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--1--
INTRODUCTION
1. Research proposal
The flow of foreign direct investment (FDI) into Vietnam begun in
1988. This turning-point was considered an achievement of the economic
transformation from central planning to socialism market-based (Kokko et
al., 2003). After economic reform was implemented, Vietnam’s annual FDI
increased dramatically, reaching $ 22.352,2 mil with annual growth rate
higher than 30% (General statistics directorate, 2014). The height of this
flow was in 2008 with a total of $ 71.000 mil, but there was a steep decline
from 2009 to the present (from registered $23.107,3 mil in 2009 to $16.348
mil in 2012, equivalent of 29.3%). Though the decrease was not against the
global trend under the impact of economic crisis, when compared with
ASEAN and China, the flow showed an increment during the past four
years. This begs for questions: What determines the attraction of Vietnam’s
FDI? What are the factors effecting the FDI distribution across Vietnam’s
regions? Given the importance of FDI to economic growth, the answers for
these are necessary for bringing in appropriate suggestions to further
improve the encouragement of upcoming FDI into Vietnam in general and
into the regions in specific. The reasons stated above urge this author to
carry out a thesis for PhD qualification with the topic “Researching the
determinants of the attraction of FDI flows into Vietnam”.
2. Research related literature:
The author’s summarized survey indicates there exists a range of both
theoretical and empirical researches done on the proposed topic, or similar,
worldwide. However, the number of empirical works on the determinants of
attraction and distribution of Vietnam’s FDI remains low. As far as these
determinants are concern, the majority of surveyed authors utilize different
variables and methods in accordance with their statistical database.
Consequently the overall results were divided into two groups, based on
primary and secondary data. Representing the first are Hafiz and Giroud
--2--
(2004), Lei et al. (2011) and Nguyen et al. (2013). On the other hand, the
papers by Parker et al. (2005), Hoàng (2006), Ho (2010), Pham (2011),
Nguyen (2011), Hoang et al. (2013) used secondary data. With respect to
the factors impacting FDI distribution in Vietnam, due to the limitation of
data, the author’s survey indicates only three typical relevant works of
Meyer and Nguyen (2005), Nguyen et al. (2008) and Dinh (2009).
3. Research objectives:
The main objective of the thesis is to identify the determinants of FDI
flows and regional distribution in Vietnam. The thesis focuses primarily on
answering the two questions:
-What determines the attraction of FDI into Vietnam?
-What are the factors that influences FDI distribution across Vietnam’s
regions?
4. Research subject and scope:
4.1. Subject
The main subjects of the thesis are the determinants of FDI flows and
regional distribution in Vietnam.
4.2. Scope
(1) Data on Vietnam’s FDI attraction from 1988 to 20131.
(2) Data on the feedback of 171 FDI firms on the contemporary
investment environment (2012 – 2013).
(3) To identify FDI attraction determinants, the thesis uses data of 24
Asian developing countries during 2000 – 2012.
(4) Lastly, to indentify factors impacting FDI distribution, data on 63 of
Vietnam’s provinces/cities during 2005 – 2013 were gathered.
5. Research methodology:
- In order to reflect foreign investors’ opinions on Vietnam’s investment
environment, qualitative methods were used.
1
2013 data are preliminary.
--3--
- For the analyses of FDI attraction’s determinants, to use an estimating
method with unbiased, consistent and effective estimators, I chose the
differenced GMM specification rather than the OLS.
- Similar to the case of Vietnam as a whole, the method to estimate and
testing hypotheses about factors impacting regional FDI distribution is also
chosen to be differenced GMM.
6. The innovation and contribution of the thesis:
Theoretical:
- With respect to Vietnam, there is no effect of first lagged FDI (FDI_1)
on the dependent variable, FDI.
- With respect to FDI regional distribution, there exists effect of past
information of independent variables on FDI.
- The use of interaction terms to analyse the difference in slope
coefficients of determinants influencing FDI in comparison with countries
in ASIA 24.
Empirical:
- Provide empirical evidence on the evaluation of foreign investors on
Vietnam’s contemporary investment environment.
- Identify the distinct model for FDI attraction determinants and factors
impacting FDI distribution. Results confirm that the decisions of foreign
investors are affected not only by current information but also past values of
the determinants.
