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정책학석사학위논문

An Empirical Analysis of the Relation between Foreign Aid and Foreign Direct Investment:

A Case Study on CLMV Countries

공적개발원조 와 해외직접투자 간의 (ODA) (FDI)

실증분석 국가 사례를 중심으로: CLMV

년 월2016 2

서울대학교 행정대학원

행정학과 정책학전공

고 안 나

- i -

Abstract

An Empirical Analysis of the Relation between Foreign Aid and Foreign Direct Investment:

A Case Study on CLMV Countries

Anna Ko

Graduate School of Public Administration

Master of Public Policy

Seoul National University

Since 1950s, internatonal donors have placed large sums in grants and

loans in developing countries through Offical Development Assistance

(ODA). Due to development of Sustainable Development Goals (SDGs) in

late 2015, international society once again noticed the importance of

international aid for eradication of poverty and any inequalities. It already

has been proven that foreign aid or development assistance facilitates

economic growth in developing nations. Moreover, Foreign Direct Investment

(FDI) has longer been implemented in developing nations long before 1950s

and has been considered as one of the important source for economic

growth of the developing nations.

These two subjects have attracted a number of interests in the literature

on development finance, and as mentioned above, it is proven that both do

have a significant impact on economic growth of developing countries.

- ii -

From the early 2000s, there were some scholars focusing on the

relationship between ODA and FDI, however the results have been

ambiguous or unclear; many of the studies find different answers on

whether the foreign aid has the power to promote the foreign investment in

the recipient countries.

This study aims to examine whether foreign aid or ODA promotes FDI

especially in CLMV countries. In particular, the study will test the

hypothesis that bilateral aid is an effective means to increase FDI flows to

host countries in aggregated and disaggregated sense. In this context, the

study employs panel tobit estimation techniques on the panel data covering

18 donor countries providing aid in CLMV region over the period from

2000 to 2014.

As a result, the study find that ODA has a statistically significant

positive effect on FDI to host countries, in this case, in CLMV region.

Individually, ODA allocated in Vietnam has a positive correlations to its

FDI inflows. It was possible to believe that foreign aid in CLMV countries,

especially in Vietnam, promotes FDI inflows therefore it assists the

economic growth of the host country. In addition, aid for social

infrastructure in CLMV region had a positive impact on FDI inflows of the

countries. However, humanitarian aid and aid for multisector has crowding

out effect on FDI inflows in Myanmar and Vietnam.

Keywords: Official Development Assistance (ODA), foreign aid, Foreign

Direct Investment (FDI), aid effectiveness, economic development, Panel

Tobit analysis

- iii -

Table of Contents

1. Introduction ·········································································································11.1 Research Background and Purpose of Study ·········································11.2 Selection of the Target Countries ····························································31.3 Concept and Definitions ············································································5

1.3.1 Foreign aid and the Official Development Assistance(ODA) ······ 61.3.2 Foreign Direct Investment (FDI) ·····················································7

2. An Overview of CLMV Countries ·································································92.1 Trends of ODA and FDI in Cambodia ················································ 122.2 Trends of ODA and FDI in Lao PDR ················································· 132.3 Major Trends of ODA and FDI in Myanmar ··································· 142.4 Trends of ODA and FDI in Vietnam ··················································· 19

3. Literature Review ····························································································· 223.1 Impacts of ODA to FDI ········································································· 223.2 ODA allocation in Different Sectors and FDI Flow ··························· 25

4. Research Question and Methods ···································································· 294.1 Research Questions and Hypotheses ······················································ 294.2 Research Methods and Design ······························································· 31

4.2.1 Scope of analysis and Identification of Variables ····················· 314.2.2 Research Design and model ··························································· 36

5. Results and Summary of Findings ································································ 395.1 Descriptive Statistics ················································································ 395.2 Panel Tobit Results and Interpretation ·················································· 40

5.2.1. Relation between ODA and FDI flows ······································· 405.2.2 Impacts of Political Factors on FDI ············································· 48

- iv -

6. Implications and Limitations ·········································································· 546.1. Conclusion and Implications ·································································· 546.2. Limitations ································································································ 56

7. Bibliography ····································································································· 58

국 문 초 록 ·········································································································· 67

- v -

List of Tables <Table 1> Political and Economic Indicators of CLMV Countries (2010~2015) ···· 11<Table 2> Receipts for Cambodia ·······································································12<Table 3> Foreign Direct Investment Flows of Cambodia ·····························13<Table 4> Receipts for Lao PDR ·······································································14<Table 5> Foreign Direct Investment Flows of Lao PDR ································14<Table 6> Receipts for Myanmar ········································································17<Table 7> Top 20 Donors of ODA for Myanmar (in Gross Disbursements) 17<Table 8> Foreign Direct Investment Flows of Myanmar ································19<Table 9> Receipts for Vietnam ·········································································21<Table 10> Foreign Direct Investment Flows of Vietnam ································21<Table 11> Description of Variables ···································································34<Table 12> Descriptive Statistics of Variables ·················································39<Table 13> Panel Tobit Analysis Results ·························································51

- 1 -

1. Introduction

1.1 Research Background and Purpose of Study

As of September 2015, the United Nations (UN) announced the

Sustainable Development Goals (SDGs) (UN, 2015), follow-up goals to the

Millenium Development Goals (MDGs); the new and improved 17

sustainable development goals and 169 targets are the action plan for the

international society to work in collaborate partnership.1)

The creation of the SDGs was a new turning point for the international

society where many of international donors were feeling aid fatigue after 15

years of MDGs. In other words, the international society realized the

importance of foreign aid in developing nations once again and there should

be collaborative support for eradication of poverty and any inequalities. In

addition, it reassured that development of developing countries is not

something that an individual country to work on by itself, however such

should be tackled by the society as a whole.

It has been proven that foreign aid facilitates socio-economic growth of

developing countries (Burnside & Dollar, 2000; Easterly, Levine &

Roodman, 2004; Hansen & Tarp, 2001; Rajan & Subramanian, 2005), and

1) SDGs main goal is to end poverty and hunger everywhere; to combat inequalities within and among countries; to build peaceful, just and inclusive societies; to p rotect human rights and promote gender equality and the empowerment of women and girls; and to ensure the lasting protection of the planet and its natural resources. All in all, th rough creating SDGs, the international society is showing effort on creating conditions for sustainable, inclusive and sustained economic growth, shared prosperity and decent work for all, taking into account different levels of national development and capacities (UN, 2015).

- 2 -

due to such facilitating factors, it can be said that it influences the issues

discussed on SDGs such as eradication of poverty and inequalities.

Moreover, other than aid, Foreign Direct Investment (FDI) is also

considered as one of the largest sources of developing countries’ economic

growth (Alfaro, Chanda, Kalemil-Ozcan & Sayek, 2004; Borensztein, De

Gregorio, & Lee, 1998; Utara, 2001; Driffield and Jones, 2013; Dunning,

1994). and its sustainable development. Historically, though controversial,

FDI has been proved that it is a major variable or factor for development

of a nation. For example, flourishing foreign investments in various sectors

or industries will be able facilitate the exports of the developing economies,

which will be the source capital for another investment in different

industries.

Since the 1950s, the international donors has provided large sums in

grants and loans through Official Development Assistance (ODA) in

international aid for developing countries. Foreign Direct Investment (FDI)

have longer been implemented in developing nations long before 1950s. As

mentioned above, these two subjects have attracted a lot of interest in the

literature on development finance, and it has been proven that these do have

a significant impact on economic growth of developing nations or recipient

nations.

Most of the papers concerning foreign aid, focus on the impact of aid

on socio-economic growth; these debate whether aid really improves

development conditions in the recipient countries. Moreover, in case of

foreign investments, most of the papers investigates the determinants of FDI,

what factors actually does attract foreign capital to invest in the host

- 3 -

countries. From 2000s, there were some scholars focusing on the relationship

between ODA and FDI, however the results have been ambiguous or

unclear; many of the studies had different opinions on whether the foreign

aid has the power to promote the foreign investment in the recipient

countries.

These studies usually share different perspectives; that is, the purpose of

providing aid, the donor hopes to ultimately achieve by aid-giving, is

conflicting between altruism and national interest. This paper will assume

that donor countries’ primary purpose in aid policy is best reflected through

its allocation of aid fund. That is, if it is possible to find out specific

pattern of the donor’s aid allocation from this study, then it will be possible

to answer what the goals of its development aid are.

Based on this assumption, the study will focus on examining whether

there is promotion effect of development aid or ODA to foreign investment

flows, especially in CLMV countries. Moreover, the study will investigate

whether ODA allocation in different sectors from donor countries in

recipient countries have a positive impact on FDI inflows in recipient

countries in donor’s perspective in order to find out the possible reasons for

such strong correlation.

1.2 Selection of the Target Countries

In March 2011, Myanmar produced a democratic government led by

newly elected President Thein Sein. The Thein Sein administration enforced

some audacious policy changes such as dialogue with opposition leader

- 4 -

Aung San Suu kyi, abandoning a grossly overvalued exchange rate in favor

of a market determined rate (MGI, 2013). Moreover, in 2015, Myanmar

currently is in the process of democratization, and undergoing more dramatic

changes; Aung San Suu Kyi’s National League for Democracy (NLD) has

won a landslide victory in Myanmar after the general elections. The NLD

now has control of parliament and was able to earn the power to choose

the next president (Korea EXIM Bank, 2015). These dramatic changes drove

a number of visitors seeking to support the transition; Myanmar is often

explained as a donor’s darling in 2010’s among the donor countries,

multilateral agencies and international Non-Governmental Organizations

(NGOs). Many of these organizations as well as the Multi-national

Corporations (MNCs) are competing to give development fund and

investment while implementing numerous development projects/programs in

Myanmar.

Spurred by high growth in the CLMV countries and the liberalization in

Myanmar in 2011, the world is once more recognizing its significance and

as a result many countries are enlarging its aids and investments especially

in social and economic infrastructure sector towards the CLMV countries. In

2015, CLMV countries records 7.12% of growth rate where the BRICs,

another regional economy with large potential, only recorded 3.90%

(Bloomberg, 2014). According to MK news (2015.03.12.), if they maintain

such high investment trend and growth rate, CLMV is expected to grow

bigger than BRICs countries within few years.

Korean government is also noticing its significance in the international

society, as of 2015, it has announced second round of major partner

- 5 -

countries, and theses CLMV countries are all included in it, due to the

Myanmar’s inclusion. Korea is already realizing its economic potentials and

the aid towards these countries are increasing as well as the FDI. Such

trend does not only reflect Korea, other countries, Japan, Australia, the

European Union, and the United States, apparently all the OECD DAC

countries are increasing its aid towards theses countries and the ASEAN

statistics show that they are also increasing its FDI amounts.

