1

EVALUATE THE IMPACTS OF FTAS ON VIETNAM IRON

AND STEEL TRADE FLOWS UNDER ASEAN+3:

GRAVITY MODEL ANALYSIS1

Dr. Nguyen Anh Thu

Do Thi Mai Hien

University of Economics and Business,

Vietnam National University, Hanoi

Abstract

This paper analyzes the impacts of all FTAs in the ASEAN+3 region which

Vietnam has signed on Vietnam Iron and Steel trading status. In this respect, a gravity

model is used with panel data an dordinary least-squares (OLS) regression method

covering 27 top trading countries from 2001 to 2012. The final gains of the paper is to

point out clearly the positive impact of ACFTA and VJEPA on increasing import flows

of iron and steel into Vietnam while AKFTA, AFTA and VJEPA has played positive

effects on exporting. AJCEP and AFTA are concluded to have little impact on both

import and export volume. Besides, effects of other determinants apart from FTAs on

trading status are also gained after this paper.

Tóm tắt

Bài nghiên cứu đi sâu đánh giá tác động của các Hiệp định thương mại tự do

(FTA) mà Việt Nam đã ký kết trong khu vực ASEAN+3 đối với hoạt động xuất nhập khẩu

mặt hàng sắt thép của Việt Nam. Phương pháp mô hình trọng lực đã được sử dụng với

nguồn dữ liệu dạng bảng, ước lượng bình phương nhỏ nhất, chạy hồi quy trên mẫu dữ

liệu bao gồm lưu lượng xuất khẩu, nhập khẩu mặt hàng sắt thép với của Việt Nam với 27

quốc gia có cán cân thương mại xuất nhập khẩu lớn với Việt Nam về mặt hàng sắt thép

từ năm 2001 đến năm 2012. Bài nghiên cứu đã chỉ ra Hiệp định ASEAN- Trung Quốc

(ACFTA) và Hiệp định song phương Việt Nam- Nhật Bản (VJEPA) có tác động thuận với

hoạt động nhập khẩu các mặt hàng sắt thép của Việt Nam trong khi các hiệp định ASEAN

- Hàn Quốc (AKFTA), Hiệp định thương mại tự do (AFTA) có ảnh hưởng tích cực đến

hoạt động xuất khẩu mặt hàng sắt thép của Việt Nam. ẠJCEP và AFTA được ghi nhận là

những hiệp định chưa có nhiều tác động đến hoạt động ngoại thương của ngành sắt thép

Việt Nam. Mức độ ảnh hưởng của những nhân tố khác ngoài các hiệp định đối với hoạt

động xuất nhập khẩu sắt thép của Việt Nam cũng đã được chỉ ra trong bài nghiên cứu.

1. Introduction

1 The research could not be completed without kind support of Mr. Nguyen Thanh Tung, Mr. Pham Van Nho and

Mr. Nguyen Tri Si. We are truly grateful to say thank to all of them. Any remaining mistakes are by the authors

alone.

2

The establishment of FTAs has been regarded as a commitment between member

nations towards a free trade area. The impacts of increasing Regional trade agreements

over years have been figured out in several industries. Iron and steel industry is known as

a sensitive industry in Vietnam which also under the significant effects of free trade

agreements. In this paper, the author tries to address main concern about the impacts of

FTAs under ASEAN+3 on Vietnam Iron and Steel industry. How is the current status of

tariff reduction of Vietnam iron and steel industry under FTAs? Up to now, what is the

trading status of Vietnam Iron and Steel Industry in ASEAN+3? These questions are all

explored carefully.

In this study, Reveal Comparative Advantage Index (RCA) of Vietnam iron and

steel industry is calculated to show how competitive is iron and steel in Vietnam’s export

compared to the product’s exports in relations to its share in the world trade while Export

and import intensity index are cultivated to measure which nations Vietnam has larger

share in export and import iron and steel. More importantly, to have a clear answer about

the effect level of FTAs on trading flows of iron and steel products, a gravity model

approach is used. Basing upon the available of information, data used in the model are

from 2001 to 2012 from trusted sources.

