論文

Determinants of Inward Foreign Direct
Investment in Vietnam
Nam Hoai TRINH & Quynh Anh Mai NGUYEN

Ⅰ . Introduction
In recent years, the empirical analyses of the relationship between Foreign
Direct Investment (FDI) and its determinants have received considerable
attention in response to the dynamics of the investment climate (Asiedu
2002, 107; Bakar and Sern 2005, 14; Kariuki 2015, 346). A good understandingof the determinants of FDI in an economy by examining the behavior of theinvestment function is significant for the formulation and implementation ofan effective investment policy; with general agreement that FDI can promotetechnology spillovers, assist human capital formation, contribute to international
trade integration, create a more competitive business environment andstrengthen enterprise development. All of these contribute to higher economic
growth, which is an important tool for reducing poverty and providing theplatform for sustainable development in developing economies (Thaddeus andYadirichukwu 2013, 41; Brima 2015, 123).
Vietnam has been reasonably successful in attracting FDI since theintroduction of the reform policy known as Doi Moi in 1986. In 1987, the first
Law on Foreign Investment was passed as the framework for the businessactivities of foreign investors in Vietnam. This law has been amended four times
since then, and the newest law was promulgated in 2006. These adjustments
are towards a more comfortable and reasonable environment for both domestic
and foreign firms operating in Vietnam. According to the General Statistics
Office of Vietnam (GSO), from 1988 to the end of 2014, total FDI inflows toVietnam were approximately US$ 291 billion in terms of commitments, while
the implementation capital inflows were US$ 124 billion. During this period,
inward FDI to Vietnam has played a very important role, not only in providing
investment capital but also in promoting export activities as well as introducing
new labor and management skills, transferring technologies and creating job

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opportunities.
The objective of this study is to examine the main determinants of FDI
inflows to Vietnam by applying the time-series regression technique. It differsfrom existing studies in the following aspects. First, it employs a more updated
and reliable dataset on inward FDI and relevant variables from 1990 to 2013
in Vietnam. Second, along with the traditional determinants, the study adds tothe literature by specifically investigating the relationship between FDI and its
other crucial determinants such as interest rate, exchange rate, external debt,
etc.
The remainder of the paper is organized as follows. Section 2 gives an
overview of inward FDI in Vietnam in terms of trend, sector, region andcountries of origin. Section 3 reviews the literature on the key determinants of
FDI inflows to the host country. Section 4 discusses the research methodology
and data used in the regression analysis. The empirical results are presented
in section 5. Finally, section 6 draws the conclusion and proposes policies andissues for future research.

Ⅱ . Overview of FDI in Vietnam
As late for FDI compared to other countries in the region, FDI in Vietnam
has a relatively short history of development. After enduring long economic
instability, Vietnam embarked on a path of reform, known as “Doi Moi” shifting
its economy in the direction of capitalism towards a market economy following
the passage of the first Law on Foreign Direct Investment in 1987. Throughout
the twenty-eight years since then, Vietnam has attracted a substantial andgrowing amount of FDI. However, the increasing trend has not been consistent.
As shown in Figure 1, from 1990 to 1996, total new FDI commitments
increased by double-digit growth rates annually. Nevertheless, there has beena decline since 1997 due to considerable negative impacts of the Asian financial
crisis in 1997. However, the FDI inflows began to rise again as countries in theregion recovered from the crisis, and the United States-Vietnam Bilateral Trade
Agreement was signed in 2001. Specifically, the situation has changed muchsince Vietnam became an official member of the WTO at the beginning of 2007.
According to the General Statistics Office of Vietnam (GSO), in 2008 FDI inflows
into Vietnam achieved a record high of $71.7 billion of registered capital after52

Determinants of Inward Foreign Direct Investment in Vietnam

twenty years of issuing the first Law on Foreign Direct Investment. However,during the period 2009-2014, the registered FDI decreased rapidly because of
the global financial and economic crisis.
Figure1: FDI inflows into Vietnam, 1990-2014

Source: Statistical Yearbook of Vietnam, 2014.

