Proceedings of Applied International Business Conference 2008
FOREIGN DIRECT INVESTMENT AND ECONOMIC GROWTH IN VIETNAM
Nguyen Thi Hoang My ψ
Thammasat University, Thailand
Abstract
Foreign Direct Investment (FDI) is expected to benefit developing countries through raising domestic
investment, creating jobs, transferring of technology, enhancing domestic competition and producing
positive externalities. However, each developing country has different initial conditions and distinctive
institutional setups. Heterogeneity in each country implies that the benefit of FDI may vary from
country to country. The purpose of this paper is to examine the role of FDI in the process of technology
diffusion and economic growth in Vietnam using time series data over the period 1986-2006. The
period includes the 1990s, when Vietnam launched economic reform – Doi Moi and the financial
liberalization process. We construct an endogenous growth model in which the rate of technological
progress is the primary determinant of long term growth rate of income. Cointegration technique is
utilized to verify the adoption of endogenous growth model for Vietnam. The result indicates that there
exists a long-run relationship between FDI and economic growth. Employing the Error Correction
Model (ECM), we examine the speed of adjustment toward the long run equilibrium. Our finding
shows that both FDI and human capital have positive effects on economic growth. Domestic
investment is stimulated by FDI. Nevertheless, the interaction between FDI and human capital may
slowdown economic growth. The finding has shed light on the causes of current macroeconomic
instability in Vietnam.
Keywords: Foreign direct investment; Economic growth; Vietnam.
JEL Classification Codes: F21; O40.
1. Introduction
Since the innovation Doi Moi in 1986 and the promulgation of Law on Foreign Investment in 1987,
FDI inflows to Vietnam have increased rapidly both in the number of projects and the amount of funds.
FDI inflows to Vietnam have played an important role as providing investment capital, stimulating
export activities, introducing new labor and management skills, transferring technologies and
generating job opportunities. However, Viet Nam has still some typical weaknesses of developing
countries in order to absorb FDI efficiently such as poor infrastructure, shortages of physical and
human capital, and weak institutions.
FDI inflows to Vietnam through the period 1988-2006 increased, reaching the peak in 1997 and falling
in the following years. Recently, it has increased significantly since the improvement of investment
environment and policies. Although many studies on FDI and growth in developing economies exist,
few studies on this subject have been done for Vietnam, especially for time series data since the lack of
some data for the period before 1990s. It is therefore impossible to undertake researches in a long-term
perspective. This paper employs an endogenous growth model in which the technological progress is
the primary determinant of GDP growth rate. The growth model is then empirically tested to examine
the effects of FDI on economic growth. We also examine the nature of the relationship between FDI
and domestic investment in Vietnam, we expect that FDI supplement domestic investment and the
effect of FDI on economic growth is significantly positive.
The outline of the rest of the paper is as follows. In Section 2, a review of related literature on FDI and
economic growth is presented. Section 3 provides a theoretical framework of endogenous growth
model. Next, the methodology and data used in the empirical study are discussed in Section 4. Section
5 is our empirical results. The final section 6 contains some concluding remarks.
ψ
Corresponding author. Nguyen Thi Hoang My. Faculty of Economics, Thammasat University,
Bangkok, Thailand. Email: [email protected]
Proceedings of Applied International Business Conference 2008
2. Literature review
There are different results in the literature regarding to how FDI affects economic growth.
Theoretically, FDI may affect economic growth directly because it contributes to capital accumulation,
and the transfer of new technologies to the recipient country. In addition, FDI enhances economic
growth indirectly where the direct transfer of technology augments the stock of knowledge in the
recipient country through labor training and skill acquisition, new management practices and
organizational arrangements (De Mello, 1999). Recent endogenous growth models imply that FDI can
affect growth through knowledge externalities and the existence of human capital in developing
economies.
Using an endogenous growth model, Borensztein et al (1998) found that FDI is an important vehicle of
technology transfer, contributing more to economic growth than domestic investment. Higher
productivity of FDI holds only when host countries have a minimum threshold stock of human capital.
