FDI spillovers in Vietnam: The overall view of transferring channels, and internal characteristics and international trade policies of domestic firms

Nguyen Van Phuong et. al. | 285



FDI spillovers in Vietnam: The overall view of
transferring channels, and internal
characteristics and international trade policies
of domestic firms
NGUYEN VAN PHUONG
International University, Vietnam National University HCMC –

TRIEU DOAN XUAN HOA
International University, Vietnam National University HCMC

HUYNH THI NGOC HIEN
International University, Vietnam National University HCMC

NGUYEN DINH KHOI
International University, Vietnam National University HCMC

Abstract
The study used a panel data of unlisted Vietnam manufacturing enterprises over the
period 2011-2015 surveyed by General Statistic Office (GSO) to investigate the channels
by which foreign direct investment firms help raise the productivity of domestic firms in
Vietnam. We estimate spillovers that occur within an industry and between different
industries, whether a technology gap between foreign and domestic firms is a limiting or
facilitating factor for technology spillovers. The heterogeneity of domestic firms, namely
absorptive capacity, technology level related to foreign firms, market share, financial
development and international trading policies of domestic firms, has been examined.
Keywords: FDI spillovers; TFP; technology gap; international trade.

286 | ICUEH2017


Acknowledgements
We would like to express our deep gratitude for the financial support from Vietnam National
University – Ho Chi Minh City within the framework of Agreement No. C2016-28- 06/HĐ-KHCN.

1. Introduction
Attracting foreign direct investment (FDI) has become an integral part of development
strategies among developing countries. Many offer special incentives to foreign investors,
including tax holidays, tariff reductions or exemptions, and subsidies for infrastructure.
While these policies rest on the premise that foreign investment facilitates technology
spillovers from foreign to domestic firms, the empirical evidence is ambiguous. FDI has
been considered as one of the major sources of economic growth of Vietnam since the
introduction of economic reform and renovation in 1986. However, there is a little study
on whether FDI has facilitated technology transfers, which benefit domestic firms in
Vietnam.
In this study, we will use a panel data of unlisted Vietnam manufacturing enterprises
over the period 2011-2015 conducted by General Statistic Office (GSO) to investigate
whether the presence of foreign direct investment helps to raise the productivity of
domestic firms in Vietnam. We estimate spillovers that occur within an industry and
between different industries, whether a technology gap between foreign and domestic
firms is a limiting or facilitating factor for technology spillovers. We also assess to the
roles of absorptive capacity of domestic firms in the context of technology spillovers. We
differ significantly from much of the empirical literature in that we recognize that the
adoption of better technology or managerial know-how is a costly learning process. The
firm’s productivity may suffer initially because some resources must be devoted to
learning. However, once the firm successfully adopts the new technology, its productivity
will raise at a higher rate, which propels the firm to a steeper growth path and raises the

productivity level in the long run. In this study, by employing a large panel of Vietnamese
manufacturing industries, we seek fresh evidence on three empirical questions.
First, we explore whether horizontal and vertical FDI spillovers influence the
productivity level and the rate of productivity growth of indigenous firms (Liu, 2008). As
previous studies showed the presence of FDI in the industry may generate negative
spillovers on the productivity level of domestic firms in the short term (Haddad &


Nguyen Van Phuong et. al. | 287


Harrison, 1993; Aitken & Harrison, 1999; and Liu, 2008). However, when considered in
the long term, FDI spillovers are more likely to have a positive effect on the rate of
productivity growth of domestic firms because FDI spillovers help enhance future
productivity capacity (firm-specific capital) of domestic firms, which determines the longterm growth rate of productivity. Consequently, our goal is to determine whether the
positive rate effect of horizontal spillovers is driven by FDI spillovers in the low-tech or
high-tech industries.
Second, we investigate whether the levels of the technology gap affect the FDI
spillovers. In previous studies, Findlay (1978) and Wang and Blomstrom (1992)
demonstrate that the greater the technology gap between FDI and domestic firms, the
more opportunities the domestic firms achieve better levels of efficiency via the imitation
of foreign technologies and innovations. However, the gap must not be too large. Finally,
we go to one step further to investigate whether the technology spillovers from FDI firms
relate to foreign trading activities of domestic firms.
2. Literature review
FDI spillover including knowledge and technology spillover from foreign direct
investment companies have attracted attention of researchers and policy makers.
Productivity spillovers from FDI occur when the entry or presence of foreign firms leads
to the enhancement of the productivity of domestic. While technology can be transferred
directly to MNCs’ subsidiaries and locally vertical-linkage firms of the host country,

