BULLETIN OF MONETARY ECONOMICS AND …. Dr. Iwan Jaya Azis Prof. Iftekhar Hasan Dr. M. Syamsuddin...
Transcript of BULLETIN OF MONETARY ECONOMICS AND …. Dr. Iwan Jaya Azis Prof. Iftekhar Hasan Dr. M. Syamsuddin...
1ANALISIS TRIWULANAN: Perkembangan Moneter, Perbankan dan Sistem Pembayaran, Triwulan II - 2007
BULLETIN OF MONETARY ECONOMICS AND BANKING
Directorate of Economic Research and Monetary PolicyBank Indonesia
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Dr. Perry WarjiyoDr. Halim Alamsyah
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BULLETIN OF MONETARY ECONOMICSAND BANKING
Volume 13, Number 1, July 2010
Quarterly Analysis: The Progress of Monetary, Banking and Payment System
Quarter II - 2010
Quarterly Report Team, Bank Indonesia
Do Regional Trade Areas Improve Export Competitiveness? - A Case of Indonesia
Amalia Adininggar Widyasanti
The Impact of ACFTA Implementation on International Trade of Indonesia
Ibrahim, Meily Ika Permata, Wahyu Ari Wibowo
Is ACFTA Proper Strategy of Sustainable Poverty Alleviation?: Proof From The Depletion
of Saving Rate
Bagus Arya Wirapati, Niken Astria Sakina Kusumawardhani
Making East Asian Regionalism Works
Fithra Faisal Hastiadi
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103
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1QUARTERLY ANALYSIS: The Progress of Monetary, Banking and Payment System, Quarter II, 2010
The Indonesian economy in second quarter of 2010 demonstrated a continued
strengthening. This optimism was supported by investment and export performance that grows
higher, in line with the global economic recovery. Economic conditions continued to show an
atmosphere that supports the optimistic better economic outlook than previously thought. The
Indonesian economy in 2010 was estimated to grow towards the upper limit of the range of
5.5% -6.0% and reached 6.0% -6.5% in 2011. In terms of prices, inflationary pressure
throughout the second quarter of 2010 showed an increase caused by the volatile foods, such
as various spices and rice. Meanwhile, the administered prices group and minimal core inflation
contributed to the price development during the second quarter of 2010. Thus, overall the
year, CPI inflation in 2010 will still be in the range of the inflation target of 5% ± 1%.
The global economic recovery still continues, although shadowed by the pressure on
global financial markets and concerns about sustainability of Europe»s economic recovery. The
rate of global economic recovery in the second quarter of 2010 was expected to moderate
compared with the first quarter of 2010. Nevertheless, these developments that remain positive
have raised optimism on global recovery process. The condition was supported by the improving
conditions in developed countries, especially the United States (U.S.) and Japan, as well as a
number of countries in Asia.
In Asia, economic growth showed an increase, in except China which slowed slightly,
related to policies pursued by the Chinese government to overcome the symptoms of
overheating. European crisis has triggered pressure on global financial markets during the second
quarter of 2010, and was reflected by the significant drop in global stock markets and the
soaring Credit Default Swap (CDS) and the yield spread of PIIGS (Portugal, Italy, Ireland, Greece,
and Spain). In Asia, the flight to quality was indicated from the position of net selling by foreign
investors in the stock market, the weakening regional currencies, as well as the rising of sovereign
CDS. So far the impact crisis in Europe has only affected the global financial markets and yet to
significantly influence the overall global economic recovery. Various measures have been taken
QUARTERLY ANALYSIS:The Progress of Monetary, Banking and Payment System
Second Quarter - 2010
Author Team of Quarterly Report, Bank Indonesia
2 Bulletin of Monetary, Economics and Banking, July 2010
by countries which experienced the crisis in Europe such as the austerity program, the help of
European Union (EU) and the International Monetary Fund (IMF) and so far they are capable of
dampening the global financial market turmoil that occurred during the second quarter of
2010
Domestic economic performance the second quarter of 2010 was expected to be better
than previous projections. In the second quarter of 2010, the domestic economy was expected
to grow 6.0%, higher than the previous projection of 5.7%. This optimism was supported by
the investment performance that rises higher. Investment growth was expected to reach 10%
(yoy) in the second quarter of 2010, as a response from domestic and external demand was
getting stronger. Better investment climate was also supported by Indonesia»s sovereign credit
rating which increased along with the improvement of economic fundamentals.
By sector, economic performance in 2010 was mainly supported by trade, hotels, and
restaurants and transport and communications sector. Acceleration for higher domestic economy
needs more support, especially related to the acceleration of the implementation of infrastructure
programs.
Improved economic growth, also reflected in regional economic growth that continued
to grow strong. The performance of the local economy was sustained by the economy activities,
especially in Jakarta, West Java, East Java and Sulawesi, Maluku and Papua. Performance of the
improved regional economic development has been driven mainly by improved performance in
consumption, investment and exports. Growth in household consumption remained strong in
the area, indicated by the increasing growth of consumer credit, retail sales growth remained
high, and stable exchange rate of farmers in various regions. In addition, the regional elections,
which many of them took place in the second quarter of 2010, also played a role in increasing
local consumption. From the investment side, the increase occurred mainly in construction
investment.
Investment activities in building showed an increase in Sumatera, Jakarta and Java, Bali
and Nusa Tenggara. Construction investment activities in these areas, were mostly for the
commercial and residential property sector. In terms of exports, a considerable growth remained
in Kalimantan, Sulawesi, Maluku and Papua and Sumatra to Jakarta for mining commodities
and products, as well as in Java, Bali and Nusa Tenggara for manufacturing product.
In terms of prices, inflationary pressure throughout the second quarter of 2010 showed
an increase that came from the non-fundamental factor. The rising prices of spices and rice
commodities along the second quarter of 2010 have put a significant pressure on CPI. The
inflation of CPI in June 2010 was recorded at 0.97 (mtm), higher than previous months like in
3QUARTERLY ANALYSIS: The Progress of Monetary, Banking and Payment System, Quarter II, 2010
May, and 0.15% -0.14% in April 2010. With these developments, during the second quarter
of 2010, CPI inflation stood at 1.41 (qtq) or reached 5.05% (yoy), increased significantly
compared with the previous quarter which reached 0.99% (qtq) or 3.43% (yoy).
The high inflation of food commodities was due to the supply constraints triggered by
the disruption of production and distribution due to heavy rainfall in some areas. Meanwhile,
the price development of the administered prices group had relatively small impact on CPI
inflation. In terms of fundamentals, core inflation pressures were still relatively low, which was
sustained by the controlled expectations of inflation, the minimum external pressure and the
adequate supply response toward the rising demand. Despite the increase of inflationary pressures
in the second quarter of 2010, in general, the CPI inflation is expected to remain in the range
of the inflation target of 5% ± 1%.
The conducive global economic conditions and the strong domestic economic
fundamentals have supported Indonesia»s balance of payments (neraca pembayaran Indonesia/
NPI) in second quarter of 2010 to remain solid. The current account recorded a surplus estimated,
mainly due to the global economic recovery that continued and the rising trend of global
commodity prices.
In terms of balance sheet capital and financial (transaksi modal dan financial/TMF) of the
second quarter 2010, it is also expected to record a surplus. TMF surpluses were supported by
the re-entry of foreign capital flows in line with the global financial market turmoil which has
subsided and the repair of credit rating outlook for Indonesia. With these developments, the
national reserves at the end of June 2010 reached 76.3 billion U.S. dollars, equivalent to 5.9
months of imports and foreign debt repayments by the Government.
Along with a solid performance of balance of payments and the sustained low risks,
exchange rate is in the strong trends. When compared with the first quarter of 2010, on
average, the rupiah was appreciated by 1.58% (qtq), reaching Rp.9.110 per U.S. dollar. The
strengthening of rupiah in the second quarter was followed by the volatility-which fell from
0.57% in the first quarter of 2010 to 0.47% in second quarter of 2010.
At the end of second quarter of 2010 rupiah closed at Rp9.060 per U.S. dollar, or gained
0.33% (ptp) compared with the first quarter of 2010. Package policies issued by Bank Indonesia
on June 15, 2010 was generally positively responded by market participants both domestically
and internationally so that the pressure on the rupiah exchange rate were relieved, and further
strengthened the monetary management and the deepening of financial markets.
The overall financial market performance in the second quarter of 2010 improved, despite
temporarily depressed in May 2010. SUN market and capital markets condition gradually
4 Bulletin of Monetary, Economics and Banking, July 2010
improved, after a depressed negative sentiment caused by the Europe»s debt crisis in May
2010. The improvement in capital markets and securities in the second quarter of 2010 was
supported by the re-entry of foreign investors and the relieved bubble pressure on the stock
market.
On the interbank money market, the liquidity conditions during the second quarter of
2010 were sufficiently good. The extension of corridor of PUAB O/N per June 17, 2010 had an
impact on the decline in PUAB O/N rates. Parallel with the improving global conditions and
domestic fundamentals, monetary policy transmission continued to improve. This was reflected
in the decline of deposit and credit rates, and credit growth which increased was estimated to
reach 18.6% by June 2010.
From the micro-banking side, national banking conditions remained stable. This was
reflected from the maintained capital adequacy ratio (CAR) as of May 2010 amounted to
17.8%. Meanwhile, the ratio of gross non-performing loans (NPLs) remained at 3.6% with a
net ratio of 1%. In addition, bank liquidity, including liquidity in the interbank money market
sustainably improved and third-party funds (TPF) remained increasing.
It is considered that the BI Rate at 6.5% rate was still consistent with the inflation target
for 2010 at 5% ± 1% and the current direction of monetary policy were also considered
conducive for the economic recovery amid the high global risk resulted from the debt crisis in
a number of European countries. The Bank Indonesia Board of Governors Meeting on July 5,
2010 decided to maintain the BI Rate at 6.5%, with the corridor of PUAB O/N rate as the
operational target for monetary policy ± 100 bps.
5Do Regional Trade Areas Improve Export Competitiveness? - A Case of Indonesia
Amalia Adininggar Widyasanti 1
Indonesia has involved in quite many regional trade agreements, since more than a decade ago.
Theoritically, free trade agreements (FTAs) are very beneficial to the countries, as resources are more
efficiently allocated due to production specialization. However, presence of asymmetric information, market
inefficiency, and economic distortion in the real world have led to a deviation of FTAs benefits from its
theoritical framework. This paper studies whether Indonesian export competitiveness is improving after
Indonesia involves in ASEAN Free Trade Agreement (AFTA) and ASEAN-China Free Trade Agreement
(ACFTA). Export competitiveness are measured by some trade indicators, such as: trade intensity index,
market share, export product dynamics, and RCA, for some Indonesian main export products. The indices
are compared across ASEAN countries and China to reveal: (i) which products are gaining or losing
competitiveness in ASEAN and China markets; and (ii) which countries are becoming Indonesian main
competitors in ASEAN and China markets. Additionally, this paper ends up with some policy
recommendations that Indonesia should undertake to improve competitiveness of its products in ASEAN
and China markets.
JEL ClassificationJEL ClassificationJEL ClassificationJEL ClassificationJEL Classification: R11, F16
Keywords: FTA, export competitiveness, Indonesia.
1 Amalia Adininggar Widyasanti is currently a Deputy Director for Trade at The Ministry of National Development Planning. Sheobtained her PhD degree in Economics from The University of Melbourne, Australia. Views and opinions expressed in this paper areher own and not representing statements of The Ministry
Abstract
DO REGIONAL TRADE AREAS IMPROVE EXPORT COMPETITIVENESS? -A CASE OF INDONESIA
6 Bulletin of Monetary, Economics and Banking, July 2010
I. INTRODUCTION
According to the theory of international trade, Free Trade Areas (FTAs) are accepted as
their mutual benefits from such trade are very beneficial to the countries due to the concept of
comparative advantage. A country will specialize in producing the products that it has a
comparative advantage. By this specialization, the world can expand total world output with
the same quantity of resources, as the economic efficiency is increased. Therefore, theoritically,
an FTA can assure that all countries involved in the agreement will gain from the trade creation
and trade diversion.
The recent trends of free trade agreements (FTAs) shows that countries in the world have
involved in many trade agreements, either bilateral or regional trade agreements. Data in Figure
1 suggests that the increase of world FTAs has been significant since 2002.
The data also shows that up until now the number of FTAs in the world is 221 agreements,
rising as much as 152 agreements from the year 2002, which was only 69 agreements. Numbers
of regional and bilateral agreements are increasing as those agreements are believed to be the
second-best option of FTA after the multilateral agreement. Because the implementation of
multilateral agreement is not optimally implemented, countries prefer to undertake quite many
regional and bilateral agreements in order to expand their trade and to strengthen their economic
relations with other countries.
Figure II.2 shows the classifications of FTA into bilateral and plurilateral agreements. Bilateral
agreement refers to a preferential trading arrangement where it involves only two parties.
Figure II.1:Development of FTAs in the World (1991-2010)
Numbers of FTAs
250
200
150
100
50
0
221210
195
134
94
8
69
Year«93«92«91 «04«95«94 «03«02«01«00«99«98«97«96 «05 «06 «08 «09«07 «10
Source: Asia Regional Integration Center Database, ADB (modified)
7Do Regional Trade Areas Improve Export Competitiveness? - A Case of Indonesia
Correspondingly, plurilateral agreement is a preferential trading arrangement that involves
more than two parties. Based on the figure, it can be seen that bilateral arrangement dominates
plurilateral arrangement, where it accounts for 77 % out of total 221 agreements in 2009.
Therefore, only 23% of the agreements are plurilateral.
Indonesia has also involved in quite many trade arrangements. Up until now, it has
implemented 7 agreements that are already in effect, and 8 arrangements that are still in the
process of negotiation or study. Table 1 shows the FTAs that Indonesia has involved.
This paper will focus on analyzing the competitiveness of Indonesian export products
after the implementation of ASEAN Free Trade Area (AFTA) and ASEAN-China Free Trade Area
(ACFTA). The reason why these FTAs are selected is because: (i) ASEAN and China are Indonesia»s
main export markets; and ASEAN countries are also Indonesian main competitors in these
markets.
Source : Asia Regional Integration Database, ADB (modified)
51(23%)
170(77%)
BILATERAL
PLURILATERAL
Figure II.2:Classification of Trade Arrangements
8 Bulletin of Monetary, Economics and Banking, July 2010
II. INDONESIA AMONG AFTA AND ACFTA
The ASEAN Heads of State and Governments decided to establish an ASEAN Free Trade
Area or AFTA in January 1992. The objective of AFTA is to eliminate tariff barriers among the
Southeast Asian countries with a view to integrating the ASEAN economies into a single
production base and creating a regional market; which will be done through elimination of
intra-regional tariffs and non-tariff barriers. The ASEAN Free Trade Area or the AFTA is perceived
to be the soul of ASEAN economic integration. The implementation of AFTA is started in January
1993. The schedule of tariff reduction for AFTA are scheduled under CEPT (Common Effective
Preferential Tariff)-Scheme, and the schedule of tariff reduction for ASEAN-6 more advanced
than CMLV countries (Cambodia, Myanmar, Lao, and Vietnam). Under the CEPT-scheme,
products are categorized into 5 (five) groups, i.e. Inclusion List (IL), Sensitive List (SL), Highly
Sensitive List (HSL), Temporary Exclusion List (TEL), and General Exception List (GEL).
For Indonesia, total numbers of tariff lines that are put under CEPT Scheme is 11.153
lines; where 98.9% or 11.028 tariff lines are included in Inclusion List. The rest of it is belong
to General Exclusion List and Sensitive List. Structure of Indonesian tariff under the CEPT scheme
can be seen in the Figure below.
Table II.1Lists of FTAs that Indonesia has involved
No Name of Arrangement Status
Source: Asia Regional Integration Database, ADB (modified)
ASEAN Free Trade Area
ASEAN-Australia and New Zealand Free Trade Agreement
ASEAN-India Regional Trade and Investment Area
ASEAN-Japan Comprehensive Economic Partnership
ASEAN-Korea Comprehensive Economic Cooperation Agreement
Japan-Indonesia Economic Partnership Agreement
ASEAN - China Comprehensive Economic Cooperation Agreement
ASEAN-EU Free Trade Agreement
Comprehensive Economic Partnership for East Asia (CEPEA/ASEAN+6)
East Asia Free Trade Area (ASEAN+3)
India-Indonesia Comprehensive Economic Cooperation Arrangement
Indonesia-Australia Free Trade Agreement
Indonesia-European Free Trade Agreement
Pakistan-Indonesia Free Trade Agreement
United States-Indonesia Free Trade Agreement
In effect
In effect
In effect
In effect
In effect
In effect
In effect
Under negotiation
Proposed/Under consultation and study
Proposed/Under consultation and study
Proposed/Under consultation and study
Proposed/Under consultation and study
Proposed/Under consultation and study
Under Negotiation
Proposed/Under consultation and study
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
9Do Regional Trade Areas Improve Export Competitiveness? - A Case of Indonesia
ASEAN Member Countries have made significant progress in lowering the intra-regional
tariffs through the Common Effective Preferential Tariff (CEPT) Scheme for AFTA. More than 99
percent of the products in the CEPT Inclusion List (IL) of ASEAN-6, comprising Brunei Darussalam,
Indonesia, Malaysia, the Philippines, Singapore and Thailand, have been brought down to the
0-5 percent tariff range. Figure II.4 shows us that imports of ASEAN-6 countries from that
regional is increasing along with the decrease of import tariff in ASEAN-6.
In November 2004, at the 10th ASEAN Summit in Vientiane, Lao PDR, the Economic
Ministers of ASEAN and China signed the Agreement on Trade in Goods (TIG) of the Framework
Agreement on Comprehensive Economic Cooperation between ASEAN and China. This is well-
Figure II.3: Structure of Indonesian Tariff Lines under CEPT Scheme
Figure II.4: Development ofImports and Tariff in ASEAN-6
Source: Ministry of Finance
11.0280
25
100
IL TEL GEL SL/HSL
Imports ($ Million) Tariff, %(Weghted Average)
Source: UNCTAD-Train Database (modified)
Imports (Million USD)
Tarif (Weghted Average)
0
20,000
40,000
60,000
80,000
100,000
120,000
140,000
160,000
180,000
0
2
4
6
8
10
12
14
16
18
«93 «94 «95 «96 «97 «98 «99 «00 «01 «02 «03 «04 «05 «06 «07
10 Bulletin of Monetary, Economics and Banking, July 2010
known as the ASEAN-China Free Trade Agreement (ACFTA), where its implementation has
come into force since July 1, 2005. In this agreement, the tariff lines under the modality of tariff
reduction was classified into 3 groups, i.e early harvest program, normal track, and sensitive
track. Tariff lines placed in the Normal Track the Normal Track the Normal Track the Normal Track the Normal Track have been gradually reduced and eliminated
according to the following Schedules (ASEAN-6 and China):
Table II.2Modality of Normal-Track Tariff Reduction for ASEAN-6
* The first date of implementation shall be 1 Jully 2005
X > 20% 20 12 5 0
15% < x < 20% 15 8 5 0
10% < x < 15% 10 8 5 0
5% < x < 10% 5 5 0 0
x < 5% Standsill 0 0
X = Applied MFNTariff Rate
ACFTA Preferential Tariff Rate(Not Later than 1 January)
2005* 2007* 2009 2010
However, the tariff reduction under Sensitive Tracks is starting to be implemented in
2012 for the Sensitive Lists, and it shall be gradually reduced to 0-5% not later than 1 January
2018. Furthermore, the tariff of products under high sensitive list should not exceed 50%
started in 2015.
Figure II.5:Import Tariff and Trade Balance of ASEAN-6 and China (2000-2007)
Source: UNComtrade and UNCTAD-Trade Database
Tariff (Weighted Average), %
Tariff Applied to ASEAN-6 in China Market
Tariff Applied to China in ASEAN-6 Market
0
2
4
6
8
10
12
14
16
2000 2001 2002 2003 2004 2005 2006 2007
2008
2007
2006
2005
2004
2003
2002
2001
2000
-15000 -10000 -5000 0 5000
Trade Balance of Indonesia With China
Trade Balance of ASEAN-6 With China
Trade Balance ($ Million)
11Do Regional Trade Areas Improve Export Competitiveness? - A Case of Indonesia
The Figure above shows us that the weighted-average tariff has been decreasing both in
ASEAN-6 and China market. Whereas, deficit in trade balance of ASEAN-6 with China tends to
increase, meaning that ASEAN-6 imports is increasing more rapidly than its exports to China.
On the other hand, the total trade balance of Indonesia with China tends to be surplus. But,
this is not the case for non oil-and-gas trade balance of Indonesia with China, where its trade
balance has started to be deficit since 2005. Therefore, Indonesian trade surplus with China
was due to a big surplus in Indonesian trade of oil and gas to China.
III. COMPETITIVENESS INDICATORS
Some literatures (Ng, 2002; Mikic, 2005; ITC Market Analysis Section, 2000; World Bank
Institute, 2010) have provided indicators and indices that are commonly used for international
trade analysis. However, this paper chooses some of the competitiveness indicators that are
considerably practical to analyze whether Indonesian export products are loosing or gaining
their competitiveness after AFTA and ACFTA come into effect. The indicators are export intensity
index, market share, and dynamic RCA.
Export intensity index is a measure of whether or not a country exports more to a given
destination than the world does on average. The expression is defined by the following equation:
Figure II.6: Non-Oil and Gas Trade Balanceof Indonesia with China (2004-2010)
Source: Ministry of Trade (modified)
2008
2007
2006
2005
2004
2003
2002
-8,000,000 -6,000,000 -4,000,000 -2,000,000 0 2,000,000
Trade Balance Indonesia with China
Trend of Trade Balance
ww
wj
iw
ij
ijX
x
X
xEII =
(II.1)
12 Bulletin of Monetary, Economics and Banking, July 2010
where xij is the dollar value of exports of country/region i to country/region j, X
im is the dollar
value of the exports of country/region i to the world, xmj
is the dollar value of the world exports
to country/region j, and Xmm
is the dollar value of market exports. An index of more than one
indicates that trade flow between countries/regions is larger than expected given their importance
in the trade.
Market share is measured by the following equation:
Where:
MSij = Market Share of country i in market j.
X ij = Exports of country i to market j.
M j
= Imports of market j.
Dynamic RCA is a modification of static RCA, and it is not yet common in use as the
static RCA has been. Dynamic RCA has been used by Edwards and Schoer (2001) to analyze
the structure and competitiveness of South African Trade.
The advantages of using the dynamic RCA are: (i) it describes RCA over some period of
time; and (ii) it provides product positioning in the export destination countries, as it offers
some criteria to cluster products according to their positions in the market. Therefore, dynamic
RCA is more useful than traditional RCA, particularly if the study is going to identify which
products are gaining or loosing the markets and to provide policy recommendation based on
market positions of the export products. In addition, dynamic RCA is more informative than
static RCA in explaining how competitive is the export products.
In this paper, the formula of dynamic RCA, which were referring to Edwards and Schoer
(2001) is calculated using the formula below and was slightly modified to fit in with the ASEAN
or China Market as follows:
%100×=j
ij
ijM
XMS
(II.2)
∑
∑
∑
∑
∆
−
∆
=∆
=
j
jm
jm
j
jm
jm
j
ji
ji
j
ji
ji
j
j
j
X
X
X
X
X
X
X
X
RCA
RCADRCA
,
,
,
,
,
,
,
,
(II.3)
13Do Regional Trade Areas Improve Export Competitiveness? - A Case of Indonesia
Where:
DRCA j = dynamic RCA indicator
X i,j
= exports of commodity j of country i to destination market (ASEAN or China)
X m,j
= exports of commodity j of ASEAN countries to destination market (ASEAN or China)
The first term of the right hand side refers to the export share of commodity j in the
reporting country»s total export to the destination market. The second term refers to the export
share of ASEAN countries of commodity j to the total ASEAN exports directed to the destination
market.
Edwards and Schoer (2001) provided a positioning matrix that is very useful to analyze
the competitiveness of the products under evaluation. The matrix is given in Table II.3.
Table II.3Positioning Matrix of Export Competitiveness
Adapted from Edwards and Shoer (2001)
Share of j ina country»s export
Share of j ina market»s export Position
Increasing RCAIncreasing RCAIncreasing RCAIncreasing RCAIncreasing RCA
Decreasing RCADecreasing RCADecreasing RCADecreasing RCADecreasing RCA
>
<
<
<
>
>
Rising stars
Falling stars
Lagging retreat
Lost opportunity
Leading retreat
Lagging opportunity
IV. DATA AND METHODOLOGY
The Data used in this paper is mainly obtained from UNCOMTRADE Database, which
was retrieved using World Integrated Trade Solution (WITS) application. The export data is
taken from 1996-2008 for ASEAN countries and China. Data for ASEAN countries consists of
Indonesia, Malaysia, Singapore, Thailand, Philipines, and Brunei, because the rest of ASEAN
countries do not have a complete data set available in WITS. The product analysis refers to
classification of 2-digit HS 1996.
Calculation of Export Intensity Index is specifically obtained from Asia Regional Integration
Center Database in Integration Indicator Database, which is available to be downloaded from
http://aric.adb.org/indicator.php.
14 Bulletin of Monetary, Economics and Banking, July 2010
A further classification of HS-1996 is also used in this paper for simplifying the analysis.
The classification in Table II.4 is referred HS-1996 Classification by sections with some
modifications in it to shorten the category.
V. RESULTS AND ANALYSIS
V.1. AFTA
Before the implementation of AFTA, which is in 1992, the contribution of Indonesia in
ASEAN-6 exports to ASEAN-6 is about 12.7%. Then this share is decreasing in 1995, but
started to gradually increase up until now. Most of the export commodities/products of Indonesia
are either increasing or stable in market share. This means that Indonesian products are quite
competitive in ASEAN market.
However, there are some products that are loosing the market. Those are chemicals,
textiles, skin and leather products, and machinery/electricals. The main competitors of these
products are Malaysia for Chemicals, Singapore for Machinery/Electricals, Thailand for textiles,
and Vietnam for textiles and Skin/leather products.
Table II.4Product Classification under HS-1996 Codes
No Product Classification HS Codes
1 Live animals and animal products 01-052 Vegetable Products 06-143 Animal or Vegetable Fats and Oil 154 Foodstuffs 16-245 Mineral Products 25-276 Chemicals 28-387 Plastics and Rubbers 39-408 ΩSkin and leather 41-439 Wood & Wood Products 44-49
10 Textiles 50-6311 Footwear 64-6712 Stone and Glass 69-7113 Metals 72-8314 Machinery / Electrical 84-8515 Transportation 86-8916 Miscellaneous 90-97
Source: UNComtrade, http://comtrade.un.org/kb/article.aspx?id=10253 (modified by author)
15Do Regional Trade Areas Improve Export Competitiveness? - A Case of Indonesia
In Table II.6, it can be seen that export intensity index of ASEAN countries is increasing
particularly in 2000s, with a slight decrease in 1995. Indonesia»s export intensity index has been
increasing, which means that AFTA has helped Indonesia to export more to other ASEAN
countries, causing export intensity of Indonesia to continously increase. Other ASEAN countries,
such as Malaysia, Singapore, and Thailand has also been experiencing an increase of export
intensity index. Therefore, AFTA has improved trade flows among countries in this region.
Table II.5Market Share of Indonesian Export Products in ASEAN
Market Share
Total 12.7% 8.8% 10.1% 10.1% 10.8% 11.6%Animal/Veg Oils 30.5% 24.2% 48.9% 51.1% 53.7% 57.5%Foodstuffs 15.0% 13.2% 16.8% 18.4% 18.2% 20.2%Footwears 15.9% 11.5% 28.0% 28.3% 24.6% 21.5%Metals 2.8% 3.3% 24.3% 23.6% 23.4% 25.3%Transportation 7.0% 14.4% 12.4% 15.6% 14.0% 17.1%Plastics&Rubber 6.5% 8.1% 9.2% 9.6% 10.3% 10.8%Wood Products 20.1% 19.1% 23.6% 24.3% 23.1% 22.7%Vegetable 17.3% 15.0% 13.4% 12.1% 10.4% 8.1%Mineral Products 19.5% 13.4% 9.8% 10.5% 12.1% 12.1%Miscellanous 6.9% 21.0% 6.7% 9.0% 9.8% 8.4%Animal Products 18.4% 18.7% 18.3% 17.5% 19.0% 22.3%Stone/Glass 20.1% 20.1% 16.4% 22.6% 20.9% 19.1%Chemicals 13.2% 9.7% 9.5% 9.3% 13.8% 9.9%Machinery/Electricals 14.2% 8.8% 6.8% 5.7% 5.5% 6.0%Skin/Leather products 20.2% 9.2% 10.7% 16.0% 13.3% 8.7%Textiles 55.7% 21.3% 25.2% 22.7% 22.1% 19.9%
Source: UNCOMTRADE Database (computed by author)
Product1992 1995 2005 2006 2007 2008
IncreasingMarketShare
Stable MarketShare
DecreasingMarketShare
Table II.6Export Intensity Index of ASEAN Countries in ASEAN Market
ASEAN 4.05 3.67 4.66 4.63 4.67 4.56
Indonesia 2.71 2.14 3.40 3.40 3.62 3.54
Malaysia 6.02 4.14 4.80 4.84 4.76 4.61
Singapore 4.53 4.55 5.77 5.72 5.87 5.71
Thailand 2.73 2.97 4.05 3.87 3.95 4.04
Viet Nam 3.98 2.97 3.26 3.09 3.09 2.91
Reporter 1992 1995 2005 2006 2007 2008
16 Bulletin of Monetary, Economics and Banking, July 2010
Another interesting result in this paper is presented in Figure II.7 concerning positioning
of Indonesian Export Competitiveness in ASEAN Market by product groups. It seem to be
satisfying that there is only 1 product group (out of 16 product groups) which has been loosing
its competitiveness in ASEAN market, as it has lost its opportunity. The product is vegetable.