As mentioned, CLMV is showing enormous potential and attracting

enormous foreign aid and investments from the international society. and

since it is located and contributing much in the ASEAN region, which is

one of the fast growing economy in the world. Despite its potential, it is

yet developed, so in other words, there is a strong need for development in

social and economic infrastructure and industries. Due to the reasons

mentioned above, CLMV countries are attracting donor countries, including

South Korea, to allocate enormous amount of foreign aid and investment

within the region. By analyzing the relationship between ODA and FDI, this

paper will analyze such status of CLMV countries and investigate whether

the donor countries are allocating its ODA in order to promote FDI for its

national interest. After investigating whether ODA facilitates FDI inflows in

CLMV countries, the paper will also investigate on is there any different

effect on FDI flows in CLMV countries if the aid for different sectors are

different.

1.3 Concept and Definitions

- 6 -

1.3.1 Foreign aid and the Official Development Assistance(ODA)

According to OECD (2003), foreign aid or development assistance refer

to flows which qualify as Official Development Assistance (ODA). In this

context, the study will not differentiate these variables and assume these as

the same. Specifically, at present the club of Western donors organized in

the Development Assistance Committee (DAC) of the OECD, defines official

development aid or Official Development Assistance (ODA) as:

i. provided by official agencies, including state and local governments,

or by their executive agencies; and

ii. each transaction of which:

a) is administered with the promotion of the economic development

and welfare of developing countries as its main objective; and

b) is concessional in character and conveys a grant element of at

least 25 percent (calculated at a rate of discount of 10 percent).”

(OECD, 2015a)

Particularly, ODA flows comprise contributions of donor countries, at

every level, to developing countries, which can be called as bilateral ODA,

and to multilateral institutions. According to OECD (2015c) Credit Reporting

System (hereafter CRS) has classified official aid flows in 10 general sector

codes, each general code with specific sectors codes defined, social

infrastructure and services, economic infrastructure and services, production

sectors, multisector/cross-cutting, commodity aid and general programme

- 7 -

assistance, action relating to debt, humanitarian aid, administrative costs of

donors, refugees in donor countries, un-allocated/undefined.

1.3.2 Foreign Direct Investment (FDI)

FDI is a key element in international economic integration. FDI creates

direct, stable and long-lasting links between economies. It encourages the

transfer of technology between countries, promotes international trade through

access to foreign markets and can be an important vehicle for economic

development.

According to OECD (2001), FDI is defined as investment by a resident

entity in one economy that reflects the objective of obtaining a lasting

interest in an enterprise resident in another economy. The lasting interest

implies the existence of a long-tern relationship between the direct investor

and the enterprise and a significant degree of influence by the direct

investor on the management of the enterprise. The ownership of at least

10% of the voting power, representing the influence by the investor, is the

basic criterion used. Hence, control by the foreign investor (ownership of

more than 50% of the voting power) is not required.

FDI can be divided into two categories: FDI flows and FDI stocks.

First of all, FDI flows, in case of associates and subsidiaries, consist of the

net sales of shares and loans to the parent company plus the parent firm’s

share of the affiliate’s reinvested earnings plus total net intra-company loans

provided by the parent company. For branches, FDI flows consist of the

increase in reinvested plus the net increase in funds received from the

- 8 -

foreign direct investor. Moreover, FDI outflows or negative flows generally

indicate at least one of the components in the above definition is negative

and not offset by positive amounts of the remaining components. Secondly,

FDI stocks in definition, for associate and subsidiary enterprises, it is the

value of the share of their capital and reserves (including retained profits)

attributable to the parent enterprise (this is equal to total assets minus total

liabilities), plus the net indebtedness of the associate or subsidiary to the

parent firm. For branches, it is the value of fixed assets and the value of

current assets and investments, excluding amounts due from the parent, less

liabilities to third parties.

Based on the definition, there are some papers uses FDI stock in order

to investigate foreign aid and FDI relationship (Arazmuradov, 2015; Kang,

Lee & Park, 2011). However, in this paper, employing from Kimura &Todo

(2010) and Yasin (2005), FDI is referred only to FDI flows within the

recipient countries, in this case, the CLMV countries.

- 9 -

2. An Overview of CLMV Countries

Cambodia, Lao PDR, Myanmar and Vietnam is known as the CLMV

countries or economic bloc; it is located within the Southeast Asian region

or Association of Southeast Asian Nations (ASEAN).2)

CLMV countries, Cambodia, Lao PDR, Myanmar and Vietnam, are the

newest member in ASEAN region. They are also the region’s least

developed; CLMV countries joined ASEAN between 1995 and 1999

compared with 1967 for the original signatories; as of 2014, per capita

income is $ 1,410 on average in these countries, compared with $19,550 for

other members (World Bank. 2015a).

Compared to the original ASEAN members, CLMV countries still need

more physical and institutional infrastructure needs to be built, which

presents a much larger work program to complete for seamless integration.

A spring board for CLMV countries is the integration process itself,

including intra-ASEAN investment inflows and technical assistance. As

CLMV members benefit from an accelerated development process, ASEAN-6

investors are well placed to capital on the rewards from CLMV’s dynamic

growth. <Table 1> below gives a brief economic introduction on CLMV

2) As of 2014, ASEAN countries have a combined GDP of $2.4 trillion, rivaling the size of some of the largest economies such a the United Kingdom at $2.5 t rillion. Recently, ASEAN has set 31st of December in 2015 as its target date for regional economic integration, including single market and production base with the free movement of goods, services, investment and skilled labor and freer flow of capital (Bloomberg, 2014). Such progressiv eeconomic opening and integration in the ASEAN market p rovides CLMV countries with opportunities to benefit from the comparative advances associated with their relatively low labor costs and energy wealth. ASEAN integration will also help the countries to start tapping global markets.

- 10 -

countries.

CLMV countries have been experiencing high growth rates in the 2000s,

with annual average GDP growth of 8% (OECD, 2015b), there countries are

projected to continue growing at a robust pace over the medium term, for

example, Lao PDR at 7.6% per annum, Cambodia at 7.1% and Myanmar at

7.8% per annum during 2015-2019 (World Bank, 2015a; OECD, 2015b).

Furthermore, driven by continued intra-regional restructuring in

manufacturing, Cambodia and Myanmar are attractive FDI locations for

labor-intensive manufacturing, and Lao PDR is more specialized in its

bountiful natural resources. (UNCTAD, 2013) In other words, CLMV

countries, due to its resources and economic potential described below, are

receiving large amounts of ODA and foreign investments from the

international society. Japan, Australia, Korea and China in bilateral donors,

and ADB and World Bank in multilateral donors are believed to be the top

donors of CLMV countries (OECD, 2015b; Hao, 2008; O'neill, D., 2014;

Devadason, 2010). However, in this study, China will not be discussed due

to its lacking data and information on China-CLMV relationship.

As for the following sub-sections of this part of the study will each

introduce the current trend of CLMV countries especially in terms of foreign

aid and investments.

- 11 -

Coun

tryGovern

men

t Typ

eTim

eGD

P (U

SD M

illion)

GD

P gro

wth

(%

)

GD

P per

capita

(USD)

Net O

DA

received

(USD M

illion)

Population

CPI

(2010

=100)

Cam

bodia

Multi-p

artydem

ocracy

under a

constitu

tional

monarch

y

2010

11,24

2.28

5.96

782.6

9 103

2.79

14,363,5

86 100.0

0 20

1112,82

9.54

7.07

879.1

5 815.2

7 14,5

93,099

105.4

8 20

1214,05

4.44

7.31

947.5

6 789.5

2 14,8

32,255

108.5

7 20

1315,22

7.99

7.36

1009.91

118

0.19

15,078,5

64 111.7

7 20

1416,70

9.43

7.03

1090.12

.

15,328,1

36 116.0

8

Lao PD

RCom

mun

ist state

2010

7,181.4

4 8.53

1147.10

595.2

9 6,260

,544

100.0

0 20

118,28

3.22

8.04

1300.98

591.1

1 6,366

,909

107.5

8 20

129,35

9.19

8.02

1445.87

581.0

6 6,473

,050

112.1

6 20

1311,18

9.51

8.52

1700.54

572.2

5 6,579

,985

119.3

0 20

1411,77

1.73

7.46

1759.78

.

6,689

,300

124.2

3

Myan

mar

Parliam

entary

govern

men

t (fro

m 20

11)

2010

..

.346.8

2 51,7

33,013

100.0

0 20

11.

..

350.6

6 52,1

25,411

105.0

2 20

1274,69

0.93

.142

1.50

763.0

5 52,5

43,841

106.5

6 20

1358,65

2.24

8.24

1106.98

785

0.12

52,983,8

29 112.4

5 20

1464,33

0.04

8.50

1203.84

.

53,437,1

59 118.6

1

Vietna

mCom

mun

ist state

2010

115,9

31.75 6.42

1333.58

402

8.11

86,932,5

00 100.0

0 20

11135,5

39.49 6.24

1543.03

639

3.49

87,840,0

00 118.6

8 20

12155,8

20.00 5.25

1755.27

501

5.33

88,772,9

00 129.4

7 20

13171,2

22.03 5.42

1908.64

642

7.09

89,708,9

00 138.0

1 20

14186,2

04.65 5.98

2052.29

.

90,730,0

00 143.6

4 Sou

rce: World

Bank,20

15a; CIA

World

Factbook,201

5; OEC

D Sta

tistics, 2015.

<Tab

le 1> P

olitical an

d Econ

omic Ind

icators of CLM

V C

ountries (2010~

2015)

- 12 -

2.1 Trends of ODA and FDI in Cambodia

According to <Table 1>, the Cambodian economy grew at 7.5% in

2013 aided by rapid expansion in exports and growth in supply from the

service sector. High GDP growth rate is expected to continue in 2014

despite labor unrest and uncertainty stemming from wage negotiations in the

garment industry, the main driver of recent economic growth. The garment

industry contributes around 80% of the country’s of the county’s exports

and is Cambodia’s main source of foreign currency, in other words, the

industry will mainly responsible for Cambodia’s FDI. The government’s

ability to solve the issues underlying labor unrest in the garment industry is

thus crucial for the economy since the uncertainty threatens the industry’s

growth potential and investor’s confidence.

Cambodia is receiving increasing amount of aid, although it is small

compared to Myanmar and Vietnam, it has received 804.8 USD Million

development assistance from international society in 2014. Its top donor is

Japan by providing 164.1 USD Million in 2012-2013 average, ADB,

Australia, United States and Korea are the following top donors.