The paper is divided into five major sections. First, a brief introduction about the

content of the paper is pointed out. Second part is a specific review of the methodology

of all previous researches. While in some ways, the paper is quite similar to the works of

URATA Shujiro and OKABE Misa (2007) in having depicted an image of trade flows

under the effects of FTAs, or Sohn, Chan-Hyun (2001) in using the gravity model

analysis to work out the relationship between the trading flows and regional trading

agreements, especially Nguyen Tien Dung (2011), this study still become unique in

applying gravity model in a new scope which is the iron and steel trade flows of Vietnam

under ASEAN+3.There has not been any study applying gravity model on Vietnam iron

and steel trade flows. Section 3 analyzes an integration of Vietnam Iron and Steel

Industry in ASEAN+3 in terms of the openness level of FTAs, competitive advantage of

Vietnam iron and steel industry in the regional integration and the change of trading

volume of Vietnam iron and steel industry after FTAs. Section 4 applies the gravity

model approach in clarifying whether FTAs has effects on iron and steel export and

imports. The final remaining part is followed to make a conclusion and

recommendations for Vietnam towards the integration in ASEAN+3.

2. Methodology

In this paper, the separate influences of FTAs and other variables are quantized by

percentage change of trading flows. The author uses gravity model to quantize the

impacts of Free trade Agreement on the import, export value of iron and steel industry

with supports of economic software eview 6.0 in order to examine the impact of the

FTAs on trade flows by controlling the factors other than tariff reduction.

Over the world, there have been a number of researches focusing on the analysis

of the effects of FTAs especially ones using gravity model to clarify the impacts of FTAs

within region on significant sectors of a country. The first formulations of the gravity

model equation are found in Timbergen (1962), Pöyhönen (1963). They applied to the

gravity equation to analyze international trade flows. Since then, the gravity model has

become popular instrument in empirical foreign trade flows. Initially, the gravity model

3

is used for explaining the exports from country i to country j which depends on the

economic sizes (GDP or GNP), their populations, direct geographical distance and a set

of dummies incorporating some kind of institutional characteristics common to specific

flows.

In the second half of the 1970s several theoretical developments have emerged in

support specifically the gravity model. Anderson (1979) made the formal attempt to

derive the gravity equation by adding assumption of product differentiation. In 1995,

Deadorff also proved that the gravity equation could be justified from standard trade

theories.

Up to now, the trend using the gravity model analysis to evaluate the effects of

FTAs on trade flows has been increasing sharply. The standard gravity model use

variables as followed: Real GDP, income gap (to account for intra-industry trade and

level of income), a measure of remoteness, adjacency and geographical characteristics

such as being landlocked. The original gravity equation looks as follows:

=

In which: A, a, b, c are the parameters to be estimated. The equation’s logarithmic

transformation is given by:

Log = + a.Log + b.Log + c.Log

The gravity model has been widely applied in international trade studies. Its

popularity is due to the concept simplicity, its appropriateness to match well with the

available data and the models’ econometric estimation. Depend upon the significant

purposes of the studies, the gravity model analysis is added more variables in many

researches to apply effectively the examination of the relationship among several factors

in international trade cases.

Determining suitable variables is one of the primary and most important

requirements in setting up econometric models to attain precise economic results. This

section provides analysis and explanations for variables used in the models.

The starting point of building up the models is based on the following

specification of the gravity model:

In which:

represents trade flows (exports or imports) between country 1 and country “i”

is the GDP of country “i”

represents the Distance between country 1 and country “i”

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is Dummy variable indicating to which Regional and Preferential Trade

Agreement a particular country belongs: “i” runs from 1 to 5, reflecting respectively

AFTA, ASEAN-China, ASEAN-Korea, ASEAN-Japan, Japan-Vietnam Economic

Partnership Agreement. represents 1 -Membership in the specific FTAs, representing

0-otherwise.

In the simple form, the gravity equation can be re-written by logarithmic

transformation as bellows:

LOG( ) = C + LOG( ) + LOG( ) + LOG( )+

In which:

Σ (Sij) represents other variables that affect trade like history, language, land

locked, borders for example. Σ (Sij) represents 1 for Colonial ties, Common language,

Landlocked, Common borders; and Σ (Sij) equals 0 for otherwise.

It is depend upon the paper’s purpose which is to build up the appropriate model

to clarify out the answer for the research questions, the relationship between trade flows

and various explanatory variables will be estimated by ordinary least-squares (OLS)

regression methods.

