Thesis of relationship of FDI and GDP of Cambodia, Laos, and Vietnam

5/19/2018 Thesis of relationship of FDI and GDP of Cambodia, Laos, and Vietnam

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Relationship between FDI and Economic Growth in

Cross-Country: Cambodia, Laos, and Vietnam

Sok Rasmey

Phnom Penh, Cambodia

Bachelor Degree in TESOL

Institute of Foreign Languages,Royal University of Phnom Penh

Year of Graduation 2011

A Dissertation

In

Finance

Presented to the Graduate Faculty

Of the Shanghai University of Finance and Economics

in Partial fulfillment of the Requirements for the

Degree of Master of Economics

2014

Supervisor of Dissertation

Ling Feng, Ph.D.

School of Finance

Shanghai University of Finance and Economics


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COPYRIGHT NOTICES

This paper has been produced and properly cited for references. Under the

copyright law, the owner of this paper reserves the rights to publish the work, control

copy and edition to make the material available online without prior notice or

acknowledgements.

For further use of any information contained in this research paper either in

part or in full, it is advisable for a proper acknowledgment of the sources and the

author including other references that the author has acknowledged. Without any

permission from the author and/or proper acknowledgement, reproduction or

publication of this paper would be regarded as violating the copyright law.

Copyright, Sok Rasmey 2014.

All rights Reserved.


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ACKNOWLEDGEMENTS

At the end of my thesis, I dedicate this thesis to those who have shown their support

and contribution. Without whom, this thesis might not have been written and to

whom I am greatly indebted.

To my parents, siblings, and relatives, my deepest gratitude goes to their

unconditional support physically, emotionally, and psychologically. Sense of love

from them encourages me to work harder and commit to complete this paper.

To my supervisor, Dr. Feng Ling, I would like to express my very sincere gratitude

for her continuous guidelines from the start till the end of this thesis. I cannot thank

her enough for her systematic and quick feedback through numbers of emails and

appointments. Without her presence and tireless assistance in many ways, this

research paper would not be able to finish on time. I highly respect her calm and

professional attitude as my supervisor, which motivates and guides me throughoutthis endeavor.

To my friends and country-mates, I am also indebted for their accompany and

motivation for countless times during our stay in foreign country. Without them, this

paper would not produce any better.

Lastly, to my professors and staff at SUFE, I am thankful for their sharing knowledgethrough lectures and personal stories. Special thanks should also been given to

teacher Haiping for his numerous assistances during my life journey in SUFE. I

wholeheartedly thank to Chinese government for offering me the prestigious

scholarship to pursue my higher education and let me explore this international life

experience.


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ABSTRACT

This paper aims to examine the relationship between Foreign Direct Investment (FDI)

and Gross Domestic Product (GDP) as a measurement of economic growth within

three countries including Cambodia, Laos, and Vietnam together from 1993 to 2012

by using cross-country panel data analysis. Different data of FDI will be used such as

total inward FDI, total FDI stock, and FDI flowing from China into these three

countries to examine the impacts of different types of FDI on local economic growth.

The claim from previous studies about results of the negative or positive relationships

of FDI and GDP are based on whether inward FDI or FDI stock is chosen. Therefore,

this paper aims to confirm all types of FDI data namely inward FDI and FDI stock

while amount of inward FDI from China into these 3 countries would be back-testing.

By using three different tests, the results from the Hausman Testing confirm that

Fixed-effect estimator is appropriate. Therefore, the fixed effect testing is further used

to give the result of the equation.

By using hypothesis of FDI leading to GDP as theoretical framework, the research

concludes that there is positive effect of FDI on local GDP growth, and the effect

holds for all types of FDI including inward FDI, FDI stock, and FDI from China in

these countries. It proves that FDI is a key economic growth determinant for these

three countries as a whole, which allows these countries to enjoy the economy

prosperity within the twenty years.

Key Words: FDI, GDP, inward FDI, FDI stock, Panel data, Hausman Test, and Fixed

effect


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ABSTRACT

FDI(GDP) 1993 2012

FDI GDP

FDI

FDI

FDI GDP

Hausman

OLS

FDIGDP

FDI

FDI

20 FDI


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TABLE OF CONTENTS

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LIST OF TABLES

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LIST OF FIGURES

Figure Title

Page

Figure 1:Foreign Direct Investment, net inflows (% of GDP) 11

Figure 2:GDP growth (annual %) 14

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CHAPTER 1: Introduction

1.1 Motivation and Research Questions

Economic development is a main concentration of every developing nation to get rid

of poverty and to move to development in the society. Annual economic development

can be easily recognized by GDP (Gross Domestic Products), which can be defined

as a measurement of one nation's total economic activity. More precisely, GDP

represents the monetary value of all products and services produced in one country

over a period of time. The commonly known equation is GDP =

Household Consumption + Government Expenditures + Investment + (Exports

Imports).

Apart from common factors of GDP, many scholars have more concentration on other

determinants that take part into the economic growth. Foreign Direct Investment

(FDI) has been also recognized to be one of the most significantly indispensable

economic growth drivers especially in the developing countries. Therefore, the

relationship of FDI and GDP representing to the economic growth indicator is a

popular researching economic study.

By studying the FDI-GDP relationship within different individual countries or within

multiple countries, different researchers make different conclusion whether it is

positive or negative relationship, whether it is short-term or long-term relationship,

etc. Different finding results are commonly come from selecting different explanatory

variables such as policy effectiveness and current economic development of one

country, level of productivity, drawbacks of negative Balance of Payment from profit

and capital repatriation, etc. From different previously available studies, there is no

universal conclusion on the same direction of FDI on GDP. Therefore, it is another

great yield of this current research paper to study the relationship FDI-GDP within

cross-countries of Indochina countries namely Cambodia, Vietnam, and Laos. Due to


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shortage of currently available data of these three countries, the main result of

regression would be into panel data analysis.

This research paper is based on two main economic growth theories including

neoclassical theory and endogenous theory of growth. Based on these two theories,

the study aims to form hypotheses as follows.

H1: There is a positive and statistically significant relationship between net

inward FDI and GDP in the panel data.

H2: There is a contemporaneous relationship between net inward FDI and

GDP in the panel data.

H3: There is a positive and statistically significant relationship between

FDI and GDP in the panel data regardless to different types of data of FDI

H4: There is a positive and statistically significant relationship between

FDI from China and GDP to crosscheck the result with H1.

1.2 Scope and Limitation

This paper aims to examine the relationship between Foreign Direct Investment (FDI)and Gross Domestic Product (GDP) as a measurement of economic growth within

three countries including Cambodia, Laos, and Vietnam together from 1993 to 2012

by using cross-country panel data analysis. Different data of FDI will be used such as

total inward FDI, total FDI stock, and FDI flowing from China into these three

countries to examine the impacts of different types of FDI on local economic growth.

Specifically, the paper aims to address four main objectives as follows:

Investigate whether the real relationship of net inward FDI and GDP is

positive.

Investigate whether there is contemporaneous relationship between net

inward FDI and GDP in the panel data.

Investigate whether the relationship of FDI and GDP remains the same

when different types of FDI substitute into a explanatory variable.

