Trade Creation and Diversion Effects of

ASEAN Free Trade Area (AFTA)

BY

Ho Sze Yin Iris

07009186

Applied Economics Major

An Honours Degree Project Submitted to

School of Business in Partial Fulfillment

of Graduation Requirement for Degree of

Bachelor of Business Administration (Honours)

Hong Kong Baptist University

Hong Kong

April 2010

1

Acknowledgements

I would like to thank Dr Kwok Yun Kwong for his continuous support and valuable

advice throughout the whole discussion of Honour Project His suggestions enhance my

analytical skills and enrich my understanding about international trade I appreciate his

effort and time to discuss my project whenever I have any problems

In addition I would like to thank all the parties who gave me supports and comments to

my project This project provides me an opportunity to experience the process of

academic research and a new insight about trade agreement

2

Abstract

Using gravity model this study examines whether formation of ASEAN Free Trade

Area (AFTA) led to trade creation among members and trade diversion from 1988-2004

Due to reduction in tariff rate there is an increase in intraregional trade after the

formation of AFTA in 1992 The empirical results show AFTA has no trade diversion as

member countries trade more with nonmember countries than hypothetical level

This paper pays particular attention in assessing the trade effects after the formation of

AFTA 1997 Asian financial Crisis and the Outbreak of Severe Acute Respiratory

Syndrome (SARS) in 2003 One of the interesting results is 1997 Asian Financial Crisis

has not led to fall in trade creation and ASEAN members exports intensively with

nonmember countries as ASEAN national currency devaluates However after the

outbreak of SARS it seems surprising that there is weakening of trade creation

negative export trade diversion and negative import trade diversion AFTA demonstrates

an economic regionalism that united its members to carry out policies and speed up

economic recovery during economic downturn

Finally the formation of China-ASEAN Free Trade Area (CAFTA) generates a larger

market and fosters economic growth in ASEAN countries It is a fundamental step

which initiates economic cooperation and strengthened trade creation and diversion

effects among ASEAN countries and China

1

Acknowledgements

I would like to thank Dr Kwok Yun Kwong for his continuous support and valuable

advice throughout the whole discussion of Honour Project His suggestions enhance my

analytical skills and enrich my understanding about international trade I appreciate his

effort and time to discuss my project whenever I have any problems

In addition I would like to thank all the parties who gave me supports and comments to

my project This project provides me an opportunity to experience the process of

academic research and a new insight about trade agreement

2

Abstract

Using gravity model this study examines whether formation of ASEAN Free Trade

Area (AFTA) led to trade creation among members and trade diversion from 1988-2004

Due to reduction in tariff rate there is an increase in intraregional trade after the

formation of AFTA in 1992 The empirical results show AFTA has no trade diversion as

member countries trade more with nonmember countries than hypothetical level

This paper pays particular attention in assessing the trade effects after the formation of

AFTA 1997 Asian financial Crisis and the Outbreak of Severe Acute Respiratory

Syndrome (SARS) in 2003 One of the interesting results is 1997 Asian Financial Crisis

has not led to fall in trade creation and ASEAN members exports intensively with

nonmember countries as ASEAN national currency devaluates However after the

outbreak of SARS it seems surprising that there is weakening of trade creation

negative export trade diversion and negative import trade diversion AFTA demonstrates

an economic regionalism that united its members to carry out policies and speed up

economic recovery during economic downturn

Finally the formation of China-ASEAN Free Trade Area (CAFTA) generates a larger

market and fosters economic growth in ASEAN countries It is a fundamental step

which initiates economic cooperation and strengthened trade creation and diversion

effects among ASEAN countries and China

2

Abstract

Using gravity model this study examines whether formation of ASEAN Free Trade

Area (AFTA) led to trade creation among members and trade diversion from 1988-2004

Due to reduction in tariff rate there is an increase in intraregional trade after the

formation of AFTA in 1992 The empirical results show AFTA has no trade diversion as

member countries trade more with nonmember countries than hypothetical level

This paper pays particular attention in assessing the trade effects after the formation of

AFTA 1997 Asian financial Crisis and the Outbreak of Severe Acute Respiratory

Syndrome (SARS) in 2003 One of the interesting results is 1997 Asian Financial Crisis

has not led to fall in trade creation and ASEAN members exports intensively with

nonmember countries as ASEAN national currency devaluates However after the

outbreak of SARS it seems surprising that there is weakening of trade creation

negative export trade diversion and negative import trade diversion AFTA demonstrates

an economic regionalism that united its members to carry out policies and speed up

economic recovery during economic downturn

Finally the formation of China-ASEAN Free Trade Area (CAFTA) generates a larger

market and fosters economic growth in ASEAN countries It is a fundamental step

which initiates economic cooperation and strengthened trade creation and diversion

effects among ASEAN countries and China

3

Content

Acknowledgements P1

Abstract P2

Content P3

1 Introduction P4

2 Overview of AFTA P6

3 Literature Review P7

4 Methodology P13

5 Empirical Results P19

6 Policy Implication and Recommendation P27

7 Conclusion P29

8 Appendix P31

9 Reference P33

4

1 Introduction

In mid-1980s many developing countries abandoned import substituting

industrialization and began to liberalize trade because this could accelerate economic

growth There has been an increasing trend of forming regional trading bloc to facilitate

trade among countries since 1990 With the establishment of World Trade Organization

(WTO) to replace General Agreement on Tariff and Trade world trade was promoted

and enhanced In East Asian economies ASEAN set up the first trading bloc which

called ASEAN Free Trade Area (AFTA) in 1992 to reduce the trade barrier across

member countries The ultimate target of AFTA is to eliminate all tariffs on intra

ASEAN imports by 2010

AFTA which has long time standing in the world economy exhibited a major effect on

world trade patterns After the establishment of AFTA a wide range of policy was

introduced to improve trade facilitation foreign direct investment and financial flow

One of the significant results is the average tariff rate of this bloc has dropped from

1276 in 1993 to 151 in 2002 (ASEAN Secretariat 2009) ASEANrsquos global trade in

2006 increased to USD$141 trillion compared with USD$123 trillion in 2005 (ASEAN

Secretariat 2009) This shows the volume of trade with member countries and

nonmember countries are substantial

In addition starting from 1 January 2010 China joins AFTA and China ndash ASEAN Free

5

Trade Area (CAFTA) forms CAFTA can give ASEAN countries confidence to access

the market in China This new trade agreement has population of over 19 billion and a

combined gross national product of approximately USD$6 trillion and annual trade

volume of USD$45 trillion (US Fed News Service 2010) Therefore it is another

important trade agreement after European Union (EU) and North American Free Trade

Association (NAFTA)

To assess the implication of AFTA on trade gravity model is widely employed to

measure the trade creation and diversion effects which will be discussed in the later part

of the study A regional trade arrangement (RTA) can improve welfare when it allows

the country to replace high cost domestic production with imports from the member

countries because the tariff is lowered On the other hand RTA can also reduce country

welfare by replacing imports from low cost nonmember countries with high cost

country Lee and Shin (2006) suggested these two effects would make the impact of

RTAs on global trade and welfare become ambiguous

The objective of this study is to test whether formation of AFTA have facilitated trade

among the member countries at an expense of nonmember countries by using gravity

model We will further examine whether trade is promoted or hindered after 1997 Asian

Financial Crisis and the Outbreak of Severe Acute Respiratory Syndrome in 2003

4

1 Introduction

In mid-1980s many developing countries abandoned import substituting

industrialization and began to liberalize trade because this could accelerate economic

growth There has been an increasing trend of forming regional trading bloc to facilitate

trade among countries since 1990 With the establishment of World Trade Organization

(WTO) to replace General Agreement on Tariff and Trade world trade was promoted

and enhanced In East Asian economies ASEAN set up the first trading bloc which

called ASEAN Free Trade Area (AFTA) in 1992 to reduce the trade barrier across

member countries The ultimate target of AFTA is to eliminate all tariffs on intra

ASEAN imports by 2010

AFTA which has long time standing in the world economy exhibited a major effect on

world trade patterns After the establishment of AFTA a wide range of policy was

introduced to improve trade facilitation foreign direct investment and financial flow

One of the significant results is the average tariff rate of this bloc has dropped from

1276 in 1993 to 151 in 2002 (ASEAN Secretariat 2009) ASEANrsquos global trade in

2006 increased to USD$141 trillion compared with USD$123 trillion in 2005 (ASEAN

Secretariat 2009) This shows the volume of trade with member countries and

nonmember countries are substantial

In addition starting from 1 January 2010 China joins AFTA and China ndash ASEAN Free

5

Trade Area (CAFTA) forms CAFTA can give ASEAN countries confidence to access

the market in China This new trade agreement has population of over 19 billion and a

combined gross national product of approximately USD$6 trillion and annual trade

volume of USD$45 trillion (US Fed News Service 2010) Therefore it is another

important trade agreement after European Union (EU) and North American Free Trade

Association (NAFTA)

To assess the implication of AFTA on trade gravity model is widely employed to

measure the trade creation and diversion effects which will be discussed in the later part

of the study A regional trade arrangement (RTA) can improve welfare when it allows

the country to replace high cost domestic production with imports from the member

countries because the tariff is lowered On the other hand RTA can also reduce country

welfare by replacing imports from low cost nonmember countries with high cost

country Lee and Shin (2006) suggested these two effects would make the impact of

RTAs on global trade and welfare become ambiguous

The objective of this study is to test whether formation of AFTA have facilitated trade

among the member countries at an expense of nonmember countries by using gravity

model We will further examine whether trade is promoted or hindered after 1997 Asian

Financial Crisis and the Outbreak of Severe Acute Respiratory Syndrome in 2003

5

Trade Area (CAFTA) forms CAFTA can give ASEAN countries confidence to access

the market in China This new trade agreement has population of over 19 billion and a

combined gross national product of approximately USD$6 trillion and annual trade

volume of USD$45 trillion (US Fed News Service 2010) Therefore it is another

important trade agreement after European Union (EU) and North American Free Trade

Association (NAFTA)

To assess the implication of AFTA on trade gravity model is widely employed to

measure the trade creation and diversion effects which will be discussed in the later part

of the study A regional trade arrangement (RTA) can improve welfare when it allows

the country to replace high cost domestic production with imports from the member

countries because the tariff is lowered On the other hand RTA can also reduce country

welfare by replacing imports from low cost nonmember countries with high cost

country Lee and Shin (2006) suggested these two effects would make the impact of

RTAs on global trade and welfare become ambiguous

The objective of this study is to test whether formation of AFTA have facilitated trade

among the member countries at an expense of nonmember countries by using gravity

model We will further examine whether trade is promoted or hindered after 1997 Asian

Financial Crisis and the Outbreak of Severe Acute Respiratory Syndrome in 2003

6

2 Overview of AFTA

Association of South-East Asian Nations Free Trade Area (AFTA) which formed in

1992 aims at removing intra regional tariffs and non tariff barrier among member

countries The ultimate goal is to enhance competitive edge of all the member countries

as a production base geared for the world market (ASEAN Secretariat 2009)

In 1992 ASEAN-6 includes Brunei Darussalam Indonesia Malaysia Philippines

Singapore and Thailand Up till now AFTA has been enlarged and has ten member

countries consisting of ASEAN-6 Vietnam Lao PDR Myanmar and Cambodia Under

the Agreement on the Common Effective Preferential Tariff (CEPT) Scheme the tariff

rates that levied on more than 99 percent of the products in the CEPT Inclusion List (IL)

have been reduced to the 0-5 percent by 2007 All manufactured products like capital

goods processed agricultural products and those products falling outside the definition

of agricultural products will be categorized in CEPT scheme (ASEAN Secretariat

2009) Products which are grouped in Highly Sensitive List like rice and the General

Exception List are excluded in CEPT Scheme (ASEAN Secretariat 2009)

Japan which was invited to attend the recent summit proposed the idea of ldquoEast Asian

Communityrdquo which means having its own currency like the system of European Union

7

3 Literature Review

To understand the reasons and implications for the formation of AFTA Bowles (1997)

pointed out AFTA was an emergence of North South regionalism and multiple

regionalism North south regionalism refers to countries with very different levels of per

capita income group together to form trading bloc For example the GNP of Singapore

is twenty five times larger than that of Indonesia (Bowles 1997) For multiple

regionalism it means countries participate in different regional groupings and

organizations Members of ASEAN also join East Asian Economic Caucus (EAEC) and

Asia Pacific Economic Cooperation (APEC) This leads to global freer trade

As trade effects of regional trade agreement are subjected to changes in external

economic environment data in the study should cover a longer time range in order to

have a comprehensive understanding of RTA Concerning AFTA there is not much

study discussed its trade effects after 1997 Asian Financial Crisis and the outbreak of

SARS in 2003 In 1997 East Asian economies had been attacked by Asian financial

Crisis which resulted in increase in unemployment rate and economic doom As massive

speculation of Thai Baht devaluation led to loss of foreign exchange reserves in the first

half of 1997 this caused actual devaluation of Thai Baht on 2 July 1997 The situation

became worse as speculation extended to other Asian currency like Malaysia Ringgit

Indonesia Rupiah and Philippine Peso (Vichitsarawong Eng and Meek 2010) Many

8

corporations and financial institutions terminated their businesses and went bankrupt

The intra ASEAN exports reduced from US$231 billion in first quarter of 1997 to

US$174 billion in first quarter in 1998 as shown in Table 81 from Appendix (Jr Yee

and Azhari 1998)

After five years the outbreak of SARS brought economic downturn to Asian economies

like Hong Kong Singapore and China The spread of diseases hurt tourism retail

industries and foreign direct investments For example Canton Export Exhibition

which provided a platform for Chinese producers to sign export contracts with foreign

business people was held between end of April and beginning of May in 2003 The

contract value and number of visitors had fallen by 77 percent and 81 percent

respectively (Hanna and Huang 2004) We are interested in whether AFTA helped to

strengthen the economic cooperation among member countries after these events

According to Viner (1950) assessment of trade agreement was based on the

combination of trade creation and diversion effects To define trade creation arises

when the FTA promotes trade among members without hampering trade with

nonmembers Trade diversion effect arises when there is a promotion of trade among

members at the expense of trade with nonmembers The previous studies that published

in the 1990s could not find out the exact trade effects of AFTA because there was not

enough statistical data to capture the long run impacts Sharma and Chua (2000)

7

3 Literature Review

To understand the reasons and implications for the formation of AFTA Bowles (1997)

pointed out AFTA was an emergence of North South regionalism and multiple

regionalism North south regionalism refers to countries with very different levels of per

capita income group together to form trading bloc For example the GNP of Singapore

is twenty five times larger than that of Indonesia (Bowles 1997) For multiple

regionalism it means countries participate in different regional groupings and

organizations Members of ASEAN also join East Asian Economic Caucus (EAEC) and

Asia Pacific Economic Cooperation (APEC) This leads to global freer trade

As trade effects of regional trade agreement are subjected to changes in external

economic environment data in the study should cover a longer time range in order to

have a comprehensive understanding of RTA Concerning AFTA there is not much

study discussed its trade effects after 1997 Asian Financial Crisis and the outbreak of

SARS in 2003 In 1997 East Asian economies had been attacked by Asian financial

Crisis which resulted in increase in unemployment rate and economic doom As massive

speculation of Thai Baht devaluation led to loss of foreign exchange reserves in the first

half of 1997 this caused actual devaluation of Thai Baht on 2 July 1997 The situation

became worse as speculation extended to other Asian currency like Malaysia Ringgit

Indonesia Rupiah and Philippine Peso (Vichitsarawong Eng and Meek 2010) Many

8

corporations and financial institutions terminated their businesses and went bankrupt

The intra ASEAN exports reduced from US$231 billion in first quarter of 1997 to

US$174 billion in first quarter in 1998 as shown in Table 81 from Appendix (Jr Yee

and Azhari 1998)

After five years the outbreak of SARS brought economic downturn to Asian economies

like Hong Kong Singapore and China The spread of diseases hurt tourism retail

industries and foreign direct investments For example Canton Export Exhibition

which provided a platform for Chinese producers to sign export contracts with foreign

business people was held between end of April and beginning of May in 2003 The

contract value and number of visitors had fallen by 77 percent and 81 percent

respectively (Hanna and Huang 2004) We are interested in whether AFTA helped to

strengthen the economic cooperation among member countries after these events

According to Viner (1950) assessment of trade agreement was based on the

combination of trade creation and diversion effects To define trade creation arises

when the FTA promotes trade among members without hampering trade with

nonmembers Trade diversion effect arises when there is a promotion of trade among

members at the expense of trade with nonmembers The previous studies that published

in the 1990s could not find out the exact trade effects of AFTA because there was not

enough statistical data to capture the long run impacts Sharma and Chua (2000)

8

corporations and financial institutions terminated their businesses and went bankrupt

The intra ASEAN exports reduced from US$231 billion in first quarter of 1997 to

US$174 billion in first quarter in 1998 as shown in Table 81 from Appendix (Jr Yee

and Azhari 1998)

After five years the outbreak of SARS brought economic downturn to Asian economies

like Hong Kong Singapore and China The spread of diseases hurt tourism retail

industries and foreign direct investments For example Canton Export Exhibition

which provided a platform for Chinese producers to sign export contracts with foreign

business people was held between end of April and beginning of May in 2003 The

contract value and number of visitors had fallen by 77 percent and 81 percent

respectively (Hanna and Huang 2004) We are interested in whether AFTA helped to

strengthen the economic cooperation among member countries after these events

According to Viner (1950) assessment of trade agreement was based on the

combination of trade creation and diversion effects To define trade creation arises

when the FTA promotes trade among members without hampering trade with

nonmembers Trade diversion effect arises when there is a promotion of trade among

members at the expense of trade with nonmembers The previous studies that published

in the 1990s could not find out the exact trade effects of AFTA because there was not

enough statistical data to capture the long run impacts Sharma and Chua (2000)

9

Thornton and Goglio (2002) Elliot and Ikemoto (2004) Tang (2005) and Jugutnath

Stewart and Brooks (2007) use gravity model to investigate trade creation and diversion

effects of AFTA However as different model are used the results are mixed

The study of Sharma and Chua (2000) and Thornton and Goglio (2002) are considered

as early literatures which determine whether there is intraregional trade bias among the

members of ASEAN based on gravity model Data covered up to mid 1990s only and

these studies had different opinion Sharma and Chua (2000) concluded that AFTA had

no trade creation effects since less than one fifth of their trade was conducted among the

bloc members Thornton and Goglio (2002) argued Southeast Asia had bias towards

intraregional trade due to the proximity similarity of economic size and language

among member countries

Recent papers had similar result and concluded that AFTA has trade creation but no

trade diversion after its formation Data sets used by Elliot and Ikemoto (2004) and

Tang (2005) covered the period after 1997 They used gravity equation and had similar

sample period to evaluate trade pattern of AFTA

Elliot and Ikemoto (2004) divided the sample period of 1982 -1999 into six distinct time

periods to compare the on going effects of before and after the formation of AFTA

European Economic Community (EEC) and NAFTA The main finding was that degree

of trade creation among AFTA member countries before 1997 was low since the

10

member countries needed to compete with new industrialized countries like China

South America and Eastern Europe After 1997 there was significant negative import

trade diversion effect as the AFTA members preferred to import goods from members

rather than nonmembers At the same time negative export trade diversion was

intensified as AFTA members preferred to export to nonmembers countries rather than

member countries Devaluation of ASEAN currencies during 1997 Asian financial crisis

was used to account for the results

Tang (2005) further extended the model used by Elliot and Ikemoto (2004) by adding

several interaction terms to examine the Linder hypothesis Since different independent

variables and dependent variables were used the result of Tang was slightly different

from Elliot and Ikemoto The dependent variable of Tangrsquos model was the export values

of country i and j and the one used in Elliot and Ikemoto was imports of country i from

trade partner j The result of Tang (2005) was similar to Elliot and Ikemoto (2004)

which concluded there was trade creation but no trade diversion effect Tang (2005)

found out that ASEAN countries have already increased their trade with the nonmember

countries even before the formation of AFTA as industrializing ASEAN countries

adopted an outward trade orientation Both of them found out that there was an increase

in intraregional trade in AFTA after the Asian financial crisis in 1997

When compared the study of Jugutnath Stewart and Brooks (2007) with literature listed

11

above this paper had an opposite view and suggested AFTA had no trade diversion and

trade creation effect during the period of 1980-2000 They noted ASEAN members had

similar characteristics and they preferred to trade more with other nonmember countries

based on the theory of comparative advantage

Contrary to the precious study that use econometric estimation Calvo-Pardo Freund

and Ornelas (2009) Cabalu and Alfonso (2007) adopted different approach in evaluating

trade effects of AFTA Both of them conclude that AFTA is trade creating rather than

diverting Calvo-Pardo Freund and Ornelas (2009) plotted the volumes of intra-AFTA

imports and imports from outside the bloc on the figures over the period of 13 years

before and after the formation of AFTA to measure the impacts They suggested the

effect of trade creation overrides trade diversion The rate of increase in imports with

members was always larger than that of nonmembers Cabalu and Alfonso (2007) used

shift and share analysis which investigated changes in values and pattern of commodity

groups between AFTA and non member countries to examine the net trade impact In

their results exports and imports of ASEAN had positive shares in its own market and

nonmember countries after its formation The category of machinery and transport

equipment had the largest gains in shares

Besides mixed result recent development of AFTA also plays a major role in affecting

trade pattern Since 1 January 2004 the CEPT Rules of Origin and its Operational

12

Certification Procedures have been improved and implemented These include (a) a

standardized method of calculating localASEAN content (b) a set of principles for

determining the cost of ASEAN origin and the guidelines for costing methodologies (c)

treatment of locally-procured materials and (d) improved verification process

including on-site verification (ASEAN Secretariat 2009) Starting from 1st August 2008

manufacturer can benefit from tariff concession if they used ASEAN content of less

than 40 percent (Arunmas 2008) This raises the question of whether trade is enhanced

under these new implementation programmes after the outbreak of SARS

With recent development of AFTA and mixed results the effects of trade creation and

diversion are not clearly defined in recent study In this paper gravity model provides

comprehensive and accurate estimation of trade effects after its formation and periods of

economic downturn in member and nonmember countries

13

4Methodology

41 Specification of Gravity Model

To estimate the intensity and transition of trade creation and trade diversion gravity

model is adopted because of its simplicity and explanatory power in assessing the

impacts of regional trading bloc The original Basic Gravity Model (BGM) which is

written by Tinbergen (1962) to analyze effects of economic integration specifies as

follows

Xij=βoYi

β1 Yj

β2 Dij

β3 εij (1)

Or using natural logarithms

log Xij = log β0 + β1 log Yi + β2 log Yj +β3 log Dij +logεij (2)

BGM states that volume of trade between two countries is determined by Gross

Domestic Product (GDP) that measures the size of the economies and distance between

them From equation 1 trade is proportional to the product of two countriesrsquo GDPs and

inversely related to distance between two countries

In order to find out the trade creation and diversion of AFTA BGM as listed above will

be further modified by including three regional institutional dummy variables This

modified gravity model will be estimated by Ordinary Least Square (OLS) from 1988 to

2004 for 46 countries as shown below

14

log Xij = log β0 + β1 log Yi + β2 log Yj +β3 log Ni +β4 log Nj +β5 log Dij + β6AFTAij +

β7exAFTAij + β8imAFTAij +logεij (3)

where Xij is the total US dollar value of exports from country i to j Yi Yj are nominal

values of gross domestic product of country i and j in US dollar Ni Nj are populations

of countries i and j Dij is the distance between countries i and j AFTAij is a dummy

variable which is 1 if two countries belong to AFTA and 0 otherwise exAFTAij is 1 if

only export country i belongs to AFTA and 0 otherwise imAFTAij is 1 if only the

import country j belongs to AFTA and 0 otherwise log ε ij is the log

normally-distributed error term

Common language and common border dummy variable which are two excluded

independent variables in our model will be discussed below They measure cultural

affinity and are expected to have positive relationship with trade If the two countries

have common language and border this makes trade easier and improves

communication with other countries Jugutnath Stewart and Brooks (2007) used official

language of a country to determine whether countries have same common languages

However this variable is difficult to delineate because different country has their dialect

and English has been widely used for communication Secondly common border is

excluded because some countries like Japan Australia Indonesia Iceland and United

Kingdom which are included in our data set are an island They do not have any

15

common border with other countries In order to improve the stability of our model

these two variables are excluded

42 Expectation of Results

In the regression equation 3 expectations of explanatory variables are listed as follows

The expected signs of independent variables Yi and Yj are positive Large economies

tend to spend large amount on imports because they have high income As they produce

a wide range of products this attracts other countries to spend on their production as

well In our model nominal GDP is employed If real GDP is used to replace the

nominal one there will be only a small difference in the coefficient of determination

(Linnemann 1966) This result is shown in the Table 52

The coefficient of Ni and Nj are uncertain Nguyen (2009) states that the coefficient are

expected to be negative because countries that have large population will have larger

resource endowment This absorption effect causes less dependence on international

specialization This will lead to a fall in trade between countries On the other hand

they are expected to be positive means a larger population means a larger domestic

market This in turn exploits economies of scale and the country will trade more with

foreign partner with a wider range of goods

The expected sign of variable Dij is negative because the greater the distance between

16

country i and j increases transportation costs time required for delivery and

communication failures Volume of trade between two countries is inversely correlated

with distance

In addition there are different expectations for coefficients of AFTAij exAFTAij and

imAFTAij AFTAij is expected to be positive and reflects the creation effect of

intraregional trade due to reduction of tariff rates and elimination of non tariff barriers

among AFTA This indicates members of AFTA have trade more with its members than

hypothetical trade level Dummy variables exAFTAij and imAFTAij captures the ldquoexport

trade diversionrdquo and ldquoimport trade diversionrdquo respectively The formation of Free Trade

Area is expected to lead to a decline of trade among member countries and nonmembers

countries (Tang 2005) Endoh (1999) who coined the term ldquoexport trade diversionrdquo

states that negative and statically significant coefficient of exAFTAij indicates that this

economic integration has caused the member countries to export their products within

the bloc rather than those outside the bloc For imAFTAij if its coefficient is negative

and statistically significant this means the members have switched their importing

activities from nonmembers to members

43 Data Description and Sources

To compare the impacts of AFTA overtime in addition to the pooled data of 1988-2004

17

the data is divided into four periods ie 1988-1992 1993-1997 1998-2002 and

2003-2004 Concerning the first breakdown of 1988-1992 and 1993-1997 this can

examine the changes in the trade flow between the member and nonmember countries

before and after the formation of AFTA For the division of 1993-1997 and 1998-2002

this can test whether the trade flow was adversely affected by 1997 Asian Financial

Crisis For 1998-2002 and 2003-2004 this can explain whether Outbreak of SARS had

adverse impacts on trade in Asian economies

The data set covers the bilateral trade flow for 46 countries They include 10 members

of AFTA and 36 nonmember countries The nonmember countries include Austria

Belgium-Luxembourg Finland France Germany Ireland Italy Netherlands Portugal

Spain Denmark Sweden United Kingdom Algeria Argentina Australia Brazil

Canada Chile China Colombia Czech Republic Egypt Japan Hong Kong Iceland

India Iran Mexico Norway New Zealand Poland Russia South Korea Switzerland

and the United States

For the dependent variable the annual export data are extracted from the Direction of

Trade Statistics GDP and population are obtained from The World Economic Outlook

and International Financial Statistics All export values and GDP are in US million

dollars Distance is collected from the Great Circle Distance between Cities The

physical distance is measured by the capital cities of 46 member and nonmember

18

countries in kilometers The values of AFTAij exAFTAij and imAFTAij depend on

countries that paired in the observations The number of observation for the pooled

sample is 30867 Some of the data are not available in the data base especially for

period of 1980s in developing countries

19

5 Empirical Results

Ordinary Least Square result for regression equation 3 is presented in Table 51 The

values of adjusted coefficient of determination in 1988-1992 and 1993-1997 are 0717

and 0748 respectively For 1998-2002 and 2003-2004 values of adjusted coefficient of

determination are 0768 and 0763 This means over 70 variation of export values

between country i and country j around its mean can be explained by the independent

variables in regression equation 3 adjusted for degree of freedom

51 Explanation of Gravity Model

All estimated coefficient are statistically significant different from zero at 1 level of

significance The coefficient of Yi Yj and Dij fulfill our expectations as stated in the

gravity model This shows gravity model plays a major role in explaining pattern of

trade flow in modern society Trade is positively related to GDP Larger economies tend

to have higher demand for imports and produce larger amount of goods for exports

Similar to the results of Endoh (1999) the coefficient of population is negative which

means increase in population will cause a decline in trade as the country produces a

wider range of product

The coefficient of Dij is negative and statistically significant Although there are

improvements in transportation technologies which can reduce the transportation cost

20

and facilitate transportation of goods between both importing and exporting countries

over time distance between countries still remains one of the most important

determinants in trade activities

52 Intraregional trade bias in AFTA

The coefficients of AFTA ij are positive and statistically significant It increases from

1915 in 1988-1992 to 2155 in 1993-1997 This shows there is trade creation effect

after the formation of AFTA This is consistent with the previous study like Tang (2005)

and Thornton and Goglio (2002) The low tariff rate facilitates trade in AFTA

After the 1997 Asian Financial Crisis the poor economic performance did not inhibited

the member countries to export goods to each other as there is a sharp jump in this

coefficient to 2857 New admission of Lao PDR and Myanmar in 1997 stimulated trade

creation effects Average regional CEPT rate for products in the Inclusion List has

dropped from 1276 in 1993 to 505 in 1998 (Jr Yee and Azhari 1998) Elliot and

Ikemoto (2004) pointed out that this regional economic shock in the form of currency

crisis created latent forces institutionalizing interdependence within the bloc

On the contrary after outbreak of SARS in 2003 the coefficient of AFTAij decreases to

2699 To further explain SARS is a highly infectious respiratory disease that had

caused doom in East Asian economies Within AFTA Singapore and Vietnam were hard

21

hit by SARS People tend to avoid social interaction which led to a slump in business

transactions The unemployment rate increased and demand for goods and services fell

Although a new arrangement of CEPT Rules of Origin and Operational Certification

Procedures which could promote trade among AFTA has been implemented on 1

January 2004 intraregional trade had declined In addition rise of trade among

nonmember countries could explain this decline As China has formally entered into

WTO in 2001 exports of ASEAN countries need to compete with Chinese products in

both export and ASEAN domestic market and ASEAN exporters would lose their

comparative advantage when developed countries give tariff concessions to China

(Kwan and Qiu 2003)

53 Export and Import Trade Diversion between member and non member countries

Finally the dummy variables of exAFTA ij and imAFTA ij have signs opposite to our

expectations They are statistically significant at 1 level of significance The positive

sign of exAFTA ij and imAFTA ij indicate that members and nonmembers have traded

with each other to greater extent than the hypothetical trade level throughout 1988-2004

(Endoh 1999) The results indicate negative trade diversion effect in AFTA

The coefficient of exAFTAij has a continuous increase from 0837 in 1988-1992 to

1135 in 1993-1997 The positive sign of this coefficient implies that the member

22

countries prefer to export goods to nonmember rather than members after the formation

of AFTA This implies AFTA members adopted export oriented strategies that promoted

export (Nguyen 2009)

The coefficient of exAFTAij increases to 1374 after 1997 The upward trend in

exAFTAij shows there is strengthening of negative export trade diversion throughout the

period of 1992-2002 The model of Elliot and Ikemoto (2004) also had similar results

and further explained the sharp jump in exAFTAij is caused by the devaluation of

ASEAN currencies after 1997 Asian Financial crisis as shown in Figure 81 (Appendix)

This could increase the competitiveness of ASEAN exports since they were relatively

cheaper when compared with the products of nonmember countries This boosted

ASEAN export trade with nonmembers

After the outbreak of SARS exAFTAij coefficient falls to 1175 in the period 2003-2004

which means there is weakening of negative trade diversion The outbreak of SARS has

caused temporary shock and persistent shock to Hong Kong and Chinese economies

Lee (2004) suggested that SARS led to a loss of GDP Hong Kong which was seriously

affected has experienced a decline in GDP by 263 GDP of Taiwan and Singapore

also were decreased by 049 and 047 respectively This reduction showed there was

a fall in demand for goods and services of ASEAN countries This could also be

explained by the slight appreciation of ASEAN currency after 2002 Value of ASEAN

23

currency increased relative to other foreign countries and ASEAN products were

relatively more expensive Therefore AFTA members prefer to export their goods to

members rather than nonmembers

The dummy variable imAFTAij measures import trade diversion of AFTA Its

coefficient increases from 058 in 1988-1992 to 0903 in 1993-1997 The upward trend

reveals that dynamic network of domestic production and foreign investment projects in

AFTA members caused a rise in its imports from nonmember countries (Nguyen 2009)

This fall in imAFTA ij after 1997 Asian Financial Crisis and outbreak of SARS implies

there is a weakening of negative import trade diversion ASEAN prefer to import goods

from members rather than nonmembers but the effects are small relative to the

coefficient of AFTAij As explained before devaluation of ASEAN currency means

foreign goods are more expensive So they prefer to import from members After the

outbreak of SARS the coefficient of imAFTA ij further drops to 0682 Spread of

diseases generated negative impacts to economies in Hong Kong and China which are

major trading partners of AFTA These two countries had the highest probable cases of

SARS This is one of the reasons why AFTA members prefer to import more goods

from members rather than nonmembers

Trade creation and diversion are subjected to changes in external economic environment

AFTA strengthened cooperation with all member countries in 1997 Asian Financial

24

Crisis and urged the members to undertake policy to promote trade which can in turn

speed up economic recovery When compared with outbreak of SARS which caused an

economic downturn in nonmember countries AFTA demonstrates an economic

regionalism that united members in the bloc As shown in the econometric results

AFTA members prefer to trade more among themselves rather than nonmembers

To a certain extent exchange rate volatility did not play a significant role in affecting

trade Most of economies in East Asia adopt a ldquomanaged floatrdquo exchange rate policy

which is beneficial to accomplish economic goals and objectives (Martin 2008) The

2SLS results of Tang (2005) shows that coefficient of exchange rate volatility is positive

which is opposite to our expectation but it is statically insignificant in the pooled sample

Although this coefficient is negative in OLS estimation overall effects of exchange rate

volatility on trade has reduced over time Tang (2005) further suggested two reasons

attributable to this phenomenon after 1997 Firstly the restructuring of financial sectors

like implementation of pegged exchange rate system and transaction of currency option

and contract lead to improvements which can avoid similar crisis in future Secondly

financial system of developed countries are so well organized that stock market and

banking operation are less vulnerable to exchange rate fluctuation

In Table 52 real values of GDP and exports replaced the nominal one in regression

equation 3 Similar results and conclusions could be drawn

25

Table 51

Empirical results of regression equation 3

based on nominal values of exports and GDP

Independent

Variables

1988-1992 1993-1997 1998-2002 2003-2004 1988-2004

Constant 3438

(18597)

2974

(1857)

0966

(5753)

0457

(1653)

2569

(2755)

log Yi 1157

(93901)

1222

(10687)

1364

(98397)

1295

(59454)

1203

(179786)

log Yj 1016

(84303)