domestic firms can only adopt new and more advanced technology from spillover effect,
which will take times and require certain resources (Jude and Levieuge, 2015). Among the
most prevalent form of spillover is the imitation of technologies through observation or
the mobility of former workers in the multinational enterprises. Thus, the companies in
the host country will be benefited from the flow of knowledge, and enhance their
efficiency.
Alternatively, fierce competition caused by the foreign firms encourage domestic ones
to stay up-to-date to survive in the market. They have to either utilize their current
resources or seek for more cutting-edge and efficient technology to remain
competitiveness (Blomstrom and Kokko, 1998). Consequently, the technological gap is
reduced and productivity is enhanced, in turn, force the multinational affiliates to


288 | ICUEH2017


innovate newer technologies (even one that has not been existed before in their host
countries) to win the competition. In summary, Damijan et al. (2013) pointed out four
main channels that how FDI inflows generate spillovers from a very beginning form as
(1) demonstration/imitation and (2) competition to a well-prepared (3) vertical/ interindustry linkage and (4) training:
- The domestic firms could take advantage of demonstration and imitation effects that
improved institutional, managerial, and technological practices. Prior literatures reported
that technological transfer would rise with the existence of FDI. More particularly, by
observing and imitating operating procedures of foreign enterprises, local ones will be
beneficial in several aspects, including advance technologies, essential marketing skills,
efficient inventory management, quality control, etc. Further, connections and alliances
with FDI corporations facilitate the knowledge flows to the domestic ones.
- The competition effects that FDI firms bring to domestic market pushes domestic
firms updating skills and technologies to raise productivity. However, Damijan et al.
(2013) also found risky for the competitive advantages of domestic firms as upstream or

downstream partners with FDI firms because the capacity and productivity level of each
individual firm will determine whether they can absorb the technology spillover from
foreign investors; otherwise, these firms would be failed in a fiercer competition. With
respect to competition, a framework is constructed by Wang and Blomstrom (1992) to
describe the correlation between the level of competition and spillover. As competition in
the host country increases, FDI corporations have to improve their technologies to gain
more market shares. As a result, local firms will have to utilize their resources or upgrade
their technologies to stay in competitiveness.
- Foreign linkage effects occur through the strictly demand quality for domestic firms
exporting to MNCs or the higher input imported from MNCs. Findlay (1978), as a pioneer
for this contribution, stated that the larger the technological gaps between the two
country, the greater the remaining chances for the less developed countries. Yet, the
pressure increases as local firms might lose in the harsh competition. Therefore, the
improvement in the technology will be faster under such circumstances.
- The speed of technology transfer will be faster if the multinational affiliate is willing
to establish upstream and downstream networks, because this helps local firms involved
in supply and distribution chains to achieve exposure to advanced technology and


Nguyen Van Phuong et. al. | 289


subsequently to promote technology improvement. It is admitted that being a part of the
network through upstream and downstream activities enables the domestic suppliers and
domestic customers to benefit from the inherited technical and commercial know-how as
well as technology spillovers, which lead to a process improvement in the short run and
a productivity improvement in the long run (Hamida, 2013).
- The moving of employees from MNCs to domestic firms and complementary workers
creates training effect of FDI spillovers. Wang (1990) extends Findlay’s model by
establishing a dynamic two-country model to analyze the interaction between FDI and

the growth of domestic human capital. With capital moving globally, the model predicts
that an increase in the growth rate of human capital and the technology diffusion rate in
the less developed country leads to a narrowing of the steady-state income gap. The
important result from the analysis shows that a greater opening to FDI from more
advanced countries leads to facilitating technology spillovers in the host country, and
hence increasing its rate of income growth. Another potential channel for technology
spillovers from FDI to take place is through the acquisition of human capital.
- The availability of relatively skilled labor is an essential magnet as well as a key driver
of agglomeration, helping to increase productivity through adoption of new technology.
It has been argued that host countries are more likely to benefit from spillovers if they
have a large supply of skilled labors (Keller, 1996). Additionally, the labor turnover as the
movement of labor from FDI firms to domestic firms can also generate productivity
improvements through either a direct spillover to complementary workers or knowledge
carried by workers who move to another firm. Fosfuri et al. (2004) and Glass and Saggi
(2002) argue that the knowledge that workers bring with them is the most essential
channel for spillovers. Providing an overall review of FDI spillover, Wang et al. (2013) also
found a significantly positive impact of FDI on domestic human capital and economic
growth through building capacity for local workers and encouraging innovations.
Literatures on technological gap emphasized the quality of technological transfer.
Inconsistent with Findlay, Glass and Saggi (1999) proposed that great distance between
the host and home country deteriorated the quality of technological transfer and the effect
of spillover due to insufficient human resources, infrastructure and networks. They
formulated that absorptive capacity and technology gap, thus, are important
determinants of technology spillover. From a different perspective, Walz (1997) suggested


290 | ICUEH2017


that knowledge spillover is the facilitator of innovative activities in backward countries.