Table 1: FDI inflows into Vietnam by sector, 1988-2014
Sector

FDI inflows by sector(%)

Manufacturing

55.95

Real estate activities

19.10

Construction

4.51

Accommodation and Food service activities

4.43

Electricity, gas, steam and air conditioning supply

3.87

Information and communication

1.63

Wholesale and retail trade; repair of motor vehicles and motorcycles

1.59

Transportation and storage

1.49

Agriculture, Forestry and Fishing

1.47

Arts, entertainment and recreation

1.44

Mining and quarrying

1.34

Professional, scientific and technical activities

0.71

Human health and social work activities

0.69

Water supply, sewerage, waste management and remediation activities

0.53

Financial, banking and insurance activities

0.53

Education and training

0.32

Administrative and support service activities

0.08

Other service activities

0.30

Source: Statistical Yearbook of Vietnam, 2014.

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As shown in Table 1, there is an uneven distribution of FDI in the industrial
sector related to the number of investment projects and the amount ofregistered capital in the period 1988-2014. In terms of the industrial sector, over
54% of the number of projects and 56% of registered capital were invested in
manufacturing, around 40% to service and the rest to agriculture. Within the
manufacturing, during the early part of 1990s, the majority of FDI was in oiland mining sector, but recently, light and heavy industries have dominated thefield. In addition, the share of FDI in agriculture now is increasing comparedwith that in the 1990s. In the service sector, the real estate activities accounted
for the largest proportion, making up more than 19% of total registered FDI. A
different point is that in the early history of the FDI in Vietnam, in the service
sector, there was no investment in construction of industrial zones, offices andapartments, but now these fields are started attracting significant portion of
FDI inflows.
Table 2 presents the top 10 countries of origin of FDI inflows into Vietnam
during 1988-2014. The inward FDI in Vietnam is dominated by regional
investors, accounting for over 70% of the total number of investment projects,
registered capital and implemented capital. The top five investors were South
Korea, Japan, Singapore, Taiwan, and British Virgin Islands. Although theUnited States is a late comer to Vietnam, the inward investment inflow has
increased significantly since 2001, after the conclusion of the Bilateral Trade
Agreement, and now it is in the seventh position of investment ranking. The
investments from European countries remained small, accounting for about
14% of the number of projects, 19% of the registered capital and 20% of theimplemented capital.
In terms of regional distribution of FDI inflows, during the period 1988-2014,
all sixty three provinces in Vietnam received FDI. However, the distributionsof FDI across provinces are very much uneven. As shown in Figure 2, theSouth East region (covering Ho Chi Minh City and its surrounding provinces)accounted for the largest share of FDI, making up more than 54% of thenumber of projects and 43% of registered capital. In the North, Hanoi andneighboring provinces were the second destinations of FDI inflows, accounting
for about 30% of the number of investment projects and 25% of registeredcapital. By contrast, the Central Highlands attracted less than 1% of the FDI
inflows. Specifically, Ho Chi Minh City received over US$38 billion in FDI

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in the period from 1988-2014, while Thai Nguyen province, the tenth largest
destination for FDI, received just over US$6.9 billion. Conversely, the smallest
10 provinces in terms of FDI inflows jointly accounted for only US$526 million
during the same period.
Table 2: Top 10 countries of origin of FDI inflows into Vietnam, 1988-2014
Country of origin

FDI inflows by country of origin (%)

South Korea

14.93

Japan

14.77

Singapore

13.03

Taiwan11.27

British Virgin Islands

7.12

Hong Kong

6.17

United States

4.35

Malaysia

4.28

China

3.16

Thailand

2.67

Source: Statistical Yearbook of Vietnam, 2014.

Figure 2: FDI inflows into Vietnam by region, 1988-2014

Source: Statistical Yearbook of Vietnam, 2014.