Ensure that the relationship FDI-GDP remains although FDI from China


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replaces the independent variable FDI.

The claim from previous studies about results of the negative or positive relationships

of FDI and GDP are based on whether inward FDI or FDI stock is chosen. Therefore,

this paper aims to confirm all types of FDI data namely inward FDI and FDI stock

while amount of inward FDI from China into these 3 countries would be back-testing.

By using three different tests, the results from the Hausman Testing confirm that

Fixed-effect estimator is appropriate. Therefore, the fixed effect testing is further used

to give the result of the equation.

By using hypothesis of FDI leading to GDP as theoretical framework, the research

concludes that there is positive effect of FDI on local GDP growth, and the effect

holds for all types of FDI including inward FDI, FDI stock, and FDI from China in

these countries. It proves that FDI is a key economic growth determinant for these

three countries as a whole, which allows these countries to enjoy the economy

prosperity within the twenty years.

However, within panel data regression in Eview7 program, due to only three

countries selected into study, this paper can only have maximum of two independent

variables on the right hand side of equation. It is also worth to note that the trusted

data of FDI and GDP of Cambodia, Vietnam, and Laos is available only from 1993

to 2012. The reasons are that Cambodia suffers civil war and social instability until

early 1990s and these three countries are among least developed and developing

countries.Such a limitation on number of independent variables and period of data,the implications and analysis would cautiously and selectively apply.

1.3 Significance of the Study

Firstly, by using panel data regression, the current paper aims to extend knowledge

to existing literature by including study of the relationship between FDI and GDP of


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Indochina countries. Secondly, the findings and implications from this paper can

offer an overview of the historical data and lead to a basic guideline for policymakers

for any more effective policy. Third, the paper provides a justification of whether the

Indochina countries should attract more inflow FDI based on finding results.

1.4 Organization of the Paper

This paper will organize as following. Chapter 2 will present literature review of

related methodology and topic such as the two main theories of the neoclassical

theory, endogenous theory of growth and other empirical findings of previous papers.Afterwards, economic background in the three countries will present in Chapter 3,

data and research methodology will discuss in Chapter 4. Findings will list in Chapter

5 while Chapter 6 is conclusion.


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CHAPTER 2: LITERATURE REVIEW

2.1 Introduction

The inward FDI is welcomed by many developing countries due to economic

development contribution in various images. In the short run, great number of people

would be hired for the MNCs production. The spillover of technology, the human

resource via trainings and working standards, the financial maturity, and others would

influence on better productivity and innovation for the local to contribute positive

long-run economy development. However, there would not be always a positive side

of inflow of FDI into every country. For further understanding about this issue,

empirical studies on previous researches would be listed down.

Exogenous growth model are also known as the Solow growth model or the Neo-

classical model, created by Robert Solow, Nobel Prize Winner in 1987 for this model.

It explains that growth of FDI improves the productivity quality and quantity, the

capital flow, and the technological improvement, which ultimately accrues the

economical output in long run. Nevertheless, the exogenous model fails to explain

reasons and process of technological development through FDI. This is called

endogenous growth theory. In the endogenous growth theory, impact of FDI on the

economic growth is adduced by knowledge spillover in four ways (Blomstrom and

Kokko, 1998). The domestic firms update higher and newer technologies following

the foreign subsidiaries. Attractive career offers from the domestic firms to absorb

key human resources from the MNCs and the training courses also go to other local

staffs. This result is also confirmed by using fixed effects estimator with country-

specific time trends and mean group estimates. On average, FDI also has a significant

long-run impact on GDP in spite of any level of development.

2.2 Previous study

Lim GuechHeang and Pahlaj Moolio (2013) study relationship between GDP and FDI

in Cambodia over 19 years from 1993 to 2011. They use simple regression analysis,


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Augmented Dickey-Fuller test, Durbin-Watson test, Breusch-Godfrey Serial

Correlation LM test, Breusch-Pagan-Godfrey test, and Jarque-Bera test. Result is

shown that there is a positive relationship of FDI and GDP in Cambodia, which

mainly contributes to employment for the local people, capital accumulation, and

export. However, Cambodia has not thrived the fullest of FDI benefits and

technology spillover.

Net Seila (2011) analyzes the effect of FDI on the economic growth of three

countries, namely Cambodia, Vietnam, and Thailand from 1987 until 2008 by using

panel data and time series. Result gives that FDI contributes productivity. From his

pooled estimation, there is a long-run effect of FDI growth. Specifically, FDI has

crowding-in effect on domestic investment in Vietnam and Thailand yet only neutral

effect in Cambodia. Based on his examination on FDI data by General Statistical

Offices of Vietnam, FDI in Vietnam contributes to more industrialization

development, export, job opportunities, and government income, boost more R&D

activities, and gives massive advantages to state-owning and domestic firms.

A study of FDI and economic growth by Nguyen Phi Lan (2006) by using 61

Vietnamese provinces in panel data testing from 1996 to 2003 shows the result of a

positive and statistically significant effect of FDI on the economic growth while the

economic growth of Vietnam is an important reason for more FDI inflows into

Vietnam too.

Henrik Hansen and John Rand (2006) study causal relationship between FDI and

economic growth of 31 developing countries from three continents over the time

19702000 as their sample. Using a mean group estimator and a model specification

that is aligned with the standard neoclassical growth model, they conclude that there

is a strong causal link from FDI to GDP matching well with the expected impact in a

standard Solow growth model. Theories of exogenous growth and endogenous

growth are often used in previous research papers to explain FDI-GDP relation.


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Likewise, Nair-Reichert and Weinhold (2001) test causality for cross-country panels

by using data of 24 countries from 1971 to 1995. Based on mixed fixed and random

(MFR) coefficient approach, they find out that FDI generally has significance on

growth although it varies result in different countries.

Although all previously mentioned researches indicate the positive GDP-FDI

relationship, Carkovic and Levine (2002) study the inward FDI impact on the

economic growth by controlling for other determinants and potential biases induced

by endogeneity, country-specific effects, and the inclusion of initial income in OLS

and panel estimator testing.Result shows that exogenous FDI does not influence on

the economic growth. The coefficient of FDI is not stable in the panel data, varying

from 323 (when controlling for initial income, schooling, and inflation) to -34 (when

controlling for initial income, schooling, and financial development). The coefficient

on FDI is still unstable when their regressions are limited to have the same number of

observations. Their conclusion claims that previous macroeconomic studies that find

a positive relationship of FDI and the growth, do not fully control for endogeneity,

country-specific effects, and the inclusion of lagged dependent variables.

Another research studies relationship of FDI and economic growth in 15 East Asian

countries covering three main levels of income group from 1990-2009 based on time

series. As a result, there is no necessity of FDI to boost economic growth and the

positive impact of FDI on the economic growth only if the countries had a certain

economic conditions (Polpat Kotrajaras, 2010).

De Mello (1999) studies impact of FDI to growth in 32 countries including 17 non-

OECD countries based on time-series and panel data estimations. By using fixed

effects regressions and country-specific intercepts, he finds out that there is no

causation of FDI to growth in his non-OECD sample, and there would be a negative

short-run impact of FDI on GDP based on the mean group estimator. Foreign

enterprises not only demand standardized working output, but also have particular


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working deadline to accomplish.