From an analysis of the endogenous model where FDI is crucial for economic growth and
specialization pattern, the author confirmed that imitation of technological and
operational aspects in the less developed countries improves R&D behavior, and indirectly
stimulates the economic growth.
Perri and Peruffo (2016) have organized the related theoretical and empirical studies
by developing a framework to analyze this phenomenon. Three main attributes of
spillover, including magnitude, scope and speed are determined by firms’ heterogeneity
and the host business environment such as learning efforts and resources, competitive
and absorptive capacity, technology gap, financial market, network and regulations. In
this way, the spillover effect is differed between micro (MNC’s subsidiaries, local firms)
and macro level (countries, economies, industries) and between short term and long
term.
Although theoretical research of FDI spillover remained underdeveloped, empirical
studies on the issues continue to increase. In the very beginning, Caves (1974) investigated
and confirmed the positive effect of spillover in Australian manufacturing industry.
Following this pioneer, numerous scholars have investigated the FDI spillovers. Mostly,
the framework is constructed using labor productivity or total factor productivity, the
presence of FDI, as well as other potential determinants of productivity. Measurement of
presence of FDI is implemented by calculation of multinational’s share of employment,
sales, and output in a particular industry. The results of presence of FDI companies and
spillover, however, are mixed. While some studies confirmed the negative relationship of
spillover and the presence of FDI (Haddad & Harrison, 1993; Aitken and Harrison, 1999;
Djankov and Heokman, 2000, Jeon et al. 2013), positive correlation between the
constructed is found in other studies (Liu et al., 2000; Haskel et al., 2007; Liu, 2002;
Javorcik, 2004).
Possible explanation for the negative impacts might be the increased competition. For
example, Aitken and Harrison (1999) discovered that FDI enterprises not only stimulate
technological transfers, but also cause a competition level to be higher in a given sector.
Some local companies, not catching up to this higher demand, are eliminated from the
market. Consequently, the total productivity of domestic organization is reduced to the

existence of FDI. This is also known as “market-stealing” effect.


Nguyen Van Phuong et. al. | 291


Another explanation for the inconsistency is that some studies cannot differentiate
between the short-term and long-term effects of FDI spillovers (Liu, 2008). Adoption of
a new technology is resource-consuming, and local firms might have to leverage their
current resource and reduce some in the production. Thus, productivity will be reduced
at first sight, and correlations might be found negative. In the long run, when domestic
firms have already exploited new technologies, they will gain efficiency, and enjoys the
higher rate of production growth. At this stage, higher efficiency will make up for the
initial loss in productivity. In brief, the results are heavily dependent on the length of the
period of time the study attempted to cover.
Other researches considered the vertical effects as the potential channel of
technological transfer. In other words, domestic firms might become suppliers and
customers of international organizations, called backward linkages and forward linkages
respectively. Through these connections, foreign enterprises will provide technical
support to local ones to improve it efficiency. As an example, local firms have to upgrade
their technology and enhance their management skills in order for their intermediate
products to meet international standards, and their customers might provide assistance.
In a similar vein, they might enjoy higher productivity thanks to the high quality inputs
from the foreign suppliers.
This issue received empirical support from recent literatures of vertical spillovers.
More specifically, backward linkages between local companies and their foreign partners
significantly enhance efficient of firms in different geographical contexts such as
Lithuania (1996-2000 panel data, Javorcik, 2004), China (1995-1999 panel data, Liu,
2008), and Indonesia (Blalock and Gertler, 2008).
Another stream of research focusing on the scope of FDI spillover employed constructs

such as domestic firm size, ownership structure of FDI firms, liberalization of trade, and
geographic aspects. Regarding domestic firm size, Aitken and Harrison (1999) suggested
that small firms would not be able to compete with FDI affiliates because of their small
production scales that do not facilitate technological development. On the other hand,
large firms will capture these opportunities given their potential capability.
The effect of international trade on domestic firm productivity and technological
spillovers have been extensively discussed on the both theoretical and practical level.
Theoretically, international trade is proposed to manifest impacts on productivity and


