other in the
period 1970–97.

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Deepening and Widening of Production Networks in ASEAN

destinations. Zweite, Malaysia, Singapur, and Thailand have not reached the same level
of export values as Northeast Asian countries, but their exports were almost as diverse as
those countries’ exports, in terms of both the number of products and the number of des-
tinations, as of 2013. As indicated by the percentages of non-zero product–destination
pairs, Jedoch, Malaysia, Singapur, and Thailand still had a far less dense product–
destination mix than Northeast Asian countries.

For Indonesia, Malaysia, die Phillipinen, and Thailand (ASEAN-4), together with Singa-
pore, the number of exported products appears to have already hit a ceiling, showing a
decline in the period 2007–13. In der Zwischenzeit, the number of destination countries trended
upwards with the exception of Malaysia, which experienced a slight decrease. Zusätzlich,
reﬂecting the fact that the number of non-zero product–destination pairs increased sub-
stantially during the period, these countries, even Malaysia, experienced a rise in the per-
centage of non-zeros, indicating that their product–destination mix had become denser,
as well as more geographically diverse. Similar trends were also observed for China, Die
Republik Korea, Indien, Australia, and New Zealand.

Malaysia and Thailand steadily increased their value of exports, although at a less rapid
rate than China, Indien, and the Republic of Korea, in the period 2007–13. Indonesien, Die
Philippinen, and Singapore, andererseits, experienced negative growth in their ex-
port values. Trotzdem, for the latter group of countries, the export product–destination
mix became more geographically diverse and denser, as discussed earlier. For the Philip-
Kiefern, insbesondere, the number of destinations noticeably increased despite the decrease
von 30 percent in export value. This suggests that the Philippines underwent a dramatic
transformation of its product composition from a heavy dependence on narrowly scoped
semiconductor operations to wider-based electric and electronic industries.

Kambodscha, Lao PDR, Myanmar, and Vietnam (CLMV), together with Brunei, have started
exporting more products to more destination countries, while strikingly increasing the
value of exports, over the period 2007–13. The most notable is Cambodia: Obwohl
its product–destination mix remained less diverse than forerunner ASEAN countries,
the number of products and the number of destinations increased by 22 percent and
36 Prozent, jeweils, and its export value increased by a factor of 51 mal.

Vietnam showed a remarkable performance among the CLMV, not only in terms of the
value of its exports, which exceeded even the level of Indonesia in 2013, but also in terms
of the number of exported products and destination countries, and the percentage of
non-zero product-destination pairs. Although Vietnam’s machinery parts and compo-
nents exports seem relatively insigniﬁcant in its total manufacturing exports to the world
(Figur 1), it has diversiﬁed and increased the density of its product-destination mix,
reaching almost the same level as the Philippines in 2013.

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Deepening and Widening of Production Networks in ASEAN

3.2 Distribution of the number of export destinations across products

Figur 2 illustrates how the number of destination market countries in ASEAN countries’
machinery parts and components exports to the world are distributed across products,
comparing 2007 Und 2013. On the horizontal axis, products at the HS six-digit level are
placed in descending order in terms of the number of destination countries for each year.
The horizontal axis ends with 445, the maximum possible number of products classiﬁed
under machinery parts and components. The vertical axis indicates the number of des-
tinations out of the maximum number of 138. The horizontal reference line represents a
country’s overall number of destination countries (Tisch 1). The area that lies below the
reference line and the scatter plot line corresponds to the number of potential and non-
zero product–destination pairs, jeweils. Note that the vertical difference of the two
scatter plot lines does not necessarily indicate a change in the number of destinations for
a particular product, as the order of products differs by year. Stattdessen, comparing scatter
plot lines across years reveals how much the number of destinations changes on average
across products.

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For respective ASEAN countries, only a limited number of products are exported si-
multaneously to a substantial portion of the country’s overall number of destination
Länder. Even for Thailand, which achieved the largest number of non-zero export
product–destination pairs among ASEAN countries in 2013, nur 24 percent of its ex-
ported products were shipped to more than half of the overall number of destinations
(which was 135 out of 138, as in Table 1). The corresponding ﬁgures for the rest of the
ASEAN-4, Singapore and Vietnam, were even smaller, ranging from 3 Prozent (Vietnam)
Zu 20 Prozent (Malaysia). Darüber hinaus, for Brunei and the rest of CLMV, no single product
was shipped simultaneously to half of the country’s overall number of destinations, Und
about half of the country’s exported products were shipped to only one country. Diese
observations illustrate the incidence of zeros in ASEAN’s potential export ﬂows.