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Ⅲ . Literature review
It is argued that the attractiveness and absorptive capacity of FDI by thehost country depend on various factors. According to UNCTAD (1998), foreign
investors who aim at exploring new markets would examine the market
development, access to the international trade from host country as well as themarket structure of host country before investing in any country. In addition,
the resource-seeking FDI would be determined by cost of raw material, labor
cost and availability of skilled worker, infrastructure development, etc. whereas
the efficiency-seeking FDI is driven by creating innovative or new bases ofcompetitiveness for businesses.
In the following headlines, some of the main determinants and their impacts
on inward FDI will be discussed in the light of earlier studies.
3.1. Market growth
The growth rate of an economy or the absolute annual changes of GDP may
be used to measure the market growth. The more output growth indicatesthe more possible investment induced (Thaddeus and Yadirichukwu 2013,43). It is obvious that a well-functioning economy gives the investors higher
profitable prospects and capabilities of the market. Thus, larger markets should
be favorable for capturing the potential benefits of economies of scale (Ledin
and Strömberg 2012, 5). The importance of output growth has been confirmed
in many previous empirical studies (Nunnenkamp 2002, 17; Arbatli 2011, 10;
Alavinasab 2013, 43). Therefore, GDP growth should be considered a key
element in attracting FDI inflows, even though it is not the only factor affecting
FDI.
3.2. Market size
The market size which is one of the most important determinants of FDI isoften measured by GDP per capita. Various empirical studies have shown thatan increase in GDP per capita is associated with increasing inward FDI into
host economies (Mukhtar et al. 2014, 29; Erdogan and Unver 2015, 85; Voka
and Dauti 2015, 37). Rising income levels are an indicator for the expansion
in the market size and purchasing power (Zenasni and Benhabib 2013, 303).
The general implication is that host countries with higher GDP per capita will56

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provide more and better chances for the industries to exploit their ownership
advantages and thus, will attract more FDI, particularly for those FDI inflowsthat are market-seeking.
3.3. Trade openness
Trade openness refers to the degree to which countries or economies permitor have trade with other countries or economies. It is generally measured by
the ratio of imports and exports to the GDP. Jordaan (2004) states that trade
openness may have a different impact on the inflows of different types of
FDI. When investments are market-seeking, trade restrictions (and thus lessopenness) can have a positive effect on FDI. The reason derives from the “tariff
jumping” hypothesis, which argues that foreign enterprises that seek to serve
local market may decide to establish subsidiaries in the host country if it isdifficult to export their products to the country. In contrast, FDI firms engaged
in export-oriented investments may prefer to locate in a more open economy
since the increased imperfections that associate with trade protection generally
lead to higher transaction costs related to exporting. Liargovas and Skandalis(2012), Chawla and Rohra (2015), Kariuki (2015), Ngendakumana and Kaseke(2015) reveal trade openness is one of the key factors that have strong positive
impact on FDI inflows whereas Schmitz and Bieri (1972) obtained a weak
positive relationship.
3.4. Interest rate
Interest rate is considered as the cost of capital when foreign firms want
to use the financial resources in the host country; this is the entry costof production activities and businesses (Hoang and Bui 2015, 216). Localborrowings in the host country might be enhanced when interest rates arelikely lower than those in the home country or elsewhere. Thus, interest rateis also an important element of FDI inflows. Çevis and Çamurdan (2007) foundthat FDI is related positively with interest rates in developing countries andtransition economies. Payaslioglu and Polat (2013) by using monthly timeseries data for the period from 2004-2012 in Turkey also revealed that interest
rate has positive and significant effect on FDI inflows. Conversely, Hoang and
Bui (2015) investigate that the real interest rate has a significant negative
relationship with FDI inflows in ASEAN countries over the period from 1991 to