292 | ICUEH2017


international spillover. In contrast, empirical studies focused on the influence of
international trade on productivity and economic growth. For instance, advanced
technology imports are considered as a major driving force for innovation, imitation, and
economic growth, and then impacts positively on technology transfers (Connolly, 2003).
Furthermore, international trade has been studied and reported that they exert a
significant impact of efficiency. On the one hand, some of these studies have considered
learning through export as a driving force of productivity growth (Bernard & Jensen,
1999; and Blalock & Gertler, 2004). Moreover, Javorcik & Spatareanu, 2008, and Girma
et al., 2008 investigates vertical and horizontal spillovers from FDI enterprises to
domestic ones and extends their investigation to trade orientation in terms of exports. In
conclusion, the results are mixed and subject to an important variable related to market
structure.
Although many studies have investigated the relationship between exports and
technology spillovers through backward and forward linkages, there are a few studies
examining the impact of imports on downstream and upstream spillovers. Blalock and
Veloso (2007), using panel data of Indonesian manufacturers, show that downstream
imports are associated with productivity achievements and consider imports as one of the

key elements to promote economic growth.
To our knowledge, this is the first study on FDI spillovers using a large, unbalanced
firm-level panel data from Vietnam.
3. Methodology
3.1.

Data

This study will use the Vietnamese annual enterprise surveys conducted during the
period 2011–2015 by the GSO (data collection of 2015 was completed in 2016). The dataset
covers a great number of enterprises operating across industries and throughout the
country, with the number of firms in the annual survey sharply increasing yearly. With
the suggestions of Rojec and Knell (2017), using firm level panel data analysis of FDI
spillovers could eliminate several failures to find unambiguously positive effects in
econometric work that be alarmed by Gorg and Greenaway ( 2004).


Nguyen Van Phuong et. al. | 293


We verify the creditable value and reliability of each observation to delete the
observations that did not satisfy the minimum criteria, such as negative sales, negative
output, negative input, negative capital stock, and missing information of key variables.
3.2.

Quantitative methodology

3.2.1. Estimate Total Factor productivity:
To begin with identify the impact of technology spillovers from FDI enterprises on
indigenous ones, we assume the firm’s production function is of the Cobb-Douglas type:

.

.

!"# = %"# (', ), *, +)-"#/ 0"#1

(1)

where Yit represents the value-added output of firm i at time t; Lit and Kit are labor and
capital inputs, respectively; and FDI is denoted by f; common technical factors are denoted
by a; stock of firm specific capital including human capital and managerial ability is
denoted by m; and external sources of knowledge are denoted by g. Similar to many
previous studies, for instance, Liu (2008) and Javorcik and Spatareanu (2008) which
relate productivity to FDI spillovers. We first estimate the firm-level total factor
productivity (TFP). We then regress from the TFP on proxies for FDI spillovers, and their
interactive terms associated with other control variables.
Taking the natural logs of Equation (1), which is denoted by small letters, we estimate
the logarithm function of production function:
2"# = 4 + 67 8"# + 69 :"# + ;"# + <"#

(2)

where y, l, k are the natural logarithm of output, labor and capital inputs, respectively; ω
is total factor productivity which is known to the firm but not to the researcher, ε stands
for random productivity shocks, and subscripts i and t index firm and time.
The concern about the estimated TFP resulting from Equation (2) is that it may be
biased because TFP can be influenced by the choice of factor input combinations in the
same period. Therefore, there may be a correlation between TFP and contemporaneous
covariates. In other words, since labor and other inputs are endogenously determined,
the use of OLS from Equation (2) is susceptible to bias the estimated coefficients (Liu,

2008). To overcome this simultaneous problem, we obtain consistent elasticity estimates
of Equation (2) by employing the Olley-Pakes (OP) methodology (the semiparametric
estimation procedure), which allows for firm specific productivity difference exhibiting


294 | ICUEH2017


idiosyncratic changes over time. According to Keller (2004), the OP estimation method
leads to a substantially greater role of FDI spillovers, which comes to results in a better
estimate of in-sample productivity growth.
3.2.2. Estimate FDI Spillovers:
FDI spillovers can occur through both horizontal and vertical linkages between
domestic and foreign firms. Vertical linkages can be divided into forward or backward
categories. Based on the existing literature (for example, see Liu, 2008; Grima et al.,
2008), several FDI linked spillover variables are constructed and used in this paper. The
degree of horizontal spillovers in industry j at time t, H_FDIjt is measured as follows:
=_?@AB# =

