OSIPP Discussion Paper : DP-2011-E-006

Quantifying the Benefits of Trade Facilitation in ASEAN

November 1, 2011
Tsunehiro Otsuki
Associate Professor, Osaka School of International Public Policy (OSIPP)【Keywords】regional integration, trade facilitation, gravity model【JEL Codes】F15、H54、L51【Abstract】
This paper assesses the performance and progress of the ASEAN economies intrade facilitation, and the effect of improved trade facilitation on the region’s
manufacturing trade with a focus on port efficiency, customs environment,
regulatory environment and service sector infrastructure. Under a scenario of
raising the below-average countries halfway to the global average, ASEAN’s tradeis estimated to increase by $99 billion, three-quarters of which comes from theregion’s own improvements. Also, regulatory reforms, for example, enhancing
transparency of trade-related regulations and ensuring law-abiding operations of
the regulatory authorities, are found to be most effective.

Correspondence: Tsunehiro Otsuki, The Osaka School of International Public
Policy, Osaka University, 1-31 Machikaneyama-cho, Toyonaka, Osaka 560-0043
Japan.
E-mail address: otsuki@osipp.osaka-u.ac.jp
Acknowledgement: This paper is originally prepared for ERIA Research Project2010 No. 3. I am grateful for financial support from the Economic ResearchInstitute for ASEAN and East Asia (ERIA), and the Japan Society for the
Promotion of Science, Grant-in-Aid for Scientific Research (B), 2010-2013.

1.

Introduction
Trade facilitation is becoming an increasingly important driving factor in trade

expansion, as tariffs and major non-tariff barriers such as import quotas and voluntary export
restraint have substantially dropped in the last three decades (ADB and UNESCAP 2009).
Trade facilitation implies trade liberalization, through reduction of the trade costs associatedwith unnecessarily complex customs and border procedures, and inefficient transit
arrangements (ADB and UNESCAP 2009).

Many developing countries have substantially liberalized trade in goods and services,
but those reforms have been mostly in the area of tariffs.
unsuccessful in reforms in a broader area of trade barriers.

Some countries are still

Trade facilitation is believed tohave a growth promotion effect, not only by increasing trade flows but also because policy
reforms and infrastructure development may help spur the internal economic growth of thecountry.

Thus, trade facilitation is becoming an important area of focus as a measure of tradeliberalization.

ASEAN initiated their concerted effort toward a free trade area in 1992, andthe member economies have liberalized intra-regional trade substantially until recently
particularly in the area of tariff reduction.

Further commitment to trade liberalization was

proposed within ASEAN in relation to their new goal of establishing an ASEAN Economic
Community (AEC).

This is specifically intended to establish a single market andproduction base, a competitive economic region, equitable economic development andintegration into the global economy. Reducing transaction costs associated with trade andother economic interchange is one of the primary goals of economic integration in ASEAN(Lee and Plummer, 2011). The ASEAN Economic Community Blueprint 1 states specificfocus related to trade facilitation, namely, (1) developing simple, harmonized andstandardized trade an customs processes, procedures and related information flows, (2)integration of customs structures and e-customs system, and (3) establishing developing
national single windows as well as an integrated ASEAN single window, among others(Layton, 2007).

ASEAN comprises a diverse set of countries, in terms of their level of trade facilitation,
ranging from countries that are far behind the global average to Singapore which is one of
the world’s best. Those countries which lag behind are also not active in international trade
and are characterized by low income. This highlights the importance of countries catchingup in the process of economic integration, and in the regional economic growth of ASEAN.

The complexities in regard to non-tariff measures in general, and the lack of a precise
definition of trade facilitation, have, however, made it difficult to quantify the benefits oftrade facilitation reform and, thus, to provide targets for each country.

This report tries toevaluate the extent of trade facilitation of countries worldwide, by constructing relevant
indices as an effort to quantify the level of trade facilitation according to Wilson, Mann andOtsuki (2005), but with a greater time period coverage (2004-2008) and more countries (99countries). A particular focus is given to the ASEAN member countries.

Performance of

the ASEAN countries is investigated over time, and is compared with the other developing
regions, as well as with the OECD countries.

1

As the next step, a regression analysis is used

“ASEAN Economic Community Blueprint” http://www.aseansec.org/21083.pdf.

to estimate the effect of trade facilitation on trade flows, by using a gravity model, and asimulation analysis is conducted to demonstrate gains from trade facilitation reforms.

This paper is organized as follows. Section 2 investigates the trade profile of theASEAN region.

Section 3 explains our approach to measuring trade facilitation, andevaluates regions and individual countries in terms of their level of trade facilitation.
Section 4 explains the empirical model to be used to estimate the effect of trade facilitation
on trade flows.

Section 5 conducts simulations of trade gains under alternative scenarios.

Section 6 provides conclusions and policy implications.

2.

Trade profile of the ASEAN region
Figure 1 indicates that ASEAN’s manufacturing trade nearly doubled from 2000 to 2008.

Intra-regional trade in ASEAN accounted for approximately one-third of its total trade in
2000.

This implies that the ASEAN region relies for its trade, predominantly exports, on

the countries outside ASEAN.

The share of its exports to countries outside the region grew

very rapidly, to account for approximately three quarters of its total trade.
ASEAN’s intra-regional trade was positive but relatively slow.

The growth inThis perhaps implies thatthe potential for growth in intra-regional trade has not been fully exploited.

The decline of tariffs in the ASEAN countries can partly account for ASEAN’s trade
expansion in the 2000s. But, improved trade facilitation also may have contributed to thetrade expansion.

For example, the number of days needed for an import decreased

dramatically in Cambodia from 55 days in 2005 to 30 days in 2009 according to the World

Trade Indicators of the World Bank. We will investigate the trends of trade facilitation in
ASEAN in more detail in Section 3.