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2009. The rise in real interest rates encourages capital cost to increase, it also
indicates that the financial risks exist; therefore it will limit FDI inflows to theregion.
3.5. Inflation rate
Representing the changes in the general price level, inflation is considered asa proxy of the macroeconomic stability. The higher the rate; the less favorable
the economic climate for investments since more time, money and efforts areneeded by foreign investors to adapt to the increasing price level (Lo et al.
2013, 41). Markets with a volatile and unpredictable inflation rate will create
uncertainty in setting the price and profitability rate to market-seeking FDI
firms and therefore, discourage their activities (Kamal et al. 2014, 258). By its
influence on local currency devaluation, high inflation rate diminishes the real
return on investment. Consequently, a low and predictable inflation rate is
expected to stimulate the FDI flows into the host country and vice versa.
3.6. Infrastructure
Infrastructure consists of many dimensions ranging from roads, railways,
ports, electricity and water supplies, and telecommunication systems toinstitutional development such as accounting, legal services, etc. According toMarr (1997), poor infrastructure may be seen as both an obstacle and a chance
for FDI firms. It is generally considered as one of the main constraints formost low-income economies. However, foreign investors also recognize thepotential for attracting FDI inflows if local governments allow more significant
foreign participation in the infrastructure sector. Moreover, Alavinasab (2013)stated that well-developed infrastructure improves the capabilities of domestic
industries, promotes the inter section relationship in the economy and supports
to generate the conditions for effective distribution of goods and services. The
previous studies of Sahoo (2006), Kamal et al. (2014), Sfar (2015) and Ahmad,
Ismail and Nordin (2015) also reveal that countries with good infrastructure
facilities attract more foreign investments; and thus have positive effects on
inward FDI. According to Asiedu (2002), the number of telephone lines per
1,000 inhabitants is a standard measurement in the literature for infrastructure.
Considering the availability of public data in Vietnam for a long period oftime required by our study, this variable is also selected as a proxy for the58

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development of infrastructure.
3.7. Exchange rate
There are various ways the exchange rate can impact on the inward FDI.
When exchange rate increases in terms of host country currency as comparedwith home country currency, it results in devaluation of host country currency.
As host country currency depreciates, the purchasing power of the foreign
investors in local currency is enhanced, and therefore, it encourages FDI firms
to invest in host country’s assets (Mukhtar et al. 2014, 30). Moreover, Culem(1998) suggests that exchange rate affects relative labor cost. A decline inhost country currency allows home country investors to hire more labor fora certain amount of home country currency. As a result, there is a significant
increase of FDI flows into the host country.
3.8. Government expenditure
Edwards (1990) and Ancharaz (2002) found that government consumption
has a negative impact on the FDI inflows to host economy. The reason for thisnegative relation is that a large size of the government spending can create
opportunities for misuse of funds by government officials. In addition, big
government may crowd out the private investment (including FDI) in importantsectors of the economy. It also generates a complex bureaucratic structurethat makes the investment environment unattractive to inward FDI and raises
the possibility of passage of higher tax rates in the future (Onyeiwu 2003, 7;
Filipovic 2005, 21). By contrast, Goodspeed et al. (2007) and Samargandi et al.
(2015) state that government spending may crowd in the private investment
since a higher level of government expenditure should translate into provisionof more public goods, especially in education, health care and infrastructurethat should encourage production and growth.
3.9. Human capital
Foreign investors are concerned about the quality of the labor force inaddition to its cost. A more educated workforce can handle machines andnew technologies faster and more efficiently, and is therefore generally moreproductive (Sichei and Kinyondo 2012, 6; Hoang and Bui 2015, 216). Noorbakhsh,
Paloni and Youssef (2001), and Sfar (2015) reveal that human capital is a

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statistically significant determinant of FDI inflows into the host country.
Therefore, higher level of human resource is a good indicator of the availabilityof skilled labors, which tends to promote the locational advantages of a country
as well as ensures higher returns on investments. According to O'Meara (2015),
the number of individuals who have attained secondary-level education is used
as a proxy for human capital.
3.10. External debt
The level of external debt indicates the net external assistance to hostcountry in the form of loans. Khan and Hassan (2013) suggested that external
debt has a negative effect on the inward FDI in Malaysia over the period 19802010. In addition, Chopra (2003) stated that the level of external indebtedness
shows the burden of repayment and debt servicing to the economy, whichmakes the country less attractive to foreign investors.