- Based on the testing results from differenced GMM, three out of 6
hypotheses related to the determinants are significant at 10%. Accordingly,
foreign investors choose Vietnam for the policy, market seeking purpose
and resource acquiring motivation.
- About the factors impacting FDI distribution, testing results by
differenced GMM with current and past data are unable to provide
sufficient evidence to reject 4 out of 5 given hypotheses. These involve the
--4--
quality of regional economic management, market seeking, efficiency
seeking and FDI’s cumulative effect.
- Based on the results, some policy suggestions aiming for improving
investment environment as well as attracting FDI at the country and region
levels are proposed.
- Lastly, thanks to the analyses based on panel data of ASIA 24, the
results not only show the motivation of Vietnam’s FDI firms but also relate
to similarities in other countries. As such, the results are hoped to provide a
“broader” perspective to policy makers.
7. Research structure:
Not counting the introduction, conclusion, and policy implications,
the thesis is composed of five chapters.
CHAPTER 1:
FACTORS DECIDE LOCATION OF FOREIGN
DIRECT INVESTMENT: THEORY AND EMPIRICAL RESEARCH
1.1. Introduction
1.2. Generalization about Foreign Direct Investment (FDI)
Theory has shown that FDI usually is created from the interaction of
forces between the host countries and the attractive ones (e.g. Dunning,
1981, 1988, UNCTAD, 2006). Capital flows of FDI will run from countries
to countries and FDI could happen thanks to the influences of push factors
from host nations and pull factors from attractive ones. Additionally, some
investor tends to create motivation push FDI for seeking potential markets
or increasing the effectiveness with lower manufacturing cost in attractive
ones.
--5--
1.3. Influences of FDI to economic growth
FDI could motivate economic growth into two ways which are direct
and indirect. Indirect impact is considered as another term which is
pervasive impact. The studies which analyze FDI’s impacts to economic
growth used different methods and approaches. Some of research mentions
to the measurement of FDI’s impacts to economic growth in general
according to direct influences, while the others concentrate find out FDI’s
impacts to manufacture, international trade, local investment in pervasivedriven.
1.4. Theory about crucial factors of FDI’s position
1.4.1. In national level
1.4.1.1. International Trade Theory
The model of first theory explaining foreign investment bases on
international trade theory is Heckscher-Ohlin model which was established
by Heckscher (1919) and Bertil Ohlin (1933). It concerns that country has
better good input factors should export products which is related to those
agents and import ones which related to other inputs.
1.4.1.2. The Theory of Firm-Specific Ownership Advantages
This theory was taken the initiative by Hymer (1960). This is the first
effort to give independent theory to solve foreign investment trends. Hymer
gave his view departing from industry economy and maintained that an
enterprise which wants to overcome international barriers and participate in
production process should have firm-specific ownership advantages.
1.4.1.3. Product Life Cycle Theories
This theory was presented firstly in 1965 and developed systematically
then by Vernon from 1966. It explains for foreign investment and
international trade and considers foreign investment is a stage of product
life cycle.
--6--
1.4.1.4. Internalization Theory
Internalization Theory was published by Buckley and Casson in 1976,
and it bases on Company Theory of Coase (1937). According to this theory,
internal transaction (IT) is better than market transaction (MT) when the
market isn’t perfect.
1.4.1.5. Eclectic Paradigm Theory (OLI)
This model is established meticulously of Dunning (1977, 1979, 1981,
1988, 1996, 1998, 2000, 2001). According to Dunning, a company decides
to invest abroad when it has OLI advantages including Ownership
Advantages, Location Advantage and Internalization Incentives.
In the general base, OLI Theory about determination of FDI’s position
will be selected as foundation to build theoretical research model about
influent factors of FDI’s attraction and factors affecting FDI’s distribution
between regions in Vietnam in Chapter 3 and Chapter 4 of the dissertation.
1.4.2. Distribution of FDI between regions in the nation
The first basic theory relating to the distribution of FDI between regions
in the nations is Popular Accumulative Impact of Krugman (1991). The
second one relates to traditional economic advantages. The final theory is
institutional factor.