Figure 1. ASEAN's intra- and inter-regional trade in manufactured goods 2000-2008(billion USD)
500
450
400
350
300
250
200
150
100
50
0
2000

2001

2002

2003

2004

From ASEAN to other

2005

2006

2007

2008

From other to ASEAN

From ASEAN to ASEAN

Source: Author’s calculation based on UN Comtrade database.

3.

Evaluating performance of ASEAN in trade facilitation
There is no clear definition of trade facilitation, since it varies depending on the extent

of measures to be included.

In a broader sense, it covers all the measures that affect the

movement of goods between buyers and sellers, along the entire international supply chain(ADB and UNESCAP, 2009).

In a narrow sense, trade facilitation simply addresses thelogistics of moving goods through ports or at customs checkpoints at national borders.

A

broader framework for understanding trade facilitation includes a number of inter-related
measures or factors, such as port reform and modernization, streamlining regulatory
requirements and harmonizing standards, as well as customs regimes.

For example, OECD

adopts a broad definition i.e. “the simplification and harmonization of international trade
procedures including the activities, practices and formalities involved in collecting,presenting, communicating and processing data, and other information required for the
movement of goods in international trade”.

Wilson, Mann and Otsuki (2005) provided

multiple indices to measure a country’s performance in trade facilitation, following thebroader definition. We follow the broader definition of trade facilitation in our analysis of its
effect.

3.1. Constructing the Indicators of Trade Facilitation

Based on a broader definition of trade facilitation, there are various measures andmeasurement approaches proposed in the literature.

The class of direct measurements

includes; time needed for customs clearance, need for irregular payment at customs, andshipping charges. These types of measures are likely to be direct and specific. Indirect
measurements include those derived from the gap between the domestic and international
prices of goods, including the tariff equivalent of non-tariff barriers. Indirect measurementsfrequently indices- are typically abstract and unit free, and, sometimes, qualitative rather
than quantitative.

The time needed for customs clearance is a frequently used measurement of tradefacilitation.

The World Bank’s “Doing Business” reports present a variety ofmeasurements of trade facilitation based on cross-country firm surveys.

These include days

to clear customs, port and terminal handling, and number of inspections for imports.

Fink,

Mattoo and Neagu (2002) use the share of liner transport charges in import values of aparticular good as their measure of maritime transport cost.

In the World Bank “Technical

Barriers to Trade” survey, product redesign costs and other costs incurred in complying withforeign standards, are directly collected from surveyed firms in developing countries.

The Asia-Pacific Economic Cooperation forum (APEC) (1999) has proposed the use of
the amount of reduction of unit import prices as a measure of trade cost reduction.
Similarly, a tariff equivalent has often been mentioned as a measure of insufficient tradefacilitation, more generally of non-tariff barriers.

A tariff equivalent is useful when one isunable to identify individual influencing factors, since it represents the effect of all
influencing factors. The drawback is that it is difficult to isolate the effects of individual
factors.

More sophisticated approaches try to identify the degree to which particularbarriers, such as technical regulations, contribute to the total tariff equivalent (Kee, Nicita
and Olarreaga, 2006).

Wilson, Mann and Otsuki (WMO, hereafter) (2003) developed indicators to measurefour areas of trade facilitation, namely; port efficiency, customs environment, regulatoryenvironment and E-business usage, for APEC member economies.

WMO (2005) extended

this study to cover 75 countries, with a minor modification of the indexed inputs of Ebusiness usage and a name-change to “service sector infrastructure”.

APEC (2004) appliedthe gravity model framework of WMO (2003) to estimate the impact of trade facilitation andtariff reduction on trade in 15 APEC member countries.

Walkenhorst and Yasui (2003)

also constructed an index of border process quality, and an index of time for borderclearance.

It was made up of sub-indices, namely, customs efficiency, hidden importbarriers, administrative integrity and trade facilitation commitments.

Index approaches

allow utilization of qualitative information as well as quantitative data, and thus makecomparison possible between different types of data. Layton (2007) developed logistic
performance index and sub-components such as documents required to export and import,
and customs clearance time, for the ASEAN and OECD countries. Hollweg and Wong(2009) also developed various logistics restrictiveness indices for the ASEAN + 6 countries,
including the barriers to trade and investment in the areas of customs procedures andmaritime/aviation/road transport.

Each class of measures has advantages and disadvantages.

The direct measures allow a

relatively straightforward interpretation of how specific trade costs affect bilateral trade, as
there is no or little data manipulation. Such measures, however, capture only very specificaspects of trade facilitation. The indirect measures are useful in measuring the aggregate
effects of various barriers, but it is difficult or impossible to isolate each effect.

The

indexed measures reflect various distinct aspects of trade facilitation, and the possibility ofdata manipulation leaves researchers a certain flexibility to construct data from different
sources.

The drawback of these measures is, however, that interpretation is quite arbitrary.

Therefore, their association with policy goals is not always straightforward.

Quantitative measures are useful in understanding to what extent developing countrieslag behind in each area of trade facilitation. The World Bank report (2006) provides
evidence that addresses this point. While the total time taken to import was 14 days on
average in OECD countries and 28 days in East Asia and the Pacific, it took 47 days inSouth Asia.

Trade in Africa took the longest time -59 days on average- to make an import.

Typical regulations in Sub-Saharan Africa required 18 signatures from domestic regulatory
agencies as compared to 3 signatures in OECD countries and 7 signatures in East Asia andthe Pacific.

On average it still takes 3 times as many days, nearly twice as many documents

and 6 times as many signatures to trade in a poor country as it does in rich countries.

In this report we update the trade facilitation indicators developed for a single timeperiod in WMO (2005) to include more countries (99 countries) and a longer time (from2004-2008).