These previous research papers can be concluded that many countries have the

positive causality of FDI and GDP, whereas negative impact of FDI and GDP also

can be found in some countries, mainly based on their selected variables and testing

methods


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CHAPTER 3: Economic Background in Cambodia, Vietnam and Laos

3.1 Benefits and Disadvantages of FDI

FDI is one of the poverty eradication mechanisms by offering mutual benefits to

MNCs (Multi-national Corporations) and host countries. FDI is defined as net inflows

of foreign investment into other countries; it includes equity capital, reinvestment of

earnings, other long-term capital and short-term capital as shown in the balance of

payments (Henrik Hansen and John Rand, 2006). With the existence of FDI, the

MNCs have benefited from cheap labor wage and friendly incentives from host

countries. Those incentives include free renting of a certain property, tax free, and so

forth. For decades, FDI has been one of the means of generating more employment,

higher wage opportunities, more internationalized working opportunities and

environment, better domestic productivity, greater human capacity development, and

technology spillover. In long term, increasing FDI growth rate can provide more

baronial benefits to the host FDI countries by accumulating domestic salary standard,

making more efficient domestic product, and narrowing foreign-domestic product

quality and foreign exchange rate gaps.

However, potential disadvantages of inward FDI are significantly noticed. The

Marxist and dependency stances regard FDI as exploitation of the foreign investors

over developing countries. The domestic firms, for instance, may likely experience

unpleasant effects from competing against the foreign MNCs for talent employment

by offering higher salary, better working environment and technology, and more

preference of employees towards international company brands and benefits.

Therefore, the domestic firms are highly likely crowded out by the MNCs with a

great financial loss and chance of bankruptcy. Completely different from expectation


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of greater employment from the higher FDI, due to efficient machines, the MNCs

probably hire few numbers of highly educated people with a great amount of salary.

Consequently, it enlarges the gap of wage between highly educated and less educated

people. FDI in some developing and poor countries, in Sub-Saharan Africa for

instance, also experiences Balance of Payment (BOP) deficits, and sadly, most of the

time, the final profits go back to original MNCs countries while FDI recipient

countries also suffer national loss of tax revenue due to some ineffective FDI-

attraction policies and corruption between authority and the MNCs.

3.2 FDI in Cambodia, Vietnam and Laos

Thus, it is not a universal agreement whether there is always a positive relationship of

FDI and GDP in every country. It is important for this current paper to study

uncertainty of FDI-economic growth by emphasizing the relationship of FDI and

GDP in three developing countries including Cambodia, Laos, and Vietnam as a

whole. Regionally, these countries are developing and neighboring countries in

Southeast Asia and used to be under the colony of France in 19th century, named as

French Indochina. They are also members of ASEAN community (The Association

of South East Asia Nation). They, however, share different economic level and

population.

From the figure 1, net inflow FDI of these three countries has similar pattern, which

FDI (in term of GDP percentage) increased for several years from 1993 until 1996

and again from 2003 until 2007. Therefore, this can conclude that net inflows of FDI

within these countries become the only one hotspot rather individual countries in the

eyes of investors. Simply it means that one country has increased or decreased FDI,

the other have also gained more or less FDI at the same time.


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Figure 1: Foreign Direct Investment, net inflows (% of GDP)

3.2.1 FDI in Cambodia

Cambodia suffered political unrest and Pol Pot Regime from 1970 to 1979, and only

until the late1980s did the country begin to stabilize again. After political and

economic stabilization, this country had 7% of annual GDP growth rate for over these

20 years despite the fact of booming FDI growth (28 times of growing amount of FDI

in 2012 and of in 1993). It shows limitation of gaining full benefits of FDI in this

country. According to a report of USAID, Cambodia and the U.S. signed a Bilateral

Textile Agreement (BTA) in 1999 for labor standard promotion. According to the

report from the U.S. embassy in Vietnam, the BTA can shortly refers to commitment

of the partner countries to produce specific goods to export into the U.S. market with

changeable tariffs assessed by satisfaction on the products into the U.S. As a result, itoffered employment for over 250,000, mostly rural women, $1.6 billion export in

2003, equal to 73 percent of Cambodian total export and 40 percent of GDP. The U.S.

and Cambodia signed a bilateral Trade and Investment Framework Agreement

(TIFA) in 2006 and discussed about a promising bilateral investment treaty (BIT) in

2012. From 1994 to 2012, the inward FDI approved by the ministry invested on

tourism (50 percent), industry (24 percent), service (19 percent), and agriculture (7

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percent). CDC (council for development of Cambodia), which has right to review and

permit projects in Cambodia, issued the Report 2009-2012 that 176 investment

projects were approved with the investment capital of USD 2,511,763,171 million

and employment to 217,265 people in 2012. Economic growth in Cambodia gained

74 percent from FDI from 1998 to 2006. According to CDRI report 2010, the largest

amount of FDI in Cambodia was originally companies from China, which mostly

focused on garment industry and consequently offered a great amount of

employment. Cambodia experienced a remarkable poverty reduction and a huge

employment for the local people. Kubny and Voss (2013) surveyed on 27 Chinese

manufacturers in Cambodia and discovered that 98% of 26,439 employees were

Cambodian. However, jobs in high positions were for Chinese while typical and low-

skilled jobs were given to Cambodian employees.

3.2.2 FDI in Vietnam

Vietnam shows a global remark as one of the fastest economic growing countries in

the Southeast Asia region with annual average GDP growth rate of 7 percent after its

economic reform in 1986 with a great success of FDI attraction (Nguyen Ngoc Anh

and Nguyen Thang, 2007). Vietnam became the third biggest inward FDI recipient in

ASEAN after Singapore and Malaysia (Mirza and Giroud, 2004). This great success

is owing to newly market-economy hotspot, stable economic and political condition

with governments commitment, cheap and largely available national mineral

resources, young and quite educated human resource, potential domestic market and

export for EU and US markets. After wars and social unrest, in 1986, the Vietnamese

government declared policy "Doi Moi" to reform their economy into "a socialist-

oriented market". The investment in Vietnam in 2005 flew into manufacturing

(50.11%), real estate (9.45%), construction (7.81%), hotels and restaurants (7.78%),

transport (7.04%). The U.S. Government put its policy to improve post-Vietnam-war

bilateral relationships with "trade normalization" (Steve Parker, 2013). With

Vietnamese commitment on trade and investment reform for the BTA of the U.S., the

tariffs on the Vietnam's products dropped from an average of 40 percent to an average


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of three percent. Ha Quang Tuyen, head of the National Account System under the

General Statistics Office (GSO) mentioned that FDI firms contribute about 20 percent

of GDP in 2013, whereas only 2 percent in 1992. Exports by FDI enterprises made up

from about 64 percent in 2012 to 66.87 percent in 2013, based on a MPI report.

Haughton and Nguyen (2002) mentions that after the effectiveness of the BTA in

2001, the BTA accumulates 30 percent more of FDI into Vietnam for the first year,

and continues doubling the inflow. It also contributes 0.6 percent of the annual GDP.