Ⅳ . Data description and methodology
In this study, we employ a multiple regression model to estimate therelationship between inward FDI and its potential determinants in Vietnam.
Annual time-series data ranging from 1990 to 2013 were collected for various
variables that have been discussed in the literature review section such as
FDI, GDP growth rate, GDP per capita, trade openness, interest rate, inflation
rate, etc. The data were obtained from General Statistics Office of Vietnam andWorld Development Indicators published by the World Bank for Vietnam. In
line with previous studies (Wafure and Nurudeen 2010, 27; Rasheed et al. 2012,
204; Thaddeus and Yadirichukwu 2013, 44; Brima 2015, 127) that have identified
the role of key factors in explaining the behavior of FDI inflows to host country,
the model for this study is specified as follows:
Ln(FDIt) =β0 +β1 Ln(GGRt) +β2 Ln(GPCt) + β3 Ln(TOt) + β4 Ln(INTt) + β5 Ln(INFt) +β6 Ln(TELt) +β7 Ln(EXCt) +β8 Ln(GCt) +β9 Ln(SECt) +β10 Ln(DEBt) +μt

Where β1 , β2 ,…, β10 are coefficients of elasticities; Ln represents the natural

logarithm of variables; and μ is the error term,
FDI=	Foreign Direct Investment inflows in Vietnam in terms of registeredcapitalGGR = GDP growth rate

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GPC = GDP per capitaTO=	Trade openness (sum of Exports and Imports as a percentage of
GDP)

INT

= Interest rate

INF

= Inflation rate

TEL = Telephone lines (per 1,000 people)
EXC = Exchange rateGC

= Government consumption (as a percentage of GDP)

SEC

= Secondary education, general pupils (as a share of Population)

DEB = External Debt
The use of log-linear specification to estimate the coefficients of variables
has several reasons. First, the relationship between these different variables
is not linear. Second, in the case of log model, the value of coefficients could
be interpreted in terms of percentage or elasticity rather than unit. Moreover,
we expect that FDI has positive relation with host country’s market size,
market growth, openness of the economy to international trade, infrastructuraldevelopment, and human capital while FDI is expected to have negative
relationship with interest rate, inflation rate, exchange rate, government
spending, and external debt.
Regarding the methods of estimation for time-series data, the unit root test is
firstly applied to examine the stationarity condition of the variables (Thaddeus
and Yadirichukwu 2013, 44). Second, once the stationarity properties of theindividual series are established, linear combinations of the integrated series
are tested for cointegration. The cointegrated relationship between variables,in general, is interpreted as their long-run equilibrium. To conduct the
cointegrating test, this study employs the Johansen cointegration methodology.

Ⅴ . Empirical results
5.1. Unit root test
To avoid the problem of spurious regression, we need to examine theproperties of stationarity for each series. In this study, unit root test would beapplied to test for the stationarity of each variable. Since the original unit root
test of Dickey-Fuller (DF) test has the weakness of presence of autocorrelationin the disturbance term, we employ the modified DF test or the Augmented

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Dickey-Fuller (ADF) test to estimate the order of integration of each variable.
Table 3 presents the ADF unit root test results for the variables involved in
the analysis. It has been observed that the null hypothesis of presence of unit
root or non-stationarity has been rejected for all the first difference variables
specified. Our findings indicate that all variables exhibit integrated order oneor I(1). This means that the series are non-stationary in level but stationary
in first-differences. Therefore, the implication is that there is a possibility of
having a cointegrating vector of which coefficient can directly be interpreted as
the long-term equilibrium.
Table 3: Augmented Dickey-Fuller unit root test results
SeriesLevel

First Difference

Without Trend

With Trend

Without Trend

With Trend

LnFDI-1.568-2.244-4.009***-3.866**

LnGGR-2.301-3.185-4.237***-4.227**

LnGPC-1.003-1.523-5.881***-5.673***

LnTO-2.150-1.368-10.209***-9.888***LnINT-2.033-1.447-4.899***-5.159***LnINF-2.570-2.663-3.280**-3.557*

LnTEL-2.561-0.198-3.170**-4.473***

LnEXC-0.532-1.916-9.219***-8.466***

LnGC-0.733-1.078-8.709***-8.280***

LnSEC-1.554-2.497-4.089***-4.177**

LnDEB-2.264-0.453-4.482***-5.464***

Source: Author’s calculation.
Note: *, ** and *** indicate significance at the 10%, 5%, and 1% levels, respectively.