There are quite many products include in the rising star groups, which are very promising to the
future of Indonesia»s trade with ASEAN. However, Indonesia has to put its attention to some
products which have lagging-opportunities. Those are metals and mineral products. According
to the results, growth of Indonesian market share for these products in ASEAN is still lower
than growth of ASEAN demand for these products. Meaning that Indonesia still have more
opportunities to increase its share of these products in ASEAN Market. In general, Indonesia
has entered to the right market in ASEAN.
Figure II.7.Positioning of Indonesian Export Competitiveness in ASEAN Market (2003-2008)
Growth of Share of jin a country»s export
Note := Increasing RCA
= Decreasing RCA
Growth of Share of jin a market»s export
Rising Star
Falling StarLagging Retreat
Lost Opportunity
LeadingRetreat
Lagging Opportunity
14
1
109
6 11
2 13
5
34
715
8
12
16
1 = Live animals and animal products, 2 = Vegetable Products, 3 = Animal or Vegetable Fats and Oils, 4 = Foodstuffs,5 = Mineral products, 6 = Chemicals, 7 = Plastics and Rubbers, 8 = Skin and Leather, 9 = Wood and Wood Products,10 = Textiles, 11 = Footwear, 12 = Stone and Glass, 13 = Metals, 14 = Machinery/Electricals, 15 = Transportation,16 = Miscellaneous
17Do Regional Trade Areas Improve Export Competitiveness? - A Case of Indonesia
V.2. ASEAN-China FTA
After the implementation of ASEAN-China FTA, the structure of Indonesian exports to
China has slightly changed. Before ACFTA, wood and articles of wood (HS-44) was among the
top 10 Indonesian export commodities to China, where its share in the total exports to China is
7.2%. However, after ACFTA, this commodity was replaced by Ores, slag, and ash (HS-26). In
addition, the share of mineral fuels, oils and product (HS-27) and animal/vegetable fats and oil
(HS-15) are increasing from 26.1% and 12.8% in 2004 to 39.2% and 18.2% in 2008. The
main reason for this is because in recent years China imported more industrial raw materials
due to the increase of its industrial activities and production. This reason is also supported by
the fact that China has increased its imports of Ores, slag, and ash and articles of iron or steel.
As Indonesia is one of the main world suppliers for mining products due to its natural resources,
therefore exports of Indonesia to China for this product is also increasing.
Table II.7Top 10 Commodities of Indonesian Exports to China (2004 and 2008)
27 Mineral fuels, oils & product of th 26.1% 27 Mineral fuels, oils & product of th 39.2%
15 Animal/veg fats & oils & their clea 12.8% 15 Animal/veg fats & oils & their clea 18.2%
29 Organic chemicals. 12.3% 40 Rubber and articles thereof. 7.7%
44 Wood and articles of wood; wood ch 7.2% 46 Manufactures of straw 6.4%
46 Manufactures of straw 5.7% 26 Ores, slag and ash. 5.6%
40 Rubber and articles thereof. 5.5% 29 Organic chemicals. 2.9%
47 Pulp of wood/of other fibrous cellu 4.3% 73 Articles of iron or steel. 2.7%
84 Nuclear reactors, boilers, mchy & m 4.2% 84 Nuclear reactors, boilers, mchy & m 2.4%
83 Miscellaneous articles of base metal 2.7% 83 Miscellaneous articles of base metal 2.2%
73 Articles of iron or steel. 2.6% 47 Pulp of wood/of other fibrous cellu 1.7%
Share to Total Exports to China Share to Total Exports to China Share to Total Exports to China Share to Total Exports to China Share to Total Exports to China 83.4% Share to Total Exports to ChinaShare to Total Exports to ChinaShare to Total Exports to ChinaShare to Total Exports to ChinaShare to Total Exports to China 89.01%
2004 Share 2008 Share
Source: UNCOMTRADE (computed by Author)
Table II.8 shows Indonesian market share in China market by product category. The
denominator of the share is total exports of ASEAN-6 + Vietnam to China Market. From the
data it can be seen that share of Indonesian export in China market tends to be stable with a
little increase in 2008. Some Indonesian products are gaining market in China after the
implementation of ACFTA in 2005. Those products are Animal/Vegetable Oils and fats, Foodstuffs,
Footwears, Metals, Mineral Products, Plastics and Rubber, as well as Skin/Leather products. It
can be seen that products that generallly gain increasing market share in China are natural-
resource based; classifying as agricultural and mining products; except footwear. Manufacturing
18 Bulletin of Monetary, Economics and Banking, July 2010
products, such as: woods, textiles, chemicals, and machinery/electrical products, are experiencing
a decrease in market share. This is because these products cannot compete with local China
products or with other ASEAN countries» products.
Table II.8Market Share of Indonesian Exports in China (2005-2008)
Market Share
Total 22.2% 20.4% 20.8% 19.8% 19.6% 22.4%Animal/Veg Oils 24.7% 29.6% 36.4% 39.6% 34.1% 34.7%Foodstuffs 5.4% 5.2% 7.7% 5.5% 7.1% 6.9%Footwears 20.5% 21.7% 24.3% 21.0% 29.4% 31.4%Metals 16.9% 14.3% 21.4% 22.4% 14.7% 16.4%Mineral Products 22.9% 21.1% 38.5% 39.7% 40.9% 38.1%Plastics&Rubber 6.3% 8.1% 8.1% 9.9% 10.0% 10.1%Skin/Leather products 4.1% 6.5% 14.3% 20.7% 17.3% 17.9%Miscellanous 1.5% 2.2% 2.3% 2.8% 3.3% 3.0%Vegetable 4.4% 4.9% 4.5% 3.5% 4.5% 6.7%Transportation 4.3% 6.6% 8.2% 8.8% 7.2% 2.5%Animal Products 25.5% 26.8% 21.5% 17.5% 9.0% 18.1%Chemicals 18.2% 19.3% 19.1% 16.5% 16.1% 14.3%Machinery/Electricals 1.6% 1.7% 1.2% 1.2% 1.3% 1.5%Stone/Glass 15.2% 20.7% 14.8% 10.7% 8.3% 4.9%Wood Products 59.1% 53.2% 49.6% 50.4% 46.4% 53.0%Textiles 31.7% 25.2% 20.9% 22.6% 22.7% 22.6%
Product2003 2004 2005 2006 2007 2008
IncreasingMarketShare
Stable Market Share
DecreasingMarketShare
The Indonesian main competitor of Chemicals, Machinery/Electricals, Wood products,
and Textiles in China market is Thailand; as its shares is increasing after ACFTA was implemented.
In addition, Vietnam is also a good supplier of wood products and textiles to China market, its
share is increasing under ACFTA framework. But, products of machinery/electricals and chemicals
of Vietnam do not seem to be competitive in China market.
Export Intensity Index of ASEAN countries in China Market tends to increase (Table II.9),
as China»s export intensity index in ASEAN has also increased. Export Intensity Index for all
countries in any year is always greater than 1, showing that trade flows between ASEAN countries
to China, or the other way around, is larger than expected given their importance in such
regional trade. This means that the implementation of ACFTA does increase trade intensity
among the participating countries and in general improve trade flows among the countries in
the region.
19Do Regional Trade Areas Improve Export Competitiveness? - A Case of Indonesia
The results of dynamic RCA calculation are summarized in the chart below (Figure II.8) to
portray the competitiveness positioning of Indonesian export products in China market. The
products were classified into the category mentioned in Table II.4.
From the result, it can be seen that there are only 3 product groups which are in ≈rising
star∆. Those products are mineral products, plastics and rubbers, and footwear. The products
which are in ≈lagging opportunity∆ are Animals/vegetable oils and fats and foodstuffs. Lagging
opportunity means that demands on these products in China are quite high, but the rate of
export growth of these products are still lower than that of the demands. Most of Indonesian
export products in China market is categorized as leading retreat and lagging retreat. On the
other hand, Indonesia in the future should not focus on exporting skins and leather as demands
in China Market for this product is decreasing.
Table II.9Export Intensity Index of ASEAN countries and China
ASEAN China 1.31 1.35 1.42 1.46 1.49 1.45
Indonesia China 1.24 1.20 1.38 1.39 1.38 1.37
Malaysia China 1.30 1.24 1.17 1.22 1.42 1.54
Singapore China 1.26 1.44 1.52 1.64 1.57 1.48
Thailand China 1.42 1.37 1.46 1.52 1.58 1.48
Viet Nam China 1.87 2.04 1.76 1.37 1.22 1.16
China ASEAN 1.31 1.34 1.34 1.37 1.43 1.43
Reporter Partner 2003 2004 2005 2006 2007 2008
Reporter Partner 2003 2004 2005 2006 2007 2008
20 Bulletin of Monetary, Economics and Banking, July 2010
VI. CONCLUSIONS
This paper provides some analysis about competitiveness of Indonesian export products
in ASEAN and China, after the implementation of ASEAN FTA and ASEAN-China FTA. The
competitiveness indicators used in this paper is market share, export intensity index, and dynamic
RCA. The results show that Indonesia is doing well in ASEAN Market by gaining some market
for some products. However, some policy strategy is needed for the products, particularly for
vegetable products which has lost the opportunity in ASEAN markets. Some policies needed
would be product diversification, improvement in quality control, and health-related concerns.
In China market, Indonesia gained the market only for the products of plastics and rubber,
mineral products, and footwear. The products which are in ≈lagging opportunity∆ are Animals/
vegetable oils and fats and foodstuffs; meaning that Indonesia can still do some improvement
to optimize the opportunity, as the rate of export growth of these products are currently still
lower than that of the demands. Most of Indonesian export products in China market is
categorized as leading retreat and lagging retreat. In the case of ACFTA, Indonesia can still do
more to improve its export performance in China market.
Figure II.8.Positioning of Indonesian Product Competitiveness in China Market Using Dynamic RCA
1 = Live animals and animal products, 2 = Vegetable Products, 3 = Animal or Vegetable Fats and Oils, 4 = Foodstuffs,5 = Mineral products, 6 = Chemicals, 7 = Plastics and Rubbers, 8 = Skin and Leather, 9 = Wood and Wood Products,10 = Textiles, 11 = Footwear, 12 = Stone and Glass, 13 = Metals, 14 = Machinery / Electricals, 15 = Transportation,16 = Miscellaneous
Growth of Share of jin a country»s export
Note := Increasing RCA
= Decreasing RCA
Growth of Share of jin a market»s export
Rising Star
Falling StarLagging Retreat
Lost Opportunity
LeadingRetreat
Lagging Opportunity
1016
13
1
2
8614
9
12
154
3
7
5 11
21Do Regional Trade Areas Improve Export Competitiveness? - A Case of Indonesia
Edwards and Schoer (2001). The Structure and Competitiveness of South African Trade, Trade
and Industrial Policy Strategy √ Annual Forum, Muldersdrift.
Ng (2002). Trade Indicators and Indices, in Development, Trade, and WTO: A Handbook, edited
by Hoekman, Mattoo, and English, The World Bank, Washington DC.
Mikic (2005). Commonly Used Trade Indicators: A Note, presented at ARTNeT Capacity Building
Workshop on Trade Research, UNESCAP.
ITC Market Analysis Section (2000). The Trade Performance Index √ Background Paper, UNCTAD/
WTO.
Utkulu and Seymen (2004). Revealed Comparative Advantage and Competitiveness: Evidence
for Turkey vis-à-vis the EU/1, paper presented at the European Trade Study Group 6th Annual
Conference, Nottingham.
World Bank Institute (2010). World Trade Indicators 2009/2010 √ User Guide to Trade Data,
The World Bank.
REFFERENCES
22 Bulletin of Monetary, Economics and Banking, July 2010
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23The Impact of ACFTA Implementation on International Trade of Indonesia
THE IMPACT OF ACFTA IMPLEMENTATIONON INTERNATIONAL TRADE OF INDONESIA
IbrahimMeily Ika Permata
Wahyu Ari Wibowo1
This study analyze the impact of the implementation of trade agreements within the framework of
ACFTA on Indonesia»s export by using the GTAP model; a Multi Regional Computable General Equilibrium
Model. Results shows that ACFTA provide opportunities for increased export from Indonesia; Indonesia
obtained a net trade creation of international trade amounted to 2% and total exports growth increased
by 1.8. However, the export performance of Indonesia in the period showed a decrease of competitiveness,
as shown by the decline in share of Indonesian export commodities which are highly competitive and high
intra-industry linkage. This paper also find that because the commodity structure of China and the non
compeeting behavior of ASEAN countries including Indonesia (tends to complement), China is relatively
easier to penetrate export to the Asean market. The entering products from China should provide
opportunities for domestic producers to increase production capacity in ASEAN, due to wider choice of
relatively cheap capital goods imports.
JEL ClassificationJEL ClassificationJEL ClassificationJEL ClassificationJEL Classification: C67, F14, R12
Keywords: ACFTA, trade, export, GTAP, Revealed Comparative Advantage, CGE.
1 The authors are researchers at the BRE-DKM Bank Indonesia and are responsible for the results this research and all opinions. Thank-you note is addressed to the Chairman DKM, Perry Warjiyo and Iskandar Simorangkir, and all other researchers who have supportedthis research
Abstract
24 Bulletin of Monetary, Economics and Banking, July 2010
1. INTRODUCTION
The development of international trade leads to more liberal forms of trade that are
accompanied by various forms of bilateral, regional and multilateral cooperation. One of the
main objectives of international trade agreements is to reduce or eliminate trade barriers.
Liberalization of world trade, with the pattern of international cooperation, provide a positive
implication on the growth of world economy. The value of world trade grew more than twice
the growth in gross domestic product (GDP) of real world (Krueger, 1999).
In the mid-1980s, preferential trading arrangements (PTA), developed as a complement
to international cooperation. In contrast to international cooperation, PTA involves two or more
countries. Based on the theory of PTA, as described by Kemp (1964) and Vanek (1965), the
impact of two or more countries that make up a custom unions (common external tariff) is the
growing prosperity of the countries that joined the union and it does not cause any decline on
the welfare of countries outside the union. This is proved in a study by Ohyama (1972) and
Kemp and Wan (1976). Rather than setting a common external tariff, a more developed pattern
of PTA is the elimination of intra-trade barriers or more familiar known as the free trade agreement
(FTA). Some FTAs that have been running are the North American Free Trade Area (NAFTA), the
European Economic Area (EEA), the African Free Trade Zone (AFTZ) and the South Asia Free
Trade Agreement (SAFTA).
Likewise with Indonesia which has agreed on trade cooperation both bilaterally, regionally
and internationally. Although Indonesia»s involvement in these various trade cooperation causes
a challenge to domestic products, the goal of these agreements are provide positive impact to
the economy of the countries involved and to economy of Indonesia in particular.
Related to the regional area, Indonesia joined the ASEAN Free Trade Area (AFTA) which
was signed on January 28, 1992. In its development, the cooperation extended to involve
other countries including China, known as the ACFTA. In particular, the involvement of Indonesia
in ACFTA need for further observed. This is related to many factors such as the readiness of
domestic products to encounter the rush of imported goods from China and the ASEAN market
that is potentially reduced for domestic products. Many literatures and existing studies have
widely reviewed the impact of ACFTA by various dimensions and analysis tools. This research is
expected to become one of the complementary study on the impact of ACFTA with new added
value. Thus, information associated with the study of ACFTA market trading will be more
complete.
The objective of this paper are (i) To contribute to the study of external sector, particularly
the international trade of Indonesia, (ii) To provide an understanding of Indonesia»s trade structure,
25The Impact of ACFTA Implementation on International Trade of Indonesia
especially within the scope of the ASEAN-China region, (iii) To measure the impact of the
implementation of ACFTA towards, on generally, the member countries in terms of agreements
on international trade, and for Indonesia in particular, and (iv) To map the opportunities and
challenges presented by the characteristics of Indonesian exports. Many opportunities are
associated with the opening of Chinese markets for export commodities of Indonesia. Yet
challenges also emerge with China competing in the ASEAN market.
The impact of ACFTA trade on the Indonesian economy covers many aspects that can be
further development of analysis such as GDP, employment, investment, inflation and international
trade. To provide added value on the existing ACFTA topics, this study will focus on ACFTA
impact on Indonesia»s exports. Analysis of various indicators of performance and characteristics
of Indonesian exports are specifically addressed to ACFTA market coverage.
In terms of analysis tool, we will only review the results of GTAP model that are related to
the trading impact of Indonesia»s export, especially with trading partner countries of ACFTA
region. Based on the results of the GTAP model, further analysis will be carried out either by
using analytical tools for international trade indicators such as the RCA, IIT, IES, IEO.
The second part of this paper will describe the empirical ground and literature review on
trade and economic balance, the third part covers the methodology, the fourth section discusses
the results and interim analysis, while conclusions and implications will wrap the paper.
II. EMPIRICAL GROUND AND LITERATURE REVIEW
II.1. The Basic Model of International Trade
The economy of a country is an aggregation of the behavior of each individual. The
balance of goods in one country can be explained based on the interaction of profit maximization
behavior of producers and utility maximization of consumers. In a closed economy (autarky), in
equilibrium (point A), the composition of goods and prices of goods is the result of the interaction
mechanism of aggregate demand and aggregate supply in the country (Figure III.1).
Aggregate supply is strongly influenced by the available factors of production (endowment)
and the level of productivity, represented by the production and technology function. In the
other hand the aggregate demand curve is strongly influenced by the level of consumer utility
(U) and available consumption baskets. The level of production, consumption and the level of
consumer utility depend on the endowment and type of products available in the economy.
Manufacturers only have the option to produce a collection of specific types of product and try
to maximize profits based on the available endowment and production function. On the other
26 Bulletin of Monetary, Economics and Banking, July 2010
hand, consumers can only maximize utility by consuming a combination of product types
manufactured domestically and indirectly, the level of utility will be very limited.
Endowment differences between countries, as well as different levels of production and
technology and the types of products cause large variations in the type of product produced
between countries. And differences in tastes and individual utility level among countries will
imply on a high demand of variation of consumption basket desired by consumers within the
region. In a broader scope and in line with the era of globalization, the economy is no longer
limited to the scope of a country but it has evolved and crossed the border. The corporates»
profit maximization and consumers» utility maximization are no longer limited in national scope
but as well as inter-nations scope.
In the open economy equilibrium model, there are opportunities to maximize the profits
by expanding into foreign markets and by producing goods exceeding the domestic demand.
On the other hand, consumers also have the opportunity to maximize utility by consuming a
certain product types exceeding the domestic supply or by consuming a more diverse product
types, not just limited to the types of products within the country. Both of the above mentioned
will eventually drive the exchange of goods between countries.
The results from the interaction of individuals in a certain country with individuals in
other country will lead to the exchange of goods, services, and factors, which is commonly
known as international trade, that caused a shift in the balance of the beginning (point A)
toward the balance on the basis of international trade (point C) (Figure III.2). Excess demand for
product x (xc-xp) can be met by imports from other countries so that consumers can choose a
basket of consumption that generate a higher level of utility, which is point C. The production
Figure III.1: The Equilibrium Modelof Closed Economy (Autarky)
Source : Markusen et al, International Trade and Evidence
A
Y
ap
aU
X
Y
X
27The Impact of ACFTA Implementation on International Trade of Indonesia
of product y that exceeds domestic demand is a surplus and will be exported in international
market. In other words, international trade is the exchange of goods, services and factors that
occur between countries or one that has passed the national/international boundaries.
Theoretically at least there are 5 advantages from trade. The first advantage is the benefits
from the exchange. By trading, a country can produce a product exceeds its domestic demand
and export the surplus (excess supply) on international markets that will eventually expand the
market and increase profitability. On the other hand, excess demand for a product can be met
by imports from other countries so that consumers can choose a basket of consumption that
generates a higher level of utility.
The second advantage is the benefits of the specialization. By trading, a country can be
more focused on one type of product which they can produce with a relatively high level of
efficiency. While the need for a product that can not be efficiently produced domestically can
be met by importing these products from other countries.
The third advantage, that can be gained from trade, is associated with the diversity of
individual preferences. The existence of trade provides more choices of products to consumers
which will assist in the fulfillment and even can raise the level of consumer utility.
The fourth advantage is associated with diversity of endowment owned by a country. By
trading, a country that prior trading did not have any or very limited access to any type of
product, will have the demand fulfilled. The fifth advantage that might be achieved is the
transfer of modern technology. With international trade, a country will have the opportunity to
learn a more efficient and modern production techniques.
Figure III.2:The Equilibrium Model of Open Economy
Source : Markusen et al, International Trade and Evidence
Q
X
Y
C
Y
*p
X
pY
cY
pX cX
28 Bulletin of Monetary, Economics and Banking, July 2010
The literatures state that a country will tend to export a product that is abundant
domestically or in other words will tend to export a product that excess supply. On the other
hand, the Ricardian model predicts that a country will focus the production on the type of
product that has the highest comparative advantage.
Heckscher-Ohlin theorem states that a country will tend to export commodities that intensively
use the abundant factor of production. For example, a country with abundant labor but with a
limited level of capital will tend to export products that are labor intensive and will tend to import
products that are capital intensive. Differences in the production function of a country will also
contribute to determine the direction of the country»s trade. A country that can produce relatively
more efficiently in a type of product will tend to become exporter of this products.
In fact, free trade does not literally take place freely. Barriers to trading can take the form
of tariff and non-tariff. Tariff setting has influence over the balance of output and prices. Such
constraints may lead to higher prices resulting in reduced demand for goods from abroad,
according to the demand-supply mechanism.
As an illustration, the increase in import tariffs may cause the price of imported goods
become relatively more expensive and reduce demand for the goods. This provides an incentive
for domestic production of goods. On the other hand, export subsidies cause the price of
domestically produced goods to become relatively cheaper and will increase the demand from
overseas markets.
II.2. The Theories of International Trade Coorporation
With the liberalization of trade in both international and regional scope, trade barriers
can be reduced and even be eliminated. Regional economic integration is a process where
several economies in the region agreed to remove barriers and ease the traffic flow of goods,
services, capital and labor. Reduction or even elimination of tariff and non tariff barriers will
accelerate regional economic integration as the traffic of goods, services, capital and labor
getting smoother.
Regional free trade or arrangement is expected to generate efficiencies and improve
welfare. It cannot be denied that trade arrangement would also increase competition among
the members. But if it is addressed wisely, there are benefits that can be gained among others,
which are the increasing specialization and the increased trade. With the comparative advantage
of each country, each country can focus on the production of goods that have a comparative
advantage that will trigger reallocation of production factors. In the end it will create a balance
of lower prices and greater output that will provide greater prosperity to the countries involved.
29The Impact of ACFTA Implementation on International Trade of Indonesia
Many studies conclude that free trade has a positive impact for the countries involved. In
addition to improving welfare (Kindleberger and Lindert, 1978), free trade will also increase the
quantity and efficiency of world trade (Hadi, 2003; Stephenson, 1994). Urata and Kiyota (2003)
found that the FTA in East Asia provide a positive influence on the economy. Exports with high
competitiveness will increase. The study of Saktyanu et al. (2007) showed that a decrease of
export subsidies in developed countries have an impact on increasing agricultural production
of Indonesia. In contrast to the results of most studies that generally state the positive impacts,
Haryadi et al. (2008) show that trade liberalization, by removing all trade barriers, causes a
reducing impact at the GDP of Indonesia and Australia-New Zealand.
One indicator to measure the impact of international trade arrangement is to look at the
occurrence of trade diversion and trade creation (Vinerian, 1950; Krueger, 1990). The positive
effects of trade creation is the occurrence of trade due to the shift of consumption of domestic
products which are high-cost to imported products from abroad which are low-cost (Vinerian,
1950); in other words the trade is increased among intra-country trade partners. However,
along with the difference in tariffs applied to partners and non-partners, it will change the
direction of trading trend, and impose negative effects of trade diversion, which refers to the
replacement of imported products that are low-cost from non-member countries with imported
products that are high-cost from partner countries (Vinerian, 1950). In other words there is a
decline of trade with the non-partner countries. Trade diversion would reduce the welfare
effects due to changes in supply orientation to a source that is relatively more expensive.
Benefits of free trade or regional cooperation are very much determined by one of the
more dominant effect. The overall effect can be positive, negative or neutral, it depends on the
size of the magnitude of trade creation and trade diversion. Free trade or the PTA would be
very advantageous if the impact on trade creation is greater than the impact on trade diversion.
Studies conducted by Lee and Shin (2006) confirmed that RTA will increase the trade between
its members. However, there was no significant decrease in trade between the RTA of members
and non-members countries. Even in some of the RTAs, trade among member and non-members
countries have increased. Despite the trade creation and trade diversion, RTA gives an overall
positive impact on trade.
II.3. Agreements on ASEAN China Free Trade Area (ACFTA)
Trade between ASEAN countries and China continues to show improvement from year
to year. For ASEAN countries, China is a major trading partners as an export destination. The
average share of exports to China by ASEAN countries from 2001-2008 varies but generally
30 Bulletin of Monetary, Economics and Banking, July 2010
quite high. Vietnam as a country that puts China as a major trading partner with the highest
share of 9%, while the Indonesian share of exports to China is recorded at 7% (Figure III.3). For
China, ASEAN countries became an important trading partner especially for the supply of raw
materials. The share of China»s imports from Singapore recorded 35% of total imports from
ASEAN or the highest market share among other Asean countries (Figure III.4). The share of
imports of goods from Indonesia is amounted to 13% of total imports from ASEAN. Trade
between ASEAN and China have a tendency to continue to rise which show the relative
importance of ASEAN-China trade for both sides. Thus, the potential gains from removing
trade barriers between ASEAN-China region will be relatively large.
The awareness on how important the role of each party, will raise the consciousness to
pioneer an agreement of economic cooperation. On November 4, 2002, an agreement of
cooperation framework emerged which is often called the ≈Framework Agreement on
Comprehensive Economic Cooperation∆. Within the framework, it was agreed that the free
trade formation for goods would take place in 2004, the service sector in 2007, and investment
in 2009. In terms of readiness for ASEAN, the free trade also applies gradually. Free trade will
be commenced in 2010 between China and ASEAN-6 which includes Indonesia, Singapore,
Thailand, Malaysia, Philippines, and Brunei. While in 2015, it will apply to China with ASEAN-
4: Cambodia, Vietnam, Laos, and Myanmar. Several issues related to the development of ACFTA,
especially in Indonesia, are shown in Diagram III.1.
From literature studies, among others by Park et al (2008), that analyzed the advantages
and prospects of ACFTA and revealed that ACFTA, which consists of 11 economies with a quite
large total population and GDP; it is possible for ACFTA to become an effective regional economic
cooperation. Relatively large intra-region tariff level is also the potential to increase trade creation.
Although China and ASEAN have sought to liberalize commerce, in fact, the level of tariffs and
barriers between them was still quite high, allowing the trade creation to take place. China
imposes tariffs on average by 9.4% for goods from ASEAN. In contrast, ASEAN nations imposed
tariffs on goods from China in average of 2.3%.
But it can not be denied that along the opportunities, there are the challenges with the
enactment of ACFTA. The biggest challenge is the raising product competition. Fear of inability
to compete in domestic market against the rushing flow of imported products from China and
the fear of inability to penetrate China»s wide open-potential market, is a challenge which, if
managed wisely, can turn into a potential opportunity. Yue (2004) takes the increase in intra-
industry trade in machinery and electrical equipment as an example of the impact of increased
trade ACFTA that considered quite successful. There are numerous studies that have considered
the impact of ACFTA trade, as shown in Table III.1.
31The Impact of ACFTA Implementation on International Trade of Indonesia
Figure III.3:Market Share of Exports to China
Figure III.4: China»s Import fromASEAN Countries
Diagram III.1:Road Map of ACFTA Agreement
9%
8%
8%
8%
7%
7%
6%
4%
4%
1%
0 2 4 6 8 10
%
Vietnam
Singapore
Philippines
Thailand
Malaysia
Indonesia
Myanmar
Brunei
Lao
Cambodia China as Aim of Main Export
Singapore
Malaysia
Thailand
Indonesia
Philippines
Vietnam
Brunei
Myanmar
Lao
Cambodia
35%
21%
18%
13%
7%
6%
1%
1%
0%
0%
0 10 20 30 40
%
Share of China»s Importfrom ASEAN Countries
Head of theASEANcountries andChina signed aframeworkagreement onComprehensiveEconomicCooperationPhnom Penh
4 NovemberEconomicMinisters ofASEAN andChina signedthe protocolchanges to theframeworkagreement inBali
6 OctoberIndonesia ratifiedthe ACFTAframeworkagreementthroughPresidentialDecreeNo.48/2004
15 June
Rising:- Ministry of FinanceDecree No.355/KMK/01/2004on StipulationCustoms Tariff onImports of goods inthe Framework ofthe Early HarvestPackage (EHP)ACFTA- Minister of FinanceDecree No.355/KMK/01/2004on Stipulation oftariffs of import dutyon import of goodswithin theframework ofBilateral EHPIndonesia-China FTA
21 July
Rising:PermenkeuNo.56/PMK/010/2006 on CustomsTariffDetermination inthe framework ofASEAN-ChinaNormal Track
7 JulyRisingPermenkeuNo.21/PMK/010/2006 onStipulation oftariffs within theframework ofnormal track in2006 ACFTA
15 MarchRisingPermenkeu No.07/KMK.04/2007 of theMinister ofFinance DecreeNo. Extension.355/2004Permenkeu No.08/PMK.04/2007 of theMinister ofFinance DecreeNo. Extension.356/KMK.01/2004
6 FebRising:PermenkeuNo.235/PMK.011/2008 aboutthedetermination of import dutyin order ACFTA
23 DecMinistry of Industryasked for a delayACFTA from 2010 to2012 due to crisis
29 Jan
10 ACFTA industryassociation asked fora delay to the Houseof Representatives.
2 Dec
In the form of jointteams unt. ACFTAwhich led Menko,involving Apindo, Kadin,and the Ministry ofTrade.