Thailand and Singapore serve a remarkably wide range of countries at the product level,
compared with other ASEAN countries. In 2013, Thailand’s top four exported products,
in terms of the number of destinations, were shipped to more than 115 Länder, Und
Singapore’s top four products were exported to more than 110 countries.10 In addition,
these countries’ export product–destination mix was notably dense with their neighboring
countries in the East Asian region: Thailand and Singapore exported 46 Und 44 Produkte,
accounting for 11 percent and 10 percent of the maximum possible number, simultane-
ously to all of the 15 (= 16 − 1) East Asian trade partners, jeweils (see Appendix
Figure A.1 for the intra-East Asian version of Figure 2).

10 All of Thailand’s top four exported products are parts and components and accessories used for
motor vehicles. Singapore’s top four products are parts and accessories of data processing equip-
ment, parts of line telephone and telegraph equipment, and electrical switches.

Asian Economic Papers

Deepening and Widening of Production Networks in ASEAN

Figur 2. Number of destinations in machinery parts and components exports to the world,
distribution across products

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Quelle: UN Comtrade database (import statistics, based on the HS 1996 classiﬁcation, at the six-digit level).

Notiz: See notes of Table 1. Countries are arranged in descending order of the total value of machinery parts and components exports to the

world in 2013.

Asian Economic Papers

Deepening and Widening of Production Networks in ASEAN

Although zero export ﬂows were still predominant among ASEAN members, all coun-
tries widened their geographic scope of export destinations on average across products in
the period 2007–13, in addition to increasing the overall number of destination countries
(except Malaysia, as reported in Table 1). Most notably, Vietnam doubled the number of
destinations at the product level from 11.6 Zu 21 on average. The largest number of des-
tinations at the product level increased from 65 Zu 91 Und, as of 2013, 14 products were
exported to more than 65 Länder. Also noteworthy was that the ASEAN-4, at the fore-
front of export product and destination diversiﬁcation, further increased the number of
destinations at the product-level from 5 Zu 6 on average.

3.3 Number of export products by destination

Looking at another aspect of the diversiﬁcation of ASEAN countries’ machinery parts
and components exports, Figur 3 illustrates how the number of products exported from
a country varies across destination market countries. The horizontal axis indicates the
number of products exported at the HS six-digit level in 2007, ending with the maximum
possible number of 445, and the vertical axis represents the number of products in 2013.
Dots show the numbers of products exported to each of East Asian trade partners and are
labelled with the ISO 3166–1 country codes for the exporter–importer pairs. Gray cross-
marks represent export ﬂows to countries outside the East Asian region, with a few out-
liers, and are labelled with the exporter–importer pair country codes. For reference, Die
45-degree line is shown to help the reader to see if the number of products exported to a
particular country increased or decreased in the period 2007–13.

Gesamt, the numbers of products exported to East Asian trade partners tended to be far
higher than those for destination countries outside the region. In 2013, the average num-
ber of products in intra-East Asian exports was 2.3 (Thailand) Zu 6.4 (Myanmar) times as
large as the average number for exports to countries outside the region. Insbesondere, Die
numbers of products exported to Singapore or Thailand were notably large. In der Zwischenzeit,
Singapore and Thailand exported more than 110 Produkte, or more than one-fourth of the
maximum possible number, to each of the East Asian trade partners, on top of the fact
that they exported about 45 products simultaneously to all the East Asian partners (as dis-
cussed in Section 3.2). Singapore and Thailand appear to have established complicated
back-and-forth trade links for a wide range of machinery parts and components inside
the region. Zusätzlich, the number of products exported to Japan was one of the largest
among Vietnam and the Philippines’ export ﬂows.

For most ASEAN countries, the number of products exported to the landlocked country
of Lao PDR was limited. Malaysia, Zum Beispiel, exported a mere 31 products to Lao PDR
In 2013, whereas its second-smallest number of products exported bilaterally within East
Asia was 76 (which was a record for Malaysia’s exports to Myanmar). Im Gegensatz, Thai-
Land, which shares a common border with Lao PDR, already exported about 300 Produkte

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Deepening and Widening of Production Networks in ASEAN

Figur 3. Number of products in machinery parts and components exports, by destination country

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Quelle: UN Comtrade database (import statistics, based on the HS 1996 classiﬁcation, at the six-digit level).

Notiz: See notes of Table 1. Countries are arranged in descending order of the total value of machinery parts and components exports to the

world in 2013.

Asian Economic Papers

Deepening and Widening of Production Networks in ASEAN

to Lao PDR as of 2007, and widened the range of products to 311 In 2013, which was the
sixth largest, following Singapore, Deutschland, Malaysia, Indonesien, and China, among
Thailand’s total export ﬂows. For Vietnam, another country sharing a border with Lao
PDR, the number of products exported to Lao PDR almost doubled to over 160 prod-
ucts in 2013, which was nearly close enough to reach the level of Vietnam’s exports to
India or the Philippines. The number of products exported to Cambodia or Myanmar also
tended to be limited for almost all the ASEAN countries, but one of the noticeable excep-
tions was Vietnam’s exports to Cambodia, with the two countries sharing a border. Diese
observations imply a positive correlation between the extent of (destination-speciﬁc)
export product diversiﬁcation and the country of origin’s geographical proximity to a
destination market.