Our trade facilitation indicators are;

Port efficiency for each country J is the average of two indexed inputs from the Global
Competitiveness Report (GCR):o Port facilities and inland waterways (integers from 1 (poorest) to 7 (best))o Air transport (integers from 1 (poorest) to 7 (best))Regulatory environment for each country J is constructed as the average of indexed
inputs from the World Competitiveness Yearbook (WCY) and World Bank GovernanceIndicators (WBGI):o Transparency of government policy is satisfactory (WCY)o Control of corruption (WBGI)Customs environment for each country J is constructed from an indexed input fromGCR:
o Hidden import barriers (integers from 1 (poorest) to 7 (best))Service sector infrastructure for each country J is from the Global Information
Technology Report (GITR):o Effect of internet on business (integers from 1 (poorest) to 7 (best)) .

First, we normalize each input into the range from 1 to 7 in order to be consistent withthe range used in GCR and GITR because the majority (four out of the six) of the raw data
come from these reports.

An “indexed input” for economy J (J = 1,2, .. , N):
II J = 1 + 6*

II J − min II J
max II J − min II J ,where the numeral denotes the “raw” data for economy J such as “air transport”.

Inthe case of two inputs (port efficiency and regulatory environment), we take an average ofthe two inputs.

3.2. Performance of the ASEAN countries in trade facilitation

Table 1 shows the descriptive statistics of the indexed indices and the aggregated indices.
Figure 2 shows the average index scores of the ASEAN countries and the world average;
they are quite similar.

This is perhaps because ASEAN includes countries with diversestages of development.

The highly developed countries such as Singapore seem to keep theaverage performance of the ASEAN higher than the developing regions as a whole.

Table 1. Descriptive statistics of the trade facilitation indicators
Category
Port Efficiency

Indexed Inputs

Mean

Std. Dev.

Min

Max

Water transport facilities

3.955

1.355

1.100

6.900

Air transport facilities

4.607

1.164

1.700

6.900

4.287

1.201

1.450

6.900

Aggregated index

Regulatory

Transparency of government policies

3.797

1.724

1.000

7.000

Environment

Control of corruption

3.742

1.244

1.000

7.000

3.693

1.267

1.075

6.913

Prevalence of trade barriers (inverse)

4.596

0.848

2.100

6.700

Extent of Business Internet Use

4.098

1.003

1.790

6.410

Aggregated index

Customs Environment

Service Sector
Infrastructure

Source: Author’s calculation based on GCR, GITR, WBGI, and WCY.

Figure 2.

Four trade facilitation indicators of ASEAN and the world in 2004 and 2008
7
ASEAN

6

World

5
4
3
2
1
0

Source: Author’s calculation based on GCR, GITR, WBGI, and WCY.

Figures 3a-3d depict average index scores across regions from 2004 to 2008.
Overall, the performance of the ASEAN is relatively better than other developing regions.
Port efficiency of the ASEAN or the East Asia and Pacific region (EAP) is the second largest
among the developing regions.

The EAP average is slightly lower than the ASEAN

average. The score is still far below the OECD average, but the ASEAN’s score is slightly
increasing over time, indicating that it is catching up with the OECD.
The regulatory environment indicator of the ASEAN or EAP is close to LAC (Latin
America and Caribbean) and ECA (Europe and Central Asia), and far lower than MENA

(Middle East and North Africa).

Its average scores are also not significantly higher than theregion with the lowest score.

The variation of customs environment scores is quite small

across the regions. The ASEAN’s score is also a little lower than that of MENA in mostperiods. Growth is slightly positive overall but not monotonic. The relative position of
the regions in regard to regulatory environment is almost unchanged over time.

This

implies that the ASEAN did not experience distinguishable improvement relative to the otherregions. Yet one needs caution in interpreting the score of regulatory environment, as thescores of regulatory environment are almost unchanged over time.

This is mainly because“control of corruption”, one of the inputs to this indicator, is normalized such that the mean
is constant over time.

In customs environment, the ASEAN or EAP is the second highest next to MENA
among the developing regions.

It exhibits positive but very small improvement from 2004

to 2008. The gap from the OECD and MENA is still significant in 2008. The difference
between the developing regions is not large in this category of trade facilitation.

In service sector infrastructure, the ASEAN or EAP is the highest among thedeveloping regions.

The gap from the OECD is large, but this region shows a rapid

improvement toward 2008.

However, the other developing regions grew rapidly as well,with some regions exhibiting even higher growth rates.

Figure 3a.

Port efficiency by region 2004-2008

6
5
ASEAN
EAP

4

ECA
LAC

3

MENA
OECD

2

SA
SSA

1
0

2004

2005

2006

2007

2008

Source: Author’s calculation based on GCR, GITR, WBGI, and WCY.

Figure 3b.

Regulatory environment by region 2004-2008

6
5

ASEAN
EAP

4

ECA
LAC

3

MENA
OECD

2

SA
SSA

1
0

2004

2005

2006

2007

2008

Source: Author’s calculation based on GCR, GITR, WBGI, and WCY.

Figure 3c.

Customs environment by region 2004-2008

6
5

ASEAN

4

EAP

3

LAC

ECA
MENA
OECD

2

SA
1
0

SSA

2004

2005

2006

2007

2008

Source: Author’s calculation based on GCR, GITR, WBGI, and WCY.

Figure 3d. Service sector infrastructure by region 2004-2008
6
5

ASEAN
EAP

4

ECA
LAC

3

MENA
OECD

2

SA
SSA

1
0

2004

2005

2006

2007

2008

Source: Author’s calculation based on GCR, GITR, WBGI, and WCY.

Figures 4a-4d present the trade facilitation scores of each of the ASEAN member
countries in 2004 and 2008. There are countries in ASEAN that are missing in 2004 or
both 2004 and 2008; Brunei is missing in 2004 except Figure 4b and Lao PDR and Myanmar
are missing in both years.

In port efficiency, Singapore is 6.9 in both years, and is highest in the sample. The
second highest is Malaysia, 5.9 in 2004 and 5.7 in 2008. The third is Thailand which grew
substantially from 4.9 in 2004 to 5.3 in 2008.
and 4.1 in 2008.