During the period between 2012 and 2013, on average (OECD, 2013),

the most largely received bilateral ODA by sector for Cambodia is Action

relating to Debt (34%), and Japan’s help on this sector has been very

significant on this phenomenon (OECD, 2015b). Economic infrastructure and

services, health and population sector has ranked second (19%) and third

(17%) in terms of bilateral ODA.

- 13 -

2.2 Trends of ODA and FDI in Lao PDR

Growth in Lao PDR’s economy increased to 8.0%, as shown in <Table

1>, in 2013 from 7.9% in 2012. However, rising inflation due to generous

monetary policy and a widened fiscal deficit will hamper economic growth

in the medium term. Despite the modest slowdown, Lao PDR still has one

of the highest growth rates in the region. The country’s growth is mainly

supported by the resource sector, hydropower industry (a major recipient of

FDI), and massive road and railway infrastructure projects. The mining and

hydro-power sectors’ contribution to the economy, however appears to be

vulnerable to lower output growth. The cancellation and suspension of some

investment projects (OECD, 2015b), including a hydropower dam project and

some infrastructure loans from China might also lead to some slowing in

the currency growth.

As shown in <Table 4>, Lao PDR is receiving increasing amount of

Cambodia 2011 2012 2013Net ODA (USD Million) 790.9 807.4 804.8

Gross ODA (USD Million) 873.8 860.2 869.4Bilateral Share (Gross ODA, %) 62.4 74.8 63.6

Total Net Recipients (USD Million) 932.4 1,117.1 1,199.6

Source: OECD Statistics, 2015.

<Table 2> Receipts for Cambodia

2010 2011 2012 2013 2014Inward 1342.16 1372.47 1835.22 1871.72 1730.35

Outward 20.58 29.16 36.18 46.25 31.92Source: UNCTAD Statistics, 2015

<Table 3> Foreign Direct Investment Flows of Cambodia

(USD Million)

- 14 -

aid from 2011; its top donor is Japan with 86.51 USD Millions of

development assistance. ADB, World Bank, Australia, Germany and Korea

has been ranked respectfully (OECD, 2013). In 2013, Lao PDR is receiving

fairly balanced ODA in different sectors, where economic infrastructure and

services sector is ranked first with 24.24 USD Millions (27%), Other social

infrastructure and services at second with 20.12 USD Millions (20%) of

total bilateral ODA received in Lao PDR.

2.3 Major Trends of ODA and FDI in Myanmar

From early 2000s, Myanmar was severely sanctioned from the

international society. Most of the economic sanctions in Myanmar was

primarily imposed from the United States government. Moreover, the

European countries including the United Kingdom, France and Germany and

the other international known donors have imposed similar type of economic

Lao PDR 2011 2012 2013Net ODA (USD Million) 392.5 408.9 421.0

Gross ODA (USD Million) 466.9 486.3 498.3Bilateral Share (Gross ODA, %) 61.2 62.5 62.3

Total Net Recipients (USD Million) 413.5 801.4 473.5

Source: OECD Statistics., 2015.

<Table 4> Receipts for Lao PDR

2010 2011 2012 2013 2014Inward 278.80 300.75 294.38 426.67 720.84

Outward -0.57 0.86 -0.08 -43.71 1.97Source: UNCTAD Statistics, 2015

<Table 5> Foreign Direct Investment Flows of Lao PDR(USD Million)

- 15 -

sanctions as the U.S. Myanmar was imposed of the most severe type of

economic sanction both in 2003 by the U.S. government due to Myanmar’s

then ruling-military junta and its large-scale repression of the democratic

opposition, Burmese Freedom and Democracy Act of 2003 (Public Law 108-

61, 50 U.S.C. 1701 note) (BFDA) (OFAC, 2015). BFDA includes its ban

on the importation of Myanmar products into the United States, and for the

additional steps, it also blocks all property and interests in property of

known or related personnels of then ruling military government.

Additionally, it prohibits the exportation or reexportation, directly or

indirectly, to Burma of financial services from the United States or by a

U.S. person, wherever located (OFAC, 2015; KIEP, 2012). Others, including

the members of European Union and Australia, also have imposed sanctions

toward Myanmar and followed the trends of U.S. government in terms of

its severity. The U.S. government continually imposed of sanctions in 2007

and 2008 in order to enlarge the scope of economic sanctions, until the

Obama administration lifted up the imposed sanctions from Myanmar

(OFAC, 2015). Other international donors also have mostly lifted up its

economic sanctions toward Myanmar in 2013. In other words, from 2012,

Myanmar was out of its isolation and was on the right track for its

socio-economic development by receiving ODA and foreign investments from

the international society (KIEP, 2012).

As of 2013, Myanmar received total of 7,640 USD million and become

the second largest ODA receiving recipient country3) from the OECD DAC

3) Top ten recipient countries are, respectfully: Afghanistan, Myanmar, Vietnam, India, Indonesia, Kenya, Tanzania,Côte d'Ivoire, Ethiopia, Pakistan.

- 16 -

member countries (OECD, 2013).

After the political transition in 2011, Myanmar government has closely

related to official aid flows; Myanmar government is efficiently managing

and coordinating flourishing development aid from the international society.

Under the Myanmar National Planning Economic Development (MNPED),

Foreign Economic Relations Department (FERD) has been managing the

foreign aid through establishing:

1. Overall coordination mechanism

2. Sector Working Group

3. Aid Information Management System (AIMS)4)

Japan, Germany, EU, Korea and USAID are the top donors in Myanmar

in terms of bilateral aid, moreover the World Bank, Asian Development

Bank (ADB) are the top donors in terms of multilateral aid (Mohinga,

2015). According to Wah Wah Maung (2015), major trends of East Asian

countries including Japan, China and Korea is to allocate aids in the sectors

of infrastructure and industrial development while that of Western countries

and the multilateral organizations (i.e. the World Bank, European Union) is

focused on giving aid on human capital development sectors such as

education and health. Moreover, nowadays, in Myanmar, many of the aid

programs and projects from international donors are concerting community

development or rural development project, for example, Korea’s Saemaeul

4) Myanmar government has created Aid Informationa Managemnt System (AIMS), also known as Mohinga System, in order to efficiently manage and coordinate the aid projects. It has been implemented from Feburary 2015 after the 1st Myanmar Development Cooperation Forum(MDCF) in Nay Pyi Taw, with technical assistance from European Union. As o f Feburary 2015, 80% of aid p rojects in Myanmar has been registered in the Mohinga System.

- 17 -

Undong Projects.

Furthermore, other than aid, Myanmar is attracting significant amount of

foreign investments due to its abundant low-waged labor, natural resources

Myanmar 2011 2012 2013Net ODA (USD Million) 374.3 504.0 3,934.8

Gross ODA (USD Million) 402.3 528.5 7,640.0Bilateral Share (Gross ODA, %) 73.8 68.8 85.1

Total Net Recipients (USD Million) 870.6 828.7 4,700.2

Source: OECD Statistics, 2015.

<Table 6> Receipts for Myanmar

2013 Ranking

Donor 2011 2012 2013

1 Japan 42.50 92.78 5331.762 France 5.91 7.31 592.263 ADB .. .. 513.134 WB(IDA) .. .. 421.035 UK 62.21 48.07 156.186 USA 30.80 33.32 80.667 Global Fund 7.69 59.97 79.288 Denmark 11.29 20.23 75.969 European Union 48.25 46.41 71.5210 Austrailia 44.37 57.73 70.0111 Austria 0.05 0.06 34.9212 Norway 19.90 22.83 31.9213 Sweden 18.97 19.79 28.1714 Switzerland 11.37 12.22 21.6815 Germany 10.73 12.52 17.8816 Korea 7.86 9.04 14.8017 UNICEF 15.37 16.48 14.7418 UNFPA 5.60 5.77 10.4919 Italy 3.22 1.54 9.0320 GAVI 5.37 21.10 9.01

Source: OECD Statistics. 2015.

<Table 7> Top 20 Donors of ODA for Myanmar (in Gross Disbursements)

(USD Million)

- 18 -

and its geographic background in the heart of the world’s fastest-growing

region. It is home to 60 million inhabitants with 46 million of working age,

and its natural resource possesses a market of half a billion people (since it

is neighboring with Thailand, India, Bangladesh, China and Lao PDR).

The Myanmar economy grew at 7.5% in 2013 and is expected to grow

even faster in 2015, benefitting from an improved investment climate

(OECD, 2015b). The high growth is driven by private investment notably

externally financed large projects, which are also boosting commodity

exports. Myanmar’s economic growth has been strongly supported by foreign

investment inflows. According to <Table 4>, FDI inflows to Myanmar

increased by about 60% in 2014 over 2013. Energy and infrastructure are

the main industries receiving large foreign investment. The recent

liberalization of the telecommunications sector has also helped to attract

foreign investment into the country. The central Bank of Myanmar recently

announced that the country has taken steps to open its banking sector to

foreign participation for the first time in nearly 50 years: nine foreign banks

have been given licenses to operate in Myanmar (OECD, 2015b). Although

they still provide limited services due to remaining restrictions, foreign

banks will benefit foreign investors in Myanmar, Exports of natural

resources, such as natural gas and mining products, will also support

Myanmar’s accelerating growth.

Despite the increasing numbers of foreign investment, Myanmar is

currently in the process of transition and facing challenges. For instance, it

possesses political (Presidential election in 2016) and socio-economic risks

(lacking banking and financial system); these are one of the major business

- 19 -

risks for foreign private companies.

2.4 Trends of ODA and FDI in Vietnam

In the CLMV region, Vietnam can be regarded as a development

success story. Political and economic reforms launched in 1986 have

transformed country from one of the poorest in the world, with per capital

income around $100 to lower middle income country within about 20 years

with per capita income of over $2,000 by the end of 2014; such economic

development has also led to eradication of absolute poverty (World Bank,

2015b). According to a recent paper published from UNDP (2015), the

country has completed a number of MDGs and targets such as eradication

of extreme poverty, achieving universal primary education, promoting gender

equality in education.

Currently, through the Socio-Economic Development Strategy

(2011-2020), Vietnam is focusing on the structural reforms in social and

business environments, environment substantiality, social equity and emerging

issues of macro economic stability (OECD, 2015b). Also, it emphasizes

development through upgrading and improvements in efficiency and

2010 2011 2012 2013 2014Inward 6669.40 1117.68 496.87 584.29 946.22

Outward . . . . .Source: UNCTAD Statistics, 2015

<Table 8> Foreign Direct Investment Flows of Myanmar(USD Million)

- 20 -

competitiveness through targets for overall and sectorial economic

performance, social targets (for example, regarding job creation and poverty

reduction) and the implementation of environmental protections (OECD,

2015b). GDP growth has been lower than targeted, but other economic

targets, such as those regarding unemployment and social investment, are

near or above target levels. Insufficient progress is being made by current

approaches to a wide range of social challenges, such as alleviating rural

poverty and expanding access to technical training and education. The need

for improved banking governance amid rising levels of bad debt is another

serious challenge that needs to be addressed to support continued

development.