1.5. Empirical research about attractive factor of FDI
The general empirical research reveals that attractive factors of FDI to
group of countries, regions or a country aren’t different much. In general,
they are divided into three groups: showing government policy (including:
national risk/ inflation, exchange rate, cost of capital in the nation, tax
policy, economic reformation, bilateral relationship, financial development,
ODA support, etc.); deciding economy (including: market’s size, economic
growth, opening trade, explorative resources, cost of labour, employee’s
capacity/human resource, technological level, facilities, geographic
distance, cultural distance,etc.) and institutional factors (including: stable
politics, quality of laws, corruption/bureaucratic, etc.). Three groups of
--7--
factors show the concepts representing for the base building the empirical
research model about influent factors of FDI and FDI’s distribution between
regions in Vietnam in chapter 3 and 4 of the dissertation.
Additionally, general results of empirical research about influent factors
of FDI in Vietnam in national and local levels allow defining research gap
in Vietnam.
1.6. Research gap in Vietnam
Base on the general of empirical research about influent factor of FDI
and FDI’s distribution between regions in Vietnam, it reveals that most of
studies haven’t conducted testing violations relating to the facts of changing
variance, autocorrelation and endogenous variables. They only limited at
initial results of the regression method according to Pooled Ordinary Least
Square, therefore the results haven’t been confident. Especially, there hasn’t
been any research model using delay variables FDI to study impacts to FDI
flows. While, the research results of Campos and Kinoshita (2003);
Carstensen and Toubal (2004); Bellak et al. (2008); and Anyanwu (2012)
proved that it’s a crucial variable and it should be included in model
studying attractive factors of FDI.
For the influent factors of FDI’s distribution between regions in
Vietnam, there are three relating research including Meyer and Nguyen
(2005); Nguyen and Nguyen (2007) and Dinh (2009). If these authors used
data from many different sources and inhomogeneous time, the dissertation
uses secondary data from the only source which is from General Statistic
Office in 2005-2013. Thus, the dissertation ensures the consistency and
reliability and updated date (especially Provincial Competitiveness Index –
PCI). That help regression results will have high reliability. In addition,
general results show that there hasn’t been research paying attention on
impacts of past information to FDI’s distribution between regions in
Vietnam. The testing results in chapter 4 prove that it is the essential
character in making decision of foreign investors in Vietnam.
--8--
1.7. Conclusion of Chapter 1
CHAPTER 2
THE CURRENT SITUATION ON FDI ATTRACTION IN
VIETNAM
2.1. Introduction
2.2. The current situation on FDI attraction in Vietnam
2.2.1. Current trend of Vietnam’s FDI
According to data from General statistics department (2014), Vietnam’s
FDI trend (both registered and implemented) increased from 1988 to 2013.
However the total implemented capital compared to registered capital is
very low (until end of 2013 the ratio is estimated to be 51.54%).
2.2.2. Vietnam’s FDI composition
With respect to industrial composition, the manufacture and processing
sectors are estimated to be dominant both in the number of projects and
capital attracted, having more than 54.76% the total of registered FDI in
Vietnam (8.725/15.932 projects).
With respect to investment partners, cumulative speaking, until
31/12/2013, Japan, Singapore, Korean, Taiwan and Virgin Islands (Britain)
are five countries that have the largest registered FDI capital in Vietnam.
With respect to regional composition, statistics show that among 63
provinces/cities, Ho Chi Minh city is attracting the most FDI ($32,403.2
mil), followed by Ba Ria – Vung Tau ($26,298 mil) and taken the third
place is Hanoi ($21,205.6 mil).
2.3. Comparing FDI attracted by Vietnam to that by other countries in
the region
In the area of ASEAN, until end of 2013 the ranking of countries
based on FDI attraction is as follows: the first place is Singapore ($63,722.3
--9--
mil), second is Indonesia ($18,444 mil), followed by Thailand ($12,649.7
mil), Malaysia ($11,582.7 mil) and Vietnam at the fifth place (with $8,900
mil).