For this paper, in order to evaluate the impacts of FTAs in ASEAN+3 region

which Vietnam has signed until now, including AFTA, ACFTA, AKFTA, AJCEP,

VJEPA on the Vietnam iron and steel industry, the author has made decision of using the

gravity model to cultivate how much these FTA affect the Vietnam iron and steel

industry’s trading. This model will be hoped to analyze the trade flows of Vietnam Iron

and Steel products with other nations on the account of the several factors, such as Real

GDP, Real GDP per capita, Real exchange rate, Income Gap, Distance between

countries. The author do hope that this gravity model will indicates whether FTAs

affected the Vietnam iron and steel industry in the scope of research, FTAs increase or

decrease the trading flows of Vietnam iron and steel industry with ASEAN+3 nations

compared to the previous normal trades flows. To examine the impacts of FTAs, dummy

variables are added into the model. If these dummy variables have positive and

significant coefficients, this means that FTA will have a good effect of accelerating the

trade flows among countries.

The gravity model in this study will have general variables in the standard gravity

model and such a number of additional dummy variables of FTAs, Border and Land

locked. Lack of coastline increases the time and cost of transportation as well as the

dependence on the quality of the infrastructure network across the region as a whole,

particularly that of the neighboring countries. Besides, the author also finds that the

increase in total trade of iron and steel products of Vietnam comes from improvement in

infrastructure, followed by logistics and efficiency of customs and other border agencies.

The non-tariff barriers also are taken into consideration, as the main challenges of

exporting iron and steel of Vietnam into other countries in ASEAN seems to be the

nontariff barriers imposed by the home countries’ government, besides tariff. The FTAs

dummy were put into this equation are the FTAs membership. When adding FTAs

dummy, this paper mentions to the impacts of being membership of FTAs in general.

5

After all, there were many motives from the author to examine the effects of several

factors on Vietnam iron and steel trade flow, however, depending on the availability of

the data base, the author will build the exporting model and importing model as

bellowed:

(i) Log = + Log + Log + +

+ + +

(ii) Log = + Log + Log + +

+ + +

In here: and are the export volume and import volume of Vietnam Iron

and steel products to the country j, Gap is the differences of Real GDP per capita of

Vietnam and the country j; Distw is the geographical distance from Vietnam to country j

which is standardized for populations; are the dummy variables measuring the

impacts of FTAs membership on the export and import flows between Vietnam and the

countries.

Export and Import flows (Yi) measured in dollars; Real GDP and Gap measured in

dollars, Distance are in thousands of kilometers, Borders represents 1 if they share a

common border and 0 otherwise. The FTAs dummy represents 0 if the trading partner is

not the member of corresponding FTA and 1 if the trading partner is the member of that

FTA since the year FTA goes into effects. Consequently, the dummy variables AFTA,

ACFTA, AKFTA, AJCEP and VJEPA will be 1 since the following years, respectively,

2006, 2006, 2007 and 2010 for the AJCEP, VJEPA. Landlocked equals 1 if the trading

country j is landlocked, 0 otherwise. The author choose those years as from this years,

such a significant tariff elimination of FTAs has been practically undertaken on Vietnam

iron and steel products and have big effects on Iron and steel industry trades.

Besides, some other important index in international trade is also used in this

study. Firstly, the Reveal Comparative Advantage Index (RCA) of Vietnam iron and steel

industry is calculated to show how competitive is iron and steel in Vietnam’s export

compared to the product’s exports in relations to its share in the world trade. The

equation to calculate RCA is shown below:

Where and are the values of Vietnam’s exports of iron and steel products

and world exports of iron and steel; and represents Vietnam’s total exports and

world total exports.

Secondly, other indexes which are also cultivated are Export Intensity Index and

Import intensity Indices. These indices reflects the ratio of the share of country i’s trade

with country j relative to the share of the world trade destined for country j. They can be

defined as follows:

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Where: : Country i’s exports to country j; : country i’s total exports to the

world : country j’s total imports from the world; : world total imports; :

country i’s total imports from the world; : country i’s exports to country j; :

country j’s total exports to the world; : world total exports.