Indonesia is the fourth, having 3.8 in 2004

The Philippines was the fifth in 2004, but its score decreased in 2008 from

3.4 to 3.3, making it the lowest. Vietnam and Cambodia which were the lowest, grew from
3.2 to 3.7 and 3.8, respectively.

In 2008 ASEAN countries above the global average (4.4)

included Singapore, Malaysia, Thailand and Brunei.

In regulatory environment, Singapore is highest (6.3) in both years, followed by
Brunei (4.2 in 2004 and 4.4 in 2008), and Malaysia (3.6 in 2004 and 3.3 in 2008).

There isvery little change in their scores from 2004 to 2008, and some countries reduced their scoresin 2008.

Unlike the other categories, all but Singapore and Brunei are below the global

average both in 2004 and 2008, indicating substantial inefficiencies in the area of regulatoryenvironment.

In customs environment, Singapore also shows the highest scores in both 2004 and2008.

Malaysia and the Philippines were second and third in 2004, respectively, butbecame fifth, and sixth, both declining by 0.6 points.

Cambodia and Vietnam remained thelowest two, but their scores rose by 0.5 and 0.7, respectively; thus, the gap between the high-score and low-score countries were narrowed.

Nevertheless, 6 countries were on or below

the global average, and further improvement is needed for the region as a whole.

In service sector infrastructure, Singapore was top, and Malaysia was the second, inboth years. The remaining countries changed ranking; the most outstanding one is Vietnam
which moved up to fifth with a score of 4.5 in 2008, from the lowest position, with a score of
merely 2.2 in 2004.
2008.

Overall, the ASEAN achieved notable improvement from 2004 toCompared to the global average, five countries still fall short in 2008, but only by asmall degree.

Figure 4a.

Port efficiency of the ASEAN countries in 2004 (left) and 2008 (right)

8
7
6
5
4
3

8
6.9

7
5.9

6
4.9

6.9
5.7

5
3.8

3.4 3.2 3.2

4
3

2

2

1

1

0

0

Source: Author’s calculation based on GCR, GITR, WBGI, and WCY.

5.3

5
4.1

3.8 3.7

3.3

Figure 4b.

Regulatory environment of the ASEAN countries in 2004 (left) and 2008 (right)

7

7

6.3

6

6.3

6

5

4.2

4

5
3.6

3
2

3 2.8

4.4

4
2.4 2.2

2

3.3

3
2

1

1

0

0

2.8 2.6

2.3 2.3

2

Source: Author’s calculation based on GCR, GITR, WBGI, and WCY.

Figure 4c.
7
654

Customs environment of the ASEAN countries in 2004 (left) and 2008 (right)
7

6.2

6.4

6
4.9 4.85

4.5 4.5
3.7

3.4

5

4

3

3

2

2

1

1

0

0

Source: Author’s calculation based on GCR, GITR, WBGI, and WCY.

4.7

4.4 4.3
4.2 4.2 4.1

Figure 4d. Service sector infrastructure of the ASEAN countries in 2004 (left) and 2008
(right)

7

7
6
5

5.2

4
3

6
4.7

4.4

5

4.1 3.954
2.4 2.2

2

5.8
4.7 4.5 4.5 4.5

4.2

3.8

3
2

1

1

0

0

Source: Author’s calculation based on GCR, GITR, WBGI, and WCY.

ASEAN countries which are also members of APEC had undertaken efforts tofacilitation facilitate trade earlier than those which are not (namely, Cambodia, Lao PDR and
Myanmar) as APEC had made a commitment to reduce trade-related transaction costs by 5
percent by 2006 according to the Shanghai Accord in 2001 in line with the Bogor Goals.

Itis generally evident that the early-committers increased their scores in most categories from2004 to 2008. Also, our observation that Cambodia is the lowest or, at best, the third lowest
among the ASEAN countries in our data confirms the superior position of the earlycommitters.
The above results of the four trade facilitation indicators are largely consistent with

those of Hollweg and Wong (2009).

They found that Singapore was rated as one of theleast restrictive countries in the world in terms of logistic regulations as barriers to trade. On
the other hand, Malaysia, Indonesia, Lao PDR, the Philippines and Vietnam were found tobe the most restrictive among ASEAN+6 countries.

The above results can also be confirmed by investigating performance indicatorsfrom other data sources.

More direct measures are available from the World Trade

Indicators of the World Bank, where information on Lao PDR is also available.

Among theindices that are comparable to ours, we investigated data on the number of days required forimport, and data on import cost per container in 2005 and 2009.

As shown in Figures 5aand 5b, Singapore again exhibits the best performance (the smallest number of days forimport, and the lowest import costs, respectively) in both categories and both years, andMalaysia the second in both categories in 2005 while it was the second and the third in theformer and the latter categories in 2009, respectively. The ranking and trend among theASEAN countries is quite close to what we observed earlier. A notable improvement isfound in the cases of Lao PDR and Cambodia in the number of days for import while the rest
are keeping up with the world in the pace of improvement.

On the other hand, import costis almost unchanged in the ASEAN countries except in Lao PDR whose cost increased
dramatically.

In a relative sense, the performance of the ASEAN group is slightly better

than the world on average, since the cost increased slightly in the world on average.

Data

for Myanmar is not available in these categories of trade facilitation, but Myanmar tends tolag behind the other ASEAN countries according to Layton’s (2007) comparative analysis of
the ASEAN countries in logistic performance.

40
Days

Days

40

30
30

20
20

10
10

0
0

Source: World Trade Indicators, the World Bank
Lao PDR
Cambodia
Indonesia
Vietnam
Brunei
Philippines
Malaysia
ThailandSingapore
World average

World average

Singapore

Malaysia

Philippines

Thailand

VietnamIndonesia

Cambodia

Lao PDR

Days
80
80

70
70

60
60

50
50

80
80

70
70

60
60

50
50

30

30

20

20

10

10

0

0

Lao PDR
Cambodia
Indonesia
Vietnam
Brunei
Philippines
Malaysia
ThailandSingapore
World average

World average

Singapore

Malaysia

Philippines

Thailand

VietnamIndonesia

Figure 5b.