"GB;"IJKLM"NOP CDEFDE"B#
"GB CDEFDE"B#

The vertical spillover effect can be divided into two categories: vertical backward and
vertical forward. The degree of backward spillovers in industry j at time t is computed as
follows, where Ykj is the output of industry k supplied to industry j.
QR@_?@AB# =

49B# =_?@AB#
∀9TB

49B =

!9B
!9

In other words, the greater the proportion of output provided to an industry with
foreign presence and the greater the activities of the foreign firms receiving the
intermediate inputs from industry k, the greater the value of the spillover effect (see
Girma et al., 2008). This measure captures the extent of backward linkages between local
firms in upstream sectors and foreign firms in downstream sectors. The output of some
foreign firms in Vietnam is used as input by some domestic firms. An increase in FDI
leads to an increase in the output of foreign firms which leads to an increase in the supply
of inputs to domestic firms. The vertical forward spillover effect in industry j at time t is
calculated as follows:
?R@_?@AB# =

6UB# =_?@AB#
∀UTB


Nguyen Van Phuong et. al. | 295


6UB =

!UB
!B

where βhj represents the proportion of sector h’s output supplied to industry j.
This measure captures the extent of forward linkages between local firms in

downstream sectors and foreign firms in upstream sectors. Some foreign firms in
Vietnam use the output of domestic firms as input. An increase in FDI leads to an increase
in demand for inputs produced by domestic firms. The existing literature views this as a
forward linkage between foreign and domestic firms.
The values of α and β are obtained from the Input-Output Tables of Vietnam estimated
by the General Statistic Office of Vietnam 2012. The dataset includes sectoral classification
of firms at
Two-digit level of Vietnamese Standard Industrial Classification (VSIC).
3.2.3. Estimate Firm specific variable:
SCALEijt is measured by sales of firm i relative to the average firm sales in the same
sector; TECH_GAPijt is the percentage difference between the average productivity of
foreign firm and that of domestic firms in the same industry; FINANijt of firm i in industry
j at time t is measured by current assets over liability of the firm. MSijt is measured the
market share of the firm i within industry j at time t. The export intensity EXPORT_INTijt
of the firm i at time t measured by the exporting value over firm total sales, The export
intensity IMPORT_INTijt of the firm i at time t measured by the importing value over firm
total assets.
3.3.

Research model:

We investigate FDI spillovers by estimating the following equation:
TFPijt = β0 + β1H_FDIjt + β2FWD_FDIjt + β3BWD_FDIjt + β4SCALEijt + β5TECH_GAPijt
+ β6FINANijt + β7MSijt + β8EXPORT_INTijt + β9IMPORT_INTijt + μi + εijt

(3)

4. Empirical analysis
The sample data has 836,466 observations taken from 322,526 unlisted domestic
firms, and 9,215 foreign direct investment firms, which accounted for 2.53% of total in

296 | ICUEH2017


Vietnam over the period from 2011 and 2015. All the firms have operated in
manufacturing and service industries. The average value added generated by FDI firms
in 2011 to 2015 is 35,948 million VND with 659,371 million VND in standard deviation. In
average, an FDI firm had 431,304 million VND in total capital stock, and 408 working
employees per year. The operation figures of domestic firms are much lower compared
to these figures of FDI firms. With the average 832 million VND input into capital, and 24
employees working per year, domestic firms generated only 832 million VND. The wage
in domestic firms in the observed period was lower than that in FDI firms (21.74%).
TFP variable is estimated by applying method developed by Olley-Pakes, with inputs,
including natural logarithms of value added, capital stock, number of labor and total labor
wage. The average natural logarithm TFP of domestic firms is 0.453 and this figure of FDI
firms is 3.38. The mean of horizontal FDI spillovers across industries is 0.155, the
backward and forward spillovers FDI has averages of 0.263 and 0.259. For international
trade, import intensive in domestic firms is around 0.234 and 0.513 for export intensive.
The correlation among variables is conducted to check the validity of independence of
variables. The result will be included in Appendix. The correlation among variables is
below 0.37, which could be confident in the validity of independence of the proxies.
Table 1
Descriptive Statistics
Variable

Obs

Mean

Std. Dev.

Min

Max

Foreign firms
Value Added (million VND)

21,198

35,948

659,371

-5,045

59,400,000

Capital (million VND)

21,198

431,304

5,219,096

14

611,000,000

Number of labor

21,198

408

1,894

1

85,206

Total Wage (million VND)

21,198

31,084

135,546

4

6,514,027

Domestic firms
Value Added (million VND)

815,268

832

65,302

-5,046

32,200,000

Capital (million VND)

815,268

38,334

1,756,038

1

693,000,000

Number of labor

815,268

24

161

1

36,680

Total Wage (million VND)

815,268

1,502

20,172

0

7,330,518

LN_TFP

815,268

0.453

2.283

-10.215

13.841


Nguyen Van Phuong et. al. | 297

Variable

Obs

Mean

Std. Dev.