1008

(91165)

1215

(90192)

1182

(54609)

1046

(160182)

log Ni -0238

(-18409)

-0219

(-19762)

-0224

(-19141)

-0144

(-7936)

-0187

(-29098)

log Nj -0125

(-9624)

-0071

(-6442)

-0163

(-14185)

-009

(-499)

-0090

(-14138)

log Dij -0983

(-50493)

-1036

(-61597)

-0994

(-59095)

-0961

(-35954)

-0993

(-102673)

AFTA ij 1915

(6511)

2155

(19970)

2857

(3200)

2699

(19042)

2019

(34473)

exAFTA ij 0837

(7308)

1135

(23365)

1374

(26723)

1175

(14575)

0902

(30698)

imAFTA ij 0580

(5232)

0903

(19035)

0775

(15353)

0682

(8532)

0466

(1609)

Adjusted R2 0717 0748 0768 0763 0741

SEE 1572 1442 1442 1448 1506

Number of

observations

7888 9194 9822 3963 30867

Notes

1 T-values are in parentheses

2 denotes the coefficient is significant at 1 level denotes the coefficient is

significant at 5 level denotes the coefficient is significant at 10 level

3 The use of real GDP and export values is reported in the Table 52 which shows there

is little difference in the coefficients in the independent variables

26

Table 52

Empirical results of regression equation 3

based on real values of exports and GDP

Independent

Variables

1988-1992 1993-1997 1998-2002

2003-2004 1988-2004

Constant 3172

(17041)

2845

(1771)

0966

(5757)

0550

(200)

2293

(24637)

log real Yi 116

(94164)

1226

(107095)

1364

(98386)

1297

(59524)

123

(182883)

log real Yj 1020

(84573)

1011

(91405)

1216

(90191)

1184

(54681)

1072

(163403)

log Ni -0239

(-18510)

-0221

(-1994)

-0224

(-19115)

-0145

(-7989)

-02

(-31263)

log Nj -0127

(-977)

-0072

(-6594)

-0163

(-14186)

-0091

(-5049)

-0103

(-16203)

log Dij -0983

(-50598)

-1036

(-61676)

-0994

(-59109)

-0960

(-35959)

-0997

(-104061)

AFTA ij 1995

(679)

2174

(2016)

2859

(32014)

2707

(19101)

2200

(37693)

exAFTA ij 0914

(7984)

1143

(23365)

1374

(26712)

1179

(14630)

1025

(34982)

imAFTA ij 0657

(5936)

0911

(19224)

0778

(15404)

0686

(8584)

0586

(20301)

Adjusted R2 0718 0748 0767 0763 0744

SEE 157 144 1442 1446 1492

Number of

observations

7888 9194 9822 3963 30867

Notes `

1 T-values are in parentheses

2 denotes the coefficient is significant at 1 level denotes the coefficient is

significant at 5 level denotes the coefficient is significant at 10 level

3 For real GDP and export values year 2000 is used as base year

27

6 Implications and Recommendations

As China joins ASEAN Free Trade Agreement in January 2010 this creates changes on

the trade flow From the side of ASEAN this agreement helps ASEAN members to

access a prosperous Chinese market From Table 82 (Appendix) there is an increasing

trend of trade among AFTA and China during the period of 2004-2008 Both sides

consider each other as crucial trading partners As tariff barrier is removed after

formation of CAFTA this can increase intra regional trade among these countries and

reduce AFTA reliance on United States European Union and Japan (Chia 2004) With

countries of different stages of economic development integrated CAFTA can narrow

the income gap between member countries (Roberts 2004)

However empirical studies show mixed results As defined in Linder Hypothesis

countries with similar levels of income per capita will exhibit similar demand produce

similar and differentiated products and trade more with each other According to

empirical study conducted by Roberts (2004) the coefficient testing of the Linder

Hypothesis is insignificant which implies that CAFTA does not have similar demand

pattern and this can be supported by the classification of different stages of economic

development among the members Roberts (2004) noted that China Cambodia Laos

PDR Myanmar and Vietnam are Low Income economies Indonesia Thailand and

Philippines are Low Middle Income economies Singapore and Brunei Darussalam are

28

High Income Economies based on World Bankrsquos classification CAFTA creates an

enlarged market which increases in competition and investment (Chirathivat 2002)

Using SMART model Zhao Malouche and Newfarmer (2008) found out that there is

only a limited increase in intraregional trade and trade diversion when they assume full

liberalization of trade between China and ASEAN is implemented Chinarsquos imports

from ASEAN would increase by 72 especially from Singapore Thailand and

Malaysia On the other hand according to the simulation conducted by the ASEAN

Secretariat (2001) CAFTA would increase ASEANs exports to China and Chinese

export to ASEAN by 48 and 551 respectively (China amp World Economy 2003)

Although previous studies had mixed results CAFTA does provide a platform for China

and ASEAN to establish a legal system for trade investment and service that complies

with the rules of WTO and international standards This allows promotion of freer trade

and attracts investment from the foreign countries (Zhang 2006)

10

member countries needed to compete with new industrialized countries like China

South America and Eastern Europe After 1997 there was significant negative import

trade diversion effect as the AFTA members preferred to import goods from members

rather than nonmembers At the same time negative export trade diversion was

intensified as AFTA members preferred to export to nonmembers countries rather than

member countries Devaluation of ASEAN currencies during 1997 Asian financial crisis

was used to account for the results

Tang (2005) further extended the model used by Elliot and Ikemoto (2004) by adding

several interaction terms to examine the Linder hypothesis Since different independent

variables and dependent variables were used the result of Tang was slightly different

from Elliot and Ikemoto The dependent variable of Tangrsquos model was the export values

of country i and j and the one used in Elliot and Ikemoto was imports of country i from

trade partner j The result of Tang (2005) was similar to Elliot and Ikemoto (2004)

which concluded there was trade creation but no trade diversion effect Tang (2005)

found out that ASEAN countries have already increased their trade with the nonmember

countries even before the formation of AFTA as industrializing ASEAN countries

adopted an outward trade orientation Both of them found out that there was an increase

in intraregional trade in AFTA after the Asian financial crisis in 1997

When compared the study of Jugutnath Stewart and Brooks (2007) with literature listed

11

above this paper had an opposite view and suggested AFTA had no trade diversion and

trade creation effect during the period of 1980-2000 They noted ASEAN members had

similar characteristics and they preferred to trade more with other nonmember countries

based on the theory of comparative advantage

Contrary to the precious study that use econometric estimation Calvo-Pardo Freund

and Ornelas (2009) Cabalu and Alfonso (2007) adopted different approach in evaluating

trade effects of AFTA Both of them conclude that AFTA is trade creating rather than

diverting Calvo-Pardo Freund and Ornelas (2009) plotted the volumes of intra-AFTA

imports and imports from outside the bloc on the figures over the period of 13 years

before and after the formation of AFTA to measure the impacts They suggested the

effect of trade creation overrides trade diversion The rate of increase in imports with

members was always larger than that of nonmembers Cabalu and Alfonso (2007) used

shift and share analysis which investigated changes in values and pattern of commodity

groups between AFTA and non member countries to examine the net trade impact In

their results exports and imports of ASEAN had positive shares in its own market and

nonmember countries after its formation The category of machinery and transport

equipment had the largest gains in shares

Besides mixed result recent development of AFTA also plays a major role in affecting

trade pattern Since 1 January 2004 the CEPT Rules of Origin and its Operational

12

Certification Procedures have been improved and implemented These include (a) a

standardized method of calculating localASEAN content (b) a set of principles for

determining the cost of ASEAN origin and the guidelines for costing methodologies (c)

treatment of locally-procured materials and (d) improved verification process

including on-site verification (ASEAN Secretariat 2009) Starting from 1st August 2008

manufacturer can benefit from tariff concession if they used ASEAN content of less

than 40 percent (Arunmas 2008) This raises the question of whether trade is enhanced

under these new implementation programmes after the outbreak of SARS

With recent development of AFTA and mixed results the effects of trade creation and

diversion are not clearly defined in recent study In this paper gravity model provides

comprehensive and accurate estimation of trade effects after its formation and periods of

economic downturn in member and nonmember countries

13

4Methodology

41 Specification of Gravity Model

To estimate the intensity and transition of trade creation and trade diversion gravity

model is adopted because of its simplicity and explanatory power in assessing the

impacts of regional trading bloc The original Basic Gravity Model (BGM) which is

written by Tinbergen (1962) to analyze effects of economic integration specifies as

follows

Xij=βoYi

β1 Yj

β2 Dij

β3 εij (1)

Or using natural logarithms

log Xij = log β0 + β1 log Yi + β2 log Yj +β3 log Dij +logεij (2)

BGM states that volume of trade between two countries is determined by Gross

Domestic Product (GDP) that measures the size of the economies and distance between

them From equation 1 trade is proportional to the product of two countriesrsquo GDPs and

inversely related to distance between two countries

In order to find out the trade creation and diversion of AFTA BGM as listed above will

be further modified by including three regional institutional dummy variables This

modified gravity model will be estimated by Ordinary Least Square (OLS) from 1988 to

2004 for 46 countries as shown below

14

log Xij = log β0 + β1 log Yi + β2 log Yj +β3 log Ni +β4 log Nj +β5 log Dij + β6AFTAij +

β7exAFTAij + β8imAFTAij +logεij (3)

where Xij is the total US dollar value of exports from country i to j Yi Yj are nominal

values of gross domestic product of country i and j in US dollar Ni Nj are populations

of countries i and j Dij is the distance between countries i and j AFTAij is a dummy

variable which is 1 if two countries belong to AFTA and 0 otherwise exAFTAij is 1 if

only export country i belongs to AFTA and 0 otherwise imAFTAij is 1 if only the

import country j belongs to AFTA and 0 otherwise log ε ij is the log

normally-distributed error term

Common language and common border dummy variable which are two excluded

independent variables in our model will be discussed below They measure cultural

affinity and are expected to have positive relationship with trade If the two countries

have common language and border this makes trade easier and improves

communication with other countries Jugutnath Stewart and Brooks (2007) used official

language of a country to determine whether countries have same common languages

However this variable is difficult to delineate because different country has their dialect

and English has been widely used for communication Secondly common border is

excluded because some countries like Japan Australia Indonesia Iceland and United

Kingdom which are included in our data set are an island They do not have any

15

common border with other countries In order to improve the stability of our model

these two variables are excluded

42 Expectation of Results

In the regression equation 3 expectations of explanatory variables are listed as follows

The expected signs of independent variables Yi and Yj are positive Large economies

tend to spend large amount on imports because they have high income As they produce

a wide range of products this attracts other countries to spend on their production as

well In our model nominal GDP is employed If real GDP is used to replace the

nominal one there will be only a small difference in the coefficient of determination

(Linnemann 1966) This result is shown in the Table 52

The coefficient of Ni and Nj are uncertain Nguyen (2009) states that the coefficient are

expected to be negative because countries that have large population will have larger

resource endowment This absorption effect causes less dependence on international

specialization This will lead to a fall in trade between countries On the other hand

they are expected to be positive means a larger population means a larger domestic

market This in turn exploits economies of scale and the country will trade more with

foreign partner with a wider range of goods

The expected sign of variable Dij is negative because the greater the distance between

16

country i and j increases transportation costs time required for delivery and

communication failures Volume of trade between two countries is inversely correlated

with distance

In addition there are different expectations for coefficients of AFTAij exAFTAij and

imAFTAij AFTAij is expected to be positive and reflects the creation effect of

intraregional trade due to reduction of tariff rates and elimination of non tariff barriers

among AFTA This indicates members of AFTA have trade more with its members than

hypothetical trade level Dummy variables exAFTAij and imAFTAij captures the ldquoexport

trade diversionrdquo and ldquoimport trade diversionrdquo respectively The formation of Free Trade

Area is expected to lead to a decline of trade among member countries and nonmembers

countries (Tang 2005) Endoh (1999) who coined the term ldquoexport trade diversionrdquo

states that negative and statically significant coefficient of exAFTAij indicates that this

economic integration has caused the member countries to export their products within

the bloc rather than those outside the bloc For imAFTAij if its coefficient is negative

and statistically significant this means the members have switched their importing

activities from nonmembers to members

43 Data Description and Sources

To compare the impacts of AFTA overtime in addition to the pooled data of 1988-2004

17

the data is divided into four periods ie 1988-1992 1993-1997 1998-2002 and

2003-2004 Concerning the first breakdown of 1988-1992 and 1993-1997 this can

examine the changes in the trade flow between the member and nonmember countries

before and after the formation of AFTA For the division of 1993-1997 and 1998-2002

this can test whether the trade flow was adversely affected by 1997 Asian Financial

Crisis For 1998-2002 and 2003-2004 this can explain whether Outbreak of SARS had

adverse impacts on trade in Asian economies

The data set covers the bilateral trade flow for 46 countries They include 10 members

of AFTA and 36 nonmember countries The nonmember countries include Austria

Belgium-Luxembourg Finland France Germany Ireland Italy Netherlands Portugal

Spain Denmark Sweden United Kingdom Algeria Argentina Australia Brazil

Canada Chile China Colombia Czech Republic Egypt Japan Hong Kong Iceland

India Iran Mexico Norway New Zealand Poland Russia South Korea Switzerland

and the United States

For the dependent variable the annual export data are extracted from the Direction of

Trade Statistics GDP and population are obtained from The World Economic Outlook

and International Financial Statistics All export values and GDP are in US million

dollars Distance is collected from the Great Circle Distance between Cities The

physical distance is measured by the capital cities of 46 member and nonmember

18

countries in kilometers The values of AFTAij exAFTAij and imAFTAij depend on

countries that paired in the observations The number of observation for the pooled

sample is 30867 Some of the data are not available in the data base especially for

period of 1980s in developing countries

19

5 Empirical Results

Ordinary Least Square result for regression equation 3 is presented in Table 51 The

values of adjusted coefficient of determination in 1988-1992 and 1993-1997 are 0717

and 0748 respectively For 1998-2002 and 2003-2004 values of adjusted coefficient of

determination are 0768 and 0763 This means over 70 variation of export values

between country i and country j around its mean can be explained by the independent

variables in regression equation 3 adjusted for degree of freedom

51 Explanation of Gravity Model

All estimated coefficient are statistically significant different from zero at 1 level of

significance The coefficient of Yi Yj and Dij fulfill our expectations as stated in the

gravity model This shows gravity model plays a major role in explaining pattern of

trade flow in modern society Trade is positively related to GDP Larger economies tend

to have higher demand for imports and produce larger amount of goods for exports

Similar to the results of Endoh (1999) the coefficient of population is negative which

means increase in population will cause a decline in trade as the country produces a

wider range of product

The coefficient of Dij is negative and statistically significant Although there are

improvements in transportation technologies which can reduce the transportation cost

20

and facilitate transportation of goods between both importing and exporting countries

over time distance between countries still remains one of the most important

determinants in trade activities

52 Intraregional trade bias in AFTA

The coefficients of AFTA ij are positive and statistically significant It increases from

1915 in 1988-1992 to 2155 in 1993-1997 This shows there is trade creation effect

after the formation of AFTA This is consistent with the previous study like Tang (2005)

and Thornton and Goglio (2002) The low tariff rate facilitates trade in AFTA

After the 1997 Asian Financial Crisis the poor economic performance did not inhibited

the member countries to export goods to each other as there is a sharp jump in this

coefficient to 2857 New admission of Lao PDR and Myanmar in 1997 stimulated trade

creation effects Average regional CEPT rate for products in the Inclusion List has

dropped from 1276 in 1993 to 505 in 1998 (Jr Yee and Azhari 1998) Elliot and

Ikemoto (2004) pointed out that this regional economic shock in the form of currency

crisis created latent forces institutionalizing interdependence within the bloc

On the contrary after outbreak of SARS in 2003 the coefficient of AFTAij decreases to

2699 To further explain SARS is a highly infectious respiratory disease that had

caused doom in East Asian economies Within AFTA Singapore and Vietnam were hard

21

hit by SARS People tend to avoid social interaction which led to a slump in business

transactions The unemployment rate increased and demand for goods and services fell

Although a new arrangement of CEPT Rules of Origin and Operational Certification

Procedures which could promote trade among AFTA has been implemented on 1

January 2004 intraregional trade had declined In addition rise of trade among

nonmember countries could explain this decline As China has formally entered into

WTO in 2001 exports of ASEAN countries need to compete with Chinese products in

both export and ASEAN domestic market and ASEAN exporters would lose their

comparative advantage when developed countries give tariff concessions to China

(Kwan and Qiu 2003)

53 Export and Import Trade Diversion between member and non member countries

Finally the dummy variables of exAFTA ij and imAFTA ij have signs opposite to our

expectations They are statistically significant at 1 level of significance The positive

sign of exAFTA ij and imAFTA ij indicate that members and nonmembers have traded

with each other to greater extent than the hypothetical trade level throughout 1988-2004

(Endoh 1999) The results indicate negative trade diversion effect in AFTA

The coefficient of exAFTAij has a continuous increase from 0837 in 1988-1992 to

1135 in 1993-1997 The positive sign of this coefficient implies that the member

22

countries prefer to export goods to nonmember rather than members after the formation

of AFTA This implies AFTA members adopted export oriented strategies that promoted

export (Nguyen 2009)

The coefficient of exAFTAij increases to 1374 after 1997 The upward trend in

exAFTAij shows there is strengthening of negative export trade diversion throughout the

period of 1992-2002 The model of Elliot and Ikemoto (2004) also had similar results

and further explained the sharp jump in exAFTAij is caused by the devaluation of

ASEAN currencies after 1997 Asian Financial crisis as shown in Figure 81 (Appendix)

This could increase the competitiveness of ASEAN exports since they were relatively

cheaper when compared with the products of nonmember countries This boosted

ASEAN export trade with nonmembers

After the outbreak of SARS exAFTAij coefficient falls to 1175 in the period 2003-2004

which means there is weakening of negative trade diversion The outbreak of SARS has

caused temporary shock and persistent shock to Hong Kong and Chinese economies

Lee (2004) suggested that SARS led to a loss of GDP Hong Kong which was seriously

affected has experienced a decline in GDP by 263 GDP of Taiwan and Singapore

also were decreased by 049 and 047 respectively This reduction showed there was

a fall in demand for goods and services of ASEAN countries This could also be

explained by the slight appreciation of ASEAN currency after 2002 Value of ASEAN

23

currency increased relative to other foreign countries and ASEAN products were

relatively more expensive Therefore AFTA members prefer to export their goods to

members rather than nonmembers

The dummy variable imAFTAij measures import trade diversion of AFTA Its

coefficient increases from 058 in 1988-1992 to 0903 in 1993-1997 The upward trend

reveals that dynamic network of domestic production and foreign investment projects in

AFTA members caused a rise in its imports from nonmember countries (Nguyen 2009)

This fall in imAFTA ij after 1997 Asian Financial Crisis and outbreak of SARS implies

there is a weakening of negative import trade diversion ASEAN prefer to import goods

from members rather than nonmembers but the effects are small relative to the

coefficient of AFTAij As explained before devaluation of ASEAN currency means

foreign goods are more expensive So they prefer to import from members After the

outbreak of SARS the coefficient of imAFTA ij further drops to 0682 Spread of

diseases generated negative impacts to economies in Hong Kong and China which are

major trading partners of AFTA These two countries had the highest probable cases of

SARS This is one of the reasons why AFTA members prefer to import more goods

from members rather than nonmembers

Trade creation and diversion are subjected to changes in external economic environment

AFTA strengthened cooperation with all member countries in 1997 Asian Financial

24

Crisis and urged the members to undertake policy to promote trade which can in turn

speed up economic recovery When compared with outbreak of SARS which caused an

economic downturn in nonmember countries AFTA demonstrates an economic

regionalism that united members in the bloc As shown in the econometric results

AFTA members prefer to trade more among themselves rather than nonmembers

To a certain extent exchange rate volatility did not play a significant role in affecting

trade Most of economies in East Asia adopt a ldquomanaged floatrdquo exchange rate policy

which is beneficial to accomplish economic goals and objectives (Martin 2008) The

2SLS results of Tang (2005) shows that coefficient of exchange rate volatility is positive

which is opposite to our expectation but it is statically insignificant in the pooled sample

Although this coefficient is negative in OLS estimation overall effects of exchange rate

volatility on trade has reduced over time Tang (2005) further suggested two reasons

attributable to this phenomenon after 1997 Firstly the restructuring of financial sectors

like implementation of pegged exchange rate system and transaction of currency option

and contract lead to improvements which can avoid similar crisis in future Secondly

financial system of developed countries are so well organized that stock market and

banking operation are less vulnerable to exchange rate fluctuation

In Table 52 real values of GDP and exports replaced the nominal one in regression

equation 3 Similar results and conclusions could be drawn

25

Table 51

Empirical results of regression equation 3

based on nominal values of exports and GDP

Independent

Variables

1988-1992 1993-1997 1998-2002 2003-2004 1988-2004

Constant 3438

(18597)

2974

(1857)

0966

(5753)

0457

(1653)

2569

(2755)

log Yi 1157

(93901)

1222

(10687)

1364

(98397)

1295

(59454)

1203

(179786)

log Yj 1016

(84303)

1008

(91165)

1215

(90192)

1182

(54609)

1046

(160182)

log Ni -0238

(-18409)

-0219

(-19762)

-0224

(-19141)

-0144

(-7936)

-0187

(-29098)

log Nj -0125

(-9624)

-0071

(-6442)

-0163

(-14185)

-009

(-499)

-0090

(-14138)

log Dij -0983

(-50493)

-1036

(-61597)

-0994

(-59095)

-0961

(-35954)

-0993

(-102673)

AFTA ij 1915

(6511)

2155

(19970)

2857

(3200)

2699

(19042)

2019

(34473)

exAFTA ij 0837

(7308)

1135

(23365)

1374

(26723)

1175

(14575)

0902

(30698)

imAFTA ij 0580

(5232)

0903

(19035)

0775

(15353)

0682

(8532)

0466

(1609)

Adjusted R2 0717 0748 0768 0763 0741

SEE 1572 1442 1442 1448 1506

Number of

observations

7888 9194 9822 3963 30867

Notes

1 T-values are in parentheses

2 denotes the coefficient is significant at 1 level denotes the coefficient is

significant at 5 level denotes the coefficient is significant at 10 level

3 The use of real GDP and export values is reported in the Table 52 which shows there

is little difference in the coefficients in the independent variables

26

Table 52

Empirical results of regression equation 3

based on real values of exports and GDP

Independent

Variables

1988-1992 1993-1997 1998-2002

2003-2004 1988-2004

Constant 3172

(17041)

2845

(1771)

0966

(5757)

0550

(200)

2293

(24637)

log real Yi 116

(94164)

1226

(107095)

1364

(98386)

1297

(59524)

123

(182883)

log real Yj 1020

(84573)

1011

(91405)

1216

(90191)

1184

(54681)

1072

(163403)

log Ni -0239

(-18510)

-0221

(-1994)

-0224

(-19115)

-0145

(-7989)

-02

(-31263)

log Nj -0127

(-977)

-0072

(-6594)

-0163

(-14186)

-0091

(-5049)

-0103

(-16203)

log Dij -0983

(-50598)

-1036

(-61676)

-0994

(-59109)

-0960

(-35959)

-0997

(-104061)

AFTA ij 1995

(679)

2174

(2016)

2859

(32014)

2707

(19101)

2200

(37693)

exAFTA ij 0914

(7984)

1143

(23365)

1374

(26712)

1179

(14630)

1025

(34982)

imAFTA ij 0657

(5936)

0911

(19224)

0778

(15404)

0686

(8584)

0586

(20301)

Adjusted R2 0718 0748 0767 0763 0744

SEE 157 144 1442 1446 1492

Number of

observations

7888 9194 9822 3963 30867

Notes `

1 T-values are in parentheses

2 denotes the coefficient is significant at 1 level denotes the coefficient is

significant at 5 level denotes the coefficient is significant at 10 level

3 For real GDP and export values year 2000 is used as base year

27

6 Implications and Recommendations

As China joins ASEAN Free Trade Agreement in January 2010 this creates changes on

the trade flow From the side of ASEAN this agreement helps ASEAN members to

access a prosperous Chinese market From Table 82 (Appendix) there is an increasing

trend of trade among AFTA and China during the period of 2004-2008 Both sides

consider each other as crucial trading partners As tariff barrier is removed after

formation of CAFTA this can increase intra regional trade among these countries and

reduce AFTA reliance on United States European Union and Japan (Chia 2004) With

countries of different stages of economic development integrated CAFTA can narrow

the income gap between member countries (Roberts 2004)

However empirical studies show mixed results As defined in Linder Hypothesis

countries with similar levels of income per capita will exhibit similar demand produce

similar and differentiated products and trade more with each other According to

empirical study conducted by Roberts (2004) the coefficient testing of the Linder

Hypothesis is insignificant which implies that CAFTA does not have similar demand

pattern and this can be supported by the classification of different stages of economic

development among the members Roberts (2004) noted that China Cambodia Laos

PDR Myanmar and Vietnam are Low Income economies Indonesia Thailand and

Philippines are Low Middle Income economies Singapore and Brunei Darussalam are

28

High Income Economies based on World Bankrsquos classification CAFTA creates an

enlarged market which increases in competition and investment (Chirathivat 2002)

Using SMART model Zhao Malouche and Newfarmer (2008) found out that there is

only a limited increase in intraregional trade and trade diversion when they assume full

liberalization of trade between China and ASEAN is implemented Chinarsquos imports

from ASEAN would increase by 72 especially from Singapore Thailand and

Malaysia On the other hand according to the simulation conducted by the ASEAN

Secretariat (2001) CAFTA would increase ASEANs exports to China and Chinese

export to ASEAN by 48 and 551 respectively (China amp World Economy 2003)

Although previous studies had mixed results CAFTA does provide a platform for China

and ASEAN to establish a legal system for trade investment and service that complies

with the rules of WTO and international standards This allows promotion of freer trade

and attracts investment from the foreign countries (Zhang 2006)

11

above this paper had an opposite view and suggested AFTA had no trade diversion and

trade creation effect during the period of 1980-2000 They noted ASEAN members had

similar characteristics and they preferred to trade more with other nonmember countries

based on the theory of comparative advantage

Contrary to the precious study that use econometric estimation Calvo-Pardo Freund

and Ornelas (2009) Cabalu and Alfonso (2007) adopted different approach in evaluating

trade effects of AFTA Both of them conclude that AFTA is trade creating rather than

diverting Calvo-Pardo Freund and Ornelas (2009) plotted the volumes of intra-AFTA

imports and imports from outside the bloc on the figures over the period of 13 years

before and after the formation of AFTA to measure the impacts They suggested the

effect of trade creation overrides trade diversion The rate of increase in imports with

members was always larger than that of nonmembers Cabalu and Alfonso (2007) used

shift and share analysis which investigated changes in values and pattern of commodity

groups between AFTA and non member countries to examine the net trade impact In

their results exports and imports of ASEAN had positive shares in its own market and

nonmember countries after its formation The category of machinery and transport

equipment had the largest gains in shares

Besides mixed result recent development of AFTA also plays a major role in affecting

trade pattern Since 1 January 2004 the CEPT Rules of Origin and its Operational

12

Certification Procedures have been improved and implemented These include (a) a

standardized method of calculating localASEAN content (b) a set of principles for

determining the cost of ASEAN origin and the guidelines for costing methodologies (c)

treatment of locally-procured materials and (d) improved verification process

including on-site verification (ASEAN Secretariat 2009) Starting from 1st August 2008

manufacturer can benefit from tariff concession if they used ASEAN content of less

than 40 percent (Arunmas 2008) This raises the question of whether trade is enhanced

under these new implementation programmes after the outbreak of SARS

With recent development of AFTA and mixed results the effects of trade creation and

diversion are not clearly defined in recent study In this paper gravity model provides

comprehensive and accurate estimation of trade effects after its formation and periods of

economic downturn in member and nonmember countries

13

4Methodology

41 Specification of Gravity Model

To estimate the intensity and transition of trade creation and trade diversion gravity

model is adopted because of its simplicity and explanatory power in assessing the

impacts of regional trading bloc The original Basic Gravity Model (BGM) which is

written by Tinbergen (1962) to analyze effects of economic integration specifies as

follows

Xij=βoYi

β1 Yj

β2 Dij

β3 εij (1)

Or using natural logarithms

log Xij = log β0 + β1 log Yi + β2 log Yj +β3 log Dij +logεij (2)

BGM states that volume of trade between two countries is determined by Gross

Domestic Product (GDP) that measures the size of the economies and distance between

them From equation 1 trade is proportional to the product of two countriesrsquo GDPs and

inversely related to distance between two countries

In order to find out the trade creation and diversion of AFTA BGM as listed above will

be further modified by including three regional institutional dummy variables This

modified gravity model will be estimated by Ordinary Least Square (OLS) from 1988 to

2004 for 46 countries as shown below

14

log Xij = log β0 + β1 log Yi + β2 log Yj +β3 log Ni +β4 log Nj +β5 log Dij + β6AFTAij +

β7exAFTAij + β8imAFTAij +logεij (3)

where Xij is the total US dollar value of exports from country i to j Yi Yj are nominal

values of gross domestic product of country i and j in US dollar Ni Nj are populations

of countries i and j Dij is the distance between countries i and j AFTAij is a dummy

variable which is 1 if two countries belong to AFTA and 0 otherwise exAFTAij is 1 if

only export country i belongs to AFTA and 0 otherwise imAFTAij is 1 if only the

import country j belongs to AFTA and 0 otherwise log ε ij is the log

normally-distributed error term

Common language and common border dummy variable which are two excluded

independent variables in our model will be discussed below They measure cultural

affinity and are expected to have positive relationship with trade If the two countries

have common language and border this makes trade easier and improves

communication with other countries Jugutnath Stewart and Brooks (2007) used official

language of a country to determine whether countries have same common languages

However this variable is difficult to delineate because different country has their dialect

and English has been widely used for communication Secondly common border is

excluded because some countries like Japan Australia Indonesia Iceland and United

Kingdom which are included in our data set are an island They do not have any

15

common border with other countries In order to improve the stability of our model

these two variables are excluded

42 Expectation of Results

In the regression equation 3 expectations of explanatory variables are listed as follows

The expected signs of independent variables Yi and Yj are positive Large economies

tend to spend large amount on imports because they have high income As they produce

a wide range of products this attracts other countries to spend on their production as

well In our model nominal GDP is employed If real GDP is used to replace the

nominal one there will be only a small difference in the coefficient of determination

(Linnemann 1966) This result is shown in the Table 52

The coefficient of Ni and Nj are uncertain Nguyen (2009) states that the coefficient are

expected to be negative because countries that have large population will have larger

resource endowment This absorption effect causes less dependence on international

specialization This will lead to a fall in trade between countries On the other hand

they are expected to be positive means a larger population means a larger domestic

market This in turn exploits economies of scale and the country will trade more with

foreign partner with a wider range of goods

The expected sign of variable Dij is negative because the greater the distance between

16

country i and j increases transportation costs time required for delivery and

communication failures Volume of trade between two countries is inversely correlated

with distance

In addition there are different expectations for coefficients of AFTAij exAFTAij and

imAFTAij AFTAij is expected to be positive and reflects the creation effect of

intraregional trade due to reduction of tariff rates and elimination of non tariff barriers

among AFTA This indicates members of AFTA have trade more with its members than

hypothetical trade level Dummy variables exAFTAij and imAFTAij captures the ldquoexport

trade diversionrdquo and ldquoimport trade diversionrdquo respectively The formation of Free Trade

Area is expected to lead to a decline of trade among member countries and nonmembers

countries (Tang 2005) Endoh (1999) who coined the term ldquoexport trade diversionrdquo

states that negative and statically significant coefficient of exAFTAij indicates that this

economic integration has caused the member countries to export their products within

the bloc rather than those outside the bloc For imAFTAij if its coefficient is negative

and statistically significant this means the members have switched their importing

activities from nonmembers to members

43 Data Description and Sources

To compare the impacts of AFTA overtime in addition to the pooled data of 1988-2004

17

the data is divided into four periods ie 1988-1992 1993-1997 1998-2002 and

2003-2004 Concerning the first breakdown of 1988-1992 and 1993-1997 this can

examine the changes in the trade flow between the member and nonmember countries

before and after the formation of AFTA For the division of 1993-1997 and 1998-2002

this can test whether the trade flow was adversely affected by 1997 Asian Financial

Crisis For 1998-2002 and 2003-2004 this can explain whether Outbreak of SARS had

adverse impacts on trade in Asian economies

The data set covers the bilateral trade flow for 46 countries They include 10 members

of AFTA and 36 nonmember countries The nonmember countries include Austria

Belgium-Luxembourg Finland France Germany Ireland Italy Netherlands Portugal

Spain Denmark Sweden United Kingdom Algeria Argentina Australia Brazil

Canada Chile China Colombia Czech Republic Egypt Japan Hong Kong Iceland

India Iran Mexico Norway New Zealand Poland Russia South Korea Switzerland

and the United States

For the dependent variable the annual export data are extracted from the Direction of

Trade Statistics GDP and population are obtained from The World Economic Outlook

and International Financial Statistics All export values and GDP are in US million

dollars Distance is collected from the Great Circle Distance between Cities The

physical distance is measured by the capital cities of 46 member and nonmember

18

countries in kilometers The values of AFTAij exAFTAij and imAFTAij depend on

countries that paired in the observations The number of observation for the pooled

sample is 30867 Some of the data are not available in the data base especially for

period of 1980s in developing countries

19

5 Empirical Results

Ordinary Least Square result for regression equation 3 is presented in Table 51 The

values of adjusted coefficient of determination in 1988-1992 and 1993-1997 are 0717

and 0748 respectively For 1998-2002 and 2003-2004 values of adjusted coefficient of

determination are 0768 and 0763 This means over 70 variation of export values

between country i and country j around its mean can be explained by the independent

variables in regression equation 3 adjusted for degree of freedom

51 Explanation of Gravity Model

All estimated coefficient are statistically significant different from zero at 1 level of

significance The coefficient of Yi Yj and Dij fulfill our expectations as stated in the

gravity model This shows gravity model plays a major role in explaining pattern of

trade flow in modern society Trade is positively related to GDP Larger economies tend

to have higher demand for imports and produce larger amount of goods for exports

Similar to the results of Endoh (1999) the coefficient of population is negative which

means increase in population will cause a decline in trade as the country produces a

wider range of product

The coefficient of Dij is negative and statistically significant Although there are

improvements in transportation technologies which can reduce the transportation cost

20

and facilitate transportation of goods between both importing and exporting countries

over time distance between countries still remains one of the most important

determinants in trade activities

52 Intraregional trade bias in AFTA

The coefficients of AFTA ij are positive and statistically significant It increases from

1915 in 1988-1992 to 2155 in 1993-1997 This shows there is trade creation effect

after the formation of AFTA This is consistent with the previous study like Tang (2005)

and Thornton and Goglio (2002) The low tariff rate facilitates trade in AFTA

After the 1997 Asian Financial Crisis the poor economic performance did not inhibited

the member countries to export goods to each other as there is a sharp jump in this

coefficient to 2857 New admission of Lao PDR and Myanmar in 1997 stimulated trade

creation effects Average regional CEPT rate for products in the Inclusion List has

dropped from 1276 in 1993 to 505 in 1998 (Jr Yee and Azhari 1998) Elliot and

Ikemoto (2004) pointed out that this regional economic shock in the form of currency

crisis created latent forces institutionalizing interdependence within the bloc

On the contrary after outbreak of SARS in 2003 the coefficient of AFTAij decreases to