Cambodia

Lao PDR

Days

Figure 5a.
The number of days needed for import in ASEAN in 2005 (left) and 2009(right)40

Source: World Trade Indicators, the World Bank

Import costs in ASEAN in 2005 (left) and 2009 (right)

40

4.

The empirical model to estimate the effect of trade facilitation

4.1 Previous studies
A critical question of direct relevance to trade facilitation in a development context
concerns the extent to which factors affecting trade transaction costs matter to trade flows,
economic growth or welfare.

Quantifying the gains from trade facilitation is complex andchallenging, but the typically used methodologies can be categorized into the following two
groups; macro-level econometric methods, and computable general equilibrium (CGE)
methods.

The macro-level econometric methods attempt to estimate the impact of facilitation
by regressing macro-level variables, such as trade flows and economic growth, on factors
related to trade facilitation and other controls.

In trade flow analysis, gravity models are

typically employed. McCallam (1997) estimates the border costs in US- Canada trade, andstarted the trend of the gravity model application for the estimation of trade (transactions)costs. Variation or elaboration of this application can be found in many studies. Thosestudies largely try to isolate the trade costs that are unaccounted for by distance as a proxy
for transportation costs. WMO (2005) used a simple log-linear gravity model where thetrade costs are considered to vary with the above mentioned four trade facilitation indicators.

Using a computable general equilibrium (CGE) method, Walkenhorst and Yasui(2003) estimated the benefit of reducing trade transaction costs, which can be accounted forby time for border clearance and quality of border process.

They point out that thepotential benefits of trade facilitation vary across countries, sectors, and types of traders.

For instance, the authors find that trade transaction costs (TTCs) range from 1-15 percent oftraded goods, depending on the country’s pre-trade facilitation condition.

Furthermore,border costs for agro-food products are 50 percent higher than those for manufactured
products, and TTCs for small/ medium enterprises are 50 percent higher than those for big
enterprises.

4.2 Gravity model

We follow a standard gravity model, where bilateral trade flow is regressed on GNP
and other gravity variables along with the trade facilitation indicators for both importers andexporters.
ln Trade = X ' β + z ' γ + e ,where X includes regular gravity variables such as GNP and bilateral distance between
trading countries, and z includes other influencing factors such as free trade agreements(FTAs) and trade facilitation. More specifically, our estimation model is as follows:tln(Trade ) = b lnPort + b lnCustoms + b lnRegulatory + b lnService + b lnPort
JI

1

J

2

I

3

J

4

J

5

t

I

t

+ b lnCustoms + b lnRegulatory + b lnService + b ln(GNP ) +b ln (GNP )
6

I

7

I

t

8

I

9

I

+ γ Port t
PJt+ b ln (GNPPC )+ b ln (GNPPC ) + b ln (DIST )+ b D
11

10

I

12

+ γ Customst
C

J

13

IJ

+ γ RegulatorytR

14+b D +b D

Adjacent

15+ γ Servicet
S

FTA

16 Lang

t

+e ,
JI

where J denotes exporter J and I denotes importer I.

The subscript t denotes time period.

GNP denotes gross national product, GNPPC denotes per capita GDP, and DIST denotes
bilateral distance between the capital cities of countries I and J.

DAdjacent, DFTA, and DLangdenote the dummy variables for two countries being adjacent, two countries being membersof at least one common FTA and two countries having a common official language,
respectively.

Port t is the global average of the port efficiency indicator in time t, and thesame applies to the rest of the indicators.

The inclusion of the average over the cross-section samples is equivalent to including time dummies. They are included in order to see
the temporal efficiency change in each indicator; the coefficients can be interpreted as
temporal efficiency. The inclusion of cross-section average is equivalent to including time
fixed effects, or time dummies, and hence, we will obtain the identical results on thecoefficients for the rest of the regressors. However, the above specification is employedbecause it is useful to know how the marginal effect of raising an indicator changes overtime.

When a panel dataset is available, the fixed effects model is a reasonablespecification where an I-J pair is considered to be the cross-sectional unit, because
unobservable country-pair-specific effects are controlled.

Inclusion of country-pair-fixed

effects rather over-controls the variations due to the differing conditions with respect to tradefacilitation, the effects of any FTA and other bilateral dummies, which are of our central
interest.

Therefore, we use the random effects model to estimate the coefficient parameters.

We also estimate an alternative model with interaction terms between tradefacilitation indicators and time dummies in order to capture the efficiency change, allowing

for the coefficients of the trade facilitation indicator to vary at each period.

Tables 2 and 3 show the regression results.

The major gravity variables haveexpected signs. Also, the coefficients of the trade facilitation indicators are all positive.
They are also all significant, except that for the importer’s customs environment indicator.
The positive signs imply that trade flow increases as trade facilitation is improved.

From

the regression model with average index variables, it is found that the coefficient for port
efficiency is negative, but those for the other categories are positive.

These signs can beinterpreted as the direction of efficiency change, with the positive sign being efficiency
growth in that category and the negative sign being efficiency regress.