Min

Max

H_FDI

815,268

0.155

0.186

0.000

1.000

FWD_FDI

815,268

0.263

0.116

0.000

0.455

BWD_FDI

815,268

0.259

0.083

0.018

0.648

SCALE

815,268

0.931

6.172

0.000

2126.932

TECH_GAP

815,268

2.187

10.849

-949.331

584.624

MS

815,268

0.001

0.009

0.000

0.990

FINAN

815,268

12.268

1756.536

-10702.700

1570140.000

IMPORT_INT

815,268

0.234

34.700

0.000

20987.750

EXPORT_INT

815,268

0.513

153.264

0.000

124495.500

The empirical analysis for FDI spillovers and others related factors is illustrated in
Table 2. In overall, the study performs the estimation for equation (3), and the impact of
internal characteristics of the firm could be summarized as follows. The positive and
significant correlations of SCALE (relative to the firm size to the average revenue of the
industry) and MS (market share) suggests that the more revenue benefits in terms of
productivity. The significantly positive impact of FINAN could be implied that the working
capital or high organizational slack could benefit for domestic firm productivity.
The study adopts sub-sample approach by splitting the sample into 4 groups to explore
the sensitivity of FDI spillovers to the different ranges of the technology gap. The high
technology level group consists of firms having productivity higher than average
productivity of foreign firms in the same industry. The low technology gap group consist
of firms with the technology gap below 25th percentile of the technology gap distribution
of all examined domestic firms, medium and high technology gap groups consist of the
firm with technology gap lying between 25th to 75th percentile and over 75th percentile
respectively.



298 | ICUEH2017


Table 2
Overall and Sub-grouping regression results
Dependent
variable

LN_TFP
High

Low

Medium

High

Technology Level

Technology Gap

Technology Gap

Technology Gap

0.5750***

-2.1198

-0.9374***

0.9920***

0.4052***

(0.0356)

(1.3886)

(0.1309)

(0.0630)

(0.1043)

3.0038***

0.1148

3.3447***

3.7262***

4.5619***

(0.0744)

(4.3900)

(0.3345)

(0.1297)

(0.2114)

3.3322***

-7.8989

5.7012***

4.4051***

4.5547***

(0.0929)

(6.5826)

(0.3719)

(0.1620)

(0.3113)

0.0137***

-0.1415*

0.0091*

0.0190***

0.0227***

(0.0025)

(0.0846)

(0.0048)

(0.0033)

(0.0073)

-0.0006**

0.0020

0.5709***

0.0945***

-0.0111***

(0.0003)

(0.0039)

(0.0331)

(0.0143)

(0.0033)

4.4492***

-7.6435*

4.0640**

3.7455

11.3694***

(0.9523)

(3.9758)

(1.7354)

(2.2869)

(4.4087)

0.0000***

0.0002

0.0000

0.0000***

0.0002***

(0.0000)

(0.0010)

(0.0000)

(0.0000)

(0.0001)

0.0003*

-13.1611

0.0004***

0.0005

0.0007

(0.0001)

(102.2326)

(0.0001)

(0.0003)

(0.0012)

-0.0000*

0.3971

0.0011

-0.0001***

-0.0003***

(0.0000)

(2.9269)

(0.0008)

(0.0000)

(0.0000)

Yes

Yes

Yes

Yes

Yes

-1.8115***

-0.7609

-3.4803***

-2.9050***

-1.1754***

(0.0538)

(29.7102)

(0.1894)

(0.0941)

(0.1680)

N

815268

15379

198174

400673

201042

R-sq

0.0623

0.2138

0.0700

0.0760

0.0672

H_FDI

FWD_FDI

BWD_FDI
SCALE

TECH_GAP

MS

FINAN

IMPORT_INT

EXPORT_INT

Control firm
size
_cons

All firms

Notes: All regressions are restricted to domestic firms. Robust standard errors in brackets.
Standard errors in parentheses * p<.10, ** p<.05, *** p<0.01