3. Data

The model uses the export and import statistics from UN COMTRADE data base

from the year 2001 to 2012 as the availability of Vietnam’s data base in this period. Real

GDP are sourced from World Bank; the Gap is calculated from Real GDP per capita

taken from World Bank; Distw; Border and Landlocked are taken from CEPII. There are

total 27 top trading partners in iron and steel which are recorded in the model for the

period 2001-2012 from the data base of UNCOMTRADE2.

According to Economic theory, real GDP will correlate positively with trade

activities. Higher income levels will lead to higher demand on the trading of goods.

Therefore, the volume of exchange goods will be greater. Iron and steel are the typical

goods following that trend. Distances are supposed to have negative impact on both

exporting and importing. The farther the distance is, the higher transportation costs might

be. High transportation cost will hinder the exchanges of goods among nations. In other

words, the greater the distance is, the less trade between countries is. The Income Gap

variable is calculated as the differences between real GDP per capita of each countries

and it is used to check out whether the trade depends on intra-trade or inter-trade. It may

be positive or negative. When the coefficient of this variable is positive, this means trade

flows are mainly depend upon the inter-industry trade based on differences in factors of

production resources. In contrast, if the income gap has a negative sign, it shows impact

of intra-industry trade.

Data used in the model are from 2001 to 2012, and is collected from trusted

sources such as:

Real GDPs, real GDP per capita (taken fixed 2005 USD’s price), are taken from

in the World Bank’s World Development Indicators

Export and import flows is picked up from WIST

2Trading partners are used in this model: Australia, Belgium, Benin, Brunei, Cambodia, Canada,

Chile, China, Colombia, Haiti, Hong Kong, India, Indonesia, Taiwan, Japan, Korea, Lao,

Malaysia, Netherlands, New Zealand, Philippines, Russia Singapore, Thailand, United Kingdom

and United States. Myanmar is excluded as the lack of statistics.

7

Distances, border and landlocked are taken from the Centre d’Etudes

Prospectives at d’InformationsInternationales (CEPII)

Econometric results

Table I: RCA for ASEAN+3 countries in Iron and Steel industry

Country 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Thailand 0.38 0.44 0.49 0.48 0.45 0.42 0.74 0.40 0.31 0.30 0.27 0.50

Philippines 0.05 0.07 0.09 0.15 0.18 0.28 0.25 0.24 0.18 0.16 0.13 0.09

Brunei 0.00 0.02 0.03 0.02 0.00 0.03 0.00 0.00 0.00 0.00 0.00 0.06

Malaysia 0.19 0.36 0.43 0.28 0.32 0.47 0.38 0.27 0.40 0.38 0.31 0.23

Indonesia 0.29 0.34 0.44 0.30 0.46 0.36 0.40 0.23 0.31 0.26 0.17 0.15

Singapore 0.17 0.23 0.26 0.20 0.20 0.25 0.27 0.18 0.24 0.23 0.21 0.23

Lao 0.04 0.06 0.45 0.15 0.01 0.00 0.02 0.01 0.03 0.01 0.02 0.03

Cambodia 0.00 0.01 0.01 0.01 0.02 0.01 0.03 0.03 0.04 0.05 0.00 0.01

Myanmar _ _ _ _ _ _ _ _ _ _ 0.01 0.02

Vietnam 0.06 0.09 0.12 0.16 0.21 0.22 0.28 0.88 0.32 0.61 0.72 0.43

China 0.46 0.36 0.36 0.70 0.72 0.94 1.07 1.15 0.50 0.71 0.79 0.77

Korea 1.84 1.60 1.69 1.51 1.65 1.56 1.44 1.55 1.91 1.81 1.87 1.97

Japan 1.51 1.63 1.53 1.36 1.50 1.46 1.37 1.54 2.19 1.96 1.93 2.11

Source: Calculated by the author from the data base of UN COMTRADE.

From the table I, the outstanding outcome to be noted is the RCA of Vietnam in

Iron and steel industry appear to be the highest index compared to ASEAN nations in

each year from 2001 to 2012. The computation of RCA for iron and steel showed that

Vietnam has developed comparative advantage in the product category over the period of

time. The general trend of RCA through years was upward trend and on account of the

further integration of Vietnam into the international market, RCA of Vietnam has been

hoped to keep increasing in the near future.