2699 To further explain SARS is a highly infectious respiratory disease that had

caused doom in East Asian economies Within AFTA Singapore and Vietnam were hard

21

hit by SARS People tend to avoid social interaction which led to a slump in business

transactions The unemployment rate increased and demand for goods and services fell

Although a new arrangement of CEPT Rules of Origin and Operational Certification

Procedures which could promote trade among AFTA has been implemented on 1

January 2004 intraregional trade had declined In addition rise of trade among

nonmember countries could explain this decline As China has formally entered into

WTO in 2001 exports of ASEAN countries need to compete with Chinese products in

both export and ASEAN domestic market and ASEAN exporters would lose their

comparative advantage when developed countries give tariff concessions to China

(Kwan and Qiu 2003)

53 Export and Import Trade Diversion between member and non member countries

Finally the dummy variables of exAFTA ij and imAFTA ij have signs opposite to our

expectations They are statistically significant at 1 level of significance The positive

sign of exAFTA ij and imAFTA ij indicate that members and nonmembers have traded

with each other to greater extent than the hypothetical trade level throughout 1988-2004

(Endoh 1999) The results indicate negative trade diversion effect in AFTA

The coefficient of exAFTAij has a continuous increase from 0837 in 1988-1992 to

1135 in 1993-1997 The positive sign of this coefficient implies that the member

22

countries prefer to export goods to nonmember rather than members after the formation

of AFTA This implies AFTA members adopted export oriented strategies that promoted

export (Nguyen 2009)

The coefficient of exAFTAij increases to 1374 after 1997 The upward trend in

exAFTAij shows there is strengthening of negative export trade diversion throughout the

period of 1992-2002 The model of Elliot and Ikemoto (2004) also had similar results

and further explained the sharp jump in exAFTAij is caused by the devaluation of

ASEAN currencies after 1997 Asian Financial crisis as shown in Figure 81 (Appendix)

This could increase the competitiveness of ASEAN exports since they were relatively

cheaper when compared with the products of nonmember countries This boosted

ASEAN export trade with nonmembers

After the outbreak of SARS exAFTAij coefficient falls to 1175 in the period 2003-2004

which means there is weakening of negative trade diversion The outbreak of SARS has

caused temporary shock and persistent shock to Hong Kong and Chinese economies

Lee (2004) suggested that SARS led to a loss of GDP Hong Kong which was seriously

affected has experienced a decline in GDP by 263 GDP of Taiwan and Singapore

also were decreased by 049 and 047 respectively This reduction showed there was

a fall in demand for goods and services of ASEAN countries This could also be

explained by the slight appreciation of ASEAN currency after 2002 Value of ASEAN

23

currency increased relative to other foreign countries and ASEAN products were

relatively more expensive Therefore AFTA members prefer to export their goods to

members rather than nonmembers

The dummy variable imAFTAij measures import trade diversion of AFTA Its

coefficient increases from 058 in 1988-1992 to 0903 in 1993-1997 The upward trend

reveals that dynamic network of domestic production and foreign investment projects in

AFTA members caused a rise in its imports from nonmember countries (Nguyen 2009)

This fall in imAFTA ij after 1997 Asian Financial Crisis and outbreak of SARS implies

there is a weakening of negative import trade diversion ASEAN prefer to import goods

from members rather than nonmembers but the effects are small relative to the

coefficient of AFTAij As explained before devaluation of ASEAN currency means

foreign goods are more expensive So they prefer to import from members After the

outbreak of SARS the coefficient of imAFTA ij further drops to 0682 Spread of

diseases generated negative impacts to economies in Hong Kong and China which are

major trading partners of AFTA These two countries had the highest probable cases of

SARS This is one of the reasons why AFTA members prefer to import more goods

from members rather than nonmembers

Trade creation and diversion are subjected to changes in external economic environment

AFTA strengthened cooperation with all member countries in 1997 Asian Financial

24

Crisis and urged the members to undertake policy to promote trade which can in turn

speed up economic recovery When compared with outbreak of SARS which caused an

economic downturn in nonmember countries AFTA demonstrates an economic

regionalism that united members in the bloc As shown in the econometric results

AFTA members prefer to trade more among themselves rather than nonmembers

To a certain extent exchange rate volatility did not play a significant role in affecting

trade Most of economies in East Asia adopt a ldquomanaged floatrdquo exchange rate policy

which is beneficial to accomplish economic goals and objectives (Martin 2008) The

2SLS results of Tang (2005) shows that coefficient of exchange rate volatility is positive

which is opposite to our expectation but it is statically insignificant in the pooled sample

Although this coefficient is negative in OLS estimation overall effects of exchange rate

volatility on trade has reduced over time Tang (2005) further suggested two reasons

attributable to this phenomenon after 1997 Firstly the restructuring of financial sectors

like implementation of pegged exchange rate system and transaction of currency option

and contract lead to improvements which can avoid similar crisis in future Secondly

financial system of developed countries are so well organized that stock market and

banking operation are less vulnerable to exchange rate fluctuation

In Table 52 real values of GDP and exports replaced the nominal one in regression

equation 3 Similar results and conclusions could be drawn

25

Table 51

Empirical results of regression equation 3

based on nominal values of exports and GDP

Independent

Variables

1988-1992 1993-1997 1998-2002 2003-2004 1988-2004

Constant 3438

(18597)

2974

(1857)

0966

(5753)

0457

(1653)

2569

(2755)

log Yi 1157

(93901)

1222

(10687)

1364

(98397)

1295

(59454)

1203

(179786)

log Yj 1016

(84303)

1008

(91165)

1215

(90192)

1182

(54609)

1046

(160182)

log Ni -0238

(-18409)

-0219

(-19762)

-0224

(-19141)

-0144

(-7936)

-0187

(-29098)

log Nj -0125

(-9624)

-0071

(-6442)

-0163

(-14185)

-009

(-499)

-0090

(-14138)

log Dij -0983

(-50493)

-1036

(-61597)

-0994

(-59095)

-0961

(-35954)

-0993

(-102673)

AFTA ij 1915

(6511)

2155

(19970)

2857

(3200)

2699

(19042)

2019

(34473)

exAFTA ij 0837

(7308)

1135

(23365)

1374

(26723)

1175

(14575)

0902

(30698)

imAFTA ij 0580

(5232)

0903

(19035)

0775

(15353)

0682

(8532)

0466

(1609)

Adjusted R2 0717 0748 0768 0763 0741

SEE 1572 1442 1442 1448 1506

Number of

observations

7888 9194 9822 3963 30867

Notes

1 T-values are in parentheses

2 denotes the coefficient is significant at 1 level denotes the coefficient is

significant at 5 level denotes the coefficient is significant at 10 level

3 The use of real GDP and export values is reported in the Table 52 which shows there

is little difference in the coefficients in the independent variables

26

Table 52

Empirical results of regression equation 3

based on real values of exports and GDP

Independent

Variables

1988-1992 1993-1997 1998-2002

2003-2004 1988-2004

Constant 3172

(17041)

2845

(1771)

0966

(5757)

0550

(200)

2293

(24637)

log real Yi 116

(94164)

1226

(107095)

1364

(98386)

1297

(59524)

123

(182883)

log real Yj 1020

(84573)

1011

(91405)

1216

(90191)

1184

(54681)

1072

(163403)

log Ni -0239

(-18510)

-0221

(-1994)

-0224

(-19115)

-0145

(-7989)

-02

(-31263)

log Nj -0127

(-977)

-0072

(-6594)

-0163

(-14186)

-0091

(-5049)

-0103

(-16203)

log Dij -0983

(-50598)

-1036

(-61676)

-0994

(-59109)

-0960

(-35959)

-0997

(-104061)

AFTA ij 1995

(679)

2174

(2016)

2859

(32014)

2707

(19101)

2200

(37693)

exAFTA ij 0914

(7984)

1143

(23365)

1374

(26712)

1179

(14630)

1025

(34982)

imAFTA ij 0657

(5936)

0911

(19224)

0778

(15404)

0686

(8584)

0586

(20301)

Adjusted R2 0718 0748 0767 0763 0744

SEE 157 144 1442 1446 1492

Number of

observations

7888 9194 9822 3963 30867

Notes `

1 T-values are in parentheses

2 denotes the coefficient is significant at 1 level denotes the coefficient is

significant at 5 level denotes the coefficient is significant at 10 level

3 For real GDP and export values year 2000 is used as base year

27

6 Implications and Recommendations

As China joins ASEAN Free Trade Agreement in January 2010 this creates changes on

the trade flow From the side of ASEAN this agreement helps ASEAN members to

access a prosperous Chinese market From Table 82 (Appendix) there is an increasing

trend of trade among AFTA and China during the period of 2004-2008 Both sides

consider each other as crucial trading partners As tariff barrier is removed after

formation of CAFTA this can increase intra regional trade among these countries and

reduce AFTA reliance on United States European Union and Japan (Chia 2004) With

countries of different stages of economic development integrated CAFTA can narrow

the income gap between member countries (Roberts 2004)

However empirical studies show mixed results As defined in Linder Hypothesis

countries with similar levels of income per capita will exhibit similar demand produce

similar and differentiated products and trade more with each other According to

empirical study conducted by Roberts (2004) the coefficient testing of the Linder

Hypothesis is insignificant which implies that CAFTA does not have similar demand

pattern and this can be supported by the classification of different stages of economic

development among the members Roberts (2004) noted that China Cambodia Laos

PDR Myanmar and Vietnam are Low Income economies Indonesia Thailand and

Philippines are Low Middle Income economies Singapore and Brunei Darussalam are

28

High Income Economies based on World Bankrsquos classification CAFTA creates an

enlarged market which increases in competition and investment (Chirathivat 2002)

Using SMART model Zhao Malouche and Newfarmer (2008) found out that there is

only a limited increase in intraregional trade and trade diversion when they assume full

liberalization of trade between China and ASEAN is implemented Chinarsquos imports

from ASEAN would increase by 72 especially from Singapore Thailand and

Malaysia On the other hand according to the simulation conducted by the ASEAN

Secretariat (2001) CAFTA would increase ASEANs exports to China and Chinese

export to ASEAN by 48 and 551 respectively (China amp World Economy 2003)

Although previous studies had mixed results CAFTA does provide a platform for China

and ASEAN to establish a legal system for trade investment and service that complies

with the rules of WTO and international standards This allows promotion of freer trade

and attracts investment from the foreign countries (Zhang 2006)

12

Certification Procedures have been improved and implemented These include (a) a

standardized method of calculating localASEAN content (b) a set of principles for

determining the cost of ASEAN origin and the guidelines for costing methodologies (c)

treatment of locally-procured materials and (d) improved verification process

including on-site verification (ASEAN Secretariat 2009) Starting from 1st August 2008

manufacturer can benefit from tariff concession if they used ASEAN content of less

than 40 percent (Arunmas 2008) This raises the question of whether trade is enhanced

under these new implementation programmes after the outbreak of SARS

With recent development of AFTA and mixed results the effects of trade creation and

diversion are not clearly defined in recent study In this paper gravity model provides

comprehensive and accurate estimation of trade effects after its formation and periods of

economic downturn in member and nonmember countries

13

4Methodology

41 Specification of Gravity Model

To estimate the intensity and transition of trade creation and trade diversion gravity

model is adopted because of its simplicity and explanatory power in assessing the

impacts of regional trading bloc The original Basic Gravity Model (BGM) which is

written by Tinbergen (1962) to analyze effects of economic integration specifies as

follows

Xij=βoYi

β1 Yj

β2 Dij

β3 εij (1)

Or using natural logarithms

log Xij = log β0 + β1 log Yi + β2 log Yj +β3 log Dij +logεij (2)

BGM states that volume of trade between two countries is determined by Gross

Domestic Product (GDP) that measures the size of the economies and distance between

them From equation 1 trade is proportional to the product of two countriesrsquo GDPs and

inversely related to distance between two countries

In order to find out the trade creation and diversion of AFTA BGM as listed above will

be further modified by including three regional institutional dummy variables This

modified gravity model will be estimated by Ordinary Least Square (OLS) from 1988 to

2004 for 46 countries as shown below

14

log Xij = log β0 + β1 log Yi + β2 log Yj +β3 log Ni +β4 log Nj +β5 log Dij + β6AFTAij +

β7exAFTAij + β8imAFTAij +logεij (3)

where Xij is the total US dollar value of exports from country i to j Yi Yj are nominal

values of gross domestic product of country i and j in US dollar Ni Nj are populations

of countries i and j Dij is the distance between countries i and j AFTAij is a dummy

variable which is 1 if two countries belong to AFTA and 0 otherwise exAFTAij is 1 if

only export country i belongs to AFTA and 0 otherwise imAFTAij is 1 if only the

import country j belongs to AFTA and 0 otherwise log ε ij is the log

normally-distributed error term

Common language and common border dummy variable which are two excluded

independent variables in our model will be discussed below They measure cultural

affinity and are expected to have positive relationship with trade If the two countries

have common language and border this makes trade easier and improves

communication with other countries Jugutnath Stewart and Brooks (2007) used official

language of a country to determine whether countries have same common languages

However this variable is difficult to delineate because different country has their dialect

and English has been widely used for communication Secondly common border is

excluded because some countries like Japan Australia Indonesia Iceland and United

Kingdom which are included in our data set are an island They do not have any

15

common border with other countries In order to improve the stability of our model

these two variables are excluded

42 Expectation of Results

In the regression equation 3 expectations of explanatory variables are listed as follows

The expected signs of independent variables Yi and Yj are positive Large economies

tend to spend large amount on imports because they have high income As they produce

a wide range of products this attracts other countries to spend on their production as

well In our model nominal GDP is employed If real GDP is used to replace the

nominal one there will be only a small difference in the coefficient of determination

(Linnemann 1966) This result is shown in the Table 52

The coefficient of Ni and Nj are uncertain Nguyen (2009) states that the coefficient are

expected to be negative because countries that have large population will have larger

resource endowment This absorption effect causes less dependence on international

specialization This will lead to a fall in trade between countries On the other hand

they are expected to be positive means a larger population means a larger domestic

market This in turn exploits economies of scale and the country will trade more with

foreign partner with a wider range of goods

The expected sign of variable Dij is negative because the greater the distance between

16

country i and j increases transportation costs time required for delivery and

communication failures Volume of trade between two countries is inversely correlated

with distance

In addition there are different expectations for coefficients of AFTAij exAFTAij and

imAFTAij AFTAij is expected to be positive and reflects the creation effect of

intraregional trade due to reduction of tariff rates and elimination of non tariff barriers

among AFTA This indicates members of AFTA have trade more with its members than

hypothetical trade level Dummy variables exAFTAij and imAFTAij captures the ldquoexport

trade diversionrdquo and ldquoimport trade diversionrdquo respectively The formation of Free Trade

Area is expected to lead to a decline of trade among member countries and nonmembers

countries (Tang 2005) Endoh (1999) who coined the term ldquoexport trade diversionrdquo

states that negative and statically significant coefficient of exAFTAij indicates that this

economic integration has caused the member countries to export their products within

the bloc rather than those outside the bloc For imAFTAij if its coefficient is negative

and statistically significant this means the members have switched their importing

activities from nonmembers to members

43 Data Description and Sources

To compare the impacts of AFTA overtime in addition to the pooled data of 1988-2004

17

the data is divided into four periods ie 1988-1992 1993-1997 1998-2002 and

2003-2004 Concerning the first breakdown of 1988-1992 and 1993-1997 this can

examine the changes in the trade flow between the member and nonmember countries

before and after the formation of AFTA For the division of 1993-1997 and 1998-2002

this can test whether the trade flow was adversely affected by 1997 Asian Financial

Crisis For 1998-2002 and 2003-2004 this can explain whether Outbreak of SARS had

adverse impacts on trade in Asian economies

The data set covers the bilateral trade flow for 46 countries They include 10 members

of AFTA and 36 nonmember countries The nonmember countries include Austria

Belgium-Luxembourg Finland France Germany Ireland Italy Netherlands Portugal

Spain Denmark Sweden United Kingdom Algeria Argentina Australia Brazil

Canada Chile China Colombia Czech Republic Egypt Japan Hong Kong Iceland

India Iran Mexico Norway New Zealand Poland Russia South Korea Switzerland

and the United States

For the dependent variable the annual export data are extracted from the Direction of

Trade Statistics GDP and population are obtained from The World Economic Outlook

and International Financial Statistics All export values and GDP are in US million

dollars Distance is collected from the Great Circle Distance between Cities The

physical distance is measured by the capital cities of 46 member and nonmember

18

countries in kilometers The values of AFTAij exAFTAij and imAFTAij depend on

countries that paired in the observations The number of observation for the pooled

sample is 30867 Some of the data are not available in the data base especially for

period of 1980s in developing countries

19

5 Empirical Results

Ordinary Least Square result for regression equation 3 is presented in Table 51 The

values of adjusted coefficient of determination in 1988-1992 and 1993-1997 are 0717

and 0748 respectively For 1998-2002 and 2003-2004 values of adjusted coefficient of

determination are 0768 and 0763 This means over 70 variation of export values

between country i and country j around its mean can be explained by the independent

variables in regression equation 3 adjusted for degree of freedom

51 Explanation of Gravity Model

All estimated coefficient are statistically significant different from zero at 1 level of

significance The coefficient of Yi Yj and Dij fulfill our expectations as stated in the

gravity model This shows gravity model plays a major role in explaining pattern of

trade flow in modern society Trade is positively related to GDP Larger economies tend

to have higher demand for imports and produce larger amount of goods for exports

Similar to the results of Endoh (1999) the coefficient of population is negative which

means increase in population will cause a decline in trade as the country produces a

wider range of product

The coefficient of Dij is negative and statistically significant Although there are

improvements in transportation technologies which can reduce the transportation cost

20

and facilitate transportation of goods between both importing and exporting countries

over time distance between countries still remains one of the most important

determinants in trade activities

52 Intraregional trade bias in AFTA

The coefficients of AFTA ij are positive and statistically significant It increases from

1915 in 1988-1992 to 2155 in 1993-1997 This shows there is trade creation effect

after the formation of AFTA This is consistent with the previous study like Tang (2005)

and Thornton and Goglio (2002) The low tariff rate facilitates trade in AFTA

After the 1997 Asian Financial Crisis the poor economic performance did not inhibited

the member countries to export goods to each other as there is a sharp jump in this

coefficient to 2857 New admission of Lao PDR and Myanmar in 1997 stimulated trade

creation effects Average regional CEPT rate for products in the Inclusion List has

dropped from 1276 in 1993 to 505 in 1998 (Jr Yee and Azhari 1998) Elliot and

Ikemoto (2004) pointed out that this regional economic shock in the form of currency

crisis created latent forces institutionalizing interdependence within the bloc

On the contrary after outbreak of SARS in 2003 the coefficient of AFTAij decreases to

2699 To further explain SARS is a highly infectious respiratory disease that had

caused doom in East Asian economies Within AFTA Singapore and Vietnam were hard

21

hit by SARS People tend to avoid social interaction which led to a slump in business

transactions The unemployment rate increased and demand for goods and services fell

Although a new arrangement of CEPT Rules of Origin and Operational Certification

Procedures which could promote trade among AFTA has been implemented on 1

January 2004 intraregional trade had declined In addition rise of trade among

nonmember countries could explain this decline As China has formally entered into

WTO in 2001 exports of ASEAN countries need to compete with Chinese products in

both export and ASEAN domestic market and ASEAN exporters would lose their

comparative advantage when developed countries give tariff concessions to China

(Kwan and Qiu 2003)

53 Export and Import Trade Diversion between member and non member countries

Finally the dummy variables of exAFTA ij and imAFTA ij have signs opposite to our

expectations They are statistically significant at 1 level of significance The positive

sign of exAFTA ij and imAFTA ij indicate that members and nonmembers have traded

with each other to greater extent than the hypothetical trade level throughout 1988-2004

(Endoh 1999) The results indicate negative trade diversion effect in AFTA

The coefficient of exAFTAij has a continuous increase from 0837 in 1988-1992 to

1135 in 1993-1997 The positive sign of this coefficient implies that the member

22

countries prefer to export goods to nonmember rather than members after the formation

of AFTA This implies AFTA members adopted export oriented strategies that promoted

export (Nguyen 2009)

The coefficient of exAFTAij increases to 1374 after 1997 The upward trend in

exAFTAij shows there is strengthening of negative export trade diversion throughout the

period of 1992-2002 The model of Elliot and Ikemoto (2004) also had similar results

and further explained the sharp jump in exAFTAij is caused by the devaluation of

ASEAN currencies after 1997 Asian Financial crisis as shown in Figure 81 (Appendix)

This could increase the competitiveness of ASEAN exports since they were relatively

cheaper when compared with the products of nonmember countries This boosted

ASEAN export trade with nonmembers

After the outbreak of SARS exAFTAij coefficient falls to 1175 in the period 2003-2004

which means there is weakening of negative trade diversion The outbreak of SARS has

caused temporary shock and persistent shock to Hong Kong and Chinese economies

Lee (2004) suggested that SARS led to a loss of GDP Hong Kong which was seriously

affected has experienced a decline in GDP by 263 GDP of Taiwan and Singapore

also were decreased by 049 and 047 respectively This reduction showed there was

a fall in demand for goods and services of ASEAN countries This could also be

explained by the slight appreciation of ASEAN currency after 2002 Value of ASEAN

23

currency increased relative to other foreign countries and ASEAN products were

relatively more expensive Therefore AFTA members prefer to export their goods to

members rather than nonmembers

The dummy variable imAFTAij measures import trade diversion of AFTA Its

coefficient increases from 058 in 1988-1992 to 0903 in 1993-1997 The upward trend

reveals that dynamic network of domestic production and foreign investment projects in

AFTA members caused a rise in its imports from nonmember countries (Nguyen 2009)

This fall in imAFTA ij after 1997 Asian Financial Crisis and outbreak of SARS implies

there is a weakening of negative import trade diversion ASEAN prefer to import goods

from members rather than nonmembers but the effects are small relative to the

coefficient of AFTAij As explained before devaluation of ASEAN currency means

foreign goods are more expensive So they prefer to import from members After the

outbreak of SARS the coefficient of imAFTA ij further drops to 0682 Spread of

diseases generated negative impacts to economies in Hong Kong and China which are

major trading partners of AFTA These two countries had the highest probable cases of

SARS This is one of the reasons why AFTA members prefer to import more goods

from members rather than nonmembers

Trade creation and diversion are subjected to changes in external economic environment

AFTA strengthened cooperation with all member countries in 1997 Asian Financial

24

Crisis and urged the members to undertake policy to promote trade which can in turn

speed up economic recovery When compared with outbreak of SARS which caused an

economic downturn in nonmember countries AFTA demonstrates an economic

regionalism that united members in the bloc As shown in the econometric results

AFTA members prefer to trade more among themselves rather than nonmembers

To a certain extent exchange rate volatility did not play a significant role in affecting

trade Most of economies in East Asia adopt a ldquomanaged floatrdquo exchange rate policy

which is beneficial to accomplish economic goals and objectives (Martin 2008) The

2SLS results of Tang (2005) shows that coefficient of exchange rate volatility is positive

which is opposite to our expectation but it is statically insignificant in the pooled sample

Although this coefficient is negative in OLS estimation overall effects of exchange rate

volatility on trade has reduced over time Tang (2005) further suggested two reasons

attributable to this phenomenon after 1997 Firstly the restructuring of financial sectors

like implementation of pegged exchange rate system and transaction of currency option

and contract lead to improvements which can avoid similar crisis in future Secondly

financial system of developed countries are so well organized that stock market and

banking operation are less vulnerable to exchange rate fluctuation

In Table 52 real values of GDP and exports replaced the nominal one in regression

equation 3 Similar results and conclusions could be drawn

25

Table 51

Empirical results of regression equation 3

based on nominal values of exports and GDP

Independent

Variables

1988-1992 1993-1997 1998-2002 2003-2004 1988-2004

Constant 3438

(18597)

2974

(1857)

0966

(5753)

0457

(1653)

2569

(2755)

log Yi 1157

(93901)

1222

(10687)

1364

(98397)

1295

(59454)

1203

(179786)

log Yj 1016

(84303)

1008

(91165)

1215

(90192)

1182

(54609)

1046

(160182)

log Ni -0238

(-18409)

-0219

(-19762)

-0224

(-19141)

-0144

(-7936)

-0187

(-29098)

log Nj -0125

(-9624)

-0071

(-6442)

-0163

(-14185)

-009

(-499)

-0090

(-14138)

log Dij -0983

(-50493)

-1036

(-61597)

-0994

(-59095)

-0961

(-35954)

-0993

(-102673)

AFTA ij 1915

(6511)

2155

(19970)

2857

(3200)

2699

(19042)

2019

(34473)

exAFTA ij 0837

(7308)

1135

(23365)

1374

(26723)

1175

(14575)

0902

(30698)

imAFTA ij 0580

(5232)

0903

(19035)

0775

(15353)

0682

(8532)

0466

(1609)

Adjusted R2 0717 0748 0768 0763 0741

SEE 1572 1442 1442 1448 1506

Number of

observations

7888 9194 9822 3963 30867

Notes

1 T-values are in parentheses

2 denotes the coefficient is significant at 1 level denotes the coefficient is

significant at 5 level denotes the coefficient is significant at 10 level

3 The use of real GDP and export values is reported in the Table 52 which shows there

is little difference in the coefficients in the independent variables

26

Table 52

Empirical results of regression equation 3

based on real values of exports and GDP

Independent

Variables

1988-1992 1993-1997 1998-2002

2003-2004 1988-2004

Constant 3172

(17041)

2845

(1771)

0966

(5757)

0550

(200)

2293

(24637)

log real Yi 116

(94164)

1226

(107095)

1364

(98386)

1297

(59524)

123

(182883)

log real Yj 1020

(84573)

1011

(91405)

1216

(90191)

1184

(54681)

1072

(163403)

log Ni -0239

(-18510)

-0221

(-1994)

-0224

(-19115)

-0145

(-7989)

-02

(-31263)

log Nj -0127

(-977)

-0072

(-6594)

-0163

(-14186)

-0091

(-5049)

-0103

(-16203)

log Dij -0983

(-50598)

-1036

(-61676)

-0994

(-59109)

-0960

(-35959)

-0997

(-104061)

AFTA ij 1995

(679)

2174

(2016)

2859

(32014)

2707

(19101)

2200

(37693)

exAFTA ij 0914

(7984)

1143

(23365)

1374

(26712)

1179

(14630)

1025

(34982)

imAFTA ij 0657

(5936)

0911

(19224)

0778

(15404)

0686

(8584)

0586

(20301)

Adjusted R2 0718 0748 0767 0763 0744

SEE 157 144 1442 1446 1492

Number of

observations

7888 9194 9822 3963 30867

Notes `

1 T-values are in parentheses

2 denotes the coefficient is significant at 1 level denotes the coefficient is

significant at 5 level denotes the coefficient is significant at 10 level

3 For real GDP and export values year 2000 is used as base year

27

6 Implications and Recommendations

As China joins ASEAN Free Trade Agreement in January 2010 this creates changes on

the trade flow From the side of ASEAN this agreement helps ASEAN members to

access a prosperous Chinese market From Table 82 (Appendix) there is an increasing

trend of trade among AFTA and China during the period of 2004-2008 Both sides

consider each other as crucial trading partners As tariff barrier is removed after

formation of CAFTA this can increase intra regional trade among these countries and

reduce AFTA reliance on United States European Union and Japan (Chia 2004) With

countries of different stages of economic development integrated CAFTA can narrow

the income gap between member countries (Roberts 2004)

However empirical studies show mixed results As defined in Linder Hypothesis

countries with similar levels of income per capita will exhibit similar demand produce

similar and differentiated products and trade more with each other According to

empirical study conducted by Roberts (2004) the coefficient testing of the Linder

Hypothesis is insignificant which implies that CAFTA does not have similar demand

pattern and this can be supported by the classification of different stages of economic

development among the members Roberts (2004) noted that China Cambodia Laos

PDR Myanmar and Vietnam are Low Income economies Indonesia Thailand and

Philippines are Low Middle Income economies Singapore and Brunei Darussalam are

28

High Income Economies based on World Bankrsquos classification CAFTA creates an

enlarged market which increases in competition and investment (Chirathivat 2002)

Using SMART model Zhao Malouche and Newfarmer (2008) found out that there is

only a limited increase in intraregional trade and trade diversion when they assume full

liberalization of trade between China and ASEAN is implemented Chinarsquos imports

from ASEAN would increase by 72 especially from Singapore Thailand and

Malaysia On the other hand according to the simulation conducted by the ASEAN

Secretariat (2001) CAFTA would increase ASEANs exports to China and Chinese

export to ASEAN by 48 and 551 respectively (China amp World Economy 2003)

Although previous studies had mixed results CAFTA does provide a platform for China

and ASEAN to establish a legal system for trade investment and service that complies

with the rules of WTO and international standards This allows promotion of freer trade

and attracts investment from the foreign countries (Zhang 2006)

13

4Methodology

41 Specification of Gravity Model

To estimate the intensity and transition of trade creation and trade diversion gravity

model is adopted because of its simplicity and explanatory power in assessing the

impacts of regional trading bloc The original Basic Gravity Model (BGM) which is

written by Tinbergen (1962) to analyze effects of economic integration specifies as

follows

Xij=βoYi

β1 Yj

β2 Dij

β3 εij (1)

Or using natural logarithms

log Xij = log β0 + β1 log Yi + β2 log Yj +β3 log Dij +logεij (2)

BGM states that volume of trade between two countries is determined by Gross

Domestic Product (GDP) that measures the size of the economies and distance between

them From equation 1 trade is proportional to the product of two countriesrsquo GDPs and

inversely related to distance between two countries

In order to find out the trade creation and diversion of AFTA BGM as listed above will

be further modified by including three regional institutional dummy variables This

modified gravity model will be estimated by Ordinary Least Square (OLS) from 1988 to

2004 for 46 countries as shown below

14

log Xij = log β0 + β1 log Yi + β2 log Yj +β3 log Ni +β4 log Nj +β5 log Dij + β6AFTAij +

β7exAFTAij + β8imAFTAij +logεij (3)

where Xij is the total US dollar value of exports from country i to j Yi Yj are nominal

values of gross domestic product of country i and j in US dollar Ni Nj are populations

of countries i and j Dij is the distance between countries i and j AFTAij is a dummy

variable which is 1 if two countries belong to AFTA and 0 otherwise exAFTAij is 1 if

only export country i belongs to AFTA and 0 otherwise imAFTAij is 1 if only the

import country j belongs to AFTA and 0 otherwise log ε ij is the log

normally-distributed error term

Common language and common border dummy variable which are two excluded

independent variables in our model will be discussed below They measure cultural

affinity and are expected to have positive relationship with trade If the two countries

have common language and border this makes trade easier and improves

communication with other countries Jugutnath Stewart and Brooks (2007) used official

language of a country to determine whether countries have same common languages

However this variable is difficult to delineate because different country has their dialect

and English has been widely used for communication Secondly common border is

excluded because some countries like Japan Australia Indonesia Iceland and United

Kingdom which are included in our data set are an island They do not have any

15

common border with other countries In order to improve the stability of our model

these two variables are excluded

42 Expectation of Results

In the regression equation 3 expectations of explanatory variables are listed as follows

The expected signs of independent variables Yi and Yj are positive Large economies

tend to spend large amount on imports because they have high income As they produce

a wide range of products this attracts other countries to spend on their production as

well In our model nominal GDP is employed If real GDP is used to replace the

nominal one there will be only a small difference in the coefficient of determination

(Linnemann 1966) This result is shown in the Table 52

The coefficient of Ni and Nj are uncertain Nguyen (2009) states that the coefficient are

expected to be negative because countries that have large population will have larger

resource endowment This absorption effect causes less dependence on international

specialization This will lead to a fall in trade between countries On the other hand

they are expected to be positive means a larger population means a larger domestic

market This in turn exploits economies of scale and the country will trade more with

foreign partner with a wider range of goods

The expected sign of variable Dij is negative because the greater the distance between

16

country i and j increases transportation costs time required for delivery and

communication failures Volume of trade between two countries is inversely correlated

with distance

In addition there are different expectations for coefficients of AFTAij exAFTAij and

imAFTAij AFTAij is expected to be positive and reflects the creation effect of

intraregional trade due to reduction of tariff rates and elimination of non tariff barriers

among AFTA This indicates members of AFTA have trade more with its members than

hypothetical trade level Dummy variables exAFTAij and imAFTAij captures the ldquoexport

trade diversionrdquo and ldquoimport trade diversionrdquo respectively The formation of Free Trade

Area is expected to lead to a decline of trade among member countries and nonmembers

countries (Tang 2005) Endoh (1999) who coined the term ldquoexport trade diversionrdquo

states that negative and statically significant coefficient of exAFTAij indicates that this

economic integration has caused the member countries to export their products within

the bloc rather than those outside the bloc For imAFTAij if its coefficient is negative

and statistically significant this means the members have switched their importing

activities from nonmembers to members

43 Data Description and Sources

To compare the impacts of AFTA overtime in addition to the pooled data of 1988-2004

17

the data is divided into four periods ie 1988-1992 1993-1997 1998-2002 and

2003-2004 Concerning the first breakdown of 1988-1992 and 1993-1997 this can

examine the changes in the trade flow between the member and nonmember countries

before and after the formation of AFTA For the division of 1993-1997 and 1998-2002

this can test whether the trade flow was adversely affected by 1997 Asian Financial

Crisis For 1998-2002 and 2003-2004 this can explain whether Outbreak of SARS had

adverse impacts on trade in Asian economies

The data set covers the bilateral trade flow for 46 countries They include 10 members

of AFTA and 36 nonmember countries The nonmember countries include Austria

Belgium-Luxembourg Finland France Germany Ireland Italy Netherlands Portugal

Spain Denmark Sweden United Kingdom Algeria Argentina Australia Brazil

Canada Chile China Colombia Czech Republic Egypt Japan Hong Kong Iceland

India Iran Mexico Norway New Zealand Poland Russia South Korea Switzerland

and the United States

For the dependent variable the annual export data are extracted from the Direction of