Compared to CLM countries, Vietnam has receiving larger volume of

aid and FDI from 2000s. The majority of FDI into Vietnam comes from

Asian countries. The top three countries are Japan followed by Singapore

and South Korea. (IFLR, 2014) The FDI are usually in Manufacturing

sector, however due to the fact that many of Vietnam workers are educated

and the wage of these people have been increasing since 2000s, nowadays

some of international private capital flows are changing its directions to

CLM countries, yet its FDI ranks the highest in the CLMV region.

Though Vietnam has received ODA since the 1960s; it was only after

the introduction of Doi Moi in 1986 and the 1993 Paris Round Table

Conference that large scale non-political bilateral and multilateral aid became

significant (McCarthy, 2009). Currently, as of 2013, it is receiving 4,084.8

USD Million from international donors; aid volume in country is showing a

little decrease from 2012. Such phenomenon can be due to emergence of

- 21 -

Myanmar and other emerging economies in ASEAN region. Japan is again

ranked as its top donor in 2012-2013, World Bank, ADB and Korea, France

respectively ranked from second to fifth. In terms of sector, bilateral ODA

allocated in Vietnam are mostly for economic infrastructure and services

(50%), other social infrastructure and services (14%) and Multisector (12%).

Vietnam 2011 2012 2013Net ODA (USD Million) 3,595.5 4,115.8 4,084.8

Gross ODA (USD Million) 4,270.0 4,789.9 4,757.6Bilateral Share (Gross ODA, %) 59.4 65.9 60.5

Total Net Recipients (USD Million) 8,360.2 9,533.2 13,751.8Source: OECD Statistics. 2015.

<Table 9> Receipts for Vietnam

2010 2011 2012 2013 2014Inward 8,000.00 7,519.00 8,368.00 8,900.00 9,200.00

Outward 900.00 950.00 1,200.00 1,956.00 1,150.00Source: UNCTAD Statistics, 2015

<Table 10> Foreign Direct Investment Flows of Vietnam(USD Million)

- 22 -

3. Literature Review

This paper investigates the relationship between foreign aid and FDI in

aggregated and disaggregated context. In general, many of the scholars have

attempted to figure out the relationship between them however the results

were quite ambiguous. In this context, the aim of the literature review will

be explained in twofold; the first part is to investigate the link between the

ODA and FDI, in aggregated sense, to see whether foreign aid has

promoting impact in foreign investment flows. The second part is to

specifically see the aid allocation in different sectors have different effects

to foreign investment or FDI. In other words, the paper will focus on

disaggregated literatures or past studies done by different scholars explaining

on sectorial analysis of foreign aid to foreign investments.

3.1 Impacts of ODA to FDI

Like mentioned in introduction, there are a few literatures that argue on

the impacts of foreign aid to recipient countries. For example, impacts of

foreign aid to recipient countries such as Least Developed Countries (LDCs)

particularly those on its economic growth have been examined to great

extent (Burnside & Dollar, 2000; Easterly, Levine & Roodman, 2004;

Hansen & Tarp, 2001; Rajan & Subramanian, 2005).

Furthermore, there are a few studies on understanding the relationship

between foreign aid and foreign investment (Alesina & Dollar, 2000; OECD,

2004; Arase, 1994; Harms and Lutz, 2006; Yasin, 2005; Kimura & Todo,

- 23 -

2010; Blaise, 2005; Park, 2014). Regarding the subject, the US government

asserts that a purpose of giving aid to developing nations is to encourage

FDI (Congress of United States, 1997), and OECD (2004) argues that

foreign aid can improve investment environment of a country and thus

promote FDI. The Japanese government also argues that a reciprocal relation

between FDI and aid helps the development in developing countries (Arase,

1994). OECD (2006) again confirms that the role of aid in promoting FDI

has come to the fore in the policy discussion among government officials

and development practitioners.

Scholars have used various models or channels to prove the relationship

between ODA and FDI, but most of the studies apply aggregate aid data of

donor countries to recipient countries, such as Papanek (1973) finds a

statistically insignificant correlation between aid and FDI across countries in

the 1950s and 1960s and he argued, by using regression model, the

collected “data contradicts aid is biased in favour of the countries which are

hospitable to (and often exploited by) the private investors of aid donor

countries (Papanek, 1973: 123)”.

Along with Papanek (1973), Berthlemy and Tichit (2004) also argues

there is a positive relationship between ODA and FDI. The authors regarded

the higher ratio of FDI inflows to GDP as an index of “good economic

policies,” and presents some evidence that three is a high correlation

between the donors grant more aid to host countries of FDI. Blaise (2005)

with aggregated data, used conditional logit analysis to investigate the

effectiveness of Japan’s ODA in promoting FDI flows in the case of the

People’s Republic of China. Japanese aid flows did show significantly

- 24 -

positive impact on private investors location choice even though other

profit-maximizing factors like the level of economic activity had a leading

spillover effect. According to Yasin (2005), asserts bilateral ODA has a

significant and positive influence on foreign investment flows as well as

trade oneness, growth rate in the labor force and exchange rates have a

positive and significant effect on FDI flows. Moreover, Karakaplan &

Neyapti (2005), by using aggregated data on FDI and foreign aid, argues

that good governance and developed financial markets will lead to positive

effects of aid. In other words, the authors empirically investigated the effect

of aid on foreign direct investment in a view of hypothesis that receiving

aid also becomes more likely to receive FDI and concluded that the

countries that receive aid also become more likely to receive FDI, but this

happens especially in case of good governance and financial market

development.

In contrast to Yasin (2005) and Karakaplan et al (2005), there are some

studies with aggregated data arguing for negative correlations between

foreign aid and FDI: Asiedu et al. (2009) find out foreign aid mitigates the

risk of FDI in the receiving countries, which includes the violation on

contractual agreements, changes in laws and regulations or the right out

nationalization of foreign owned property can be mitigated by receiving –

foreign aid that could be either from the countries that owned FDI or other

donors. Harms and Lutz (2006) used aggregated aid data for 92 developing

host countries from 1988 to 1999. and find that the effect of aid on FDI is

generally insignificant but significantly positive for countries in which private

agents face substantial regulatory burdens (Harms and Lutz 2006: 780). In

- 25 -

addition, Kosak and Tobin (2006) found that aid and FDI are unrelated in

world’s poorer countries, and further emphasized that foreign aid in

developing countries are mainly in the form of supporting government

budget, humanitarian activities and human capital development. Alesina &

Dollar (2000) also argued that aid does not significantly increase investment

and growth but increase the size of government. Thangamani et al. (2011)

uses Kasuga (2007)’s argument to find the relative impact of financial

source such as foreign direct investment, aid, and savings are depends on

countries’ income level, financial structure, and government infrastructure.

According to Caselli et al. (2007) the marginal product of capital is roughly

same across countries, and increasing aid to developing countries will lower

the marginal product of capital in these countries; in other words, aid and

FDI to be substitute rather than being complements.

3.2 ODA allocation in Different Sectors and FDI Flow

Studies on the relationship between ODA sector allocation to recipient

countries and FDI are still lacking. There were some studies attempted to

use disaggregated data, such as Kimura & Todo (2010) distinguish between

five major donors and separate 'aid for infrastructure' from other aid (mainly

budget support, debt relief, and humanitarian aid); the authors employed a

large data of donor-recipient country pairs and conduct gravity equation

estimation in order to examine the effect through which aid from a donor

country promotes FDI from the same donor in particular, a vanguard effect.

- 26 -

In this context, there are also a number of studies presents positive

effect from ODA to FDI, Kang, Lee & Park (2010) analyzed in twofold,

macro and micro-level, to investigate the similarity or any resemblance of

Korea and Japan’s ODA practices. The authors argued that Korea’s current

foreign aid practices have strong resemblances to Japan’s ODA practices of

the 1980s in macro-level as shown in the aid distribution by type, region,

income and sector. By employing gravity model and panel GMM estimation,

aids from Korea and Japan particularly create more FDI inflow into their

respective recipient developing countries.

Both studies (Kimura et al., 2010; and Kang et al., 2010) employed

such model from the recent studies on determinants of FDI (Egger and

Winner, 2006; Africano & Magalhães, 2005), finds no infrastructure effect,

no negative rent-seeking effect but a positive vanguard effect. In this case,

the authors have argued that particularly Japan’s aid is a vanguard of FDI;

vanguard effect arises when foreign aid from a particular donor country

promotes FDI from the same country but not from other countries. Park

(2014) also used both fixed-effected model and random-effected model based

on panel data for countries to find out ODA variables have an impact on

FDI along with other economic (i.e. deregulation policies toward private

companies, GDP) and political factor (i.e. bilateral economic agreements,

governance) of Korea’s aid activity. In addition, Park (2014) also presented

positive results; ODA flows of the Korean government has a vanguard

effect of private investments of Korean companies towards ODA recipient

countries. Moreover, Arazmuradov (2015) uses both fixed and random-effect

panel model to figure out that aid had a moderate complementary effect on

- 27 -

FDI inflow; there was a crowding out effect such that domestic investment

reduced FDI stocks, natural resources were a key attraction for private

capital, and increases in development aid offset the crowding out effect of

domestic capital on FDI. Kapfer et al. (2007) focus on aid for economic

infrastructure (communication, transportation, energy), which they find to

have a significant effect on FDI. Mayer's (2006: 34) analysis of dyadic aid

and FDI patterns suggests, however, that the "very strong effect [of aid for

infrastructure] seems entirely caused by the cross-sectional variation in the

data" and largely disappears once country-pair fixed effects are included.

Donaubauer, Herzer & Nunnenkamp (2012) also studies with disaggregated

data, more specifically than Mayer’s, investigates aid for education is an

effective means to increase FDI flows to host countries in Latin America

where schooling and education appears to be inadequate from the viewpoint

of foreign investors. As a result, the authors confirm that aid for education

does induce high FDI inflows in host countries. Lastly, Thangamani, Xu and

Zhong (2010) also investigates the relationship between foreign aid in

physical capital development and human capital and infrastructure

development and FDI in South Asian countries. With various analysis,

e.g.fixed effects method, panel instrumental variable method, foreign aid in

physical and human capital sector or forms serves as complementary factors,

or positive impacts on either variables to foreign investment in South Asian

Economies.