2.4. Survey results on Vietnam’s investment environment:
The results from surveying 171 FDI firms in Vietnam shows 66.1% of
the firms agree that they chose Vietnam in comparison with other countries;
90.1% agree that Vietnam is a destination of ASEAN’s FDI; 62% of the
firms investing in Vietnam because of market seeking purpose; 86%
suggested that Vietnam investment environment has changed positively
ever since joining the WTO (this also shows the satisfactory with current
environment in Vietnam); 83.6% suggested that they will continue investing
in Vietnam and the next choices would be China and Cambodia.
2.5. Conclusions
CHAPTER 3
ANALYSING THE FACTORS AFFECTING FDI ATTRACTION
IN VIETNAM
3.1. Introduction
3.2. Hypotheses and model
Based on the 6 hypotheses given, theoretical research model of
determinants of FDI attraction in Vietnam is established as follows:
--10--
Figure 3.1: theoretical research model of determinants of FDI
attraction in Vietnam
Based on the summary of empirical researches in Chapter 1 and
Vietnam’s unique economic – social characteristics, the empirical research
model on determinants of FDI attraction in Vietnam is established as
follows:
∑
∑
(
∑
(
∑
)
)
And
∑
∑
∑
(
∑
(
)
Where:
+ i = 1,…, 24: represents 24 Asian nations;
+ t = 2000,…, 2012 : is an indicator of time;
+ FDI: Foreign direct investment attracted (USD);
)
--11--
+ Xi: a set of variables related to policy frameworks, including inflation
rate (Infla), exchange rate (ExchRa), domestic credit in private sector
(FinDev), official development assistance (ODA).
+ Yi: a set of variables related to economy, including local gross
domestic product (GDP), urban population (UrPop), direct exporting metal
(Resour), number of working labour (Labour), number of students in
vocational schools (HuCa) and number of landlines (Infras);
+ Zi: a set of variables related to institutional quality, including
corruption control index (Corrupt), regulation quality (Regul) and Law
evaluation indicator (Law).
+ VNt: a set of interactive terms between Vietnam and countries in
ASIA 24. These terms are the product of each independent variables and the
dummy variable (which receives 1 for Vietnam and 0 otherwise).
+ FDIit-1 or FDI_1: FDI’s first lag.
+ FDIVNt-1: the first lag of the interaction between FDI and the dummy
variable.
3.3. Data and research methodology
3.3.1. Variables
3.3.2. Data
The data on the dependent variable, FDI, are gathered from summary
statistics of UNCTAD during 2000 – 2012.
With respect to independent variables related to policy frameworks,
economics and institutional quality, the author collected from the source of
World Bank (during 2000 – 2012). Of those, Corrupt, Regul and Law are
ranked from 0 to 100 (with 0 as the lowest rank and 100 as the highest
rank).
3.3.3. Research method
In the empirical models established, in addition to other independent
variables, the first lag of FDI is considered an independent variable, and the
data used are panel data from 24 of Asia’s developing countries. Therefore
--12--
this is a dynamic panel data model. Thus, to estimate and test proposed
hypotheses related to determinants of Vietnam’s FDI attraction, differenced
GMM estimator (with fixed effects) is utilized.
3.4. Research results
3.4.1. Variables’ summary statistics
On average, during the research period, attracted FDI in ASIA 24 is
$8.820 mil, among which the highest value is $280,000 mil and the lowest
is -$4.55 mil2. For the independent variables, the ones related to policy
frameworks, averaged inflation rate is 7.36%, averaged exchange rate is
1,696.38 LCU/USD, averaged domestic credit rate for private sector
compared with GDP is 40.7% and the rate of ODA to GNI is 3.26%. For the
economic factors, averaged GDP is $294,000 mil annually with a growth
rate of 6.14%, averaged rate of urban population to total population is
46.2% and the regional rate of foreign trade is 88.28% of GDP. In addition,
the averaged rate of exporting ore and metal value to total exporting value is
more than 7.17% GDP. The averaged number of mobile phone registries on
100 people is more than 45 and the averaged number of vocational students
is 8,284,530. For the factors related to institutional policy, regulation quality
indicator gets the highest averaged point (40.2), followed by law indicator
(39.17) and lastly, corruption control (36.26).