Trade Statistics GDP and population are obtained from The World Economic Outlook

and International Financial Statistics All export values and GDP are in US million

dollars Distance is collected from the Great Circle Distance between Cities The

physical distance is measured by the capital cities of 46 member and nonmember

18

countries in kilometers The values of AFTAij exAFTAij and imAFTAij depend on

countries that paired in the observations The number of observation for the pooled

sample is 30867 Some of the data are not available in the data base especially for

period of 1980s in developing countries

19

5 Empirical Results

Ordinary Least Square result for regression equation 3 is presented in Table 51 The

values of adjusted coefficient of determination in 1988-1992 and 1993-1997 are 0717

and 0748 respectively For 1998-2002 and 2003-2004 values of adjusted coefficient of

determination are 0768 and 0763 This means over 70 variation of export values

between country i and country j around its mean can be explained by the independent

variables in regression equation 3 adjusted for degree of freedom

51 Explanation of Gravity Model

All estimated coefficient are statistically significant different from zero at 1 level of

significance The coefficient of Yi Yj and Dij fulfill our expectations as stated in the

gravity model This shows gravity model plays a major role in explaining pattern of

trade flow in modern society Trade is positively related to GDP Larger economies tend

to have higher demand for imports and produce larger amount of goods for exports

Similar to the results of Endoh (1999) the coefficient of population is negative which

means increase in population will cause a decline in trade as the country produces a

wider range of product

The coefficient of Dij is negative and statistically significant Although there are

improvements in transportation technologies which can reduce the transportation cost

20

and facilitate transportation of goods between both importing and exporting countries

over time distance between countries still remains one of the most important

determinants in trade activities

52 Intraregional trade bias in AFTA

The coefficients of AFTA ij are positive and statistically significant It increases from

1915 in 1988-1992 to 2155 in 1993-1997 This shows there is trade creation effect

after the formation of AFTA This is consistent with the previous study like Tang (2005)

and Thornton and Goglio (2002) The low tariff rate facilitates trade in AFTA

After the 1997 Asian Financial Crisis the poor economic performance did not inhibited

the member countries to export goods to each other as there is a sharp jump in this

coefficient to 2857 New admission of Lao PDR and Myanmar in 1997 stimulated trade

creation effects Average regional CEPT rate for products in the Inclusion List has

dropped from 1276 in 1993 to 505 in 1998 (Jr Yee and Azhari 1998) Elliot and

Ikemoto (2004) pointed out that this regional economic shock in the form of currency

crisis created latent forces institutionalizing interdependence within the bloc

On the contrary after outbreak of SARS in 2003 the coefficient of AFTAij decreases to

2699 To further explain SARS is a highly infectious respiratory disease that had

caused doom in East Asian economies Within AFTA Singapore and Vietnam were hard

21

hit by SARS People tend to avoid social interaction which led to a slump in business

transactions The unemployment rate increased and demand for goods and services fell

Although a new arrangement of CEPT Rules of Origin and Operational Certification

Procedures which could promote trade among AFTA has been implemented on 1

January 2004 intraregional trade had declined In addition rise of trade among

nonmember countries could explain this decline As China has formally entered into

WTO in 2001 exports of ASEAN countries need to compete with Chinese products in

both export and ASEAN domestic market and ASEAN exporters would lose their

comparative advantage when developed countries give tariff concessions to China

(Kwan and Qiu 2003)

53 Export and Import Trade Diversion between member and non member countries

Finally the dummy variables of exAFTA ij and imAFTA ij have signs opposite to our

expectations They are statistically significant at 1 level of significance The positive

sign of exAFTA ij and imAFTA ij indicate that members and nonmembers have traded

with each other to greater extent than the hypothetical trade level throughout 1988-2004

(Endoh 1999) The results indicate negative trade diversion effect in AFTA

The coefficient of exAFTAij has a continuous increase from 0837 in 1988-1992 to

1135 in 1993-1997 The positive sign of this coefficient implies that the member

22

countries prefer to export goods to nonmember rather than members after the formation

of AFTA This implies AFTA members adopted export oriented strategies that promoted

export (Nguyen 2009)

The coefficient of exAFTAij increases to 1374 after 1997 The upward trend in

exAFTAij shows there is strengthening of negative export trade diversion throughout the

period of 1992-2002 The model of Elliot and Ikemoto (2004) also had similar results

and further explained the sharp jump in exAFTAij is caused by the devaluation of

ASEAN currencies after 1997 Asian Financial crisis as shown in Figure 81 (Appendix)

This could increase the competitiveness of ASEAN exports since they were relatively

cheaper when compared with the products of nonmember countries This boosted

ASEAN export trade with nonmembers

After the outbreak of SARS exAFTAij coefficient falls to 1175 in the period 2003-2004

which means there is weakening of negative trade diversion The outbreak of SARS has

caused temporary shock and persistent shock to Hong Kong and Chinese economies

Lee (2004) suggested that SARS led to a loss of GDP Hong Kong which was seriously

affected has experienced a decline in GDP by 263 GDP of Taiwan and Singapore

also were decreased by 049 and 047 respectively This reduction showed there was

a fall in demand for goods and services of ASEAN countries This could also be

explained by the slight appreciation of ASEAN currency after 2002 Value of ASEAN

23

currency increased relative to other foreign countries and ASEAN products were

relatively more expensive Therefore AFTA members prefer to export their goods to

members rather than nonmembers

The dummy variable imAFTAij measures import trade diversion of AFTA Its

coefficient increases from 058 in 1988-1992 to 0903 in 1993-1997 The upward trend

reveals that dynamic network of domestic production and foreign investment projects in

AFTA members caused a rise in its imports from nonmember countries (Nguyen 2009)

This fall in imAFTA ij after 1997 Asian Financial Crisis and outbreak of SARS implies

there is a weakening of negative import trade diversion ASEAN prefer to import goods

from members rather than nonmembers but the effects are small relative to the

coefficient of AFTAij As explained before devaluation of ASEAN currency means

foreign goods are more expensive So they prefer to import from members After the

outbreak of SARS the coefficient of imAFTA ij further drops to 0682 Spread of

diseases generated negative impacts to economies in Hong Kong and China which are

major trading partners of AFTA These two countries had the highest probable cases of

SARS This is one of the reasons why AFTA members prefer to import more goods

from members rather than nonmembers

Trade creation and diversion are subjected to changes in external economic environment

AFTA strengthened cooperation with all member countries in 1997 Asian Financial

24

Crisis and urged the members to undertake policy to promote trade which can in turn

speed up economic recovery When compared with outbreak of SARS which caused an

economic downturn in nonmember countries AFTA demonstrates an economic

regionalism that united members in the bloc As shown in the econometric results

AFTA members prefer to trade more among themselves rather than nonmembers

To a certain extent exchange rate volatility did not play a significant role in affecting

trade Most of economies in East Asia adopt a ldquomanaged floatrdquo exchange rate policy

which is beneficial to accomplish economic goals and objectives (Martin 2008) The

2SLS results of Tang (2005) shows that coefficient of exchange rate volatility is positive

which is opposite to our expectation but it is statically insignificant in the pooled sample

Although this coefficient is negative in OLS estimation overall effects of exchange rate

volatility on trade has reduced over time Tang (2005) further suggested two reasons

attributable to this phenomenon after 1997 Firstly the restructuring of financial sectors

like implementation of pegged exchange rate system and transaction of currency option

and contract lead to improvements which can avoid similar crisis in future Secondly

financial system of developed countries are so well organized that stock market and

banking operation are less vulnerable to exchange rate fluctuation

In Table 52 real values of GDP and exports replaced the nominal one in regression

equation 3 Similar results and conclusions could be drawn

25

Table 51

Empirical results of regression equation 3

based on nominal values of exports and GDP

Independent

Variables

1988-1992 1993-1997 1998-2002 2003-2004 1988-2004

Constant 3438

(18597)

2974

(1857)

0966

(5753)

0457

(1653)

2569

(2755)

log Yi 1157

(93901)

1222

(10687)

1364

(98397)

1295

(59454)

1203

(179786)

log Yj 1016

(84303)

1008

(91165)

1215

(90192)

1182

(54609)

1046

(160182)

log Ni -0238

(-18409)

-0219

(-19762)

-0224

(-19141)

-0144

(-7936)

-0187

(-29098)

log Nj -0125

(-9624)

-0071

(-6442)

-0163

(-14185)

-009

(-499)

-0090

(-14138)

log Dij -0983

(-50493)

-1036

(-61597)

-0994

(-59095)

-0961

(-35954)

-0993

(-102673)

AFTA ij 1915

(6511)

2155

(19970)

2857

(3200)

2699

(19042)

2019

(34473)

exAFTA ij 0837

(7308)

1135

(23365)

1374

(26723)

1175

(14575)

0902

(30698)

imAFTA ij 0580

(5232)

0903

(19035)

0775

(15353)

0682

(8532)

0466

(1609)

Adjusted R2 0717 0748 0768 0763 0741

SEE 1572 1442 1442 1448 1506

Number of

observations

7888 9194 9822 3963 30867

Notes

1 T-values are in parentheses

2 denotes the coefficient is significant at 1 level denotes the coefficient is

significant at 5 level denotes the coefficient is significant at 10 level

3 The use of real GDP and export values is reported in the Table 52 which shows there

is little difference in the coefficients in the independent variables

26

Table 52

Empirical results of regression equation 3

based on real values of exports and GDP

Independent

Variables

1988-1992 1993-1997 1998-2002

2003-2004 1988-2004

Constant 3172

(17041)

2845

(1771)

0966

(5757)

0550

(200)

2293

(24637)

log real Yi 116

(94164)

1226

(107095)

1364

(98386)

1297

(59524)

123

(182883)

log real Yj 1020

(84573)

1011

(91405)

1216

(90191)

1184

(54681)

1072

(163403)

log Ni -0239

(-18510)

-0221

(-1994)

-0224

(-19115)

-0145

(-7989)

-02

(-31263)

log Nj -0127

(-977)

-0072

(-6594)

-0163

(-14186)

-0091

(-5049)

-0103

(-16203)

log Dij -0983

(-50598)

-1036

(-61676)

-0994

(-59109)

-0960

(-35959)

-0997

(-104061)

AFTA ij 1995

(679)

2174

(2016)

2859

(32014)

2707

(19101)

2200

(37693)

exAFTA ij 0914

(7984)

1143

(23365)

1374

(26712)

1179

(14630)

1025

(34982)

imAFTA ij 0657

(5936)

0911

(19224)

0778

(15404)

0686

(8584)

0586

(20301)

Adjusted R2 0718 0748 0767 0763 0744

SEE 157 144 1442 1446 1492

Number of

observations

7888 9194 9822 3963 30867

Notes `

1 T-values are in parentheses

2 denotes the coefficient is significant at 1 level denotes the coefficient is

significant at 5 level denotes the coefficient is significant at 10 level

3 For real GDP and export values year 2000 is used as base year

27

6 Implications and Recommendations

As China joins ASEAN Free Trade Agreement in January 2010 this creates changes on

the trade flow From the side of ASEAN this agreement helps ASEAN members to

access a prosperous Chinese market From Table 82 (Appendix) there is an increasing

trend of trade among AFTA and China during the period of 2004-2008 Both sides

consider each other as crucial trading partners As tariff barrier is removed after

formation of CAFTA this can increase intra regional trade among these countries and

reduce AFTA reliance on United States European Union and Japan (Chia 2004) With

countries of different stages of economic development integrated CAFTA can narrow

the income gap between member countries (Roberts 2004)

However empirical studies show mixed results As defined in Linder Hypothesis

countries with similar levels of income per capita will exhibit similar demand produce

similar and differentiated products and trade more with each other According to

empirical study conducted by Roberts (2004) the coefficient testing of the Linder

Hypothesis is insignificant which implies that CAFTA does not have similar demand

pattern and this can be supported by the classification of different stages of economic

development among the members Roberts (2004) noted that China Cambodia Laos

PDR Myanmar and Vietnam are Low Income economies Indonesia Thailand and

Philippines are Low Middle Income economies Singapore and Brunei Darussalam are

28

High Income Economies based on World Bankrsquos classification CAFTA creates an

enlarged market which increases in competition and investment (Chirathivat 2002)

Using SMART model Zhao Malouche and Newfarmer (2008) found out that there is

only a limited increase in intraregional trade and trade diversion when they assume full

liberalization of trade between China and ASEAN is implemented Chinarsquos imports

from ASEAN would increase by 72 especially from Singapore Thailand and

Malaysia On the other hand according to the simulation conducted by the ASEAN

Secretariat (2001) CAFTA would increase ASEANs exports to China and Chinese

export to ASEAN by 48 and 551 respectively (China amp World Economy 2003)

Although previous studies had mixed results CAFTA does provide a platform for China

and ASEAN to establish a legal system for trade investment and service that complies

with the rules of WTO and international standards This allows promotion of freer trade

and attracts investment from the foreign countries (Zhang 2006)

14

log Xij = log β0 + β1 log Yi + β2 log Yj +β3 log Ni +β4 log Nj +β5 log Dij + β6AFTAij +

β7exAFTAij + β8imAFTAij +logεij (3)

where Xij is the total US dollar value of exports from country i to j Yi Yj are nominal

values of gross domestic product of country i and j in US dollar Ni Nj are populations

of countries i and j Dij is the distance between countries i and j AFTAij is a dummy

variable which is 1 if two countries belong to AFTA and 0 otherwise exAFTAij is 1 if

only export country i belongs to AFTA and 0 otherwise imAFTAij is 1 if only the

import country j belongs to AFTA and 0 otherwise log ε ij is the log

normally-distributed error term

Common language and common border dummy variable which are two excluded

independent variables in our model will be discussed below They measure cultural

affinity and are expected to have positive relationship with trade If the two countries

have common language and border this makes trade easier and improves

communication with other countries Jugutnath Stewart and Brooks (2007) used official

language of a country to determine whether countries have same common languages

However this variable is difficult to delineate because different country has their dialect

and English has been widely used for communication Secondly common border is

excluded because some countries like Japan Australia Indonesia Iceland and United

Kingdom which are included in our data set are an island They do not have any

15

common border with other countries In order to improve the stability of our model

these two variables are excluded

42 Expectation of Results

In the regression equation 3 expectations of explanatory variables are listed as follows

The expected signs of independent variables Yi and Yj are positive Large economies

tend to spend large amount on imports because they have high income As they produce

a wide range of products this attracts other countries to spend on their production as

well In our model nominal GDP is employed If real GDP is used to replace the

nominal one there will be only a small difference in the coefficient of determination

(Linnemann 1966) This result is shown in the Table 52

The coefficient of Ni and Nj are uncertain Nguyen (2009) states that the coefficient are

expected to be negative because countries that have large population will have larger

resource endowment This absorption effect causes less dependence on international

specialization This will lead to a fall in trade between countries On the other hand

they are expected to be positive means a larger population means a larger domestic

market This in turn exploits economies of scale and the country will trade more with

foreign partner with a wider range of goods

The expected sign of variable Dij is negative because the greater the distance between

16

country i and j increases transportation costs time required for delivery and

communication failures Volume of trade between two countries is inversely correlated

with distance

In addition there are different expectations for coefficients of AFTAij exAFTAij and

imAFTAij AFTAij is expected to be positive and reflects the creation effect of

intraregional trade due to reduction of tariff rates and elimination of non tariff barriers

among AFTA This indicates members of AFTA have trade more with its members than

hypothetical trade level Dummy variables exAFTAij and imAFTAij captures the ldquoexport

trade diversionrdquo and ldquoimport trade diversionrdquo respectively The formation of Free Trade

Area is expected to lead to a decline of trade among member countries and nonmembers

countries (Tang 2005) Endoh (1999) who coined the term ldquoexport trade diversionrdquo

states that negative and statically significant coefficient of exAFTAij indicates that this

economic integration has caused the member countries to export their products within

the bloc rather than those outside the bloc For imAFTAij if its coefficient is negative

and statistically significant this means the members have switched their importing

activities from nonmembers to members

43 Data Description and Sources

To compare the impacts of AFTA overtime in addition to the pooled data of 1988-2004

17

the data is divided into four periods ie 1988-1992 1993-1997 1998-2002 and

2003-2004 Concerning the first breakdown of 1988-1992 and 1993-1997 this can

examine the changes in the trade flow between the member and nonmember countries

before and after the formation of AFTA For the division of 1993-1997 and 1998-2002

this can test whether the trade flow was adversely affected by 1997 Asian Financial

Crisis For 1998-2002 and 2003-2004 this can explain whether Outbreak of SARS had

adverse impacts on trade in Asian economies

The data set covers the bilateral trade flow for 46 countries They include 10 members

of AFTA and 36 nonmember countries The nonmember countries include Austria

Belgium-Luxembourg Finland France Germany Ireland Italy Netherlands Portugal

Spain Denmark Sweden United Kingdom Algeria Argentina Australia Brazil

Canada Chile China Colombia Czech Republic Egypt Japan Hong Kong Iceland

India Iran Mexico Norway New Zealand Poland Russia South Korea Switzerland

and the United States

For the dependent variable the annual export data are extracted from the Direction of

Trade Statistics GDP and population are obtained from The World Economic Outlook

and International Financial Statistics All export values and GDP are in US million

dollars Distance is collected from the Great Circle Distance between Cities The

physical distance is measured by the capital cities of 46 member and nonmember

18

countries in kilometers The values of AFTAij exAFTAij and imAFTAij depend on

countries that paired in the observations The number of observation for the pooled

sample is 30867 Some of the data are not available in the data base especially for

period of 1980s in developing countries

19

5 Empirical Results

Ordinary Least Square result for regression equation 3 is presented in Table 51 The

values of adjusted coefficient of determination in 1988-1992 and 1993-1997 are 0717

and 0748 respectively For 1998-2002 and 2003-2004 values of adjusted coefficient of

determination are 0768 and 0763 This means over 70 variation of export values

between country i and country j around its mean can be explained by the independent

variables in regression equation 3 adjusted for degree of freedom

51 Explanation of Gravity Model

All estimated coefficient are statistically significant different from zero at 1 level of

significance The coefficient of Yi Yj and Dij fulfill our expectations as stated in the

gravity model This shows gravity model plays a major role in explaining pattern of

trade flow in modern society Trade is positively related to GDP Larger economies tend

to have higher demand for imports and produce larger amount of goods for exports

Similar to the results of Endoh (1999) the coefficient of population is negative which

means increase in population will cause a decline in trade as the country produces a

wider range of product

The coefficient of Dij is negative and statistically significant Although there are

improvements in transportation technologies which can reduce the transportation cost

20

and facilitate transportation of goods between both importing and exporting countries

over time distance between countries still remains one of the most important

determinants in trade activities

52 Intraregional trade bias in AFTA

The coefficients of AFTA ij are positive and statistically significant It increases from

1915 in 1988-1992 to 2155 in 1993-1997 This shows there is trade creation effect

after the formation of AFTA This is consistent with the previous study like Tang (2005)

and Thornton and Goglio (2002) The low tariff rate facilitates trade in AFTA

After the 1997 Asian Financial Crisis the poor economic performance did not inhibited

the member countries to export goods to each other as there is a sharp jump in this

coefficient to 2857 New admission of Lao PDR and Myanmar in 1997 stimulated trade

creation effects Average regional CEPT rate for products in the Inclusion List has

dropped from 1276 in 1993 to 505 in 1998 (Jr Yee and Azhari 1998) Elliot and

Ikemoto (2004) pointed out that this regional economic shock in the form of currency

crisis created latent forces institutionalizing interdependence within the bloc

On the contrary after outbreak of SARS in 2003 the coefficient of AFTAij decreases to

2699 To further explain SARS is a highly infectious respiratory disease that had

caused doom in East Asian economies Within AFTA Singapore and Vietnam were hard

21

hit by SARS People tend to avoid social interaction which led to a slump in business

transactions The unemployment rate increased and demand for goods and services fell

Although a new arrangement of CEPT Rules of Origin and Operational Certification

Procedures which could promote trade among AFTA has been implemented on 1

January 2004 intraregional trade had declined In addition rise of trade among

nonmember countries could explain this decline As China has formally entered into

WTO in 2001 exports of ASEAN countries need to compete with Chinese products in

both export and ASEAN domestic market and ASEAN exporters would lose their

comparative advantage when developed countries give tariff concessions to China

(Kwan and Qiu 2003)

53 Export and Import Trade Diversion between member and non member countries

Finally the dummy variables of exAFTA ij and imAFTA ij have signs opposite to our

expectations They are statistically significant at 1 level of significance The positive

sign of exAFTA ij and imAFTA ij indicate that members and nonmembers have traded

with each other to greater extent than the hypothetical trade level throughout 1988-2004

(Endoh 1999) The results indicate negative trade diversion effect in AFTA

The coefficient of exAFTAij has a continuous increase from 0837 in 1988-1992 to

1135 in 1993-1997 The positive sign of this coefficient implies that the member

22

countries prefer to export goods to nonmember rather than members after the formation

of AFTA This implies AFTA members adopted export oriented strategies that promoted

export (Nguyen 2009)

The coefficient of exAFTAij increases to 1374 after 1997 The upward trend in

exAFTAij shows there is strengthening of negative export trade diversion throughout the

period of 1992-2002 The model of Elliot and Ikemoto (2004) also had similar results

and further explained the sharp jump in exAFTAij is caused by the devaluation of

ASEAN currencies after 1997 Asian Financial crisis as shown in Figure 81 (Appendix)

This could increase the competitiveness of ASEAN exports since they were relatively

cheaper when compared with the products of nonmember countries This boosted

ASEAN export trade with nonmembers

After the outbreak of SARS exAFTAij coefficient falls to 1175 in the period 2003-2004

which means there is weakening of negative trade diversion The outbreak of SARS has

caused temporary shock and persistent shock to Hong Kong and Chinese economies

Lee (2004) suggested that SARS led to a loss of GDP Hong Kong which was seriously

affected has experienced a decline in GDP by 263 GDP of Taiwan and Singapore

also were decreased by 049 and 047 respectively This reduction showed there was

a fall in demand for goods and services of ASEAN countries This could also be

explained by the slight appreciation of ASEAN currency after 2002 Value of ASEAN

23

currency increased relative to other foreign countries and ASEAN products were

relatively more expensive Therefore AFTA members prefer to export their goods to

members rather than nonmembers

The dummy variable imAFTAij measures import trade diversion of AFTA Its

coefficient increases from 058 in 1988-1992 to 0903 in 1993-1997 The upward trend

reveals that dynamic network of domestic production and foreign investment projects in

AFTA members caused a rise in its imports from nonmember countries (Nguyen 2009)

This fall in imAFTA ij after 1997 Asian Financial Crisis and outbreak of SARS implies

there is a weakening of negative import trade diversion ASEAN prefer to import goods

from members rather than nonmembers but the effects are small relative to the

coefficient of AFTAij As explained before devaluation of ASEAN currency means

foreign goods are more expensive So they prefer to import from members After the

outbreak of SARS the coefficient of imAFTA ij further drops to 0682 Spread of

diseases generated negative impacts to economies in Hong Kong and China which are

major trading partners of AFTA These two countries had the highest probable cases of

SARS This is one of the reasons why AFTA members prefer to import more goods

from members rather than nonmembers

Trade creation and diversion are subjected to changes in external economic environment

AFTA strengthened cooperation with all member countries in 1997 Asian Financial

24

Crisis and urged the members to undertake policy to promote trade which can in turn

speed up economic recovery When compared with outbreak of SARS which caused an

economic downturn in nonmember countries AFTA demonstrates an economic

regionalism that united members in the bloc As shown in the econometric results

AFTA members prefer to trade more among themselves rather than nonmembers

To a certain extent exchange rate volatility did not play a significant role in affecting

trade Most of economies in East Asia adopt a ldquomanaged floatrdquo exchange rate policy

which is beneficial to accomplish economic goals and objectives (Martin 2008) The

2SLS results of Tang (2005) shows that coefficient of exchange rate volatility is positive

which is opposite to our expectation but it is statically insignificant in the pooled sample

Although this coefficient is negative in OLS estimation overall effects of exchange rate

volatility on trade has reduced over time Tang (2005) further suggested two reasons

attributable to this phenomenon after 1997 Firstly the restructuring of financial sectors

like implementation of pegged exchange rate system and transaction of currency option

and contract lead to improvements which can avoid similar crisis in future Secondly

financial system of developed countries are so well organized that stock market and

banking operation are less vulnerable to exchange rate fluctuation

In Table 52 real values of GDP and exports replaced the nominal one in regression

equation 3 Similar results and conclusions could be drawn

25

Table 51

Empirical results of regression equation 3

based on nominal values of exports and GDP

Independent

Variables

1988-1992 1993-1997 1998-2002 2003-2004 1988-2004

Constant 3438

(18597)

2974

(1857)

0966

(5753)

0457

(1653)

2569

(2755)

log Yi 1157

(93901)

1222

(10687)

1364

(98397)

1295

(59454)

1203

(179786)

log Yj 1016

(84303)

1008

(91165)

1215

(90192)

1182

(54609)

1046

(160182)

log Ni -0238

(-18409)

-0219

(-19762)

-0224

(-19141)

-0144

(-7936)

-0187

(-29098)

log Nj -0125

(-9624)

-0071

(-6442)

-0163

(-14185)

-009

(-499)

-0090

(-14138)

log Dij -0983

(-50493)

-1036

(-61597)

-0994

(-59095)

-0961

(-35954)

-0993

(-102673)

AFTA ij 1915

(6511)

2155

(19970)

2857

(3200)

2699

(19042)

2019

(34473)

exAFTA ij 0837

(7308)

1135

(23365)

1374

(26723)

1175

(14575)

0902

(30698)

imAFTA ij 0580

(5232)

0903

(19035)

0775

(15353)

0682

(8532)

0466

(1609)

Adjusted R2 0717 0748 0768 0763 0741

SEE 1572 1442 1442 1448 1506

Number of

observations

7888 9194 9822 3963 30867

Notes

1 T-values are in parentheses

2 denotes the coefficient is significant at 1 level denotes the coefficient is

significant at 5 level denotes the coefficient is significant at 10 level

3 The use of real GDP and export values is reported in the Table 52 which shows there

is little difference in the coefficients in the independent variables

26

Table 52

Empirical results of regression equation 3

based on real values of exports and GDP

Independent

Variables

1988-1992 1993-1997 1998-2002

2003-2004 1988-2004

Constant 3172

(17041)

2845

(1771)

0966

(5757)

0550

(200)

2293

(24637)

log real Yi 116

(94164)

1226

(107095)

1364

(98386)

1297

(59524)

123

(182883)

log real Yj 1020

(84573)

1011

(91405)

1216

(90191)

1184

(54681)

1072

(163403)

log Ni -0239

(-18510)

-0221

(-1994)

-0224

(-19115)

-0145

(-7989)

-02

(-31263)

log Nj -0127

(-977)

-0072

(-6594)

-0163

(-14186)

-0091

(-5049)

-0103

(-16203)

log Dij -0983

(-50598)

-1036

(-61676)

-0994

(-59109)

-0960

(-35959)

-0997

(-104061)

AFTA ij 1995

(679)

2174

(2016)

2859

(32014)

2707

(19101)

2200

(37693)

exAFTA ij 0914

(7984)

1143

(23365)

1374

(26712)

1179

(14630)

1025

(34982)

imAFTA ij 0657

(5936)

0911

(19224)

0778

(15404)

0686

(8584)

0586

(20301)

Adjusted R2 0718 0748 0767 0763 0744

SEE 157 144 1442 1446 1492

Number of

observations

7888 9194 9822 3963 30867

Notes `

1 T-values are in parentheses

2 denotes the coefficient is significant at 1 level denotes the coefficient is

significant at 5 level denotes the coefficient is significant at 10 level

3 For real GDP and export values year 2000 is used as base year

27

6 Implications and Recommendations

As China joins ASEAN Free Trade Agreement in January 2010 this creates changes on

the trade flow From the side of ASEAN this agreement helps ASEAN members to

access a prosperous Chinese market From Table 82 (Appendix) there is an increasing

trend of trade among AFTA and China during the period of 2004-2008 Both sides

consider each other as crucial trading partners As tariff barrier is removed after

formation of CAFTA this can increase intra regional trade among these countries and

reduce AFTA reliance on United States European Union and Japan (Chia 2004) With

countries of different stages of economic development integrated CAFTA can narrow

the income gap between member countries (Roberts 2004)

However empirical studies show mixed results As defined in Linder Hypothesis

countries with similar levels of income per capita will exhibit similar demand produce

similar and differentiated products and trade more with each other According to

empirical study conducted by Roberts (2004) the coefficient testing of the Linder

Hypothesis is insignificant which implies that CAFTA does not have similar demand

pattern and this can be supported by the classification of different stages of economic

development among the members Roberts (2004) noted that China Cambodia Laos

PDR Myanmar and Vietnam are Low Income economies Indonesia Thailand and

Philippines are Low Middle Income economies Singapore and Brunei Darussalam are

28

High Income Economies based on World Bankrsquos classification CAFTA creates an

enlarged market which increases in competition and investment (Chirathivat 2002)

Using SMART model Zhao Malouche and Newfarmer (2008) found out that there is

only a limited increase in intraregional trade and trade diversion when they assume full

liberalization of trade between China and ASEAN is implemented Chinarsquos imports

from ASEAN would increase by 72 especially from Singapore Thailand and

Malaysia On the other hand according to the simulation conducted by the ASEAN

Secretariat (2001) CAFTA would increase ASEANs exports to China and Chinese

export to ASEAN by 48 and 551 respectively (China amp World Economy 2003)

Although previous studies had mixed results CAFTA does provide a platform for China

and ASEAN to establish a legal system for trade investment and service that complies

with the rules of WTO and international standards This allows promotion of freer trade

and attracts investment from the foreign countries (Zhang 2006)

15

common border with other countries In order to improve the stability of our model

these two variables are excluded

42 Expectation of Results

In the regression equation 3 expectations of explanatory variables are listed as follows

The expected signs of independent variables Yi and Yj are positive Large economies

tend to spend large amount on imports because they have high income As they produce

a wide range of products this attracts other countries to spend on their production as

well In our model nominal GDP is employed If real GDP is used to replace the

nominal one there will be only a small difference in the coefficient of determination

(Linnemann 1966) This result is shown in the Table 52

The coefficient of Ni and Nj are uncertain Nguyen (2009) states that the coefficient are

expected to be negative because countries that have large population will have larger

resource endowment This absorption effect causes less dependence on international

specialization This will lead to a fall in trade between countries On the other hand

they are expected to be positive means a larger population means a larger domestic

market This in turn exploits economies of scale and the country will trade more with

foreign partner with a wider range of goods

The expected sign of variable Dij is negative because the greater the distance between

16

country i and j increases transportation costs time required for delivery and

communication failures Volume of trade between two countries is inversely correlated

with distance

In addition there are different expectations for coefficients of AFTAij exAFTAij and

imAFTAij AFTAij is expected to be positive and reflects the creation effect of

intraregional trade due to reduction of tariff rates and elimination of non tariff barriers

among AFTA This indicates members of AFTA have trade more with its members than

hypothetical trade level Dummy variables exAFTAij and imAFTAij captures the ldquoexport

trade diversionrdquo and ldquoimport trade diversionrdquo respectively The formation of Free Trade

Area is expected to lead to a decline of trade among member countries and nonmembers

countries (Tang 2005) Endoh (1999) who coined the term ldquoexport trade diversionrdquo

states that negative and statically significant coefficient of exAFTAij indicates that this

economic integration has caused the member countries to export their products within

the bloc rather than those outside the bloc For imAFTAij if its coefficient is negative

and statistically significant this means the members have switched their importing

activities from nonmembers to members

43 Data Description and Sources

To compare the impacts of AFTA overtime in addition to the pooled data of 1988-2004

17

the data is divided into four periods ie 1988-1992 1993-1997 1998-2002 and

2003-2004 Concerning the first breakdown of 1988-1992 and 1993-1997 this can

examine the changes in the trade flow between the member and nonmember countries

before and after the formation of AFTA For the division of 1993-1997 and 1998-2002

this can test whether the trade flow was adversely affected by 1997 Asian Financial

Crisis For 1998-2002 and 2003-2004 this can explain whether Outbreak of SARS had

adverse impacts on trade in Asian economies

The data set covers the bilateral trade flow for 46 countries They include 10 members

of AFTA and 36 nonmember countries The nonmember countries include Austria

Belgium-Luxembourg Finland France Germany Ireland Italy Netherlands Portugal

Spain Denmark Sweden United Kingdom Algeria Argentina Australia Brazil

Canada Chile China Colombia Czech Republic Egypt Japan Hong Kong Iceland

India Iran Mexico Norway New Zealand Poland Russia South Korea Switzerland

and the United States

For the dependent variable the annual export data are extracted from the Direction of

Trade Statistics GDP and population are obtained from The World Economic Outlook

and International Financial Statistics All export values and GDP are in US million

dollars Distance is collected from the Great Circle Distance between Cities The

physical distance is measured by the capital cities of 46 member and nonmember

18

countries in kilometers The values of AFTAij exAFTAij and imAFTAij depend on

countries that paired in the observations The number of observation for the pooled

sample is 30867 Some of the data are not available in the data base especially for

period of 1980s in developing countries

19

5 Empirical Results

Ordinary Least Square result for regression equation 3 is presented in Table 51 The

values of adjusted coefficient of determination in 1988-1992 and 1993-1997 are 0717

and 0748 respectively For 1998-2002 and 2003-2004 values of adjusted coefficient of

determination are 0768 and 0763 This means over 70 variation of export values

between country i and country j around its mean can be explained by the independent

variables in regression equation 3 adjusted for degree of freedom

51 Explanation of Gravity Model

All estimated coefficient are statistically significant different from zero at 1 level of

significance The coefficient of Yi Yj and Dij fulfill our expectations as stated in the

gravity model This shows gravity model plays a major role in explaining pattern of

trade flow in modern society Trade is positively related to GDP Larger economies tend

to have higher demand for imports and produce larger amount of goods for exports

Similar to the results of Endoh (1999) the coefficient of population is negative which

means increase in population will cause a decline in trade as the country produces a

wider range of product

The coefficient of Dij is negative and statistically significant Although there are

improvements in transportation technologies which can reduce the transportation cost

20

and facilitate transportation of goods between both importing and exporting countries

over time distance between countries still remains one of the most important

determinants in trade activities

52 Intraregional trade bias in AFTA

The coefficients of AFTA ij are positive and statistically significant It increases from

1915 in 1988-1992 to 2155 in 1993-1997 This shows there is trade creation effect

after the formation of AFTA This is consistent with the previous study like Tang (2005)

and Thornton and Goglio (2002) The low tariff rate facilitates trade in AFTA

After the 1997 Asian Financial Crisis the poor economic performance did not inhibited

the member countries to export goods to each other as there is a sharp jump in this

coefficient to 2857 New admission of Lao PDR and Myanmar in 1997 stimulated trade

creation effects Average regional CEPT rate for products in the Inclusion List has

dropped from 1276 in 1993 to 505 in 1998 (Jr Yee and Azhari 1998) Elliot and

Ikemoto (2004) pointed out that this regional economic shock in the form of currency

crisis created latent forces institutionalizing interdependence within the bloc

On the contrary after outbreak of SARS in 2003 the coefficient of AFTAij decreases to

2699 To further explain SARS is a highly infectious respiratory disease that had

caused doom in East Asian economies Within AFTA Singapore and Vietnam were hard

21

hit by SARS People tend to avoid social interaction which led to a slump in business

transactions The unemployment rate increased and demand for goods and services fell

Although a new arrangement of CEPT Rules of Origin and Operational Certification

Procedures which could promote trade among AFTA has been implemented on 1

January 2004 intraregional trade had declined In addition rise of trade among

nonmember countries could explain this decline As China has formally entered into

WTO in 2001 exports of ASEAN countries need to compete with Chinese products in

both export and ASEAN domestic market and ASEAN exporters would lose their

comparative advantage when developed countries give tariff concessions to China

(Kwan and Qiu 2003)