5.2. Cointegration test
The cointegrating relationship between the variables is tested by employing
the Johansen Maximum Likelihood method. The test is needed to find the longterm relation between a group of variables, particularly in the case that theseries are non-stationary at level. The prerequisite for the cointegration testis that each series has to be integrated of the same order. According to theresults of unit root test in Table 3, all variables exhibit integrated order one orI(1). Therefore, we will examine the long-term relationship by a cointegration
test.
In this study, Johansen trace test and maximum eigenvalue test are applied

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to check whether there exists a cointegration relationship between thevariables of interest. Results of these tests are shown in Table 4 which provides
the number of cointegrating vectors.
Table 4: Johansen cointegration test results
Hypothesized Number of
Cointegrating Equation(s)None*

Eigenvalue

Trace Statistics

5% Critical Value-

664.565277.71

At most 1*

0.9998474.078

233.13

At most 2*

0.9979332.359

192.89At most 3*

0.9847236.236156.00

At most 4*

0.9272175.963

124.24

At most 5*

0.9230117.006

94.15

At most 6*

0.830976.133

68.52

At most 7*

0.713847.356

47.21

At most 8

0.627424.652

29.68

At most 9

0.4896

9.184

15.41

At most 10

0.3280

0.043

3.76

Source: Author’s calculation.
Note: * denotes rejection of the null hypothesis at the 5% significance level.

As presented in Table 4, the trace test and maximum eigenvalue test imply
the existence of 8 cointegrating vectors at the 5% level of significance. Thisfinding confirms that there is a long-run relation among FDI, GDP growth rate,
GDP per capita, Trade openness, Interest rate, Inflation rate, Telephone lines,
Exchange rate, Government consumption, Secondary education and External
Debt.
The results regarding long-term relationship between FDI and its
determinants are presented in Table 5. GDP growth rate shows a positive andstatistically significant relationship with FDI inflows in Vietnam. Particularly,
a 1% increase in the rate of GDP growth will lead to about 0.4% rise in FDI
inflows. This result is consistent with the findings of Nunnenkamp (2002),
Arbatli (2011), and Alavinasab (2013). It is obvious that Vietnam, with arapidly growing economy, provides relatively better opportunities for foreign
investors in making profits. A high rate of economic growth is an indicator ofdevelopment potential.
However, our findings show that GDP per capita has an insignificant effect

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on FDI inflows with an unexpected sign. Consistent with the findings of Asiedu(2002) and Akin (2009), this result suggests that FDI is taken into account thesize of market in Vietnam not in per capita basis but rather in aggregate size.
Table 5: Long-run regression results
Variable

Coefficient

Std. Error

t-Statistics

Prob.

LnGGR

0.3950*0.2150

1.84

0.066

LnGPC

-0.84620.7504

-1.13

0.259

LnTO

4.1078***1.3883

2.96

0.003

LnINT

0.28410.6421

0.44

0.658

LnINF

-0.8947***

0.1937

-4.62

0.000

LnTEL

-0.9540***0.2680

-3.56

0.000

LnEXC

3.8311**1.5407

2.49

0.013

LnGC

-6.4177***

1.9002

-3.38

0.001

LnSEC

3.9608***0.9621

4.12

0.000

LnDEB

3.2150***0.5092

6.31

0.000

R-squared = 0.8962

Adjusted R-squared = 0.8821

Source: Author’s calculation.
Note: *, ** and *** indicate significance at the 10%, 5%, and 1% levels, respectively.