The BTA encourages Vietnam to be more open-economy and eliminate obstacles to

FDI. After the open access to the US market, this earns more confidence and

attraction of FDI in Vietnam (Varamini Hossein and Vu Anh, 2007).

3.2.3 FDI in Laos

After French colony and war in Indochina until 1986, the economy of Laos (The Lao

Peoples Democratic Republic) reformed into a free market system under great

assistances from the U.S. Nowadays, Laos still remains one of the poorest countries

and one of the five communist countries in the world, based on a statement of the

USAID. Laos is regarded as one of the most world's challenging countries for

business startup with up to one-year license permission. With the objective to assist

economy of Laos, the U.S. also offers the BTA. Based on the same report of 2007,

Laos has had Unilateral Trade agreements with 39 countries and bilateral

investment treaties with more than 25 countries(Phonethavong, 2012). The NSEDP

2006-2010 by the Committee for Planning and Investment, published in October

2006, states that within the current situation of Laos (insufficient and limited human

and capital resource), the foreign investment is a major driver of the economic

development despite of exploitation of the natural resource and environment. For

example, FDI on rubber help eliminate rural poverty (Oliver Schoenweger and Alfons

llenberg, 2009). About 80 percent of the total FDI invest in medium or long term

into sector of resource, specifically mining, hydropower, and agriculture ( Oliver

Schoenweger & Alfons llenberg , 2009).


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3.3 GDP in Cambodia, Vietnam and Laos

Figure 2 shows the annual GDP growth rate in percentage of the three countries,

which have similar growing rate of 7 percent despite the currently different economic

level. It is also worth for noting that annual rates of GDP growth of Vietnam and

Laos fluctuate less than of Cambodia, based on figure 2. Volatility of the GDP of

Cambodia is remarkably high while the data GDP of Vietnam and Laos is generally

between 6 to 8 percent.

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Previous empirical studies show various results of the relationship of FDI and GDP

mainly as positive and negative based on different regions and historically available

data. Since these three selected countries have never been selected into studying the

causality of FDI and GDP, this paper attempts to extend another yield into economic

research resource.

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CHAPTER 4: DATA AND RESEARCH METHODOLOGY

There is a common problem to collect and analyze data from developing and/or least

developed countries. Because the selected countries are developing countries in the

Southeast Asia, the data periods of which are fewer than 30 years. Consequently,

testing each countrys data individually to determine the relationship of FDI and GDP

with at least 30 observations is unfeasible. Thus, to quantify the economic analysis of

at least 30 observations, these three selected countries data is combined together to

form a panel data.

Reasons of selecting only 20 years are because of the limitation of data available

from these countries due to wars and recovery of economic circumstances.

Specifically, Cambodia has recovered herself economically from early 1990s only,

and thus, GDP records are available only from 1993 onward.

4.1 Data

The study covers data of FDI and GDP of three countries: Cambodia, Laos, and

Vietnam over 20 years (from 1993 to 2012). GDP functions as indicator of economic

development. The data of GDP, the net inward FDI, and trade was gathered from

World Bank database under Southeast Asia region classification. For a quite stable

study (reduce short-run fluctuation) and due to data availability, the annual data was

utilized in this analysis. GDP (in current USD) functions as a dependent variable

while net inflow FDI (BoP in current USD) is explanatory variable and TRADE is a

controlled variable in our panel data analysis.

Secondly, the FDI stock data from UNCTAD is also utilized for the panel data testing

in order to compare if there is different result between the FDI stock and the net

inward FDI. The same GDP data from the World Bank would be used. The FDI stock

refers to the total value of capital, reserved, and retained profits plus indebted net of

the international company in a foreign country.


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Thirdly, the FDI net inflow data from China into these three countries would replace

over the variable FDI for the third panel data testing; however, the data availability

only starts from 1993 due to shortage of data of inward FDI into Cambodia again

while the other two countries already had earlier year data of Chinese FDI. The FDI

data is extracted from China Statistical Year Book 1993-2013. The main reason of

testing the relationship of Chinese FDI and GDP within these countries is to confirm

that the three different tests would modify altogether the same results for more

reliability. *DCXXNU =FD ID>BDBDBD


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select the best method between the FE and the RE models. The RE estimator is

assumed into null hypothesis and alternative hypothesis is the FE estimator (Hausman

1978).The Hasuman test can only activate on Random effect estimation by observing

on results of P value. Thus, The Random effect testing is always the first test,

followed by Hausman Test. If P value of Hausman test result is less than 5%, null

hypothesis of the RE-estimator is rejected and FE-estimator as alternative hypothesis

is accepted into further testing, and vice versa.

In some cases of equations and available data of variables, the Random effect

estimator cannot execute the result nor any further testing, so Pooled estimationwould be the final regression calculation to provide the result.

In Eviews 7 program, number of cross sections (N) must be more than number of

coefficients (x) in Random-effect analysis. Therefore, because only three countries

(N=3) are selected into model analysis, the number of independent variables would

be no more than two for Random-effect test (x


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The parameter "2 captures other controlling variables that affect growth. In this study,

2 dummy variables are entrance of WTO of the chosen countries and Asian Financial

Crisis during 1997-1998. Cambodia, Vietnam, and Laos became the member of WTO

in year 2004, 2007, and 2013 respectively. Thus, dummy value will be given 0 before

these countries become WTO member and 1 when and after they become the WTO

members. The dummy of Asian financial crisis has value of 1 for all countries in

1997 and 1998 while the other years have dummy value of 0.

Each equation would have different four main results based on value of dummy 0 and

1. For dummy WTO, it is indispensable to note that due to current available data ofFDI from 1993 to 2012 while Laos has become member of WTO from 2013 only, so

when dummy value is 0, there are 45 observations with three cross-countries. When

dummy value is 1, the whole data of Laos would be unqualified, and thus, only two

cross-countries under study with only 14 observations under study. Therefore, when

dummy value is 1, the result is excluded. For dummy Asian financial CRISIS, the

valid result when dummy value is 0, simply without year 1997 and 1998 for Asian

financial crisis time, which might affect unusual economic conditions over theselected countries for regression. Thus, from now on, only two main dummy values

are valid when dummy WTO and CRISIS =0.

4.2.1 Model with net inward FDI

Only panel data method is measured with mainly three variables (GDP, FDI, and

trade) of these three countries from 1993 to 2012. The panel data regression model is

log(GDPt)= !+ "1log(FDIt)+"2dummy + "3log(trade)+ t (2)

where log(GDP)is the dependent variable, log(FDI) is the independent variable, !,

"1, "2 and "3are coefficients, t refers to time, and t refers to error in the analysis.

The "1and "3 enhance the impact of FDI and TRADE towards the economic growth,

so the parameters "1and "3 are expected to be positive.


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Using FDI as an independent variable FDIt, it is assumed there is a contemporaneous

relationship between FDI and GDP. Likewise, this equation is to study whether these

two main factors exist over the period of time. Upon completion of the

contemporaneous analysis one lagged FDI logFDI(-1) will be applied to cross-

check whether the results are consistent with prior test.

log(GDPt)= !+ "1log(FDIt-1)+"2dummy + "3log(tradet)+t (3)

By using one-lagged FDI as an independent variable instead of FDI, it is assumed that

FDI takes time to impact on GDP. Given the endogeneity of the independent variableon the right side due to the contemporaneousness, lagged independent variable is

introduced on the right side.