Another point to note is that Brunei, Kambodscha, Lao PDR, and Myanmar have almost
no trade in machinery parts and components with one another. As of 2013, two-thirds of
exporter–importer pairs of these less-developed ASEAN countries actually had no trans-
actions of machinery parts or components at all. It appears that, despite the networking of
back-and-forth trade links of machinery parts and components within East Asia centering
on Singapore and Thailand, machinery production fragmentation has not yet occurred
among the less developed ASEAN countries.

3.4 Number of export product–destination pairs: Ins and outs

Nächste, looking at changes in the number of (non-zero) product–destination pairs in a
country’s exports, Figur 4 reveals that a substantial amount of ins and outs of product–
destination pairs are going on beneath the surface. A country experiences a change in the
number of product–destination pairs (d.h., on the extensive margin) by exporting a new
product that has never been exported before, or by exporting an already-exported prod-
uct to a new destination country to which the country had not previously provided that
product.11 Ins of product–destination pairs occur through entries of products to a coun-
try’s export product mix, or through entries of destinations to a country’s product-speciﬁc
destination mix. Ähnlich, outs of product–destination pairs occur through exits of prod-
Produkte, or through exits of destinations. The stacked bars in Figure 4 show the composition
of changes in the number of product–estination pairs by comparing a country’s export
pattern between 2007 Und 2013. The number of product–destination pairs in the initial
year of 2007 equals the sum of continuing pairs and outs of pairs attributing to exits of
products or destinations, while the number of pairs in the latter year of 2013 equals the
sum of continuing pairs and ins due to entries of products or destinations.

11 To the best of our knowledge, Besedeˇs and Prusa (2011) is one of few previous studies that exam-

ine changes in a country’s exports to the world by decomposing the extensive margin into the new
product margin and the new destination margin. We follow Besedeˇs and Prusa’s way of think-
ing of the extensive margin. Other studies, such as Kehoe and Ruhl (2013), focus only on the new
product margin because they examine changes in trade patterns for a selected country pair.

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Figur 4. Number of product-destination pairs in machinery parts and components exports to
die Welt

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Quelle: UN Comtrade database (import statistics, based on the HS 1996 classiﬁcation, at the six-digit level).

Notiz: See notes of Table 1. Countries are arranged in descending order of the total value of machinery parts and components exports to the

world in 2013.

Asian Economic Papers

Deepening and Widening of Production Networks in ASEAN

All the ASEAN countries increased the number of pairs by between 3 Prozent (Singapur)
Und 96 Prozent (Kambodscha) for the period 2007–13. In der Zwischenzeit, all countries experienced a
substantial amount of ins and outs of product–destination pairs. The relative importance
of ins and outs, as a percentage of the number of continuing pairs, tends to be larger for a
country with a smaller number of pairs in total. Even for Singapore and Thailand, whose
product–destination mix is outstandingly diverse among the ASEAN countries, ins and
outs of product–destination pairs reached the level of 40 percent and 30 Prozent der
number of continuing pairs, jeweils. For Lao PDR, whose product–destination mix
was the least diverse, ins and outs of product–destination pairs were eight and ﬁve times
as large as the number of continuing pairs, jeweils.

Not only for Singapore and the ASEAN-4, whose export product mix appears to have
already hit a ceiling (Tisch 1), but even for countries lagging in export product diversiﬁ-
cation, entries and exits of destinations tended to occur to a greater extent, compared with
entries and exits of products. Zusätzlich, there were a considerable number of exits, als
well as entries, of export destinations, suggesting that countries have undergone a non-
negligible downsizing of the (product-speciﬁc) destination mix for some products, while
diversifying the destination mix for other products, during a period of only six years. A
remarkable exception was Myanmar, for which the overall number of exported products,
as well as the overall number of destinations, increased by 30 Zu 50 percent in the period
2007–13 (Tisch 1), and ins of product–destination pairs were equally attributed to entries
of products and to entries of destinations.

4. Probability of exporting a product to a particular market

The preceding section highlighted that networks of back-and-forth trade links of machin-
ery parts and components have developed, notably inside the East Asian region, centering
on Singapore and Thailand. In addition to Singapore, Thailand, and the other ASEAN-4
Länder, Vietnam is an increasingly active player in the formation of global, sowie
regional, production networks in the machinery industry. Vietnam’s machinery parts
and components exports seem relatively insigniﬁcant in its total manufacturing exports,
but are remarkably diversiﬁed in terms of both a wider range of exported products and
destination market countries. In sharp contrast to Vietnam, the rest of the CLMV and
Brunei lag far behind other ASEAN countries in terms of export product and destina-
tion diversiﬁcation, as well as in terms of the value of machinery parts and components
exports, although there are signs of catching up. These less-developed ASEAN countries
were only involved in machinery production networks to a limited extent. Darüber hinaus, ma-
chinery parts and components trade was not observed at all between the less developed
ASEAN countries.