53 Export and Import Trade Diversion between member and non member countries

Finally the dummy variables of exAFTA ij and imAFTA ij have signs opposite to our

expectations They are statistically significant at 1 level of significance The positive

sign of exAFTA ij and imAFTA ij indicate that members and nonmembers have traded

with each other to greater extent than the hypothetical trade level throughout 1988-2004

(Endoh 1999) The results indicate negative trade diversion effect in AFTA

The coefficient of exAFTAij has a continuous increase from 0837 in 1988-1992 to

1135 in 1993-1997 The positive sign of this coefficient implies that the member

22

countries prefer to export goods to nonmember rather than members after the formation

of AFTA This implies AFTA members adopted export oriented strategies that promoted

export (Nguyen 2009)

The coefficient of exAFTAij increases to 1374 after 1997 The upward trend in

exAFTAij shows there is strengthening of negative export trade diversion throughout the

period of 1992-2002 The model of Elliot and Ikemoto (2004) also had similar results

and further explained the sharp jump in exAFTAij is caused by the devaluation of

ASEAN currencies after 1997 Asian Financial crisis as shown in Figure 81 (Appendix)

This could increase the competitiveness of ASEAN exports since they were relatively

cheaper when compared with the products of nonmember countries This boosted

ASEAN export trade with nonmembers

After the outbreak of SARS exAFTAij coefficient falls to 1175 in the period 2003-2004

which means there is weakening of negative trade diversion The outbreak of SARS has

caused temporary shock and persistent shock to Hong Kong and Chinese economies

Lee (2004) suggested that SARS led to a loss of GDP Hong Kong which was seriously

affected has experienced a decline in GDP by 263 GDP of Taiwan and Singapore

also were decreased by 049 and 047 respectively This reduction showed there was

a fall in demand for goods and services of ASEAN countries This could also be

explained by the slight appreciation of ASEAN currency after 2002 Value of ASEAN

23

currency increased relative to other foreign countries and ASEAN products were

relatively more expensive Therefore AFTA members prefer to export their goods to

members rather than nonmembers

The dummy variable imAFTAij measures import trade diversion of AFTA Its

coefficient increases from 058 in 1988-1992 to 0903 in 1993-1997 The upward trend

reveals that dynamic network of domestic production and foreign investment projects in

AFTA members caused a rise in its imports from nonmember countries (Nguyen 2009)

This fall in imAFTA ij after 1997 Asian Financial Crisis and outbreak of SARS implies

there is a weakening of negative import trade diversion ASEAN prefer to import goods

from members rather than nonmembers but the effects are small relative to the

coefficient of AFTAij As explained before devaluation of ASEAN currency means

foreign goods are more expensive So they prefer to import from members After the

outbreak of SARS the coefficient of imAFTA ij further drops to 0682 Spread of

diseases generated negative impacts to economies in Hong Kong and China which are

major trading partners of AFTA These two countries had the highest probable cases of

SARS This is one of the reasons why AFTA members prefer to import more goods

from members rather than nonmembers

Trade creation and diversion are subjected to changes in external economic environment

AFTA strengthened cooperation with all member countries in 1997 Asian Financial

24

Crisis and urged the members to undertake policy to promote trade which can in turn

speed up economic recovery When compared with outbreak of SARS which caused an

economic downturn in nonmember countries AFTA demonstrates an economic

regionalism that united members in the bloc As shown in the econometric results

AFTA members prefer to trade more among themselves rather than nonmembers

To a certain extent exchange rate volatility did not play a significant role in affecting

trade Most of economies in East Asia adopt a ldquomanaged floatrdquo exchange rate policy

which is beneficial to accomplish economic goals and objectives (Martin 2008) The

2SLS results of Tang (2005) shows that coefficient of exchange rate volatility is positive

which is opposite to our expectation but it is statically insignificant in the pooled sample

Although this coefficient is negative in OLS estimation overall effects of exchange rate

volatility on trade has reduced over time Tang (2005) further suggested two reasons

attributable to this phenomenon after 1997 Firstly the restructuring of financial sectors

like implementation of pegged exchange rate system and transaction of currency option

and contract lead to improvements which can avoid similar crisis in future Secondly

financial system of developed countries are so well organized that stock market and

banking operation are less vulnerable to exchange rate fluctuation

In Table 52 real values of GDP and exports replaced the nominal one in regression

equation 3 Similar results and conclusions could be drawn

25

Table 51

Empirical results of regression equation 3

based on nominal values of exports and GDP

Independent

Variables

1988-1992 1993-1997 1998-2002 2003-2004 1988-2004

Constant 3438

(18597)

2974

(1857)

0966

(5753)

0457

(1653)

2569

(2755)

log Yi 1157

(93901)

1222

(10687)

1364

(98397)

1295

(59454)

1203

(179786)

log Yj 1016

(84303)

1008

(91165)

1215

(90192)

1182

(54609)

1046

(160182)

log Ni -0238

(-18409)

-0219

(-19762)

-0224

(-19141)

-0144

(-7936)

-0187

(-29098)

log Nj -0125

(-9624)

-0071

(-6442)

-0163

(-14185)

-009

(-499)

-0090

(-14138)

log Dij -0983

(-50493)

-1036

(-61597)

-0994

(-59095)

-0961

(-35954)

-0993

(-102673)

AFTA ij 1915

(6511)

2155

(19970)

2857

(3200)

2699

(19042)

2019

(34473)

exAFTA ij 0837

(7308)

1135

(23365)

1374

(26723)

1175

(14575)

0902

(30698)

imAFTA ij 0580

(5232)

0903

(19035)

0775

(15353)

0682

(8532)

0466

(1609)

Adjusted R2 0717 0748 0768 0763 0741

SEE 1572 1442 1442 1448 1506

Number of

observations

7888 9194 9822 3963 30867

Notes

1 T-values are in parentheses

2 denotes the coefficient is significant at 1 level denotes the coefficient is

significant at 5 level denotes the coefficient is significant at 10 level

3 The use of real GDP and export values is reported in the Table 52 which shows there

is little difference in the coefficients in the independent variables

26

Table 52

Empirical results of regression equation 3

based on real values of exports and GDP

Independent

Variables

1988-1992 1993-1997 1998-2002

2003-2004 1988-2004

Constant 3172

(17041)

2845

(1771)

0966

(5757)

0550

(200)

2293

(24637)

log real Yi 116

(94164)

1226

(107095)

1364

(98386)

1297

(59524)

123

(182883)

log real Yj 1020

(84573)

1011

(91405)

1216

(90191)

1184

(54681)

1072

(163403)

log Ni -0239

(-18510)

-0221

(-1994)

-0224

(-19115)

-0145

(-7989)

-02

(-31263)

log Nj -0127

(-977)

-0072

(-6594)

-0163

(-14186)

-0091

(-5049)

-0103

(-16203)

log Dij -0983

(-50598)

-1036

(-61676)

-0994

(-59109)

-0960

(-35959)

-0997

(-104061)

AFTA ij 1995

(679)

2174

(2016)

2859

(32014)

2707

(19101)

2200

(37693)

exAFTA ij 0914

(7984)

1143

(23365)

1374

(26712)

1179

(14630)

1025

(34982)

imAFTA ij 0657

(5936)

0911

(19224)

0778

(15404)

0686

(8584)

0586

(20301)

Adjusted R2 0718 0748 0767 0763 0744

SEE 157 144 1442 1446 1492

Number of

observations

7888 9194 9822 3963 30867

Notes `

1 T-values are in parentheses

2 denotes the coefficient is significant at 1 level denotes the coefficient is

significant at 5 level denotes the coefficient is significant at 10 level

3 For real GDP and export values year 2000 is used as base year

27

6 Implications and Recommendations

As China joins ASEAN Free Trade Agreement in January 2010 this creates changes on

the trade flow From the side of ASEAN this agreement helps ASEAN members to

access a prosperous Chinese market From Table 82 (Appendix) there is an increasing

trend of trade among AFTA and China during the period of 2004-2008 Both sides

consider each other as crucial trading partners As tariff barrier is removed after

formation of CAFTA this can increase intra regional trade among these countries and

reduce AFTA reliance on United States European Union and Japan (Chia 2004) With

countries of different stages of economic development integrated CAFTA can narrow

the income gap between member countries (Roberts 2004)

However empirical studies show mixed results As defined in Linder Hypothesis

countries with similar levels of income per capita will exhibit similar demand produce

similar and differentiated products and trade more with each other According to

empirical study conducted by Roberts (2004) the coefficient testing of the Linder

Hypothesis is insignificant which implies that CAFTA does not have similar demand

pattern and this can be supported by the classification of different stages of economic

development among the members Roberts (2004) noted that China Cambodia Laos

PDR Myanmar and Vietnam are Low Income economies Indonesia Thailand and

Philippines are Low Middle Income economies Singapore and Brunei Darussalam are

28

High Income Economies based on World Bankrsquos classification CAFTA creates an

enlarged market which increases in competition and investment (Chirathivat 2002)

Using SMART model Zhao Malouche and Newfarmer (2008) found out that there is

only a limited increase in intraregional trade and trade diversion when they assume full

liberalization of trade between China and ASEAN is implemented Chinarsquos imports

from ASEAN would increase by 72 especially from Singapore Thailand and

Malaysia On the other hand according to the simulation conducted by the ASEAN

Secretariat (2001) CAFTA would increase ASEANs exports to China and Chinese

export to ASEAN by 48 and 551 respectively (China amp World Economy 2003)

Although previous studies had mixed results CAFTA does provide a platform for China

and ASEAN to establish a legal system for trade investment and service that complies

with the rules of WTO and international standards This allows promotion of freer trade

and attracts investment from the foreign countries (Zhang 2006)

16

country i and j increases transportation costs time required for delivery and

communication failures Volume of trade between two countries is inversely correlated

with distance

In addition there are different expectations for coefficients of AFTAij exAFTAij and

imAFTAij AFTAij is expected to be positive and reflects the creation effect of

intraregional trade due to reduction of tariff rates and elimination of non tariff barriers

among AFTA This indicates members of AFTA have trade more with its members than

hypothetical trade level Dummy variables exAFTAij and imAFTAij captures the ldquoexport

trade diversionrdquo and ldquoimport trade diversionrdquo respectively The formation of Free Trade

Area is expected to lead to a decline of trade among member countries and nonmembers

countries (Tang 2005) Endoh (1999) who coined the term ldquoexport trade diversionrdquo

states that negative and statically significant coefficient of exAFTAij indicates that this

economic integration has caused the member countries to export their products within

the bloc rather than those outside the bloc For imAFTAij if its coefficient is negative

and statistically significant this means the members have switched their importing

activities from nonmembers to members

43 Data Description and Sources

To compare the impacts of AFTA overtime in addition to the pooled data of 1988-2004

17

the data is divided into four periods ie 1988-1992 1993-1997 1998-2002 and

2003-2004 Concerning the first breakdown of 1988-1992 and 1993-1997 this can

examine the changes in the trade flow between the member and nonmember countries

before and after the formation of AFTA For the division of 1993-1997 and 1998-2002

this can test whether the trade flow was adversely affected by 1997 Asian Financial

Crisis For 1998-2002 and 2003-2004 this can explain whether Outbreak of SARS had

adverse impacts on trade in Asian economies

The data set covers the bilateral trade flow for 46 countries They include 10 members

of AFTA and 36 nonmember countries The nonmember countries include Austria

Belgium-Luxembourg Finland France Germany Ireland Italy Netherlands Portugal

Spain Denmark Sweden United Kingdom Algeria Argentina Australia Brazil

Canada Chile China Colombia Czech Republic Egypt Japan Hong Kong Iceland

India Iran Mexico Norway New Zealand Poland Russia South Korea Switzerland

and the United States

For the dependent variable the annual export data are extracted from the Direction of

Trade Statistics GDP and population are obtained from The World Economic Outlook

and International Financial Statistics All export values and GDP are in US million

dollars Distance is collected from the Great Circle Distance between Cities The

physical distance is measured by the capital cities of 46 member and nonmember

18

countries in kilometers The values of AFTAij exAFTAij and imAFTAij depend on

countries that paired in the observations The number of observation for the pooled

sample is 30867 Some of the data are not available in the data base especially for

period of 1980s in developing countries

19

5 Empirical Results

Ordinary Least Square result for regression equation 3 is presented in Table 51 The

values of adjusted coefficient of determination in 1988-1992 and 1993-1997 are 0717

and 0748 respectively For 1998-2002 and 2003-2004 values of adjusted coefficient of

determination are 0768 and 0763 This means over 70 variation of export values

between country i and country j around its mean can be explained by the independent

variables in regression equation 3 adjusted for degree of freedom

51 Explanation of Gravity Model

All estimated coefficient are statistically significant different from zero at 1 level of

significance The coefficient of Yi Yj and Dij fulfill our expectations as stated in the

gravity model This shows gravity model plays a major role in explaining pattern of

trade flow in modern society Trade is positively related to GDP Larger economies tend

to have higher demand for imports and produce larger amount of goods for exports

Similar to the results of Endoh (1999) the coefficient of population is negative which

means increase in population will cause a decline in trade as the country produces a

wider range of product

The coefficient of Dij is negative and statistically significant Although there are

improvements in transportation technologies which can reduce the transportation cost

20

and facilitate transportation of goods between both importing and exporting countries

over time distance between countries still remains one of the most important

determinants in trade activities

52 Intraregional trade bias in AFTA

The coefficients of AFTA ij are positive and statistically significant It increases from

1915 in 1988-1992 to 2155 in 1993-1997 This shows there is trade creation effect

after the formation of AFTA This is consistent with the previous study like Tang (2005)

and Thornton and Goglio (2002) The low tariff rate facilitates trade in AFTA

After the 1997 Asian Financial Crisis the poor economic performance did not inhibited

the member countries to export goods to each other as there is a sharp jump in this

coefficient to 2857 New admission of Lao PDR and Myanmar in 1997 stimulated trade

creation effects Average regional CEPT rate for products in the Inclusion List has

dropped from 1276 in 1993 to 505 in 1998 (Jr Yee and Azhari 1998) Elliot and

Ikemoto (2004) pointed out that this regional economic shock in the form of currency

crisis created latent forces institutionalizing interdependence within the bloc

On the contrary after outbreak of SARS in 2003 the coefficient of AFTAij decreases to

2699 To further explain SARS is a highly infectious respiratory disease that had

caused doom in East Asian economies Within AFTA Singapore and Vietnam were hard

21

hit by SARS People tend to avoid social interaction which led to a slump in business

transactions The unemployment rate increased and demand for goods and services fell

Although a new arrangement of CEPT Rules of Origin and Operational Certification

Procedures which could promote trade among AFTA has been implemented on 1

January 2004 intraregional trade had declined In addition rise of trade among

nonmember countries could explain this decline As China has formally entered into

WTO in 2001 exports of ASEAN countries need to compete with Chinese products in

both export and ASEAN domestic market and ASEAN exporters would lose their

comparative advantage when developed countries give tariff concessions to China

(Kwan and Qiu 2003)

53 Export and Import Trade Diversion between member and non member countries

Finally the dummy variables of exAFTA ij and imAFTA ij have signs opposite to our

expectations They are statistically significant at 1 level of significance The positive

sign of exAFTA ij and imAFTA ij indicate that members and nonmembers have traded

with each other to greater extent than the hypothetical trade level throughout 1988-2004

(Endoh 1999) The results indicate negative trade diversion effect in AFTA

The coefficient of exAFTAij has a continuous increase from 0837 in 1988-1992 to

1135 in 1993-1997 The positive sign of this coefficient implies that the member

22

countries prefer to export goods to nonmember rather than members after the formation

of AFTA This implies AFTA members adopted export oriented strategies that promoted

export (Nguyen 2009)

The coefficient of exAFTAij increases to 1374 after 1997 The upward trend in

exAFTAij shows there is strengthening of negative export trade diversion throughout the

period of 1992-2002 The model of Elliot and Ikemoto (2004) also had similar results

and further explained the sharp jump in exAFTAij is caused by the devaluation of

ASEAN currencies after 1997 Asian Financial crisis as shown in Figure 81 (Appendix)

This could increase the competitiveness of ASEAN exports since they were relatively

cheaper when compared with the products of nonmember countries This boosted

ASEAN export trade with nonmembers

After the outbreak of SARS exAFTAij coefficient falls to 1175 in the period 2003-2004

which means there is weakening of negative trade diversion The outbreak of SARS has

caused temporary shock and persistent shock to Hong Kong and Chinese economies

Lee (2004) suggested that SARS led to a loss of GDP Hong Kong which was seriously

affected has experienced a decline in GDP by 263 GDP of Taiwan and Singapore

also were decreased by 049 and 047 respectively This reduction showed there was

a fall in demand for goods and services of ASEAN countries This could also be

explained by the slight appreciation of ASEAN currency after 2002 Value of ASEAN

23

currency increased relative to other foreign countries and ASEAN products were

relatively more expensive Therefore AFTA members prefer to export their goods to

members rather than nonmembers

The dummy variable imAFTAij measures import trade diversion of AFTA Its

coefficient increases from 058 in 1988-1992 to 0903 in 1993-1997 The upward trend

reveals that dynamic network of domestic production and foreign investment projects in

AFTA members caused a rise in its imports from nonmember countries (Nguyen 2009)

This fall in imAFTA ij after 1997 Asian Financial Crisis and outbreak of SARS implies

there is a weakening of negative import trade diversion ASEAN prefer to import goods

from members rather than nonmembers but the effects are small relative to the

coefficient of AFTAij As explained before devaluation of ASEAN currency means

foreign goods are more expensive So they prefer to import from members After the

outbreak of SARS the coefficient of imAFTA ij further drops to 0682 Spread of

diseases generated negative impacts to economies in Hong Kong and China which are

major trading partners of AFTA These two countries had the highest probable cases of

SARS This is one of the reasons why AFTA members prefer to import more goods

from members rather than nonmembers

Trade creation and diversion are subjected to changes in external economic environment

AFTA strengthened cooperation with all member countries in 1997 Asian Financial

24

Crisis and urged the members to undertake policy to promote trade which can in turn

speed up economic recovery When compared with outbreak of SARS which caused an

economic downturn in nonmember countries AFTA demonstrates an economic

regionalism that united members in the bloc As shown in the econometric results

AFTA members prefer to trade more among themselves rather than nonmembers

To a certain extent exchange rate volatility did not play a significant role in affecting

trade Most of economies in East Asia adopt a ldquomanaged floatrdquo exchange rate policy

which is beneficial to accomplish economic goals and objectives (Martin 2008) The

2SLS results of Tang (2005) shows that coefficient of exchange rate volatility is positive

which is opposite to our expectation but it is statically insignificant in the pooled sample

Although this coefficient is negative in OLS estimation overall effects of exchange rate

volatility on trade has reduced over time Tang (2005) further suggested two reasons

attributable to this phenomenon after 1997 Firstly the restructuring of financial sectors

like implementation of pegged exchange rate system and transaction of currency option

and contract lead to improvements which can avoid similar crisis in future Secondly

financial system of developed countries are so well organized that stock market and

banking operation are less vulnerable to exchange rate fluctuation

In Table 52 real values of GDP and exports replaced the nominal one in regression

equation 3 Similar results and conclusions could be drawn

25

Table 51

Empirical results of regression equation 3

based on nominal values of exports and GDP

Independent

Variables

1988-1992 1993-1997 1998-2002 2003-2004 1988-2004

Constant 3438

(18597)

2974

(1857)

0966

(5753)

0457

(1653)

2569

(2755)

log Yi 1157

(93901)

1222

(10687)

1364

(98397)

1295

(59454)

1203

(179786)

log Yj 1016

(84303)

1008

(91165)

1215

(90192)

1182

(54609)

1046

(160182)

log Ni -0238

(-18409)

-0219

(-19762)

-0224

(-19141)

-0144

(-7936)

-0187

(-29098)

log Nj -0125

(-9624)

-0071

(-6442)

-0163

(-14185)

-009

(-499)

-0090

(-14138)

log Dij -0983

(-50493)

-1036

(-61597)

-0994

(-59095)

-0961

(-35954)

-0993

(-102673)

AFTA ij 1915

(6511)

2155

(19970)

2857

(3200)

2699

(19042)

2019

(34473)

exAFTA ij 0837

(7308)

1135

(23365)

1374

(26723)

1175

(14575)

0902

(30698)

imAFTA ij 0580

(5232)

0903

(19035)

0775

(15353)

0682

(8532)

0466

(1609)

Adjusted R2 0717 0748 0768 0763 0741

SEE 1572 1442 1442 1448 1506

Number of

observations

7888 9194 9822 3963 30867

Notes

1 T-values are in parentheses

2 denotes the coefficient is significant at 1 level denotes the coefficient is

significant at 5 level denotes the coefficient is significant at 10 level

3 The use of real GDP and export values is reported in the Table 52 which shows there

is little difference in the coefficients in the independent variables

26

Table 52

Empirical results of regression equation 3

based on real values of exports and GDP

Independent

Variables

1988-1992 1993-1997 1998-2002

2003-2004 1988-2004

Constant 3172

(17041)

2845

(1771)

0966

(5757)

0550

(200)

2293

(24637)

log real Yi 116

(94164)

1226

(107095)

1364

(98386)

1297

(59524)

123

(182883)

log real Yj 1020

(84573)

1011

(91405)

1216

(90191)

1184

(54681)

1072

(163403)

log Ni -0239

(-18510)

-0221

(-1994)

-0224

(-19115)

-0145

(-7989)

-02

(-31263)

log Nj -0127

(-977)

-0072

(-6594)

-0163

(-14186)

-0091

(-5049)

-0103

(-16203)

log Dij -0983

(-50598)

-1036

(-61676)

-0994

(-59109)

-0960

(-35959)

-0997

(-104061)

AFTA ij 1995

(679)

2174

(2016)

2859

(32014)

2707

(19101)

2200

(37693)

exAFTA ij 0914

(7984)

1143

(23365)

1374

(26712)

1179

(14630)

1025

(34982)

imAFTA ij 0657

(5936)

0911

(19224)

0778

(15404)

0686

(8584)

0586

(20301)

Adjusted R2 0718 0748 0767 0763 0744

SEE 157 144 1442 1446 1492

Number of

observations

7888 9194 9822 3963 30867

Notes `

1 T-values are in parentheses

2 denotes the coefficient is significant at 1 level denotes the coefficient is

significant at 5 level denotes the coefficient is significant at 10 level

3 For real GDP and export values year 2000 is used as base year

27

6 Implications and Recommendations

As China joins ASEAN Free Trade Agreement in January 2010 this creates changes on

the trade flow From the side of ASEAN this agreement helps ASEAN members to

access a prosperous Chinese market From Table 82 (Appendix) there is an increasing

trend of trade among AFTA and China during the period of 2004-2008 Both sides

consider each other as crucial trading partners As tariff barrier is removed after

formation of CAFTA this can increase intra regional trade among these countries and

reduce AFTA reliance on United States European Union and Japan (Chia 2004) With

countries of different stages of economic development integrated CAFTA can narrow

the income gap between member countries (Roberts 2004)

However empirical studies show mixed results As defined in Linder Hypothesis

countries with similar levels of income per capita will exhibit similar demand produce

similar and differentiated products and trade more with each other According to

empirical study conducted by Roberts (2004) the coefficient testing of the Linder

Hypothesis is insignificant which implies that CAFTA does not have similar demand

pattern and this can be supported by the classification of different stages of economic

development among the members Roberts (2004) noted that China Cambodia Laos

PDR Myanmar and Vietnam are Low Income economies Indonesia Thailand and

Philippines are Low Middle Income economies Singapore and Brunei Darussalam are

28

High Income Economies based on World Bankrsquos classification CAFTA creates an

enlarged market which increases in competition and investment (Chirathivat 2002)

Using SMART model Zhao Malouche and Newfarmer (2008) found out that there is

only a limited increase in intraregional trade and trade diversion when they assume full

liberalization of trade between China and ASEAN is implemented Chinarsquos imports

from ASEAN would increase by 72 especially from Singapore Thailand and

Malaysia On the other hand according to the simulation conducted by the ASEAN

Secretariat (2001) CAFTA would increase ASEANs exports to China and Chinese

export to ASEAN by 48 and 551 respectively (China amp World Economy 2003)

Although previous studies had mixed results CAFTA does provide a platform for China

and ASEAN to establish a legal system for trade investment and service that complies

with the rules of WTO and international standards This allows promotion of freer trade

and attracts investment from the foreign countries (Zhang 2006)

17

the data is divided into four periods ie 1988-1992 1993-1997 1998-2002 and

2003-2004 Concerning the first breakdown of 1988-1992 and 1993-1997 this can

examine the changes in the trade flow between the member and nonmember countries

before and after the formation of AFTA For the division of 1993-1997 and 1998-2002

this can test whether the trade flow was adversely affected by 1997 Asian Financial

Crisis For 1998-2002 and 2003-2004 this can explain whether Outbreak of SARS had

adverse impacts on trade in Asian economies

The data set covers the bilateral trade flow for 46 countries They include 10 members

of AFTA and 36 nonmember countries The nonmember countries include Austria

Belgium-Luxembourg Finland France Germany Ireland Italy Netherlands Portugal

Spain Denmark Sweden United Kingdom Algeria Argentina Australia Brazil

Canada Chile China Colombia Czech Republic Egypt Japan Hong Kong Iceland

India Iran Mexico Norway New Zealand Poland Russia South Korea Switzerland

and the United States

For the dependent variable the annual export data are extracted from the Direction of

Trade Statistics GDP and population are obtained from The World Economic Outlook

and International Financial Statistics All export values and GDP are in US million

dollars Distance is collected from the Great Circle Distance between Cities The

physical distance is measured by the capital cities of 46 member and nonmember

18

countries in kilometers The values of AFTAij exAFTAij and imAFTAij depend on

countries that paired in the observations The number of observation for the pooled

sample is 30867 Some of the data are not available in the data base especially for

period of 1980s in developing countries

19

5 Empirical Results

Ordinary Least Square result for regression equation 3 is presented in Table 51 The

values of adjusted coefficient of determination in 1988-1992 and 1993-1997 are 0717

and 0748 respectively For 1998-2002 and 2003-2004 values of adjusted coefficient of

determination are 0768 and 0763 This means over 70 variation of export values

between country i and country j around its mean can be explained by the independent

variables in regression equation 3 adjusted for degree of freedom

51 Explanation of Gravity Model

All estimated coefficient are statistically significant different from zero at 1 level of

significance The coefficient of Yi Yj and Dij fulfill our expectations as stated in the

gravity model This shows gravity model plays a major role in explaining pattern of

trade flow in modern society Trade is positively related to GDP Larger economies tend

to have higher demand for imports and produce larger amount of goods for exports

Similar to the results of Endoh (1999) the coefficient of population is negative which

means increase in population will cause a decline in trade as the country produces a

wider range of product

The coefficient of Dij is negative and statistically significant Although there are

improvements in transportation technologies which can reduce the transportation cost

20

and facilitate transportation of goods between both importing and exporting countries

over time distance between countries still remains one of the most important

determinants in trade activities

52 Intraregional trade bias in AFTA

The coefficients of AFTA ij are positive and statistically significant It increases from

1915 in 1988-1992 to 2155 in 1993-1997 This shows there is trade creation effect

after the formation of AFTA This is consistent with the previous study like Tang (2005)

and Thornton and Goglio (2002) The low tariff rate facilitates trade in AFTA

After the 1997 Asian Financial Crisis the poor economic performance did not inhibited

the member countries to export goods to each other as there is a sharp jump in this

coefficient to 2857 New admission of Lao PDR and Myanmar in 1997 stimulated trade

creation effects Average regional CEPT rate for products in the Inclusion List has

dropped from 1276 in 1993 to 505 in 1998 (Jr Yee and Azhari 1998) Elliot and

Ikemoto (2004) pointed out that this regional economic shock in the form of currency

crisis created latent forces institutionalizing interdependence within the bloc

On the contrary after outbreak of SARS in 2003 the coefficient of AFTAij decreases to

2699 To further explain SARS is a highly infectious respiratory disease that had

caused doom in East Asian economies Within AFTA Singapore and Vietnam were hard

21

hit by SARS People tend to avoid social interaction which led to a slump in business

transactions The unemployment rate increased and demand for goods and services fell

Although a new arrangement of CEPT Rules of Origin and Operational Certification

Procedures which could promote trade among AFTA has been implemented on 1

January 2004 intraregional trade had declined In addition rise of trade among

nonmember countries could explain this decline As China has formally entered into

WTO in 2001 exports of ASEAN countries need to compete with Chinese products in

both export and ASEAN domestic market and ASEAN exporters would lose their

comparative advantage when developed countries give tariff concessions to China

(Kwan and Qiu 2003)

53 Export and Import Trade Diversion between member and non member countries

Finally the dummy variables of exAFTA ij and imAFTA ij have signs opposite to our

expectations They are statistically significant at 1 level of significance The positive

sign of exAFTA ij and imAFTA ij indicate that members and nonmembers have traded

with each other to greater extent than the hypothetical trade level throughout 1988-2004

(Endoh 1999) The results indicate negative trade diversion effect in AFTA

The coefficient of exAFTAij has a continuous increase from 0837 in 1988-1992 to

1135 in 1993-1997 The positive sign of this coefficient implies that the member

22

countries prefer to export goods to nonmember rather than members after the formation

of AFTA This implies AFTA members adopted export oriented strategies that promoted

export (Nguyen 2009)

The coefficient of exAFTAij increases to 1374 after 1997 The upward trend in

exAFTAij shows there is strengthening of negative export trade diversion throughout the

period of 1992-2002 The model of Elliot and Ikemoto (2004) also had similar results

and further explained the sharp jump in exAFTAij is caused by the devaluation of

ASEAN currencies after 1997 Asian Financial crisis as shown in Figure 81 (Appendix)

This could increase the competitiveness of ASEAN exports since they were relatively

cheaper when compared with the products of nonmember countries This boosted

ASEAN export trade with nonmembers

After the outbreak of SARS exAFTAij coefficient falls to 1175 in the period 2003-2004

which means there is weakening of negative trade diversion The outbreak of SARS has

caused temporary shock and persistent shock to Hong Kong and Chinese economies

Lee (2004) suggested that SARS led to a loss of GDP Hong Kong which was seriously

affected has experienced a decline in GDP by 263 GDP of Taiwan and Singapore

also were decreased by 049 and 047 respectively This reduction showed there was

a fall in demand for goods and services of ASEAN countries This could also be

explained by the slight appreciation of ASEAN currency after 2002 Value of ASEAN

23

currency increased relative to other foreign countries and ASEAN products were

relatively more expensive Therefore AFTA members prefer to export their goods to

members rather than nonmembers

The dummy variable imAFTAij measures import trade diversion of AFTA Its

coefficient increases from 058 in 1988-1992 to 0903 in 1993-1997 The upward trend

reveals that dynamic network of domestic production and foreign investment projects in

AFTA members caused a rise in its imports from nonmember countries (Nguyen 2009)

This fall in imAFTA ij after 1997 Asian Financial Crisis and outbreak of SARS implies

there is a weakening of negative import trade diversion ASEAN prefer to import goods

from members rather than nonmembers but the effects are small relative to the

coefficient of AFTAij As explained before devaluation of ASEAN currency means

foreign goods are more expensive So they prefer to import from members After the

outbreak of SARS the coefficient of imAFTA ij further drops to 0682 Spread of

diseases generated negative impacts to economies in Hong Kong and China which are

major trading partners of AFTA These two countries had the highest probable cases of

SARS This is one of the reasons why AFTA members prefer to import more goods

from members rather than nonmembers

Trade creation and diversion are subjected to changes in external economic environment

AFTA strengthened cooperation with all member countries in 1997 Asian Financial

24

Crisis and urged the members to undertake policy to promote trade which can in turn

speed up economic recovery When compared with outbreak of SARS which caused an

economic downturn in nonmember countries AFTA demonstrates an economic

regionalism that united members in the bloc As shown in the econometric results

AFTA members prefer to trade more among themselves rather than nonmembers

To a certain extent exchange rate volatility did not play a significant role in affecting

trade Most of economies in East Asia adopt a ldquomanaged floatrdquo exchange rate policy

which is beneficial to accomplish economic goals and objectives (Martin 2008) The

2SLS results of Tang (2005) shows that coefficient of exchange rate volatility is positive

which is opposite to our expectation but it is statically insignificant in the pooled sample

Although this coefficient is negative in OLS estimation overall effects of exchange rate

volatility on trade has reduced over time Tang (2005) further suggested two reasons

attributable to this phenomenon after 1997 Firstly the restructuring of financial sectors

like implementation of pegged exchange rate system and transaction of currency option

and contract lead to improvements which can avoid similar crisis in future Secondly

financial system of developed countries are so well organized that stock market and

banking operation are less vulnerable to exchange rate fluctuation

In Table 52 real values of GDP and exports replaced the nominal one in regression

equation 3 Similar results and conclusions could be drawn

25

Table 51

Empirical results of regression equation 3

based on nominal values of exports and GDP

Independent

Variables

1988-1992 1993-1997 1998-2002 2003-2004 1988-2004

Constant 3438

(18597)

2974

(1857)

0966

(5753)

0457

(1653)

2569

(2755)

log Yi 1157

(93901)

1222

(10687)

1364

(98397)

1295

(59454)

1203

(179786)

log Yj 1016

(84303)

1008

(91165)

1215

(90192)

1182

(54609)

1046

(160182)

log Ni -0238

(-18409)

-0219

(-19762)

-0224

(-19141)

-0144

(-7936)

-0187

(-29098)

log Nj -0125

(-9624)

-0071

(-6442)

-0163

(-14185)

-009

(-499)

-0090

(-14138)

log Dij -0983

(-50493)

-1036

(-61597)

-0994

(-59095)

-0961

(-35954)

-0993

(-102673)

AFTA ij 1915

(6511)

2155

(19970)

2857

(3200)

2699

(19042)

2019

(34473)

exAFTA ij 0837

(7308)

1135

(23365)

1374

(26723)

1175

(14575)

0902

(30698)

imAFTA ij 0580

(5232)

0903

(19035)

0775

(15353)

0682

(8532)

0466

(1609)

Adjusted R2 0717 0748 0768 0763 0741

SEE 1572 1442 1442 1448 1506

Number of

observations

7888 9194 9822 3963 30867

Notes

1 T-values are in parentheses

2 denotes the coefficient is significant at 1 level denotes the coefficient is

significant at 5 level denotes the coefficient is significant at 10 level

3 The use of real GDP and export values is reported in the Table 52 which shows there

is little difference in the coefficients in the independent variables

26

Table 52

Empirical results of regression equation 3

based on real values of exports and GDP

Independent

Variables

1988-1992 1993-1997 1998-2002

2003-2004 1988-2004

Constant 3172

(17041)

2845

(1771)

0966

(5757)

0550

(200)

2293

(24637)

log real Yi 116

(94164)

1226

(107095)

1364

(98386)

1297

(59524)

123

(182883)

log real Yj 1020

(84573)

1011

(91405)

1216

(90191)

1184

(54681)

1072

(163403)

log Ni -0239

(-18510)