It is vitally indispensable to scrutiny whether the relationship between FDI and GDP

is from the contemporaneous relationship or beyond the contemporaneous

relationship (lagged FDI). Therefore, another regression is applied:

log(GDPt)= !+ "1log(FDIt)+ "2log(FDIt-1)+"3dummy +t (4)

Where log(GDP) is the dependent variable, log(FDI) and log(FDIt-1) are the

independent variables, !, "1, "2 and "3are coefficients, t refers to time, and trefers to

error in the analysis.

4.2.2 Compare Model with inward FDI and with FDI stock

From previous research studies, it is claimed that relationship of FDI-GDP findings

can be changed when different data of FDI is selected whether it is net inward FDI or

FDI stock. Therefore, it is essential to clarify which types of FDI data is into analysis.

Comparison of regression model between FDI stock and inward FDI will simply

explain by following equations:

log(GDPt)= !+ "1log(FDIt) +"2dummy +t (5-1)

log(GDPt)= !+ "1log(FDIstockt)+ "2dummy +t (5-2)


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log(GDPt)= !+ "1log(FDIt) +"2log(FDIstockt)+ "3dummy +t (6)

where log(GDP) is the dependent variable, log(FDIstock) and log(FDI) are the

independent variables of net FDI stock and net inward FDI, !, "1,and "2 are

coefficients, t refers to time, and trefers to error in the analysis.

4.2.3 Model with Chinese FDI

The independent variable FDI from equation (1) will be substituted by a new

variable of Chinese FDI flowing into these three countries so that this new equation

(4) will be a backup testing the result of equation (1) and (2). In other words,relationship of the FDI of China and GDP is tested whether it has the identical

direction to the relationship of the total FDI-GDP. The panel data regression equation

turns to

log(GDPt)= !+ "1log(FDIchinat)+ "2dummy + t (7)

log(GDPt)= !+ "1log(FDIchinat)+ "2log(Tradet) + "3dummy + t (8)

where log(GDP) is the dependent variable, log(FDIchina) is the independent variable

of net inflow of FDI from China into selected countries, !, "1,and "2are coefficients,

t refers to time, and trefers to error in the analysis.


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CHAPTER 5: EMPIRICAL FINDINGS

5.1 Panel Data Testing

First, the only way to differentiate the choice between RE-estimation and FE-

estimation, the Random Effect estimator must be first tested by letting log(GDP t) be

the dependent variable, and log(FDIt) and log(tradet) be independent and controlling

variables. Then, the qualification between Random Effect and the Fixed Effect

estimator would be determined by P-value of the Hausman Testing. If the probability

of the Hausman test result is less than 5%, null hypothesis of Random Effect

estimation is rejected, and alternative hypothesis of Fixed Effect test is accepted, and

vice versa. As mentioned earlier, due to more accurate results from the Fixed Effect

estimation, the Fixed Effect testing is more expected to be qualified for regression

calculation. Inevitably, for particular regression tests, pooled estimation is used

whenever condition of Random effect testing is invalid.

5.2 Model with Total Inward FDI

In this part, we first examine whether there is a contemporaneous impact of FDI on

GDP, for which the results are reported in table 1, and then we check whether FDI

has long-term effect on GDP, beyond the contemporaneous impact, with the results

reported in Tables 2-3.

"#$%& '( JH;2C#;29> K&H4%; 9A 17L #>D "KM7J

"#$ %&''"( IF WTO=0 )* +,)-)-./Variable Coefficient Prob. Coefficient Prob.C 5.380908 0 5.900162 0LOGFDI 0.068097 0.0145 0.069745 0.0083LOGTRADE 0.708897 0 0.684277 0R-squared 0.990121 0.992762

Data testing into result: (table 1)


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log(GDPt)= 5.380908+ 0.068097log(FDIt)+ 0.708897log(tradet)+ t for D: WTO=0

log(GDPt)= 5.900162+ 0.069745 log(FDIt)+ 0.684277 log(tradet)+ tfor D: Crisis

With 3 cross-section countries from year 1993 to 2012, there are total 45 unbalanced

observations for the case of dummy of WTO value 0. There are total 53 unbalanced

observations for the case of dummy of Asian Crisis value 0. For both dummies, the

R-squared of 99% means that 99% in dependent variable is explained by independent

variable. From the Fixed-effect testing in table 1, FDI has the probability less than

5%, indicating that FDI has a significant relationship with GDP. The coefficient of

0.068 in logFDI implies that 1% increases in logFDI will lead to a 6.8% increase inlogGDP holding other variables constant.

For both cases of dummies, the results prove that there is positive and significant

impact of net inward FDI on the economy within selective countries.

"#$%& )( JH;2C#;29> K&H4%; 9A GM6'GN617L #>D GN6"KM7J

"#$ %&''"( IF WTO=0 )* +,)-)-./ 0123452 65778Variable Coefficient Prob. Coefficient Prob. Coefficient Prob.C 4.531573 0 5.332076 0 9:; /LAG1LOGFDI 0.04915 0.0577 0.079954 0.0011 /:/>?>@A /://9BLOGTRADE 0.762703 0 0.700432 0 /:A@@?= /R-squared 0.991508 0.994544 /:==?>A?

From Table 2, the equations of regression result for one-lagged FDI are

case D: WTO log(GDPt)= 4.531573+ 0.04915log(FDIt-1)+ 0.762703log(tradet)+ t

(P value of FDIt-1=5.77% >5%)case D: Crisis log(GDPt)= 5.332076 + 0.079954log(FDIt-1)+ 0.700432log(tradet)+ t

case no dummy log(GDPt)= 9:;+ 0.063log(FDIt-1)+ 0.72239log(tradet)+ t

Based on table 3 and table 4, with 3 cross-section countries from year 1993 to 2012,

there are total 42 unbalanced observations for the case of dummy of WTO value 0.

There are total 50 unbalanced observations for the case of dummy of Asian Crisis

value 0. For both dummies, the R-square still remains more than 99%.


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For one-lagged FDI as independent variable, there are two different scenarios based

on dummies. For WTO dummy, Fixed effect result shows P value of the FDI(-1) is

more than 5%, which means that the variable is not significant. However, for case of

crisis dummy, FDI(-1) is consistent with GDP. The different result might happen

because of different number of observations compatible with the dummies. Despite

the fact that two different dummies provide different significant and insignificant P-

values, from the total 56 unbalanced observations without any dummy variables

conditions (table 2), it might be concluded that one-lagged FDI still has significant

relationship with GDP. This conclusion will be clarified by next equation of log(FDI)

and lag1logFDI. The R-squared of 99% means that 99% in dependent variable is

explained by independent variable.

From the explanation based on table 1 and 2, the result can conclude that H1

hypothesis has confirmed to be true.