25 Dec
2002 2003 2004 2005 2006 2007 2008 2009
32 Bulletin of Monetary, Economics and Banking, July 2010
Table III.1Previous Studies on ACFTA
- Overall, ACFTA will increase net trade, output and regional welfare
- The impact on each country varies
- Big advantage goes to countries like Singapore, Malaysia, Indonesia andThailand than other member countries that are relatively poorer such asCambodia, Laos and Myanmar.
- Optimistic about the prospects for implementation of ACFTA
- ASEAN is a potential huge market for Chinese exports as well asalternative import sources
- China is a potential market for ASEAN exports products mainly forintermediate and capital goods
- ACFTA will provide significant economic benefits to the economy ofASEAN and China
- The pressure of competition from China will bring negative impact in theshort term but will have a positive impact by increasing productivity andefficiency in the long term
- This study compares the impact of various trade cooperation, followed byChina. The findings for ACFTA showed that China will benefit from itsparticipation in the ACFTA
- Improvement of ASEAN exports to China
- Competition with imported products from China
- There was a trade creation of ASEAN-China which tends to be higherthan the growth of intra-trade among ASEAN countries
- Singapore and Malaysia to obtain the benefits of inter-and intra-industryspecialization while Thailand gain the advantage of intra-industryspecialization. However, Indonesia and the Philippines do not gain much
- Improvement of ASEAN exports to China and vice versa
- Indonesia, Malaysia, Singapore and Thailand will experience the biggestbenefit in terms of exports
- The main export commodities of ASEAN to China are the intermediategoods so that China»s increased exports would encourage increasedexports of ASEAN
- ASEAN»s GDP rose by 0.9% while China»s GDP increased by 0.3%
- Economic benefits: improved specialization and trade. However, tradediversion will also occur with the significant non-members.
- Impact of trade: an increase in ASEAN exports to China and vice versa.The biggest increase in exports will be experienced by Indonesia,Malaysia, Singapore and Thailand. By sector, the biggest advantage willbe enjoyed by textile and clothing products, machinery and electricalequipment, and other industries. There is a significant improvement forintra-industry trade.
- Impact on GDP: ASEAN»s GDP will increase by 0.9% and by 0.3% forChina»s GDP. Vietnam will experience the largest increase. While Indonesiawill experience a decline in GDP.
- Non-economic benefits: an increase in political and social relationship.
Researcher Finding(s)Analysis Method
Park et al 2008 Trading Indicator and GTAP
Park 2007 Qualitative
Jiang & 2008 GTAPMcKibbin
Tambunan 2005 Trading indicator
Okamoto 2005 Trading indicator
Universal GTAPAcces toCompititivenessand Trade(UACT)
Yue 2004 GTAP
Year
33The Impact of ACFTA Implementation on International Trade of Indonesia
III. METHODOLOGY
III.1. Computable General Equilibrium Model
There are several approaches in the study of world trade, which two of the classifications
are the general equilibrium and partial models. General equilibrium theory explains the linkages
of the entire market mechanism as a system that interacts simultaniously. If the market, in the
equilibrium condition, changes or if there is any partial interference on the market, then there
will be adjustments in the relevant market and other markets. One model that is often used in
various studies is the General Trade Analysis Project (GTAP), a Computable General Equlibrium
(CGE) model developed by Purdue University.
CGE model is often used for the industrial, trade and fiscal sector2 . In this model,
production factors market conditions and market of production output are in equilibrium. The
primary basis of the CGE model is an understanding on how the economy works and then the
usage of the data in accordance with the developed model.
In this GTAP model, the economy is assumed to be in general equilibrium state, where all
agents in the economy do not have the ability to influence prices or act as a price taker, so the
price, that is entirely formed, is the interaction between demand and supply. Implicitly this
assumes that every market is in the perfect competition (competitive) condition and this approach
is widely referred as the Walrasian General Equilibrium
The general equilibrium in the CGE model is reflected in nominal terms (quantity multiplied
by price) that represent the flow of funds, either accompanied by the flow of goods (transaction)
or not (transfer). The CGE model consists of equations representing the balance of the entire
market, from the input markets to output markets for the whole sectors that are analyzed. The
CGE model also explicitly models the rational behavior of economic agents like producers who
tend to maximize their profits, households who maximize the satisfaction (utility) and other
economic agents. Included in this CGE model is the specification of the specification that is
related with the flow of funds between agencies, and other equations that define the formation
of price and quantity. Overall, the CGE model is a set of mathematical equations that can be
solved simultaneously.
GTAP model is a multi-sectors and multi-regions CGE model. Standard GTAP model consists
of households, government, and companies in each economy3 (Diagram III.2). Social welfare
function is assumed to consist of private expenditure, national savings, and government spending.
2 Working Paper 2009, Semar 2009: Suatu Model Financial Computable General Equilibrium, BRE DKM.3 TSQ Discussion Paper, How Will the Regional FTAs Shape the Indonesian Economy? Evaluation by the Computable General Equilibrium
Model, Masahiko Tsutsumi, August 2001.
34 Bulletin of Monetary, Economics and Banking, July 2010
Savings is considered as a proxy of the delayed consumption. Under the regional income
constraint, principal agents are to maximize their welfare.
Like the other CGE models. the GTAP standard model provides the specification of various
theories and the behaviour of agents, explicitly in the form of mathematical equation. Selection
of functional form refers to two main things, (i) the suitability of the theory, and (ii) empirical
facts, and (iii) the need for research. One form of the function (henceforth we refer as nesting),
which is often used, is a Cob-Douglas function where the parameter that indicates the proportion
of the forming components assumed to be fixed. If the relative price of a commodity changes,
the user √ let say for consumption - will also experience changes to maintain the nominal
proportion in accordance with the amount of the which was previously determined (relative
share).
Diagram III.2:Agen Blocks in GTAP Model
Consumption expenditure consists of a variety of tradable commodities in the model.
The households determine their demands for each commodity based on three factors: relative
price, minimum consumption, and income level. This demand system called the Constant
Difference elasticity (CDE). On the other hand, government spending on individual commodities
is still formulized under the Cob-Douglas function.
Commodities are produced by both domestic and foreign producers. Both party then
later combined in a bundle of commodities which is a composite of domestic and import
Source: A Graphical Exposition of GTAP Model, Brockmeier, 1996
World / ROW
PrivateHousehold
Producent
Government
RegionalHousehold
Global Saving
VIPAVIGA
TAXES
SAVE
TAXES
PRIVEXP GOVEXP
XTAX TAXES
VDPA
NETINV
VOAMTAX
VDGA
VIFAVDFA
VXMD
35The Impact of ACFTA Implementation on International Trade of Indonesia
products. In the GTAP model, the composition of both products follows the Constant Elasticity
Substitute (CES) function. This import-domestic demand system is proposed by Armington
(1969) that allows the modeler to change elasticity of substitution between domestic and
import products depend on the experiments.
The companies are assumed to maximize their revenues. In the process of production,
labor, capital, land form the composite of primary input to follow the form of the CES nesting,
thus allowing the substitution of the three primary inputs. This is consistent with the theory
and empirical facts in which a sector can switch from labor-intensive to capital-intensive or
otherwise.
The composite of primary input is then combined with the intermediate input within the
nesting that takes form as a Leontief function. These specifications are clearly required to
maintain the complementarity between primary inputs with the intermediate inputs as it is
difficult to imagine if labor can be replaced, let say, by cooking oil in the production process in
hotels and restaurants sector, for example. Land is immobile while the labor and capital are
mobile within the industry. In this standard model of GTAP, the international mobility of
endowments is not allowed.
Saving in each country is carried out (collected) by a fiction institution, that is, global
banks and is allocated as a source of finance for investment. How to connect a savings to
investment depends on the theories and the empirical facts that can be altered based on the
purpose of the research.
In general, any question proposed in a research must be translated into a simulation
model. This simulation setting is critical and one of the important components is the closure,
which is the division of variables to be placed as an endogenous or exogenous variables. This
closure greatly affect the interest and the simulation results, one of them is to restrict whether
the dimension of this simulation is short-term (one of which is marked by the fixed sectored
capital) or long term.
III.2. Analysis Flow
This research aims to measure the impact of international trade ACFTA for Indonesia and
how they impact on Indonesia»s export commodities. Related to this, described in this section is
the analysis flow performed as shown in Diagram III.3.
36 Bulletin of Monetary, Economics and Banking, July 2010
Diagram III.3:Analysis Flowchart
The first stage is the process of aggregation and disaggregation of the countries and
commodities categories. Next is running the CGE model, using the GTAP model which is a CGE
model to perform simulation specifically related to international trade. After applying the shock,
in this case on the tariffs, then the model starts to run. The data used is the trade data world-
wide in 2004 is the standard data included within the GTAP model version 7 in 2008.
The simulation results based on CGE models are then analyzed to see the opportunities
and challenges which are encountered in real terms of economy as already simulated. The
simulation model will also be confronted with the analysis of international trade indicators on
export and import data from UNCOMTRADE period 2001-2008.
For period 2001-2008, the analysis is divided into two periods: Period I, in 2001-2004
which can be viewed as the period before implementation of the ACFTA. The next one is Period
II in 2005-2008 which is considered as the implementation period of ACFTA. The data used is
a 3-digit SITC data (ver.3) which is aggregated into 2 digits. Meanwhile, regrouping is done to
SimulationResult
Chance
Challenge
The process of aggregation anddisaggregation of State & Sector Run GTAP (CGE Model)
Shock Rate0%
Execution
RCAIndicator
IITIndicator
OverlapIndicator
SimilarityIndicator
CompetitivenessMap of Indonesia»s
Commodities
Chance
Challenge
China Market
ASEAN Market
Indonesiavs
ASEAN Countries
Indonesiavs
China
Spearman RCIndicator
37The Impact of ACFTA Implementation on International Trade of Indonesia
equilize the commodity code between GTAP version with the version of SITC to achieve
compability of these two tools. Conversion from SITC commodity groups to the GTAP is using
primary reference presented in the GTAP website.
III.3. Setting of GTAP Model Simulation
Generally, closures that are used in the simulation follow the standard GTAP closure,
which are:4
1. Price and quantity variable of tradable commodities across countries that are not included
in the category of endowment commodities, are treated as endogenous variable.
2. Revenue from each region is endogenous.
3. All policy variables, productivity (technical changes) and populations are treated as exogenous
In simulating the impact of ACFTA implementation on international trade of ASEAN in
general and Indonesia in particular, particularly related to exports, the shocks applied are:
1. The tariffs applicable between the ASEAN countries with China is 0% (not applicable).
2. ACFTA member countries still impose tariffs on the non ACFTA member (rest of the world,
ROW).
3. Vice versa, ROW charges against members of ACFTA
III.4. Correlation Test on International Trading Indicator
Based on the previous GTAP model simulation results, to view the competitiveness map
of Indonesia and the challenges and opportunities encountered as the result of the establishment
of a forum for international trade, ACFTA, for international trade in Indonesia, the analysis is
resumed by using several trading indicators: (i) Revealed Comparative Advantage (RCA), ( ii)
Intra-Industry Trade (IIT), (iii) Index of Export Overlap (IEO), and (iv) Index of Export similarities
(IES).
Indicators of international trade are used to provide clarification and additional information
on the findings by GTAP. The trade indicators also complement the results of research because
they can provide information on the performance of Indonesia»s export commodities in greater
detail.
On the RCA indicators, we conducted Spearman»s rank correlation coefficient (SRC) which
is a statistical measure of non-parametric and can be calculated by the following formula:
4 The setting of this simulation is available by the author.
38 Bulletin of Monetary, Economics and Banking, July 2010
This test is needed to see if there are similarities on competitiveness rankings of the two
countries in pairs that were observed. Signs of the SRC indicate the direction of the relationship
between independent variable X and dependent variable Y. The value of SRC is between 0 and
1 that when X and Y perfectly monotonically related, then the SRC will be 1.
A. Revealed Comparative Advantage (RCA)
To see the competitiveness of export products, the indicator used is the Revealed
Comparative Advantage (RCA) indicator where if RCA> 1, it indicates the existence of
comparative advantage.
RCA = (Xij / Xj) / (Xi
w / X
w)
where:
Xij = exports of commodity i of country j
Xj = total exports of country j
Xiw = world exports of commodity i
Xw = total world exports
B. Intra Industry Trade (IIT)
To see the flow of international trade we use the indicator of Intra-Industry Trade, or also
often called the Grubel-Lloyd index (IIT). Based on the formula, the indicator is in a value
between 0 and 1. IIT that is approaching 0 reflects trade flows that are inter-industry, while if IIT
is approaching 1, it indicates that trade flows are intra-industry. In general, this indicator explains
that, a commodity of a country tends to have be related in the chain of international trade if
value is close to 1. This can be illustrated with export and import trade of a country for
manufacturing industry in the same group of goods (usually refers to groups of goods according
to SITC). A country can export electronic components and at the same time import of electronic
articles. On the other hand, for the trade of certain commodities such as natural resource-
based commodities such as oil and gas, a country tends to act as an exporter and do limited or
no import at all. If this happens then, the value of oil and gas commodity IIT is close to 0, or that
the trade is inter-industry.
(III.1)Σi i i
i i i i
ρ( (( (
) )) )
x x y y
Σi x x y y 22=
Σ
39The Impact of ACFTA Implementation on International Trade of Indonesia
To measure the IIT level, then the Grubel and Llyod is used as follow:
(III.2)
Where:
X(i,j,t) is the export value of commodity i of country j in year t
M(i,j,t) is the import value of commodity i of country j in year t
The calculation here is using 3 digit-SITC data classification of commodity i which is then
aggregated into 2 digits. In the GLI calculation there is a tendency that the more detailed data
of commodities, the smaller the value of GLI will become. Referring to previous studies, this
research also uses 2 digits considering that it is sufficient to identify the IIT process in ACFTA
countries
C. Index of Export Overlap (IEO)
To measure the level of each ASEAN country competition with China in trade ACFTA and
also the level of competition among ASEAN countries in utilizing the export opportunity to
China, the index of export overlap (IEO) is used. The equation of overlapping index is expressed
by this equation:
GLI ( j,t ) =Σi X ( i, j, t )( + M ( i, j, t ) − X ( i, j, t ) M ( i, j, t )−
Σi X ( i, j, t )( M ( i, j, t )− )
IEO ( j1, j
2, t ) = 100 x Σ min (X (i, j
1, t), X (i, j
2, t) /
t tΣ X ( i, j
1, t )
IEO size is used to measure the level of competition which is indicated by the export share
that overlap between total export of the two economies. The greater the overlap area (area b)
indicates a greater competition between the two countries. The index ranged from 100 which
means the full overlap and 0 which means no overlap.
40 Bulletin of Monetary, Economics and Banking, July 2010
Diagram III.4:Competition Between Economy A and B with Overlapped Export Size
D. Index of Export Similarity (IES)
Index of Export Similarity is used to measure the extent of similarity of the export products
composition from two economies. The similarity index equation is expressed as the following:
where:
s(i,j,t) is the share of the export commodity i toward the total economy export j in year t
IES index value ranges from 0 to 100 where 100 indicates that the export composition of
the two economies are identical, whereas 0 if the two are very different. As IES ignores the size
effect of its exports, IES analysis is always juxtaposed with the IEO indicator.
III.5. Data
As stated before, The data used in the analysis of this research are derived from GTAP
version 7.0 data with benchmark data in 2004. The coverage of countries in the data base of
GTAP reaches 113 countries with 57 details of the commodities sector. Meanwhile, for the
analysis of the indicators of international trade we use data from UNCOMTRADE which mainly
include import export data to the countries within the scope of observation, which is ACFTA
members. The processed data is in period 2001-2008
Source : Regional Economic Outlook: Asia and Pasific, Oct 2007
a
b
c
Economy A
Economy BEXpo
rt V
alue
Comodity (i)
IEO for economy A = b/(a+b)IEO for economy B = b/(c+b)
Lower valueadded
Higher valueadded
IES ( j1, j
2, t ) = 100 x Σ s (i, j
1, t)s (i, j
2, t) /
i iΣ s ( i, j
1, t )2
iΣ s ( i, j
2, t )2
41The Impact of ACFTA Implementation on International Trade of Indonesia
IV. RESULT AND ANALYSIS
Results of the simulation generated from the GTAP model includes a variety of indicators
that may be developed further. But even so, this research is more focused on the analysis of
export commodities of ACFTA member, especially Indonesia. In general there are two parts of
focus on the analysis. The first part is to see the effects of shocks giveb to the member countries
of ACFTA, while the second part leads to the quantitative impact of trade by commodity details.
The result of the first part of the analysis is to see how the balance between the impact of trade
direction and trade creation as a result of the implementation of the FTA.
IV.1. Calculation Result with GTAP Model
Various literature studies provide a general picture of the impact of trade between member
countries in a trading arrangement which tend to increase. But the trade with the non-member
countries will decline. Analysis of trade effects in a trade group is often known by the analysis
of trade creation and trade diversion. We can see the impact entirely, by comparing the magnitude
of each of the two trading effects. If the trade creation impact is larger, in general the trade
agreements benefit the members. And vice versa if the trade creation impact is lower, then the
trade agreements do not benefit the members overall
Though it was found that the impact of trade creation is more prominent than trade
divertion, we need a further observation in general to see, whether positive results are enjoyed
equally by member countries or not. Likewise, the details of export commodities which have
increased need to be further explored of whether a generic commodity, in general, is in control
by all or a certain group of member country
The increase in trade volume among ACFTA member is mainly caused by the introduction
of the Chinese market and the enactment of a lower tariff. Thus, the occurrence of trade
diversion which was originally addressed to the non-ACFTA trading partners shifts toward the
fellow members of the ACFTA. This process of change can be in analogy with the existence of
a nominal amount of funds held by economic agents (countries) that can be spent with more
goods as a result of declining prices. Importer preferences also change in the face of dynamics
of changes in import prices as a result of tariff reduction. If the reduction in import tariffs
causes the price to be cheaper than the price of goods originating from non-member countries
(assuming the quality of goods are the same), then a decline in trade with non-member country
or trade divertion will take place
42 Bulletin of Monetary, Economics and Banking, July 2010
GTAP simulation results to measure the impact of trade (trade effect) as a whole (net
effect) for ACFTA member countries are reflected in Figure III.5 and Figure III.6. Total net trade
creation in the region of ACFTA is 2.1%, sourced from the trade creation among member
countries ACFTA by 18.4% and the decline in trade diversion which is the reduction in trade
with non-member countries (rest of the world) by 1.8%5 .
Figure III.5 The Impact of ACFTA Policyon Trade in ASEAN
Figure III.6. The Impact of ACFTAon Net Trade Creation
From individual member states ACFTA, Vietnam and Thailand have the largest trade
creation, respectively 9.1% and 2.5%, while Singapore got the minimal results of 0.4% (Figure
III.6). The net value of trade creation is influenced by import tariffs during the simulation. The
average import tariff in Vietnam and Thailand are still relatively high, while in Singapore it has
recorded 0%. Based on preliminary data of GTAP, import tariffs for composite goods from
China in Vietnam and Thailand are respectively 18.0 and 11.3%. as for other countries
successively Indonesia (11.3%), Malaysia (7.5%), Philippines (5.3%), as well as other ASEAN
(7.8%). The amount of tariff goods are generally in line with tariffs imposed by China on goods
originating from those countries. Except for goods from Singapore where the China is still
applying the composite tariff of 4.2%
With the enactment of ACFTA trade agreements, the import export development among
ASEAN countries with China is changing. Import of goods from China to Vietnam and Thailand
is raising high by 147%, and 101%, while Singapore recorded a decline in imports by 1.2%
(Figure III.7). This is aligned with the previous explanation that the sensitivity of changes in
import tariffs is in line with the import conditions which was previously high and after the
5 The complete calculation result is shown at appendix 1.
Trade Creation
Trade Diversion
-4.0
-3.0
-2.0
-1.0
0.0
0 5 10 15 20 25 30 35 40
SIN
PHI
IND
THA
MAL
CHI
VIE
ASEAN
OTHERS ASEAN
ACFTA
Net Trade
Percentage (%)
0.0
2.0
4.0
6.0
8.0
10.0
Vietnam,9.1
Thailand,2.5
China,2.3
Indonesia,2.0
Malaysia,1.9 Philippines,
1.32
Singapore,0.4
OtherASEAN, 2.2
ASEAN,2.02
ACFTA,2.1
43The Impact of ACFTA Implementation on International Trade of Indonesia
shock of 0% tariff (post ACFTA). With the changing dynamics of exports and imports as a
result of tariff changes in the scope of ACFTA is reflected in (Figure III.8).
The bilateral pair of Vietnam and China, before the implementation of ACFTA, also apply
high tariff structure on a reciprocal basis. Post-implementation of ACFTA, the simulation results
show the a great change in total exports and imports respectively 6.4% and 11.5%.6
6 The value of export and import growth, in the results of the GTAP model, is recorded as a change from the base value which is usedin the GTAP model data base
Figure III.7. The Impact of Export andImport Change with China (%)
Figure III.8. The Impact on Total Exportand Import Change (%)
For Indonesia, the impact of net creation is by 2.0% which is caused from the trade
creation by10.3% and the trade diversion by 1.5% (Figure III.5 and III.6). The calculation of
trade creation and trade diversion above is based on the total international trade which is the
sum of total value of exports and imports of Indonesia with all its trading partner countries.
Meanwhile, the calculation of net value creation, with approach to the total exports value
minus total imports (net exports), is conducted to see the impact on the balance of payments.
From the simulation of the impact to the balance of payments Indonesia, there is an increase
in total imports by 2.3% or higher compared with the rising in exports by 1.8%. Thus, overall
the Indonesia»s trade surplus fell by 2.3% or USD247 million (Figure III.9 and see Appendix 1
for complete results of net creation with the calculation of total exportsimports and the net
exports)
Although the surplus of Indonesia»s trade balance within the ACFTA region recorded an
increase, the overall impact on the total trade balance still recorded a decrease of surplus.
This is due to the share of Indonesia»s trade with ROW is more dominant compared with the
Export to China, growth (%)
Import from China, growth (%)
-10
20
50
80
110
140
ASEANothers ASEAN
SIN
PILIND
THA
MAL
VIE
0 10 20 30 40 50
Export to World, growth (%)
0.0
2.0
4.0
6.0
Import from World, growth (%)
0 1 2 3
ASEANothers ASEAN
ACFTA
SIN
PILIND
THA
MAL CHI
VIE11.5
6.4
44 Bulletin of Monetary, Economics and Banking, July 2010
Figure III.11. The Impact of ACFTA Policyon Indonesia»s Export and Import Change
Figure III.12. The Impact of ACFTAon Commodity Sectoral (%)
ROW
ASEAN
Export Growth (%)
INDONESIA 'S TRADE
-10
0
10
20
30
40
50
-10 -5 0 5 10 15 20 25 30 35 40 45
Import Growth (%)
TOTAL
CHINA
ACFTA
%
-8
-4
0
4
8
12
China ACFTA ASEAN ROW World
-2.3
6.5
8.3
-3.5-2.3
-6.2
8.39.5
-0.6
0.5
57 Commodities Sector42 Commodities Sector
Figure III.9. The Impact of ACFTAon Indonesia»s Net Exports (%)
Figure III.10. The ShareExport of Indonesia √ GTAP Data (%)
ACFTA region. As an illustration, Indonesia»s exports (GTAP level data base) with ROW trading
partners reached 74%, or far larger than the export with fellow members of the ACFTA by
26% (Figure III.10)
From the simulation results we obtained the change in Indonesia»s import and export,
with trading partners among members of ACFTA, each grew by 11.7% and 9.1%. With the
increase in exports greater than imports, the impact on Indonesia»s trade surplus recorded an
increase of 6.5% or USD253 (Figure III.9). Meanwhile, Indonesia»s import and export transactions
with trading partners from the ROW recorded a negative growth each by -1.7% and -1.3%,
thus the balance of trade fell by 3.5% or USD499 million
USD Millions Growth %
-600
-400
-200
0
200
400
600
Mutation of Trade Balance (USD)
Mutation of Trade Balance (%)-10.0
-8.0
-6.0
-4.0
-2.0
0.0
2.0
4.0
6.0
8.0
10.0
-15
268 253
-499
-247
-2.3
8.36.5
-3.5-2.3
China ASEAN ACFTA WOR Total China ASEAN ACFTA WOR Total
ASEAN16%
CHINA10%ACFTA
26%ROW74%
45The Impact of ACFTA Implementation on International Trade of Indonesia
Based on figure III.9 above, it has been shown that the simulation results in the growth of
the trade balance fell by 2.3%. Simulation of the GTAP model of exports and imports are
derived from details of the 57 commodities consist of 42 export and import (tradable)
commodities, while the other 15 commodities are in the form of services or of non-tradable
commodities (Grouping Table of 42 tradable sectors and the conversion tables are available in
appendix 2 to 5). Separation of these groups of goods are required to facilitate the subsequent
analysis which use the import export data from UNCOMTRADE. As known, import export
statistics on international trade in various publications including UNCOMTRADE, are tradable
commodities. Meanwhile, in the analysis of the real sector in the context of GDP, the discussion
of commodities consists of tradable and non-tradable commodities. Therefore, the import and
export simulation results derived from GTAP can be further learnt for a more detailed analysis,
one of them by analyzing the tradable commodity
There is a difference the result of simulation when we compare the total results of 57
commodities and the 42 tradable commodities. The overall changes of impact in Indonesia»s
net exports toward the 42 commodities are presented in appendix 2. However, to facilitate
tabulation, the 42 tradable commodities can be further aggregated into 6 types of main tradable
commodities, as seen in table III.2 and III.3 (The conversion table of 6 types of primary tradable
commodities and 1 service commodity is shown in appendix 5). From Figure III.12 and table III.3
we can see that the simulation results of total net exports in 42 commodities (tradable) have
grown by 0.5%. The simulation results of other tradable commodities of Indonesia»s exports to
China increased high enough to 41.4% so that the overall exports to the ACFTA rose 11.9%
(Table III.2). Meanwhile, a negative impact of net exports (trade balance) arises in trading with
China and ROW (Table III.3).
Table III.2 The Post Impact of ACFTA Policyon the Growth of IndonesiaExport Commodities (in %)
Commodities Sector ASEAN ACFTA China ROW World
Agricultural Products -10.9 -5.3 33.9 -0.5 -2.0Food Products -4.7 4.7 16.5 -1.8 -0.1Extractive Industries -0.3 2.2 5.2 -0.6 -0.1Light Industry -21.3 17.6 60.4 -1.7 0.5Heavy Industry -3.2 18.2 48.7 -3.0 4.7Technology Intensive Industries -3.11 2.3 63.1 -1.8 3.9Total -4.4 11.9 41.4 -1.7 2.1
Table III.3 The Post Impact of ACFTA Policy onthe Growth of Indonesia
Net Export Commodities (in %) 7
Commodities Sector ASEAN ACFTA China ROW World
Agricultural Product -14.3 -49.2 -7.8 1.2 -3.8Food Product -37.8 4.9 9.3 -3.1 -1.9Extractive Industries 2.5 -0.5 -30.2 -1.1 -1.7Light Industry -32.2 -90.2 -256.2 0.3 -1.7Heavy Industry 27.7 79.3 70.7 -20.9 20.6Technology Intensive Industries 27.7 -9.2 -43.3 15.9 1.3Total 9.5 8.3 -6.2 -0.6 0.5
7 Negative growth indicates a contribution in declining the trade balance, while the positive balance of trade means a controbution inraising the balance
46 Bulletin of Monetary, Economics and Banking, July 2010
Table III.4The Growth of Reduction on Import Tariff
DutyTariff
Y E A R
0% 2,857 25.6% 2,864 25.6% 2,639 30.2% 2,639 30.2% 5,709 65.3% 7,306 83.6% 7,306 83.6% 7,778 89.0%5% 3,893 34.8% 3,888 34.8% 3,218 36.9% 3,219 36.8% 2,219 25.4% 622 7.1% 622 7.1% 150 1.7%8% 86 1.0% 85 1.0% 33 0.4% 33 0.4% 33 0.4% 33 0.4%8% 1,850 21.2% 1,866 21.4% 3 0.0% 3 0.0% 3 0.0% 3 0.0%
10% 1,702 15.2% 1,702 15.2% 131 1.5% 131 1.5% 95 1.1% 95 1.1% 95 1.1% 95 1.1%12% 90 1.0% 90 1.0% - 0.0% - 0.0% - 0.0% - 0.0%13% 18 0.2% 18 0.2% 48 0.5% 48 0.5% 48 0.5% 48 0.5% 48 0.5% 48 0.5%15% 1,537 13.8% 1,537 13.8% 315 3.6% 304 3.5% 278 3.2% 278 3.2% 278 3.2% 278 3.2%20% 269 2.4% 269 2.4% 126 1.4% 123 1.4% 123 1.4% 123 1.4% 123 1.4% 123 1.4%25% 318 2.8% 318 2.8% 20 0.2% 20 0.2% 19 0.2% 19 0.2% 19 0.2% 19 0.2%30% 39 0.3% 39 0.3% 39 0.4% 39 0.4% 39 0.4% 39 0.4% 39 0.4% 39 0.4%
>30% : 538 4.8% 538 4.8% 170 1.9% 173 2.0% 172 2.0% 172 2.0% 172 2.0% 172 2.0%TOTAL 11,171 100.0% 11,173 100.0% 8,732 100.0% 8,737 100.0% 8,738 100.0% 8,738 100.0% 8,738 100.0% 8,738 100.0%
2005 2006 2007 2008 2009 2010 2011 2012Total
Tariff PostPercentage Total
Tariff PostPercentage Total
Tariff PostPercentage Total
Tariff PostPercentage Total
Tariff PostPercentage Total
Tariff PostPercentage Total
Tariff PostPercentage Total
Tariff PostPercentage
AVERAGE OFAVERAGE OFAVERAGE OFAVERAGE OFAVERAGE OF 9.57%9.57%9.57%9.57%9.57% 9.49%9.49%9.49%9.49%9.49% 6.38%6.38%6.38%6.38%6.38% 6.38%6.38%6.38%6.38%6.38% 3.83%3.83%3.83%3.83%3.83% 2.92%2.92%2.92%2.92%2.92% 2.92%2.92%2.92%2.92%2.92% 2.65%2.65%2.65%2.65%2.65% DUTY TARIFF DUTY TARIFF DUTY TARIFF DUTY TARIFF DUTY TARIFF
IV.2. The Analysis Result on International Trade Indicator
Based on the output generated by the GTAP model, the development of analysis is aimed
at the direction of the opportunities and challenges of Indonesia»s export product development.