-0221

(-1994)

-0224

(-19115)

-0145

(-7989)

-02

(-31263)

log Nj -0127

(-977)

-0072

(-6594)

-0163

(-14186)

-0091

(-5049)

-0103

(-16203)

log Dij -0983

(-50598)

-1036

(-61676)

-0994

(-59109)

-0960

(-35959)

-0997

(-104061)

AFTA ij 1995

(679)

2174

(2016)

2859

(32014)

2707

(19101)

2200

(37693)

exAFTA ij 0914

(7984)

1143

(23365)

1374

(26712)

1179

(14630)

1025

(34982)

imAFTA ij 0657

(5936)

0911

(19224)

0778

(15404)

0686

(8584)

0586

(20301)

Adjusted R2 0718 0748 0767 0763 0744

SEE 157 144 1442 1446 1492

Number of

observations

7888 9194 9822 3963 30867

Notes `

1 T-values are in parentheses

2 denotes the coefficient is significant at 1 level denotes the coefficient is

significant at 5 level denotes the coefficient is significant at 10 level

3 For real GDP and export values year 2000 is used as base year

27

6 Implications and Recommendations

As China joins ASEAN Free Trade Agreement in January 2010 this creates changes on

the trade flow From the side of ASEAN this agreement helps ASEAN members to

access a prosperous Chinese market From Table 82 (Appendix) there is an increasing

trend of trade among AFTA and China during the period of 2004-2008 Both sides

consider each other as crucial trading partners As tariff barrier is removed after

formation of CAFTA this can increase intra regional trade among these countries and

reduce AFTA reliance on United States European Union and Japan (Chia 2004) With

countries of different stages of economic development integrated CAFTA can narrow

the income gap between member countries (Roberts 2004)

However empirical studies show mixed results As defined in Linder Hypothesis

countries with similar levels of income per capita will exhibit similar demand produce

similar and differentiated products and trade more with each other According to

empirical study conducted by Roberts (2004) the coefficient testing of the Linder

Hypothesis is insignificant which implies that CAFTA does not have similar demand

pattern and this can be supported by the classification of different stages of economic

development among the members Roberts (2004) noted that China Cambodia Laos

PDR Myanmar and Vietnam are Low Income economies Indonesia Thailand and

Philippines are Low Middle Income economies Singapore and Brunei Darussalam are

28

High Income Economies based on World Bankrsquos classification CAFTA creates an

enlarged market which increases in competition and investment (Chirathivat 2002)

Using SMART model Zhao Malouche and Newfarmer (2008) found out that there is

only a limited increase in intraregional trade and trade diversion when they assume full

liberalization of trade between China and ASEAN is implemented Chinarsquos imports

from ASEAN would increase by 72 especially from Singapore Thailand and

Malaysia On the other hand according to the simulation conducted by the ASEAN

Secretariat (2001) CAFTA would increase ASEANs exports to China and Chinese

export to ASEAN by 48 and 551 respectively (China amp World Economy 2003)

Although previous studies had mixed results CAFTA does provide a platform for China

and ASEAN to establish a legal system for trade investment and service that complies

with the rules of WTO and international standards This allows promotion of freer trade

and attracts investment from the foreign countries (Zhang 2006)

18

countries in kilometers The values of AFTAij exAFTAij and imAFTAij depend on

countries that paired in the observations The number of observation for the pooled

sample is 30867 Some of the data are not available in the data base especially for

period of 1980s in developing countries

19

5 Empirical Results

Ordinary Least Square result for regression equation 3 is presented in Table 51 The

values of adjusted coefficient of determination in 1988-1992 and 1993-1997 are 0717

and 0748 respectively For 1998-2002 and 2003-2004 values of adjusted coefficient of

determination are 0768 and 0763 This means over 70 variation of export values

between country i and country j around its mean can be explained by the independent

variables in regression equation 3 adjusted for degree of freedom

51 Explanation of Gravity Model

All estimated coefficient are statistically significant different from zero at 1 level of

significance The coefficient of Yi Yj and Dij fulfill our expectations as stated in the

gravity model This shows gravity model plays a major role in explaining pattern of

trade flow in modern society Trade is positively related to GDP Larger economies tend

to have higher demand for imports and produce larger amount of goods for exports

Similar to the results of Endoh (1999) the coefficient of population is negative which

means increase in population will cause a decline in trade as the country produces a

wider range of product

The coefficient of Dij is negative and statistically significant Although there are

improvements in transportation technologies which can reduce the transportation cost

20

and facilitate transportation of goods between both importing and exporting countries

over time distance between countries still remains one of the most important

determinants in trade activities

52 Intraregional trade bias in AFTA

The coefficients of AFTA ij are positive and statistically significant It increases from

1915 in 1988-1992 to 2155 in 1993-1997 This shows there is trade creation effect

after the formation of AFTA This is consistent with the previous study like Tang (2005)

and Thornton and Goglio (2002) The low tariff rate facilitates trade in AFTA

After the 1997 Asian Financial Crisis the poor economic performance did not inhibited

the member countries to export goods to each other as there is a sharp jump in this

coefficient to 2857 New admission of Lao PDR and Myanmar in 1997 stimulated trade

creation effects Average regional CEPT rate for products in the Inclusion List has

dropped from 1276 in 1993 to 505 in 1998 (Jr Yee and Azhari 1998) Elliot and

Ikemoto (2004) pointed out that this regional economic shock in the form of currency

crisis created latent forces institutionalizing interdependence within the bloc

On the contrary after outbreak of SARS in 2003 the coefficient of AFTAij decreases to

2699 To further explain SARS is a highly infectious respiratory disease that had

caused doom in East Asian economies Within AFTA Singapore and Vietnam were hard

21

hit by SARS People tend to avoid social interaction which led to a slump in business

transactions The unemployment rate increased and demand for goods and services fell

Although a new arrangement of CEPT Rules of Origin and Operational Certification

Procedures which could promote trade among AFTA has been implemented on 1

January 2004 intraregional trade had declined In addition rise of trade among

nonmember countries could explain this decline As China has formally entered into

WTO in 2001 exports of ASEAN countries need to compete with Chinese products in

both export and ASEAN domestic market and ASEAN exporters would lose their

comparative advantage when developed countries give tariff concessions to China

(Kwan and Qiu 2003)

53 Export and Import Trade Diversion between member and non member countries

Finally the dummy variables of exAFTA ij and imAFTA ij have signs opposite to our

expectations They are statistically significant at 1 level of significance The positive

sign of exAFTA ij and imAFTA ij indicate that members and nonmembers have traded

with each other to greater extent than the hypothetical trade level throughout 1988-2004

(Endoh 1999) The results indicate negative trade diversion effect in AFTA

The coefficient of exAFTAij has a continuous increase from 0837 in 1988-1992 to

1135 in 1993-1997 The positive sign of this coefficient implies that the member

22

countries prefer to export goods to nonmember rather than members after the formation

of AFTA This implies AFTA members adopted export oriented strategies that promoted

export (Nguyen 2009)

The coefficient of exAFTAij increases to 1374 after 1997 The upward trend in

exAFTAij shows there is strengthening of negative export trade diversion throughout the

period of 1992-2002 The model of Elliot and Ikemoto (2004) also had similar results

and further explained the sharp jump in exAFTAij is caused by the devaluation of

ASEAN currencies after 1997 Asian Financial crisis as shown in Figure 81 (Appendix)

This could increase the competitiveness of ASEAN exports since they were relatively

cheaper when compared with the products of nonmember countries This boosted

ASEAN export trade with nonmembers

After the outbreak of SARS exAFTAij coefficient falls to 1175 in the period 2003-2004

which means there is weakening of negative trade diversion The outbreak of SARS has

caused temporary shock and persistent shock to Hong Kong and Chinese economies

Lee (2004) suggested that SARS led to a loss of GDP Hong Kong which was seriously

affected has experienced a decline in GDP by 263 GDP of Taiwan and Singapore

also were decreased by 049 and 047 respectively This reduction showed there was

a fall in demand for goods and services of ASEAN countries This could also be

explained by the slight appreciation of ASEAN currency after 2002 Value of ASEAN

23

currency increased relative to other foreign countries and ASEAN products were

relatively more expensive Therefore AFTA members prefer to export their goods to

members rather than nonmembers

The dummy variable imAFTAij measures import trade diversion of AFTA Its

coefficient increases from 058 in 1988-1992 to 0903 in 1993-1997 The upward trend

reveals that dynamic network of domestic production and foreign investment projects in

AFTA members caused a rise in its imports from nonmember countries (Nguyen 2009)

This fall in imAFTA ij after 1997 Asian Financial Crisis and outbreak of SARS implies

there is a weakening of negative import trade diversion ASEAN prefer to import goods

from members rather than nonmembers but the effects are small relative to the

coefficient of AFTAij As explained before devaluation of ASEAN currency means

foreign goods are more expensive So they prefer to import from members After the

outbreak of SARS the coefficient of imAFTA ij further drops to 0682 Spread of

diseases generated negative impacts to economies in Hong Kong and China which are

major trading partners of AFTA These two countries had the highest probable cases of

SARS This is one of the reasons why AFTA members prefer to import more goods

from members rather than nonmembers

Trade creation and diversion are subjected to changes in external economic environment

AFTA strengthened cooperation with all member countries in 1997 Asian Financial

24

Crisis and urged the members to undertake policy to promote trade which can in turn

speed up economic recovery When compared with outbreak of SARS which caused an

economic downturn in nonmember countries AFTA demonstrates an economic

regionalism that united members in the bloc As shown in the econometric results

AFTA members prefer to trade more among themselves rather than nonmembers

To a certain extent exchange rate volatility did not play a significant role in affecting

trade Most of economies in East Asia adopt a ldquomanaged floatrdquo exchange rate policy

which is beneficial to accomplish economic goals and objectives (Martin 2008) The

2SLS results of Tang (2005) shows that coefficient of exchange rate volatility is positive

which is opposite to our expectation but it is statically insignificant in the pooled sample

Although this coefficient is negative in OLS estimation overall effects of exchange rate

volatility on trade has reduced over time Tang (2005) further suggested two reasons

attributable to this phenomenon after 1997 Firstly the restructuring of financial sectors

like implementation of pegged exchange rate system and transaction of currency option

and contract lead to improvements which can avoid similar crisis in future Secondly

financial system of developed countries are so well organized that stock market and

banking operation are less vulnerable to exchange rate fluctuation

In Table 52 real values of GDP and exports replaced the nominal one in regression

equation 3 Similar results and conclusions could be drawn

25

Table 51

Empirical results of regression equation 3

based on nominal values of exports and GDP

Independent

Variables

1988-1992 1993-1997 1998-2002 2003-2004 1988-2004

Constant 3438

(18597)

2974

(1857)

0966

(5753)

0457

(1653)

2569

(2755)

log Yi 1157

(93901)

1222

(10687)

1364

(98397)

1295

(59454)

1203

(179786)

log Yj 1016

(84303)

1008

(91165)

1215

(90192)

1182

(54609)

1046

(160182)

log Ni -0238

(-18409)

-0219

(-19762)

-0224

(-19141)

-0144

(-7936)

-0187

(-29098)

log Nj -0125

(-9624)

-0071

(-6442)

-0163

(-14185)

-009

(-499)

-0090

(-14138)

log Dij -0983

(-50493)

-1036

(-61597)

-0994

(-59095)

-0961

(-35954)

-0993

(-102673)

AFTA ij 1915

(6511)

2155

(19970)

2857

(3200)

2699

(19042)

2019

(34473)

exAFTA ij 0837

(7308)

1135

(23365)

1374

(26723)

1175

(14575)

0902

(30698)

imAFTA ij 0580

(5232)

0903

(19035)

0775

(15353)

0682

(8532)

0466

(1609)

Adjusted R2 0717 0748 0768 0763 0741

SEE 1572 1442 1442 1448 1506

Number of

observations

7888 9194 9822 3963 30867

Notes

1 T-values are in parentheses

2 denotes the coefficient is significant at 1 level denotes the coefficient is

significant at 5 level denotes the coefficient is significant at 10 level

3 The use of real GDP and export values is reported in the Table 52 which shows there

is little difference in the coefficients in the independent variables

26

Table 52

Empirical results of regression equation 3

based on real values of exports and GDP

Independent

Variables

1988-1992 1993-1997 1998-2002

2003-2004 1988-2004

Constant 3172

(17041)

2845

(1771)

0966

(5757)

0550

(200)

2293

(24637)

log real Yi 116

(94164)

1226

(107095)

1364

(98386)

1297

(59524)

123

(182883)

log real Yj 1020

(84573)

1011

(91405)

1216

(90191)

1184

(54681)

1072

(163403)

log Ni -0239

(-18510)

-0221

(-1994)

-0224

(-19115)

-0145

(-7989)

-02

(-31263)

log Nj -0127

(-977)

-0072

(-6594)

-0163

(-14186)

-0091

(-5049)

-0103

(-16203)

log Dij -0983

(-50598)

-1036

(-61676)

-0994

(-59109)

-0960

(-35959)

-0997

(-104061)

AFTA ij 1995

(679)

2174

(2016)

2859

(32014)

2707

(19101)

2200

(37693)

exAFTA ij 0914

(7984)

1143

(23365)

1374

(26712)

1179

(14630)

1025

(34982)

imAFTA ij 0657

(5936)

0911

(19224)

0778

(15404)

0686

(8584)

0586

(20301)

Adjusted R2 0718 0748 0767 0763 0744

SEE 157 144 1442 1446 1492

Number of

observations

7888 9194 9822 3963 30867

Notes `

1 T-values are in parentheses

2 denotes the coefficient is significant at 1 level denotes the coefficient is

significant at 5 level denotes the coefficient is significant at 10 level

3 For real GDP and export values year 2000 is used as base year

27

6 Implications and Recommendations

As China joins ASEAN Free Trade Agreement in January 2010 this creates changes on

the trade flow From the side of ASEAN this agreement helps ASEAN members to

access a prosperous Chinese market From Table 82 (Appendix) there is an increasing

trend of trade among AFTA and China during the period of 2004-2008 Both sides

consider each other as crucial trading partners As tariff barrier is removed after

formation of CAFTA this can increase intra regional trade among these countries and

reduce AFTA reliance on United States European Union and Japan (Chia 2004) With

countries of different stages of economic development integrated CAFTA can narrow

the income gap between member countries (Roberts 2004)

However empirical studies show mixed results As defined in Linder Hypothesis

countries with similar levels of income per capita will exhibit similar demand produce

similar and differentiated products and trade more with each other According to

empirical study conducted by Roberts (2004) the coefficient testing of the Linder

Hypothesis is insignificant which implies that CAFTA does not have similar demand

pattern and this can be supported by the classification of different stages of economic

development among the members Roberts (2004) noted that China Cambodia Laos

PDR Myanmar and Vietnam are Low Income economies Indonesia Thailand and

Philippines are Low Middle Income economies Singapore and Brunei Darussalam are

28

High Income Economies based on World Bankrsquos classification CAFTA creates an

enlarged market which increases in competition and investment (Chirathivat 2002)

Using SMART model Zhao Malouche and Newfarmer (2008) found out that there is

only a limited increase in intraregional trade and trade diversion when they assume full

liberalization of trade between China and ASEAN is implemented Chinarsquos imports

from ASEAN would increase by 72 especially from Singapore Thailand and

Malaysia On the other hand according to the simulation conducted by the ASEAN

Secretariat (2001) CAFTA would increase ASEANs exports to China and Chinese

export to ASEAN by 48 and 551 respectively (China amp World Economy 2003)

Although previous studies had mixed results CAFTA does provide a platform for China

and ASEAN to establish a legal system for trade investment and service that complies

with the rules of WTO and international standards This allows promotion of freer trade

and attracts investment from the foreign countries (Zhang 2006)

19

5 Empirical Results

Ordinary Least Square result for regression equation 3 is presented in Table 51 The

values of adjusted coefficient of determination in 1988-1992 and 1993-1997 are 0717

and 0748 respectively For 1998-2002 and 2003-2004 values of adjusted coefficient of

determination are 0768 and 0763 This means over 70 variation of export values

between country i and country j around its mean can be explained by the independent

variables in regression equation 3 adjusted for degree of freedom

51 Explanation of Gravity Model

All estimated coefficient are statistically significant different from zero at 1 level of

significance The coefficient of Yi Yj and Dij fulfill our expectations as stated in the

gravity model This shows gravity model plays a major role in explaining pattern of

trade flow in modern society Trade is positively related to GDP Larger economies tend

to have higher demand for imports and produce larger amount of goods for exports

Similar to the results of Endoh (1999) the coefficient of population is negative which

means increase in population will cause a decline in trade as the country produces a

wider range of product

The coefficient of Dij is negative and statistically significant Although there are

improvements in transportation technologies which can reduce the transportation cost

20

and facilitate transportation of goods between both importing and exporting countries

over time distance between countries still remains one of the most important

determinants in trade activities

52 Intraregional trade bias in AFTA

The coefficients of AFTA ij are positive and statistically significant It increases from

1915 in 1988-1992 to 2155 in 1993-1997 This shows there is trade creation effect

after the formation of AFTA This is consistent with the previous study like Tang (2005)

and Thornton and Goglio (2002) The low tariff rate facilitates trade in AFTA

After the 1997 Asian Financial Crisis the poor economic performance did not inhibited

the member countries to export goods to each other as there is a sharp jump in this

coefficient to 2857 New admission of Lao PDR and Myanmar in 1997 stimulated trade

creation effects Average regional CEPT rate for products in the Inclusion List has

dropped from 1276 in 1993 to 505 in 1998 (Jr Yee and Azhari 1998) Elliot and

Ikemoto (2004) pointed out that this regional economic shock in the form of currency

crisis created latent forces institutionalizing interdependence within the bloc

On the contrary after outbreak of SARS in 2003 the coefficient of AFTAij decreases to

2699 To further explain SARS is a highly infectious respiratory disease that had

caused doom in East Asian economies Within AFTA Singapore and Vietnam were hard

21

hit by SARS People tend to avoid social interaction which led to a slump in business

transactions The unemployment rate increased and demand for goods and services fell

Although a new arrangement of CEPT Rules of Origin and Operational Certification

Procedures which could promote trade among AFTA has been implemented on 1

January 2004 intraregional trade had declined In addition rise of trade among

nonmember countries could explain this decline As China has formally entered into

WTO in 2001 exports of ASEAN countries need to compete with Chinese products in

both export and ASEAN domestic market and ASEAN exporters would lose their

comparative advantage when developed countries give tariff concessions to China

(Kwan and Qiu 2003)

53 Export and Import Trade Diversion between member and non member countries

Finally the dummy variables of exAFTA ij and imAFTA ij have signs opposite to our

expectations They are statistically significant at 1 level of significance The positive

sign of exAFTA ij and imAFTA ij indicate that members and nonmembers have traded

with each other to greater extent than the hypothetical trade level throughout 1988-2004

(Endoh 1999) The results indicate negative trade diversion effect in AFTA

The coefficient of exAFTAij has a continuous increase from 0837 in 1988-1992 to

1135 in 1993-1997 The positive sign of this coefficient implies that the member

22

countries prefer to export goods to nonmember rather than members after the formation

of AFTA This implies AFTA members adopted export oriented strategies that promoted

export (Nguyen 2009)

The coefficient of exAFTAij increases to 1374 after 1997 The upward trend in

exAFTAij shows there is strengthening of negative export trade diversion throughout the

period of 1992-2002 The model of Elliot and Ikemoto (2004) also had similar results

and further explained the sharp jump in exAFTAij is caused by the devaluation of

ASEAN currencies after 1997 Asian Financial crisis as shown in Figure 81 (Appendix)

This could increase the competitiveness of ASEAN exports since they were relatively

cheaper when compared with the products of nonmember countries This boosted

ASEAN export trade with nonmembers

After the outbreak of SARS exAFTAij coefficient falls to 1175 in the period 2003-2004

which means there is weakening of negative trade diversion The outbreak of SARS has

caused temporary shock and persistent shock to Hong Kong and Chinese economies

Lee (2004) suggested that SARS led to a loss of GDP Hong Kong which was seriously

affected has experienced a decline in GDP by 263 GDP of Taiwan and Singapore

also were decreased by 049 and 047 respectively This reduction showed there was

a fall in demand for goods and services of ASEAN countries This could also be

explained by the slight appreciation of ASEAN currency after 2002 Value of ASEAN

23

currency increased relative to other foreign countries and ASEAN products were

relatively more expensive Therefore AFTA members prefer to export their goods to

members rather than nonmembers

The dummy variable imAFTAij measures import trade diversion of AFTA Its

coefficient increases from 058 in 1988-1992 to 0903 in 1993-1997 The upward trend

reveals that dynamic network of domestic production and foreign investment projects in

AFTA members caused a rise in its imports from nonmember countries (Nguyen 2009)

This fall in imAFTA ij after 1997 Asian Financial Crisis and outbreak of SARS implies

there is a weakening of negative import trade diversion ASEAN prefer to import goods

from members rather than nonmembers but the effects are small relative to the

coefficient of AFTAij As explained before devaluation of ASEAN currency means

foreign goods are more expensive So they prefer to import from members After the

outbreak of SARS the coefficient of imAFTA ij further drops to 0682 Spread of

diseases generated negative impacts to economies in Hong Kong and China which are

major trading partners of AFTA These two countries had the highest probable cases of

SARS This is one of the reasons why AFTA members prefer to import more goods

from members rather than nonmembers

Trade creation and diversion are subjected to changes in external economic environment

AFTA strengthened cooperation with all member countries in 1997 Asian Financial

24

Crisis and urged the members to undertake policy to promote trade which can in turn

speed up economic recovery When compared with outbreak of SARS which caused an

economic downturn in nonmember countries AFTA demonstrates an economic

regionalism that united members in the bloc As shown in the econometric results

AFTA members prefer to trade more among themselves rather than nonmembers

To a certain extent exchange rate volatility did not play a significant role in affecting

trade Most of economies in East Asia adopt a ldquomanaged floatrdquo exchange rate policy

which is beneficial to accomplish economic goals and objectives (Martin 2008) The

2SLS results of Tang (2005) shows that coefficient of exchange rate volatility is positive

which is opposite to our expectation but it is statically insignificant in the pooled sample

Although this coefficient is negative in OLS estimation overall effects of exchange rate

volatility on trade has reduced over time Tang (2005) further suggested two reasons

attributable to this phenomenon after 1997 Firstly the restructuring of financial sectors

like implementation of pegged exchange rate system and transaction of currency option

and contract lead to improvements which can avoid similar crisis in future Secondly

financial system of developed countries are so well organized that stock market and

banking operation are less vulnerable to exchange rate fluctuation

In Table 52 real values of GDP and exports replaced the nominal one in regression

equation 3 Similar results and conclusions could be drawn

25

Table 51

Empirical results of regression equation 3

based on nominal values of exports and GDP

Independent

Variables

1988-1992 1993-1997 1998-2002 2003-2004 1988-2004

Constant 3438

(18597)

2974

(1857)

0966

(5753)

0457

(1653)

2569

(2755)

log Yi 1157

(93901)

1222

(10687)

1364

(98397)

1295

(59454)

1203

(179786)

log Yj 1016

(84303)

1008

(91165)

1215

(90192)

1182

(54609)

1046

(160182)

log Ni -0238

(-18409)

-0219

(-19762)

-0224

(-19141)

-0144

(-7936)

-0187

(-29098)

log Nj -0125

(-9624)

-0071

(-6442)

-0163

(-14185)

-009

(-499)

-0090

(-14138)

log Dij -0983

(-50493)

-1036

(-61597)

-0994

(-59095)

-0961

(-35954)

-0993

(-102673)

AFTA ij 1915

(6511)

2155

(19970)

2857

(3200)

2699

(19042)

2019

(34473)

exAFTA ij 0837

(7308)

1135

(23365)

1374

(26723)

1175

(14575)

0902

(30698)

imAFTA ij 0580

(5232)

0903

(19035)

0775

(15353)

0682

(8532)

0466

(1609)

Adjusted R2 0717 0748 0768 0763 0741

SEE 1572 1442 1442 1448 1506

Number of

observations

7888 9194 9822 3963 30867

Notes

1 T-values are in parentheses

2 denotes the coefficient is significant at 1 level denotes the coefficient is

significant at 5 level denotes the coefficient is significant at 10 level

3 The use of real GDP and export values is reported in the Table 52 which shows there

is little difference in the coefficients in the independent variables

26

Table 52

Empirical results of regression equation 3

based on real values of exports and GDP

Independent

Variables

1988-1992 1993-1997 1998-2002

2003-2004 1988-2004

Constant 3172

(17041)

2845

(1771)

0966

(5757)

0550

(200)

2293

(24637)

log real Yi 116

(94164)

1226

(107095)

1364

(98386)

1297

(59524)

123

(182883)

log real Yj 1020

(84573)

1011

(91405)

1216

(90191)

1184

(54681)

1072

(163403)

log Ni -0239

(-18510)

-0221

(-1994)

-0224

(-19115)

-0145

(-7989)

-02

(-31263)

log Nj -0127

(-977)

-0072

(-6594)

-0163

(-14186)

-0091

(-5049)

-0103

(-16203)

log Dij -0983

(-50598)

-1036

(-61676)

-0994

(-59109)

-0960

(-35959)

-0997

(-104061)

AFTA ij 1995

(679)

2174

(2016)

2859

(32014)

2707

(19101)

2200

(37693)

exAFTA ij 0914

(7984)

1143

(23365)

1374

(26712)

1179

(14630)

1025

(34982)

imAFTA ij 0657

(5936)

0911

(19224)

0778

(15404)

0686

(8584)

0586

(20301)

Adjusted R2 0718 0748 0767 0763 0744

SEE 157 144 1442 1446 1492

Number of

observations

7888 9194 9822 3963 30867

Notes `

1 T-values are in parentheses

2 denotes the coefficient is significant at 1 level denotes the coefficient is

significant at 5 level denotes the coefficient is significant at 10 level

3 For real GDP and export values year 2000 is used as base year

27

6 Implications and Recommendations

As China joins ASEAN Free Trade Agreement in January 2010 this creates changes on

the trade flow From the side of ASEAN this agreement helps ASEAN members to

access a prosperous Chinese market From Table 82 (Appendix) there is an increasing

trend of trade among AFTA and China during the period of 2004-2008 Both sides

consider each other as crucial trading partners As tariff barrier is removed after

formation of CAFTA this can increase intra regional trade among these countries and

reduce AFTA reliance on United States European Union and Japan (Chia 2004) With

countries of different stages of economic development integrated CAFTA can narrow

the income gap between member countries (Roberts 2004)

However empirical studies show mixed results As defined in Linder Hypothesis

countries with similar levels of income per capita will exhibit similar demand produce

similar and differentiated products and trade more with each other According to

empirical study conducted by Roberts (2004) the coefficient testing of the Linder

Hypothesis is insignificant which implies that CAFTA does not have similar demand

pattern and this can be supported by the classification of different stages of economic

development among the members Roberts (2004) noted that China Cambodia Laos

PDR Myanmar and Vietnam are Low Income economies Indonesia Thailand and

Philippines are Low Middle Income economies Singapore and Brunei Darussalam are

28

High Income Economies based on World Bankrsquos classification CAFTA creates an

enlarged market which increases in competition and investment (Chirathivat 2002)

Using SMART model Zhao Malouche and Newfarmer (2008) found out that there is

only a limited increase in intraregional trade and trade diversion when they assume full

liberalization of trade between China and ASEAN is implemented Chinarsquos imports

from ASEAN would increase by 72 especially from Singapore Thailand and

Malaysia On the other hand according to the simulation conducted by the ASEAN

Secretariat (2001) CAFTA would increase ASEANs exports to China and Chinese

export to ASEAN by 48 and 551 respectively (China amp World Economy 2003)

Although previous studies had mixed results CAFTA does provide a platform for China

and ASEAN to establish a legal system for trade investment and service that complies

with the rules of WTO and international standards This allows promotion of freer trade

and attracts investment from the foreign countries (Zhang 2006)

20

and facilitate transportation of goods between both importing and exporting countries

over time distance between countries still remains one of the most important

determinants in trade activities

52 Intraregional trade bias in AFTA

The coefficients of AFTA ij are positive and statistically significant It increases from

1915 in 1988-1992 to 2155 in 1993-1997 This shows there is trade creation effect

after the formation of AFTA This is consistent with the previous study like Tang (2005)

and Thornton and Goglio (2002) The low tariff rate facilitates trade in AFTA

After the 1997 Asian Financial Crisis the poor economic performance did not inhibited

the member countries to export goods to each other as there is a sharp jump in this

coefficient to 2857 New admission of Lao PDR and Myanmar in 1997 stimulated trade

creation effects Average regional CEPT rate for products in the Inclusion List has

dropped from 1276 in 1993 to 505 in 1998 (Jr Yee and Azhari 1998) Elliot and

Ikemoto (2004) pointed out that this regional economic shock in the form of currency

crisis created latent forces institutionalizing interdependence within the bloc

On the contrary after outbreak of SARS in 2003 the coefficient of AFTAij decreases to

2699 To further explain SARS is a highly infectious respiratory disease that had

caused doom in East Asian economies Within AFTA Singapore and Vietnam were hard

21

hit by SARS People tend to avoid social interaction which led to a slump in business

transactions The unemployment rate increased and demand for goods and services fell

Although a new arrangement of CEPT Rules of Origin and Operational Certification

Procedures which could promote trade among AFTA has been implemented on 1

January 2004 intraregional trade had declined In addition rise of trade among

nonmember countries could explain this decline As China has formally entered into

WTO in 2001 exports of ASEAN countries need to compete with Chinese products in

both export and ASEAN domestic market and ASEAN exporters would lose their

comparative advantage when developed countries give tariff concessions to China

(Kwan and Qiu 2003)

53 Export and Import Trade Diversion between member and non member countries

Finally the dummy variables of exAFTA ij and imAFTA ij have signs opposite to our

expectations They are statistically significant at 1 level of significance The positive

sign of exAFTA ij and imAFTA ij indicate that members and nonmembers have traded

with each other to greater extent than the hypothetical trade level throughout 1988-2004

(Endoh 1999) The results indicate negative trade diversion effect in AFTA

The coefficient of exAFTAij has a continuous increase from 0837 in 1988-1992 to

1135 in 1993-1997 The positive sign of this coefficient implies that the member

22

countries prefer to export goods to nonmember rather than members after the formation

of AFTA This implies AFTA members adopted export oriented strategies that promoted

export (Nguyen 2009)

The coefficient of exAFTAij increases to 1374 after 1997 The upward trend in

exAFTAij shows there is strengthening of negative export trade diversion throughout the

period of 1992-2002 The model of Elliot and Ikemoto (2004) also had similar results

and further explained the sharp jump in exAFTAij is caused by the devaluation of

ASEAN currencies after 1997 Asian Financial crisis as shown in Figure 81 (Appendix)

This could increase the competitiveness of ASEAN exports since they were relatively

cheaper when compared with the products of nonmember countries This boosted

ASEAN export trade with nonmembers

After the outbreak of SARS exAFTAij coefficient falls to 1175 in the period 2003-2004

which means there is weakening of negative trade diversion The outbreak of SARS has

caused temporary shock and persistent shock to Hong Kong and Chinese economies

Lee (2004) suggested that SARS led to a loss of GDP Hong Kong which was seriously

affected has experienced a decline in GDP by 263 GDP of Taiwan and Singapore

also were decreased by 049 and 047 respectively This reduction showed there was

a fall in demand for goods and services of ASEAN countries This could also be

explained by the slight appreciation of ASEAN currency after 2002 Value of ASEAN

23

currency increased relative to other foreign countries and ASEAN products were

relatively more expensive Therefore AFTA members prefer to export their goods to

members rather than nonmembers

The dummy variable imAFTAij measures import trade diversion of AFTA Its

coefficient increases from 058 in 1988-1992 to 0903 in 1993-1997 The upward trend

reveals that dynamic network of domestic production and foreign investment projects in

AFTA members caused a rise in its imports from nonmember countries (Nguyen 2009)

This fall in imAFTA ij after 1997 Asian Financial Crisis and outbreak of SARS implies

there is a weakening of negative import trade diversion ASEAN prefer to import goods

from members rather than nonmembers but the effects are small relative to the

coefficient of AFTAij As explained before devaluation of ASEAN currency means

foreign goods are more expensive So they prefer to import from members After the

outbreak of SARS the coefficient of imAFTA ij further drops to 0682 Spread of

diseases generated negative impacts to economies in Hong Kong and China which are

major trading partners of AFTA These two countries had the highest probable cases of

SARS This is one of the reasons why AFTA members prefer to import more goods

from members rather than nonmembers

Trade creation and diversion are subjected to changes in external economic environment

AFTA strengthened cooperation with all member countries in 1997 Asian Financial

24

Crisis and urged the members to undertake policy to promote trade which can in turn

speed up economic recovery When compared with outbreak of SARS which caused an

economic downturn in nonmember countries AFTA demonstrates an economic

regionalism that united members in the bloc As shown in the econometric results

AFTA members prefer to trade more among themselves rather than nonmembers

To a certain extent exchange rate volatility did not play a significant role in affecting

trade Most of economies in East Asia adopt a ldquomanaged floatrdquo exchange rate policy

which is beneficial to accomplish economic goals and objectives (Martin 2008) The

2SLS results of Tang (2005) shows that coefficient of exchange rate volatility is positive

which is opposite to our expectation but it is statically insignificant in the pooled sample

Although this coefficient is negative in OLS estimation overall effects of exchange rate

volatility on trade has reduced over time Tang (2005) further suggested two reasons

attributable to this phenomenon after 1997 Firstly the restructuring of financial sectors

like implementation of pegged exchange rate system and transaction of currency option

and contract lead to improvements which can avoid similar crisis in future Secondly

financial system of developed countries are so well organized that stock market and

banking operation are less vulnerable to exchange rate fluctuation

In Table 52 real values of GDP and exports replaced the nominal one in regression

equation 3 Similar results and conclusions could be drawn

25

Table 51

Empirical results of regression equation 3

based on nominal values of exports and GDP

Independent

Variables

1988-1992 1993-1997 1998-2002 2003-2004 1988-2004

Constant 3438

(18597)

2974

(1857)

0966

(5753)

0457

(1653)

2569

(2755)

log Yi 1157

(93901)

1222

(10687)

1364

(98397)

1295

(59454)

1203

(179786)

log Yj 1016

(84303)

1008

(91165)

1215

(90192)

1182

(54609)

1046

(160182)

log Ni -0238

(-18409)

-0219

(-19762)

-0224

(-19141)

-0144

(-7936)

-0187

(-29098)

log Nj -0125

(-9624)

-0071

(-6442)

-0163

(-14185)

-009

(-499)

-0090

(-14138)

log Dij -0983

(-50493)

-1036

(-61597)

-0994

(-59095)

-0961

(-35954)

-0993

(-102673)

AFTA ij 1915

(6511)

2155

(19970)

2857

(3200)

2699

(19042)

2019

(34473)

exAFTA ij 0837

(7308)

1135

(23365)

1374

(26723)

1175

(14575)

0902

(30698)

imAFTA ij 0580

(5232)

0903

(19035)

0775

(15353)

0682

(8532)