3.4.2. Identify correlation coefficient matrix among variables
The majority of independent variables used (except for Infla, ExchRa,
Open and Corrupt) have correlation coefficients with FDI at significance
level less than or equals to 10%. Of those, the ones that have correlation
sign contradicting theoretical reasoning are FinDev, ODA, Open and
Resour. Furthermore, the correlation coefficients between FDI and GDP is
estimated to be highest (0.8478). About the correlation among independent
2
According to UNCTAD, whenever a nation has 1 of the 3 FDI flows (equity, returns for reinvestment and crossfirm debts) that has a negative value and there is not enough positive inflow, the FDI has a negative sign
(divestment).
--13--
variables, the majority of correlation coefficients among the policy
framework group and economic group variables are all small (less than 0.6),
with the exception of the correlation between GDP and ODA and HuCa
(close to 0.8). These coefficients reflect the close relationship between GDP
and ODA and number of vocational students. In contrast, for the factors
related to institutional quality the coefficients are high, with the highest
being the coefficients between Corrupt and Law (0.88). These results
confirm the existent of a multi-collinearity in the model. However, to reach
research goal, this violation is acceptable and the variables are still chosen.
3.4.3. Regression results
Table 3.7: Results from one step differenced GMM for current data
Variable
Infla
Model 1
0,0179
Model 2
-0,0071
Model 3
Model 4
-0,0155
-0,0155
-0,7287 -3,7990***
-3,8207***
ExchRa
-0,6071
FinDev
0,0142
-0,0163*
-0,0098
-0,0128
-0,1527*
0,1107*
0,1457**
0,1444**
1,5840**
1,5038**
1,5281**
0,0163
-0,0193
-0,0158
0,0438***
0,0459***
0,0479***
0,0405**
0,0474***
0,0483***
Infras
0,0128
-0,0002
-0,0196
HuCa
0,5114
0,8735
10,233
-0,0601
-0,1221
Regul
0,2545
0,2634
Law
0,2641
0,3598
-0,0278
-0,0194
ODA
GDP
UrPop
Open
Resour
Corrupt
FDI_1
InflaVN
0,3497***
0,0336
-10,375
FinDevVN
0,0855
ODAVN
0,9653
--14--
UrPopVN
-6,4973
OpenVN
0,9933
ResourVN
-32,9104
InfrasVN
-10,5608
CorruptVN
-27.3501
LawVN
-16,9958
FDI_1VN
24,4690
227
185
169
169
Wald Test
14,930
12,530
13,380
7,810
P-value
0,0000
0,0000
0,0000
0,0000
Sagan test:
31,530
37,230
33,730
38,860
P-value
0,012
0,241
0,384
0,188
Arellano-Bond test
0,460
-0,780
-0,890
-0,830
P-value
0,647
0,436
0,376
0,404
No. of observations
* : Pvalue <10% ; ** : Pvalue <5%; *** : Pvalue <1%
Table 3.8: Results from one step differenced GMM for past data
Variable
Model 1
Model 2
Model 3
Model 4
Infla_1
-0,0329**
-0,0303**
-0,0251*
-0,0391**
ExchRa_1
0,1314
-0,9026*
-1,5651
-2,6318
FinDev_1
0,0285***
0,0082
0,0101
0,0340*
-0,1159
-0,1255*
-0,0897
-0,0149
-0,8610*
-0,6133
-0,5192
UrPop_1
0,1457*
0,0202
0,0866
Open_1
0,0188*
0,0161
0,0332**
Resour_1
-0,0122
-0,0104
-0,0065
Infras_1
0,6068***
0,6192***
0,5374*
HuCa_1
0,0883
0,7062
0,6349
0,0503
0,0112
ODA_1
GDP_1
Corrupt_1
--15--
Regul_1
Law_1
FDI_1
0,5103***
-0,0427
-0,3936
0,0542
0,4246
-0,4159
-0,0579
-0,1978
InflaVN_1
-0,1756
FinDevVN_1
-0,1576
ODAVN_1
-0,2083
UrPopVN_1
2,1666
OpenVN_1
-0,0393
ResourVN_1
-0,2489
InfrasVN_1
-15,124
CorruptVN_1
-3,0109
FDIVN_1
35,952
230
188
159
146
18,59
11,71
7,77
4,15
P-value
0,0000
0,0000
0,0000
0,0000
Sagan test:
19,430
58,610
64,400
88,600
0,195
0,001
0,000
0,000
-0,430
-1,740
-1,720
-2,050
0,664
0,082
0,085
0,040
No. of observations
Wald Test
P-value
Arellano-Bond test
P-value
* : Pvalue <10% ; ** : Pvalue <5%; *** : Pvalue <1%
In table 3.7, the results for one-step differenced GMM for current data
of model 3 and 4 indicate that most of the variables related to policy
framework group and economic group have significant coefficients.