Nevertheless, the RCA of Vietnam was below one. We aware that RCA were

regarded as low if it is below one and strong if it is over one or two. The case of Vietnam,

all of RCA index over years were still below 1, which reveals that Vietnam seemed not to

have comparative advantages in iron and steel products. This industry depends on the

availability of natural resources in country and the development of the industry. A

snapshot of Vietnam iron and steel industry in the integration phase can explain clearly

8

why Vietnam has comparative disadvantage in iron and steel industry, although the role

of this industry is typically important for the reform of country.

Besides, the RCA of ASEAN nations were below one, in other words, all of these

countries got comparative disadvantage with big trading partner China, Korea, Japan.

Therefore, most of the ASEAN countries including Vietnam, can facilitate importing iron

and steel from Japan, China and Korea in ASEAN+3 region.

Apart from measuring the competitive advantages of Vietnam iron and steel with

other nations, the trade intensities is the typical index for pointing out the share of

Vietnam iron and steel trade with another country. The value of index may range from 0

to 100. It reflects that country is importing more (or less) from country j than might be

expected from that country’s share in total world trade. In export side, if the value is 0 or

nearer to 0, it implies that export link between these countries is negligible and if the

value is nearer to 100 that indicates that the performance is relatively significant and if it

exceeds 100 it reveals that a country export more than expected with the other countries.

The trade intensity is usually divided into the export intensity and import intensity.

Table II: Vietnam’s Export and Import intensity index with ASEAN+3

countries, sector: Iron and steel industry.

Yea

r

Ind

on

esia

Th

ail

an

d

Mala

ysi

a

Sin

gap

ore

Ph

ilip

pin

es

Cam

bod

ia

Jap

an

Kore

a

Ch

ina

Lao

2006 MII 4.13 3.10 11.52 2.96 0.69 1696.95 0.97 0.67 0.99 398.24

EII 5.31 6.64 4.46 1.68 19.66 126.95 2.14 1.58 6.22

2007 MII 17.09 1.68 14.36 1.27 3.73 1091.63 0.74 1.13 1.50 546.35

EII 5.32 8.53 13.97 0.83 12.16 205.35 1.79 1.31 4.60

2008 MII 12.58 5.93 5.01 5.88 29.40 498.26 0.17 0.97 0.32 369.00

EII 6.51 7.13 8.69 1.11 4.83 86.95 2.27 2.26 3.18

2009 MII 11.29 3.47 14.68 2.91 9.83 247.04 0.54 0.76 0.33 246.48

EII 4.59 8.72 12.39 0.97 2.40 53.12 1.53 2.19 3.00

2010 MII 8.91 2.09 10.98 3.86 5.25 234.72 1.63 1.81 1.47 152.84

EII 2.99 6.49 12.91 1.33 1.63 119.23 1.81 3.16 3.29

2011 MII 8.96 4.86 8.54 3.39 9.90 154.53 2.06 1.33 0.93 308.42

EII 3.40 5.75 9.19 1.54 1.97 0.53 2.43 3.72 2.53

2012 MII 10.15 4.57 8.77 2.10 7.09 110.61 2.80 0.84 0.53 106.08

EII 2.70 1.29 3.35 2.04 0.98 67.24 2.58 3.12 3.01

9

Source: Computed from Trade Map Statistics

The table II demonstrates that Vietnam’s export intensity and import intensity

index are mostly greater than one with all ASEAN+3 nations in iron and steel industry,

implying a strong link between Vietnam and individual members with associated FTAs

in the region. Vietnam’s import intensity index (MII) was quite small with Japan for

many years before 2010 but has improved strongly after signing the VJEPA. Vietnam’s

export has forced with Singapore recently, while declined with several countries, namely

Indonesia, Thailand and Malaysia. Cambodia and Lao become outstanding with high

value of export intensity index (EII) and MII with Vietnam, this comes froma low total

volume in both total export and import of these two country which the volume with

Vietnam plays a majority of.

This section, through the statistical analysis of trade intensity and RCA, the

strength and nature of bilateral trading relationships between countries, is examined.

Some concluding remarks are achieved. Vietnam has comparative disadvantage in iron

and steel industry. Meanwhile, Korea, China and Japan, with high RCA index of more

than one are confirmed to have comparative advantage in iron and steel sectors. ASEAN

nations have lower RCA than these big countries. Vietnam, in near future might keep

importing more from China, Japan and Korea. The export and import intensity indices

have proved for this trend, especially after the years of FTAs establishment. A last thing

to note is a strong trading relation among countries in iron and steel industry.