Also applying endogenous growth theory framework for a data set of six MENA countries in period
1975-1990, Abdel-Hameed M.Bashir (1999) concluded that FDI leads to economic growth and human
capital has a negative impact on growth since the countries in sample experience lower secondary
school enrollment. Shiva S.Makki and Agapi Somwaru (2004) used the same growth theory framework
for cross section data of sixty-six developing countries in period 1971-2000 and realized that FDI and
trade contribute toward advancing economic growth in developing countries. FDI stimulates domestic
investment and benefits from FDI would be greatly enhanced if host country has better stock of human
capital. Li and Liu (2005) based on a panel data set for 84 countries over the period 1970-99, applied
single equation and simultaneous equation system techniques to examine the relationship between FDI
and economic growth. Their results showed a significant endogenous relationship between FDI and
economic growth. FDI not only directly promotes economic growth by itself but also indirectly via
interaction terms. Positive effect of FDI on economic growth through its interaction with human capital
in developing countries, negative effects of FDI on economic growth via interaction with technology
gap.
Most researches were done for cross section data. Some researches used time series data such as Akinlo
(2004) who applied Ordinary Least Squares with Error Correction Model for Nigeria period 1970-2001
and concluded that extractive FDI does not enhance growth as manufacturing FDI in Nigeria.
Wasantha Athukorala (2003) applied simple production approach to test time series data for Sri Lanka
period 1959- 2002 using Cointegration and Error Correction Model pointed out that FDI inflows do not
exert an independent influence on economic growth. The direction of causation is not towards from
FDI to GDP growth but GDP growth to FDI
3. Theoretical framework
The model used in this paper is followed closely from Barro and Sala-i-Martin (1995), Borensztein et
al (1995). We suppose that the economy produces a single consumption good according to the
following technology:
Yt = AH tα K t1−α
(1)
in which Y is final output of economy with inputs being physical capital K and human capital H, A is a
fixed technology parameter. We assume that human capital H is a given endowment. Physical capital
consists of an aggregate of different varieties of capital goods, and hence capital accumulation takes
place through the expansion of the number of varieties.
The stock of physical capital of the economy is given by:

K =

1
N
∫0
1− α
x( j )
 (1−α )
dj 

(2)
That is, total capital is a composite of different varieties of capital goods, each one being denoted by
x(j). We assume that the total number of varieties of capital goods, N, is produced by two types of
firms: domestic and foreign firms present in the economy. The domestic firms produce n and the
foreign firms produce n* varieties. Then N is the sum of n and n* (N= n+n*).
Assume that some firms specialize in producing capital goods, and then rent it out to other firms to
produce final goods at the rental rate of m(j). The demand for each variety of capital good, x(j), is given
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Proceedings of Applied International Business Conference 2008
by the equality between the rental rate and the marginal productivity of the capital good in the
production of the final good, that is:
m( j ) = ∂Y ( K , H ) / ∂K = A(1 − α ) H α x( j ) −α
(3)
Equation (3) shows that m(j) is dependent upon demand for capital good, x(j). Developing countries
usually apply modern technology which is transferred via FDI from foreign and multinational
corporations.
Assume that the technology adaptation is costly, requiring a fixed setup cost F before production of the
new type of capital can take place.
We assume that the fixed setup cost depends negatively on the number of foreign firms operating in the
host economy (n*) to capture the notion that foreign firms bring to the developing economy an advance
in “knowledge” applicable to the production of new capital goods and FDI is the main channel in this
framework.
Besides, there is a “catch-up” effect in technological progress by which the setup cost depends
negatively on how many varieties are produced domestically compared to those produced in more
advanced countries (which we denote by N*), since it is cheaper to imitate products already in existence
for some time than products at the frontier of innovation. The fixed costs of applying technology via
foreign firms fall when the number of domestically produced capital goods goes up.