On the other hand, the studies reveals negative or crowding-out effect

exists between ODA and FDI flows: according to Selaya and Sunesen

(2012) refine major aid categories to argue that aid may raise the marginal

- 28 -

productivity of capital by financing complementary inputs, such as public

infrastructure projects and human capital investment, on the other hand

crowds out productive of private investments if it comes in the shape of

FDI inflows. Specifically the authors used disaggregated data, projects related

to social and economic infrastructure are assumed to attract FDI by

improving the supply of complementary factors of production, however, aid

is supposed to crowd out FDI when granted as "pure physical capital

transfers" (Selaya and Sunesen 2012: 2155). The empirical analysis reveals

the expected opposing effects of both types of aid on FDI, even though the

categorization of aid is still fairly broad and not related to specific 'needs'

or bottlenecks to FDI in the recipient countries.

In this context, by using both aggregated and disaggregated data, the

literature review seems to indicate that there are two distinct possibilities

regarding the impact of ODA (or aid for sectors) on FDI;

(1) a positive effect, or both are complementary factors, that is more

significant in bilateral ODA allocated to infrastructures and that

could be intentional i.e. vanguard effect suggested by Kimura and

Todo (2007),

(2) a negative substitution effect created by the crowding out of

private investment (for example, tied aid flows)

- 29 -

4. Research Question and Methods

4.1 Research Questions and Hypotheses

Research questions in this study included the following:

RQ 1: Does Official Development Assistance (ODA) from donor

countries promotes private capital flow, especially the Foreign Direct

Investment (FDI) in the recipient countries?

RQ 2: Does ODA allocated to different sectors show different effects on

the recipient countries’ private capital inflow?

Specific hypotheses addressed by this study include the following:

For the first research question, the hypotheses are written below.

H0: ODA from donor countries promotes FDI flows in the recipient

countries.

H1: ODA from donor countries does not have significant impact on

recipient countries’ foreign investment flow.

For the second research question, in order to investigate the reasons for

promoting effects of ODA to foreign investment flows in recipient countries,

this paper aim to any positive relationship between the ODA allocation in

different sectors- such as social infrastructure development, economic

infrastructure development, humanitarian aid, debt relief, and

multisector/cross-sectional- and FDI flows in the recipient countries.

- 30 -

These sectors are selected because both social and economic

infrastructure development includes the most important sectors for a country

to develop, such as education, health, water and sanitation, government and

civil society, transportation and storage, communications, energy generation,

distribution, banking and financial services (OECD, 2015a) and these were

one of the major receipts of CLMV countries as mentioned above.

Action relating to debt sector includes Debt forgiveness, relief of

multilateral debt, rescheduling and refinancing sectors, and for Myanmar, the

sector ranked the top receipts for the country, and other CLV countries, it

was one of the big sources of official development aid as well.

Humanitarian aid, which consists of emergency response, reconstruction

relief and rehabilitation, was selected in order to find out the donor

countries’ motivation of ODA. Humanitarian aid is generally allocated for

emergencies of countries such as economic, social, humanitarian problems or

disasters.

Lastly, Multisector/cross-cutting sector was selected, since it is a

emerging source of ODA from donor countries in developing nations; OECD

DAC countries in have been allocating aid in the sector, which has been

increasing from 2000 (5.36 USD Million) to 2013 (10.34 USD Milions),

with a slight decreasing from 2010 to 2012, however (OECD, 2015b). This

is because the sector consists general environmental protection and other

multisector (i.e., urban development and management, rural development,

non-agricultural alternative development, multisector education/training,

research and scientific institution). (OECD, 2015; OECD, 2015b)

H3: ODA allocated to social infrastructure and services sector has

- 31 -

positive effect on FDI in recipient countries.

H4: ODA allocated to economic infrastructure and services sector has

positive effect on FDI in recipient countries.

H5: Humanitarian aid from donor countries has positive effect on FDI

in recipient countries.

H6: ODA allocated to action relating to debt sector has positive effect

on FDI in recipient countries.

H7: ODA allocated to multisector/cross-cutting has positive effect on

FDI in recipient countries.

4.2 Research Methods and Design

4.2.1 Scope of analysis and Identification of Variables

The data in this study covers four recipient countries, Cambodia, Lao

PDR, Myanmar and Vietnam, as known as CLMV countries, from 2000 to

2014. As mentioned above, these CLMV countries are receiving increasing

amount of ODA and foreign investments due to its economic potential,

improvements in business environments (e.g. infrastructure and industry

projects from ODA and FDI volume) and socio-economic development.

As for the donor countries, the research will focus on the OECD DAC

countries that have been allocating ODA and directly invested to CLMV

countries (Cambodia, Lao PDR, Myanmar and Vietnam) from 2000 to 2014.

These countries are: Australia, Austria, Belgium, Canada, Czech Republic,

Denmark, Finland, France, Germany, Japan, Korea, Luxemburg, Netherlands,

- 32 -

Norway, New Zealand, Sweden, United Kingdom, United States.5)

1) Dependent Variables

The dependent variable in this study is the annual bilateral foreign

direct investment flows from aforementioned donor countries to CLMV

countries during the period from 2000 to 2014. There will be total of five

dependent variables in total; aggregated amount of bilateral FDI from donor

countries to CLMV countries, !"#$%& , and separate bilateral FDI from

donor countries to each CLMV countries, "#$%&.

The FDI data were collected from the ASEAN statistics, where it

collects its data from each member countries statistics department, and

UNCTAD bilateral FDI data.

2) Independent Variables

The independent variable in this study will be described focusing on the

variables based on characteristics of individual countries to be analyzed. The

independent variables were analyzed separately into three categories: bilateral

ODA from donor countries to CLMV countries, the ratio of bilateral aid for

five sectors selected before, and political factors.

To begin with, for the relevance of bilateral ODA and FDI, the main

5) Greece, Iceland, Ireland, Italy, Poland, Portugal, Slovak Republic, Slovenia, Spain, Switzerland were exemted from the study, since these countries either allocate low amount of ODA or invest low amoung of FDI towards CLMV countries. By

- 33 -

independent variable in this study, bilateral ODA or development aid is the

net actually provided (not just committed, i.e. allocated but not yet

transferred to the recipient country) by aforementioned DAC member

countries. For the first part of the question, it is the sum of grants, loans,

technical assistance and all of the aid allocated in various sectors; same

with the dependent variable, there will be five variables, aggregated bilateral

ODA flows in the CLMV region as a whole and each individual CLMV

countries (Cambodia, Lao PDR, Myanmar and Vietnam).

As for the aid for five different sectors, which is another main

independent variable in this part of the study will be the ratio of bilateral

aid for each sectors, identified earlier in the paper: social infrastructure and

services, economic infrastructure and services, action related to debt,

humanitarian aid. These variables on each sectors will also be again

categorized for the CLMV region, and each individual country. The bilateral

ODA data on each sectors were gathered from OECD Credit Reporting

System period from 2000 to 2014.

In addition, for the relationship between political factor and FDI are

also examined in the study. Political factors such as the degree of risk of

forfeiture, political stability of the recipient or host country, political

freedom, the degree of democracy are already proved in the past literature

that it has positive relationships with FDI flows in recipient countries

(Karakaplan et al. 2005; Park, 2014; Mallaye & Yogo, 2011). This study

will be discussing on the basis of the countries that have signed political

treaty or agreement. Park (2014) has considered similar variable, he has

categorized the political factor in four categorical (dummy) variables, to find

- 34 -

any positive relationship between FDI expansion of Korean government. In

this context, this paper will be using two categorical variables (0-1) to look

if there is a positive effect from the bilateral treaty or Free Trade

Agreement (FTA) between donor countries and CLMV countries, since FTA

is the most effective way for contracting countries to have trade

liberalization, which will definitely impact foreign investments within the

host countries (KIET, 2011). Moreover, CLMV is one of the economic bloc

of Association of South East Asian Nations(ASEAN), this study has

regarded ASEAN FTA with aforementioned DAC countries also as a

political agreement between the countries.

The following <Table 11> summarizes the variables used in the

analysis.

- 35 -

Name Variable Description Source

Dependent Variable

FDI flow "#$%& FDI flow from country j to iASEAN

Statistics, UNCTAD

Independent Variables

Bilateral ODA flows

'()%& Bilateral ODA from country j to iOECD CRS

Bilateral ODA for social

infrastructure*'%+,-%&

Ratio of ODA allocated in Social Infrastructure and Services sector over Bilateral ODA from country j

to i

OECD CRS

Bilateral ODA for economic

infrastructure.%+,-%&

Ratio of ODA allocated in Economic Infrastructure and Services sector over bilateral

ODA from country j to i

OECD CRS

Bilateral ODA for Humanitarian aid

/0)%(-%&Ratio of Humanitarian Aid over

bilateral ODA from country j to iOECD CRS

Bilateral ODA for debt relief

(-%&

Ratio of ODA allocated in Action related to Debt sector over

bilateral ODA from country j to i

OECD CRS

Bilateral ODA for Multisector

102-%&Ratio of ODA allocated in

Multisector over bilateral ODA from country j to i

OECD CRS

Bilateral FTA 3%,4)%&Bilateral FTA signed with country

i and jASEAN

Statistics

Exports of donor countries

exp'-4*&Exports of goods and services (%

of GDP) World Bank

ODA per Capita '()8.-&ODA per capita of donor

countries OECD CRS

<Table 11> Description of Variables

- 36 -

4.2.2 Research Design and model

As mentioned above, the overall objective of this study is to investigate

the bilateral ODA from donor countries to recipient countries have a

significant and promoting effect on FDI flows. As shown in the literature

review, it is possible to see that there are possibly multiple channels to

investigate whether foreign aid affects FDI, for example, Kang, Lee & Park

(2010) and Kimura & Todo (2010) employed gravity equation type

estimation in order examine the vanguard effect between aid from a donor

country and foreign investments; Blaise (2005) used conditional logit

analysis to investigate whether the aid flows from Japan in China has a

significantly positive correlations in which Japanese aid indeed was

influential in terms of private investors’ location choices for his investments.

Furthermore, there are a number of studies that employed tobit analysis.

Generally, at first, tobit analysis have been used in studies on finding FDI

determinants or factors. For example, Lemi and Asefa (2003), examine the

effect of economic and political instability on FDI to African economies by

using the Generalized Auto-Regressive Conditional Heteroscedasticity

(GARCH) model. The indicators specifying uncertainty in inflation rates and

real exchange rates are derived from the GARCH model and are used in

the FDI model as indicators of political uncertainty. As censored values are

found in U.S. FDI data, panel Tobit models- in which four distinct FDI

variables are dependent variables- are estimated and compared with the

standard random effects model. Consequently, as for the result indicates that

the effect of uncertainty on the FDI flow is insignificant for all the source

- 37 -

countries. Economic and political uncertainty is not a matter of concern for

the combined U.S. FDI variable, only political instability and government

policy decisions for the U.S. manufacturing FDI are significant factors.