The study of the relationship between FDI and GDP whether it is from the

contemporaneous relationship or beyond the contemporaneous relationship (lagged

FDI) can only in case of dummy crisis =0 while the dummy WTO =0 can be studied

by pooled estimation only. The regression result:

Table 3: Estimation Result of LOGFDI and LAG1LOGFDI

899%&D

JH;2C#;29> !"#$% $''$()

"#$ %&''"( IF WTO=0 )* +,)-)-./Variable Coefficient Prob. Coefficient Prob.

C 9.178466 0 12.83522 0LOGFDI 0.394628 0.0094 0.22482 0.0263LAG1LOGFDI 0.301467 0.0421 0.290689 0.0056R-squared 0.823352 0.934261

Pooled estimation result of dummy WTO=0

log(GDPt)= 9.178466 + 0.394628 log(FDIt)+ 0.301467log(FDIt-1) +t (table 3)



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HR

observations for the case of dummy of WTO value 0 while the R-square is more than

82%.


observations for the case of dummy of WTO value 0. while the R-square is more than

82%. It means that 82% of dependent variable can be explained by independent

variable. From the Fixed-effect testing in table 3, FDI has the probability less than

5%, indicating that FDI has a significant relationship with GDP.

Fixed effect estimation result of dummy crisis=0 (table 3)log(GDPt)= 12.83522+ 0.22482log(FDIt)+ 0.290689log(FDIt-1) +t

With 3 cross-section countries from year 1993 to 2012, there are total 51 balanced

observations for the case of dummy of Asian Crisis value 0. For both dummies, the

R-square still remains more than 93%, which again refers to 93% of dependent

variable can be explained by FDI and one-lagged FDI as independent variables.

Different dummies offer different types of tests for calculation yet quite similar

results. For the dummy of WTO, only pooled estimation is suitable for the analysis

while more reliable testing of fixed estimation works on crisis dummy. The positive

coefficients and P-values of FDI and one-lagged FDI (P


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5.3 Compare Model with inward FDI and FDI stock

Literature has shown different results for the effect of inward FDI and FDI stock on

local economy growth. So here we are going to check whether these two types of FDI

have different economic impacts in these three countries in our sample. Our findings

for inward FDI and FDI stocks are reported in Tables 4-6 respectively.

The Random effect estimator testing is first used to test the equation (5) and equation

(6) which have log(GDP) as dependent variable and independent variables as

log(FDI) and log(FDIstock). The Hausman test shows result of p smaller than 5

percent, which means Fixed-effect estimator is appropriate for the both equations.

Table 4: Estimation result of LOGFDI

!"#$% $''$() !"#$% $''$()

"#$ %&''"( IF WTO=0 )* +,)-)-./Variable Coefficient Prob. Coefficient Prob.C 15.65231 0 13.23919 0LOGFDI 0.357966 0 0.491279 0R-squared 0.893861 0.918883

The regression model between FDI stock and inward FDI will simply explain by

following equation results:

Fixed effect estimation result of dummy WTO=0

log(GDPt)= 15.65231+ 0.357966log(FDIt) +t (table 4) (5-1)

log(GDPt)= 19.13735+ 0.458946log(FDIstockt)+ t (table 5) (5-2)


observations for the case of dummy of WTO value 0 while the R-square is more than89% for equation (5-1) and more than 93% for equation (5-2). It means that variable

inward FDI can explain 89% of variable GDP and 93% of variable FDI stock variable

GDP. Within the positive coefficient of independent variables, it can conclude there

is positive relationship of inward FDI and GDP and of FDI stock and GDP. The P-

value is less than 5% (P


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Table 5: Estimation result of LOGFDISTOCK

!"#$% $''$() !"#$% $''$()

"#$ %&''"( IF WTO=0 )* +,)-)-./Variable Coefficient Prob. Coefficient Prob.C 19.13735 0 ;B:9B/;< 0LOGFDISTOCK 0.458946 0 /:99/;> 0R-squared 0.936325 /:=9 !"#$% $''$()

"#$ %&''"( IF WTO=0 )* +,)-)-./Variable Coefficient Prob. Coefficient Prob.C ;>:/9A?9 0 ;9:??99> 0

LOGFDI /:;=@ /://;@ /:@@?B@B 0%&'*")-C&+D /:?A9/@> / /:=BB?

estimation result: (table 6)

dummy WTO=0

log(GDPt)= ;>:/9A?9+ /: ;=@log(FDIt)+ /: ?A9/@>Eog(FDIstockt) +t (6)

dummy crisis=0


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H_

log(GDPt)= 15.33556+ 0.223828log(FDIt)+ 0.401644log(FDIstockt) +t (6)

From table 6, under pooled estimation regression, with 3 cross-section countries from

year 1993 to 2012, there are total 45 unbalanced observations for the case of dummy

of WTO value 0 and the R-square is more than 95%. For dummy crisis, under fixed

effect estimation, there are total 54 balanced observations and the R-square is more

than 96%. All coefficients are positive and P values of the independent variables are

less than 5%; thus, the relationship of FDI(inward), FDI(stock) and GDP is confirmed

to be positive and statistically significant.

From the whole equations of the (5) and (6) regardless of dummies, it can conclude

that the relationship of FDI and GDP for the selected countries is stably positive and

significant for both types of FDI data. This can conclude that the hypothesis H3 is

true.

5.4 Model with Chinese FDI

China is one of the most important FDI sources for the three countries in our sample.

So here we would like to examine whether the FDI from China has similar impacts on

local economic growth in these three countries. The findings are similar in that FDI

from China positively contributes to local economic growth. The findings are

reported in Tables 7-9.

The same methodology is used to calculate the equation by starting from Random

effect testing, and using Hausman Test to clarify qualified effect estimator whether

Random or Fixed effect will be further put into calculation. In some cases, when

Random Effect is not be able to test the equation, pooled estimation will be used for

the analysis.

"#$%& .( JH;2C#;29> K&H4%; 9A GN617LBOLPM


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HV

,FG647 HIIJK2 ,FG647 HIIJK2

"#$ E4LL6M )* 0C&./ )* +,)-)-./

#FN1FOEJ +4JII1K1JG2 (N4O: +4JII1K1JG2 (N4O:

+ @;:/


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KW

Random effect result when dummy WTO=0 (table 8)

log(GDPt)=


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K:

CHAPTER 6: CONCLUSION AND RECOMMENDATION

The main objective of this paper is to scrutinize what roles FDI has on the economic

growth of Indochina countries namely: Cambodia, Vietnam, and Laos. Panel data

testing was applied to assess whether FDI and Trade have a positive or negative

connection. Based on various testing, findings from the panel data regression prove

that there is a significantly positive relationship of FDI and GDP within these three

countries. The positive and significant elasticity from FDI concludes that FDI is a key

factor of GDP growth.

To confirm the credibility of conclusion drawn from the earlier research study on the

FDI-GDP relationship, different types of the FDI were incorporated into

consideration and calculation. The testing on total net inflow FDI and FDI stock into

these countries has provided the same result. Based on one-lagged net inward FDI

data analysis result, the conclusion can precisely state that FDI and GDP of these

countries are contemporaneous and it may take some period of time for FDI to boost

the whole economy. However, the inward FDI from China into these three countries

cannot be a significant impact on the total economic growth based on the result of

econometric analysis.