Development of the analysis is done by basing the GTAP model simulation results which are
combined with the analysis of trading indicators. Based on the findings in the model in the
previous section, we have produced details of commodities which hold the chance of positive
contribution to the balance of trade in some 42 commodities in the tradable goods groups.
From the increasing number of export commodities, we will map further by looking at the
competitiveness of the commodity in the ACFTA market.
At this stage of data processing, there are two main sources of the commodity details
based on the GTAP commodity and SITC 3-digit (ver.3). Therefore it is necessary to convert
some of the details of SITC commodities, as much as 261, into the details of commodities
which is in accordance with the number of GTAP commodities, which is only 42. The main
source of the conversion comes from the GTAP model discussion forums at Purdue University
website. 8
Meanwhile, to provide a better analysis, we divide the period of observation of the arranged
indicators. This periode separation, referred as period I and II, is also intended to see the impact
of international trade before and after the implementation of ACFTA policies. The first period
covers the incoming data of the year 2001-2004, while the period II covers the year 2005-
2008. The dividing line of this two period separation, is the time ACFTA policy was in
8 Complete conversion table is available and can be requested to the author or to the editor of BEMP.
47The Impact of ACFTA Implementation on International Trade of Indonesia
implementation by 20049 . Based on data from the Ministry of Trade of Indonesia, the
implementation of ACFTA with the application of import tariffs has been gradually running the
25.6% or as many as 2857 tariff alredy recorded 0% in 2005 (Table III.4). Growth of these 0%
tariffs continued to increase to 83.6% or as much as 7306 postal tariffs in 2010. The progress
to all 0% tariff for members of the ACFTA, is according to the phasing scheme which has been
arranged in staging scheme of early harvest program, normal track and sensitive/highly sensitive
list.
IV .2.1.The Analysis Approach on Competitiveness of RCA and IIT ProductLinkages
There are two main indicators used for the analysis in the following sections. The use of
RCA and IIT indicators together, among others, presents in the Yumiko»s (2005) work. The
similar competitiveness of the commodities from the measurement of produced by the RCA
indicator will be tested further using the Spearman rank correlation (SRC). This SRC test also
has been used in a study conducted by Shafaeddin (2002).
RCA in this section analysis calculation is using market trading partners» data in the
ACFTA region as Indonesia»s total exports. The scope of coverage is to portray the RCA
competitiveness of Indonesian commodities in the market ACFTA. Similarly for the approach in
measuring IIT indicator we use the import export data with trading partners in the region
coverage ACFTA. Using this combination of the two indicators, the first step is to identify the
distribution of Indonesia»s export commodities based on comparative advantage and IIT indicators.
Thus the data processed will be mapped based on certain restrictions. For RCA, the
restriction of commodities with high and low competitiveness is determined by the division of
RCA values below and above 1. Meanwhile, the central determinant for IIT indicator is 0.5.
Based on the quadrant map, as reflected in Figure III.13 - III.14, quadrant I is also called the
main quadrant where the commodities with RCA above 1 and has a high-linkages in the chain
of trade with partner countries of the ACFTA region based on the IIT indicators. In general,
commodities with high IIT and RCA have the potential to have a greater chance to survive and
make penetration in a competitive market. High IIT indicators show a level of confidence of
export competitiveness of the RCA with a more convincing chance. Quadrants II and IV are also
considered potential since they have either high RCA or IIT as an advantage. Meanwhile the
quadrant III is the development quadrant since it has low value of RCA and IIT.
9 Ratification of ACFTA agreement framework through Keppres No.48/2004
48 Bulletin of Monetary, Economics and Banking, July 2010
In the two observation periods which are periode I and II, from Figure III.13 √ III.16 we
can obtain a general picture that there is a tendency to decreasing of the competitiveness
quality of Indonesian export commodities in ACFTA region. Based on the pattern of distribution
of commodities in the two periodes, as depicted in Figure III.13 and III.14, we can see the
development of export share shifts per quadrant. The export value share in quadrant I declined
from 33% to 19% with the number of commodities remains the same which is 9 (with different
composition or type). Some of Indonesia»s prime commodities that remain in the main quadrant
are oil, motored vehicles, textiles, and beverages. Relatively ideal conditions occur if the
development indicate a larger increase in export share in the quadrat I. The complete results of
composition and scope of the commodity per quadrant as measured in the RCA and IIT matrix,
are presented in appendix 6. To simplify the matrix table in appendix 6 can be simplified as
shown in Figure III.13 and III.14 for the 42 types of tradable commodities.
Figure III.13.Quadrant of RCA and IIT in Period I
Figure III.14.Quadrant of RCA and IIT in Period II
Quadrant IV
Quadrant II
Quadrant III
IIT
RCA
Quadrant I
-0.5 0.5 1.5 2.5 3.5 4.5-
0.2
0.4
0.6
0.8
1.0
Quadrant IV
Quadrant II
Quadrant III
Quadrant I
-0.5 0.5 1.5 2.5 3.5 4.5-
0.2
0.4
0.6
0.8
1.0IIT
RCA
Meanwhile, a more pessimistic result is shown when oil and gas commodities are excluded
in the calculation of RCA and IIT indicators. By using the data in the second period, the share of
export commodities in the first quadrant decreased from 19% to 12%. This development has
become important to be observed given the diminishing role of oil and gas commodities, while
the development of the non-oil commodities is still challenged by various obstacles. The complete
results for the analysis of this section are presented in Appendix 6, including the commodities
in each quadrant
49The Impact of ACFTA Implementation on International Trade of Indonesia
Figure III.15. The Growth of Export Shareper Quadrant from Period I to II
Figure III.16. The Export Share Quadrant IIWith and Without Oil and Gas
IV.2.2. The Analysis Approach of Competition Intensity
To provide a more complete result, this study also illustrates the challenges and
opportunities of Indonesia»s export commodities in ACFTA market. The analysis is done by
using the index of export similarity (IES) and the index of export overlap (IEO) indicators. Technical
analysis is conducted by comparing the characteristics of each country»s exports in ASEAN
bilaterally with China. After the result of IEO and IES indicators is generated for each country,
the next stage is to compare the results between the two periods of observation: period I
(2001-2004) and period II (2005-2008). With the two observation period, the dynamics that
occur can be more interesting to be further reviewed
As China join the ASEAN market, there is a threat of a decline for Indonesian exports
among ASEAN member trading partners that have been established so far. From the
measurement of competition intensity of exports of each country in ASEAN with China, we
gain an overview of developments which tend to decrease the intensity of competition in two
observation periods (Figure III.17) 10 . The intensity of competition tends to increase when both
indicators are showing an increase. Of the two observation periods of both indicators, we
obtain that the development of Indonesian products have the tendency to diminish their intensity
of competition with the presence with China»s export products. The reduced intensity of
competition of Indonesian products in China are in line with the rising share of Indonesia»s
exports of natural resource-based commodities such as mining and other natural products such
33%
31%
19%
18%
Quadrant I,19%
Quadrant IV,41%
Quadrant III,III%
Quadrant II,37%
19%
41%
37%
Quadrant I,12%
Quadrant IV,41%
Quadrant III,4%
Quadrant II,43%
3%
10The first period is shown in blue and the seconf perios is shown in red.
50 Bulletin of Monetary, Economics and Banking, July 2010
as oil and gas, palm oil and rubber along with rising prices and global demand. On the other
hand, the composition of Chinese exports are likely to lead to industrial products (Figure III.18)11 .
Based on the observation of IEO indicator, countries with relatively small scale of economies
have a relatively high index value such as Brunei, Philippines, Chambodia, and Vietnam.
Meanwhile, from the IES, a relatively advanced countries like Singapore, Malaysia, and Thailand
have a relatively high index. The high index of IES of some relatively advanced countries in the
ASEAN countries with China is also aligned with the development of the Chinese exports
proportion that is relatively high in industrial products.
Figure III.17.The Growth of Competition Intensitywith China in 2 Observation Periods
Figure III.18. The Growth of ExportShare of Industrial Commodities
11The share of industrial exports is derived from the sum of the value of exports in SITC with code digit that begin with 5 to 9, whilefor the code digits from 0 to 4 are not the industry
12 The test is based on the 50 largest commodities, based on the share that ranges around 90 percent.
0
10
20
30
40
50
60
70
80
90
100
40 50 60 70 80 90 100
IES
IND
BRN
CAM
MAL
PILSIN
THA
VIE
IEO
%
0
20
40
60
80
100Period I (2001-2004)
Period II (2005-2008)
Indonesia Singapore Thailand Philippines Malaysia Vietnam Cambodia Brunei China
To provide support for the above analysis conclusion, where the intensity of export
commodities competition, particularly between Indonesia and China that are increasingly
declining, we conducted a test with additional analysis tools. Tests are conducted by performing
Spearman rank correlation test (SRC) on the RCA indicator. SRC test for RCA of Indonesia and
China concluded a negative relationship with a significant level of 1% to 50 commodity criteria
and RCA> 1 (Table III.5). By testing on the largest 50 commodity categories we obtain coefficient
of -0.3 with the significant level of 5%12 . Similarly to the tests on the commodities which have
high competitiveness or RCA> 1 it yielded coefficient of -0.54 with significant level of 1%. As
for the test on the overall commodity based on 2-digit SITC amount 69 commodities, it produced
negative but insignificant relationship. The negative Spearmans»s Rho coefficient can be
interpreted a different structure on the competitiveness of Indonesian export commodities to
51The Impact of ACFTA Implementation on International Trade of Indonesia
China. These results may also mean that Indonesia»s main export commodity is not the Chinese
leading export. Tests on the two observation periods show consistent results for Indonesia,
which yield negative and significant coefficient.
Table III.5The Spearman Rank Correlation Test on RCA
Period I (2001 - 2004)
All CommoditiesAll CommoditiesAll CommoditiesAll CommoditiesAll Commodities(69 Commodities)(69 Commodities)(69 Commodities)(69 Commodities)(69 Commodities)Spearman»s rho: -0.04 0.03 0.03 0.08 -0.31 0.34 0.08 0.34 -0.20 0.04 0.02 -0.02 -0.18 0.21 0.16 0.31degrees of freedom: 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67P-value: 0.71 0.82 0.79 0.52 0.01 0.00 0.53 0.00 0.10 0.75 0.90 0.86 0.13 0.09 0.18 0.01
50 Commodities50 Commodities50 Commodities50 Commodities50 CommoditiesSpearman»s rho: -0.30 -0.25 -0.14 0.00 -0.57 0.19 0.02 0.28 -0.47 -0.28 -0.28 -0.14 -0.53 -0.07 -0.19 0.16degrees of freedom: 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48P-value: 0.03 0.08 0.34 1.00 0.00 0.20 0.90 0.05 0.00 0.05 0.05 0.32 0.00 0.62 0.20 0.26
RCA >1RCA >1RCA >1RCA >1RCA >1Spearman»s rho: -0.54 -0.10 -0.07 -0.28 -0.59 -0.23 -0.7 10.00 -0.51 -0.61 -0.37 -0.69 -0.56 -0.36 -0.28degrees of freedom: 31 18 30 7 18 21 17 2 28 19 29 11 23 24 7P-value: 0.00 0.67 0.69 0.46 0.01 0.29 0.00 1.00 0.00 0.00 0.04 0.01 0.00 0.07 0.46
Period II (2005 - 2008)
C h i n a C h i n a
IND SING THAI PHI MAL VIET CAMB BRU IND SING THAI PHI MAL VIET CAMB BRU
Similar results to Indonesia are also found in other ASEAN countries. In general, the test
on 50 commodities, and on commodities with high RCA showed a negative and significant
relationship. This shows that the Chinese exports commodities to ASEAN is not a primary
commodity from other ASEAN countries.
With the intensity of competition indicators and SRC test for the RCA indicator, we obtained
that more evidence for the conclusion that the decrease in the intensity of competition between
China and Indonesia is accompanied with the structure of export commodities which does not
compete one with another, which is similar with the exports commodities of other ASEAN
members. These results illustrate the existence of a more complementary relationship so that
the Chinese export to ASEAN is relatively easy. From the quantitative results of GTAP model, it
is also shown the increase of Chinese exports to ASEAN that reached 50.5% (Appendix 1).
Analysis of China»s market opening opportunities can also be done with the IES and the
IEO indicators. Unlike the measurement of IEO and IES indicators in the previous section, in
which China became the center of attention, we can use Indonesia as the central point of
attention. Bilaterally between Indonesia and each ASEAN country, there is a pattern of diminishing
competition relationships, supported by the IEO and IES indicators that go down (Figure III.19).
This indicates the relatively reduced level of product competition among ASEAN countries to
China. The GTAP simulation results also indicated that the overall exports from ASEAN to China
52 Bulletin of Monetary, Economics and Banking, July 2010
increased by 31.1% with the lowest range of Philippine exports of 16.1% and the highest is
Thailand»s exports by 43.3% (Appendix 1). Unlike the case when the export commodity that is
used is the total exports of each country. Figure III.18 reflects the degree of homogeneity
between Indonesian export products with each of the ASEAN countries in the world market is
higher than exports to the market ACFTA13 . Among ASEAN countries, Vietnam export products
relative have the highest index of IES.
13 Blue field represents the index size for export to the world market, and the red field represents the export to the ACFTA market
Figure III.19. The Growth of Indonesia»sCompetition Intensity with ASEAN
to Chinese Market
Figure III.20. The Comparation of Growthof Competition Intensity in ACFTA and
World Market
IES
BRN
CAMMAL
PILSIN
THA
VIE
IEO0
10
20
30
40
50
60
70
80
90
100
0 20 40 60 80 1000
10
20
30
40
50
60
70
80
90
100
0 20 40 60 80 100
IES
MAL
PILSIN
THAVIE
IEO
V. CONCLUSIONS
Trade arrangement within the ACFTA framework provides opportunities to increase exports
of Indonesia. From the results of GTAP model, Indonesia overall has a net trade creation of 2%
that comes from the effects of trade creation of 10.3% from ACFTA members and trade diversion
of -1.5% with ROW trading partners. Although the cooperation agreement ACFTA imposes
negative impact on overall Indonesia»s trade balance by a decrease of 2.3%, the results of
further analysis of the international export commodities (tradable) show the positive impact of
0.5%.
In terms of export, Indonesia commodities are likely to increase by 2.1% mainly due to
the increase in exports to China. Opportunities for market expansion into China is supported
by the characteristics of the export commodities of Indonesia and other ASEAN countries which
have a relatively low degree of competition. Thus, export goods from Indonesia and ASEAN in
53The Impact of ACFTA Implementation on International Trade of Indonesia
general are much easier to expand. Result analysis of IEO and IES indicators in the two periods
of observation lead to the conclusion that, the degree of competition intensity, of Indonesian
export goods to the ACFTA region bilaterally with individual ASEAN countries, is declining. The
conclusion is also supported by the degree of homogeneity of export commodities to ACFTA
that is lower than the overall exports to world markets. With such a low homogeneity, the level
of competition with other ASEAN countries to the Chinese market is relatively reduced.
However, Indonesia»s exports face a new challenge with the entry of imported goods
China in ASEAN region. The trade with other countries in the region, which has been interwoven
so far, is potentially decreasing. From the results of GTAP model, we obtained the estimates of
ASEAN countries» exports to the ASEAN region that has decreased by 4.9%, including Indonesian
exports decline by 4.4%. On the other hand, China»s export to ASEAN increased by 50.5%.
The results of this paper shows that the export commodities of China and ASEAN countries
tend to indicate the decline of the level of commodity equation. This is in line with the growth
of goods exports from China that are moving towards exports of industrial goods. From the
Spearman Rank Correlation test results on RCA indicators, it generally shows a more
complementary relationship between China»s export goods with ASEAN countries.
The challenge of improving Indonesia»s exports in ACFTA era is increasing with the declining
of Indonesian exports competitiveness of. Based on historical data which is divided into two
periods, we found that the share of principal commodity groups decreased from initially 33%
to 19% of total Indonesian exports. The challenge is growing as one component in the formation
of export share comes from oil and gas sector. If we remove the oil and gas export commodities
in the calculation, the share of primary commodity exports which intially reached 19% will be
dropped to 12%.
To take advantage of the ACFTA agreement on export development, we need a strategy
to move the basket of commodities, especially non-oil exports from quadrants II and IV to the
quadrant I. Development of export commodities which have high competitiveness needs to
consider also the characteristics of commodities that have high relevance within the international
trade chain. The results of this research show that potential commodities with high IIT indicators
that need to have the competitiveness strengthened are the machinery and parts, chemical
industry, electronic equipment, and metal and iron industry. As for potential commodities with
high RCA but need a high added value, in general are natural resource-based commodities that
should be processed further in the form of product diversification and higher value products.
Meanwhile, related to the challenges faced by the rampage of China»s products, we
should utilize the imported goods from China with medium and high technology which comes
54 Bulletin of Monetary, Economics and Banking, July 2010
from countries outside the region. Thus, we can provide a broader option for producers to
invest in machinery and equipment with a range of goods from China with more competitive
price. Furthermore, we expected that the direction from ACFTA cooperation can improve welfare
in the region and particularly for Indonesia.
55The Impact of ACFTA Implementation on International Trade of Indonesia
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New York.
57The Impact of ACFTA Implementation on International Trade of Indonesia
Appendix 1RESULT FROM RUNNING MODEL GTAP (i)
Total Trade with the worldBefore 87,511.4 152,058.6 150,571.0 119,465.2 50,743.5 32,196.5 12,418.0 604,964.2 680,765.6 1,285,729.8After 89,068.8 154,265.3 151,110.7 119,834.8 51,305.8 34,243.0 12,601.5 612,429.9 694,627.9 1,307,057.8
Trade Between MembersBefore 22,913.2 50,074.3 51,485.6 33,341.4 13,183.3 6,680.2 3,136.4 180,814.4 50,581.0 231,395.4After 25,597.1 55,134.6 54,122.1 38,146.3 13,915.4 7,263.7 3,164.2 197,343.4 76,135.7 273,479.1
Trade with ChinaBefore 8,194.3 22,580.3 16,600.2 14,436.8 5,495.9 2,988.6 439.9 70,736.0 0.0 70,736.0After 11,521.6 28,812.4 21,022.3 20,682.0 6,415.2 3,767.2 491.3 92,712.0 0.0 92,712.0
Trade with ASEANBefore 14,718.9 27,494.0 34,885.4 18,904.6 7,687.4 3,691.6 2,696.5 110,078.4 50,581.0 160,659.4After 14,075.5 26,322.2 33.099.8 17,464.3 7,500.2 3,496.5 2,672.9 104,631.4 76,135.7 180,767.1
Trade with non-Members (ROW)Before 64,598.3 101,984.5 99,085.4 86,123.9 37,560.3 25,516.5 9,281.5 424,150.4 630,184.7 1,054,335.1After 63,471.8 99,130.6 96,988.6 81,688.8 37,390.4 26,979.3 9,437.2 415,086.7 618,492.3 1,033.579,0
export to the WorldValue 1,557.4 2,206.7 539.7 369.6 562.3 2,046.5 183.5 7,465.7 13,862.3 21,328.0% 1.8 1.5 0.4 0.3 1.1 6.4 1.5 1.2 2.0 1.7
export to ACFTAValue 2,683.9 5,060.3 2,636.5 4,804.9 732,1 583.5 27.8 16,529.0 25,554.7 42,083.7% 11.7 10.1 5.1 14.4 5.6 8.7 0.9 9.1 50.5 18.2
export to ChinaValue 3,327.3 6,232.1 4,422.1 6,245.2 919.3 778.6 51.4 21,976.0 0,0 21,976.0% 40.6 27.6 26.6 43.3 16.7 26.1 11.7 31.1 0.0 31.1
export to ASEANValue -643.4 -1,171.8 -1,785.6 -1,440.3 -187.2 -195.1 -23.6 -5,447.0 25,554.7 20,107.7% -4.4 -4.3 -5.1 -7.6 -2.4 -5.3 -0.9 -4.9 50.5 12.5
export to ROWValue -1,126.5 -2,853.9 -2,096.8 -4,435.1 -169.9 1,462.8 155.7 -9,063.7 -11,692.4 -20,756.1% -1.7 -2.8 -2.1 -5.1 -0.5 5.7 1.7 -2.1 -1.9 -2.0
Indonesia Malaysia Singapore Thailand Philippines Vietnam Other ASEAN China ACFTAASEAN
E X P O R T
58 Bulletin of Monetary, Economics and Banking, July 2010
Total Trade with the worldBefore 76,947.2 106,330.1 160,658.5 102,806.7 48,824.9 36,636.9 9,142.6 541,346.9 599,116.4 1,140,463.3After 78,751.1 109,023.8 161,353.0 108,042.8 49,580.5 40,841.0 9,438.2 557,030.4 614,267.2 1,171,297.6
Trade Between MembersBefore 26,780.3 37,141.4 47,641.5 25,166.2 14,151.3 13,068,8 5,771.6 169,721.1 74,668.3 244,389.4After 29,211.4 40,947.6 46,777.7 32,180.0 15,585.8 20,307,6 6,235.2 191,245.3 98,412.1 289,657.4
Trade with ChinaBefore 8,828.6 10,088.2 13,723.0 7,946.1 5,708.3 5,624,5 1,616.2 53,534.9 0.0 53,534.9After 12,170.8 15,346.2 13,562.8 15,956.9 7,567.9 13,890,7 2,378.8 80,874.1 0.0 80,874.1
Trade with ASEANBefore 17,951.7 27,053.2 33,918.5 17,220.1 8,443.0 7,444,3 4,155.4 116,186.2 74,668.3 190,854.5After 17,040.6 25,601.4 33,214.9 16,223.1 8,017.9 6,416,9 3,856.4 110,371.2 98,412.1 208,783.3
Trade with non-Members (ROW)Before 50,167.0 69,188.7 113,017.2 77,640.5 34,673.7 23,568.3 3,371.0 371,626.4 524,448.1 896,074.5After 49,539.7 68,076.2 114,575.2 75,862.9 33,994.6 20,533.5 3,202.8 365,784.9 515,855.0 881,639.9
Import from the WorldValue 1,803.9 2,693.7 694.5 5,236.1 755.6 4,204.1 295.6 15,683.5 15,150.8 30,834.3% 2.3 2.5 0.4 5.1 1.5 11.5 3.2 2.9 2.5 2.7
Import from ACFTAValue 2,431.1 3,806.2 -863.8 7,013.8 1,434.5 7,238.8 463.6 21,524.2 23,743.8 45,268.0% 9.1 10.2 -1.8 27.9 10.1 55.4 8.0 12.7 31.8 18.5
Import from CinaValue 3,342.2 5,258.0 -160.2 8,010.8 1,859.6 8,266.2 762.6 27,339.2 0,0 27,339.2% 37.9 52.1 -1.2 100.8 32.6 147.0 47.2 51.1 0.0 51.1
Import from ASEANValue -911.1 -1,451.8 -703.6 -997.0 -425.1 -1,027.4 -299.0 -5,815.0 23,743.8 17,928.8% -5.1 -5.4 -2.1 -5.8 -5.0 -13.8 -7.2 -5.0 31.8 9.4
Import from ROWValue -627.3 -1,112.5 1,558.0 -1,777.6 -679.1 -3,034.8 -168.2 -5,841.5 -8,593.1 -14,434.6% -1.3 -1.6 1.4 -2.3 -2.0 -12.9 -5.0 -1.6 -1.6 -1.6
Indonesia Malaysia Singapore Thailand Philippines Vietnam Other ASEAN China ACFTAASEAN
Appendix 1RESULT FROM RUNNING MODEL GTAP (ii)
I M P O R T
59The Impact of ACFTA Implementation on International Trade of Indonesia
Total Trade with the worldBefore 164,458.6 258,388,7 311,229,5 222,271,9 99,568,4 68,833,4 21,560,6 1,146,311,1 1,279,882,0 2,426,193,1After 167,819.9 263,289,1 312,463,7 227,877,6 100,886,3 75,084,0 22,039,7 1,169,460,3 1,308,895,1 2,478,355,4
Trade Between MembersBefore 49,693.5 87,215,7 99,127,1 58,507,6 27,334,6 19,749,0 8,908,0 350,535,5 125,249,3 475,784,8After 54,808.5 96,082,2 100,899,8 70,326,3 29,501,2 27,571,3 9,399,4 388,588,7 174,547,8 563,136,5
Trade with ChinaBefore 17,022.9 32,668,5 30,323,2 22,382,9 11,204,2 8,613,1 2,056,1 124,270,9 0,0 124,270,9After 23,692.4 44,158,6 34,585,1 36,638,9 13,983,1 17,657,9 2,870,1 173,586,1 0,0 173,586,1
Trade with ASEANBefore 32,670,6 54,547,2 68,803,9 36,124,7 16,130,4 11,135,9 6,851,9 226,264,6 125,249,3 351,513,9After 31,116,1 51,923,6 66,314,7 33,687,4 15,518,1 9,913,4 6,529,3 215,002,6 174,547,8 389,550,4
Trade with non-Members (ROW)Before 114,765,3 171,173,2 212,102,6 163,764,4 72,234,0 49,084,8 12,652,5 795,776,8 1,154,632,8 1,950,409,6After 113,011,5 167,206,8 211,563,8 157,551,7 71,385,0 47,512,8 12,640,0 780,871,6 1,134,347,3 1,915,218,9
Total Net Trade CreationValue 3,361,3 4,900,4 1,234,2 5,605,7 1,317,9 6,250,6 479,1 23,149,2 29,013,1 52,162,3% 2,0 1,9 0,4 2,5 1,3 9,1 2,2 2,0 2,3 2,1
Trade Creation among MemberValue 5,115,0 8,866,5 1,772,7 11,818,7 2,166,6 7,822,3 491,4 38,053,2 49,298,5 87,351,7% 10,3 10,2 1,8 20,2 7,9 39,6 5,5 10,9 39,4 18,4
Trade Creation with ChinaValue 6,669,5 11,490,1 4,261,9 14,256,0 2,778,9 9,044,8 814,0 49,315,2 0,0 49,315,2% 39,2 35,2 14,1 63,7 24,8 105,0 39,6 39,7 0,0 39,7
Trade Creation with ASEANValue -1,554,5 -2,623,6 -2,489,2 -2,437,3 -612,3 -1,222,5 -322,6 -11,262,0 49,298,5 38,036,5% -4,8 -4,8 -3,6 -6,7 -3,8 -11,0 -4,7 -5,0 39,4 10,8
Trade DiversionValue -1,753,8 -3,966,4 -538,8 -6,212,7 -849,0 -1,572,0 -12,5 -14,905,2 -20,285,5 -35,190,7% -1,5 -2,3 -0,3 -3,8 -1,2 -3,2 -0,1 -1,9 -1,8 -1,8
TOTAL TRADE Indonesia Malaysia Singapore Thailand Philippines Vietnam Other ASEAN China ACFTA(EXPORT + IMPORT) ASEAN
Appendix 1RESULT FROM RUNNING MODEL GTAP (iii)
60 Bulletin of Monetary, Economics and Banking, July 2010
Total TradeBefore 10.564.2 45.728.5 -10.087.5 16.658.5 1.918.6 -4.440.4 3.275.4 63.617.3 81.649.2 145.266.5After 10.317.7 45.241.5 -10.242.3 11.792.0 1.725.3 -6.598.0 3.163.3 55.399.5 80.360.7 135.760.2
Trade between MemberBefore -3.867.1 12.932.9 3.844.1 8.175.2 -968.0 -6.388.6 -2.635.2 11.093.3 -24.087.3 -12.994.0After -3.614.3 14.187.0 7.344.4 5.966.3 -1.670.4 -13.043.9 -3.071.0 6.098.1 -22.276.4 -16.178.3
Trade with ChinaBefore -634.3 12.492.1 2.877.2 6.490.7 -212.4 -2.635.9 -1.176.3 17.201.1 0.0 17.201.1After -649.2 13.466.2 7.459.5 4.725.1 -1.152.7 -10.123.5 -1.887.5 11.837.9 0.0 11.837.9
Trade with ASEANBefore -3.232.8 440.8 966.9 1.684.5 -755.6 -3.752.7 -1.458.9 -6.107.8 -24.087.3 -30.195.1After -2.965.1 720.8 -115.1 1.241.2 -517.7 -2.920.4 -1.183.5 -5.739.8 -22.276.4 -28.016.2
Trade with non-Members (ROW)Before 14.431.3 32.795.8 -13.931.8 8.483.4 2.886.6 1.948.2 5.910.5 52.524.0 105.736.6 158.260.6After 13.932.1 31.054.4 -17.586.6 5.825.9 3.395.8 6.445.8 6.234.4 49.301.8 102.637.3 151.939.1
Total Net Trade CreationValue -246.5 -487.0 -154.8 -4.866.5 -193.3 -2.157.6 -112.1 -8.217.8 -1.288.5 -9.506.3% -2.3 -1.1 -1.5 -29.2 -10.1 -48.6 -3.4 -12.9 -1.6 -6.5
Trade Creation among MemberValue 252.8 1.254.1 3.500.3 -2.208.9 -702.4 -6.655.3 -435.8 -4.995.2 1.810.9 -3.184.3% 6.5 9.7 91.1 -27.0 -72.6 -104.2 -16.5 -45.0 7.5 -24.5
Trade creation with ChinaValue -14.9 974.1 4.582.3 -1.765.6 -940.3 -7.487.6 -711.2 -5.363.2 0.0 -5.363.2% -2.3 7.8 159.3 -27.2 -442.7 -284.1 -60.5 -31.2 -31.2
Trade Creation with ASEANValue 267.7 280.0 -1.082.0 -443.3 237.9 832.3 275.4 368.0 1.810.9 2.178.9% 8.3 63.5 -111.9 -26.3 31.5 22.2 18.9 6.0 7.5 7.2
Trade DiversionValue -499.2 -1.741.4 -3.654.8 -2.657.5 509.2 4.497.6 323.9 -3.222.2 -3.099.3 -6.321.5% -3.5 -5.3 -26.2 -31.3 17.6 230.9 5.5 -6.1 -2.9 -4.0
Indonesia Malaysia Singapore Thailand Philippines Vietnam Other ASEAN China ACFTAASEAN
Appendix 1RESULT FROM RUNNING MODEL GTAP (iv)
EXPORT NET
61The Impact of ACFTA Implementation on International Trade of IndonesiaA
pp
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1.217
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790.2
894.2
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258.7
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5,766
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4,976
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Com
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ORLD
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%%
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%42
62 Bulletin of Monetary, Economics and Banking, July 2010
31.P
aper
Produ
cts1,5
50.6
1,667
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7.07.5
0.52
578.3
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32. P
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7.035
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1.521
1.439
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33. C
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3,373
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6.761
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35. Ir
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209.5
210.7
1.20.6
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185.6
179.2
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6.117
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-8.9
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38. M
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423.0
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39.P
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230.5
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226.6
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41.M
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7
Com
mod
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Expo
rt to
ACF
TA
42
Expo
rt to
ASE
ANEx
port
to C
HINA
Expo
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the
WOR
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pre
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Expo
rt to
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Ap
pen
dix
2C
OM
PAR
ATI
ON
OF
IMPA
CT
OF
AC
TFA
ON
IND
ON
ESIA
(C
OM
MO
DIT
IES)
- (
ii)
63The Impact of ACFTA Implementation on International Trade of IndonesiaA
pp
end
ix 2
CO
MPA
RA
TIO
N O
F IM
PAC
T O
F A
CTF
A O
N IN
DO
NES
IA (
CO
MM
OD
ITIE
S) -
(iii
)
VIMS
1.Ric
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3.50.3
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107.8
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85.4
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199.6
254.3
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98.9
87.5
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100.7
166.8
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140.8
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318.4
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01
Com
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pre
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pre
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are
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%%
%
Expo
rt to
ACF
TAEx
port
to A
SEAN
Expo
rt to
CHI
NAEx
port
to W
ORLD
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rt to
ROW
64 Bulletin of Monetary, Economics and Banking, July 2010
Com
mod
ities 42
pre
post
chg
%sh
are
pre
post
chg
%sh
are
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chg
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%31
Pape
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287.8
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332
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1,586
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Chem
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4,128
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319.4
3.20.5
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60.3
5,793
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34M
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326.5
365.9
39.4
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163.9
154.1
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162.6
211.8
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238.3
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277.8
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982.2
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806.2
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138.2
239.3
101.1
73.2
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70.6
46.7
1.40.0
82,4
41.7
2,425
.1-16
.6-0.