Nguyen Van Phuong et. al. | 299


As presented in Table 2, foreign firms outperform domestic firms in terms of
productivity level. This study finds significant relationship of horizontal and vertical,
including both backward and forward spillovers to productivity of domestic firms in
Vietnam of period 2011-2015. This result consistent with Nicolini and Resmini (2010)
examine data of Bulgaria, Poland, and Romania. This positive spillover is consistent with
firms having the medium and high technology gap. However, the empirical analysis also
shows that horizontal spillovers has negative effect on productivity of domestic firms with
the low technology gap. It could be explained by the hypothesis of FDI spillovers has been
offset by the increase in competitiveness. The higher penetration of foreign firms in the
industry, the higher market share is controlled by foreign firms. Domestic firms have to
compete with foreign firms having larger capital stock, which is a considerable advantage
among firms with the similar productivity level. Aitken and Harrison (1999), and Jeon et
al. (2013) predict negative horizontal spillovers could occur in low technology or high
fixed cost sectors.
In general, the technology gap has been proven empirically that it could prevent the
FDI spillover. However, the negative impact of the technology gap is just significant for
domestic firms having the high technology gap, or we could say firms with the low and
medium technology gap could overcome the drawback of the gap.
In the context of international trading policies, we find a positive relationship between
import intensity and productivity of domestic firms. Import is the channel of knowledge
spillovers. This finding consistent with the result of Dmijan and Knell (2005)’s studying
the case of Slovenia and Estonia. However, our investigation shows the negative
relationship of export intensity and firm productivity among the firms with the medium

and high technology gap. This phenomenon could be explained that these Vietnamese
firms have the low level of technology and they export products required low technology
application.
5. Conclusion
The relationship between FDI and firm productivity still attracts concern to many
researchers. While this topic has been provided rich insight into the impacts of FDI
spillovers, few empirical researches have investigated for the case of Vietnam. In this
study, we examine the effects of FDI spillovers on the productivity of domestic firms.


300 | ICUEH2017


Based on the sample of 331,741 service and manufacturing firms operation in Vietnam in
the period from 2011 to 2015, we illustrate how the spillovers from FDI occurs for the
domestic firms. Horizontal and vertical spillovers impact positively on productivity of
domestic firms. The technology gap is considered as a vital condition for technology
spillovers. Among firms having the low technology gap, horizontal spillovers are offset by
pressure in competitiveness that FDI firm bring to. The technology gap also prevents the
development of productivity of the domestic firms with the high technology gap.
International trade strategies are discussed via firms’ import intensity and export
intensity. The empirical results showed the positive impact of importing activities on
productivity of domestic firms, while exporting activities related negatively to the level of
technology of domestic firms. Several specific characteristics of domestics firms are
examined, and the high organizational slack appears to relate positively to firm
productivity.

References
Aitken, B. J., & Harrison, A. E. (1999). Do domestic firms benefit from direct foreign investment? Evidence
from Venezuela. American economic review, 605-618.

Bernard, A. B., & Jensen, J. B. (1999). Exceptional exporter performance: cause, effect, or both?. Journal of
international economics, 47(1), 1-25.
Blalock, G., & Gertler, P. J. (2004). Learning from exporting revisited in a less developed setting. Journal of
Development Economics, 75(2), 397-416.
Blalock, G., & Gertler, P. J. (2008). Welfare gains from foreign direct investment through technology
transfer to local suppliers. Journal of International Economics, 74(2), 402-421.
Blalock, G., & Veloso, F. M. (2007). Imports, productivity growth, and supply chain learning. World
Development, 35(7), 1134-1151.
Blomström, M., & Kokko, A. (1998). Foreign investment as a vehicle for international technology transfer.
In Creation and Transfer of Knowledge (pp. 279-311). Springer, Berlin, Heidelberg.
Caves, R. E. (1974). Multinational firms,
markets. Economica, 41(162), 176-193.

competition,

and

productivity

in

host-country

Connolly, M. (2003). The dual nature of trade: measuring its impact on imitation and growth. Journal of
Development Economics, 72(1), 31-55.