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Deepening and Widening of Production Networks in ASEAN

To help us understand the observed patterns of ASEAN countries’ involvement in in-
ternational production networks in the machinery industry, this section offers a statisti-
cal analysis of the probability that a product at the HS six-digit level is exported from a
particular country of origin to a particular destination country. In line with Baldwin and
Harrigan (2011), we document a reduced-form relationship between the probability of
a non-zero export ﬂow and its explanatory variables for ASEAN countries’ machinery
parts and components exports in 2013. Applying gravity logic to the incidence of zeros in
terms of global production sharing suggests that a non-zero export ﬂow is more likely the
less costly the transport of the good from the country of origin to the destination market
country, the lower the service link costs to coordinate geographically separated produc-
tion stages across borders, the larger the production of the good in the country of origin,
the larger the demand for the good in the destination, and the larger the differences in
location advantages, such as wages, between the countries.

4.1 Variables and data

To measure the factors affecting the probability of exporting, we include the following
Variablen: as proxy for international transportation costs, telecommunication costs, Und
other costs related to geographical distance, we use bilateral distance (km) between the
country of origin and destination countries, and country pair–speciﬁc dummies indicat-
ing contiguity and the common ofﬁcial language. Distance would affect the incidence
of zero and non-zero trade ﬂows within production networks more than in other forms
of transactions, because intermediate goods and semi-ﬁnished products cross borders
multiple times through the global value chain. Zusätzlich, the service link costs, al-
though dependent on a country’s trade and investment-related policies as well, würde
depend on distance to a considerable extent. Data on distance and associated indicator
variables are obtained from the GeoDist database of the Centre d’Etudes Prospectives et
d’Informations Internationales (CEPII).

As a proxy for the size of production and demand for a product at the HS six-digit level,
we include the GDP of both the country of origin and the destination country instead of
more immediately relevant industry-level input-output data. As an economy grows, In-
dustrial production becomes larger in scale and diversiﬁed enough to be able to take part
in global production sharing and to be attractive to foreign investors, possibly leading to
the emergence of non-zero trade ﬂows. Data on GDPs (in current U.S. dollars) come from
the World Bank’s World Development Indicators (WDI) database.

In addition to these variables that have been traditionally used in the gravity literature,
we control for the differences in location advantages that provide a basis for a shift of
production activities from one country to another through cross-border fragmenta-
tion of production, which is accompanied by a newly formed trade link between the
Länder. The international wage differentials are considered an important element

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Deepening and Widening of Production Networks in ASEAN

of location advantages. We use GDP per capita as a proxy for wages and introduce the
absolute value of the difference in GDP per capita between the country of origin and the
destination country.

We also consider, for both the country of origin and the destination country, the trade-
and investment-related policies that reduce the service link costs by introducing the
World Bank’s Logistics Performance Index (LPI). Although technological advancement
in information and communication technology and transportation technology all over
the world has improved the timeliness and efﬁciency of coordination between geo-
graphically disperse production stages, a country’s competence and the quality of trade
logistics services and infrastructure make a difference in the attractiveness as an invest-
ment destination for networking ﬁrms and the global competitiveness to participate in
production networks.

Non-zero export ﬂows are more likely when a pair of countries belongs to a common
regional trade agreement (RTA), because the formation of an RTA not only reduces
transportation costs by lowering tariffs but also facilitates cross-border transactions in a
broader sense. We include a country pair–speciﬁc dummy indicating that an RTA is in
force, as of 1 Januar 2013. ASEAN countries are now linked not only with other ASEAN
countries but also with all the East Asian partners by RTAs. Zusätzlich, as of 1 Januar
2013, Brunei, Lao PDR, Malaysia, and Singapore have formed RTAs with non-East Asian
Länder. Information on RTAs notiﬁed to the World Trade Organization (WTO) is avail-
able in the WTO’s Regional Trade Agreements Information System (RTA-IS) database.