Specifically, at 1% level the significant variables are ExchRa, Open and
HuCa, at the 5% level GDP is tested to be significant. Different from OLS,
the first lag of FDI in this case is not significant even at 10%. In addition,
the slope differences between Vietnam and the 23 countries in the sample
are not significant at the 10% level (the interaction terms of ExchRaVN,
--16--
GDPVN, HuCaVN and RegulVN is excluded for causing multicollinearity).
With respect to model’s goodness-of-fit when using differenced GMM,
for model 3 and 4, the Sargan and Arellano-Bond tests are both insignificant
at the 10% level (P-value of those are all larger than 0.1) so that we cannot
reject the null hypotheses of exogenous instruments and serial correlation.
This shows that GMM method is suitable for fitting the data. Additionally,
Wald test results for both models have P-value smaller than 0.01,
confirming that the models are suitable for explaining the impact on FDI.
Similar reasoning are used to justify the use of past data. Unlike current
data, there are only have two variables, Infla_1 and Infras_1 that have
significant impact on FDI to ASIA 24 in general and Vietnam in specific (at
10% level). FDI_1 is tested to not have significance in impact on FDI at
10%. Aside from the interaction terms, ExchRaVN_1, GDPVN_1,
HuCaVN_1, RegulVN_1 and LawVN_1 is excluded for causing multicollinearity. Testing results show that similar to the case of current data, the
interaction terms given are all insignificant at the 10% level. For goodnessof-fit, Wald test results for both models have P-value smaller than 0.01,
confirming that the models are suitable for explaining the impact on FDI.
However this is not reliable, since the results from Sargan and AreallanoBond of model 3 and 4 are all insignificant at 10% (P-value of these tests
are both smaller than 0.1). Accordingly, testing results are sufficient to
reject null hypotheses of exogenous instrument variables and second order
serial correlation. This means differenced GMM estimator is not suitable for
past data of independent variables.
3.4.4. Hypotheses testings
Results of differenced GMM estimating method indicate that 3 out of 6
hypotheses cannot be rejected at the 10% level, including the policy
frameworks, market seeking and resource seeking purpose.
3.5. Conclusion
--17--
CHAPTER 4
ANALYSES OF FACTORS INFLUENCING FDI DISTRIBUTION IN
VIETNAM
4.1. Introduction
4.2. Hypotheses and research model
From the five given hypotheses, theoretical research model of factors
influencing FDI distribution across Vietnam’s regions is established as
follows:
Figure 4.2: Theoretical research model of factors influencing FDI
distribution across Vietnam’s regions
Based on summary from empirical researches done by Chenga and
Kwan (2000), Sun et al. (2002) and Chen (2009) for China, empirical
research model of factors influencing FDI distribution across Vietnam’s
regions is consolidated as follows:
∑
∑
(
And
)
--18--
∑
∑
(
)
Where:
+ i = 1,…, 63: represents Vietnam’s 63 provinces/cities;
+ t = 2005,…, 2013 : is an indicator of time;
+ FDI: Foreign direct investment (registered) ($mil) ;
+ Xi: a set of variables related to local economic management capability,
including inflation rate (Infla) and provincial competitiveness index (PCI);
+ Yi: a set of variables related to economy, including local gross
domestic product (GDP), urban population (UrPop), direct exporting metal
(Resour), number of working labour (Labour), number of students in
vocational schools (HuCa) and number of landlines (Infras);
+ Dummy_tt_HN: Dummy variable which is 1 for provinces/cities
within 100 km2 from Hanoi and 0 otherwise;
+ Dummy_tt_HCM: Dummy variable which is 1 for provinces/cities
within 100 km2 from Ho Chi Minh city and 0 otherwise;
+ FDIit-1 or FDI_1: FDI’s first lag.