The table III gives the results for the regression coefficients of all variables for

Exports and Imports model. Almost all the standard gravity variables have the expected

and statistically significant sign. Besides, R-squared value in export and import model are

respectively 0.657 and 0.554, quite high and be accepted for depicting the export and

import equation.

Table III: The econometric results

Export model Import model

Log 0.496*** 0.661***

(0.00) (0.00)

Log 8.088*** 2.765***

(0.00) (0.00)

0.03 -0.031

(0.66) (0.6263)

-1.689*** -0.389***

(0.00) (0.0047)

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Export model Import model

AFTA 0.986* -1.910***

(0.145) (0.0038)

ACFTA -0.735 2.559***

(0.257) (0.001)

AKFTA 1.556** -0.186

(0.012) (0.757)

AJCEP -1.631*** -1.1097**

(0.005) (0.0478)

VJEPA 1.614* 2.366**

(0.131) (0.0235)

Border 1.779*** -1.511***

(0.0001) (0.0005)

Landlocked -0.058 -1.246**

(0.91) (0.0128)

Constant -186.747*** -65.448***

(0.00) (0.00)

R-squared 0.657 0.554

Adjusted R-

squared 0.641 0.537

*: p< 0.15, **: p< 0.05, ***: p< 0.01

Source: The author’s calculation

Before examining the effects of FTAs on trade flows of Vietnam iron and

steel industry, the author does wish to high light the general effects of other

concerning variables in the model to check out its impacts on trade flows of

Vietnam iron and steel.

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Firstly, Real GDP which measures the economies of scale are seen to have

positive sign in both export and import equation. It reveals that the growth of economy of

Vietnam as well as the trading countries will foster the export and import flows in and

out Vietnam. In other words, Real GDP factor has positive effects on trading of iron and

steel industry. More specific, for exporting, the volume will increase respectively by an

average of 0.496 percent and 8.09 percent if real GDP of the destination market and

Vietnam rise by about 1 unit. Importing iron and steel is also under the same positive

effect of real GDP as in exporting but with different coefficients.

Secondly, about the income gap variable, this one appeared to be positive sign in

export model and negative sign in importing one but there are no statistical significance

in both two equations. It can be explained that the exporting iron and steel of Vietnam

mainly are related to inter-industry trade with trading partners; meanwhile, the importing

iron and steel of Vietnam are intra-trade. However, this effect does not play in the trade

flows of iron and steel. It does not have any significant effects on the exporting and

importing volume of Vietnam iron and steel industry.

Thirdly, distance is recorded at negative sign with both export and importing

value. This matches with the theory in gravity models. Other dummies, like border,

landlocked are relatively meet the author’s expectation. Border has positive and

significant sign in export but negative sign in import equation. This comes from the data

base that Vietnam seems to export more easily with neighboring countries while imports

did not follow that trend. The import of Vietnam might be unique for some several

reasons. Vietnam seems to import more with the markets in which can supply the cheap

price but still guarantee suitable quality. Having borders with Vietnam, there are only

Lao, Cambodia and China. Luckily, there is only China having comparative advantages

for Vietnam to import. Lao, Cambodia, with the same or even lower developed level in

iron and steel industry, are likely not the key market to import for Vietnam, even though

they have borders advantage. However, the exporting to these countries is potential.

Landlocked, as presented in the previous section, are hindrance for trading activities. In

the iron and steel equation, landlocked has negative sign in import equation and does not

have much effects on exporting.

The most important part gained from the above table is the FTA’s effects on

Vietnam iron and steel trade flows. Among all FTAs mentioned, only AKFTA and

AJEPA are recorded as having significantly positive sign for exports model. AKFTA is

noticed as a FTA has positive and significant impact on the export when the coefficient

of AKFTA dummy is quite high at 1.556 at a significance level of 5 percent. This is

appropriate with the fact that from 2010, the export volume of iron and steel to Korea has

sharply plunged after 2007 when AKFTA went into force. VJEPA remarks a larger

impact on exporting when its coefficient reaches a number of 1.614 at the significant

level of 15 percent. This is consistent with the expected sign from the analysis in

previous section.