Nguyen Van Phuong et. al. | 301

Damijan, J. P., Rojec, M., Majcen, B., & Knell, M. (2013). Impact of firm heterogeneity on direct and spillover
effects of FDI: Micro-evidence from ten transition countries. Journal of comparative economics, 41(3),
895-922.
Djankov, S., & Hoekman, B. (2000). Foreign investment and productivity growth in Czech enterprises. The
World Bank Economic Review, 14(1), 49-64.
Findlay, R. (1978). Relative backwardness, direct foreign investment, and the transfer of technology: a
simple dynamic model. The Quarterly Journal of Economics, 92(1), 1-16.
Fosfuri, A. (2002). Country risk and the international flows of technology: evidence from the chemical
industry. Universidad Carlos III de Madrid. Departamento de Economía de la Empresa.
Fosfuri, A. (2004). Determinants of international activity: evidence from the chemical processing
industry. Research Policy, 33(10), 1599-1614.
Girma, S., & Gong, Y. (2008). FDI, linkages and the efficiency of state-owned enterprises in China. The
Journal of Development Studies, 44(5), 728-749.
Glass, A. J., & Saggi, K. (1999). Foreign direct investment and the nature of R&D. Canadian journal of
Economics, 92-117.
Glass, A. J., & Saggi, K. (2002). Intellectual property rights and foreign direct investment. Journal of
International economics, 56(2), 387-410.
Görg, H., & Greenaway, D. (2004). Much ado about nothing? Do domestic firms really benefit from foreign
direct investment?. The World Bank Research Observer, 19(2), 171-197.
Haddad, M., & Harrison, A. (1993). Are there positive spillovers from direct foreign investment?: Evidence
from panel data for Morocco. Journal of development economics, 42(1), 51-74.
Hamida, L. B. (2013). Are there regional spillovers from FDI in the Swiss manufacturing
industry?. International Business Review, 22(4), 754-769.
Javorcik, B. S., & Spatareanu, M. (2008). To share or not to share: Does local participation matter for
spillovers from foreign direct investment?. Journal of development Economics, 85(1), 194-217.
Javorcik, B.S. (2004). Does foreign direct investment increase the productivity of domestic firms? In search
of spillovers through backward linkages. The American Economic Review, 94(3), 605-627.
Jeon, Y., Park, B. I., & Ghauri, P. N. (2013). Foreign direct investment spillover effects in China: Are they
different across industries with different technological levels?. China Economic Review, 26, 105-117.
Jude, C., & Levieuge, G. (2015). Growth effect of FDI in developing economies: the role of institutional

quality.
Keller, W. (1996). Absorptive capacity: On the creation and acquisition of technology in
development. Journal of development economics, 49(1), 199-227.
Liu, X., Siler, P., Wang, C., & Wei, Y. (2000). Productivity spillovers from foreign direct investment:
Evidence from UK industry level panel data. Journal of International Business Studies, 31(3), 407-425.
Liu, Z. (2002). Foreign direct investment and technology spillover: Evidence from China. Journal of
comparative Economics, 30(3), 579-602.


302 | ICUEH2017


Liu, Z. (2008). Foreign direct investment and technology spillovers: Theory and evidence. Journal of
Development Economics, 85(1), 176-193.
Nicolini, M., & Resmini, L. (2010). FDI spillovers in new EU member states. Economics of Transition, 18(3),
487-511.
Perri, A., & Peruffo, E. (2016). Knowledge spillovers from FDI: a critical review from the international
business perspective. International Journal of Management Reviews, 18(1), 3-27.
Walz, U. (1997). Innovation, foreign direct investment and growth. Economica, 64(253), 63-79.
Wang, J. (2013). The economic impact of special economic zones: Evidence from Chinese
municipalities. Journal of development economics, 101, 133-147.
Wang, J. Y. (1990). Growth, technology transfer, and the long-run theory of international capital
movements. Journal of International Economics, 29(3-4), 255-271.
Wang, J. Y., & Blomström, M. (1992). Foreign investment and technology transfer: A simple
model. European economic review, 36(1), 137-155.


Nguyen Van Phuong et. al. | 303

Appendix
Table 3
Correlation
LN_TFP
LN_TFP





H_FDI

FWD_FDI

HUM_CAP

SCALE

TECH_GAP

MS

IMPORT_INT

EXPORT_INT

FINAN

1

H_FDI

0.0657*

1

FWD_FDI

-0.0096*

-0.1836*

1

HUM_CAP

0.0135*

0.0018*

-0.0089*

1

SCALE

0.1847*

0.0041*

-0.0058*

0.0214*

1

TECH_GAP

-0.0032*

0.0392*

-0.0250*

0.0002

-0.0020*

1

MS

0.1648*

0.0816*

-0.0187*

0.0184*

0.3686*

-0.0093*

1

IMPORT_INT

0.0068*

0.0038*

0.0017

0.0002

0.0016

0.0011

0.0013

1

EXPORT_INT

-0.0017

0.0012

-0.0006

0.0001

-0.0003

-0.0006

-0.0001

0.0094*

1

FINAN

0.0013

-0.0001

-0.0022*

-0.0007

0.0008

-0.0002

0.0004

-0.0000

-0.0000

1