7-0.
0539
Trans
porta
tion E
qp.
870.0
1,083
.521
3.524
.50.8
451
2.338
3.8-12
8.5-25
.1-0.
7435
7.769
9.734
2.095
.64.1
31,5
36.2
1,609
.773
.54.8
0.12
666.2
526.2
-140.0
-21.0
-0.39
40Ele
c tron
ic s3,9
05.8
4,103
.219
7.45.1
0.77
2,983
.62,8
44.0
-139.6
-4.7
-0.81
922.2
1,259
.233
7.036
.54.0
76,6
39.7
6,788
.714
9.02.2
0.24
2,733
.92,6
85.5
-48.4
-1.8
-0.13
41 M
achin
ery Eq
pt.3,8
73.8
4,265
.139
1.310
.11.5
32,5
30.7
2,366
.1-16
4.6-6.
5-0.
951,3
43.1
1,899
.055
5.941
.46.7
210
,595.4
10,78
6.619
1.21.8
0.31
6,721
.66,5
21.5
-200.1
-3.0
-0.55
42Ind
ustry
Nec
393.1
512.9
119.8
30.5
0.47
217.4
173.6
-43.8
-20.1
-0.25
175.7
339.3
163.6
93.1
1.98
667.7
739.9
72.2
10.8
0.12
274.6
227.0
-47.6
-17.3
-0.13
Total
25.53
0.827
,972.1
2,441
.39.6
9.617
,259.1
16,35
7.5-90
1.6-5.
2-5.
28,2
71.7
11,61
4.63,3
42.9
40.4
40.4
61,71
4.463
,280.7
1,566
.32.5
2.536
,183.6
35,30
8.6-87
5.0-2.
4-2.
4
Ap
pen
dix
2C
OM
PAR
ATI
ON
OF
IMPA
CT
OF
AC
TFA
ON
IND
ON
ESIA
(C
OM
MO
DIT
IES)
- (
iv)
Expo
rt to
ACF
TAEx
port
to A
SEAN
Expo
rt to
CHI
NAEx
port
to W
ORLD
Expo
rt to
ROW
65The Impact of ACFTA Implementation on International Trade of Indonesia
APPENDIX 3TABEL OF DATA AGREGATION OF14 REGIONS DAN 42 SECTORS
1 Japan Japan2 Korea Korea3 Cina Cina4 India India5 Indonesia Indonesia6 Malaysia Malaysia7 Singapore Singapore8 Thailand Thailand9 Philippines Philippines
10 Vietnam Vietnam11 Other ASEAN Cambodia, Lao PDR, Myanmar, Brunei Darussalam12 USA USA13 EU 25 Austria, Belgium, Cyprus, Czech Republic, Denmark, Estonia, Finland,
France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania,Luxemborg, Malta, Netherlands, Poland, Portugal, Slovakia, Slovenia,Spain, Sweden, UK
14 Rest of The World Australia, New Zealand, Rest of Oceania, Hongkong, Taiwan, Rest ofEast Asia, Bangladesh, Pakistan, Sri Lanka, Rest of South Asia, Canada,Mexico, Rest of North America, Argentina, Bolivia, Brazil, Chile,Colombia, Ecuador, Paraguay, Peru, Uruguay, Venezuela, Rest ofSouth America, Costa Rica, Guatemala, Nicaragua, Panama, Rest ofCentral America, Caribbean, Switzerland, Norway, Rest of EFTA,Albania, Bulgaria, Belarus, Croatia, Romania, Russian Federation,Ukraine, Rest of Eastern Europe, Rest of Europe, Kazakhstan,Kyrgyztan, Rest of Former Soviet Union, Armenia, Azerbaijan, Georgia,Iran, Turkey, Rest of Western Asia, Egypt, Morocco, Tunisia, Rest ofNorth Africa, Nigeria, Senegal, Rest of Western Africa, Central Africa,South Central Africa, Ethiopia, Madagascar, Malawi, Mauritius,Mozambique, Tanzania, Uganda, Zambia, Zimbabwe, Rest of EasternAfrica, Bostwana, South Africa, Rest of South African Customs
No. Regional Aggregation Member
I. Region Aggregation
66 Bulletin of Monetary, Economics and Banking, July 2010
1 PDR Paddy rice2 WHT Wheat3 GRO Cereal grains nec4 V_F Vegetables, fruit, nuts5 OSD Oil seeds6 C_B Sugar cane, sugar beet7 PFB Plant-based fibers8 OCR Crops nec9 CTL Cattle, sheep, goats, horses
10 OAP Animal products nec11 RMK Raw milk12 WOL Wool, silk-worm cocoons13 FRS Forestry14 FSH Fishing15 COA Coal16 OIL Oil17 GAS Gas18 OMN Minerals nec19 CMT Meat: cattle, sheep, goats, horse20 OMT Meat products nec21 VOL Vegetable oils and fats22 MIL Dairy products23 PCR Processed rice24 SGR Sugar25 OFD Food products nec26 B_T Beverages and tobacco products27 TEX Textiles28 WAP Wearing apparel29 LEA Leather products30 LUM Wood products31 PPP Paper products, publishing32 P_C Petroleum, coal products33 CRP Chemical,rubber,plastic prods34 NMM Mineral products nec35 I_S Ferrous metals36 NFM Metals nec37 FMP Metal products38 MVH Motor vehicles and parts39 OTN Transport equipment nec40 ELE Electronic equipment41 OME Machinery and equipment nec42 OMF Manufactures nec43 OTHERS Electricity; Gas manufacture, distribution; Water; Construction; Trade;
Transport nec; Sea transport; Air transport; Communication; Financialservices nec; Insurance; Business services nec; Recreation and otherservices; Public Administration/Defence/Health/Education; Dwellings
No. Sectoral Aggregation Member
II. Sector Aggregation
67The Impact of ACFTA Implementation on International Trade of Indonesia
APPENDIX 4CONVERTION TABLE FOR 7 COMMODITIES SECTOR
Agricultural Product Paddy rice, wheat, cereal grains nec, vegetable, fruit, nuts, oil seeds, sugar cane, sugarbeet, plant-based, crops nec, bovine cattle, sheep and goats, horse, animal product,raw milk, wool silk-worm cocoons, bovine cattle, sheep and goats, horse meat product
Food Product Meat product nec, vegetable oil and fats, dairy products, processed rice, sugar, foodproducts nec, beverages and tobacco products
Extractive Industry Forestry, fishing, coal, oil, gas, minerals nec, petroleum, coal productsLight Manufacturing Textiles, wearing apparel, leather product, wood productsHeavy Paper products, publishing, chemical, rubber, plastic products, mineral products nec,
ferrous metals, metalsManufacturing necTechnology-intensive Metal products, motor vehicle and parts, transport equipment nec,Manufacturing electronic, machinery and equipment nec, manufacturing necServices Electronic, gas manufacturing, distribustion, water, construction trade, transport,
financial, business, recreational services, public administrayion and defense, education,health, dwellings and services
Sector Commodities
Source : ADB, WP No 130, 2008nec : not elsewhere classified
68 Bulletin of Monetary, Economics and Banking, July 2010
APPENDIX 5TABLE MAP OF RCA AND IIT QUADRANTS (TOTAL)
I 9 33 Chemical 1.11 0.85 1,644,317,782 11.62%
16 Oil 2.26 0.82 1,382,885,185 9.77%
27 Textils 1.62 0.64 588,106,204 4.16%
38 Motor Vehicles 1.12 0.85 332,659,537 2.35%
35 Metals 1.04 0.88 251,830,711 1.78%
34 Mining products 1.48 0.69 196,203,561 1.39%
26 Beverages 1.30 0.82 177,537,037 1.25%
11 Pure Milk 1.11 0.73 30,045,361 0.21%
22 Dairy products 1.09 0.52 534,984 0.00%
Total 4,604,120,362 32.54%
Quadrant Number Code Classification of Main Commodities RCA IIT Export Value Export Share
Period I (Average 2001-2004)
II 8 41 Machinery and equipment 0.42 0.83 1,986,833,043 14.04%
37 Metal products 0.77 0.87 163,943,461 1.16%
4 Vegetables 0.87 0.77 119,663,788 0.85%
25 Food products 0.98 0.89 111,614,849 0.79%
29 Leather products 0.89 0.88 71,961,181 0.51%
20 Meat products 0.68 0.60 36,946,777 0.26%
5 Oil Seeds 0.94 0.51 11,503,016 0.08%
19 Meat 0.20 0.68 80,856 0.00%
Total 2,502,546,970 17.69%
Quadrant Number Code Classification of Main Commodities RCA IIT Export Value Export Share
III 14 40 Electronics 0.73 0.30 1,840,619,562 13.01%32 Petroleum 0.49 0.31 414,346,141 2.93%42 Industry Nec 0.64 0.48 228,466,798 1.61%28 Apparel 0.79 0.22 125,014,619 0.88%39 Transport equipment 0.56 0.34 56,274,523 0.40%3 Cereal Grain 0.22 0.09 3,990,231 0.03%24 Sugar 0.05 0.03 2,398,110 0.02%2 Wheat 0.78 0.45 2,288,071 0.02%10 Animal products 0.18 0.39 1,437,850 0.01%23 Processed Rice 0.01 0.01 503,919 0.00%1 Rice 0.00 0.00 0 0.00%6 Sugar Cane 0.00 0.00 0 0.00%7 Fiber 0.00 0.00 0 0.00%12 Wool 0.00 0.00 0 0.00%
Total 2,675,339,823 18.91%
Quadrant Number Code Classification of Main Commodities RCA IIT Export Value Export Share
Period I (Average 2001-2004)
Period I (Average 2001-2004)
69The Impact of ACFTA Implementation on International Trade of Indonesia
IV 11 8 Crops Nec 2.60 0.15 510,303,657 3.61%9 Livestock 2.15 0.14 29,072,147 0.21%13 Forestry 4.10 0.04 3,619,860 0.03%14 Fishing 1.98 0.24 179,706,122 1.27%15 Coal 7.00 0.07 344,450,420 2.43%17 Gas 1.57 0.14 148,201,956 1.05%18 Minerals Nec 5.59 0.34 360,869,596 2.55%21 Vegetable Oil 3.82 0.06 683,396,677 4.83%30 Wood products 3.19 0.12 493,267,281 3.49%31 Paper Products 4.57 0.27 916,030,861 6.47%36 Metal Nec 2.79 0.33 697,866,399 4.93%
Total 4,366,784,974 30.86%
Quadrant Number Code Classification of Main Commodities RCA IIT Export Value Export Share
Period I (Average 2001-2004)
Note : Calculation is based on SITC data conversion from UNCOMTRADE to 42 tradable commodities in GTAP
I 9 16 Oil 2.45 0.82 2,716,031,454 9.51%
38 Motor Vicle 1.23 0.74 859,808,533 3.01%
27 Textiles 1.01 0.74 684,776,101 2.40%
30 Wood Products 1.68 0.64 410,094,630 1.44%
26 Beverages 1.31 0.79 261,927,830 0.92%
25 Food Products 1.05 0.96 224,759,805 0.79%
29 Leather Products 1.16 0.82 179,757,549 0.63%
5 Oil Seeds 2.36 0.62 27,301,185 0.10%
22 Dairy Products 1.47 0.83 1,913,165 0.01%
Total 5,366,370,249 18.78%
Quadrant Number Code Classification of Main Commodities RCA IIT Export Value Export Share
Period II (Average 2005-2008)
II 11 41 Machine Equipment 0.42 0.82 3,459,339,492 12.11%
33 Chemical 0.87 0.71 2,554,706,472 8.94%
40 Electronics 0.48 0.61 2,072,101,828 7.25%
35 Iron Metal 0.69 0.58 685,974,318 2.40%
42 Industry Nec 0.47 0.56 427,122,284 1.49%
39 Transport Equipment 0.81 0.71 379,215,365 1.33%
37 Metal Products 0.55 0.66 285,388,289 1.00%
4 Vegetable 0.82 0.64 214,127,650 0.75%
34 Mining Product 0.90 0.86 207,486,926 0.73%
28 Apparel 0.46 0.67 151,515,810 0.53%
10 Animal Product 0.28 0.58 2,958,244 0.01%
Total 10,439,936,678 36.54%
Quadrant Number Code Classification of Main Commodities RCA IIT Export Value Export Share
Period II (Average 2005-2008)
70 Bulletin of Monetary, Economics and Banking, July 2010
III 10 32 Petroleum 0.38 0.19 935,618,846 3.27%
11 Pure Milk 0.67 0.33 25,279,380 0.09%
24 Sugar 0.27 0.11 17,854,983 0.06%
3 Cereal Grain 0.55 0.40 8,389,705 0.03%
23 Processed rice 0.00 0.01 330,037 0.00%
19 Meat 0.01 0.20 7,325 0.00%
1 Rice 0.00 0.00 0 0.00%
6 Sugar Cane 0.00 0.00 0 0.00%
7 Fiber 0.00 0.00 0 0.00%
12 Wool 0.00 0.00 0 0.00%
Total 987,480,275 3.46%
Quadrant Number Code Classification of Main Commodities RCA IIT Export Value Export Share
Period II (Average 2005-2008)
IV 12 36 Metal Nec 3.77 0.29 2,482.296,551 8.69%
21 Vegetable Oil 5.11 0.03 2,156.452,594 7.55%
17 Gas 6.78 0.05 1,846.798,666 6.46%
8 Crops Nec 2.91 0.13 1,498.317,400 5.24%
31 Paper Products 4.39 0.37 1,442.952,860 5.05%
15 Coal 7.08 0.05 1,170.145,644 4.10%
18 Mineral Nec 5.39 0.35 709,176,692 2.48%
14 Fishery 1.89 0.25 229,429,381 0.80%
20 Meat Products 2.12 0.37 203,014,679 0.71%
9 Livestock 1.63 0.06 27,159,304 0.10%
2 Wheat 1.45 0.32 6,619,736 0.02%
13 Forestry 5.36 0.12 5,956,443 0.02%
Total 11,778,319,950 41.22%
Quadrant Number Code Classification of Main Commodities RCA IIT Export Value Export Share
Period II (Average 2005-2008)
Note : Calculation is based on SITC data conversion from UNCOMTRADE to 42 tradable commodities in GTAP
71The Impact of ACFTA Implementation on International Trade of Indonesia
I 10 33 Chemical 1.18 0.85 1,644,317,782 13.03%27 Textiles 1.72 0.64 588,106,204 4.66%38 Motor vehicle 1.19 0.85 332,659,537 2.64%35 Iron Metal 1.11 0.88 251,830,711 2.00%34 Mining Products 1.57 0.69 196,203,561 1.55%26 Beverages 1.39 0.82 177,537,037 1.41%25 Food Products 1.04 0.89 111,614,849 0.88%11 Pure Milk 1.18 0.73 30,045,361 0.24%5 Oil Seeds 1.00 0.51 11,503,016 0.09%22 Dairy Products 1.16 0.52 534,984 0.00%
Total 3,343,818,057 26.50%
Quadrant Number Code Classification of Main Commodities RCA IIT Export Value Export Share
Period I (Average 2001-2004)
APPENDIX 6TABLE MAP OF RCA AND IIT QUADRANTS (NON OIL AND GAS)
II 6 41 Machine Equipment 0.45 0.83 1,986,833,043 15.75%
37 Metal Products 0.82 0.87 163,943,461 1.30%
4 Vegetable 0.93 0.77 119,663,788 0.95%
29 Leather Products 0.95 0.88 71,961,181 0.57%
20 Meat Products 0.73 0.60 36,946,777 0.29%
19 Meat 0.21 0.68 80,856 0.00%
Total 2,379,429,106 18.86%
Quadrant Number Code Classification of Main Commodities RCA IIT Export Value Export Share
Period I (Average 2001-2004)
III 14 40 Electronics 0.77 0.30 1,840,619,562 14.59%32 Petroleum 0.52 0.31 414,346,141 3.28%42 Industry Nec 0.69 0.48 228,466,798 1.81%28 Apparel 0.85 0.22 125,014,619 0.99%39 Transport Equipment 0.59 0.34 56,274,523 0.45%3 Cereal Grain 0.24 0.09 3,990,231 0.03%24 Sugar 0.05 0.03 2,398,110 0.02%2 Wheat 0.83 0.45 2,288,071 0.02%10 Animal Products 0.19 0.39 1,437,850 0.01%23 Processed Rice 0.01 0.01 503,919 0.00%1 Rice 0.00 0.00 0 0.00%6 Sugar Cane 0.00 0.00 0 0.00%7 Fiber 0.00 0.00 0 0.00%12 Wool 0.00 0.00 0 0.00%
Total 2,675,339,823 21.20%
Quadrant Number Code Classification of Main Commodities RCA IIT Export Value Export Share
Period I (Average 2001-2004)
72 Bulletin of Monetary, Economics and Banking, July 2010
IV 10 31 Paper Products 4.87 0.27 916,030,861 7.26%36 Metal Nec 2.98 0.33 697,866,399 5.53%21 Vegetable oil 4.07 0.06 683,396,677 5.42%8 Crops Nec 2.77 0.15 510,303,657 4.04%30 Wood Products 3.39 0.12 493,267,281 3.91%18 Mineral Nec 5.96 0.34 360,869,596 2.86%15 Coal 7.45 0.07 344,450,420 2.73%14 Fishery 2.11 0.24 179,706,122 1.42%9 Livestock 2.29 0.14 29,072,147 0.23%13 Forestry 4.37 0.04 3,619,860 0.03%
Total 4,218,583,018 33.43%
Quadrant Number Code Classification of Main Commodities RCA IIT Export Value Export Share
Period I (Average 2001-2004)
Note: Calculation is based on SITC data conversion (non oil and gas) from UNCOMTRADE to 42 tradable commodities in GTAP
I 9 38 Motor vehicle 1.39 0.74 859,808,533 3.58%
27 Textiles 1.14 0.74 684,776,101 2.85%
30 Wood Products 1.89 0.64 410,094,630 1.71%
26 Beverages 1.49 0.79 261,927,830 1.09%
25 Food Products 1.18 0.96 224,759,805 0.94%
34 Mining Products 1.02 0.86 207,486,926 0.86%
29 Leather Products 1.31 0.82 179,757,549 0.75%
5 Oil Seeds 2.65 0.62 27,301,185 0.11%
22 Dairy Products 1.67 0.83 1,913,165 0.01%
Total 2.857.825.721 11.90%
Quadrant Number Code Classification of Main Commodities RCA IIT Export Value Export Share
Period II (Average 2005-2008)
II 10 41 Machinery Eqpt. 0.47 0.82 3,459,339,492 14.41%
33 Chemical 0.98 0.71 2,554,706,472 10.64%
40 Elektronics 0.54 0.61 2,072,101,828 8.63%
35 Iron Metal 0.78 0.58 685,974,318 2.86%
42 IndustryNec 0.53 0.56 427,122,284 1.78%
39 Transport Eqpt. 0.92 0.71 379,215,365 1.58%
37 Metal Products 0.62 0.66 285,388,289 1.19%
4 Beverages 0.92 0.64 214,127,650 0.89%
28 Apparel 0.52 0.67 151,515,810 0.63%
10 Animal Products 0.32 0.58 2,958,244 0.01%
Total 10,232,449,752 42.62%
Quadrant Number Code Classification of Main Commodities RCA IIT Export Value Export Share
Period II (Average 2005-2008)
73The Impact of ACFTA Implementation on International Trade of Indonesia
III 10 32 Petroleum 0.43 0.19 935,618,846 3.90%
11 Pure Milk 0.76 0.33 25,279,380 0.11%
24 Sugar 0.31 0.11 17,854,983 0.07%
3 Cereal Grain 0.62 0.40 8,389,705 0.03%
23 Processed Rice 0.00 0.01 330,037 0.00%
19 Meat 0.01 0.20 7,325 0.00%
1 Rice 0.00 0.00 0 0.00%
6 Sugar Cane 0.00 0.00 0 0.00%
7 Fiber 0.00 0.00 0 0.00%
12 Wool 0.00 0.00 0 0.00%
Total 987,480,275 4.11%
Quadrant Number Code Classification of Main Commodities RCA IIT Export Value Export Share
Period II (Average 2005-2008)
IV 11 36 Metal Nec 4.26 0.29 2,482,296,551 10.34%
21 Oil Vegetable 5.78 0.03 2,156,452,594 8.98%
8 Crops Nec 3.29 0.13 1,498,317,400 6.24%
31 Paper Products 4.96 0.37 1,442,952,860 6.01%
15 Coal 8.01 0.05 1,170,145,644 4.87%
18 Mineral Nec 6.09 0.35 709,176,692 2.95%
14 Fishery 2.14 0.25 229,429,381 0.96%
20 Meat Products 2.40 0.37 203,014,679 0.85%
9 Livestock 1.84 0.06 27,159,304 0.11%
2 Wheat 1.66 0.32 6,619,736 0.03%
13 Forestry 6.07 0.12 5,956,443 0.02%
Total 9,931,521,284 41.37%
Quadrant Number Code Classification of Main Commodities RCA IIT Export Value Export Share
Period II (Average 2005-2008)
Note: Calculation is based on SITC data conversion (non oil and gas) from UNCOMTRADE to 42 tradable commodities in GTAP
74 Bulletin of Monetary, Economics and Banking, July 2010
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75Is ACFTA Proper Strategy of Sustainable Poverty Alleviation?: Proof From The Depletion of Saving Rate
The outcome of Regional Free Trade Area (R-FTA) still remains a conundrum. Regional free trade
area (R-FTA) is one of the manifestations of the economy integration phenomenon. R-FTA brings many
pros and cons to the economists. It allows better allocation of resources especially by eliminating tariffs,
thus making people have higher purchasing power for goods. While the increase of purchasing power is
good for growth engine and poverty alleviation progress, this paper proves that there is potency for the
agreement to be detrimental in the long run.
The main focus in this paper is the potential impact of ACFTA to the saving rate as the shock buffer
for the poor in time of recessions and crises, where purchasing power decreases significantly. We view
the ACFTA impact through the series of net import, defined as the difference between imports from
export. We use Dynamic Panel Data (DPD) to estimate the impact of net import to the saving rate, assuming
that there is a dynamic relationship between saving rate and its lagged value. The estimation result proves
that there is a negative relationship between import and the saving per capita, which indicates the
consumptive behavior of ASEAN people under high import. Moreover, the dynamic relationship shows
that saving per capita is not persistent, meaning that the saving rate will be decreased gradually.
Therefore, we can expect that in the long rung, the savings will be depleted into nothing if we
keep letting the import flooded domestic market without imposing any pre-emptive and reactive policies.
This paper provides a set of historical estimation of the potential impact of ACFTA on saving rate and its
policy implication to endure the impact.
Keywords: : : : : Free Trade, Poverty Alleviation, Saving BehaviorFree Trade, Poverty Alleviation, Saving BehaviorFree Trade, Poverty Alleviation, Saving BehaviorFree Trade, Poverty Alleviation, Saving BehaviorFree Trade, Poverty Alleviation, Saving Behavior
JEL Classification Code: : : : : E38, F15E38, F15E38, F15E38, F15E38, F15
1 Bagus Arya Wirapati is bachelor graduate from Faculty of Economics University of Indonesia and currently serving as Pengajar Mudain Gerakan Indonesia Mengajar. [email protected]
2 Niken A.S. Kusumawardhani is bachelor graduate from Faculty of Economics University of Indonesia and currently a Master Studentat Institut D»Etudes Politiques (Sciences Po) Paris. [email protected]
IS ACFTA A PROPER STRATEGYOF SUSTAINABLE POVERTY ALLEVIATION?:
PROOF FROM THE DEPLETION OF SAVING RATE
Bagus Arya Wirapati 1 danNiken Astria Sakina Kusumawardhani 2 *****
Abstract
76 Bulletin of Monetary, Economics and Banking, July 2010
I. INTRODUCTION
According to Mid-Term National Development Plan (Rencana Pembangunan Jangka
Menengah/RPJM) 2010-2014, the government of Indonesia has targeted economic growth
rates of 5.5% in 2010, 7% in 2012, and above 7% in 2014. Meanwhile, in the National Long-
Term Development Plan (Rencana Pembangunan Jangka Panjang/RPJP) 2005-2025, the
government has targeted to achieve the prosperity of the nation at an equal level with other
middle-income countries and to maintain open unemployment rate and poverty rate of less
than 5%.
Government»s targets and efforts above are determined in order to face the free trade
agreement between Indonesia and other countries. Indonesia has many multilateral or bilateral
free trade agreements with other countries, including South Korea (2007), Japan (2007), Australia
and New Zealand (2009), India (2009), and China (2010). Those free trade agreements may
bring opportunities and threats to Indonesia economy.
The agreement of ASEAN-China Free Trade Area (ACFTA) reduced tariffs of 90 percent of
imported goods to zero. ASEAN countries, especially the developing ones (note that Singapore
is considered as developed country), will be flooded by flow of goods under ACFTA. Increase of
access to great quantity of low-price goods, in term of expenditure, would be very beneficial
for the poor. Todaro and Smith (2008, [59]) argued that an increase of the poor»s access to the
goods and services is one proof of the poverty alleviation progresses. It would increase the
fulfillment of the poor»s primary and secondary needs. Therefore, based on expenditure point
of view, the number of poverty will decrease due to the increase of the poor»s ability to access
goods under this free trade agreement.