AFTA has a coefficient of 0.986 with statistically significant level of 15 percent,

indicating that AFTA has relative impact on Vietnam export iron and steel within

ASEAN region. The complicated trend of Vietnam export flows within ASEAN, as

depicted in the chapter 3 might reflect that export flows of Vietnam iron and steel

products is largely conflicted over time and it is difficult to clarify out clearly the impact

12

of AFTA on this era in short time but after all, AFTA still is illustrated to force the

exports flows of Vietnam. ACFTA also does not have significant sign in export equation.

The author can understand why this result comes out. There is the fact that China is a big

country of supplying iron and steel globally, the demand for importing this kind of goods

are still quite low, besides, there was a downward trend of Vietnam’s export flows to

China recently, this causes a negative sign of ACFTA but no statistically significant.

In term of importing model, ACFTA become the key FTA having positive and

statistically significant coefficient. An increase of about 2.559 percent in import value

will be gained from the establishment of ACFTA. Meanwhile, VJFTA creates an average

increase of 2.366 percent of import volume. From the view of iron and steel sector, China

and Japan are two main potential suppliers for Vietnam in long time. This outcome has

therefore, totally reflected accurately the fact of import flows among these countries

thanks to tariff elimination under ACFTA and VJEPA.

However, the downward trend of import flows recently of Vietnam from ASEAN

markets causes AFTA be reflected to have statistically negative sign of 1.910 percent.

Along with AFTA, AJCEP was also recorded at the same sign like AFTA with minus

1.109 percent in affecting the importing Vietnam iron and steel. It uncovers that joining

these FTA does not bring out improvement in the exports from ASEAN countries to

Vietnam in iron and steel sector. Only AKFTA, with the short time of establishment, in

the model, does not have significance in importing equation. It is the complicatedly

fluctuation of importing flow from Korea to Vietnam over years accompanying with a

short time of establishment of AKFTA that the effects does not be taken into account.

Hope that for the latter studies, with longer time of series data, it can be pointed out

accurately the influences of AKFTA. This outcome plays as a reflection only.

5. Conclusion

This paper has been successful to demonstrate the different effects of FTAs on

Vietnam Iron and steel trade flows. Depend upon the RCA, export intensity and import

intensity index, Vietnam are considered to have comparative disadvantage in iron and

steel productivity. The imports of Vietnam are strong with China, Japan and Korea while

for ASEAN nations, the intensity levels are quite less. When FTAs are implemented,

several changes in trade flows of Vietnam iron and steel products are improved. The

import from China has increased sharply over the years after 2006. The export of

Vietnam to Korea rises rapidly after 2010. AFTA are seen to have little impacts on trade

flows of Vietnam when trends are complicated over years. By quantizing statistics

through export and import gravity models, the impacts level of AKFTA, AFTA and

VJEPA are foreseen to force the export iron and steel products of Vietnam to the related

member nations. ACFTA and AJCEP do not have any significant effects on stimulating

the exporting iron and steel. For importing, ACFTA is remarked to force the importing

from China to Vietnam these years. VJEPA is also the FTAs gaining significantly good

impacts on forcing the importing from Japan. AKFTA, AFTA and AJCEP have not

uncovered the clear impact on Vietnam’s imports iron and steel. Vietnam iron and steel

industry should take advantages effectively of some FTAs which have positive effects on

exporting, such as AKFTA and VJEPA.

13

Despite that the research has gained major achievements, there are still some

limitations in the research, which create premise for the later studies. First, the more

observations we have, the better the estimation quality is. In the paper, however, data for

variables in the research are just collected from 2001 to 2012 due to time and budget

constraints. The paper bypasses some typical variables of the gravity model, only

concentrates on FTA membership and additional simple geographical variables like

Distance, Borders, Land locked when examining the influences of them on trade flows.

Thus, to some extent, it does not fully reflect the effects of all factors on Vietnam iron

and steel industry. The author hope that in the latter studies, some other variables like

FDI could be added into the equation to check it out the impact level of this typical

variable on trading flows. Besides, the models in the research have a backward looking

characteristic. It means they are set up to make statements for the previous and present

status of Vietnam iron and steel trade flows. The suggestion for the next period of the

development of Vietnam iron and steel industry is not cultivated.

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