Moreover, Petri (2010) used both GMM and tobit model analysis to argue

that Asian FDI flows, in contrast to other FDI flows, systematically favor

hosts with relatively low technology achievement and relatively strong

intellectual property rights regimes. He argues that the type of ‘Asian

exceptionalism’ is consistent with ‘flying geese’ theories that have argued

that Asian development is the result of technology flows among economies

that occupy nearby rungs of the technology ladder. Acaravci and Ozturk

(2012) investigate the causal relationship between economic growth, export

and FDI for the ten transition European countries. Results reveal that there

is causal relationship between FDI, export and economic growth in four out

of ten countries considered. Aguiar, Aguiar-Conraia, Gulamhussen &

Magalhaes (2012) investigates the factors affecting Brazilian FDI according

to the country source. Tobit, Heckit and Probit models are estimated with

the 2005 data of 180 countries making and not making investments in

Brazil. The result of analysis indicates that countries with low political risk

undertake more FDI in Brazil.

This paper will be employing panel tobit analysis in order to prove that

ODA has a promoting effect in FDI flows in CLMV countries. The study

will be employing panel tobit model with fixed effects since the dependent

variable "#$%&, a large number bilateral FDI data of donor countries to

recipient countries takes on the value of zero and these have to be analyzed

using a censored regression model, hence simple OLS estimation will yield

- 38 -

biased estimate. In these circumstances, data are censored and the

appropriate statistical model for estimating an FDI equation is the Tobit

estimated by the maximum likelihood method (Tobin, 1958; McDonal &

Moffitt, 1980; Tong, 2005), the basic tobit model can now be written as

follows:

9%&:;<= ><?'()%& ><@*'%+,-%& ><A.%+,-%& ><B(-%& ><CD0)%(-%&><EFG2-%& ><H3%,4)%& ><IJ.)-& ><K'()8.-& ><?=exp'-4-&

"#$%&:;9:%& i f J:%& N=

= i f J:%& ≤=

- 39 -

5. Results and Summary of Findings

5.1 Descriptive Statistics

In order to understand the characteristics of the countries and allocation

of ODA and FDI from donors to recipients, descriptive statistics can be

useful. For each variable, mean, standard deviation, minimum, maximum and

the number of observation are illustrated in the <Table12>.

Variable Obs. Mean Std. Dev. Min MaxDependent Variables

fdic 270 9077537 2.58e+07 0 2.03e+08fdil 270 968333.3 3791640 0 4.69e+07fdim 270 1.85e+07 8.04e+07 0 8.51e+08fdiv 270 1.52e+08 4.48e+08 0 3.31e+09

fdiclmv 270 1.81e+08 4.69e+08 0 3.38e+09Independent VariablesBilateral ODA flows

odac 270 2.29e+07 4.04e+07 0 2.57e+08odal 270 1.13e+07 2.23e+07 0 1.60e+08odam 270 3.09e+07 2.98e+08 0 4.86e+09odav 270 1.14e+08 3.17e+08 0 2.55e+09

odaclmv 270 1.79e+08 5.75e+08 0 7.70e+09Bilateral aid for social infrastructure

soinfcr 270 52.65868 831.4132 0 13659soinflr 270 .8619481 5.254938 0 84.5757soinfmr 270 .9150422 5.173167 0 74.7727soinfvr 270 .6947667 2.655619 0 35.9129

soinfclmvr 270 .4066959 .5666836 0 4.5688Bilateral aid for economic infrastructure

einfcr 270 .06258 .1404103 -.4519 1einflr 270 .1671944 .6366163 0 7.4161einfmr 270 .0448148 .3233247 0 5.0532einfvr 270 .1212156 .2496294 0 2.0325

<Table 12> Descriptive Statistics of Variables

- 40 -

5.2 Panel Tobit Results and Interpretation

5.2.1. Relation between ODA and FDI flows

As for the most important variable throughout this study, bilateral ODA,

strong evidence was found of an impact of Bilateral ODA on FDI. <Table

13> shows that the model used in the paper delivered positive statistically

significant coefficients of the aid variables. The aggregated data for CLMV

countries and each country will be explained in twofold:

A. Bilateral ODA and FDI flows

B. Sectorial analysis of bilateral ODA and FDI flows

einfclmvr 270 .0897393 .1563431 0 1.3878Bilateral aid for debt relief

dcr 270 .0000248 .0004077 0 .0067dlr 270 .0116148 .0568364 0 .3927

dmr 270 .0968478 .5232252 0 7.0496dvr 270 .0170037 .1244132 0 1.4934

dclmvr 270 .0766604 .6203383 0 9.6575Bilateral aid for humanitarian aid

huaidcr 270 .0188037 .0678328 0 .5814huaidlr 270 .0130604 .0719472 0 1huaidmr 270 .6046518 2.928781 0 33.7012huaidvr 270 .0084278 .0266437 0 .2805

huaidclmvr 270 .05134 .1127286 0 .8416Bilateral aid for multisector

mulcr 270 .0965831 .1680748 0 .9076488mullr 270 .0860093 .1504111 0 1mulvr 270 .106279 .1318778 0 .5902337mulmr 270 .0324929 .1002547 0 .8502321

mulclmvr 270 .0910248 .0963715 0 .5249949Political and other factors

bifta 270 .0814815 .2740811 0 1odaper 270 263.8283 257.3433 3.906363 1098.704exportr 270 .3143342 .3443474 0 1.796108

- 41 -

(1) CLMV countries

A. Bilateral ODA and FDI flows

As shown in the <Table 13>, it can be said that bilateral ODA of

donor countries do promote foreign investment, or FDI, in CLMV countries.

The aggregated bilateral ODA flows received in CLMV region is positively

correlated with bilateral FDI flows with a coefficient of 0.350 at the 0.01

significance level. The highly significant aggregated ODA of the CLMV

region show that USD $1 invested in aid raises the FDI by $0.350.

This also follows the results from the past studies (Kimura and Todo

,2010; Driffield & Jones, 2013), it is said that ODA has a vanguard effect

on FDI. Possible reasons for the vanguard or promoting effect of ODA on

FDI are that aid could transmit tactic information on the business

environment of the recipient country, reduce country risk with the provision

of a quasi government guarantee, and set donor country-specific business

standards in advance for private investments.

B. Sectorial analysis of bilateral ODA and FDI flows

The coefficient on the aggregated aid ratio data allocated in Social

Infrastructure and Development sector over overall bilateral aid is statistically

significant, corroborating the positive effect of bilateral aid for social

infrastructure development on FDI flows in CLMV countries.

The positive relationship may be due to the findings of Mayer (2006)

- 42 -

and Donaubauer et al. (2012); Mayer (2006) explains aid for social

infrastructure as a distinct determinant of FDI. Aid for Social infrastructure

and Development sectors includes education, health or sanitary programs and

projects and in this context, Donaubauer et al. (2012) suggests that aid for

social infrastructure especially aid for education is an effective means to

increase FDI flows to host countries where schooling and qualification

appear to be inadequate from the viewpoint of foreign direct investors in

Latin American countries.

(2) Cambodia and Lao PDR

According to <Table 13>, it can be said that there are no significant

results shown for Cambodia and Lao PDR; in other words, foreign aid

received by Cambodia and Lao PDR does not have any promotion effect on

FDI in these countries. Such results might have been shown because of the

following reasons.

According to the World Bank (2016), Cambodia and Lao PDR, as

mentioned before in the former chapter, are still in the stage of developing

and these countries are classified as the Least Developed Countries(LDCs)

by the United Nations(UN). Especially, Cambodia and Lao PDR is

considered as significantly underdeveloped especially within the ASEAN

region. Moreover, Cambodia and Lao PDR each ranked 127 and 134 out of

189 countries in terms of business environment index (World Bank, 2014a),

while Vietnam ranked at 78, Myanmar at 177. These countries also ranked

135 and 148 on Logistics Performance Index (LPI) in 2014 (World Bank,

2014b).

- 43 -

All in all, due to the situation mentioned above, it would have been

difficult for Cambodia and Lao PDR to receive large amount of foreign

investments and this may be why these two countries did not show any

significant correlations.

(3) Myanmar

A. Bilateral ODA and FDI flows

There were no significant correlations shown between the bilateral ODA

from 18 donors on FDI flows in Myanmar. This may be because Myanmar

was suffered from long-term economic sanctions (World Bank, 2014c) from

the international community, and currently it is going through a critical

transformation.

Biglaiser and Lektzian (2011) investigated whether U.S. sanctions

influence U.S. FDI inflows into targeted countries using panel data for 171

countries from 1965 to 2000; the authors were able to find strong evidence

that US investors pull out of countries targeted for U.S. sanctions prior to

their imposition. Similar disinvestment trends can be found in Myanmar.

Moreover, as mentioned before, a number of countries including the

European states followed U.S. in terms of its period and severity. As a

result, despite its economic potential, Myanmar was isolated for most of its

post-independence period; it was not able to receive FDI from the

international society until 2011 when a new administration took office.

Moreover, since Myanmar ranked 177 in business environment index out

of 189 countries (World Bank, 2014a), it can be said that such result

- 44 -

follows the findings of Karakaplan et al.(2005) and Yashin (2005). It is true

that Karakaplan et al.(2005) argues that countries with good governance and

financial market will receive larger amount of FDI; in contrast, Myanmar

with underdeveloped financial market will be difficult to induce foreign

investments. However Harms and Lutz (2006) asserts that effect of aid

proves to be strictly positive “where firms have to cope with substantial

restrictions on their activities” (Harms and Lutz, 2006: 780). Following such

finding, Myanmar should also have been found that aid received from

international donors have positively correlations on its FDI flows, since

currently it does not have business friendly policies especially towards the

foreign private companies. However most of the economic sanctions imposed

in Myanmar were lifted up in 2011, and it is currently on the process of

political and economic transition, for a better result, it should be

re-investgated for positive aid effect on foreign investment within the host

country.

B. Sectorial analysis of bilateral ODA and FDI flows

As shown in <Table 13>, the ratio of humanitarian aid over bilateral

ODA has a negative correlation with FDI flows in Myanmar at a 0.01

significance level. In other words, humanitarian aid in Myanmar tend to

crowds out FDI inflows in Myanmar. This may be explained by other

negative correlations between the year effect and FDI flows in Myanmar.