Thus, we postulate the following functional form for the setup cost:
F = F (n * , N / N * ),
*
where ∂F / ∂n* p 0 and ∂F / ∂ ( N / N ) p 0
(4)
Beside the fixed setup cost, FDI enterprises also incur variables cost and opportunity cost of fund,
interest rate r in order to produce capital goods. Assume that there is a constant marginal cost of
production of x(j) equal to 1, and that capital goods depreciate fully. Assuming a steady state where the
interest rate r is constant, profits for the producer of a new variety of capital j are:
∏ ( j ) t = − F ( n *t , N t / N *t ) +
∞
∫t
[m( j ) x( j ) − x( j )]e −r ( s −t ) ds
(5)
Replacing m(j) from (3) into equation (5) and solving the conditions for maximizing profits will
produce the demand for j capital good in the equilibrium.
x( j ) = HA1/ α (1 − α ) 2 / α
(6)
Note that x(j) is independent of time, that is, at each instant the level of production of each new good is
the same. Moreover, the level of production across the different varieties is also the same due to the
symmetry among producers. Substituting equation (6) into the demand function (3), we obtain the
rental rate:
m( j ) = 1 /(1 − α )
(7)
which gives the rental rate as a markup over maintenance costs.
Finally, we assume that there is free entry, and hence, the rate of return r will be such that profits are
equal to zero. Solving for the zero profits condition we obtain the equilibrium interest rate:
r = Ψ F ( n * , N / N * ) −1 H
(8)
where
Ψ = A1 / α α (1 − α )( 2 −α ) / α
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Proceedings of Applied International Business Conference 2008
Assume further that the economy consists of households and the process of capital accumulation is
driven by savings behavior. We assume that households maximize the following standard intertemporal utility function:
Ut =
∞ C1s −σ − ρ ( s −t )
e
ds
t 1− σ
∫
(9)
where C denotes units of consumption of the final good Y, ρ is the subjective rate of time preference,
σ is the consumption elasticity of marginal utility and is a constant. Given a rate of return equal to r,
the optimal consumption path is given by the standard condition:
.
Ct
1
=
(r − ρ )
Ct
σ
(10)
As the economy is in steady state equilibrium, the rate of growth of consumption is equal to the rate of
growth of output, which we denote by g
Replace r in (8) into equation (10), we obtain the following expression for the rate of growth of the
economy:
g=
1
σ
[ΨF ( n* , N / N * ) −1 H − ρ ]
(11)
The above model shows that the existence of FDI, by which the new capital goods are created,
increased the stock of physical capital at lower production costs and affect to the economic growth of
an economy.
Furthermore, the effect of FDI on the growth rate of the economy is positively associated with the level
of human capital, that is, the higher the level of human capital in the host country, the higher the effect
of FDI on the growth rate of the economy. Equation (11) also shows that a high level of human capital,
H, raises the rate of growth, g.
4. Methodology and data
Methodology
In order to test the impact of FDI on economic growth, we use approximate equation of above
theoretical framework growth model:
g t =α 0+α 1FDI t +α 2( FDI * H )t +α 3H t +α 4X t + ε t
(12)
The dependent variable gt denotes economic growth, measured by the growth rate of real Gross
Domestic Product (GDP) per capita; FDIt represents foreign direct investment, measured by the ratio of
implemented FDI in GDP; The variables Ht represents the stock of human capital, measured the effect
of human capital on growth. The interaction term (FDI*H)t helps to explain the role of human capital
on the contribution of FDI to economic growth. The presence of this variable is regarded as the
measurement of the economy’s absorptive ability of FDI, which depends on the skilled labors of an
economy.
The stock of human capital in a host country is critical for absorbing foreign knowledge and an
important determinant of whether potential spillovers will be realized. The application of advanced
technologies embodied in FDI requires a sufficient level of human capital in host countries. That is, the
higher the level of human capital in host country, the higher the effect of FDI on the country’s
economic growth. The interaction term estimates the combined impact of FDI and human capital and
indicates the nature of the relationship between the two. A positive coefficient for the interaction term
would suggest that FDI and human capital reinforce each other in advancing economic growth.
X is a set of other variables that are frequently included as determinants of growth such as government
consumption GC; population growth; trade (exports plus imports) of goods and services; the initial
GDP per capita; inflation; domestic investment (I). In this paper, we will use GC as other variable
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Proceedings of Applied International Business Conference 2008
affect economic growth since Vietnam is a transition country that government spending accounts for
large share in GDP and is used to build infrastructure and institutions.