0466

(1609)

Adjusted R2 0717 0748 0768 0763 0741

SEE 1572 1442 1442 1448 1506

Number of

observations

7888 9194 9822 3963 30867

Notes

1 T-values are in parentheses

2 denotes the coefficient is significant at 1 level denotes the coefficient is

significant at 5 level denotes the coefficient is significant at 10 level

3 The use of real GDP and export values is reported in the Table 52 which shows there

is little difference in the coefficients in the independent variables

26

Table 52

Empirical results of regression equation 3

based on real values of exports and GDP

Independent

Variables

1988-1992 1993-1997 1998-2002

2003-2004 1988-2004

Constant 3172

(17041)

2845

(1771)

0966

(5757)

0550

(200)

2293

(24637)

log real Yi 116

(94164)

1226

(107095)

1364

(98386)

1297

(59524)

123

(182883)

log real Yj 1020

(84573)

1011

(91405)

1216

(90191)

1184

(54681)

1072

(163403)

log Ni -0239

(-18510)

-0221

(-1994)

-0224

(-19115)

-0145

(-7989)

-02

(-31263)

log Nj -0127

(-977)

-0072

(-6594)

-0163

(-14186)

-0091

(-5049)

-0103

(-16203)

log Dij -0983

(-50598)

-1036

(-61676)

-0994

(-59109)

-0960

(-35959)

-0997

(-104061)

AFTA ij 1995

(679)

2174

(2016)

2859

(32014)

2707

(19101)

2200

(37693)

exAFTA ij 0914

(7984)

1143

(23365)

1374

(26712)

1179

(14630)

1025

(34982)

imAFTA ij 0657

(5936)

0911

(19224)

0778

(15404)

0686

(8584)

0586

(20301)

Adjusted R2 0718 0748 0767 0763 0744

SEE 157 144 1442 1446 1492

Number of

observations

7888 9194 9822 3963 30867

Notes `

1 T-values are in parentheses

2 denotes the coefficient is significant at 1 level denotes the coefficient is

significant at 5 level denotes the coefficient is significant at 10 level

3 For real GDP and export values year 2000 is used as base year

27

6 Implications and Recommendations

As China joins ASEAN Free Trade Agreement in January 2010 this creates changes on

the trade flow From the side of ASEAN this agreement helps ASEAN members to

access a prosperous Chinese market From Table 82 (Appendix) there is an increasing

trend of trade among AFTA and China during the period of 2004-2008 Both sides

consider each other as crucial trading partners As tariff barrier is removed after

formation of CAFTA this can increase intra regional trade among these countries and

reduce AFTA reliance on United States European Union and Japan (Chia 2004) With

countries of different stages of economic development integrated CAFTA can narrow

the income gap between member countries (Roberts 2004)

However empirical studies show mixed results As defined in Linder Hypothesis

countries with similar levels of income per capita will exhibit similar demand produce

similar and differentiated products and trade more with each other According to

empirical study conducted by Roberts (2004) the coefficient testing of the Linder

Hypothesis is insignificant which implies that CAFTA does not have similar demand

pattern and this can be supported by the classification of different stages of economic

development among the members Roberts (2004) noted that China Cambodia Laos

PDR Myanmar and Vietnam are Low Income economies Indonesia Thailand and

Philippines are Low Middle Income economies Singapore and Brunei Darussalam are

28

High Income Economies based on World Bankrsquos classification CAFTA creates an

enlarged market which increases in competition and investment (Chirathivat 2002)

Using SMART model Zhao Malouche and Newfarmer (2008) found out that there is

only a limited increase in intraregional trade and trade diversion when they assume full

liberalization of trade between China and ASEAN is implemented Chinarsquos imports

from ASEAN would increase by 72 especially from Singapore Thailand and

Malaysia On the other hand according to the simulation conducted by the ASEAN

Secretariat (2001) CAFTA would increase ASEANs exports to China and Chinese

export to ASEAN by 48 and 551 respectively (China amp World Economy 2003)

Although previous studies had mixed results CAFTA does provide a platform for China

and ASEAN to establish a legal system for trade investment and service that complies

with the rules of WTO and international standards This allows promotion of freer trade

and attracts investment from the foreign countries (Zhang 2006)

21

hit by SARS People tend to avoid social interaction which led to a slump in business

transactions The unemployment rate increased and demand for goods and services fell

Although a new arrangement of CEPT Rules of Origin and Operational Certification

Procedures which could promote trade among AFTA has been implemented on 1

January 2004 intraregional trade had declined In addition rise of trade among

nonmember countries could explain this decline As China has formally entered into

WTO in 2001 exports of ASEAN countries need to compete with Chinese products in

both export and ASEAN domestic market and ASEAN exporters would lose their

comparative advantage when developed countries give tariff concessions to China

(Kwan and Qiu 2003)

53 Export and Import Trade Diversion between member and non member countries

Finally the dummy variables of exAFTA ij and imAFTA ij have signs opposite to our

expectations They are statistically significant at 1 level of significance The positive

sign of exAFTA ij and imAFTA ij indicate that members and nonmembers have traded

with each other to greater extent than the hypothetical trade level throughout 1988-2004

(Endoh 1999) The results indicate negative trade diversion effect in AFTA

The coefficient of exAFTAij has a continuous increase from 0837 in 1988-1992 to

1135 in 1993-1997 The positive sign of this coefficient implies that the member

22

countries prefer to export goods to nonmember rather than members after the formation

of AFTA This implies AFTA members adopted export oriented strategies that promoted

export (Nguyen 2009)

The coefficient of exAFTAij increases to 1374 after 1997 The upward trend in

exAFTAij shows there is strengthening of negative export trade diversion throughout the

period of 1992-2002 The model of Elliot and Ikemoto (2004) also had similar results

and further explained the sharp jump in exAFTAij is caused by the devaluation of

ASEAN currencies after 1997 Asian Financial crisis as shown in Figure 81 (Appendix)

This could increase the competitiveness of ASEAN exports since they were relatively

cheaper when compared with the products of nonmember countries This boosted

ASEAN export trade with nonmembers

After the outbreak of SARS exAFTAij coefficient falls to 1175 in the period 2003-2004

which means there is weakening of negative trade diversion The outbreak of SARS has

caused temporary shock and persistent shock to Hong Kong and Chinese economies

Lee (2004) suggested that SARS led to a loss of GDP Hong Kong which was seriously

affected has experienced a decline in GDP by 263 GDP of Taiwan and Singapore

also were decreased by 049 and 047 respectively This reduction showed there was

a fall in demand for goods and services of ASEAN countries This could also be

explained by the slight appreciation of ASEAN currency after 2002 Value of ASEAN

23

currency increased relative to other foreign countries and ASEAN products were

relatively more expensive Therefore AFTA members prefer to export their goods to

members rather than nonmembers

The dummy variable imAFTAij measures import trade diversion of AFTA Its

coefficient increases from 058 in 1988-1992 to 0903 in 1993-1997 The upward trend

reveals that dynamic network of domestic production and foreign investment projects in

AFTA members caused a rise in its imports from nonmember countries (Nguyen 2009)

This fall in imAFTA ij after 1997 Asian Financial Crisis and outbreak of SARS implies

there is a weakening of negative import trade diversion ASEAN prefer to import goods

from members rather than nonmembers but the effects are small relative to the

coefficient of AFTAij As explained before devaluation of ASEAN currency means

foreign goods are more expensive So they prefer to import from members After the

outbreak of SARS the coefficient of imAFTA ij further drops to 0682 Spread of

diseases generated negative impacts to economies in Hong Kong and China which are

major trading partners of AFTA These two countries had the highest probable cases of

SARS This is one of the reasons why AFTA members prefer to import more goods

from members rather than nonmembers

Trade creation and diversion are subjected to changes in external economic environment

AFTA strengthened cooperation with all member countries in 1997 Asian Financial

24

Crisis and urged the members to undertake policy to promote trade which can in turn

speed up economic recovery When compared with outbreak of SARS which caused an

economic downturn in nonmember countries AFTA demonstrates an economic

regionalism that united members in the bloc As shown in the econometric results

AFTA members prefer to trade more among themselves rather than nonmembers

To a certain extent exchange rate volatility did not play a significant role in affecting

trade Most of economies in East Asia adopt a ldquomanaged floatrdquo exchange rate policy

which is beneficial to accomplish economic goals and objectives (Martin 2008) The

2SLS results of Tang (2005) shows that coefficient of exchange rate volatility is positive

which is opposite to our expectation but it is statically insignificant in the pooled sample

Although this coefficient is negative in OLS estimation overall effects of exchange rate

volatility on trade has reduced over time Tang (2005) further suggested two reasons

attributable to this phenomenon after 1997 Firstly the restructuring of financial sectors

like implementation of pegged exchange rate system and transaction of currency option

and contract lead to improvements which can avoid similar crisis in future Secondly

financial system of developed countries are so well organized that stock market and

banking operation are less vulnerable to exchange rate fluctuation

In Table 52 real values of GDP and exports replaced the nominal one in regression

equation 3 Similar results and conclusions could be drawn

25

Table 51

Empirical results of regression equation 3

based on nominal values of exports and GDP

Independent

Variables

1988-1992 1993-1997 1998-2002 2003-2004 1988-2004

Constant 3438

(18597)

2974

(1857)

0966

(5753)

0457

(1653)

2569

(2755)

log Yi 1157

(93901)

1222

(10687)

1364

(98397)

1295

(59454)

1203

(179786)

log Yj 1016

(84303)

1008

(91165)

1215

(90192)

1182

(54609)

1046

(160182)

log Ni -0238

(-18409)

-0219

(-19762)

-0224

(-19141)

-0144

(-7936)

-0187

(-29098)

log Nj -0125

(-9624)

-0071

(-6442)

-0163

(-14185)

-009

(-499)

-0090

(-14138)

log Dij -0983

(-50493)

-1036

(-61597)

-0994

(-59095)

-0961

(-35954)

-0993

(-102673)

AFTA ij 1915

(6511)

2155

(19970)

2857

(3200)

2699

(19042)

2019

(34473)

exAFTA ij 0837

(7308)

1135

(23365)

1374

(26723)

1175

(14575)

0902

(30698)

imAFTA ij 0580

(5232)

0903

(19035)

0775

(15353)

0682

(8532)

0466

(1609)

Adjusted R2 0717 0748 0768 0763 0741

SEE 1572 1442 1442 1448 1506

Number of

observations

7888 9194 9822 3963 30867

Notes

1 T-values are in parentheses

2 denotes the coefficient is significant at 1 level denotes the coefficient is

significant at 5 level denotes the coefficient is significant at 10 level

3 The use of real GDP and export values is reported in the Table 52 which shows there

is little difference in the coefficients in the independent variables

26

Table 52

Empirical results of regression equation 3

based on real values of exports and GDP

Independent

Variables

1988-1992 1993-1997 1998-2002

2003-2004 1988-2004

Constant 3172

(17041)

2845

(1771)

0966

(5757)

0550

(200)

2293

(24637)

log real Yi 116

(94164)

1226

(107095)

1364

(98386)

1297

(59524)

123

(182883)

log real Yj 1020

(84573)

1011

(91405)

1216

(90191)

1184

(54681)

1072

(163403)

log Ni -0239

(-18510)

-0221

(-1994)

-0224

(-19115)

-0145

(-7989)

-02

(-31263)

log Nj -0127

(-977)

-0072

(-6594)

-0163

(-14186)

-0091

(-5049)

-0103

(-16203)

log Dij -0983

(-50598)

-1036

(-61676)

-0994

(-59109)

-0960

(-35959)

-0997

(-104061)

AFTA ij 1995

(679)

2174

(2016)

2859

(32014)

2707

(19101)

2200

(37693)

exAFTA ij 0914

(7984)

1143

(23365)

1374

(26712)

1179

(14630)

1025

(34982)

imAFTA ij 0657

(5936)

0911

(19224)

0778

(15404)

0686

(8584)

0586

(20301)

Adjusted R2 0718 0748 0767 0763 0744

SEE 157 144 1442 1446 1492

Number of

observations

7888 9194 9822 3963 30867

Notes `

1 T-values are in parentheses

2 denotes the coefficient is significant at 1 level denotes the coefficient is

significant at 5 level denotes the coefficient is significant at 10 level

3 For real GDP and export values year 2000 is used as base year

27

6 Implications and Recommendations

As China joins ASEAN Free Trade Agreement in January 2010 this creates changes on

the trade flow From the side of ASEAN this agreement helps ASEAN members to

access a prosperous Chinese market From Table 82 (Appendix) there is an increasing

trend of trade among AFTA and China during the period of 2004-2008 Both sides

consider each other as crucial trading partners As tariff barrier is removed after

formation of CAFTA this can increase intra regional trade among these countries and

reduce AFTA reliance on United States European Union and Japan (Chia 2004) With

countries of different stages of economic development integrated CAFTA can narrow

the income gap between member countries (Roberts 2004)

However empirical studies show mixed results As defined in Linder Hypothesis

countries with similar levels of income per capita will exhibit similar demand produce

similar and differentiated products and trade more with each other According to

empirical study conducted by Roberts (2004) the coefficient testing of the Linder

Hypothesis is insignificant which implies that CAFTA does not have similar demand

pattern and this can be supported by the classification of different stages of economic

development among the members Roberts (2004) noted that China Cambodia Laos

PDR Myanmar and Vietnam are Low Income economies Indonesia Thailand and

Philippines are Low Middle Income economies Singapore and Brunei Darussalam are

28

High Income Economies based on World Bankrsquos classification CAFTA creates an

enlarged market which increases in competition and investment (Chirathivat 2002)

Using SMART model Zhao Malouche and Newfarmer (2008) found out that there is

only a limited increase in intraregional trade and trade diversion when they assume full

liberalization of trade between China and ASEAN is implemented Chinarsquos imports

from ASEAN would increase by 72 especially from Singapore Thailand and

Malaysia On the other hand according to the simulation conducted by the ASEAN

Secretariat (2001) CAFTA would increase ASEANs exports to China and Chinese

export to ASEAN by 48 and 551 respectively (China amp World Economy 2003)

Although previous studies had mixed results CAFTA does provide a platform for China

and ASEAN to establish a legal system for trade investment and service that complies

with the rules of WTO and international standards This allows promotion of freer trade

and attracts investment from the foreign countries (Zhang 2006)

22

countries prefer to export goods to nonmember rather than members after the formation

of AFTA This implies AFTA members adopted export oriented strategies that promoted

export (Nguyen 2009)

The coefficient of exAFTAij increases to 1374 after 1997 The upward trend in

exAFTAij shows there is strengthening of negative export trade diversion throughout the

period of 1992-2002 The model of Elliot and Ikemoto (2004) also had similar results

and further explained the sharp jump in exAFTAij is caused by the devaluation of

ASEAN currencies after 1997 Asian Financial crisis as shown in Figure 81 (Appendix)

This could increase the competitiveness of ASEAN exports since they were relatively

cheaper when compared with the products of nonmember countries This boosted

ASEAN export trade with nonmembers

After the outbreak of SARS exAFTAij coefficient falls to 1175 in the period 2003-2004

which means there is weakening of negative trade diversion The outbreak of SARS has

caused temporary shock and persistent shock to Hong Kong and Chinese economies

Lee (2004) suggested that SARS led to a loss of GDP Hong Kong which was seriously

affected has experienced a decline in GDP by 263 GDP of Taiwan and Singapore

also were decreased by 049 and 047 respectively This reduction showed there was

a fall in demand for goods and services of ASEAN countries This could also be

explained by the slight appreciation of ASEAN currency after 2002 Value of ASEAN

23

currency increased relative to other foreign countries and ASEAN products were

relatively more expensive Therefore AFTA members prefer to export their goods to

members rather than nonmembers

The dummy variable imAFTAij measures import trade diversion of AFTA Its

coefficient increases from 058 in 1988-1992 to 0903 in 1993-1997 The upward trend

reveals that dynamic network of domestic production and foreign investment projects in

AFTA members caused a rise in its imports from nonmember countries (Nguyen 2009)

This fall in imAFTA ij after 1997 Asian Financial Crisis and outbreak of SARS implies

there is a weakening of negative import trade diversion ASEAN prefer to import goods

from members rather than nonmembers but the effects are small relative to the

coefficient of AFTAij As explained before devaluation of ASEAN currency means

foreign goods are more expensive So they prefer to import from members After the

outbreak of SARS the coefficient of imAFTA ij further drops to 0682 Spread of

diseases generated negative impacts to economies in Hong Kong and China which are

major trading partners of AFTA These two countries had the highest probable cases of

SARS This is one of the reasons why AFTA members prefer to import more goods

from members rather than nonmembers

Trade creation and diversion are subjected to changes in external economic environment

AFTA strengthened cooperation with all member countries in 1997 Asian Financial

24

Crisis and urged the members to undertake policy to promote trade which can in turn

speed up economic recovery When compared with outbreak of SARS which caused an

economic downturn in nonmember countries AFTA demonstrates an economic

regionalism that united members in the bloc As shown in the econometric results

AFTA members prefer to trade more among themselves rather than nonmembers

To a certain extent exchange rate volatility did not play a significant role in affecting

trade Most of economies in East Asia adopt a ldquomanaged floatrdquo exchange rate policy

which is beneficial to accomplish economic goals and objectives (Martin 2008) The

2SLS results of Tang (2005) shows that coefficient of exchange rate volatility is positive

which is opposite to our expectation but it is statically insignificant in the pooled sample

Although this coefficient is negative in OLS estimation overall effects of exchange rate

volatility on trade has reduced over time Tang (2005) further suggested two reasons

attributable to this phenomenon after 1997 Firstly the restructuring of financial sectors

like implementation of pegged exchange rate system and transaction of currency option

and contract lead to improvements which can avoid similar crisis in future Secondly

financial system of developed countries are so well organized that stock market and

banking operation are less vulnerable to exchange rate fluctuation

In Table 52 real values of GDP and exports replaced the nominal one in regression

equation 3 Similar results and conclusions could be drawn

25

Table 51

Empirical results of regression equation 3

based on nominal values of exports and GDP

Independent

Variables

1988-1992 1993-1997 1998-2002 2003-2004 1988-2004

Constant 3438

(18597)

2974

(1857)

0966

(5753)

0457

(1653)

2569

(2755)

log Yi 1157

(93901)

1222

(10687)

1364

(98397)

1295

(59454)

1203

(179786)

log Yj 1016

(84303)

1008

(91165)

1215

(90192)

1182

(54609)

1046

(160182)

log Ni -0238

(-18409)

-0219

(-19762)

-0224

(-19141)

-0144

(-7936)

-0187

(-29098)

log Nj -0125

(-9624)

-0071

(-6442)

-0163

(-14185)

-009

(-499)

-0090

(-14138)

log Dij -0983

(-50493)

-1036

(-61597)

-0994

(-59095)

-0961

(-35954)

-0993

(-102673)

AFTA ij 1915

(6511)

2155

(19970)

2857

(3200)

2699

(19042)

2019

(34473)

exAFTA ij 0837

(7308)

1135

(23365)

1374

(26723)

1175

(14575)

0902

(30698)

imAFTA ij 0580

(5232)

0903

(19035)

0775

(15353)

0682

(8532)

0466

(1609)

Adjusted R2 0717 0748 0768 0763 0741

SEE 1572 1442 1442 1448 1506

Number of

observations

7888 9194 9822 3963 30867

Notes

1 T-values are in parentheses

2 denotes the coefficient is significant at 1 level denotes the coefficient is

significant at 5 level denotes the coefficient is significant at 10 level

3 The use of real GDP and export values is reported in the Table 52 which shows there

is little difference in the coefficients in the independent variables

26

Table 52

Empirical results of regression equation 3

based on real values of exports and GDP

Independent

Variables

1988-1992 1993-1997 1998-2002

2003-2004 1988-2004

Constant 3172

(17041)

2845

(1771)

0966

(5757)

0550

(200)

2293

(24637)

log real Yi 116

(94164)

1226

(107095)

1364

(98386)

1297

(59524)

123

(182883)

log real Yj 1020

(84573)

1011

(91405)

1216

(90191)

1184

(54681)

1072

(163403)

log Ni -0239

(-18510)

-0221

(-1994)

-0224

(-19115)

-0145

(-7989)

-02

(-31263)

log Nj -0127

(-977)

-0072

(-6594)

-0163

(-14186)

-0091

(-5049)

-0103

(-16203)

log Dij -0983

(-50598)

-1036

(-61676)

-0994

(-59109)

-0960

(-35959)

-0997

(-104061)

AFTA ij 1995

(679)

2174

(2016)

2859

(32014)

2707

(19101)

2200

(37693)

exAFTA ij 0914

(7984)

1143

(23365)

1374

(26712)

1179

(14630)

1025

(34982)

imAFTA ij 0657

(5936)

0911

(19224)

0778

(15404)

0686

(8584)

0586

(20301)

Adjusted R2 0718 0748 0767 0763 0744

SEE 157 144 1442 1446 1492

Number of

observations

7888 9194 9822 3963 30867

Notes `

1 T-values are in parentheses

2 denotes the coefficient is significant at 1 level denotes the coefficient is

significant at 5 level denotes the coefficient is significant at 10 level

3 For real GDP and export values year 2000 is used as base year

27

6 Implications and Recommendations

As China joins ASEAN Free Trade Agreement in January 2010 this creates changes on

the trade flow From the side of ASEAN this agreement helps ASEAN members to

access a prosperous Chinese market From Table 82 (Appendix) there is an increasing

trend of trade among AFTA and China during the period of 2004-2008 Both sides

consider each other as crucial trading partners As tariff barrier is removed after

formation of CAFTA this can increase intra regional trade among these countries and

reduce AFTA reliance on United States European Union and Japan (Chia 2004) With

countries of different stages of economic development integrated CAFTA can narrow

the income gap between member countries (Roberts 2004)

However empirical studies show mixed results As defined in Linder Hypothesis

countries with similar levels of income per capita will exhibit similar demand produce

similar and differentiated products and trade more with each other According to

empirical study conducted by Roberts (2004) the coefficient testing of the Linder

Hypothesis is insignificant which implies that CAFTA does not have similar demand

pattern and this can be supported by the classification of different stages of economic

development among the members Roberts (2004) noted that China Cambodia Laos

PDR Myanmar and Vietnam are Low Income economies Indonesia Thailand and

Philippines are Low Middle Income economies Singapore and Brunei Darussalam are

28

High Income Economies based on World Bankrsquos classification CAFTA creates an

enlarged market which increases in competition and investment (Chirathivat 2002)

Using SMART model Zhao Malouche and Newfarmer (2008) found out that there is

only a limited increase in intraregional trade and trade diversion when they assume full

liberalization of trade between China and ASEAN is implemented Chinarsquos imports

from ASEAN would increase by 72 especially from Singapore Thailand and

Malaysia On the other hand according to the simulation conducted by the ASEAN

Secretariat (2001) CAFTA would increase ASEANs exports to China and Chinese

export to ASEAN by 48 and 551 respectively (China amp World Economy 2003)

Although previous studies had mixed results CAFTA does provide a platform for China

and ASEAN to establish a legal system for trade investment and service that complies

with the rules of WTO and international standards This allows promotion of freer trade

and attracts investment from the foreign countries (Zhang 2006)

23

currency increased relative to other foreign countries and ASEAN products were

relatively more expensive Therefore AFTA members prefer to export their goods to

members rather than nonmembers

The dummy variable imAFTAij measures import trade diversion of AFTA Its

coefficient increases from 058 in 1988-1992 to 0903 in 1993-1997 The upward trend

reveals that dynamic network of domestic production and foreign investment projects in

AFTA members caused a rise in its imports from nonmember countries (Nguyen 2009)

This fall in imAFTA ij after 1997 Asian Financial Crisis and outbreak of SARS implies

there is a weakening of negative import trade diversion ASEAN prefer to import goods

from members rather than nonmembers but the effects are small relative to the

coefficient of AFTAij As explained before devaluation of ASEAN currency means

foreign goods are more expensive So they prefer to import from members After the

outbreak of SARS the coefficient of imAFTA ij further drops to 0682 Spread of

diseases generated negative impacts to economies in Hong Kong and China which are

major trading partners of AFTA These two countries had the highest probable cases of

SARS This is one of the reasons why AFTA members prefer to import more goods

from members rather than nonmembers

Trade creation and diversion are subjected to changes in external economic environment

AFTA strengthened cooperation with all member countries in 1997 Asian Financial

24

Crisis and urged the members to undertake policy to promote trade which can in turn

speed up economic recovery When compared with outbreak of SARS which caused an

economic downturn in nonmember countries AFTA demonstrates an economic

regionalism that united members in the bloc As shown in the econometric results

AFTA members prefer to trade more among themselves rather than nonmembers

To a certain extent exchange rate volatility did not play a significant role in affecting

trade Most of economies in East Asia adopt a ldquomanaged floatrdquo exchange rate policy

which is beneficial to accomplish economic goals and objectives (Martin 2008) The

2SLS results of Tang (2005) shows that coefficient of exchange rate volatility is positive

which is opposite to our expectation but it is statically insignificant in the pooled sample

Although this coefficient is negative in OLS estimation overall effects of exchange rate

volatility on trade has reduced over time Tang (2005) further suggested two reasons

attributable to this phenomenon after 1997 Firstly the restructuring of financial sectors

like implementation of pegged exchange rate system and transaction of currency option

and contract lead to improvements which can avoid similar crisis in future Secondly

financial system of developed countries are so well organized that stock market and

banking operation are less vulnerable to exchange rate fluctuation

In Table 52 real values of GDP and exports replaced the nominal one in regression

equation 3 Similar results and conclusions could be drawn

25

Table 51

Empirical results of regression equation 3

based on nominal values of exports and GDP

Independent

Variables

1988-1992 1993-1997 1998-2002 2003-2004 1988-2004

Constant 3438

(18597)

2974

(1857)

0966

(5753)

0457

(1653)

2569

(2755)

log Yi 1157

(93901)

1222

(10687)

1364

(98397)

1295

(59454)

1203

(179786)

log Yj 1016

(84303)

1008

(91165)

1215

(90192)

1182

(54609)

1046

(160182)

log Ni -0238

(-18409)

-0219

(-19762)

-0224

(-19141)

-0144

(-7936)

-0187

(-29098)

log Nj -0125

(-9624)

-0071

(-6442)

-0163

(-14185)

-009

(-499)

-0090

(-14138)

log Dij -0983

(-50493)

-1036

(-61597)

-0994

(-59095)

-0961

(-35954)

-0993

(-102673)

AFTA ij 1915

(6511)

2155

(19970)

2857

(3200)

2699

(19042)

2019

(34473)

exAFTA ij 0837

(7308)

1135

(23365)

1374

(26723)

1175

(14575)

0902

(30698)

imAFTA ij 0580

(5232)

0903

(19035)

0775

(15353)

0682

(8532)

0466

(1609)

Adjusted R2 0717 0748 0768 0763 0741

SEE 1572 1442 1442 1448 1506

Number of

observations

7888 9194 9822 3963 30867

Notes

1 T-values are in parentheses

2 denotes the coefficient is significant at 1 level denotes the coefficient is

significant at 5 level denotes the coefficient is significant at 10 level

3 The use of real GDP and export values is reported in the Table 52 which shows there

is little difference in the coefficients in the independent variables

26

Table 52

Empirical results of regression equation 3

based on real values of exports and GDP

Independent

Variables

1988-1992 1993-1997 1998-2002

2003-2004 1988-2004

Constant 3172

(17041)

2845

(1771)

0966

(5757)

0550

(200)

2293

(24637)

log real Yi 116

(94164)

1226

(107095)

1364

(98386)

1297

(59524)

123

(182883)

log real Yj 1020

(84573)

1011

(91405)

1216

(90191)

1184

(54681)

1072

(163403)

log Ni -0239

(-18510)

-0221

(-1994)

-0224

(-19115)

-0145

(-7989)

-02

(-31263)

log Nj -0127

(-977)

-0072

(-6594)

-0163

(-14186)

-0091

(-5049)

-0103

(-16203)

log Dij -0983

(-50598)

-1036

(-61676)

-0994

(-59109)

-0960

(-35959)

-0997

(-104061)

AFTA ij 1995

(679)

2174

(2016)

2859

(32014)

2707

(19101)

2200

(37693)

exAFTA ij 0914

(7984)

1143

(23365)

1374

(26712)

1179

(14630)

1025

(34982)

imAFTA ij 0657

(5936)

0911

(19224)

0778

(15404)

0686

(8584)

0586

(20301)

Adjusted R2 0718 0748 0767 0763 0744

SEE 157 144 1442 1446 1492

Number of

observations

7888 9194 9822 3963 30867

Notes `

1 T-values are in parentheses

2 denotes the coefficient is significant at 1 level denotes the coefficient is

significant at 5 level denotes the coefficient is significant at 10 level

3 For real GDP and export values year 2000 is used as base year

27

6 Implications and Recommendations

As China joins ASEAN Free Trade Agreement in January 2010 this creates changes on

the trade flow From the side of ASEAN this agreement helps ASEAN members to

access a prosperous Chinese market From Table 82 (Appendix) there is an increasing

trend of trade among AFTA and China during the period of 2004-2008 Both sides

consider each other as crucial trading partners As tariff barrier is removed after

formation of CAFTA this can increase intra regional trade among these countries and

reduce AFTA reliance on United States European Union and Japan (Chia 2004) With

countries of different stages of economic development integrated CAFTA can narrow

the income gap between member countries (Roberts 2004)

However empirical studies show mixed results As defined in Linder Hypothesis

countries with similar levels of income per capita will exhibit similar demand produce

similar and differentiated products and trade more with each other According to

empirical study conducted by Roberts (2004) the coefficient testing of the Linder

Hypothesis is insignificant which implies that CAFTA does not have similar demand

pattern and this can be supported by the classification of different stages of economic

development among the members Roberts (2004) noted that China Cambodia Laos

PDR Myanmar and Vietnam are Low Income economies Indonesia Thailand and

Philippines are Low Middle Income economies Singapore and Brunei Darussalam are

28

High Income Economies based on World Bankrsquos classification CAFTA creates an

enlarged market which increases in competition and investment (Chirathivat 2002)

Using SMART model Zhao Malouche and Newfarmer (2008) found out that there is

only a limited increase in intraregional trade and trade diversion when they assume full

liberalization of trade between China and ASEAN is implemented Chinarsquos imports

from ASEAN would increase by 72 especially from Singapore Thailand and

Malaysia On the other hand according to the simulation conducted by the ASEAN

Secretariat (2001) CAFTA would increase ASEANs exports to China and Chinese

export to ASEAN by 48 and 551 respectively (China amp World Economy 2003)

Although previous studies had mixed results CAFTA does provide a platform for China

and ASEAN to establish a legal system for trade investment and service that complies

with the rules of WTO and international standards This allows promotion of freer trade

and attracts investment from the foreign countries (Zhang 2006)

24

Crisis and urged the members to undertake policy to promote trade which can in turn

speed up economic recovery When compared with outbreak of SARS which caused an

economic downturn in nonmember countries AFTA demonstrates an economic

regionalism that united members in the bloc As shown in the econometric results

AFTA members prefer to trade more among themselves rather than nonmembers

To a certain extent exchange rate volatility did not play a significant role in affecting

trade Most of economies in East Asia adopt a ldquomanaged floatrdquo exchange rate policy

which is beneficial to accomplish economic goals and objectives (Martin 2008) The

2SLS results of Tang (2005) shows that coefficient of exchange rate volatility is positive

which is opposite to our expectation but it is statically insignificant in the pooled sample

Although this coefficient is negative in OLS estimation overall effects of exchange rate

volatility on trade has reduced over time Tang (2005) further suggested two reasons

attributable to this phenomenon after 1997 Firstly the restructuring of financial sectors

like implementation of pegged exchange rate system and transaction of currency option

and contract lead to improvements which can avoid similar crisis in future Secondly

financial system of developed countries are so well organized that stock market and

banking operation are less vulnerable to exchange rate fluctuation

In Table 52 real values of GDP and exports replaced the nominal one in regression

equation 3 Similar results and conclusions could be drawn

25

Table 51

Empirical results of regression equation 3

based on nominal values of exports and GDP

Independent

Variables

1988-1992 1993-1997 1998-2002 2003-2004 1988-2004

Constant 3438

(18597)

2974

(1857)

0966

(5753)

0457

(1653)

2569

(2755)

log Yi 1157

(93901)

1222

(10687)

1364

(98397)

1295

(59454)

1203

(179786)

log Yj 1016

(84303)

1008

(91165)

1215

(90192)

1182

(54609)

1046

(160182)

log Ni -0238

(-18409)

-0219

(-19762)

-0224

(-19141)

-0144

(-7936)

-0187

(-29098)

log Nj -0125

(-9624)

-0071

(-6442)

-0163

(-14185)

-009

(-499)

-0090

(-14138)

log Dij -0983

(-50493)

-1036

(-61597)

-0994

(-59095)

-0961

(-35954)

-0993

(-102673)

AFTA ij 1915

(6511)

2155

(19970)

2857

(3200)

2699

(19042)

2019

(34473)

exAFTA ij 0837

(7308)

1135

(23365)

1374

(26723)

1175

(14575)

0902

(30698)

imAFTA ij 0580

(5232)

0903

(19035)

0775

(15353)

0682

(8532)

0466

(1609)

Adjusted R2 0717 0748 0768 0763 0741

SEE 1572 1442 1442 1448 1506

Number of

observations

7888 9194 9822 3963 30867

Notes

1 T-values are in parentheses

2 denotes the coefficient is significant at 1 level denotes the coefficient is

significant at 5 level denotes the coefficient is significant at 10 level

3 The use of real GDP and export values is reported in the Table 52 which shows there

is little difference in the coefficients in the independent variables

26

Table 52

Empirical results of regression equation 3

based on real values of exports and GDP

Independent

Variables

1988-1992 1993-1997 1998-2002

2003-2004 1988-2004

Constant 3172

(17041)

2845

(1771)

0966

(5757)

0550

(200)

2293

(24637)

log real Yi 116

(94164)

1226

(107095)

1364

(98386)

1297

(59524)

123

(182883)

log real Yj 1020

(84573)

1011

(91405)

1216

(90191)

1184

(54681)

1072

(163403)

log Ni -0239

(-18510)

-0221

(-1994)

-0224

(-19115)

-0145

(-7989)

-02

(-31263)

log Nj -0127

(-977)

-0072

(-6594)

-0163

(-14186)

-0091

(-5049)

-0103

(-16203)

log Dij -0983

(-50598)

-1036

(-61676)

-0994

(-59109)

-0960

(-35959)

-0997

(-104061)

AFTA ij 1995

(679)

2174

(2016)

2859

(32014)

2707

(19101)

2200

(37693)

exAFTA ij 0914

(7984)

1143

(23365)

1374

(26712)

1179

(14630)

1025

(34982)

imAFTA ij 0657

(5936)

0911

(19224)

0778

(15404)

0686

(8584)

0586

(20301)