The year 2007, 2011, and 2013 were also shown that it has negative or

substituting effect on FDI inflows; Myanmar suffered from terrible natural

- 45 -

disasters such as flood, earthquake in the following years (UNICEF, 2007;

Reliefweb, 2011; 2013)in which many countries including US, Japan and

other European countries actively placed humanitarian aid in Myanmar. In

other words, this result may be explained as the donors placed

humanitarinan aid or emergency relief to support Myanmar on the disasters

solely on humanitarian support without any intentions such as its own

national interest of a donor country.

In addition, another substituting relationship was found, aid for

Multisector in Myanmar was negatively correlated at 0.05 significance level.

According to OECD (2014) sector classification, Multisector is a

cross-cutting sector that includes urban development and management and

rural development. In the detail classification for urban development and

management it is articulated that it includes “integrated urban development

projects; local development and urban management; urban infrastructure and

services; municipal finances; urban environmental management; urban

development and planning; urban renewal and urban housing; land

information systems” (OECD, 2014: 20). Moreover, for rural development is

explained as: “Integrated rural development projects; e.g. regional

development planning; promotion of decentralized and multisectoral

competence for planning, co-ordination and management; implementation of

regional development and measures (including natural reserve management);

land management; land use planning; land settlement and resettlement

activities [excluding resettlement of refugees and internally displaced persons

(72010)]; functional integration of rural and urban areas; geographical

information systems (OECD, 2014: 20).”

- 46 -

In this context, it is possible to understand that aid programs/projects in

Multisector are a total development project of a specific community in a

country. According to OECD (2013), aid for Multisector is Myanmar’s Top

5 bilateral ODA receipts by sector; since these include cross-sectional

programs/projects for community development, it is possible to believe that

aid for Mutisector has a substituting effect on FDI flows.

(4) Vietnam

A. Bilateral ODA and FDI flows

Vietnam has shown positive correlation between the bilateral ODA flows

from the 18 donor countries to its FDI flows with a coefficient of 0.911 at

0.01 significance level. In other words, it can be said that if ODA from

donors increases by USD $1, Vietnam will be receiving USD $0.911 more

of foreign investments.

Such positive correlation between aid received by Vietnam on its FDI

flows can be explained Yasin (2005); Yasin (2005) argued that there are

unconditional positive effects of aid on FDI flows were found in

sub-Saharan Africa.

Moreover, this also follows the results from Kimura and Todo (2010), it

is said that ODA has a vanguard effect on FDI. Moreover, in case of

Vietnam, it also follows the findings from Karakaplan et al.(2005); it shows

that aid is more likely to induce FDI in host countries with better

governance and more developed financial market. Vietnam can be considered

as a developed country compared to CLM countries especially in terms of

- 47 -

business environment and infrastructure indicators since it ranked 78 out of

189 countries on its business environement (World Bank, 2014a).

B. Sectorial analysis of bilateral ODA and FDI flows

According to <Table 13>, the ratio of aid allocated in Social

Infrastructure and Development sector has been found that there is a positive

correlation with FDI flows in Vietnam at 0.1 significance level. The reason

for positive result also follow the findings of Mayer (2006) and Donaubaur

et al. (2012), already explained before in the part of the aggregated aid

ratio for social infrastructure development having positive correlations with

FDI flows in CLMV countries. Moreover, since Vietnam is the most

developed country compared to CLM countries, its economic infrastructure

already has been developed in last decade when it was flourishing with

international assistance. Social infrastructure is considered as the next

important measure for the country’s further development; this may be why

aid for social infrastructure promotes FDI flows in Vietnam.

Moroeover, the ratio of aid for Multisector has a substituting effect on

FDI flows in each country at 0.05 significance level. Currently in Vietnam,

aid for Multisector is Top 3 bilateral ODA receipts by sector. As explained

before, Multisector aid programs/projects are implemented cross-sectionally

for community development; it concerms various sectors in a

program/project, in other words, foreign investments will be placed in

different sectors where FDI can induce synergy effects.

- 48 -

5.2.2 Impacts of Political Factors on FDI

(1) CLMV

As for the relationship between political factors and FDI flows,

aggregated data for CLMV region on bilateral FTA show positive correlation

at 0.01 significance level. This results are similar to the study done by Park

(2014); the study also analyzed the relationship between political factor,

ratification of bilateral economic agreements, and FDI flows in host

countries through various models. Park (2014) investigated that the

ratification of agreements can be seen in the political factors and South

Korea and host country of the individual, significant results came out

positive. In this context, the findings in this study on political factors can

mean that the existence or ratification of economic agreements will increase

FDI from donor countries in CLMV countries.

(2) Cambodia and Lao PDR

Cambodia and Lao PDR did not show any significant results in terms

of the relationship between political/ economic factors and FDI inflows. This

result may be, as mentioned above, since these two countries are categorized

as the Least Developed Countries (LDCs); in other words, receive too small

amount of foreign capitals compared to Myanmar and Vietnam.

- 49 -

(3) Myanmar

In case of Myanmar, there were no significant correlations found

between political factor and FDI inflows. This result is also because of the

fact that it has been isolated from the international society in terms of

political and economic aspect, and was imposed with various economic

sanctions from other countries.

Moreover, in terms of political factor, this study regarded Myanmar and

ASEAN as the same; in other words, the study considered that a donor

country has a political relationship or agreements with Myanmar, if a donor

country already signed a FTA with ASEAN. However, since Myanmar was

isolated due to its undemocratic political regimes, ASEAN FTA should not

have been considered to have the same effect as the specific FTA between

Myanmar and a donor country.

(4) Vietnam

In case of Vietnam, it has been shown that, in <Table 13>, there is a

positive correlation between the ratification of FTAs and FDI flows at a

0.01 significance level, same as the aggregate data for the region.

This result, as mentioned before, also follws the findings of Park (2014)

where the author argues the ratification of economic agreements, a political

factor in the study as well, since it employs diplomatic relations between

both investing and investment receiving countries, show significant results to

FDI flows in recipient countries. Since through having such diplomatic or

- 50 -

political understandings, it would have been easier for the private companies

to enter the host countries. Moreover, with the support from the government

in various terms, the private companies were to mitigate any risks by

receiving important and necessary information for business operation in the

host country.

In this context, it could be said that the existence or ratifiction of

economic agreements, a political factor in the study, will increase FDI from

donor countries in Vietnam or host countries.

- 51 -

VARIA

BLESCLM

V 

Cam

bodia

LaoPD

RM

yanmar

Vietnam

Year effects

2001.year

3.703e+

072.63

2e+07

1.187

e+07

2.934e+

07

9.639e

+06

(1.491e+

08)(0)

(0)(4

.369e+

07)

(1.606e+

08)

2002.year

-9.75

0e+07

1.613e+

07

-7.062e

+06

-2.195e+

07-9.64

3e+07

(1.904e+

08)(0)

(0)(5

.312e+

07)

(2.068e+

08)

2003.year

-2.38

6e+08

5.968e+

06

-4.002e

+07

-8.546e+

07-2.26

0e+08

(1.946e+

08)(0)

(0)(5

.750e+

07)

(2.117e+

08)

2004.year

-2.25

9e+08

4.806e+

06

-2.555e

+07

-5.559e+

07-2.04

8e+08

(1.921e+

08)(0)

(0)(5

.511e+

07)

(2.097e+

08)

2005.year

-4.85

3e+07

2.138e+

07

5.354

e+07

-6.738e+

07-1.68

8e+07

(1.967e+

08)(0)

(0)(5

.969e+

07)

(2.122e+

08)

2006.year

-1.03

3e+08

1.420e+

07

2.290

e+06

-1.826e+

07-1.50

5e+08

(2.037e+

08)(0)

(0)(6

.173e+

07)

(2.246e+

08)

2007.year

-5.38

5e+07

3.170e+

07

1.979

e+07

-1.475e+

08**

-1.395e+

08(2.0

13e+08)

(0)(0)

(7.236

e+07)

(2.210e+

08)

2008.year

-1.10

7e+08

2.659e+

07

-7.467e

+06

-8.773e+

07-2.17

4e+08

(2.033e+

08)(0)

(0)(7

.679e+

07)

(2.205e+

08)

2009.year

1.880e+

079.84

0e+06

-2.123e

+07

-1.153e+

08-6.54

4e+07

(2.038e+

08)(0)

(0)(7

.353e+

07)

(2.243e+

08)

2010.year

-1.91

5e+08

4.632e+

06

-3.125e

+07

-4.092e+

07-3.34

7e+08

(2.086e+

08)(0)

(0)(6

.704e+

07)

(2.304e+

08)

<Tab

le 13> P

anel T

obit A

nalysis Resu

lts

- 52 -

VARIA

BLESCLM

V 

Cam

bodia

LaoPD

RM

yanmar

Vietnam

2011.year

-2.53

7e+08

1.205e+

07

1.114

e+07

-1.159e

+08*

-4.126e+

08*

(2.114e+

08)(0)

(0)(6

.968e+

07)

(2.363e+

08)

2012.year

-3.39

3e+08

1.047e+

07

-4.782e

+08

-1.009e+

08-5.7

70e+08**

(2.158e+

08)(0)

(0)(6

.914e+

07)

(2.522e+

08)

2013.year

-3.44

7e+08

1.792e+

06

-4.768e

+08

-1.242e

+08*

-4.221e+

08*

(2.173e+

08)(0)

(0)(7

.408e+

07)

(2.417e+

08)

2014.year

1.061e+

082.45

4e+07

9.867

e+07

6.900e+

06

4.201e

+07

(1.648e+

08)(0)

(0)(4

.961e+

07)

(1.757e+

08)

Bilateral OD

A

Bilateral O

DA

0.350***

-0.1000

0.133

-0.0213

0.911***

(0.0635)

(0)(0)

(0.024

3)(0.1

82)Se

ctorial A

ids

Bilateral aid

for

Socia In

fra.5.6

79e+08**

3.008e+

07

6.202

e+07

8.926e+

06

4.399e+

08*

(2.213e+

08)(0)

(0)(6

.966e+

07)

(2.323e+

08)

Bilateral aid

for

Econom

ic Infra.