Time series econometric model is utilized to examine the relationship between the variables as
suggested in the model. Prior to analyzing the long-run cointegrated time series relationships and shortrun dynamics, time series variables are tested to discover the order of integration of each variable in the
model.
Unit root test
Most of macroeconomic time-series are non stationary in level form. The problem with non stationary
data is that the conventional OLS regression method can easily yields incorrect conclusions. The results
obtained from this kind of regression are said to be spurious and regressions are named spurious
regressions (Granger and Newbold, 1974).
Testing for non stationary is equivalent to testing for the existence of a unit root. Several statistical
methods are constructed to test for unit roots. This paper applies Augmented Dickey Fuller (ADF)
method which is an extension of the Dickey-Fuller (DF) test to eliminate the possible autocorrelation
occurred in the original DF test.
p
∆xt = α + γxt −1 + λt + ∑ β i ∆xt − i + ε t
i =1
where ∆ is the difference operator, α, γ, β and λ are coefficients to be estimated, xt is the variable
whose unit roots are examined, t is the time trend which is included to test for trend stationary of the
variable and ε is the white noise error term.
The test involves testing the null hypothesis that γ =0 (the series is nonstationary) against the
alternative hypothesis that γ <0 (the series is stationary). If the null hypothesis can be rejected, the
series xt is stationary at level or integrated of order zero, xt ~I(0). However, if the null hypothesis
cannot be rejected, xt is nonstationary at level and is said to be integrated series.
Cointegration Test
The cointegration test is needed to find the long-run relationship among a group of variables,
particularly in the case that series are non-stationary at level. The prerequisite condition of the
cointegration test is that each series have to be integrated of the same order.
As unit root tests show that the variables are all I(d), the cointegration technique is appropriate to
estimate the long run relationship between variables. The cointegration test is proceeded by applying
the method developed by Johansen (1988) and Johansen and Juselius (1990).
The number of cointegrating vectors (r) is determined by two likelihood ratio tests. In the first test
(λtrace) the null hypothesis of at most r cointegrating vectors is tested against the alternative of r+1
vectors. The second test is based on the eigenvectors (λmax) of the stochastic matrix where the null
hypothesis is that there are at most r cointegrating vectors against the alternative hypothesis of
cointegrating vectors > r. If λtrace or λmax is greater than the critical value at specified level of
significance, then the null hypothesis of r cointegrating vector will be rejected
Vector Error Correction (VEC) Model
A vector error correction (VEC) model is a restricted VAR designed for use with non stationary series
that are known to be cointegrated. The VEC has cointegration relations built into the specification so
that it restricts the long-run behavior of the endogenous variables to converge to their cointegrating
relationships while allowing for short-run adjustment dynamics. The cointegration term is known as the
error correction term since the deviation from long-run equilibrium is corrected gradually through a
series of partial short-run adjustments. Consider the following equation,
yt = α t + βxt + zt
zt = yt − (α t + βxt )
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Proceedings of Applied International Business Conference 2008
“Granger Representation Theorem” (Engle and Granger, 1987) says that if xt and yt are cointegrated,
we can find short-run adjustment dynamics pattern in the form of “Error-Correction Mechanisms”
which can be written as follows,
∆xt = φ1zt −1 + {lagged (∆xt , ∆yt )} + ε1t
∆yt = φ2 zt −1 + {lagged (∆xt , ∆yt )} + ε 2t
where zt-1 is the error-correction (EC) term, ε1t and ε2t are white noise and φ1, φ2 are non-zero
coefficients.
Data
This analysis is based on time series data set of Vietnam over period 1986-2006. The main source of
data is various issues taken from East Asian Economic Perspectives, Statistical Yearbook of Vietnam
General Statistical Office, Asian Development Bank Key Indicator 2006, 2007, IMF reports, UN data...
Table 1 summarizes the variable measurement and data sources.
Table 1: Variable definitions and data sources
Description and Sources
GDP per capita growth (annual %). Author’s calculation from GDP per capita,
measured in 1994dong. Source: UNdata
Secondary school enrolment rate used as a proxy for human capital. Source:
UNdata and GSO
Share of foreign direct investment (as percent of GDP).