Table 2. Regression results of the gravity model (random effects model)
Variables
log of exporter GDP
log of exporter GDP per capita
log of importer GDP
log of importer GDP per capita
log of exporter's port efficiency
log of exporter's regulatory environment
log of exporter's customs environment
log of exporter's service sector infrastructure
log of importer's port efficiency
log of importer's regulatory environment
log of importer's customs environment
log of importer's service sector infrastructure
log of distance
FTA dummy
language dummy
adjacency dummy
2005 dummy
2006 dummy
2007 dummy
2008 dummy

Model with time dummies
1.426***(0.0164)0.0348(0.0274)
0.863***(0.0152)-0.106***(0.0258)
0.851***(0.113)0.174*(0.0952)0.805***(0.118)0.435***(0.107)0.325***(0.0846)
0.411***(0.0954)0.0543(0.0971)0.170**(0.0857)-1.440***(0.0334)
0.233***(0.0454)0.937***(0.0852)
0.672***(0.166)0.0131(0.0164)-0.0782***(0.0191)-0.00175(0.0214)0.0669**(0.0280)-33.35***(0.554)-0.751***(0.157)1.926***(0.350)0.975***(0.216)0.370***(0.0510)-43.26***(1.799)34,8618,700

34,8618,700

mean of port efficiency
mean of regulatory environment
mean of customs environment
mean of service sector infrastructure
constant
Observations
Number of id

Model with time average
1.426***(0.0164)0.0348(0.0274)
0.863***(0.0152)-0.106***(0.0258)
0.851***(0.113)0.174*(0.0952)0.805***(0.118)0.435***(0.107)0.325***(0.0846)
0.411***(0.0954)0.0543(0.0971)0.170**(0.0857)-1.440***(0.0334)
0.233***(0.0454)0.937***(0.0852)
0.672***(0.166)

Source: Author’s estimation.
Note: The significance levels at 10 per cent, 5 per cent and 1 per cent are denoted by *, ** and ***,
respectively.

Table 3 also shows the results for the model with interaction terms between indicatorand time, where only coefficient estimators for trade facilitation indicators are presented.
The mixed signs within category indicate a non-monotonic trend of effects of tradefacilitation in all categories.

Table 4 compares the coefficients across our two models aswell as those estimated in WMO (2005).

They show similar signs in overall.

The results

regarding efficiency change between our two models are quite similar.

Table 3. Regression results of the gravity model with time-indicator interaction terms(random effects model, only coefficients of the indicator variables)
Indicator
Name

Port Efficiency

Regulatory
Environment

Customs
Environment

Service Sector
Infrastructure

Year

Exporter

ImporterBase year (2004)

1.008***

0.469***

2005-0.185-0.08022006-0.1110.08742007

0.0264-0.1692008

0.0513-0.194

Base year (2004)

0.271**

0.561***

2005-0.189**-0.171**2006-0.259***-0.239**2007-0.218**-0.234**2008-0.180*-0.204**

Base year (2004)

0.575***-0.07412005

0.425***

0.121

2006

0.847***

0.262*

2007

0.401***

0.316**

2008

0.372***

0.221

Base year (2004)

0.377***-0.00813

2005

0.294**

0.102

2006

0.263*

0.112

2007

0.194

0.207*

2008

0.439**

0.278*

Source: Author’s estimation.
Note: The significance levels at 10 per cent, 5 per cent and 1 per cent are denoted by *, ** and ***,
respectively.

Table 4. Comparison of estimated coefficients for indicators and their temporary
efficiency change
WMO(2005)
0.924***
0.307*
0.620***
0.281*
n.a.
0.472**
1.943***
0.729***

With timeaveraged TF

With timeinteracted TF

0.851***
0.325***
0.174*
0.411***
0.805***
0.05430.435***
0.170**

1.008***
0.469***
0.271**
0.561***
0.575***-0.07410.377***-0.00813

Efficiency change in Port
Efficiency

n.a.

-

Mixed

Efficiency change in Regulatory
Environment

n.a.

+

Largely -Efficiency change in Customs
Environment

n.a.

+

Largely +Efficiency change in Service
Sector Infrastructure

n.a.

+

Largely +Port Efficiency
Regulatory Environment
Customs Environment
Service Sector Infrastructure

Exporter
Importer
Exporter
Importer
Exporter
Importer
Exporter
Importer

Number of countries
Number of years

75
2

99
5

99
5

Source: WMO (2005) and author’s estimation.

5.

Simulation analysis – gains from trade facilitation reforms in theworld and the ASEAN countries
The gravity model allows us to examine how much trade among the countries in thesample might increase from improved trade facilitation. We will examine scenarios that
focus on improved port efficiency, improved customs environments, improved service sector
infrastructure, and improvements in regulatory environments.

Thus, we can informstakeholders on which specific trade facilitation initiatives might have the greatest potential
to increase trade.

We base our policy simulation on the estimated coefficients in the model in Table 2.
For the simulation of alternative trade facilitation improvements, we first examine theformula with all countries improving trade facilitation by 5 percent. Then we examine theformula which brings the below-average countries in the group half-way to the global
average (approximated by the average for the entire set of countries).

Since each economy

has a specific value for each trade facilitation indicator, each country that is below-averageon that indicator will improve by a different amount so as to climb half-way to the average.

The countries for which we will simulate an improvement in trade facilitation will
differ for each trade facilitation indicator.

However, because trade facilitation links

exporters and importers, all economies enjoy an increase in trade between each other, evenwhen only some have an improvement in their trade facilitation indicator.

Having thecoefficients for both importers’ and exporters’ trade facilitation measures enables us tosimulate the change in trade flow from different perspectives: i.e. the country itself and theregion or world as a whole.

From the standpoint of a specific country, improvement in, for example, port efficiency
should increase both its own imports and exports. The same can be expected for regulatoryenvironment, and service sector infrastructure, as well as customs on the import side. But,a country will export more not only because of its own reforms, but also because of reforms
undertaken by its trading partners as importers.

Thus export gains are the sum of thesimulated effect on exports of unilateral domestic reform and of import reforms undertakenby the country’s trading partners. On the import side, a country’s imports increase first on
account of its unilateral domestic reforms, and secondarily on account of the reforms

undertaken by its trading partners as exporters.

Examining the relative gains to trade fromunilateral reforms as compared to partner’s reforms, and on exports vs. imports, and acrosstrade facilitation indicators, offers three dimensions of potential insight to policymakers,
donors, and the private sector.

5.1. A 5% improvement

Table 5 presents the result of a 5% improvement of trade facilitation indicators.