3.113e+

081.77

0e+07

5.032

e+06

4.552e+

07

-1.866e+

08(2.7

04e+08)

(0)(0)

(1.964

e+08)

(3.306e+

08)

Bilateral aid

for

deb

t relief-2

.227e+

08

-6.382e+

09

6.714

e+08

-1.721e+

07-3.13

7e+08

(2.797e+

08)(0)

(0)(1

.379e+

08)

(8.165e+

08)

Bilateral aid

for

hum

anitarian

aid-40

.17-2.961

e+08

-9.630e

+06

-1.756e+

08**

-2.160e+

09(16,066)

(0)(0)

(7.160

e+07)

(2.134e+

09)

Bilateral aid

for

multise

ctor

-5.90

6e+08

-9.900e+

06

-5.942e

+07

-1.017e+

09**

-7.546e

+08**

(3.822e+

08)(0)

(0)(4

.017e+

08)

(3.226e+

08)

- 53 -

VARIA

BLESCLM

V 

Cam

bodia

LaoPD

RM

yanmar

Vietnam

Political and

other fa

ctors

Bilateral FTA

6.998e+

08***

6.845e+

07

3.667

e+07

4.260e+

07

6.820e+

08***

(1.242e+

08)(0)

(0)(3

.810e+

07)

(1.386e+

08)

Exports

7.451e+

07-1.856

e+06

-2.231e

+08

-1.463e+

072.378

e+08*

(1.171e+

08)(0)

(0)(5

.293e+

07)

(1.360e+

08)

ODA p

er capita

-417,9

13***-6

9,296

-288,3

18-119,211**

-549,868***(1

37,179)

(0)(0)

(52,38

7)(174,354)

Constan

t-1

.920e+

06

-1.185e+

07

-1.063e

+08

2.596e+

08**

2.417e

+08

(2.219e+

08)(0)

(0)(1

.234e+

08)

(2.881e+

08)

Observation

s270

270

270

270

270

Standard

errors in

paren

theses

*** p<0.0

1, ** p<0.0

5, * p<0.1

- 54 -

6. Implications and Limitations

6.1. Conclusion and Implications

By using tobit analysis with panel data of 18 donor countries from

2000 to 2014, the study was able to find positive correlations between

bilateral ODA and FDI in CLMV countries in aggregated and disaggregated

sense. The study investigated that the bilateral ODA is a facilitating factor

for foreign investments to host countries in CLMV countries, especially in

Vietnam. The result is to match the past literatures assessing the relationship

of ODA on FDI (Kimura & Todo, 20010, Yasin, 2005; Arazmuradov,

2015; Park, 2014).

Like mentioned above, the reasons for the phenomenon may be in order

to reduce risks for home countries’ corporations by possessing some kind of

country-country treaty or projects; gaining information on business

environment of the recipient country. However, Cambodia and Lao PDR,

since both countries receive small amount of FDI compared to the countries

located in the region, did not show any significant correlations between the

variables. Moreover, same result was found in case of Myanmar as well,

since Myanmar is a country that is currently going through a political and

socio-economic transition. In this context, it could be said that the

assumption of generally when providing aid, the ultimate goal of the donor

countries is based on its own national interests.

Furthermore, in terms of sectorial analysis, aid for social infrastructure

development promotes FDI inflows in CLMV region.. Especially in Vietnam,

- 55 -

aid for social infrastructure for example, any aid projects/programsas related

to education, health significantly promotes FDI inflows. Such findings also

can be explained from the past literature of Mayer (2006) and Donaubauer

et al. (2012).

On the other hand, humanitarian aid allocated in Myanmar has a

crowding out effect towards FDI inflows; in other words, it is possible to

argue that any natural disasters and humanitarian issues may bring altruism

in international donors. In addition, aid for multisector also crowds out FDI

inflows in Myanmar and Vietnam.

All in all, the results from the study provides strong empirical evidence

that foreign aid is indeed associated with higher FDI inflows to developing

countries in this case, CLMV countries. Furthermore, well targeted

sector-specific ODA could possibly remove critical impediments to higher

FDI inflows and, thus, assist to diffuse FDI-related benefits across

developing host countries.

In this context, it is possible to believe that developing nations, in this

case the CLMV countries, do receive positive consequences on its

socio-economic development from foreign aid, because, in the end, the ODA

received from the donors induces foreign investments in the country, since it

is proven that FDI positively impacts the host countries’ economic

development. Despite the fact that international donors might consider its

national interest when providing aid to developing countries in order to

easily transfer its own private capital, this phenomenon cannot be just

regarded as something selfish, it rather it is better/conclusive to consider as

a ‘win-win’ for both donor and recipient(host) countries.

- 56 -

6.2. Limitations

Despite its implications mentioned above, the study possess the follwing

limitations.

To begin with, the study had its limitations in the sense that it had

non-comprehensive sectorial analysis on ODA flows. There were only five

ODA sectors analyzed among ten sectors classified in the OECD CRS

system. At first, the five sectors were chosen because those sectors were

most ODA receiving sector in each CLMV countries, however, it would

have been more comprehensive to see all of the ten sectors to have better

empirical results.

Furthermore, the study may have had comprehensive results if it

compared CLMV economic bloc with other economic blocs, such as BRICs.

It is true that the study had comprehensive analysis by looking into each

country; however the by analyzing another economic bloc with specific

analysis on each countries on that economic bloc, the study would have

far-reaching results to discuss.

Lastly, the study would have been more extensive, if is also used

methods such as Focus Group Interview (FGI) or any other interviews with

on related personnel in order to investigate the reasons behind the empirical

results. Moreover, in line with the conclusion of well targeted sector specific

ODA can remove ant obstacles for higher FDI flows, to further explore

possible synergies between aid and FDI flows (OECD, 2002; Kimura

&Todo, 2010; Yasin, 2005), the case of aid for social infrastructure in

CLMV countries invites future research into the alignment of sector-specific

- 57 -

aid with FDI and the related needs in particular host countries or regions

(i.e. Donaubauer et al., 2012). For instance, aid targeted at health- any aid

projects/programs related to in order to fight HIV/AIDS- could improve

access to FDI for countries with particularly high infection rates. Likewise,

aid may help upgrade physical infrastructure and, thus it can remove critical

impediments to higher FDI flows to where physical infrastructure is

particularly deficient. At the same time, deeper insights into the relationship

between aid and FDI could be gained if inward FDI was differentiated by

sectors and industries. It clearly deserves more attention whether

sector-specific aid such as aid for education attracts FDI to certain sectors

and particular types of FDI, though not necessarily other types.

- 58 -

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국 문 초 록

년 이후 국제사회의 공여국들은 공적개발원조 를 통하여 1950 , (ODA)

상당한 양의 유상 및 무상원조를 개발도상국에 지원해왔다 년대 이. 1990

후 새천년개발목표 의 구호 아래에, (Millenium Development Goals: SDGs)

서 지속되어온 개발원조는 년 지속가능발전 목표2015 (Sustainable

의 수립 이후 새로운 전환점을 맞이하고 있다Development Goals: SDGs) .

지속가능발전목표 의 수립은 원조 피로 를 느끼고 (SDGs) (aid fatigue)

있던 국제사회에 개발원조 증대의 필요성을 다시금 환기시키는 계기가

되었다 또한 개발도상국가의 발전이 개별국가의 숙제가 아닌 국제사회 .

모두가 함께 해결해가야하는 과제임을 확인시키고 가난과 불평등의 종식

을 위한 국제사회의 관심을 촉발시켰다.

그동안의 공적개발원조 관련 연구들은 국제사회의 원조가 개(ODA)

발도상국가의 사회 및 경제발전에 중요한 동인으로 작용하였음을 이미

증명하고 있다 한편 해외직접투자 의 경우 . (Foreign Direct Investment: FDI)

본격적인 국제사회의 개발원조가 나타나기 이전부터 개발도상국의 발전

에 크게 기여해온 주요 요소였다 해외직접투자 가 개발도상국의 발. (FDI)

전에 미치는 영향에 대한 많은 연구가 선행되었으며 이를 통해 해외직접

투자 의 결정요인 투자규모 등과 신흥국가 발전에 관한 유의미한 (FDI) ,

결과가 존재함을 확인하였다.

이에 공적개발원조 와 해외직접투자 는 모두 개발도상국의 (ODA) (FDI)

사회 및 경제발전에 중요한 요소로서 평가받으며 개발금융과 관련한 연

구에서 중요한 주제로 다루어져 왔다 년부터 진행되어 온 관련 연. 2000

구들은 공적개발원조 와 해외직접투자 상호간의 상관관계를 (ODA) (FDI)

- 68 -

규명하고자 하였다 하지만 대부분의 경우 일관된 결과를 제시하지 못하.

며 개발도상국에 대한 해외원조가 해외직접투자 를 촉진시키는 요인(FDI)

으로 작용하는지에 관하여 상반된 결과를 제시하고 있었다.

본 연구는 공적개발원조 와 해외직접투자 간의 관계에 대(ODA) (FDI)

한 관심을 바탕으로 개발도상국에 대한 공적개발원조 가 해외직접(ODA)

투자 를 촉진시키는지 알아보고자 하였다 나아가 (FDI) . OECD Credit

에서 제시한 가지의 원조 분야 중 캄보디아 라Reporting System(CRS) 11 ,

오스 미얀마 그리고 베트남, (Cambodia, Lao PDR, Myanmar, Vietnam:

이 가장 많이 제공받고있는 분야를 선택하여 각 분야별 공적개발CLMV) ,

원조 가 해외직접투자 에 유의미한 영향을 미치는지에 대해 분(ODA) (FDI)

석하고자 하였다 이를 위해 년부터 까지의 개의 공여국 데이. 2000 2014 18

터를 바탕으로 패널 토빗 모형을 사용하여 공적개발원조 와 해외직(ODA)

접투자 간의 상관관계를 추정하였다(FDI) .

분석결과 먼저 지역전체를 대상으로 하는 경우 공적개발원조, CLMV

와 해외직접투자 간에는 양의 상관관계가 존재함을 파악하였(ODA) (FDI)

다 개별국가 차원에서는 베트남에 제공된 공적개발원조 가 해외직. (ODA)

접투자 를 촉진시킨다는 결과가 확인할 수 있었다(FDI) .

분야별 분석의 경우 사회 인프라 및 서비스 부문 원조가 전, CLMV

체 지역과 베트남의 해외투자를 촉진한다는 것을 파악하였다 하지만 미.

얀마와 베트남에서의 인도적 지원 과 다부문(Humanitarian aid) (Multisector)

원조는 오히려 해외투자를 축소시키고 구축효과가 존재함을 확인할 수

있었다.

마지막으로 분석 결과를 통해 국제사회로부터 제공받은 공적개발원,

조 를 통해 지역으로의 해외직접투자 유입이 활성화되(ODA) CLMV (FDI)

고 있음을 파악하였다 또한 베트남의 경우 이를 통해 최근 다양한 부문 . ,

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개발을 위해 투자를 유치하고 있으며 결국 경제성장의 디딤돌 역할을 하

고있음을 확인 할 수 있었다.

주요어 공적개발원조 개발 원조 해외직접투자 원조효과성: (ODA), , (FDI), ,

경제성장 패널토빗 모형,