Openness to trade including imports and exports has a positive andstatistically significant influence on FDI inflows. This conforms to both
economic and statistical expectation. This means that a decrease in the levelof restrictions imposed on trade exchanges tends to enhance FDI inflows into
the host country. Demirhan and Masca (2008), Ranjan and Agrawal (2011), andKamal et al. (2014) also found a strong positive relationship between trade
openness and FDI. A significant portion of imports of Vietnam consists of highly
capital-intensive products, fuel and raw materials used for domestic production
which help to expand the country’s production capacity. Whereas the demandfor imports has been increasing since 1990, Vietnam is also emerging as animportant exporter to the international market such as apparel and clothing
accessories, rice, fishery products (Anwar and Nguyen 2011, 43). Additionally,
Vietnam has widened its export markets from traditional trading partners
such as Japan, Korea, and other Asian countries to Australia, the United States,
Canada, Germany, and France.
The estimation results also reveal that interest rate has a statisticallyinsignificant effect on inward FDI with an unexpected positive sign. It indicates64Determinants of Inward Foreign Direct Investment in Vietnam

that interest rate does not affect the FDI inflows in Vietnam during this period.
By contrast, the coefficient of inflation rate is negative and statisticallysignificant at the 1% level of significance. It also indicates that a 1% rise ininflation rate tends to decrease FDI inflows by 0.89%. Consistent with theprevious study of Thaddeus and Yadirichukwu (2013), the high inflation rate
devalues domestic currency and raises the cost of production such as wages,
cost of raw material, land prices and cost of capital. As a result, it erodes thereal return on investment and discourages FDI in countries with high inflation
rates.
Telephone lines are found to have a negative and statistically significant
relationship with FDI. This unexpected sign might be derived from theunavailability of annual data for mobile phone subscribers in Vietnam thatshould be included in this proxy. By the end of 2014, the number of telephone
subscribers nationwide was 142.5 million, which included approximately 136
million mobile phone subscribers and only 6.4 million fixed telephone lines(GSO, 2014). Another possible reason is that this measure only captures theavailability and not the reliability of the infrastructure (Asiedu 2002, 111).
The effect of exchange rate on FDI inflows in Vietnam is positive andstatistically significant at the 5% significance level. It exhibits that FDI will
increase by about 3.83% if exchange rate increases by 1%. This result is inline with our expectation that a depreciation of exchange rate enhances hostmarket’s competitiveness due to lower cost of production and promotes export
growth, and thus it provides more favorable conditions for FDI inflows in
Vietnam. Exchange rate regime of Vietnam is officially described as a “managed
floating regime” and yet has some characteristics of a crawling peg, with asteady pace of devaluation against the U.S. dollar (Nguyen and Nguyen 2009,139).
Moreover, the empirical findings show that government consumption has
a negative and statistically significant impact on the inward FDI in the caseof Vietnam. Its coefficient of elasticity also reveals that FDI inflows are more
responsive to government spending than other variables of interest. This
result might be derived from the ineffectiveness of Vietnamese government
expenditure, specifically in infrastructure, education, etc. Consistent with thefindings of Edwards (1990) and Ancharaz (2002), recent economic reforms byboth developed and developing countries are meant to reduce the relative size

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of government to make it more effective through better remuneration packages.
Therefore, the smaller a government is, the more efficient it is perceived tobe, thus creating a more favorable environment for both domestic and foreign
firms operating in the host country’s market.
Secondary education as a proxy for human capital has a positive andstatistically significant relation with the FDI inflows at the 1% significancelevel. It implies that a 1% rise in secondary education will lead to about 3.96%
increase in inward FDI. An educated labor force has been recognized as animportant determinant of FDI inflows in Vietnam, especially when firms are
efficiency seeking. Sfar (2015) also suggests that a higher level of education in
the workforce can promote higher levels of FDI.
Lastly, external debt is found to have a positive and statistically significant
effect on inward FDI. The possible reason for this unexpected sign is that
Vietnam’s economy is characterized by low levels of savings. Inflows of external
debts and external aids support the economy to invest more than its domestic
saving. This also might help the economy to establish projects necessary for thedevelopment and growth of the economy (Ali 2013, 185). As the development of
infrastructure, construction of heavy mechanical industries and other important
industries often require huge financial resources; external loans can assist
Vietnam to establish these overheads for the economy, thereby creating an
attractive environment for foreign investors.