It is indeed would reduce poverty level but the sustainability of this poverty alleviation still
remains as a conundrum. Since the poor has greater marginal propensity to consume than the
have, the poor will likely choose to consume more; consequently, reducing the proportion of
savings from their income. They tend to increase the consumption rather than savings for
future buffer against economic shocks and instability. This behavior will lead them to lower
level of resilience against the economic downturn. Therefore, imposing Regional Free Trade
Area, in this case ACFTA, to increase the availability low-price goods is hypothesized to be an
improper strategy for sustainable poverty alleviation, especially in the long run.
This paper aims to answer the main question of whether ACFTA is a proper strategy of
sustainable poverty alleviation. To answer such question, main goal of this paper is to get an
empirical result of relationship between net import and savings rate as a proxy of the country»s
poverty rate. The paper will be organized in following manner: chapter 2 describes about
77Is ACFTA Proper Strategy of Sustainable Poverty Alleviation?: Proof From The Depletion of Saving Rate
ACFTA. Chapter 3 presents literature review and conceptual framework of the model used in
this research. Chapter 4 explains about research methodology, while chapter 5 includes analysis
and discussion of empirical result. Finally, the summary and policy recommendation will be
presented in chapter 6.
II. ASEAN-CHINA FREE TRADE AGREEMENT (ACFTA)
Regional Free Trade Area (R-FTA) is one of the manifestations of the economy integration
phenomenon. R-FTA brings many pros and cons to the economists. It allows better allocation of
resources especially by eliminating tariffs, thus making people have higher purchasing power for
goods. ASEAN-China Free Trade Area (ACFTA) is implemented by eliminating or reducing barriers
to trade in goods (both tariff and non tariff), improving access to service market and also investment
rules and regulations, as well as improvement of economic cooperation in order to improve the
welfare of ASEAN and China community. ACFTA brings various fortunes for ASEAN countries, as
well as its misfortunes. Government of Indonesia hopes that ACFTA will bring future favorable
implications, such as wider opportunity for Indonesia to enter China markets by means of relatively
low tariff and large population, increased cooperation between businessmen in both countries
through the establishment of strategic alliances, increased purchasing power of China goods
due to reduced tariffs or costs, and improved possibility of transfer of technology between
business people in both countries. Whether the expectations will turn into reality or not, it still
takes many years to come to finally see the actual impact of ACFTA.
Chinese Premier Zhu Rongji originated the idea of a free trade area between China and
ASEAN at the China-ASEAN Summit, November 2000. In October 2001, a group of economic
experts from China and ASEAN issued a recommendation for establishment of ASEAN-China
within ten years in the future. A month later, in November 2001, during another China-ASEAN
Summit, the leaders from respected countries started to negotiate the possibility for such an
idea. A year later, the ASEAN leaders and Chinese Premier Zhu Rongji signed the ACFTA
Framework Agreement. This agreement served as a roadmap for the establishment of the free
trade area between China and ASEAN. The agreement stated that the free trade area should be
completed by 2010, considering that four ASEAN members are expected to join the network by
2015. The ACFTA Framework Agreement is a groundbreaking document, for while individual
ASEAN members had previously created free trade agreements, ASEAN as an organization had
never before made such a bond with an outside nation. Moreover, the ACFTA Framework
Agreement was China»s first free trade agreement with a foreign nation. Since the ACFTA
Framework Agreement, both China and ASEAN have entered into negotiations with other
countries regarding free trade agreements.
78 Bulletin of Monetary, Economics and Banking, July 2010
According to ACFTA agreement, tariff elimination should be done gradually. The steps
are Early Harvest Program (EHP), Normal Track I and II, and Sensitive/Highly Sensitive List. Each
step is scheduled between each ASEAN countries and China bilaterally, which means that each
country decides its own schedule for tariff reduction or elimination for each category of product.
Since November 2002, ASEAN 6 (Indonesia, Singapore, Thailand, Malaysia, Philippine, Brunei)
and China have agreed to sign ACFTA, for 0% entry tariff per January 2004 exclusively for
products categorized as EHP. Beginning from 2004, each year Indonesia reduced tariff for
imported products from China. During 2004-2009, around 65% Chinese products have been
identified as free-entry products from Dirjen Bea Cukai, Indonesia Ministry of Finance. In January
2010, around 1598 or 18% products form China received reduction of 5% tariff while 82% of
total 8.738 import products from China have been completely excluded from tariff charge. On
the contrary, during 2004-2009, balance of trade between Indonesia and China showed that
Indonesia imports more products from China rather than exports. Therefore, during 2003-
2009, Indonesia has accumulatively a trade deficit (on non-oil trading) with China as of USD
12.6 million (around 120 trillion Rupiah). Compared to other ASEAN countries, Singapore is
the biggest exporter to China, while Indonesia is at the 5th ranking right after Thailand. The
biggest deficit of trade between Indonesia and China is around USD 7.2 million in 2008.
Indonesia»s participation in various agreements of free trade agreements can not be
prevented or reversed, although the manufacturing sector expressed its reluctance due to fear
of competition. However, typically in the agreement of free trade, there are clauses that provide
opportunity for involved parties to modify and ability to temporary suspense the concessions in
order to improve its competitiveness or strength. To protect the manufacturing sector from the
invasion of import products, government should enacted cross-ministries coordination that
involves representatives from real sector and related associations.
Since the establishment of ACFTA this January 2010, negative reactions from the
associations of real sector players have been heard. Most of them stated that they are not ready
yet to compete with China, and they asked for the government to postpone the implementation
of ACFTA agreement. Especially for the case of ACFTA and Common Effective Preferential
Tariff-ASEAN Free Trade Agreement (CEPT-AFTA), Indonesia still agree to reduce the tariff
according to schedule, where products categorized as Normal Track (NT1) ACFTA and Inclusion
List (IL) CEPT-AFTA for ASEAN planned to have 0% of entry tariff beginning January 1, 2010.
The Minister of Trade has postponed the elimination of entry tariff for some products due to
unpreparedness of some domestic sectors. At the moment being, Indonesia is in the process of
postponing tariff cut in 227 categories of product.
79Is ACFTA Proper Strategy of Sustainable Poverty Alleviation?: Proof From The Depletion of Saving Rate
III. REVIEW LITERATURE
III.1. The Role of Saving For an Economy
Savings plays an important role for an economy and each type of savings plays different
important roles. Savings are done by three entities in an economy: households, companies, and
government. Households save to cover expenses of their children and for future buffer during
retirement period. Companies retain a part of their profit as retained earning for future investment
to expand their businesses. On the other hand, government saves if the tax revenue exceeds
the government expenditure. Government saves to build public facilities or infrastructures such
as hospitals, bridges, or harbors. Lack of savings by each entity leads to different impact.
Households may have to struggle to fund their big expenses, so they have to make big loans to
banks for school expenses. If companies save too little, for example they disburse all their
income for shareholders in form of dividends; they may find it hard to fund the expansion of
their branches. Therefore, the companies lose their potential to grow. Government who saves
too little also will not be able to build physical infrastructure, and it is going to affect the
economy of the country as a whole. Foreign investors would not prefer to invest in the country
due to lack of infrastructure, and domestically, less development by government means higher
rate of unemployment and sub-optimal economic growth.
In order to possess high level of national income or prosperity, firstly a country must
possess high level of productivity. Determinants of productivity are working capitals such as
physical capital, human capital, natural resources, and technological knowledge. The more
working capitals a country has, the faster it grows compared to the others. Possession of
working capitals determines the level of productivity that a country may achieve. It»s clear to
see that one way to improve one country»s productivity is to invest its resources in form of
working capitals. The endogenous growth theories since the mid 1980s by Romer (1986,
1990), Lucas (1988), and Barro (1990) in Mikesell and Zinser (1973, [41]) confirmed the view
that the accumulation of physical capital is the critical driver of long-run economic growth.
Investment in working capital should be translated as increased saving rate of the country
itself. It»s because more usage of resources today to produce working capitals means reducing
resources available to for consumption at the time being. Reduced consumption means
increased saving. Therefore, we can conclude that more saving allows better investment in
working capitals and productivity, which in the future will lead to higher level of national
income. Development economists regard saving rate as a key performance indicator, and it is
labeled as a primary condition for achieving a satisfactory rate of economic growth (Mikesell
and Zinser, 1973, [41]).
80 Bulletin of Monetary, Economics and Banking, July 2010
A classic view of the macro-economic dynamics of the growth process was that increasing
savings when transformed into productive investment would help achieve an economic growth
(Harrod, 1939; Domar, 1946; Lewis, 1954; Solow, 1956 in AlFoul (2010, [1])). These studies
provide empirical support for hypotheses that savings growth promotes economic growth. The
conventional perception is that savings contribute to higher investment and hence higher GDP
growth in the short run (Japelli and Pagano, 1994, [32]). Finally, a study by AlFoul (2010, [1])
confirmed that during period of 1965-2007 in Morocco, a long-run two-way relationship
between real GDP and real gross domestic saving (GDS) is proved to be exist; while in the same
period in Tunisia, the results reveal that saving stimulates growth, not the other way around.
Supported by previous studies, we believe that higher savings would lead to higher growth
rate. Saving itself is defined as the result of income deducted by consumption, or can be
expressed by S = Y √ T √ C, where S = saving, Y = income, T = tax, and C = consumption.
Figure IV.1.Consumption Function
Source: Azzopardi (2004, [4])
Consumption Consumption = Disposable Income
Negative Saving
Positive Saving
Consumption FunctionC = a + c (Y-T)
a 45 degree
Disposable Income
The consumption function in the Figure IV.1 above states that consumption equals a
fixed amount of «a» plus a fraction «c» of disposable income (Y-T). A household has positive
saving when its disposable income exceeds its consumption, and it has negative saving when
its consumption exceeds its disposable income. Priorities of consumption of each household
may differ one another, but generally the basic necessities will be on the top of consumption
list. For example, during economic crisis and income falls very low, households take out their
money from savings to buy basic necessities of their life. Keynes concluded in his book, ≈The
General Theory of Employment, Interest, and Money∆, that savings depends on disposable
income. The conventional wisdom is that rich people save larger fraction of their disposable
income compared to poor people. Poor people have less disposable income, and generally they
spend all of their income for their needs, making them have no chance to save. Therefore, we
81Is ACFTA Proper Strategy of Sustainable Poverty Alleviation?: Proof From The Depletion of Saving Rate
assume that the poor has lower marginal propensity to save compared to the rich. When poor
people begin to save or to save more than they used to, it»s a signal that their wealth is improving.
II.2 Determinants of Saving Rate
Savings has been considered a critical macro-economic variable with micro-economic
foundation for achieving price stability and promoting employment opportunities thereby
contributing to sustainable economic growth (Mishra et al., 2010, [42]). As Keynes said that
saving depends on disposable income, we should criticize whether there is a dynamic relationship
between saving rate and its lagged value. People do not get higher disposable income all of a
sudden, there»s a process that people usually go through to earn high level of income. Since
previous period»s disposable income usually relates to disposable income of the next period, the
same should apply for saving rate. Higgins and Williamson (1996, [23]) estimated the relationship
for 16 Asian countries from 1950 to 1992, using IMF data on savings rates, and Penn World
Table (PWT) data on income and prices, and demographic data from United Nations database.
Higgins and Williamson (1996, [23]) used lagged value of savings, dependency ratio, annual
growth in real GDP, and relative price of investment good which encouraged saving as explanatory
variables for savings (Schultz, 2004, [54]). This equation becomes unique because it assumes
there is a dynamic relationship between saving rate (Sti) and its lagged value (St-1). Schultz
(2004, [54]) contended that saving rate is expected to change gradually over time to new
condition, and a year is not an adequate time for saving rate to achieve its new condition.
Saving rate should adapt in more than a year period, adjusting to individual»s level of disposable
income. Since we assume that saving rate of period t has a relationship with saving rate at
period t-1, it implies that whatever errors are present in the savings equation in one year will
not be independent of the error in savings in the prior or following years (Schultz, 2004, [54]).
This dynamic relationship of saving and its lagged value shows that lagged value of saving
should be included as one of the determinants of saving rate as a dependent variable.
Government saves if its revenue from taxes exceeds its spending. The summary of
government activities of spending and receiving tax revenue can be seen in its budget balance.
According to Keynesian open-economy model, there is a positive association between budget
balance and trade balance. In Keynesian open-economy model, budget deficit may lead to
trade deficit. The higher budget deficits put upward pressures on interest rates, where higher
interest rates would raise the foreign exchange value of the currency, and the stronger currency
would in turn reduce net exports, in other words, trade deficit. However, this conventional
view of the twin deficits has not gained much empirical support. Evans (1985, 1986) in Darrat
(1988, [12]) has found no reliable relationship for the US between budget deficits on the one
82 Bulletin of Monetary, Economics and Banking, July 2010
hand and either interest rates or exchange rates on the other. The empirical evidence is somewhat
less ambiguous and suggests that trade deficits in the US are inversely related to the exchange
value of the dollar, though the response is both small and sluggish. Proponents of this
conventional view found partial relationship between higher budget deficits and higher interest
rates (Plosser (1982, [46]), Hoelscher (1983, [25]), Cebula (1987, [10]), and Wachtel and Young
(1987, [60]). The other proponents such as Feldstein (1982) in Islam (1998, [30]) concluded
that larger budget deficits result in higher interest rates, which causes the appreciation of
exchange rate, thereby worsening the trade imbalance.
Different empirical results of the relationship between the twin deficits attracted more
research in respected topic. Another hypotheses being developed were (1) trade deficits because
budget deficits, (2) the two deficits are causally independent, and (3) the two deficits have
bidirectional causality. Over the 3 hypotheses, the hypothesis of bidirectional relationship between
budget deficit and trade deficit gained much empirical support. Islam (1998, [30]) examined
the direction of causality between budget deficits and trade deficits based on Granger test for
Brazil during 1973:1Q through 1991:4Q. Based on Granger»s causality test, Islam (1998, [30])
concluded that there is a bilateral causality between trade and budget imbalances. Another
empirical result presented by Darrat (1988, [12]) also concluded that there is a mutual causality
relationship between budget and trade deficit. Darrat (1988, [12]) hypothesized that not only
budget deficit causes trade deficit, but trade deficit may also cause budget deficit. According
to Darrat (1988, [12]), when a country»s level of net export fell off (caused by other factors than
the budget deficit), the pressure on the government would be increased. Decrease in the level
of net export would harm domestic industries, leading to higher unemployment rate and loss
of foreign market shares. This situation would in turn decrease the revenue of the government
from tax, since business activities in the export sector were depressed. The government also
would spend more to stimulate the depressed sector or to give aid to harmed domestic industries.
The empirical results of Darrat (1988, [12]) only partially support the conventional view that
budget deficits caused trade deficit, but strongly support the causality between trade deficits
to budget deficits. The empirical result of Darrat (1988, [12]) and Islam (1998, [30]) supported
the view that trade deficit has bidirectional causality with budget deficit.
The Keynesian revolution based on under-employment equilibrium made saving a function
of income and income a function of investment, as opposed to the Neoclassical view of saving
as a determinant of investment (Mikesell and Zinser, 1973, [41]). Empirical tests of saving-
income relationship have been conducted in two big groups: Keynesian or non-Keynesian
hypotheses. Kuznets (1960, [25]) in Mikesell and Zinser (1973, [41]) was among the first to do
a cross-sectional study between per capita income and saving. Kuznets (1960, [25]) achieved a
83Is ACFTA Proper Strategy of Sustainable Poverty Alleviation?: Proof From The Depletion of Saving Rate
conclusion that there was a tendency for countries with high capita income to have higher
saving ratios, but the tendency was not very consistent. Singh (1971) in Mikesell and Zinser
(1973, [41]) as a proponent of the Keynesian also concluded that when per capita GNP rose
from $100 to $1000 the gross saving ratio increased by 8 percentage points. Singh (1971) also
found that at a per capita GNP growth rate of 2 percent, it would take 50 years to increase the
saving rate by 3 percentage points. On the other hand, the proponent of non-Keynesian
hypotheses came up with a very theory of saving behavior. Dusenberry (1949, [15]), Friedman
(1957, [17]), Modigliani et al. (1954, [43]) concluded a rise in per capita in- come would not
merely lead to a higher savings ratio. One of the studies, conducted by Friedman (1957, [17]),
resulted in a new hypothesis called ≈Permanent Income Hypothesis (PIH)∆. Friedman»s hypothesis
is that people consume permanent income, and all of the transitory income (difference between
actual income and permanent income) will be allocated to saving. This implies a heavy reliance
on past behavior as a determinant of consumption spending; but changes in transitory income
will immediately lead to changes in the level of saving.
Classic analyses on savings and growth have focused on two main issues: (1) the effect of
higher savings on long run growth, and (2) the impact of higher savings on investment.
Neoclassical models inspired by Solow (1956, [57]) suggested that an increase in saving ratios
generates higher growth only in the short run, during the transition between steady states
(Edwards, 1995, [16]). More recent studies by Romer (1986, [50]) predicted that higher savings
(and the related increase in capital accumulation) might lead to permanent increase in growth
rates. Proponents of this conventional perception conclude that savings contribute to higher
investment and also higher GDP growth in the short run (noted that the catching up effect and
the law of diminishing return are exist). That»s why according to Quah (1993) in Edwards (1995,
[16]) middle-income countries are slowly vanishing. As the countries are in transition to achieve
similar steady state as high-income countries, this assumption provides a basis for researchers
to study the direction of causality between growth rate and saving rate. Mohan (2006, [45])
studied about the direction of causality between growth rate and saving rate using the concept
of Granger causality. His study is supported by previous studies that revealed that higher level
of growth rate led to higher level of saving (Caroll and Weil (1994, [9]), Sinha (1996, [55]), Saltz
(1999, [52], and Anoruo and Ahmad (2001, [2]). Caroll and Weil (1994, [9]) examined the
relationship between income growth and saving using both cross-country and household data.
At the aggregate level, they found that growth causes saving, and households with higher
income growth save more than households with low growth at household level. Caroll and
Weil (1994, [9]) explained this phenomenon by using theory of habit stock effect. They contended
that initially, a country has its own saving habit. When the rate of growth is increased in the first
period of life, the country»s income is going to be increased more than its consumption, and
84 Bulletin of Monetary, Economics and Banking, July 2010
therefore increased first period saving rate. The average saving rate of a fast-growing economy
will be higher than that of a slow-growing economy (Modigliani, 1970, [44]). What makes
Mohan»s (2006, [45]) work interesting was that he divided countries that become his samples
into different income levels (LIC/LMC/UMC/HIC). The primary hypothesis of Mohan (2006, [45])
is whether the income level of the economy influences the direction of causality between
growth rate and savings. Using time series annual data, Granger causality tests were conducted.
Mohan (2006, [45]) concluded that his study favored the hypothesis that the causality is from
economic growth rate to growth rate of savings. Mohan (2006, [45]) contended that income
levels play an important role in determining the direction of causality, he argued that the
explanation of positive causality between economic growth rate and saving rate could be best
explained by the human wealth effect theory.
The relationship between interest rates and aggregate saving involves a number of complex
theoretical and econometric problems; the most important are separating out income and
substitution effects of interest changes, quantifying the role of expectations and planning
horizons in saving decisions, and solving a difficult econometric identification problem. Williamson
(1968 in Balassa (1989, [5]) in an empirical study of six Asian countries found that with the
exception of Burma, real rates of interest were negatively correlated with national savings. In
turn, Gupta (1970, [19]) found the interest elasticity of savings to be positive and statistically
significant at the 1 percent level for India, when per capita disposable income was used as
explanatory variable. A study by Yusuf and Peter (1984, [61]) concluded that a one percent rise
in the interest rate was accompanied by an approximately one percent increase in gross national
saving; i.e. an interest elasticity of savings of 1 (Balassa, 1989, [5]). Several other studies have
concentrated principally on the effects of interest rate reforms in Korea, Taiwan and Indonesia,
where increases in bank deposit rates (along with increased load rates) have been accompanied
by sharp rises in savings deposits without dampening the business demand for loans. But this
may simply entail a redirection of savings and a change in the pattern of investment toward
more productive forms rather than an increase in the saving propensity.
Inflation is a good macroeconomic proxy for stability. Several studies proved different
results concerning the relationship between inflation and saving rates. Some studies analyzed
effect of inflation and savings showed a negative effect (Heer and Suessmuth (2006, [22])).
Haan (1990) in Heer and Suessmuth (2006, [22]) found that a rise of the inflation rate from
0%-5% decreased savings by almost 10%. However, proponents of positive relationship between
saving rate and inflation are more common. Based on precautionary saving theory, households
increase their savings whenever they feel threatened by the instability of the country»s economy.
As previously said, inflation is often used as a proxy for economic stability. Consequently, savings
85Is ACFTA Proper Strategy of Sustainable Poverty Alleviation?: Proof From The Depletion of Saving Rate
will increase whenever inflation is set at a higher rate. Deaton (1977, [14]) argued that unexpected
inflation caused involuntary saving because individual consumers were not sophisticated enough
to differentiate between relative price changes and absolute price changes. This lack of possible
means for individual customers to compare relative and absolute price changes would eventually
lead them to think that all goods are relatively more expensive; so that they choose to consume
less and save more (assume real income is maintained at same level). According to Deaton
(1977, [14]), as unexpected inflation rises, saving ratio also rises. Meanwhile, Howard (1978,
[27]) argued that inflation influences saving in two different assumptions. As long as the inflation
is unexpected, it will increase saving rate, since it creates pessimism about economic stability,
so that people are encouraged to save more. But if the inflation is expected (provided in advance),
it encourages people to increase their purchase of durable goods, therefore decreasing their
savings during inflationary period.
Modern consumption theory starts with the presumption that consumers like to smooth
out consumption over time, whether over the life cycle (Modigliani and Brumberg, 1954, [43])
or in the face of temporary fluctuations to income (the permanent income hypothesis of Friedman
(1957, [17])). Life cycle saving theory from Modigliani and Brumberg (1954, [43]) suggested
that consumers tend to smooth consumption over a lifetime. Modigliani and Brumberg (1954,
[43]) assumed in their model that savings would be high when incomes are high (during
productive working age), and people will dis-save during retirement. Life-cycle theory of saving
predicts a rise in saving as the youth-dependency ratio declines in the later stages of demographic
transition. Young-dependency ratio is regarded as a constraint for saving because children
charge a heavy expenditure for the working age population. Children contribute to consumption,
but not to production. That»s why high young dependency ratio is expected to impose a constraint
for saving (Leff, 1969, [37]). Leff (1969, [37]) found that dependency ratio significantly influence
aggregate savings. High dependency ratio is also used to evaluate the disparity between
developing and developed countries. Old-dependency ratio is also regarded as another constraint
for saving in the countries with no retirement plan. The elderly will be a burden for their working
children since they have no more income, or if the retired adult still should spend some expenses
for their young children. Both cases will be constraints for saving. Formally, if adults with fewer
children have more resources available over a lifetime, and these additional resources are
consumed by the adults themselves (rather than on children»s education for example),
consumption smoothing implies that consumption will also be higher after retirement, and
hence saving for retirement will have to be higher (Attanasio et al., (1999, [3]); Scholz et al.
(2006, [53]); Skinner (2004, [56])). Many studies find evidence of an impact of the youth and
old-age dependency ratios. For the youth-dependency ratio, Rijckeghem and Üçer (2009, [48])
estimated that a 1% point reduction in this ratio is associated with a 0.3 percentage point
86 Bulletin of Monetary, Economics and Banking, July 2010
increase in the saving rate in the short-run (0.5 percentage points in the long-run). The
corresponding are 1.4 and 2.8 for the old-age dependency ratio.
IV. METHODOLOGY
IV.1. Estimation Method and Model
We use Dynamic Panel Data (DPD) model to estimate the characteristic and the
determinants of saving. We assume that there are dynamic relationship between savings and
its lagged value. We define the lagged value relationship on current savings as the persistence
of savings over time. Savings are considered as persistent if the coefficient of the lagged value
approach 1, since it means that under the rest remains constant, savings tends to be constant
over time. However, if the coefficient is significantly different from 1, savings are considered as
not persistent, since the value will change over time, either increasing or decreasing, with the
rest remain constant. Savings is increasing if the coefficient is higher than 1, and reversely
decreasing when the coefficient is lower than 1. For this estimation, we use gross domestic
savings per capita to show individual savings, replacing household savings which cannot be
used due to unavailability of data for all ASEAN countries.
The main focus on this model is the import from ASEAN countries and China as the main
variable. We use ratio of net import from ASEAN countries and China from the total GDP for
estimation. Why net import while others use net export? The reason is to simplify the
interpretation so that we put import on our main focus in trade, nor the reverse. This variable
can be explained as the contribution of the ACFTA on the total GDP of ASEAN countries. The
main hypothesis is that import from ASEAN countries and China has negative impact on the
savings, which proves that an increase in the respective import will decrease the savings, due to
an increase in consumption. We are also going to compare the elasticity of import to the
persistency of savings to see whether under the ACFTA savings will be depleted over time,
indicating an increase of the poor»s vulnerability.
In order to acquire a more accurate, precise coefficient to compare, we insert more regressor
as control variables. Their role is simply as the explanatory terms which specify the model to get
more accurate coefficients, and also for a direction in applying it to the policy implications. The
control variables in the model are as follows:
1. The income of people, represented by the GDP per capita. An increase in people»s income
provides people with more funds to save. Therefore, the relationship is expected to be positive.
2. The economic growth, defined as the percent change of current GDP from the previous
year. An increase in economic growth, which expands the economy, increase the potency of
87Is ACFTA Proper Strategy of Sustainable Poverty Alleviation?: Proof From The Depletion of Saving Rate
economic activities and a rise in income per capita which has positive relationship with
savings.
3. The deposit interest rate. This is one of the pull factors for the people to save more since
interest rate reflects the rate of return for not holding cash in some periods. Though people
do not usually care for deposit interest rate, but the impact should be positive since rationally
people would aim for higher return. However, in the end, it depends on the opportunity
cost.
4. Price change or inflation. It has reverse effect from the interest rate, or we could call it as the
opportunity cost we have mentioned before. An increase in price level requires people to
hold more cash to consume even on the same volume of consumption. If the inflation rate
is higher than the interest rate, the opportunity cost of saving will increase and motivate
people to hold cash, and reversely. We could compare the elasticity of this variable with the
interest rate elasticity to gain a conclusion which is more important between interest rate
and inflation rate. We could expand the result into a policy implication, especially for the
monetary policy on interest rate and inflation.
5. Dependency Ratio. This is the only demographical indicator among those macroeconomic
indicators. The impact of this variable can be twofold. It is whether the increase of dependency
ratio will increase or decrease savings. Generally, we would expect negative impact since an
increase in dependency ratio will increase current spending, leaving the savings being depleted
currently. However, a forward-looking paradigm might exist where an increase in dependency
ratio will motivate people to prepare for this dependent people»s needs in the future, like
school or health.
ittititi
titititi
DEPENDINFLINTR
GROWTHINCOMEIMPORTSAVINGSSAVINGS
εβββ
βββα
++++
+++= −
,6,5,4
,3,2,11,
where,
SAVINGS is savings per capita
IMPORT is ratio of net import from ASEAN-China countries from total GDP
INTR is deposit interest rate
INFL is inflation rate (based on CPI)
DEPEND is dependency ratio
i is individual, consist of ASEAN countries3
t is yearly time dimension
3 Note that we exclude China from the panel estimation since we assume that China bears more benefit under this ACFTA, whileASEAN»s developing countries hold more risks of losses.
88 Bulletin of Monetary, Economics and Banking, July 2010
IV.2. Data
We estimate it using panel data of all ASEAN countries from 2000 to 2008. Since ACFTA
has not been imposed for long, we use historical data to predict the impact of ACFTA in the
present and the future. We receive data for savings per capita and import from United Nations»
UNSTATS and UNCOMTRADE. For interest rate and inflation, we use data from IMF»s International
Financial Statistics (IFS) and for dependency ratio we use data from CEIC.
The DPD methodology that we use for this model is Arellano-Bond 1st Difference GMM
due to the following reasons:
1. Relationship is existed within savings and its lagged value.
2. We assume that there are dynamic relationship within savings and economic growth, as
explained in Mohan (2006, [45]), also with the interest rate and inflation.
3. The unobserved country-specific error term (wi) in terms of demographical indicators are
correlated with the dependency ratio.
4. The country numbers as cross section data (N = 10) is relatively higher than the number of
time series. (T = 7).4
Now that we have several problems arises above, we are obliged to eliminate the problems,
which are solvable using the Arellano-Bond GMM. The Arellano-Bond GMM itself is an estimation
methodology to observe the effect of dynamic relationship between the dependent variables
and its lagged value. As for the endogeneity problem, we impose instrumental variables on the
GMM. For instrumental variables imposed in this model, we put the lagged value of the
endogenous regressor (growth, interest rate and inflation)
The third problem, correlation of unobserved country-specific error term is eliminated
using the first difference in Arellano-Bond GMM following this formula:
4 Since Arellano Bond GMM use first difference and we put first lag of savings on the model, the estimator is automatically drop twofirst observation, therefore the remaining time observation is 7.
where,
then,
wi is the unobserved country-specific error term. As we can see from the equation above, we
have eliminated the unobserved country-specific error term using the first difference term.
∆yi,t
= α1∆y
i,t-1 + α
2∆X
i,t + ∆
i,t
yi,t − y
i,t-1 = α
1 (y
i,t-1 − y
i,t-2)
+ α
2 (X
i,t − X
i,t-1) + (
i,t −
i,t-1)
i,t = w
i + u
i,t
i,t −
i,t-1 = (w
i − w
i,t)
+ (u
i,t − u
i,t-1) = u
i,t − u
i,t-1 = ∆u
i,t
89Is ACFTA Proper Strategy of Sustainable Poverty Alleviation?: Proof From The Depletion of Saving Rate
Therefore, the error term remains is vi,t which is panel data error term from the estimation.