Prior studies about relationship of FDI and GDP for these two decades over the

selected countries, it is agreeable that FDI has contributed remarkably to the

economic growth and poverty reduction. The current paper recommends that more

FDI is highly encouraged into these countries to contribute GDP prosperity further,

yet it is also advisable to examine the negative impacts of FDI too.

This paper did not focus on long-term effects of FDI of these countries in the future

and any other possible relationships of FDI and other important variables including

productivity, and domestic firms. Therefore, new studies should focus on the long-

term economic growth in terms of human resource and productivity development,

technological spillover, and FDI-policy effectiveness.


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KH

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Appendices

Total net inward FDI of Cambodia, Vietnam, and Laos from 1993 to 2012

GDP and FDI convert into log(GDP) and log(FDI)


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Net FDI stock and Chinese FDI in Cambodia, Vietnam, and Laos

Year

Chinese FDI FDISTOCK

Cambodia Vietnam Laos Cambodia Vietnam Laos

1993 NA 11610000 NA 125000000 2020000000 57150000

1994 NA NA 50000 194000000 3960000000 116000000

1995 1310000 28300000 NA 356000000 5740000000 211000000

1996 7440000 1450000 150000 942000000 8140000000 371000000

1997 5450000 1540000 390000 956000000 10400000000 4580000001998 2900000 14140000 1120000 1200000000 12000000000 503000000

1999 2480000 130000 NA 1430000000 13400000000 554000000

2000 1940000 560000 3070000 1580000000 14700000000 588000000

2001 9300000 1480000 1040000 1730000000 16000000000 612000000

2002 13740000 2510000 5150000 1870000000 17400000000 617000000

2003 12520000 3380000000 400000 1960000000 18900000000 636000000

2004 20690000 3120000000 4250000 2090000000 20500000000 653000000

2005 2760000 2150000000 4210000 2470000000 22500000000 681000000

2006 2120000 2140000000 6870000 2950000000 24900000000 868000000

2007 6340000 730000 3000000 3820000000 31600000000 1190000000

2008 2920000 2070000 6700000 4640000000 41100000000 1420000000

2009 13370000 4420000 2430000 5180000000 48700000000 1610000000

2010 10350000 20790000 9450000 5960000000 56700000000 1890000000

2011 17370000 8880000 5880000 6850000000 64200000000 2190000000

2012 16600000 2870000 2000000 8410000000 72500000000 2480000000


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log(GDPt)= !+ "1log(FDIt)+"2dummy + "3log(trade)+ t (2)

Correlated Random Effects - Hausman TestEquation: Untitled

Test cross-section random effectsTest Summary Chi-Sq. Statistic Chi-Sq. d.f. Prob.Cross-sectionrandom 18.524683 2 0.0001

Fixed effect

Dependent Variable: LOGGDPMethod: Panel Least SquaresSample: 1993 2012 IF WTO=0Periods included: 20Cross-sections included: 3Total panel (unbalanced) observations: 45Variable Coefficient Std. Error t-Statistic Prob.C 5.380908 0.673932 7.984354 0LOGFDI 0.068097 0.026651 2.555149 0.0145LOGTRADE 0.708897 0.035909 19.74166 0

Effects Specification

Cross-section fixed (dummy variables)

R-squared 0.990121 Mean dependent var 22.53962Adjusted R-squared 0.989133 S.D. dependent var 1.217516S.E. of regression 0.126922 Akaike info criterion -1.186043Sum squared resid 0.644372 Schwarz criterion -0.985302Log likelihood 31.68596 Hannan-Quinn criter. -1.111209

F-statistic 1002.198 Durbin-Watson stat 0.484014Prob(F-statistic) 0

Dummy crisis =0

Hausman Test

Correlated Random Effects - Hausman TestEquation: UntitledTest cross-section random effectsTest Summary Chi-Sq. Chi-Sq. Prob.


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Statistic d.f.

Cross-section random 62.589427 2 0

Fixed effectDependent Variable: LOGGDPMethod: Panel Least SquaresSample: 1993 2012 IF CRISIS=0Periods included: 18Cross-sections included: 3Total panel (unbalanced) observations: 53

Variable Coefficient Std. Error t-Statistic Prob.

C 5.900162 0.470514 12.53982 0LOGFDI 0.069745 0.025322 2.754342 0.0083LOGTRADE 0.684277 0.030892 22.1505 0



R-squared 0.992762 Mean dependent var 22.94192Adjusted R-squared 0.992159 S.D. dependent var 1.386225S.E. of regression 0.122751 Akaike info criterion -1.267733Sum squared resid 0.723252 Schwarz criterion -1.081856Log likelihood 38.59492 Hannan-Quinn criter. -1.196254F-statistic 1645.914 Durbin-Watson stat 0.537168Prob(F-statistic) 0

log(GDPt)= !+ "1log(FDIt-1)+"2dummy + "3log(tradet)+t (3)

Dummy WTO=0Correlated Random Effects - Hausman TestEquation: UntitledTest cross-section random effects

Test Summary Chi-Sq. StatisticChi-Sq.d.f. Prob.


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Fixed effectDependent Variable: LOGGDPMethod: Panel Least SquaresSample: 1993 2012 IF WTO=0Periods included: 19Cross-sections included: 3Total panel (unbalanced) observations: 42


C 4.531573 0.709528 6.386741 0LAG1LOGFDI 0.04915 0.025091 1.958863 0.0577LOGTRADE 0.762703 0.036465 20.91589 0



R-squared 0.991508 Mean dependent var 22.57908

Adjusted R-squared 0.990589 S.D. dependent var 1.224154S.E. of regression 0.118753 Akaike info criterion -1.312203Sum squared resid 0.521782 Schwarz criterion -1.105338Log likelihood 32.55627 Hannan-Quinn criter. -1.236379F-statistic 1079.953 Durbin-Watson stat 0.486485Prob(F-statistic) 0

Dummy crisis=0

Hausman test

Correlated Random Effects - Hausman TestEquation: UntitledTest cross-section random effects



Fixed effectDependent Variable: LOGGDP


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Method: Panel Least SquaresSample: 1993 2012 IF CRISIS=0

Periods included: 17Cross-sections included: 3Total panel (unbalanced) observations: 50


C 5.332076 0.463674 11.49962 0LAG1LOGFDI 0.079954 0.022955 3.48312 0.0011LOGTRADE 0.700432 0.029729 23.56085 0



R-squared 0.994544 Mean dependent var 22.9992Adjusted R-squared 0.994059 S.D. dependent var 1.386702S.E. of regression 0.106882 Akaike info criterion -1.539541Sum squared resid 0.51407 Schwarz criterion -1.348339Log likelihood 43.48853 Hannan-Quinn criter. -1.46673F-statistic 2050.766 Durbin-Watson stat 0.548614

Prob(F-statistic) 0

log(GDPt)= !+ "1log(FDIt)+ "2log(FDIt-1)+"3dummy +t (4)

dummy WTO

pooled estimation

Dependent Variable: LOGGDPMethod: Panel Least Squares

Sample: 1993 2012 IF WTO=0Periods included: 19Cross-sections included: 3Total panel (unbalanced) observations: 42Variable Coefficient Std. Error t-Statistic Prob.C 9.178466 0.99729 9.203405 0LOGFDI 0.394628 0.14451 2.730801 0.0094LAG1LOGFDI 0.301467 0.143469 2.101264 0.0421R-squared 0.823352 Mean dependent var 22.57908