The

trade gains in percentage are simply equal to 5% times the coefficient of the indicator ofinterest.

Therefore, the magnitude of the percent change is in the same order as thecoefficients.

The total gains from an improvement in all indicators at the same time are$1,634 billion, or 16%. The total gains from exporters, improvement are $1,148 billion, or11%, whereas those from importers’ improvement is $487 billion, or 4.8%.

Table 5. Result of simulation: a collective 5% improvement of trade facilitation (million
USD)
Indicator
Port Efficiency
Regulatory Environment
Customs Environment
Service Sector Infrastructure
Total
Source: Author’s estimation.

Exporter's changevalue% change
431,362
4.26
88,1400.87
408,018
4.03
220,390
2.17
1,147,911
11.32

Importer's changevalue% change
164,823
1.63
208,073
2.05
27,4980.27
86,196
0.85
486,590
4.80

Total
value
% change596,186
5.88
296,2142.92
435,5164.30
306,586
3.02
1,634,502
16.12

5.2. The below-average countries halfway to the global average

The total gain to the world in terms of trade value is found to be $716.4 billion. Table
6 shows that gains from reforms are greatest ($387.9 billion) in regulatory environment
followed by the port efficiency category ($199.6 billions).

The gain from customs

improvement is $104.3 billion and that from service improvement is $24.6 billion.

The

gains to a country increase either by its own trade in facilitation improvement or by its
partners’ improvement in trade facilitation.

Figure 6 shows gains from ASEAN’s own improvement in trade facilitation and its
partners’ improvement.

The increase in ASEAN’s intra-regional trade from its own

improvement is quite small. The gain in its trade with the rest of the world from ASEAN’s
own improvement is three times greater than that from ASEAN’s intra-regional trade gains.
The gain is about halved if only the rest of the world improves trade facilitation.

Thus,

ASEAN’s aggressive improvement would pay off to the region even though the rest of theworld does not make any improvement.

Table 6. Result of simulation: the below-average countries halfway to the global average(million USD)
Indicator
Port Efficiency
Regulatory Environment
Customs Environment
Service Sector Infrastructure
Total

Source: Author’s estimation.

Exporter's changevalue% change
132,392
1.31
120,436
1.19
95,9250.95
14,0570.14
362,809
3.58

Importer's changevalue% change
67,2470.66
267,425
2.64
8,412
0.08
10,5530.10
353,637
3.49

Total
value
% change
199,6391.97
387,861
3.83
104,337
1.03
24,6100.24
716,446
7.07

Figure 6.

Trade gains from ASEAN’s own effort v.s. partners’ efforts (million USD)

30000
25000
20000
15000
10000
5000
0
Within ASEAN

as Exporter with ROW

as Importer with ROWPort Efficiency

Regulatory Environment

Customs Environment

Service Sector Infrastructure

Source: Author’s estimation.

Figures 7 and 7b show total trade gains in each region from the exporters’ andimporters’ perspectives respectively.

In Figure 7a, ASEAN’s exports are estimated toincrease by approximately $34 billion. Gains are around $10 billion in the port, regulatory
and customs categories, but only $1 billion in the service category.

The gains from service

improvement tend to be small both because the elasticity of trade with respect to the service
sector infrastructure indicator is small, and because most ASEAN countries have beensuccessful in their performance in service sector infrastructure improvement.

The ASEAN

region’s estimated total gain is generally greater than MENA, SA and SSA and smaller thanEAP, and LAC.

Figure 7b shows that gains are greatest in ASEAN in the regulatory environment
category; it is approximately $30 billion. On the other hand, the gains are much smaller inthe other categories.

Figure 7a.

Trade gains as exporter by region (million USD)

80000
70000
60000
50000
40000
30000
20000
10000
0
ASEAN

EAP

ECA

LAC

MENA

SA

SSA

Port Efficiency

Regulatory Environment

Customs Environment

Service Sector InfrastructureOECD

Source: Author’s estimation.

Figure 7b.

Trade gains as importer by region (million USD)

120000100000
80000
60000
40000
20000
0
ASEAN

EAP

ECA

LAC

MENA

SA

SSA

Port Efficiency

Regulatory Environment

Customs Environment

Service Sector Infrastructure

Source: Author’s estimation.

OECD

Figure 8a shows trade gains in ASEAN as an exporter, arising from its own
improvement in trade facilitation. In terms of trade value, the Philippines gains most fromits own improvement, in particular $5.6 billion from its improvements in ports. Thailand
gains $4.2 billion from its improvement in its regulatory environment.
billion from its improvement in its customs environment.

Malaysia gains $3.8

In percentage terms, thePhilippines’ gain is the largest (13.9%) from port improvement, followed by improvement in
its regulatory environment (8.5%). Cambodia also gains 7.2% from port improvements.
Thus, different countries gain from their own improvements in different categories of tradefacilitation.

The countries with high trade facilitation scores have less or zero estimatedgain, simply because they improve only slightly or not at all under the current formula.

Figure 8a. Trade gains of the ASEAN countries as exporter by own improvement(million USD)
Source: Author’s estimation.
6000

5000

4000

3000

2000

1000

0
VietnamThailandSingapore

Malaysia

Brunei
Darussalam

Philippines

Port Efficiency

Regulatory Environment

Customs Environment

Service Sector Infrastructure

Indonesia

CambodiaFigure 8b. Trade gains of the ASEAN countries as importer by own improvement(million USD)
12000
10000
8000
6000
4000
2000
0
VietnamThailandSingapore Malaysia

Brunei Philippines Indonesia Cambodia
Darussalam

Port Efficiency

Regulatory Environment

Customs Environment

Service Sector Infrastructure

Source: Author’s estimation.

Figure 8b shows trade gains in ASEAN as an importer from its own improvement intrade facilitation. Overall, trade gains are large from the group’s own improvements in its
regulatory environment.
enjoy large gains.