Hence, we should worry anymore about this correlation between errors and the independent
variables since the problematic unobserved country-specific error term has been eliminated
from the estimation.
V. RESULT AND ANALYSIS
Using Arellano-Bond GMM in two-step estimation from Stata 11, we acquire the following
result:
Coef. (Std. Error) [Prob.]
Saving (-1)Saving (-1)Saving (-1)Saving (-1)Saving (-1) 0.1439227* 0.149482** 0.5340291***(0.0605343) (0.0697293) (0.0995964)
[0.022] [0.032] [0.000]ImportImportImportImportImport -5.13867 -6.781835*** -3.844283
(5.173365) (1.697932) (5.063839)[0.326] [0.000] [0.448]
IncomeIncomeIncomeIncomeIncome 0.6441702*** 0.6125879*** 0.2395092***(0.0509349) (.0662613) (0.0486907)
[0.000] [0.000] [0.000]GrowthGrowthGrowthGrowthGrowth 1.540742 10.84045 12.7541**
(3.339246) (19.5483) (6.328766)[0.647] [0.579] [0.044]
IntrIntrIntrIntrIntr 2.08293 40.2688 14.3462(10.82252) (41.9624) (12.91631)
[0.848] [0.337] [0.267]InflInflInflInflInfl -1.352008 -6.455056 3.970357
(2.637306) (8.411291) (4.28696)[0.611] [0.443] [0.354]
DependDependDependDependDepend 4.962723 12.66345* 4.704166(5.290578) (7.258577) (3.515673)
[0.354] [0.081] [0.181]
FE GMM OLSVARIABLES
*** (**) [*] significant under 1% (5%) [10%] critical value
ContinuumContinuumContinuumContinuumContinuumFE 0.1439227 UNBIASEDUNBIASEDUNBIASEDUNBIASEDUNBIASED
GMM 0.149482OLS 0.5340291
ValidityValidityValidityValidityValiditySargan 1.000000 VALIDVALIDVALIDVALIDVALID
ConsistencyConsistencyConsistencyConsistencyConsistencyM1 0.4301 INCONSISTENTINCONSISTENTINCONSISTENTINCONSISTENTINCONSISTENTM2 0.4489
GMM POST-ESTIMATION ΩΩΩΩΩ
90 Bulletin of Monetary, Economics and Banking, July 2010
First, we are going to see the post-estimation. The continuum indicates that lagged value
coefficient in GMM (Arellano-Bond First Difference) is slightly higher than Fixed Effect estimation,
while the OLS»s coefficient is significantly higher than the GMM, which makes sense since OLS
usually provides us with a somewhat excessively high coefficient. Therefore, we receive unbiased
estimators in this model due to the continuum condition.
The Sargan test shows us that there are no correlations between the residuals and the
over-identifying restrictions of instrumental variables if they are truly exogenous. In this case,
this might be because we do not put any instrumental variables in our estimation. Therefore,
we should not worry about the validity of our model, since the Sargan Test shows us good
result.
However, the Arellano-Bond test indicates that there is no autocorrelation in M1 which
makes the estimators to be inconsistent, but the bright side is that there is no autocorrelation
in M2, since if otherwise, the estimation would be completely inconsistent. We have done
many statistical engineering on the variables as well as adding and dropping variables or changing
their definitions, yet this is the best outcome we could have in terms of p-value of M1. Moreover,
since this is our basic model, therefore, we decided to use this model as our estimation.
Now, we are going to compare the results between the three methodologies before we
emphasize the whole result of Arellano-Bond GMM. The key variables, Import, have negative
impact in all of the three, which means that this negative correlation is not due to the utilization
of DPD in our estimation. The differences between methodologies are located in the difference
of coefficient measurements. It happens not only in the key variable, but also in the control
variables. The regressor does have same relationship in all of the methodologies, except one for
the inflation in OLS. While difference methodology might provide us with significantly different
relationship, our model here provides us with similar results. Therefore, as we said before, we
should not worry about the distortion of estimation result due to the difference of methodology
and the existence of control variables.
The next step is to emphasize the Arellano-Bond results. The import has negative
relationship to savings just like our hypothesis stated. It means that if savings will be depleted
under increasing import. While import has negative relationship, the estimation shows that
savings is not quite persistent over time to hold the waves of import which will devour savings
in the process over time. The savings is considered as not persistent since the dependent lagged
value»s coefficient is significantly lower than 0, precisely 0.1779878. It means that under the
rest remains constant, the savings are going to deplete continuously, even without increase in
imports. Both dependent lagged value and import are significant under 5% critical value which
means that their impact is consistent over time.
91Is ACFTA Proper Strategy of Sustainable Poverty Alleviation?: Proof From The Depletion of Saving Rate
Now for the control variables, only income per capita and dependency ratio which is
significant under 5% critical value, while the remaining is not significant. Income per capita has
positive relationship with savings which means that an increase in income per capita will increase
the savings. Economic growth also encourages people to save since it has positive relationship
with savings. So does the interest rate. An increase in deposit interest rate brings positive
impact on the motivation of people to save. While lastly, as expected, inflation holds negative
impact on the savings since people have to hold more money.
The estimation has provided us with the required information on how import affects the
saving rate along with other macroeconomic and demographic explanatory terms. We are
going to focus more on how the regressors affect the dependent variable. Significance does
matter but even for the insignificant variables, we are still analyzing the impact of the regressor
since we can still consider the coefficient as the tendency of how the variables affect the
dependent variable.
V.1. The Savings Behavior in ASEAN
We consider the estimation result as a behavior model of savings in our specific region,
ASEAN, under flowing trade of goods within ASEAN and China. Let us recall the estimation
result of Arellano-Bond GMM for analyzing purpose.
The lagged dependent variable»s coefficient shows us the persistency of savings per capita
over time, ceteris paribus. It indicates the behavior of people to keep their savings over time in
condition where the rest remain constant. The coefficient value of lagged dependent variable is
significantly below 1.00, precisely 0.15, which means the saving per capita would decrease by
85% over time. It indicates that people will draw their savings in high proportion in order to
fulfill both their needs and wants. If we take wants into account, since needs are basic goods
that cannot be eliminated from routine consumption buckets, we could expect people tend to
become consumptive since they consume goods outside basic needs which along with the
basic needs consumption, it depletes the saving per capita by 85%. Recall that we assume the
rest remain constant, so that it means there is no adjustments of consumption under price
changes; therefore the coefficient shows only the depletion series of saving rate. Based on this
estimation, we take a simple and quick conclusion that ASEAN people weigh more on
consumptive behavior, which is a behavior that can be found in developing countries, recall
that most of ASEAN countries are developing countries.
The net import has negative impact on saving rate. It means that an increase in the
import over the export level will deplete the consumption. This is just like our hypothesis
92 Bulletin of Monetary, Economics and Banking, July 2010
stated earlier in this paper. An increase in import level, while export remains constant, will
reduce people»s savings. This is due to the increase of consumption under the increase of
goods availability in economy. As estimated before in the coefficient of saving»s lagged value,
ASEAN people tend to consume more over time in such a high proportion of 85%. This data
is estimated before the ACFTA being implemented in ASEAN (ACFTA was started in January,
2010). Therefore, we can expect that under ACFTA, the flow of goods will surely become
high as the import on ASEAN countries increases; the consumption pattern of ASEAN people
would increase. If the other variables assumed to be constant, the savings would be decreased
to nothing in a short time. But, this is not without solution. The answer for it lies on the half-
side of net import, which is the export side. The export here acts as the counter-effect of the
import that reversely will increase saving rate. This logic comes from the formula of Net
Import, which is the subtraction of import with the export. An increase in export would
decrease the net import. Therefore, the export has reverse effect from the import. An increase
in export would let people to produce more products, allowing them to gain more income
from the economic activity. For another simple explanation, the export is an additional
component of GDP, so an increase in export would increase GDP and bear the potential of
increasing income per capita.
Speaking of income per capita, the estimation shows us that the income per capita has
positive effect on the savings, and moreover has positive impact. The coefficient of this variable
is 0.61. The implication of this coefficient is that ASEAN people would provide 61% of their
income change for saving and use up to 39% of it to consume. It could also work on the
reverse, when the income per capita reduced, people will draw their savings by 69% of their
income change, since they need more liquidity to consume needs under decreasing income,
probably under recession or crisis. This is also one of the answers to endure the impact of
ACFTA that is in line with export solution. Income is surely an important component to improve
if we are aim to increase or keep savings from the community. As discussed before, export is
one of the components of GDP and income, which means that export, needs to be one our
vital solution to increase people»s income.
We might think that there is some inconsistency inside this estimation analysis. At first,
we thought that people tend to become consumptive since the persistency of savings is very
low. But, reversely, the income per capita»s coefficient shows that people distribute more of
their income change to the savings, rather than to consumption. One point that we need to
see is that the consumptive behavior we analyze first is under the assumption where the income
is constant. With constant income over time, people tends to deplete their savings to consume
more and this might be because of the insufficiency of income for ASEAN people, especially
93Is ACFTA Proper Strategy of Sustainable Poverty Alleviation?: Proof From The Depletion of Saving Rate
those who live in developing countries, to fulfill their needs and wants. Therefore, people keep
on drawing their savings to fulfill their needs and wants.
For the income change that is allocated more to the savings, the explanation might lie
within the estimation of dependency ratio parameter. The dependency ratio has significant
positive impact on saving rate. It can be explained through precautionary saving behavior theory,
but this time we relate the instability discussed in the theory to high expense that the productive
groups bear. More people depend on the productive age; more funds will be needed to prepare
for future consumption. One simplest example is for children who are still enrolling on school
or university. The parents who are in productive population must allocate more of their income
for their children educational plan. This is also shows that most of ASEAN people are a risk-
averse kind of people when they have more people under their care. However, this is not to be
proud of, since this variable only explains why people allocate more of their income change for
saving. We cannot use this variable as our hope to increase savings. Increasing dependency
ratio is surely not an answer to keep the savings rate; it is just an explanatory term.
The remaining variables are not significant; however we are still going to analyze the
insignificant impact to see the potential impact these variables can do for the saving rate.
Growth has positive impact which means that the expansion of the economy could provide
people with opportunity to increase income and furthermore the saving. This is due to rapid
growth of population that usually happens in ASEAN as a region of developing countries. An
increase in growth itself might not affect the saving rate since it might not increase the individual
income of the people. If the economic growth is not as fast as the population growth, then
basically the income per capita, our significant variable, will be decreased. That is why growth
is not significant in affecting the saving rate.
Deposit interest rate will increase saving rate since it is a proxy of return if depositors save
their funding on banks. An increase in return would encourage people to save more, in hope to
gain more return from the interest. Interest rate is not significant because return on saving is
not quite encouraging for most people. This is because most people which have only regular
income would not save huge amount of money, like about billions Rupiah. This interest rate
would not provide them with significant return if not invested in more than hundred billions
Rupiah. Since most people only save up to millions Rupiah, the potential return would not be
that encouraging for them to save more.
Reversely, inflation has negative impact on the saving since under high price, people have
to consume more in terms of value, not the quantity. Therefore, they have to reduce saving in
order to adjust their money allocation on the increasing price to consume needs in the same
quantity. The reason why this variable is not significant is because people might have more
94 Bulletin of Monetary, Economics and Banking, July 2010
proportion on wants in their consumption rather than basic needs. If people consume more
basic needs they will adjust their savings to keep them being able to consume this basic needs.
But, if people consume wants in high proportion, when price increases, they can just decrease
their consumption on these wants to keep them being able to access basic needs. This is
because wants is a normal goods which the quantity demanded will decrease if the price
increase, while basic needs is an inferior goods which the quantity demanded will only be
adjusted under the change of income (price does not matter). Therefore, under high proportion
of wants consumption, high inflation can still allow people to reduce their normal goods
consumption so that they can keep more of their savings.
Usually we will compare the coefficient of these two variables to see which one has more
impact on the saving rate, but unfortunately these two variables are not significant. We cannot
compare the parameter estimated in this model since the coefficient might not work like stated
in the estimation. Therefore, we are not going to put them on our focus of our policy
recommendation. But, we must keep in mind that these variables might have these impacts in
the future which can be potential tools in the future.
V.2. ACFTA and The Poverty Allevation Strategy
Our estimation on import concludes that import is not an appropriate answer for
sustainable poverty alleviation. While we might think that this trade openness could increase
people»s access to more goods and services which in terms of Expenditure Poverty, the poverty
rate would be decreased even though the income of people does not change, we missed one
point where these expenditures could be quite bothersome in the future. This is due to the
depletion behavior the savings bear under the increasing of imports. Therefore, this depletion
of poverty rate might be a temporary one since it depends on the availability of goods from
abroad. We can expect that if one day a shock would occur, and the flow of trade needs to be
halted, the availability of goods would be depleting and therefore the poverty rate would be
re-bounced. Moreover, under the depletion of savings, people (especially the poor) would not
be prepared to adjust their income to overcome the increasing price due to the decreasing
quantity supplied. This is where our key variable, savings, enters to become the buffer for these
people for future risk preparation. The potency of savings depletion is the reason why we
conclude that the ACFTA is not an answer, or a proper strategy for poverty alleviation, even if
in the other hand it could boost economic growth.
The estimation shows us that this ACFTA is probably a big disadvantage for sustainable
poverty alleviation strategy. However, the ACFTA has been implemented and is progressing for
95Is ACFTA Proper Strategy of Sustainable Poverty Alleviation?: Proof From The Depletion of Saving Rate
months up until now. It is impossible to suddenly alienate the agreement in this moment, and
probably for long time to the future. In addition, it is not like that the ACFTA is completely
malice for ASEAN countries since, in fact; it provides us with various opportunities, even for
poverty alleviation. The most important thing is how to make use of these opportunities to
provide us with enough savings so that sustainable poverty alleviation could be achieved.
Based on our estimation, the most important variable to increase saving rate is the income
per capita. It means that the key on expanding people»s savings lies on how we harness the
potentials of trade openness in ACFTA to increase income per capita. The lifting of tariff barriers
across ASEAN and China for trades must not be used to increase our domestic availability of
goods so that people could easily access goods since that would be our disadvantage in terms
of savings. We must take advantage of this agreement to improve our export side so that we
could increase income per capita. The estimation shows that in reverse of the negative impact
of import on saving rate, the export does have positive impact since net import is the subtraction
of import by export. Increase in export means that the productive side of the economy is
progressing since the increase of GDP is the result from the productions rather than solely
consumptions. Moreover, the increase in export employs more people to increase the output,
so the income of the people could be improved due to the increase of employment or the
potential of increasing wage due to the increase in output growth.
Therefore, the government should support the export side to overcome the ACFTA
challenges. This can be done by providing facilities for producers, especially the export-oriented
ones, to produce more goods which can be potentially circulated in ASEAN and China. Export
subsidy would be one of the solutions to promote export however it could be distortive on
international price that is avoided in the free trade agreement.
Commodity-imported control might be better than the export commodity. However, the
commodity-imported control we talk about here is not how we limit the goods imported to our
country. It is about how we counterbalance the flow of consumption goods with the imports of
raw materials required for export-oriented industries. As we stated before, under free trade
agreement, we can expect cheaper goods even for the raw materials. We must view this as an
opportunity to access cheaper raw materials in order to increase productivity and impose a
more competitive price for our export commodities. This way, we can improve our export side
without sacrificing the import side which is required for maintaining availability of goods. The
solution provides us with income side and expenditure side of poverty alleviation.
Price stabilization is also required expand people»s saving. The price needs to be stabilized
in low condition. This is a concern for central banks to achieve this condition. How can this
price stabilization be important for this? The reason is twofold. First is that high domestic price
96 Bulletin of Monetary, Economics and Banking, July 2010
is one of the factors which determines the motivation to trade. Any basic trade theorems as
explained in textbooks like Markusen, et al (1994, [40]) and Krugman and Obstfeld (2006, [35])
emphasized the role of price relativity in the trade creation. Exporters would like to export their
goods if the goods» price at the partner country is higher than the price in their country, assume
that there is no dumping policy. This is due to the potential of capturing more profit from the
trade since they can sell at a higher price. Increase in domestic price will flood the domestic
market with imported goods which aim to be sold at higher price. It would result on the
increase of consumption which is what we avoid in ACFTA. Moreover, the price itself is also the
determinant of exchange rate since they are both related to the currency»s purchasing power.
High price means weaker exchange rate and the reverse. By maintaining price at low level,
exchange rate can stay at strong level which is encouraging for exporters to export more.
Second, the price level is also a motivation for people to hold liquid money than to save.
This is because the increase in price means that the people are required to expend more even
for the same level of consumption. High price would put savings at disadvantage. In addition,
price fluctuations would be even worse. This is due to the uncertainty that the people face so
that they begin to be more preserve on the economic condition. In that case, no matter high or
low price the economy has, people would not be motivated to save.
Therefore, simply a low level of price is not sufficient to draw people to save, not only
because that fluctuations will increase uncertainty, but also the low price and strong currency
might decrease our export commodities» quantity demanded from partner countries which is
detrimental if we are aiming to improve saving potential through export promotion. A stable
price in relatively low level is more appropriate than only a low price condition. This might also be
the reason why on the estimation before, the inflation rate was proved to be insignificant. It
might be due to the additional uncertainty component that determines savings along with inflation.
Lastly, the other opportunity that the government needs to utilize is the possibility of more
direct investment that the ACFTA could provide. We must not forget that ACFTA is not solely an
agreement for trades for goods and services, but also for an increasing opportunity for more
foreign direct investment (FDI). The question mark that might arise from this recommendation is
probably how can this FDI increase saving rate since the transmission mechanism might be quite
long, but it is possible to utilize the mechanism. The FDI can open more job opportunity to
employ more domestic workers. This will increase the employment side so that people»s income
can be raised. Moreover, if we impose this FDI more at the export-oriented industries, we could
improve the productivity of the industries, allowing them to export more to expand our income
per capita. In the end, again, the FDI is a mechanism to expand our exports and income per
capita since it is considered as our key variable here to increase saving rate.
97Is ACFTA Proper Strategy of Sustainable Poverty Alleviation?: Proof From The Depletion of Saving Rate
We might be considering that increasing productivity of export-oriented products
excessively might be detrimental for us if crisis and recession occur in the region. Under crisis
and recession, the purchasing power of our partner countries might be reduced and the trade
activity would be frozen temporarily. This will create a big shock to our economy since our
export side will be devoured by the decreasing import demand to partner countries. It is indeed
something that we must be cautious for, but at the same time, this is something that our
demographical advantage takes into account.
Most of ASEAN countries have great population, especially Indonesia that has population
of approximately two hundred million people. This is a demographical advantage for ASEAN,
since they have an abundant domestic market for times when the foreign demand is depleting.
Moreover, by increasing saving rate, we have provided our people with enough purchasing
power in times like this which, in fact, is what the saving rate»s role from the beginning. So,
countries like Singapore which rely so much on trade, while at the same time does not bear the
great population advantage, can still survive the recession due to the mountains of saving they
have provided in the first place to overcome ACFTA. It is not only working for small population
countries, but also on the other ASEAN countries as well. Therefore, we are not going to suffer
great increase in the number of poverty, as we are afraid of in the beginning.
The policies stated above need a good coordination and cooperation between the
government and the central bank. The central bank is in charge of the price stability task, while
the government is in charge of the real sector policies that improve the export directly. This
cannot be completed well without a good cooperation from both parties. This way, the saving
rate can be maintained for people»s buffer against future shocks that could throw more people
into poverty, resulting in an overshoot of poverty rate. Keep this in mind, that we are not
rejecting ACFTA with this research. Reversely, we view this as an opportunity to support the
poverty alleviation strategy. However, the ACFTA itself is not a proper strategy for sustainable
poverty alleviation since the impact on the poverty alleviation is only on the short run. Despite
of it being an inappropriate strategy, the ACFTA provides us with opportunity to expand the
sustainable poverty alleviation strategy. The authentic proof of this is how the ACFTA can be
taking into advantage as the policy recommendation we emphasized above. ACFTA is not
something we must afraid of. It is an opportunity that we must look at the bright side.
VI. CONCLUSION
This paper has proved that, despite of being an effective growth engine as practitioners
emphasized, there is potency that regional free trade like ACFTA might be detrimental, in
98 Bulletin of Monetary, Economics and Banking, July 2010
some ways, for developing countries in ASEAN, especially for sustainable poverty alleviation
strategy.
Depletion of the saving rate is something that we propose in this paper. Saving rate, as a
shock buffer for the poor under recession, is an important part of sustainable poverty alleviation.
The estimation has proven that import from ASEAN and China impacts on the depletion of
savings for ASEAN countries. This is due to the increasing circulation of goods in the region that
allows people to access goods easily, accommodating the consumptive behavior that a developing
countries» population bear. In addition, the saving rate itself in ASEAN is not a persistent being
since when the rest remain constant; it will deplete itself gradually due to the continuous
consumption.
Developing people»s income per capita is the key solution if we want to successively
overcome this challenge. Estimation proved that people still tend to save when they get extra
income. This is the important point that we must take into advantage. Under this circumstance,
unable to severe the ties of ACFTA no matter how detrimental it is, governments of ASEAN
countries must increase its people»s income per capita using the opportunity that ACFTA provides.
There are four policies recommendation that we emphasized in this paper. Those are: (1)
Counterbalance the import wave that ACFTA brings by promoting exports, since the barriers
have been gradually lifted, across the ASEAN and China, in order to boost income per capita;
(2) Controlling the commodities exported to our market, focusing more on raw materials import,
to avoid over-consumptive behavior on consumption goods and increasing the productivity of
domestic industry, especially the export oriented industry; (3) Stabilize the price fluctuations to
encourage people to save more and strengthen the currency»s purchasing power so that exporters
are encouraged to export more and the import waved can be endured; and (4) Promoting
foreign direct investment to boost employment and increase the productivity of export oriented
industry. These policies must be done under good cooperation and coordination by government
and central bank.
We do not reject ACFTA in this paper; we view ACFTA as an opportunity to develop
ASEAN even more. It is reflected by our recommendations. Despite that we stated ACFTA as
detrimental in some ways, used ACFTA as the vessel to increase saving rate to counterbalance
the depletion impact of it to saving rate. In conclusion, ACFTA itself is not a proper strategy for
poverty alleviation if we leave it as it be, but can still be utilized to support sustainable poverty
alleviation strategy with the authentic opportunity it can provide. ACFTA is not something we
must afraid of. It is an opportunity that we must look at the bright side.
99Is ACFTA Proper Strategy of Sustainable Poverty Alleviation?: Proof From The Depletion of Saving Rate
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103Making East Asian Regionalism Works
1 Earlier version of this paper has been presented on the International Conference on Business and Economics held in Bukit Tinggi,Indonesia (April 2010) and Thessaloniki, Greece (May 2010)
2 Graduate School of Asia-Pacific Studies (GSAPS), Waseda University 1-21-1 Nishi-Waseda, Shinjuku-ku, Tokyo 169-0051, JAPANE-mail: [email protected]
MAKING EAST ASIAN REGIONALISM WORKS1
Fithra Faisal Hastiadi 2
A b s t r a c t
For the past few years, regionalism has been progressing in East Asia with the likes of China,
Japan, and Korea (CJK) as the most prominent actors. Unfortunately, with the absence of trade arrangement
amongst the CJK, the present regional trade scheme is not sufficient to reach sustainability. This paper
uncovers the inefficient scheme through Engle-Granger Cointegration and Error Correction Mechanism.
Moreover, the paper underlines the importance of triangular trade agreement for accelerating the phase
of growth in CJK which eventually create a spillover effect to East Asia as a whole. Employing Two Stage
Least Squares in a static panel fixed effect model, the paper argues that the spillover effect will function
as an impetus for creating region-wide FTA. Furthermore, the paper also identifies a number of economic
and political factors that can support the formation of East Asian Regionalism.
JEL ClassificationJEL ClassificationJEL ClassificationJEL ClassificationJEL Classification: F15, C13, C22, C33
Keywords: Regionalism, Engle-Granger Cointegration, Error Correction Mechanism, Fixed Effect, Two
Stage Least Squares
104 Bulletin of Monetary, Economics and Banking, July 2010
I. INTRODUCTION
In this new millennium, regionalism has begun to emerge in East Asia. East Asian Countries
have been focusing on ways to expand intra regional trade that include: the establishment of
Regional Trade Agreements (RTAs) in the form of Free Trade Agreements (FTAs) and Economic
Partnership Agreements (EPAs). The trend towards regionalism has created a profound regional
and indeed global significance (Harvey and Lee, 2002). Japan, Korea and China are regarded as
the key actors for such action in East Asia.
Being acknowledged as the economic front runners, Japan, China and Korea are assumed
to have heavy responsibility for the economic welfare in the East Asian region. It is very obvious
that East Asian regionalism cannot be put into practice without these countries» strong support.
Unfortunately, the lack of institutional arrangements among these giant countries has stalled
the overall welfare effect for the East Asian communities. The present driving force of the
China-Japan-Korea (CJK) relationship is the market by which in some sense is not enough; it
should be matched by regionalism. The main focus of the regionalism is to make these countries
grow together so that it can spread positive externalities throughout the East Asian region. In
the long run it is expected that CJK will lead regionalism in East Asia.
The remainder of the paper is organized as follows. The second section studies the
economic structures and trade patterns in the CJK. The third section examines the effect of
openness in the CJK to economic growth in these particular countries. The fourth section
analyzes the prospects of the CJK increased welfare in creating spillover effect to ASEAN4,
which in this paper serves as a proxy for ASEAN countries. The fifth section presents the future
trend and path towards East Asian Regionalism, and finally the last section presents some
concluding remarks.
II. REVIEW ON JAPAN, CHINA AND KOREA ECONOMIC RELATION
Tracing back the relations since the post war era, economic ties between Japan, Korea and
China has evolved in somewhat gradual ways. The evolution of trade activities emerged from the
likes of China, which has a substantial transformation of trade structures. In the early 90»s, primary
commodities accounted for more than one third of China»s total export to Japan and Korea. In
this new millennium, it is still top Chinese export to Japan and Korea, but it is persistently followed
by the fast growth of machinery and transport (Chan and Chin Kuo, 2005). From this point of
view, trade within the north East Asian region is deemed to have substantial movement as a
result from the shift of trade towards a more industrialized structure. The emergence of China as
a regional manufacturing center is a dominant factor that contributes the trade shift.
105Making East Asian Regionalism Works
The overall picture of the trade amongst these countries is described in Diagram V.1. It is
clear that trade activity is very intense by which performs as the major contributing factor for
economic growth in the region. The vast amount of trade has been very likely steered up by the
amount of FDI flows among them with Japan as the sole leader of it (Diagram V.2). In other
words, the creation of economic transformation in China and Korea that geared up the trade
was enchanted by Japan»s role in making investment in those countries.
Diagram V.1.Trade among Japan, China and Korea (2006, $Billion)
Diagram V.2.Investment among Japan, China and Korea (2005, $Billion)
Source: Watanabe (2008)
China Korea
Japan
118.5
92.9
27.3
50.3
44.5
87.7
China Korea
Japan
6.57
0.18
1.74
0.013
2.61
0.012
Source: Watanabe (2008)
106 Bulletin of Monetary, Economics and Banking, July 2010
To some extent, trade is almost synonymous to a country»s welfare. More specifically,
some research pointed out export as an engine of economic growth. From this stand point, it is
important to measure export sustainability to the economy, which in this section export among
the CJK become the main focus.
As already explained earlier, Japan, China and Korea are experiencing golden period in
doing export among them. Economic welfare is the most notable goal which links in this activity,
but is it sufficient to boost the economy in the long run? A pure market driven activity without
specific regional trade agreement might sometime create bias. It is clear that Japan, Korea and
China are lacking of such agreement among them (Urata and Kiyota, 2003) as described in the
table V.1.
To make an effective regionalism, Japan, China and Korea should support each other.
Therefore, intra regional cooperation within the CJK must take place by which can create
sustainable growth in East Asian region. The following sections serve to prove export sustainability
to economic growth, in the absence of trade arrangements, for the short and the long run.
Engle-Granger Cointegration and Error Correction Mechanism test are then employed for this
cause. This test employs time series quarterly data of GDP and for Japan, China and Korea
ranging from 1985 to 2004. The data is taken from CEIC database.
In doing Engle Granger Cointegration test, this paper divides the export relationship in to
three parts which are described in the following equations:
Table V.1Japan, China and Korea FTAs/EPAs
Countries Situation
China
Korea
Japan
Concluded
Under Negotiations
Under Considerations
Concluded
Under Negotiations
Under Considerations
Concluded
Under Negotiations
Under Considerations
Countries
Chile, ASEAN, Hong Kong, Macao
NZ, Australia, Pakistan, Singapore, GCC, SACU
Iceland, India, Japan-Korea-China, FTAAP, Switzerland
Chile, Singapore, EFTA, ASEAN, USA
India, Mexico, Canada, EU
FTAAP, China, Mercosur, NZ, South Africa, Japan-China-Korea,
Australia, GCC
Singapore, Mexico, Malaysia, Philippines, Chile, Thailand,
Brunei, Indonesia
India, Vietnam, Australia, Switzerland, Korea, GCC, ASEAN
FTAAP, Japan-China-Korea, South Africa
Source: Japanese Ministry of Economy, Trade and Industry, 2007
107Making East Asian Regionalism Works
In these equations, JPGDP, CHGDP and KRGDP are Japan»s GDP, China»s GDP, and Korea»s
GDP respectively while Export JP, Export CH and Export KR are the variables of export destinations
to Japan, China and Korea. It would be possible to cointegrate Export and GDP since the trend
in export and GDP would offset to each other, creating a stationary residual. The residual is
called a cointegration parameter. In the data, if we find that the initial regression of the residual
(ut) gives stationarity it means that ut is stationary at order 0 (level) and it is notated as I(0). But
if ut is stationer in first difference, the variables of Export and GDP will be cointegrated in the
first difference which can be notated with I(1).