4.3. Data and research methodology
4.3.1. Data
Data on 63 provinces of Viet Nam during 2005 – 2013 were gathered
from the yearbooks of General statistics department and the yearbooks of
provinces/cities. From original 64 provinces/cities, Ha Tay and Hanoi were
merged in 2007, thereby these regions’ data is incorporated under the name
of Hanoi in the period. Other regions are coded from 1 to 63, from Hanoi to
Ca Mau.
4.3.2. Research methodology
With similar reasoning as in Chapter 3, regression models for factors
impacting FDI distribution in Vietnam will also be done for both current
and past data of independent variables.
--19--
Additionally, the first lag of FDI is used as an independent variable
influencing foreign investors’ decisions, and data used are panel data from
63 provinces during 2005 – 2013, therefore in theory this is a dynamic panel
data regression. Thus, to estimate and test proposed hypotheses related to
factors impacting FDI distribution in Vietnam, differenced GMM estimator
(with fixed effects) is utilized, similar to that in estimating and testing for
FDI determinants in Chapter 3.
4.4. Research results
4.4.1. Variables’ summary statistics
On
average,
during
the
research
period,
registered
FDI
at
provinces/cities reached $mil 345.15 per annum, with a standard deviation
of 1,039.68. With respect to variables related to local economic
management, the averaged growth rate of consumer index compared to last
period is about 107%, provincial competitiveness index is higher than 56.3
points and the leading were regions in the South Eastern and the Cuu Long
River delta. As of economic variables, averaged local GDP is 34,192.8
billion VND, with annual growth rate of 11.19%. Urban population is more
than 409,000 on average, concentrating mostly at the South Eastern and the
Cuu Long River delta. Averaged direct export value is $ 1,263,244,000.
Labour force in local businesses has the maximum of 4,000.9 thousands and
on average is 768.2 thousands. The number of students in vocational
schools is more than 8.479. The number of landlines is reported to be close
to 177,000. Overall the South Eastern and the Cuu Long River delta are the
most prominent areas in all surveyed variables.
4.4.2. Computing the correlation coefficient matrix among variables
In comparison with the dependent variable FDI, the correlation
coefficients of independent variables are all quite small (less than 0.6). In
contrast to other variables, the sign of the coefficient of Infla is not as
expected. Additionally, the coefficients of the rest of the variables are
relatively small (the largest being that between GDP and Open, more than
--20--
0.85). These signs may indicate a multi-collinearity in the model. However,
to reach research goal, this violation is acceptable and the variables are still
chosen.
4.4.3. Regression results
According to the two-step GMM estimating with current data (table
4.6), the variables tested to be significant at the 1% level are Infla and
Dummy_tt_HCM, at 5% are UrPop, HaCa and Dummy_tt_HN, at 10% we
have only Labour. Therefore, the distribution of FDI across Vietnam’s
regions is affected by inflation rate, urban population, labour force, number
of vocational students. Additionally, the trend of FDI convergence at two
biggest cities, Hanoi and Ho Chi Minh, is confirmed. In contrast to current
data, testing results for past data only indicate the significance of first lag of
Infla_1 (at 1% level). This shows that FDI distribution is solely impacted by
past information of inflation. Furthermore, unlike OLS, differenced GMM
estimator shows insignificant FDI_1 coefficient even at the 10% level.
With respect to model’s goodness-of-fit when using differenced GMM,
in both cases of current and past data, the p-values of Wald tests are smaller
than 1%, so that we can reject the null hypothesis of jointly insignificant
coefficients. This shows that GMM method is suitable for explaining the
impact on FDI. On the other hand, the results of Sagan and Arellano-Bond
GMM method for three models with both types of data are significant at the
5% level. There is not enough evidence to reject the null hypotheses of
exogenous instrument variables and no serial correlation, which mean the
GMM estimators are suitable for analyzing the data. In specific, the testing
results of independent variables’ impact on FDI are unchanged in all three
models, showing the stability and reliability of the estimators. Moreover,
the fact that GMM estimating method is appropriate for the two data types
confirms that FDI distribution is affected by both current and past
information.

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