Source: calculation from the level of FDI and GDP, both measured in US$
Share of government consumption (as percent of GDP)
Source: ADB Key Indicators 2007
Share of investment (as percentage of GDP). Source: East Asian Economic
Perspectives 2007 (ICSEAD)
GDP growth (annual %). Source: ADB Key Indicators 2007
Interest rate (annual %). Source: ADB Key Indicators 2007
Variable
g
H
FDI
GC
I
G
R
5. Econometric results
The ADF test results for variables involved in our equations are presented in Table 2. Our results show
that all variables exhibit integrated order one. This means that the series are non-stationary in level but
stationary in first-differences. The implication is that there is a possibility of having a co-integrating
vector whose coefficient can directly be interpreted as long-term equilibrium.
Table 2: Summary of ADF unit root test result
Series
ADF Test Computed t- stat of γ
Number of lags
gt
FDIt
Ht
(FDI*H)t
GCt
It
Rt
Gt
∆gt
∆FDIt
∆Ht
∆(FDI*H)t
∆GCt
∆It
∆Rt
∆Gt
-1.568
-1.289
-3.077
-1.131
-2.063
-2.842
-2.465
-2.358
-3.88*
-4.039*
-2.972**
-3.965*
-3.129**
-3.008**
-4.749*
-3.947*
3
0
2
0
4
1
1
1
1
0
3
0
0
0
3
0
Note: 1. The Augmented Dickey-Fuller (ADF) test is under the null of a unit root. The optimal lag length for ADF
regression is selected based on the AIC criterion. 2. * and ** means the rejection of a unit root at 1% and 5% level
of significance respectively.
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Proceedings of Applied International Business Conference 2008
As next step, Johansen trace test is used to check whether we have a cointegration relationship. Results
of the trace test and maximal eigenvalue test are reported in Table 3 for growth equation (12) which
gives the number of cointegrating vectors. According to the Table 3, we can reject the hypothesis that
no cointegration exists.
Table 3: Cointegration tests for growth rate per capita
Hypothesis
r=0
r≤2
r≤1
λtrace
92.45638*
47.32699*
16.37043*
5% Critical value
47.85613
29.79707
15.49471
Note: Trace test indicates 3 cointegrating eqn(s) at the 5% level of significant
r≤3
0.837055
3.841466
Hypothesis
r=0
r≤2
r≤3
r≤1
λmax
45.12939*
30.95656*
15.53338*
0.837055
5% Critical value
27.58434
21.13162
14.26460
3.841466
Note: Max-eigenvalue test indicates 3 cointegrating eqn(s) at the 5% level of significant
The test results are presented in Table 3 which indicates that for the growth equation, the trace test and
maximal eigenvalue test imply the existence of 3 cointegrating vector at 5% level of significant.
Table 4 reports the cointegration estimates by normalizing the coefficient of g to one, we obtain the
long-run elasticities of per capita growth rate with respect to other variables.
Based on the signs and the magnitude of coefficients, the results show that the coefficients are plausible
for FDI and H. FDI has positive impact on per capita growth, for each percentage point of increase in
the FDI-to-GDP ratio, the rate of growth of the economy increases by 4.468 percentage points.
Coefficient of human capital shows that there is a positive link between human capital and per capita
growth, both significant at 1%. However, the interaction term between FDI and H has a negative effect
on per capita economic growth. The interactions of FDI with human capital help to examine the
absorptive capacity of foreign technology through FDI in Vietnam.
Table 4: Econometric results of cointegration estimates by normalizing the coefficients of
dependent variables to one
Dependent variable: growth rate of GDP
Dependent variable: domestic
per capita
investment as percent of GDP
(1)
(2)
(3)
FDIt
4.468*
3.774*
0.022
(9.686)
(16.531)
(0.045)
Ht
0.357*
0.366*
(9.759)
(14.551)
(FDI*H)t
-0.083*
- 0.081*
(-9.200)
(-14.636)
GCt
1.319*
(4.401)
-0.949*
Rt
(-14.232)
Gt
0.213
(0.251)
Adjusted-R2
0.692
0.84
0.44
The signs of coefficients of interaction term between of FDI and H show that low secondary enrollment
rate may slowdown the contribution of FDI to growth. Borensztein et al (1995) stated that benefits of
FDI on host country depend on its absorptive capability, which is measured by the interaction between
FDI and H. In order a developing country captures such benefit, human capital much reach a certain
threshold. Too low labor skills may restrict the effect of FDI on growth.