As illustrated by Figure 4, all ASEAN countries with the exception of Myanmar have
undergone diversiﬁcation of export ﬂows to a greater extent by exporting an already-
exported product to a new destination country, to which the country had not previously
provided that product. This observation suggests that the country of origin’s global ex-
perience in exporting the product has a considerable positive effect on the probability of
exporting in a later year. We therefore include an origin-product pair-speciﬁc dummy in-
dicating the country of origin’s previous experience in exporting the product. This global-
export-experience dummy takes a value of 1 if the country exported the product at the HS
six-digit level to at least one country in the world in the initial year of 2007.

zuletzt, as illustrated by Figure 3 and Appendix Figure A.1, ASEAN countries tend to ex-
port a wider range of products to East Asian trade partners than to destination countries
outside the region, and consequently have developed networks of back-and-forth trade
links most notably with East Asian partners. These observations suggest that there may
be an additional premium for intra-East Asian trade even after controlling for the pre-
viously discussed factors. In order to capture any possible fundamental difference be-
tween intra-East Asian exports and exports to countries outside the region, we introduce

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Deepening and Widening of Production Networks in ASEAN

destination-speciﬁc intercept and slope dummies indicating intra-East Asian trade,
which equals 1 if the destination, as well as the origin ASEAN country, are in the East
Asian region. Beachten Sie, dass, because ASEAN countries have RTAs in force with all the East
asiatische Länder, the interaction term between the RTA dummy and the intra-East Asia
slope dummy is subsumed into the intra-East Asia intercept dummy. Mit anderen Worten,
what the intra-East Asia intercept dummy actually captures contains the effect of the
RTA formation.

4.2 Ergebnisse

We estimate two different versions of speciﬁcation, with and without the intra-East Asia
intercept and slope dummies, using logistic regression. The dependent variable is a bi-
nary indicator for a non-zero export ﬂow in a particular HS six-digit code of machinery
parts and components from a particular origin country of ASEAN to a particular des-
tination market in 2013, conditional on being exported from the country of origin to at
least one other country in the world from 139 countries in our data set. Our sample in-
cludes respective ASEAN countries’ potential export ﬂows (d.h., product-destination pairs)
for which full data on explanatory variables are available. All continuous variables are
log transformed.

The results are shown in Table 2. For each speciﬁcation, we report the estimated coefﬁ-
cients in log-odds units—that is, on the log odds ratios of the probability of exporting, für
respective explanatory variables including interaction terms, and the average marginal
effects of the independent variables on the predicted probability of exporting. Standard
errors are robust and are clustered on exporter–importer pairs, allowing an arbitrary cor-
relation in errors within a cluster but assuming independence across clusters.

The ﬁrst pair of columns in Table 2 reports our baseline results for a speciﬁcation with-
out the intra-East Asia dummy. In the case of binary explanatory variables, an average
marginal effect measures how the predicted probability of exporting changes on aver-
age across observations as the binary explanatory variable of interest changes from 0 Zu
1, holding all other variables as given. Zum Beispiel, the global-export-experience dummy
has a strong positive marginal effect on the export probability: On average, the products
that the country of origin has experience in exporting to at least one country in the world
in the initial year are 18.8 percentage points more likely to be exported in a later year.

Likewise, the average marginal effect for continuous variables measures the instantaneous
rate of change in the probability of exporting, but the interpretation is not that straight-
forward because the estimated marginal effect depends on how the independent variable
is scaled. In the case of continuous variables, we limit our attention to checking the signs
and signiﬁcance of the marginal effects and comparing the magnitude of the marginal
effects between independent variables on the same scale.

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Deepening and Widening of Production Networks in ASEAN

Tisch 2. Statistical determinants of ASEAN’s non-zero export ﬂows
of machinery parts and components, 2013, logit estimation

(1)
Coef

dy/dx

(2)
Coef

dy/dx

−0.540∗∗∗ −0.079∗∗∗ −0.451∗∗∗ −0.072∗∗∗
(0.067)

(0.010)

Log distance

∗ Intra-East Asia dummy

Contiguity dummy

Common-language dummy

∗ Intra-East Asia dummy

Log origin country’s GDP

Log destination country’s GDP

∗ Intra-East Asia dummy

Log abs. diff. in GDP per capita

∗ Intra-East Asia dummy

Log origin’s logistics performance

Log destination’s logistics performance

∗ Intra-East Asia dummy

RTA dummy

Global-export-experience dummy

Intra-East Asia dummy

0.41
(0.219)
0.124
(0.094)

0.064
(0.036)
0.019
(0.014)

∗∗∗

0.469
(0.031)
0.367∗∗∗
(0.019)

∗∗∗

0.069
(0.005)
0.054∗∗∗
(0.003)

−0.053∗
(0.022)

−0.008∗
(0.003)

3.000∗∗∗
(0.214)
1.755∗∗∗
(0.214)

0.441∗∗∗
(0.031)
0.258∗∗∗
(0.031)

0.058
(0.100)
1.889
(0.130)

∗∗∗

0.009
(0.015)
0.188
(0.008)

∗∗∗

(0.013)

0.068
(0.004)
0.053∗∗∗
(0.003)

0.038
(0.033)
0.008
(0.015)