Ⅵ . Conclusion
It has been acknowledged that FDI brings benefits to the recipient
countries through providing capital, foreign exchange, modern technology
and also narrows the gap between domestic savings and investments (Azamand Lukman 2010, 41). This study investigated the key determinants ofinward FDI in Vietnam by using time-series data from 1990 to 2013. The
empirical results reveal that GDP growth rate, trade openness, exchange rate,secondary education as a proxy for human capital and external debt encourage
FDI inflows in Vietnam while inflation rate, telephone lines as a proxy for
infrastructure development and government expenditure tend to deter inward
FDI. The effects of GDP per capita and interest rate on inward FDI, in addition,
are statistically insignificant with unexpected signs. These results are consistent66

Determinants of Inward Foreign Direct Investment in Vietnam

with previous studies of Demirhan and Masca (2008), Ranjan and Agrawal (2011)
and Sfar (2015).
The empirical findings have several important policy implications. First, since
the market growth of the host country has a significant positive impact on
inward FDI, there is need for sustainable growth of the country’s GDP. This
will strengthen the attractiveness of Vietnam’s economy for foreign investors.
Second, as the openness of the economy is also a significant determinant,government should make further efforts to enhance the implementation of its
reform agenda, which has the potential to attract more FDI inflows. Third,
inflation rate is found to have a negative relationship with FDI inflows, whichindicates a sign of weak macroeconomic performance and investors both foreignand domestic may not be willing to invest in a market with high inflation rate.
Thus, the authorities should maintain policies aimed at controlling the rate of
inflation. This requires a monetary policy framework which focuses on inflation
as a target variable (Brima 2015, 132). In addition, to ensure the attractionof more inward FDI, Vietnamese government should improve the quality of
infrastructure; increase the public spending on education to enhance capacityof labor force and augment cooperation between training centers and foreign
firms.
With regard to the scope for further studies, we recommend future
researchers to examine other potential determinants that are likely to affectthe inward FDI in Vietnam such as political regime, regulations, rule of law,effectiveness of government, control of corruptions, taxes and tariff, and natural
resources. Infrastructure can also be investigated as a different proxy withavailable data, e.g. roads, electricity and water supplies, which might lead tomore reliable results. It may also be worthwhile to examine the correlation
as well as the causal relationship between economic growth, trade openness,interest rate, etc. and inward FDI in Vietnam by applying the Granger
causality test. Additionally, it would be interesting to implement wider analyses
for groups of countries, including Vietnam to identify the determinants of FDI
inflows.

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70Determinants of Inward Foreign Direct Investment in Vietnam

Abstract

Determinants of Inward Foreign Direct
Investment in Vietnam
Nam Hoai TRINH & Quynh Anh Mai NGUYEN

Foreign direct investment (FDI) is seen as one of the key sources of capital
inflows and driver of economic growth and development in many developing
countries. Vietnam has recorded high level of success in mobilizing hugeinvestment to support its economic growth. During the past three decades,
Vietnam’s economy grew at an annual average rate of about 7.5%, making it oneof the fastest growing countries in the world. This study aims to examine thedeterminants of inward FDI in Vietnam over the period 1990-2013 using timeseries analysis techniques that address the problem of nonstationarity of data.
Specifically, the Unit root test and Cointegration approach are applied to ensurethat the regressions are not spurious. The empirical results reveal that grossdomestic product (GDP) growth rate, trade openness, exchange rate, secondary
education and external debt have positive effects on FDI inflows whereas
inflation rate, telephone lines and government consumption are found to havenegative impacts on FDI inflows. Moreover, the effects of GDP per capita andinterest rate on inward FDI are statistically insignificant with unexpected
signs. Ultimately, the paper suggests that synchronized efforts should focus
on strengthening the capacity of economic growth, trade effectiveness, andlabor skills in order to ensure stability in macroeconomic performance, which
enhances the confidence of foreign investors in Vietnam.
Keywords: Foreign Direct Investment (FDI), FDI determinants, Vietnam,
Time-series analysis.

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