Adjusted R2 0718 0748 0767 0763 0744

SEE 157 144 1442 1446 1492

Number of

observations

7888 9194 9822 3963 30867

Notes `

1 T-values are in parentheses

2 denotes the coefficient is significant at 1 level denotes the coefficient is

significant at 5 level denotes the coefficient is significant at 10 level

3 For real GDP and export values year 2000 is used as base year

27

6 Implications and Recommendations

As China joins ASEAN Free Trade Agreement in January 2010 this creates changes on

the trade flow From the side of ASEAN this agreement helps ASEAN members to

access a prosperous Chinese market From Table 82 (Appendix) there is an increasing

trend of trade among AFTA and China during the period of 2004-2008 Both sides

consider each other as crucial trading partners As tariff barrier is removed after

formation of CAFTA this can increase intra regional trade among these countries and

reduce AFTA reliance on United States European Union and Japan (Chia 2004) With

countries of different stages of economic development integrated CAFTA can narrow

the income gap between member countries (Roberts 2004)

However empirical studies show mixed results As defined in Linder Hypothesis

countries with similar levels of income per capita will exhibit similar demand produce

similar and differentiated products and trade more with each other According to

empirical study conducted by Roberts (2004) the coefficient testing of the Linder

Hypothesis is insignificant which implies that CAFTA does not have similar demand

pattern and this can be supported by the classification of different stages of economic

development among the members Roberts (2004) noted that China Cambodia Laos

PDR Myanmar and Vietnam are Low Income economies Indonesia Thailand and

Philippines are Low Middle Income economies Singapore and Brunei Darussalam are

28

High Income Economies based on World Bankrsquos classification CAFTA creates an

enlarged market which increases in competition and investment (Chirathivat 2002)

Using SMART model Zhao Malouche and Newfarmer (2008) found out that there is

only a limited increase in intraregional trade and trade diversion when they assume full

liberalization of trade between China and ASEAN is implemented Chinarsquos imports

from ASEAN would increase by 72 especially from Singapore Thailand and

Malaysia On the other hand according to the simulation conducted by the ASEAN

Secretariat (2001) CAFTA would increase ASEANs exports to China and Chinese

export to ASEAN by 48 and 551 respectively (China amp World Economy 2003)

Although previous studies had mixed results CAFTA does provide a platform for China

and ASEAN to establish a legal system for trade investment and service that complies

with the rules of WTO and international standards This allows promotion of freer trade

and attracts investment from the foreign countries (Zhang 2006)

25

Table 51

Empirical results of regression equation 3

based on nominal values of exports and GDP

Independent

Variables

1988-1992 1993-1997 1998-2002 2003-2004 1988-2004

Constant 3438

(18597)

2974

(1857)

0966

(5753)

0457

(1653)

2569

(2755)

log Yi 1157

(93901)

1222

(10687)

1364

(98397)

1295

(59454)

1203

(179786)

log Yj 1016

(84303)

1008

(91165)

1215

(90192)

1182

(54609)

1046

(160182)

log Ni -0238

(-18409)

-0219

(-19762)

-0224

(-19141)

-0144

(-7936)

-0187

(-29098)

log Nj -0125

(-9624)

-0071

(-6442)

-0163

(-14185)

-009

(-499)

-0090

(-14138)

log Dij -0983

(-50493)

-1036

(-61597)

-0994

(-59095)

-0961

(-35954)

-0993

(-102673)

AFTA ij 1915

(6511)

2155

(19970)

2857

(3200)

2699

(19042)

2019

(34473)

exAFTA ij 0837

(7308)

1135

(23365)

1374

(26723)

1175

(14575)

0902

(30698)

imAFTA ij 0580

(5232)

0903

(19035)

0775

(15353)

0682

(8532)

0466

(1609)

Adjusted R2 0717 0748 0768 0763 0741

SEE 1572 1442 1442 1448 1506

Number of

observations

7888 9194 9822 3963 30867

Notes

1 T-values are in parentheses

2 denotes the coefficient is significant at 1 level denotes the coefficient is

significant at 5 level denotes the coefficient is significant at 10 level

3 The use of real GDP and export values is reported in the Table 52 which shows there

is little difference in the coefficients in the independent variables

26

Table 52

Empirical results of regression equation 3

based on real values of exports and GDP

Independent

Variables

1988-1992 1993-1997 1998-2002

2003-2004 1988-2004

Constant 3172

(17041)

2845

(1771)

0966

(5757)

0550

(200)

2293

(24637)

log real Yi 116

(94164)

1226

(107095)

1364

(98386)

1297

(59524)

123

(182883)

log real Yj 1020

(84573)

1011

(91405)

1216

(90191)

1184

(54681)

1072

(163403)

log Ni -0239

(-18510)

-0221

(-1994)

-0224

(-19115)

-0145

(-7989)

-02

(-31263)

log Nj -0127

(-977)

-0072

(-6594)

-0163

(-14186)

-0091

(-5049)

-0103

(-16203)

log Dij -0983

(-50598)

-1036

(-61676)

-0994

(-59109)

-0960

(-35959)

-0997

(-104061)

AFTA ij 1995

(679)

2174

(2016)

2859

(32014)

2707

(19101)

2200

(37693)

exAFTA ij 0914

(7984)

1143

(23365)

1374

(26712)

1179

(14630)

1025

(34982)

imAFTA ij 0657

(5936)

0911

(19224)

0778

(15404)

0686

(8584)

0586

(20301)

Adjusted R2 0718 0748 0767 0763 0744

SEE 157 144 1442 1446 1492

Number of

observations

7888 9194 9822 3963 30867

Notes `

1 T-values are in parentheses

2 denotes the coefficient is significant at 1 level denotes the coefficient is

significant at 5 level denotes the coefficient is significant at 10 level

3 For real GDP and export values year 2000 is used as base year

27

6 Implications and Recommendations

As China joins ASEAN Free Trade Agreement in January 2010 this creates changes on

the trade flow From the side of ASEAN this agreement helps ASEAN members to

access a prosperous Chinese market From Table 82 (Appendix) there is an increasing

trend of trade among AFTA and China during the period of 2004-2008 Both sides

consider each other as crucial trading partners As tariff barrier is removed after

formation of CAFTA this can increase intra regional trade among these countries and

reduce AFTA reliance on United States European Union and Japan (Chia 2004) With

countries of different stages of economic development integrated CAFTA can narrow

the income gap between member countries (Roberts 2004)

However empirical studies show mixed results As defined in Linder Hypothesis

countries with similar levels of income per capita will exhibit similar demand produce

similar and differentiated products and trade more with each other According to

empirical study conducted by Roberts (2004) the coefficient testing of the Linder

Hypothesis is insignificant which implies that CAFTA does not have similar demand

pattern and this can be supported by the classification of different stages of economic

development among the members Roberts (2004) noted that China Cambodia Laos

PDR Myanmar and Vietnam are Low Income economies Indonesia Thailand and

Philippines are Low Middle Income economies Singapore and Brunei Darussalam are

28

High Income Economies based on World Bankrsquos classification CAFTA creates an

enlarged market which increases in competition and investment (Chirathivat 2002)

Using SMART model Zhao Malouche and Newfarmer (2008) found out that there is

only a limited increase in intraregional trade and trade diversion when they assume full

liberalization of trade between China and ASEAN is implemented Chinarsquos imports

from ASEAN would increase by 72 especially from Singapore Thailand and

Malaysia On the other hand according to the simulation conducted by the ASEAN

Secretariat (2001) CAFTA would increase ASEANs exports to China and Chinese

export to ASEAN by 48 and 551 respectively (China amp World Economy 2003)

Although previous studies had mixed results CAFTA does provide a platform for China

and ASEAN to establish a legal system for trade investment and service that complies

with the rules of WTO and international standards This allows promotion of freer trade

and attracts investment from the foreign countries (Zhang 2006)

26

Table 52

Empirical results of regression equation 3

based on real values of exports and GDP

Independent

Variables

1988-1992 1993-1997 1998-2002

2003-2004 1988-2004

Constant 3172

(17041)

2845

(1771)

0966

(5757)

0550

(200)

2293

(24637)

log real Yi 116

(94164)

1226

(107095)

1364

(98386)

1297

(59524)

123

(182883)

log real Yj 1020

(84573)

1011

(91405)

1216

(90191)

1184

(54681)

1072

(163403)

log Ni -0239

(-18510)

-0221

(-1994)

-0224

(-19115)

-0145

(-7989)

-02

(-31263)

log Nj -0127

(-977)

-0072

(-6594)

-0163

(-14186)

-0091

(-5049)

-0103

(-16203)

log Dij -0983

(-50598)

-1036

(-61676)

-0994

(-59109)

-0960

(-35959)

-0997

(-104061)

AFTA ij 1995

(679)

2174

(2016)

2859

(32014)

2707

(19101)

2200

(37693)

exAFTA ij 0914

(7984)

1143

(23365)

1374

(26712)

1179

(14630)

1025

(34982)

imAFTA ij 0657

(5936)

0911

(19224)

0778

(15404)

0686

(8584)

0586

(20301)

Adjusted R2 0718 0748 0767 0763 0744

SEE 157 144 1442 1446 1492

Number of

observations

7888 9194 9822 3963 30867

Notes `

1 T-values are in parentheses

2 denotes the coefficient is significant at 1 level denotes the coefficient is

significant at 5 level denotes the coefficient is significant at 10 level

3 For real GDP and export values year 2000 is used as base year

27

6 Implications and Recommendations

As China joins ASEAN Free Trade Agreement in January 2010 this creates changes on

the trade flow From the side of ASEAN this agreement helps ASEAN members to

access a prosperous Chinese market From Table 82 (Appendix) there is an increasing

trend of trade among AFTA and China during the period of 2004-2008 Both sides

consider each other as crucial trading partners As tariff barrier is removed after

formation of CAFTA this can increase intra regional trade among these countries and

reduce AFTA reliance on United States European Union and Japan (Chia 2004) With

countries of different stages of economic development integrated CAFTA can narrow

the income gap between member countries (Roberts 2004)

However empirical studies show mixed results As defined in Linder Hypothesis

countries with similar levels of income per capita will exhibit similar demand produce

similar and differentiated products and trade more with each other According to

empirical study conducted by Roberts (2004) the coefficient testing of the Linder

Hypothesis is insignificant which implies that CAFTA does not have similar demand

pattern and this can be supported by the classification of different stages of economic

development among the members Roberts (2004) noted that China Cambodia Laos

PDR Myanmar and Vietnam are Low Income economies Indonesia Thailand and

Philippines are Low Middle Income economies Singapore and Brunei Darussalam are

28

High Income Economies based on World Bankrsquos classification CAFTA creates an

enlarged market which increases in competition and investment (Chirathivat 2002)

Using SMART model Zhao Malouche and Newfarmer (2008) found out that there is

only a limited increase in intraregional trade and trade diversion when they assume full

liberalization of trade between China and ASEAN is implemented Chinarsquos imports

from ASEAN would increase by 72 especially from Singapore Thailand and

Malaysia On the other hand according to the simulation conducted by the ASEAN

Secretariat (2001) CAFTA would increase ASEANs exports to China and Chinese

export to ASEAN by 48 and 551 respectively (China amp World Economy 2003)

Although previous studies had mixed results CAFTA does provide a platform for China

and ASEAN to establish a legal system for trade investment and service that complies

with the rules of WTO and international standards This allows promotion of freer trade

and attracts investment from the foreign countries (Zhang 2006)

27

6 Implications and Recommendations

As China joins ASEAN Free Trade Agreement in January 2010 this creates changes on

the trade flow From the side of ASEAN this agreement helps ASEAN members to

access a prosperous Chinese market From Table 82 (Appendix) there is an increasing

trend of trade among AFTA and China during the period of 2004-2008 Both sides

consider each other as crucial trading partners As tariff barrier is removed after

formation of CAFTA this can increase intra regional trade among these countries and

reduce AFTA reliance on United States European Union and Japan (Chia 2004) With

countries of different stages of economic development integrated CAFTA can narrow

the income gap between member countries (Roberts 2004)

However empirical studies show mixed results As defined in Linder Hypothesis

countries with similar levels of income per capita will exhibit similar demand produce

similar and differentiated products and trade more with each other According to

empirical study conducted by Roberts (2004) the coefficient testing of the Linder

Hypothesis is insignificant which implies that CAFTA does not have similar demand

pattern and this can be supported by the classification of different stages of economic

development among the members Roberts (2004) noted that China Cambodia Laos

PDR Myanmar and Vietnam are Low Income economies Indonesia Thailand and

Philippines are Low Middle Income economies Singapore and Brunei Darussalam are

28

High Income Economies based on World Bankrsquos classification CAFTA creates an

enlarged market which increases in competition and investment (Chirathivat 2002)

Using SMART model Zhao Malouche and Newfarmer (2008) found out that there is

only a limited increase in intraregional trade and trade diversion when they assume full

liberalization of trade between China and ASEAN is implemented Chinarsquos imports

from ASEAN would increase by 72 especially from Singapore Thailand and

Malaysia On the other hand according to the simulation conducted by the ASEAN

Secretariat (2001) CAFTA would increase ASEANs exports to China and Chinese

export to ASEAN by 48 and 551 respectively (China amp World Economy 2003)

Although previous studies had mixed results CAFTA does provide a platform for China

and ASEAN to establish a legal system for trade investment and service that complies

with the rules of WTO and international standards This allows promotion of freer trade

and attracts investment from the foreign countries (Zhang 2006)

28

High Income Economies based on World Bankrsquos classification CAFTA creates an

enlarged market which increases in competition and investment (Chirathivat 2002)

Using SMART model Zhao Malouche and Newfarmer (2008) found out that there is

only a limited increase in intraregional trade and trade diversion when they assume full

liberalization of trade between China and ASEAN is implemented Chinarsquos imports

from ASEAN would increase by 72 especially from Singapore Thailand and

Malaysia On the other hand according to the simulation conducted by the ASEAN

Secretariat (2001) CAFTA would increase ASEANs exports to China and Chinese

export to ASEAN by 48 and 551 respectively (China amp World Economy 2003)

Although previous studies had mixed results CAFTA does provide a platform for China

and ASEAN to establish a legal system for trade investment and service that complies

with the rules of WTO and international standards This allows promotion of freer trade

and attracts investment from the foreign countries (Zhang 2006)

29

7 Conclusion

With establishment of AFTA in 1992 it has successfully implemented CEPT scheme

and developed a time schedule in achieving a lower tariff rate This has facilitated trade

among the member countries Gravity Model is employed to investigate the relationship

between ex post bilateral trade values GDP and distance In sum there are three main

findings about trade effects of AFTA

Firstly our result shows AFTA has created intraregional trade bias and no trade

diversion effects By introducing three institutional dummy variables AFTA imAFTAij

and exAFTAij trade creation import trade diversion and export trade diversion are

examined In general the empirical results in this study are largely consistent with

previous literature

As trade creation and diversion are subjected to changes in external economic

environment one of the objectives in this paper is to find out whether there is a

strengthening or weakening of the trade effects especially in the period during or after

1997 Asian financial crisis and Outbreak of SARS These two events made the Asian

countries suffered economically With the use of OLS estimation our second main

finding shows 1997 Asian Economic Crisis had fostered AFTA export activities with

nonmember countries due to devaluation of ASEAN national currency Also trade was

promoted within the bloc after 1997 because of successful implementation of CEPT

30

scheme

Thirdly the outbreak of SARS has weakened intraregional trade bias negative export

trade diversion and negative import trade diversion Within the bloc Singapore and

Vietnam were hard hit by SARS Decline in intraregional trade creation could be

explained by increase in trade between nonmember countries Members of AFTA prefer

to import and export with members rather than nonmembers because spread of diseases

generated negative impacts to economies of Hong Kong and China which are their

major trading partners

With proliferation of FTAs in East Asia AFTA members need to take ldquospaghetti bowl

effectrdquo into consideration as multiple and overlapping FTAs result in diverse rules of

origin product standards and conformance requirements that will impede production

process and increase transaction cost (Chia 2004) The formation of CAFTA is a

milestone which enhances economic cooperation with economies of different stages of

development There should be strengthening of trade creation effects and trade

diversion effects as trade among CAFTA is facilitated

31

8 Appendix

Table 81

Intra ASEAN Exports First Quarter 1997-1998 in US Million Dollar

Source ASEAN Secretariat

Figure 81

Exchange rate of ASEAN-5 National currency against US Dollar from 1996-2008

Source ASEAN Statistical Yearbook 2008

32

Table 82 Trade Values of ASEAN Member States with China 2004-2008

(Value in million US$)

Country Name 2004 2005 2006 2007 2008

Brunei Darussalam 243 234 174 201 0

Cambodia 12 15 13 11 13

Indonesia 4605 6662 8344 8897 11637

Lao PDR 1 4 1 35 15

Malaysia 8634 9465 11391 15443 18422

Myanmar 75 119 133 475 499

Philippines 2653 4077 4628 5750 5467

Singapore 15321 19770 26472 28925 29082

Thailand 7098 9083 10840 14873 15931

Viet Nam 2711 2828 3015 3336 4491

ASEAN Export 41352 52258 65010 77945 85558

Brunei Darussalam 87 94 120 157 171

Cambodia 337 430 516 653 933

Indonesia 4101 5843 6637 8616 15247

Lao PDR 89 185 23 43 131

Malaysia 11353 14361 15543 18897 18646

Myanmar 351 286 397 564 671

Philippines 2659 2973 3647 4001 4250

Singapore 16137 20527 27185 31908 31583

Thailand 8183 11116 13578 16184 19936

Viet Nam 4416 5322 7306 12148 15545

ASEAN Import 47714 61136 74951 93173 107114

Source ASEAN Trade Statistics Database (Data as of July 2009)

33

9 Reference

ASEAN Secretariat (2009)

Available at httpwwwaseansecorg19585htm

ASEAN Secretariat (2009) ldquoASEAN Statistical Yearbook 2008rdquo Jakarta ASEAN

Secretariat

Robert R Teh Jr Raymond Yee and Noordin Azhari (1998) ldquoASEAN Reader Volume

5 the Sixth ASEAN Summit and Acceleration of AFTArdquo ASEAN Secretariat

Available at httpwwwaseansecorgPDFaftavol5pdf

Benjamin A Roberts (2004) ldquoA Gravity Study Of the Proposed China Asean Free

Trade Areardquo The International Trade Journal Laredo Winter 2004 Vol 18 Iss 4 p

335

Bhavish Jugutnath Mark Stewart Robert Brooks (2007) ldquoAsiaPacific Regional Trade

Agreements An empirical studyrdquo Journal of Asian Economics Vol 18 Iss 6 pp

974-987

Great Circle Distance between Cities

Available at httpwwwmarinewaypointscomlearngreatcircleshtml

Cabalu Helen and Alfonso Cristina (2007) ldquoDoes AFTA Create or Divert Traderdquo

Global Economy Journal Vol 7 Iss 4

Chia Siow Yue (2004) ldquoASEAN-China Free Trade Areardquo Paper for presentation at the

AEP Conference

China amp World Economy (2003) ldquoIV The Significance of China-ASEAN Free Trade

Areardquo

Donald Hanna Yiping Huang (2004) ldquoThe Impact of SARS on Asian Economiesrdquo

Asian Economic Papers Vol 3 Iss 1 p 102

Elliott Robert JR and Kengo Ikemoto (2004) ldquoAFTA and the Asian Crisis Help or

Hindrance to ASEAN Intra- Regional Traderdquo Asian Economic Journal 2004 Vol18

No1 1-23

30

scheme

Thirdly the outbreak of SARS has weakened intraregional trade bias negative export

trade diversion and negative import trade diversion Within the bloc Singapore and

Vietnam were hard hit by SARS Decline in intraregional trade creation could be

explained by increase in trade between nonmember countries Members of AFTA prefer

to import and export with members rather than nonmembers because spread of diseases

generated negative impacts to economies of Hong Kong and China which are their

major trading partners

With proliferation of FTAs in East Asia AFTA members need to take ldquospaghetti bowl

effectrdquo into consideration as multiple and overlapping FTAs result in diverse rules of

origin product standards and conformance requirements that will impede production

process and increase transaction cost (Chia 2004) The formation of CAFTA is a

milestone which enhances economic cooperation with economies of different stages of

development There should be strengthening of trade creation effects and trade

diversion effects as trade among CAFTA is facilitated

31

8 Appendix

Table 81

Intra ASEAN Exports First Quarter 1997-1998 in US Million Dollar

Source ASEAN Secretariat

Figure 81

Exchange rate of ASEAN-5 National currency against US Dollar from 1996-2008

Source ASEAN Statistical Yearbook 2008

32

Table 82 Trade Values of ASEAN Member States with China 2004-2008

(Value in million US$)

Country Name 2004 2005 2006 2007 2008

Brunei Darussalam 243 234 174 201 0

Cambodia 12 15 13 11 13

Indonesia 4605 6662 8344 8897 11637

Lao PDR 1 4 1 35 15

Malaysia 8634 9465 11391 15443 18422

Myanmar 75 119 133 475 499

Philippines 2653 4077 4628 5750 5467

Singapore 15321 19770 26472 28925 29082

Thailand 7098 9083 10840 14873 15931

Viet Nam 2711 2828 3015 3336 4491

ASEAN Export 41352 52258 65010 77945 85558

Brunei Darussalam 87 94 120 157 171

Cambodia 337 430 516 653 933

Indonesia 4101 5843 6637 8616 15247

Lao PDR 89 185 23 43 131

Malaysia 11353 14361 15543 18897 18646

Myanmar 351 286 397 564 671

Philippines 2659 2973 3647 4001 4250

Singapore 16137 20527 27185 31908 31583

Thailand 8183 11116 13578 16184 19936

Viet Nam 4416 5322 7306 12148 15545

ASEAN Import 47714 61136 74951 93173 107114

Source ASEAN Trade Statistics Database (Data as of July 2009)

33

9 Reference

ASEAN Secretariat (2009)

Available at httpwwwaseansecorg19585htm

ASEAN Secretariat (2009) ldquoASEAN Statistical Yearbook 2008rdquo Jakarta ASEAN

Secretariat

Robert R Teh Jr Raymond Yee and Noordin Azhari (1998) ldquoASEAN Reader Volume

5 the Sixth ASEAN Summit and Acceleration of AFTArdquo ASEAN Secretariat

Available at httpwwwaseansecorgPDFaftavol5pdf

Benjamin A Roberts (2004) ldquoA Gravity Study Of the Proposed China Asean Free

Trade Areardquo The International Trade Journal Laredo Winter 2004 Vol 18 Iss 4 p

335

Bhavish Jugutnath Mark Stewart Robert Brooks (2007) ldquoAsiaPacific Regional Trade

Agreements An empirical studyrdquo Journal of Asian Economics Vol 18 Iss 6 pp

974-987

Great Circle Distance between Cities

Available at httpwwwmarinewaypointscomlearngreatcircleshtml

Cabalu Helen and Alfonso Cristina (2007) ldquoDoes AFTA Create or Divert Traderdquo

Global Economy Journal Vol 7 Iss 4

Chia Siow Yue (2004) ldquoASEAN-China Free Trade Areardquo Paper for presentation at the

AEP Conference

China amp World Economy (2003) ldquoIV The Significance of China-ASEAN Free Trade

Areardquo

Donald Hanna Yiping Huang (2004) ldquoThe Impact of SARS on Asian Economiesrdquo

Asian Economic Papers Vol 3 Iss 1 p 102

Elliott Robert JR and Kengo Ikemoto (2004) ldquoAFTA and the Asian Crisis Help or

Hindrance to ASEAN Intra- Regional Traderdquo Asian Economic Journal 2004 Vol18

No1 1-23

31

8 Appendix

Table 81

Intra ASEAN Exports First Quarter 1997-1998 in US Million Dollar

Source ASEAN Secretariat

Figure 81

Exchange rate of ASEAN-5 National currency against US Dollar from 1996-2008

Source ASEAN Statistical Yearbook 2008

32

Table 82 Trade Values of ASEAN Member States with China 2004-2008

(Value in million US$)

Country Name 2004 2005 2006 2007 2008

Brunei Darussalam 243 234 174 201 0

Cambodia 12 15 13 11 13

Indonesia 4605 6662 8344 8897 11637

Lao PDR 1 4 1 35 15

Malaysia 8634 9465 11391 15443 18422

Myanmar 75 119 133 475 499

Philippines 2653 4077 4628 5750 5467

Singapore 15321 19770 26472 28925 29082

Thailand 7098 9083 10840 14873 15931

Viet Nam 2711 2828 3015 3336 4491

ASEAN Export 41352 52258 65010 77945 85558

Brunei Darussalam 87 94 120 157 171

Cambodia 337 430 516 653 933

Indonesia 4101 5843 6637 8616 15247

Lao PDR 89 185 23 43 131

Malaysia 11353 14361 15543 18897 18646

Myanmar 351 286 397 564 671

Philippines 2659 2973 3647 4001 4250

Singapore 16137 20527 27185 31908 31583

Thailand 8183 11116 13578 16184 19936

Viet Nam 4416 5322 7306 12148 15545

ASEAN Import 47714 61136 74951 93173 107114

Source ASEAN Trade Statistics Database (Data as of July 2009)

33

9 Reference

ASEAN Secretariat (2009)

Available at httpwwwaseansecorg19585htm

ASEAN Secretariat (2009) ldquoASEAN Statistical Yearbook 2008rdquo Jakarta ASEAN

Secretariat

Robert R Teh Jr Raymond Yee and Noordin Azhari (1998) ldquoASEAN Reader Volume

5 the Sixth ASEAN Summit and Acceleration of AFTArdquo ASEAN Secretariat

Available at httpwwwaseansecorgPDFaftavol5pdf

Benjamin A Roberts (2004) ldquoA Gravity Study Of the Proposed China Asean Free

Trade Areardquo The International Trade Journal Laredo Winter 2004 Vol 18 Iss 4 p

335

Bhavish Jugutnath Mark Stewart Robert Brooks (2007) ldquoAsiaPacific Regional Trade

Agreements An empirical studyrdquo Journal of Asian Economics Vol 18 Iss 6 pp

974-987

Great Circle Distance between Cities

Available at httpwwwmarinewaypointscomlearngreatcircleshtml

Cabalu Helen and Alfonso Cristina (2007) ldquoDoes AFTA Create or Divert Traderdquo

Global Economy Journal Vol 7 Iss 4

Chia Siow Yue (2004) ldquoASEAN-China Free Trade Areardquo Paper for presentation at the

AEP Conference

China amp World Economy (2003) ldquoIV The Significance of China-ASEAN Free Trade

Areardquo

Donald Hanna Yiping Huang (2004) ldquoThe Impact of SARS on Asian Economiesrdquo

Asian Economic Papers Vol 3 Iss 1 p 102

Elliott Robert JR and Kengo Ikemoto (2004) ldquoAFTA and the Asian Crisis Help or

Hindrance to ASEAN Intra- Regional Traderdquo Asian Economic Journal 2004 Vol18

No1 1-23

32

Table 82 Trade Values of ASEAN Member States with China 2004-2008

(Value in million US$)

Country Name 2004 2005 2006 2007 2008

Brunei Darussalam 243 234 174 201 0

Cambodia 12 15 13 11 13

Indonesia 4605 6662 8344 8897 11637

Lao PDR 1 4 1 35 15

Malaysia 8634 9465 11391 15443 18422

Myanmar 75 119 133 475 499

Philippines 2653 4077 4628 5750 5467

Singapore 15321 19770 26472 28925 29082

Thailand 7098 9083 10840 14873 15931

Viet Nam 2711 2828 3015 3336 4491

ASEAN Export 41352 52258 65010 77945 85558

Brunei Darussalam 87 94 120 157 171

Cambodia 337 430 516 653 933

Indonesia 4101 5843 6637 8616 15247

Lao PDR 89 185 23 43 131

Malaysia 11353 14361 15543 18897 18646

Myanmar 351 286 397 564 671

Philippines 2659 2973 3647 4001 4250

Singapore 16137 20527 27185 31908 31583

Thailand 8183 11116 13578 16184 19936

Viet Nam 4416 5322 7306 12148 15545

ASEAN Import 47714 61136 74951 93173 107114

Source ASEAN Trade Statistics Database (Data as of July 2009)

33

9 Reference

ASEAN Secretariat (2009)

Available at httpwwwaseansecorg19585htm

ASEAN Secretariat (2009) ldquoASEAN Statistical Yearbook 2008rdquo Jakarta ASEAN

Secretariat

Robert R Teh Jr Raymond Yee and Noordin Azhari (1998) ldquoASEAN Reader Volume

5 the Sixth ASEAN Summit and Acceleration of AFTArdquo ASEAN Secretariat

Available at httpwwwaseansecorgPDFaftavol5pdf

Benjamin A Roberts (2004) ldquoA Gravity Study Of the Proposed China Asean Free

Trade Areardquo The International Trade Journal Laredo Winter 2004 Vol 18 Iss 4 p

335

Bhavish Jugutnath Mark Stewart Robert Brooks (2007) ldquoAsiaPacific Regional Trade

Agreements An empirical studyrdquo Journal of Asian Economics Vol 18 Iss 6 pp

974-987

Great Circle Distance between Cities

Available at httpwwwmarinewaypointscomlearngreatcircleshtml

Cabalu Helen and Alfonso Cristina (2007) ldquoDoes AFTA Create or Divert Traderdquo

Global Economy Journal Vol 7 Iss 4

Chia Siow Yue (2004) ldquoASEAN-China Free Trade Areardquo Paper for presentation at the

AEP Conference

China amp World Economy (2003) ldquoIV The Significance of China-ASEAN Free Trade

Areardquo

Donald Hanna Yiping Huang (2004) ldquoThe Impact of SARS on Asian Economiesrdquo

Asian Economic Papers Vol 3 Iss 1 p 102

Elliott Robert JR and Kengo Ikemoto (2004) ldquoAFTA and the Asian Crisis Help or

Hindrance to ASEAN Intra- Regional Traderdquo Asian Economic Journal 2004 Vol18

No1 1-23

33

9 Reference

ASEAN Secretariat (2009)

Available at httpwwwaseansecorg19585htm

ASEAN Secretariat (2009) ldquoASEAN Statistical Yearbook 2008rdquo Jakarta ASEAN

Secretariat

Robert R Teh Jr Raymond Yee and Noordin Azhari (1998) ldquoASEAN Reader Volume

5 the Sixth ASEAN Summit and Acceleration of AFTArdquo ASEAN Secretariat

Available at httpwwwaseansecorgPDFaftavol5pdf

Benjamin A Roberts (2004) ldquoA Gravity Study Of the Proposed China Asean Free

Trade Areardquo The International Trade Journal Laredo Winter 2004 Vol 18 Iss 4 p

335

Bhavish Jugutnath Mark Stewart Robert Brooks (2007) ldquoAsiaPacific Regional Trade

Agreements An empirical studyrdquo Journal of Asian Economics Vol 18 Iss 6 pp

974-987

Great Circle Distance between Cities

Available at httpwwwmarinewaypointscomlearngreatcircleshtml

Cabalu Helen and Alfonso Cristina (2007) ldquoDoes AFTA Create or Divert Traderdquo

Global Economy Journal Vol 7 Iss 4

Chia Siow Yue (2004) ldquoASEAN-China Free Trade Areardquo Paper for presentation at the

AEP Conference

China amp World Economy (2003) ldquoIV The Significance of China-ASEAN Free Trade

Areardquo

Donald Hanna Yiping Huang (2004) ldquoThe Impact of SARS on Asian Economiesrdquo

Asian Economic Papers Vol 3 Iss 1 p 102

Elliott Robert JR and Kengo Ikemoto (2004) ldquoAFTA and the Asian Crisis Help or

Hindrance to ASEAN Intra- Regional Traderdquo Asian Economic Journal 2004 Vol18

No1 1-23

34

Hans Linnemann (1966) An Econometric Study of International Trade North ndash

Holland Amsterdam

Hector Calvo-Pardo Caroline Freund Emanuel Ornelas (2009) ldquoThe ASEAN Free

Trade Agreement Impact on Trade Flows and External Trade Barriersrdquo World Bank

Policy Research Working Paper No 4960

International Monetary Fund Direction of Trade Statistics Yearbook (1988-2004)

International Monetary Fund World Economic Outlook Database (1988-2004)

Available at httpwwwimforgexternalpubsftweo200902weodataindexaspx

Jong Wha Lee (2004) ldquoGlobalization and Disease The Case of SARSrdquo Asian

Economic Papers Vol 3 No 1 p 113

Longyue Zhao Mariem Malouche and Richard Newfarmer(2008) ldquoChinas emerging

regional trade policyrdquo Journal of Chinese Economic and Foreign Trade Studies Vol 1

Iss 1 p 21

Masahiro Endoh (1999) ldquoTrade creation and trade diversion in the EEC the LAFTA

and the CMEA 1960-1994rdquo Applied Economics Vol 31 No 2 p 207

Michael F Martin (2008) ldquoEast Asia Foreign Exchange Rate Policiesrdquo Congressional

Research Service Report for Congress April 10 2008

Nguyen Trung Kien (2009) ldquoGravity Model by Panel Data Approach- An Empirical

Application with Implications for the ASEAN Free Trade Areardquo ASEAN Economic

Bulletin Vol 26 No 3 (2009) pp 266ndash77

Paul Bowles (1997) ldquoASEAN AFTA and the New Regionalismrdquo Pacific Affairs

Vol70 No2 pp219-233

Phusadee Arunmas (2008) ldquoThai firms urged to tap eased rulesrdquo Bangkok Post

Thailand 18th

July 2008

Sharma Subhash C Chua Soo Y (2000) ldquoASEAN economic integration and

intra-regional traderdquo Applied Economics Letter Vol 7 Iss 3 pp 165-69

Suthiphand Chirathivat (2002) ldquoASEAN-China Free Trade Area background

35

implications and future developmentrdquo Journal Of Asian Economics Vol 13 No 5

September-October 2002 pp 671-86

Tang Donny (2005) ldquoEffects of the Regional Trading Arrangements on Trade

Evidence from the NAFTA ANZCER and ASEAN Countries 1989-2000rdquo The

Journal of International Trade amp Economic Development Vol14 No2 241-265

Thanyaluk Vichitsarawong Li Li Eng Gary K Meek (2010) The Impact of the Asian

Financial Crisis on Conservatism and Timeliness of Earnings Evidence from Hong

Kong Malaysia Singapore and Thailand Journal of International Financial

Management amp Accounting Vol 21 Iss 1 p 32

Thornton John and Goglio Alessandro (2002) ldquoRegional bias and intra-regional trade

in Southeast Asiardquo Applied Economics Letters Vol 9 Iss 4 pp 205-208

Tinbergen Jan (1962) Shaping the World Economy-Suggestions for an international

policy The Twentieth Century Fund New York

Lee Jong-Wha and Shin Kwanho (2006) ldquoDoes Regionalism Lead to More Global

Trade Integration in East Asiardquo North American Journal of Economics and Finance

December 2006 Vol 17 Iss 3 pp 283-301

US Fed News Service (2010) ldquoASEAN ndash China Free Trade Area Not a Zero Sum

Gamerdquo Jan 9 2010

Yunling Zhang (2006) ldquoChina and East Asian Economic Integration and Cooperationrdquo

Journal Of Economics Development December 2006 Vol31 No2

Y K Kwan and Larry D Qiu (2003) The ASEAN+3 trading bloc East Asian Bureau

of Economic Research Australian National University Trade Working Papers No 196