(0.100)
−0.238
(0.159)
0.247
(0.210)
0.016
(0.117)
0.227
(0.202)
0.464
(0.030)
0.388∗∗∗
(0.021)
−0.170∗∗
(0.058)
−0.065∗∗ −0.009∗∗
(0.024)
(0.003)
0.021
(0.045)
3.125∗∗∗
(0.220)
1.498∗∗∗
(0.221)
2.479
(0.602)
−0.168
(0.129)
1.885
(0.124)
3.688∗
(1.463)

−0.024
(0.018)
0.187
(0.007)
0.028
(0.033)

0.457∗∗∗
(0.032)
0.280∗∗∗
(0.031)

∗∗∗

Number of observations

Pseudo R2 (McFadden)
Wald χ 2 Statistiken
Prob. > Wald χ 2 Statistiken

322,477 (origin-destination-product
combinations)

0.187
1,946
0.000

0.189
2,205
0.000

Quelle: UN Comtrade database (import statistics, based on the HS 1996 classiﬁcation, Bei der

six-digit level), CEPII GeoDist database (distance and geographical indicators), WB WDI (BIP) Und

LPI database (Logistics Performance Index), WTO RTA-IS database (RTA dummy).

Notiz: Dependent variable is a binary indicator for a non-zero export ﬂow in a particular HS

six-digit code from a particular origin country to a particular destination market country. Machinery

industries are deﬁned as HS 84-92, and among them we identify parts and components, following

Kimura and Obashi (2010). Brunei is not included in the estimation reported above because the data

for the Logistics Performance Index are not available. Reported results are the estimated coefﬁcients

(in log-odds units) and the average marginal effects on the predicted probability of exporting. Der

estimates for the constant term are not reported but are included in the regressions. Standard errors
are clustered on exporter-importer pair. Asterisks denote statistical signiﬁcance: ***signiﬁcant at the
0.1 percent level; **signiﬁcant at the 1 percent level; *signiﬁcant at the 5 percent level.

In our baseline results, most of the explanatory variables have statistically signiﬁcant
average marginal effects on the probability of exporting as expected, but with two ex-
ceptions: Erste, the absolute value of the difference in GDP per capita has a negative and
signiﬁcant marginal effect on the export probability, as opposed to the expectation that

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non-zero export ﬂows of machinery parts and components are more likely when dif-
ferences in location advantages between the pair of countries are large. Auf der einen Seite,
we need to account for other crucial elements of location advantages beyond the inter-
national wage differentials for further analysis. Andererseits, this result suggests
that ASEAN countries do not export a wide range of machinery parts and components
to high-income countries, but rather have developed export links of machinery parts
and components with destination countries at a similar level of economic develop-
ment, including ASEAN countries themselves and other developing countries in the
East Asian region. Zweite, the contiguity dummy, the common-language dummy, Und
the RTA dummy have a positive (as expected) but insigniﬁcant marginal effect on the
export probability.

The second pair of columns in the table is for a speciﬁcation that also includes the intra-
East Asia intercept and slope dummies. By introducing the intra-East Asia dummy, Die
average marginal effects for the contiguity dummy and the common-language dummy
become small in magnitude, although remaining insigniﬁcant, and the marginal effect
for the RTA dummy turns negative but also remains insigniﬁcant.12 For all the other ex-
planatory variables, the marginal effects are similar to their baseline estimates in terms of
sign and signiﬁcance. The intra-East Asia dummy of interest has a positive, but insigniﬁ-
kippen, marginal effect on the probability of exporting. We do not detect any statistically sig-
niﬁcant premium for intra-East Asian exports, compared with exports to countries outside
the region, on average across ASEAN countries’ potential export ﬂows, after controlling
for differences in trade costs, production and demand size, location advantages, service
link costs, and exporting experience.

In sum, the logit estimation results reported in Table 2 illustrate a clear relationship be-
tween the probability of exporting, and gravity and other variables for ASEAN countries’
machinery parts and components exports: A non-zero export ﬂow is more likely the lower
the trade costs, the larger the production in the country of origin, the larger the demand
in the destination country, the smaller the gap in GDP per capita between the origin and
destination countries, and the lower the service link costs. Zusätzlich, the country of ori-
gin’s global experience in exporting a particular product has a large positive effect on the
export probability.

12 Debaere and Mostashari (2010) studied the impact of changing tariffs (at the product level) An
the range of products exported and found that a mere 5–12 percent of the extensive margin of
exports to the United States is explained by tariff cuts. In line with Debaere and Mostashari, Wir
could look into each RTA to see if it actually lowers tariffs or contributes to facilitating cross-
border transactions of machinery parts and components, although this is beyond the scope of
this paper.