Table V.2Cointegration Parameters
Dependent Variable GDP (Japan) GDB (China) GDB (Korea)
Independent Variable
Export to Jepang na Stationer Stationer
Export to China Stationer na Stationer
Export to Korea Stationer Stationer na
From table V.2 we can see that, GDP and export relationship in the CJK yields stability in
the long run. It is proven by the stationarity of the error term in each of the cases. The
cointegration test that proves long run equilibrium describes that the model is not spurious.
(V.1)JPGDP = βo + β
1 .ExportCH + µ
t
(V.2)CHGDP = βo + β
1 .ExportJP + µ
t
ii. Korea and Japan Export Relationship
(V.3)KRGDP = βo + β
1 .ExportJP + µ
t
(V.4)JPGDP = βo + β
1 .ExportKR + µ
t
iii. China and Korea Export Relationship
(V.5)CHGDP = βo + β
1 .ExportKR + µ
t
(V.6)KRGDP = βo + β
1 .ExportCH + µ
t
i. China and Japan Export Relationship
108 Bulletin of Monetary, Economics and Banking, July 2010
Export is proven to be the engine of economic advancement in these countries. It approves
some previous research as the likes of Dorasami (1996), and Ekanayake (1999) of export and
economic growth relationship.
We have seen the long run relationship between Export and GDP. However, in order to
make it objective, we should also see the short run since it is still plausible to perceive
disequilibrium. Thus, could be noted as equilibrium error. This error then could be used to
relate the behavior of the short run Japanese GDP The technique to correct short-run
disequilibrium to its long run long run equilibrium is called Error Correction Mechanism (ECM).
The model of ECM is as follows:
(V.7)∆GDP_X = βo + β
1 .∆Export_Y + β
2.µ
t-1 + e
t
µt-1
is a cointegrated error lag 1, or could be noted mathematically as:
Ut-1
= GDPCountry Xt-1
- βo - β
1 ExportCountryY
t-1 (V.8)
In this equation, ∆GDPCountry X is the difference in GDP for Japan, Korea and China,
while ∆ExportCountry Y is the difference in export from country X to Country Y. As for
example, applies for the effect of Japan»s export to China on Japan»s GDP. From the above
model we can see that the long run relation between Export and GDP in Japan, China and
Korea would be balanced by the previous error. Below is the output for each country»s regressions:
i. Japani. Japani. Japani. Japani. Japan
In the short run, there is an equilibrium error for Japan»s Export to China with its relation
to Japan»s GDP. The coefficient of residual gives negative sign (-0.18), which means that Japan»s
Export to China is below the long run equilibrium. This will only lead to a rise of export for the
Tabel V.3Equilibrium Errors
Dependent Variable
Independent Variable
Equilibrium error for Export to Japan na -1.0 9 *** -0.23 *
Equilibrium error for Export to China -0.18 *** na -0.48 ***
Equilibrium error for Export to Korea 0.017773 -1.33 *** na
Note: Statistical significance is indicated by *(10%), **(5%), and ***(1%)
GDP (Japan) GDP (China) GDP (Korea)
109Making East Asian Regionalism Works
following periods. But it is important to note that the absolute value of the coefficient (adjustment
rate) is very small (0.18). This suggests that Japan»s Export to China is moving in a slow phase to
reach the long run equilibrium.
As for the relationship between Japan and Korea, the equilibrium error of the export
trend is not significant. These suggest that Japan»s GDP is adjusting to the change in Japan»s
export to Korea in the same period of time. In other words, Japan and Korea relationship in
terms of export has already reached steady state level.
ii. Chinaii. Chinaii. Chinaii. Chinaii. China
The residuals for the relationship between China»s GDP with China»s Export to Japan and
Korea are significant. These suggest that there is an equilibrium error in the short run. The
negative signs put the Export for a constant rise to reach the long run equilibrium. In China»s
case, the adjustment rate or the phase of acceleration for the long run equilibrium is very fast.
It can be seen through the absolute value of the equilibrium error coefficients which are 1.09
and 1.33 for China»s relationship to Korea and Japan respectively.
iii. Koreaiii. Koreaiii. Koreaiii. Koreaiii. Korea
Korea»s case is somewhat similar to China. The residuals for the relationship between
Korea»s GDP with Korea»s Export to Japan and China are significant. It yields similar explanation
with China»s case. However, the adjustment rate for the case of Korea is slower than China»s
but it is still faster than Japan»s. It gives the absolute value of 0.23 and 0.48 for Korea»s trade
relationship to Japan and China respectively.
From the ECM, we can conclude that North East Asian region is not moving at the
same phase to reach the long run equilibrium, which in this case Japan is the slowest one.
The insignificant value of acceleration rate for the case of Japan trade relationship with Korea
is also important point to note since it can be interpreted as an exhausted Korean market for
Japanese products (steady state condition). These facts are very crucial since it diminishes
Japan»s role as the sole leader in the north East Asia. Although whoever the leader is not to
important, but the stalled effect of a country»s economic growth in these region will only
serve as stumbling blocks in creating East Asian welfare. The rising growth of China and
Korea will soon meet its end mimicking the pattern of Japan if no serious action is site4.
Therefore, In order to strengthen regional welfare and accelerate the phase of adjusting,
economic integration must take place.
110 Bulletin of Monetary, Economics and Banking, July 2010
III. THE OPENNESS IN TRADE
Greater economic interdependence between Japan, China and Korea will act well as the
base of creating regionalism. In this sense, triangular trade agreements that dismantle trade
barriers will smooth the progress of improved trade flows among these countries by means of
greater market access. But unfortunately, this supporting environment only operates as fact in
a sheet. The process of regionalism in this area is proven to be difficult.
These countries may have aggressively reached other countries in making FTA»s and EPA»s
but none of which have been progressing among them (see table V.1). The reason of it will be
a subject for another research, while this section tries to focus on the effect of such agreement
to the economy. The lack of trade arrangements is being noted as the main factor that contributes
intra regional trade ineffectiveness in north East Asia. This hypothesis will be proved in the
following sections to come.
Export lead growth approach that has been done in the previous section with
cointegration and error correction model has actually provided the basis to measure openness
of a country, but in some ways this alone is not enough. It only works for confirming the
paradigm of trade as an engine of growth but it is not sufficient to measure a more robust
pattern of openness. Therefore, we then may have to address Dollar»s Relative Price Level (RPL
index).
This index is a measure of outward orientation of an economy which was explored by
Summers and Heston (1988). Using the US as the benchmark country, the index of country i»s
relative price level (RPL) is:
(V.9)RPLi
= 100 x Pi /P
us x 1/e
Where e is the exchange rate and Pi is the consumption price index for country i and P
us is the
consumption price index for US. Therefore, we can use the formula to measure inward- or
outward-orientation of a trade policy. With using the same analogy, this paper then customizes
the RPL index into this formula:
(V.10)RPLi
= 100 x Pi /P
tp x 1/e
Where Ptp is the consumption price index for the trading partner and e is the exchange rate (no.
of units of domestic currency per unit of trading partner currency). The customized RPL is then
become a powerful tool to analyze trade openness between the trading countries.
111Making East Asian Regionalism Works
(V.11)∆GDP_X = βo + β
1 .∆RPL_Y + β
2.µ
t-1 + e
t
As already explained in the previous section, ECM provides the description of short run
shock. In this particular case, we examine the openness vis a vis trade liberalization trend in
north East Asia region. This test employs time series quarterly data of Exchange rate, CPI,
Export for CJK ranging from 2001 to 2005, the data is taken from CEIC data base. Below is the
equation:
From this particular test we can see that generally trade openness is affecting a country»s
GDP in a positive way. But in the short run, trade openness in the CJK is still below the equilibrium.
This suggests that trade openness is still finding its form in this area. Although we might not
see regionalism which liberalize trade in the short run, but the trend towards openness in trade
vis a vis regionalism is progressing in a respectful manner. We can see this through the adjustment
rate for the long run equilibrium (the coefficients of residuals) that yields an average of 1.1,
consequently we might see regionalism in North East Asia happen in the future.
IV. THE SPILLOVER EFFECT FROM JAPAN-KOREA-CHINA TRIANGULAR TRADETO ASEAN 4
As giants of Asia, the growth of Japan, Korea and China will most likely create positive
effect to the neighboring countries. Regionally speaking, the growth of North East Asia will
This equation mimics equation V.7, but the previous dependent variable is substituted
from export to RPL in order to suit the goal which is to measure the openness. ∆GDP Country
X is the difference in GDP from Japan, Korea and China, ∆RPL Country Y is the difference in
RPL from a country X to Country Y. ∆RPL Country Y measures the openness of trade from
of country X towards Y. Below is the outputs for each country:
Table V.4Cointegration Parameters
Equilibrium error for Openness to Japan na -1.23 *** -1.31 ***
Equilibrium error for Openness to China -1.15 *** na -0.97 ***
Equilibrium error for Openness to Korea -0.72 ** -1.24 *** na
Note: Statistical significance is indicated by *(10%), **(5%), and ***(1%)
Dependent Variable
Independent VariableGDP (Japan) GDP (China) GDP (Korea)
112 Bulletin of Monetary, Economics and Banking, July 2010
boost the East Asian growth as whole, in this sense we might want to exercise its effect to
ASEAN countries. To simplify things, this paper limits the effect to ASEAN4 since these countries
have the same economic characteristics. This paper employs static panel data model for this
purpose. The panel data is analyzed annually from 1989 to 2007 which consist of ASEAN 4»s
Export, Import, Consumption, Investment, Government expenditure, GDP, and GDP of Japan,
China, Korea. The data is taken from WDI online database. The following sections provide the
analysis.
A static panel data model can be specified as follows:
(V.12)
Where: λt and η
t are time and individual specific effects respectively, x it is a vector of the
explanatory variables, (i) is the time component of the panel, (N) is the cross-section
dimension (or the number of cross-section observations), and N x T is the total number of
observations. The idea is to run the models in order to have a consistent estimator for the
β coefficients, and the model (fixed or random) choice depends on the hypothesis assumed
for the relationship between the error-term (ε it ) and the regressors (x it ). The static panel
data analysis developed in the empirical section of the paper was based on two basic panel
models, the fixed (FE) and the random (RE) effect models. Since the time periods (1989-
2007) exceed the individual observations (Indonesia, Malaysia, Thailand, Philippines) therefore
FE is considered as the most appropriate method (Nachrowi and Usman, 2008). The model
is described as follows:
, t = 1,..., Ti = 1,...,NXYitititit
+++= εηλβ
(V.13)
Where:
Yit
= GDP growth of ASEAN 4 for time t and country i
Xit
= Independent Variables (ASEAN 4 consumption growth, investment growth, government
expenditure growth, export-import growth and Japan-China-Korea GDP growth for
time t)
Wit and Z
it are dummy variables which are defined as follows:
Wit = 1 for country i, where i = Indonesia, Malaysia, Philippines, Thailand
= 0 for others
itiTTiiNtNttititeZZZWWWXY ++++++++++++= δδδγγγβα .......
221122111
113Making East Asian Regionalism Works
Zit
= 1 for Period t where t = 1989, 1990..., 2007
= 0 for others
The above structural equation is actually a simultaneous equation in which employs
causality relationship. To see the simultaneity, the above model can be decomposed into four
parts:
(V.14)
(V.15)
(V.16)
(V.17)
ttttttttKGDPCGDPJGDPXGICY .......
87654321ββββββββ +++++++=
tttYCC ..
3121βββ ++= −
tttYrI ..
321βββ ++=
ttttttKGDPCGDPJGDPCEXX .....
654321ββββββ +++++=
Equation V.14 describes the effects of ASEAN 4 consumption (Ct), investment (I
t),
government expenditure (Gt), export growth (X
t) and the North East Asian GDP growth (JGDP
t,
CGDPt, KGDP
t) on ASEAN4 GDP growth (Y
t). From the model, it is clear that consumption
growth, investment growth and export growth have their own determinants that simultaneously
form the structural equation. Consumption growth (Ct) is formed by last year»s consumption
growth (Ct-1
), and the present GDP growth (Yt), Investment (I
t) on the other hand is influenced
by the interest rate (rt) and the GDP growth (C
t). It is also expected that exchange rate (EX
t),
consumption growth (Ct) and trading partners economic growth (JGDP
t, CGDP
t, KGDP
t) have
some influences on export growth (Xt) for ASEAN 4.
From the structural equation, we can divide the variables into two, endogenous and
predetermined (exogenous). The first one is treated as stochastic while the latter as non
stochasti3. To see which simultaneous model that can satisfies the need, we have to address
the identification process. If K is the number of exogenous variables within the model, k is the
number of exogenous variables within the equation and M is the number of endogenous
variable within the model, so the criteria to state whether an equation is unidentified, just
identified, or over identified are describe as follows:
If K-k < M-1, so the equation is unidentified
If K-k = M-1, so the equation is exactly identified
If K-k > M-1, so the equation is over identified
Based form the above criteria, table V.5 summarize the order condition from the system:
114 Bulletin of Monetary, Economics and Banking, July 2010
1 2 1 3 1 4 5 6 7 8 9t t t t t t t t tY C Y r G EX JGDP CGDP KGDP− −= Π +Π +Π +Π +Π +Π +Π +Π +Π
10 11 1 12 1 13 14 15 16 17 18t t t t t t t t tC C Y r G EX JGDP CGDP KGDP− −= Π +Π +Π +Π +Π +Π +Π +Π +Π
19 20 1 21 1 22 23 24 25 26 27t t t t t t t t tI C Y r G EX JGDP CGDP KGDP− −= Π +Π +Π +Π +Π +Π +Π +Π +Π
28 29 1 30 1 31 32 33 34 35 36t t t t t t t t tX C Y r G EX JGDP CGDP KGDP− −= Π +Π +Π +Π +Π +Π +Π +Π +Π
Table V.5Order Condition
1 Yt 6 > 2 over identified
2 Ct 9 > 1 over identified
3 It 9 > 1 over identified
4 Xt 6 > 1 over identified
No Equation Criteria Conclusion
For the case of over identified, we might want to employ two stage least squares (2SLS)
approach as an elegant way to deal with such problem. 2SLS regression analysis, as suggested
by Angrist and Imbens (1995). Below is the detailed procedure of 2SLS.
In stage one, least square regression on the reduced form equation has to take place by
which it can yields Ct-1
, Yt-1
, rt, G
t, EX
t, JGDP
t, CGDP
t, KGDP
t as the instrumental variables,
therefore all equations from V.14 up to V.17 have to be transformed into reduced form equation
as the followings:
(V.18)
(V.19)
(V.20)
(V.21)
Note: Π is (β/(1- β))
From stage one we get as the fitted values with which we can run for the second stage.
In stage two, these fitted values are then plugged in to the main equation. The last step is to
run least squares on each of the above equations to get 2SLS estimation as described below in
Table V.6.
From the output above we can conclude that the North East Asian (Japan, Korea and
China) economic growth boost the ASEAN4 economic growth, it confirms the proposition of
this paper. Investment flows, in the form of FDI, has also operated as a dominant integrating
power in East Asia as whole. Although we cannot find legitimate determinant for FDI in the
output, but it is clear that FDI is trade related in nature. With its essentially open and outward-
looking economies, the region is highly dependent on foreign investment for its economic
115Making East Asian Regionalism Works
growth. But still, the boosting power is not as much as in the spillover effect from the giant
countries of Japan, Korea and China. Japan, in terms of GDP growth, has the biggest influence
towards ASEAN4 followed by China and Korea at the second and third place. This fact is
described by the coefficient parameter that gives the value of 0.546, 0.311 and 0.250 for
Japan, China and Korea respectively.
The ranking of influence is presumably caused by the number FDI inflows to ASEAN from
these countries as described below in Table V.7. The only bias is on China and Korea, even
though the cumulative FDI from Korea to ASEAN4 was bigger than China»s, but it does not
seem to be reflected on the ranking of influence. As for this, it is assumed that the high
economic growth rate of China had been the major contributing factor (Urata, 2008) that
Table V.6Two Stage Least Squares Regression Output
Independent Variable
YYYYY na 0.776 *** -0.087 Na
CCCCC 0.470 *** na Na -0.64 **IIIII 0.025 na Na NaXXXXX 0.072* na Na Na
Note: Statistical significance is indicated by *(10%), **(5%), and ***(1%)
Y C I XDependent Variable
Instrumental Variable
Y (Japan)Y (Japan)Y (Japan)Y (Japan)Y (Japan) 0.546 ** na Na 2.949***
Y (China)Y (China)Y (China)Y (China)Y (China) 0.311 ** na Na 1.112 ***
Y (Korea)Y (Korea)Y (Korea)Y (Korea)Y (Korea) 0.250 ** na Na -3.760
C (-1)C (-1)C (-1)C (-1)C (-1) na 0.01 Na Na
RRRRR na na 0.137 Na
Y (-1)Y (-1)Y (-1)Y (-1)Y (-1) na na Na Na
EXEXEXEXEX na na Na 0
GGGGG 0.122** na Na Na
Table V.7FDI flows to ASEAN 4 (US$ million)
Japan 288.06 8,096.02 4,761.11 3,055.68 16,200.87
Korea 331.88 235.58 98.51 238.13 904.1
China -36.78 50.16 120.72 4.07 138.17
Source: ASEAN secretariat
Host Country Indonesia Thailand Malaysia Philippines
Source Country
Total Cummulative1995-2003
116 Bulletin of Monetary, Economics and Banking, July 2010
overtook the influence of Korea»s cumulative FDI flow to ASEAN4. However, such factor is not
enough to surpass3 Japan»s influence to ASEAN4»s economic growth since Japan»s FDI
contribution to ASEAN4 outweighed China»s by more than one hundred folds.
The story goes hand in hand with the flying-geese hypothesis that was developed by
Japanese economist, Kaname Akamatsu (1935). This model has been frequently proposed to
examine the patterns and characteristics of East Asian economic integration. ≈The premise of
the flying-geese pattern suggests that a group of nations in this region are flying together in
layers with Japan at the front layer. The layers signify the different stages of economic
development achieved in various countries∆ (Xing, 2007). In the flying-geese model of regional
economic development, Japan as the leading goose leads the second-tier geese (China, Korea)
which, in their turn, are followed by the third-tier geese (ASEAN4).
Another important thing to note is the low significant value of exports within ASEAN4 in
terms of creating GDP growth. These are intriguing facts since export is considered as the main
determinant of GDP growth. It is suspected that the effect of rivalry between ASEAN4 members
and China is the main factor which creates insignificant value. This factor is supported by Holst
and Weiss (2004) that pointed out China»s emergence for creating short and medium term
direct and indirect competition between ASEAN and China. They argued that ASEAN and
China are experiencing intensified export competition in prominent third markets. This can
lead to painful domestic structural adjustments within the ASEAN in the short run. Then again
the mind set in viewing the economic opportunity or threat depends on whether China»s economy
is perceived as complementary or competitive vis-à-vis individual ASEAN economies and on
whether the latter economies are able to exploit their complementary opportunities and
overcome the competitive threats.
Chia (2006) argued that ≈the differences in resource and factor endowments, production
structures, and productivities lead to a complementary relationship, whereas similarities in these
areas lead to a competitive relationship.∆ In the long run, regionalism is expected to
accommodate welfare for East Asia. The growing significance of China market for ASEAN will
serve as the basis for regionalism. Thus, a unified East Asia could accelerate the momentum of
overall trade liberalization and boost regional economic growth.
3 From the ECM simulation as confirmed earlier, we found that China has taken over Japan»s role in East Asia. But this is true if weaddress the long run effect. This section only measures the present condition in the absence of the intertemporal problem.
117Making East Asian Regionalism Works
V. THE FUTURE OF EAST ASIAN REGIONALISM (EAR)
The next task is to shape the future of EAR, but then will the future exist? In part C of this
paper, we measure the trend toward openness vis a vis regionalism by using ECM for the RPL
index in North East Asia (CJK). Since we include two sub regions, the best way to measure it is
by using test of convergence of the term of trade for CJK and ASEAN4. The notion of convergence
implies that differences between the series must follow a stationary process (Bernard & Durlauf,
1996; Oxley & Greasley, 1995). Thus, stochastic convergence implies that income differences
among countries cannot contain unit roots.
Following Bernard and Durlauf (1995), stochastic convergence occurs if the differential
log trade system, yt, follows a stationary process, where y
t = ASEAN4tot
t - CJKtot
t, where
ASEAN4tott is the logarithm term of trade of ASEAN4, and CJKtot
t is logarithm term of trade
of CJK, and both series are in the first difference (I(1)). Stochastic convergence is tested by
using the conventional augmented Dickey-Fuller (ADF) regression which shows a significance
result in proving stationarity for yt (see Table V.8). This indicates long-run convergence between
the two trading systems.
Table V.8ADF Test for Term of Trade
ADF Test Statistic -3.519465 1% Critical Value* -3.7204
5% Critical Value -2.9850
10% Critical Value -2.6318
*MacKinnon critical values for rejection of hypothesis of a unit root.
A major drawback of the standard ADF unit root test procedure is that the power of the
test is quite low. To overcome this problem, the paper utilizes cointegration test as suggested
by Baharumshah et al. (2007). The following is the Engle Granger Cointegration:
Table V.9ADF Test for Cointegration Residual
ADF Test Statistic -5.623714 1% Critical Value * -3.7204
5% Critical Value -2.9850
10% Critical Value -2.6318
*MacKinnon critical values for rejection of hypothesis of a unit root.
Ut = ASEANtott − βο − β1CJKtot
t (V.22)
118 Bulletin of Monetary, Economics and Banking, July 2010
Open = α + βXit + γ1W1t + γ2W2t + γ3W3t + ... + γNWN + δ1Zi1 + δ2Zi2 + δ3Zi3 + ... + δtZiT + eit
(V.23)
The residual ( U
t ) gives stationary result (see Table V.9) which means that the two regions
have long run relationship (convergence). It is worth to say that with the test of convergence,
EAR will be there to stay in the long run. The robust finding surely creates optimistic view for
EAR. But knowing the future is not enough, we still need to find out the clear path to reach the
future. The next section serves to give the answer.
Feng and Genna (2003) argued that homogeneity of domestic institutions is needed to
go hand in hand with the regional integration process. Moreover, they pointed out inflation,
taxation and government regulation as representing factors for the economic institutions.
Another variable that might enhance integration is population as already identified by Tamura
(1995). He argued that large population is a catalyst for integration due to economic
agglomeration. Scholars like Milner and Kubota (2005) even pointed out democracy as an
important factor that could foster regionalism. Their empirical work on the developing countries
from 1970-1999 showed that regime change toward democracy was associated with trade
liberalization, and regionalization.
Given those works, this paper tries to combine the variables into one complete model
that can determine the formation of EAR. The formula as follows:
Where:,
Openit = Regionalism for time t and country i
Xit = Independent Variables (ASEAN4 + CJK»s rail ways, tax, democracy, governance,
industry, gross school enrolment rate, inflation and population)
Wit and Zit are dummy variables which are defined as follows:
Wit = 1 for country i, where i = Indonesia, Malaysia, Philippines, Thailand China, Japan,
Korea, otherwise 0.
Zit = 1 for Period t where t = 1998, 2000..., 2007, , otherwise 0.
The paper employs fixed effect model to estimate the variables. The followings are the
explanations for the variables used:
i) The paper use the proxy of trade openness (net export per GDP) for regionalism. The variable
of openness is used to represent regionalism since regionalism creates openness to some
sectors of economy. Openness here functions as dependent variable that is determined by
some independent variables.
119Making East Asian Regionalism Works
ii) Railways as goods transported (million ton-km) is used to explain physical infrastructure
readiness. Pairing up with this variable is the gross school enrolment rate which serves as
the basic for human capital infrastructure. Sound infrastructure (both physical and human)
will provide steadiness and assuredness in making investment among members. In other
words, good infrastructure will only lead to a sustainable intra trade and investment that
serve as the basis of EAR.
iii) To measure democracy, the indices produced by Freedom House (2000) that is the index of
democracy called POLITY. Democratization is expected to open up new avenues of support
for freer trade vis-à-vis regionalism.
iv) Moving to the next variable is the taxation policy, the higher the rate the more it will diminish
the prospects of EAR
v) Other variable that also matters is governance which is measured by the six governance
indicators estimated by Kaufmann (2003). These indices describe various aspects of the
governance structures of a broad cross section of countries, including measures of Voice
and Accountability, Political stability, Government Effectiveness, Regulatory Quality, Rule of
Law, and Control of Corruption. In general, the Governance index provides explanatory
power to explain the capability and quality of governance from each member country. The
better indicator a country has the more it has the chance to capitalize regionalism.
vi) Macroeconomic variable which is represented by inflation creates ambiguous expectation.
High inflation might deter the formation of EAR since the very beginning but some scholars
prove the other way aroun4. One of argument that supporting the latter proposition is
given by Cohen (1997) who argued that the inflationary policy (high inflation) resulting
from the government action will tend to raise the obstacle to private investors which in turn
demand for greater integration. The loss of discretion in the fiscal and monetary policy will
then reduced the risk of uncertainty. vii) Large market together with the ongoing
industrialization process sums up the last aspects of EAR formation. The sheer size of the
East Asian population creates not only the potential demand for the goods traded in the
region but also the supply of labor force and the low absolute level of wages. In other
words, Lewis»s unlimited supply of labor will persist longer in East Asia. The process will lead
to an upward trend towards industrialization (value added as percentage from GDP) in the
region. The trend is very important since homogeneity in industrialization among countries
in the region will smooth the progress of EAR.
The results shows us that Economic and political factors such as Infrastructure (railways
and gross education), governance, taxation policy, industrialization and Democracy have
significant effect towards Regionalism (Openness) in East Asia while Inflation gives insignificant
role.
120 Bulletin of Monetary, Economics and Banking, July 2010
Note: Statistical significance is indicated by *(10%), **(5%), and ***(1%)
Table V.10.Factors Affecting Openness
LOG (RAILWAYS) 0.115860 2.059379**TAX -0.029831 -3.530943***DEMOCRACY -0.004282 -2.051852**GOVERNANCE 0.257508 3.860438***INDUSTRY 0.049930 4.861010***LOG (POPULATION) 0.863634 2.154852**GROSS EDUCATION 0.011445 2.217493**INFLATION -0.001545 -0.441719R-squared 0.99251Adjusted R-squared 0.98975
Dependent Variable : OPENNES
Independent VariableIndependent VariableIndependent VariableIndependent VariableIndependent Variable CoefficientCoefficientCoefficientCoefficientCoefficient t-Statistict-Statistict-Statistict-Statistict-Statistic
The signs of coefficient for railways, gross education, governance, and industrialization
are positive which mean the bigger the variable the more they create Openness. The negative
sign of the coefficient for tax describes the opposite relation between corporate tax rate and
the future prospect of EAR, the higher the rate the more it will the deteriorate the EAR. The
negative sign of democracy is against expectation but it is still rational since democracy is still
finding its form in East Asia. We have to define what democracy really means in order to
make it works. The insignificant role of inflation for EAR is expected due to the ambiguity
given.
VI. CONCLUSION
We have made an interim conclusion that export leads the overall growth in North East
Asia. However, it is important to note that Japan»s phase of adjustment towards long run
equilibrium is quite slow compared to the likes of Korea and China. This only yields as a stumbling
block in forming regionalism in East Asia. The hard task is about making these countries move
together in the same phase, which is why regionalism has to take place.
Since regionalism is an abstract term, the use of RPL index is essential. RPL index is a
proxy of outward orientation of a country or in other words it is a representation of regionalism.
Regionalism in this case goes hand in hand with openness in which it creates trade arrangements
that liberalize some sectors in the economy. The ECM simulation gives a clear picture of the
current form of openness which is below the equilibrium. It suggests that the trend towards
121Making East Asian Regionalism Works
regionalism is still far behin4. It somewhat confirms the ineffectiveness of current triangular
trade in North East Asia. It is expected that regionalism can eliminates such bias in trade.
Moreover, since North East Asian countries has a big scale of economy, its economic
development will substantially affect the neighboring countries in East Asia specifically ASEAN4.
It is demonstrated by the large share of China-Japan-Korea growth that affects ASEAN4»s GDP.
In the short run, there is a rivalry competition between China and ASEAN. However, in
the long run regionalism is expected to accommodate export growth for East Asia as whole. In
a sense of creating integration in East Asia, there is a need to set up more formal institutional
mechanisms for trade. It is rational for such mutually dependent countries in the region to
institutionalize de facto integration through the establishment of regional arrangements (Kawai,
2005). The growing significance of China, Japan and Korea market for ASEAN4 will then serve
as the basis for a single East Asian Wide FTA. The next task is to shape the future of EAR, but
then will the future exist? Using the test of convergence, it is found that EAR will be there to
stay. The robust finding surely creates optimistic view for EAR. But knowing the future is not
enough, we still need to find out the clear path to reach the future. What are the paths then?
From a static panel data simulation it is found that sound physical infrastructure, good
governance, inflation, competitive taxation policy, sizeable market and the trend towards
industrialization are the main factors that serve as building blocks for EAR.
To wrap up, EAR will enable the region to cope with the future challenges of globalization
and remain internationally competitive. An integrated East Asia would lead to the advancement
in economies of scale, fuller development of production networks. Moreover, Chia (2007) stated
that EAR could help the less developed East Asian economies which would otherwise become
marginalized as they lack the attraction of sizeable market and lack negotiating resources.
122 Bulletin of Monetary, Economics and Banking, July 2010
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125
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