In terms of trade value, Indonesia, the Philippines and Thailand

In percentage terms, the Philippines’ gain from improvement in its

regulatory environment is the greatest (16.1%), followed by Indonesia (11.8%).

Figures 9a-9b show trade gains as exporter and importer, respectively, from both own
and partners’ improvements in trade facilitation. According to Figure 9a, Singapore’s gainas exporter from improvement in its regulatory environment is the greatest ($9.6 billion),
followed by Thailand ($7.9 billion). Given that Singapore and Thailand themselves do notmake an improvement under the current scenario, this result is mainly because of the large

trade gains from improvement of their major trading partners, most importantly Malaysia
and China, whose regulatory environment scores are lower than the global average.

Itshould be noted, however, that their trade gains are measured in terms of trade value, andthat they are not necessarily the largest in terms of percentage.
gain in percentage is only 4.2%.

For example, Singapore’s

In percentage, the Philippines’ gain from port

improvement is the greatest (14%), followed by its gain from improvement in its regulatoryenvironment (9%). According to Figure 9b, Indonesia’s gain is the greatest ($14.2 billion),
followed by Thailand ($12.2 billion) and Philippines ($12.2 billion), and their gains inpercentage are also high. Those countries gain dominantly from improvement in regulatoryenvironment.

From the fact that their regulatory environment scores were far lower than

the global average, those countries are expected to gain substantially from their own
improvement.

Figure 9a. Trade gains of the ASEAN countries as exporter by global improvement(million USD)
12000
10000
8000
6000
4000
2000
0

Port Efficiency

Regulatory Environment

Customs Environment

Service Sector Infrastructure

Source: Author’s estimation.

Figure 9b. Trade gains of the ASEAN countries as importer by global improvement(million USD)
12000
10000
8000
6000
4000
2000
0

Port Efficiency

Regulatory Environment

Customs Environment

Service Sector Infrastructure

Source: Author’s estimation.

In summary, the results suggest that the ASEAN countries can gain in trade bothfrom their own improvement of trade facilitation as well as from their partners’ improvement.
The most prominent trade gain is witnessed from improvement in regulatory environments,
whereas not much gain is expected from improvement in service sector infrastructure.
crucial shortfall is that Lao PDR and Myanmar are not included in our analysis.

A

Accordingto the other studies, performance of those countries in trade facilitation is similar to or poorer
than the lowest-ranked countries in our analysis.

Thus, those countries are likely to gain

substantially from their own improvement in trade facilitation under the formula used for thesimulation analysis while contribution of their efforts to trade expansion in ASEAN as awhole will be limited due to their relatively small share of trade flow in the region’s trade.

6.

Conclusions
This paper develops measures of trade facilitation, in line with Wilson, Mann andOtsuki’s (2005) indicators, using data that are more up to date, and with a broader country
coverage It investigates their changes over time and their variation across countries andregions, with particular focus on the ASEAN economies.

We consider four categories oftrade facilitation – port efficiency, the customs environment, the regulatory environment andservice sector infrastructure. The paper then estimates the effect of trade facilitation on
trade flows of manufactured goods using a gravity model.

Catching-up by countries withrelatively poor performance in terms of trade facilitation is found to increase trade
substantially, through both import and export channels.

The major findings are as follows:•

ASEAN countries’ performance in trade facilitation is diverse. Singapore, Malaysia
and Brunei are far better than the global average in all categories, whereas thePhilippines, Vietnam and Cambodia fall behind the global average in most categories.
•

When compared with other regions, ASEAN’s average performance is better thanmost developing regions.

It is close to that of Europe, Central Asia and Latin

America and the Caribbean, but is behind the Middle East and North Africa.
•

There is slight improvement in ASEAN’s score over time in port efficiency, and aremarkable improvement in service sector infrastructure.

•The gravity model estimation supports the positive effect of all the four tradefacilitation indicators on bilateral trade flows, and indicates that the effect ofimprovement in the regulatory environment is greatest. The efficiency change is
detected in the categories of customs environment, regulatory environment, andservice sector infrastructure.

•

A simulation analysis is conducted under a scenario that brings below-averagecountries halfway to the global average with respect to each of the four tradefacilitation categories.

The improvement goal is set halfway to the global averagefor the below-average countries, whereas the above-average countries are left
unchanged.

Trade gain arises 1) when a country improves trade facilitation by its

own efforts, or 2) when its trading partner improves trade facilitation.

The greater

is the gain 1) the greater is the estimated elasticity or, 2) the smaller its originalscore is (thus the higher is the target level is), or 3) the smaller is its partners’
original score.
•

The total global trade gain is estimated to be $716 billion.

The gain from

improvement is greatest ($387 billion) in the regulatory environment category,followed by port efficiency ($199 billions).

The gain from improvement incustoms efficiency is $104 billion and that from improvement in service sector
infrastructure is $25 billion.
•

ASEAN’s total gain is estimated to be $99 billion.

About 75% of the gain comesfrom the region’s own improvement, which encourages aggressive commitment toinvestment in trade facilitation.

•Within ASEAN, Vietnam, Cambodia and the Philippines tend to experience agreater percentage increase in their trade flows as a result of their own efforts, thus
supporting the idea of capacity building in countries with relatively poor
performance. Yet, countries with no change in trade facilitation can still enjoy
trade gains from their partners’ improvements.

For example, Singapore can gainnearly $10 billion from its partners’ improvements in their regulatory environments.

Thus, capacity building in the below-average countries is found to be particularly
effective in promoting intra-ASEAN trade, and its trade with the rest of the world.

Thus,

the current focus of the ASEAN in trade facilitation is proved to be rewarding, particularly
under the current situation where there is limited room for further tariff reduction.

It isrecommended that ASEAN focus primarily on regulatory reforms concerning trade throughmaking policies more transparent and ensuring effective and law-abiding operations of theregulatory authorities, in order to realize the returns to their effort rapidly, and on fostering
capacity building in the member countries that lag behind in terms of trade facilitation.

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