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Tisch 3. Country-by-country comparison of marginal effects of selected
erklärende Variablen

Variable

Malaysia

Singapur

Thailand

Philippinen

Vietnam

Indonesien

Kambodscha

Myanmar

Lao PDR

Brunei

Log
destination’s in GDP per
BIP

capita

Log abs. diff. Log destination’s Global-export

logistics
Leistung

Erfahrung
dummy

Intra-East
Asia dummy

∗∗∗

0.059∗∗∗
(0.007)
0.061∗∗∗
(0.007)
0.056∗∗∗
(0.007)
0.035∗∗∗
(0.006)
0.041
(0.005)
0.050∗∗∗
(0.006)
0.012∗∗∗
(0.002)
−0.001
(0.004)
0.008
(0.005)
0.001
(0.005)

−0.015
(0.010)
0.005
(0.015)
−0.027∗∗
(0.009)
−0.018
(0.009)
−0.002
(0.008)
−0.020∗∗
(0.008)
0.000
(0.005)
0.000
(0.004)
0.000
(0.005)
−0.003
(0.004)

0.333∗∗∗
(0.083)
0.236∗∗
(0.084)
0.425∗∗∗
(0.096)
0.540∗∗∗
(0.089)
∗∗
0.318
(0.099)
0.396∗∗∗
(0.084)
0.084
(0.047)
0.157∗
(0.062)
0.100
(0.089)
0.217∗∗∗
(0.037)

∗∗∗

0.298∗∗∗
(0.013)
0.298∗∗∗
(0.014)
0.305∗∗∗
(0.013)
0.179∗∗∗
(0.009)
0.166
(0.006
0.213∗∗∗
(0.010)
0.034∗∗∗
(0.004)
0.019∗∗∗
(0.004)
0.016∗∗∗
(0.004)
0.029∗∗∗
(0.004)

0.045
(0.074)
−0.068
(0.061)
0.235∗∗∗
(0.031)
0.250∗∗∗
(0.063)
∗∗
0.107
(0.035)
0.133
(0.076)
−0.004
(0.009)
0.050∗∗
(0.018)
−0.012
(0.019)
0.015
(0.015)

Quelle: UN Comtrade database (import statistics, based on the HS 1996 classiﬁcation, at the six-digit level), CEPII

GeoDist database (distance and geographical indicators), WB WDI (BIP) and LPI database (Logistics Performance

Index), WTO RTA-IS database (RTA dummy).

Notiz: Reported results are from by-country logit estimation with the speciﬁcation (2) in Table 2. See notes of

Tisch 2. Brunei, as a destination country, is not included in the estimation reported above because the data for the
Logistics Performance Index is not available. Asterisks denote statistical signiﬁcance: ***signiﬁcant at the 0.1 Prozent
Ebene; **signiﬁcant at the 1 percent level; *signiﬁcant at the 5 percent level.

4.3 Country-by-country comparison

We also conduct the same statistical analysis for each of the origin ASEAN countries, us-
ing the speciﬁcation with the intra-East Asia dummy. The estimated average marginal
effects for selected explanatory variables are compared between countries in Table 3. Erste,
the global-export-experience dummy has a notably large and positive average marginal
effect on the probability of exporting in the cases of Thailand, Malaysia, and Singapore,
whose export product mix was already diverse enough to hit a ceiling in the initial year
von 2007 (Tisch 1). The estimated marginal effects for the global-export-experience dummy
are far smaller in the less-developed ASEAN countries, such as Lao PDR and Myanmar,
reﬂecting the fact that a non-negligible amount of entries of products to the country’s
product-destination mix occurred in the period 2007–13 (Figur 4).

Zweite, the estimated average marginal effects for the destination country’s GDP are rel-
atively small in magnitude and statistically insigniﬁcant in the case of the less-developed
ASEAN countries. The estimates for the destination country’s Logistics Performance show
a similar pattern, especially in Cambodia and Lao PDR. One possible explanation for
these results is that a substantial portion of non-zero export ﬂows from less-developed
ASEAN countries is dictated by multinational ﬁrms’ global operations and ﬁrms’

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decisions on where to locate the fragmented production stages across borders, rather than
simply driven by a larger size of GDP or a better quality of trade logistics and infrastruc-
ture in the (export) destination country. If this is the case, Die (export) country of origin’s
attractiveness as an investment destination for multinational ﬁrms does matter for the ex-
port probability, and the export ﬂow to a destination country where a mother factory is
located does not depend on the destination country market’s characteristics.13

Dritte, the absolute value of the difference in GDP per capita has a negative and signif-
icant average marginal effect on the probability of exporting in the cases of Thailand
and Indonesia. Both countries were in the middle of the GDP per capita ranking among
ASEAN countries, achieving a level close to the ASEAN average in 2013. Although fur-
ther analysis on the effect of the differences in location advantages on the export probabil-
ity is certainly needed, these countries appear to have developed and diversiﬁed export
links of machinery parts and components, at least to some extent, with countries at a simi-
lar level of economic development, including their ASEAN neighbors, China and India.