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Adjusted R-squared 0.814293 S.D. dependent var 1.224154S.E. of regression 0.527534 Akaike info criterion 1.627541

Sum squared resid 10.85338 Schwarz criterion 1.75166Log likelihood -31.17836 Hannan-Quinn criter. 1.673035F-statistic 90.88894 Durbin-Watson stat 0.251644Prob(F-statistic) 0

Dummy crisis


Test cross-section random effects


Cross-section random 74.885826 2 0Fixed effect

Dependent Variable: LOGGDPMethod: Panel Least SquaresSample: 1993 2012 IF CRISIS=0

Periods included: 17Cross-sections included: 3Total panel (balanced) observations: 51


C 12.83522 1.061045 12.09677 0LOGFDI 0.22482 0.097941 2.295454 0.0263LAG1LOGFDI 0.290689 0.099894 2.90998 0.0056



R-squared 0.934261 Mean dependent var 23.00638Adjusted R-squared 0.928545 S.D. dependent var 1.37372S.E. of regression 0.36721 Akaike info criterion 0.927128Sum squared resid 6.202785 Schwarz criterion 1.116523Log likelihood -18.64177 Hannan-Quinn criter. 0.999502


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F-statistic 163.4354 Durbin-Watson stat 0.370418Prob(F-statistic) 0

log(GDPt)= !+ "1log(FDIt) +"2dummy +t (5)

dummy WTO


Test Summary

Chi-Sq.

Statistic

Chi-Sq.

d.f. Prob.Cross-section random 15.982927 1 0.0001

FIXED EFFECT


Sample: 1993 2012 IF WTO=0

Periods included: 20Cross-sections included: 3Total panel (unbalanced) observations: 45

Variable CoefficientStd.Error t-Statistic Prob.

C 15.65231 1.386768 11.2869 0LOGFDI 0.357966 0.072006 4.971304 0



R-squared 0.893861 Mean dependent var 22.53962Adjusted R-squared 0.886095 S.D. dependent var 1.217516

S.E. of regression 0.410909Akaike info

criterion 1.143798Sum squared 6.9227 Schwarz criterion 1.30439


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OK

resid

Log likelihood -21.73546

Hannan-Quinn

criter. 1.203665F-statistic 115.0958 Durbin-Watson stat 0.245338Prob(F-statistic) 0

DUMMY CRISIS


Test Summary Chi-Sq. Statistic Chi-Sq.d.f. Prob.



Sample: 1993 2012 IF CRISIS=0

Periods included: 18Cross-sections included: 3Total panel (balanced) observations: 54


C 13.23919 1.061153 12.47623 0LOGFDI 0.491279 0.053614 9.163198 0



R-squared 0.918883 Mean dependent var 22.94976Adjusted R-squared 0.914016 S.D. dependent var 1.374292S.E. of regression 0.402984 Akaike info criterion 1.091345Sum squared resid 8.119789 Schwarz criterion 1.238677Log likelihood -25.46632 Hannan-Quinn criter. 1.148166F-statistic 188.7983 Durbin-Watson stat 0.457948Prob(F-statistic) 0


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log(GDPt)= !+ "1log(FDIstockt)+ "2dummy +t (6)

DUMMY WTO




FIXED EFFECTDependent Variable: LOGGDPMethod: Panel Least Squares

Sample: 1993 2012 IF WTO=0Periods included: 20Cross-sections included: 3Total panel (unbalanced) observations: 45


C 19.13735 0.413695 46.25961 0LOGFDISTOCK 0.458946 0.055437 8.278729 0



R-squared 0.936325 Mean dependent var 22.53962Adjusted R-squared 0.931666 S.D. dependent var 1.217516


criterion 0.632842Sum squaredresid 4.15308 Schwarz criterion 0.793435


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OR

Log likelihood -10.23896Hannan-Quinn

criter. 0.69271

F-statistic 200.9653 Durbin-Watson stat 0.182328Prob(F-statistic) 0DUMMY CRISISCorrelated Random Effects - Hausman TestEquation: UntitledTest cross-section random effects



FIXED EFFECTDependent Variable: LOGGDPMethod: Panel Least Squares

Sample: 1993 2012 IF CRISIS=0Periods included: 18Cross-sections included: 3Total panel (balanced) observations: 54


C 18.58014 0.3224 57.63079 0LOGFDISTOCK 0.55016 0.040258 13.66576 0



R-squared 0.954101 Mean dependent var 22.94976Adjusted R-squared 0.951347 S.D. dependent var 1.374292S.E. of regression 0.303134 Akaike info criterion 0.521901Sum squared resid 4.594499 Schwarz criterion 0.669233Log likelihood -10.09132 Hannan-Quinn criter. 0.578721F-statistic 346.4484 Durbin-Watson stat 0.297251Prob(F-statistic) 0

Dummy WTO


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Test cross-section random effects


Cross-section random 16.846615 2 0.0002Fixed effect result


Sample: 1993 2012 IF WTO=0Periods included: 20Cross-sections included: 3Total panel (unbalanced) observations: 45

VariableCoefficient

Std.Error t-Statistic Prob.

C 16.05735 0.953329 16.84345 0LOGFDI 0.192416 0.054981 3.499693 0.0012

LOGFDISTOCK 0.375026 0.05465 6.862294 0



R-squared 0.951252 Mean dependent var 22.53962Adjusted R-squared 0.946377 S.D. dependent var 1.217516S.E. of regression 0.281936 Akaike info criterion 0.410168Sum squared resid 3.179522 Schwarz criterion 0.610908

Log likelihood -4.228772 Hannan-Quinn criter. 0.485002F-statistic 195.1352 Durbin-Watson stat 0.34484Prob(F-statistic) 0

Dummy crisis



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Test Summary Chi-Sq. Statistic Chi-Sq. d.f. Prob.

Cross-sectionrandom 35.993425 2 0

Fixed effect

Dependent Variable: LOGGDPMethod: Panel Least SquaresSample: 1993 2012 IF CRISIS=0Periods included: 18Cross-sections included: 3

Total panel (balanced) observations: 54


C 15.33556 0.692511 22.14487 0LOGFDI 0.223828 0.044171 5.06732 0LOGFDISTOCK 0.401644 0.044092 9.109162 0


Cross-section fixed (dummy variables)R-squared 0.969883 Mean dependent var 22.94976Adjusted R-squared 0.967425 S.D. dependent var 1.374292


criterion 0.137576Sum squaredresid 3.014693 Schwarz criterion 0.321741

Log likelihood 1.285442Hannan-Quinn

criter. 0.208602F-statistic 394.4992 Durbin-Watson stat 0.604068

Prob(F-statistic) 0

log(GDPt)= !+ "1log(FDIchina)+ "2dummy + t (7)

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Thesis of relationship of FDI and GDP of Cambodia, Laos, and Vietnam