Government consumption in regression (2) shows a positive effect on economic growth. This may
contradict with findings from other researches of other countries but it is consistent with a transition
economy like Vietnam since in Vietnam, government still play a leading role in the development
process. Government spending in Vietnam was used to build infrastructure and institutions to attract
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Proceedings of Applied International Business Conference 2008
foreign investment and indirectly affect investment in human capital and thus contribute to economic
growth.
Results of Estimation of ECM
The results of cointegration test show that there is a long-run relationship between FDI and economic
growth. As a result, according to the Granger Representation Theorem, we can formulate an error
correction model in order to capture the short run movement of all variables included in this cointegrating regression.
The error-correction term (ECT) is derived by normalizing the cointegrating vector on g. It captures the
changes in g required to eliminate past departures of actual values of the variables from the equilibrium
levels. According to the results, the coefficient of the error-correction term (ECT) which is commonly
recognized as the adjustment coefficient has emerged with the negative sign and statistical significance.
The negative and significant sign of the adjustment coefficient shows how much of the disequilibrium
is being corrected, i.e. the extent to which any disequilibrium in the previous period effects any
adjustment in gt. This implies that there is adjustment process which prevents the errors in the long-run
relationship become larger. Equation (13) would be used to explain the short run movement of
economic growth in Vietnam.
∆g t = 0.930 − 0.019∆g t −1 − 1.259∆FDI t −1 − 0.497 ∆H t −1 + 0.022∆( FDI * H ) t −1 − 0.775 ECTt −1
(13)
Diagnostic Tests show that there is no problem of autocorrelation because the probability value is 0.079
indicating that the null hypothesis of no autocorrelation cannot be reject at 5% level of significant. The
problem of heteroscedasticity also does not exist since probability value is 0.15. In this equation, the
speed of adjustment toward equilibrium in the long run by coefficient of lagged error correction term
(ECTt-1) is -0.775 and statistically significant at 1% level. It means that the error occurred in the past
will be corrected in the following year. Its negative sign suggests that the actual growth rate is higher
than its long-run equilibrium value and there will be a mechanism to reduce the actual growth rate by
0.775 in the next period so that the error will be slowed down and growth rate will be forced back
toward equilibrium. Another way to explain that within one year, about 77.5% of the disequilibrium
between actual and long run economic growth can be decreased. Therefore, growth rate and its
determinants have the stable long-run relationship.
FDI and Domestic Investment
As above results, FDI has positive impact on economic growth through investment. Economic results
of regression (3) help us to check whether FDI augments domestic investment in Vietnam or it crowds
out. Our result shows that FDI has a positive effect on domestic investment even though insignificant
statistic. The positive relationship shows that FDI complement to domestic investment in Vietnam.
6. Conclusion
The paper analyzes the role of FDI on economic growth in Vietnam for the period 1986-2006 using the
endogenous growth theory framework. We find that FDI contribute significantly to economic growth.
The results also show that FDI stimulate domestic investment and FDI will be better utilized if
Vietnam has better stock of human capital.
This study might be a good reference for future studies on the causality relationship between FDI and
economic growth in Vietnam. The paper has some drawbacks such as the limitations as the quality of
data and the sufficient length of time-series. The short time-series of 21 annual observations from 1986
to 2006 though acceptable for statistical analysis, the problem of degree of freedom may draw some
concerns. It is more valuable if the causality test was performed on the relationship between FDI,
domestic investment and economic growth.
Acknowledgement
I would like to thank my advisor, Assoc. Prof. Dr. Bhanupong Nidhiprabha for his valuable
instructions, comments and discussions. This work was supported by Asian Development Bank.
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Proceedings of Applied International Business Conference 2008
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