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zuletzt, the estimated average marginal effects for the intra-East Asia dummy are posi-
tive and signiﬁcant in the case of some countries. Zum Beispiel, Thailand, which is one of
the most important players in regional production networks in East Asia, has on aver-
age a 23.5 percentage point greater probability of exporting a particular product to East
Asian trade partners than comparable non-East Asian countries. The marginal effect for
the intra-East Asia dummy is also relatively large and signiﬁcant in Myanmar, nicht wie
other less developed ASEAN countries. The latter result reﬂects Myanmar’s strikingly
high ratio of the average number of products in intra-East Asian exports to that in exports
to countries outside the region (Figur 3).

In contrast to Thailand, the intra-East Asia dummy has no statistically signiﬁcant aver-
age marginal effect on the probability of exporting in Malaysia and Singapore, both of
which appear to be actively involved in global, as well as regional, machinery production
Netzwerke. Zusätzlich, no premium for intra-East Asian trade is statistically detected for
the less developed ASEAN countries with the exception of Myanmar, which reﬂects the
fact that these countries have not yet been integrated into not only global, but even into
regional, production networks.

5. Abschluss

This paper has assessed the degree of involvement of ASEAN countries in interna-
tional production networks in the machinery industry, making use of product-level

13 Fung, Iizaka, and Siu (2010) empirically shows that foreign direct investment inﬂow positively

affects the host country’s exports of parts and components in East Asia.

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Deepening and Widening of Production Networks in ASEAN

international trade data. We have documented ASEAN’s networking of back-and-forth
trade links of machinery parts and components, notably with East Asian partners, center-
ing on Singapore and Thailand. In addition to Singapore, Thailand, and other ASEAN-4
Länder, Vietnam is an increasingly active player in such networks. Although the less-
developed ASEAN countries have limited involvement in regional, as well as global,
production networks, they are ﬁnally starting to join production networks in our sam-
ple period. Außerdem, we highlight that the probability of a non-zero ﬂow in ASEAN
countries’ machinery parts and components exports is negatively correlated to trade costs
and service link costs, and is positively correlated to production and demand size, Und
the country of origin’s global experience in exporting a particular product, along with a
premium for intra-East Asian trade in some countries.

The empirical investigation based on the product-level international trade data is proven
to be effective in assessing the degree of participation in production networks. In partic-
ular, the initial stage of joining production networks is vividly traced by this approach.
Deepening and widening of production networks along with the formation of domestic
industrial agglomeration are also clearly illustrated. This does not complete the assess-
ment of the whole industrialization process, Jedoch. The formation of industrial ag-
glomeration, together with international production networks, is a novel phenomenon
in the evolution of the new international division of labor with the second unbundling
in ASEAN and East Asia. Industrial agglomeration in this region is motivated by the
development of inter-ﬁrm (arm’s length) transactions in proximity, rather than the one
observed in Western Europe where economic activities with high transport costs are at-
tracted by the most immobile element, Menschen. Although both statistical data and the
analytical approach are underdeveloped, the assessment of the functioning and conse-
quences of industrial agglomeration has become increasingly important. We observe
in a series of microeconomic surveys conducted by the Economic Research Institute
for ASEAN and East Asia (ERIA) the occurrence of technology transfers and spill-over
through transactions between foreign afﬁliates and local ﬁrms in industrial agglomer-
ation, which encourages process/product innovation at the ﬁrm level and industrial
upgrading at the aggregated level.14 Our future research agenda should include the
development of new empirical approaches for capturing the expansion of the scale and
scope of industrial agglomeration by using international trade data.

Verweise

Ando, Mitsuyo, and Fukunari Kimura. 2005. The Formation of International Production and Dis-
tribution Networks in East Asia. In: International Trade in East Asia (NBER-East Asia Seminar on Eco-
nomics, Volumen 14), edited by Takatoshi Ito and Andrew K. Rose, S. 177–213. Chicago: Universität
of Chicago Press.

14 Sehen, Zum Beispiel, Kimura, Machikita, and Ueki (2015).

Asian Economic Papers

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Beweis. American Economic Journal: Microeconomics 3(2):60–88.

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Haveman, Jon, and David Hummels. 2004. Alternative Hypotheses and the Volume of Trade: Der
Gravity Equation and the Extent of Specialization. Canadian Journal of Economics 37(1):199–218.

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Appendix A: Intra-East Asian data

Figure A.1 Number of destinations in intra-East Asian machinery parts and components exports,
distribution across products

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Quelle: UN Comtrade database (import statistics, based on the HS 1996 classiﬁcation, at the six-digit level).

Notiz: This is the intra-East Asian trade version of Figure 2. See notes of Figure 2.

Asian Economic Papers Deepening and Widening of Production image

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