Article
Impact of FDI on
Economic Growth
in South Asia: Does
Nature of FDI
Matters?*
Review of Market Integration
12(1–2) 51–69, 2020
© 2020 India
Development Foundation
SAGE Publications
sagepub.in/home.nav
DOI: 10.1177/0974929220969679
http://journals.sagepub.com/home/rmi
Saswata Chaudhury1, Nitya Nanda2 and
Bhawna Tyagi3
Abstract
Foreign direct investment (FDI) is believed to be an important
determinant of economic growth in developing countries, but its impact
varies across countries. Presence of other determinants (like domestic
investment, inflation, infrastructure and external trade) may augment
or retard the potential impact of FDI on economic growth. Moreover,
due to the non-homogeneous nature of sectoral FDI, the sectoral
composition may create differential impact on economic growth. Hence,
it is necessary to identify and measure the differential impact of sectorwise (primary versus secondary versus tertiary sector) FDI inflow.
Exploring the nature and behaviour of overall and sectoral FDI inflow in
South Asian countries in the recent past, this article has taken a holistic
approach in studying and analysing the FDI-growth dynamics. The study
found that the impacts of FDI in South Asia are indeed influenced by
sectoral composition of FDI.
*This article is an outcome of a project supported by South Asia Network of Economic
Research Institutes under 16th RRC.
The Energy and Resources Institute, New Delhi, Delhi, India.
Council for Social Development, New Delhi, Delhi, India.
3
Alliance for an Energy Efficient Economy, New Delhi, Delhi, India.
1
2
Corresponding author:
Saswata Chaudhury, The Energy and Resources Institute, New Delhi, Delhi 110003, India.
E-mail: saswatac@teri.res.in
52
Review of Market Integration 12(1–2)
JEL Classification: F21, O47, C33, F6, O2
Keywords
Foreign direct investment, economic growth, South Asia, panel data
analysis
Introduction
Background
Spate of economic liberalisation since 1980s resulted in the flow of
private capital in the form of foreign direct investment (FDI) across
many developing countries. Foreign investment, particularly FDI, has
often been seen as a major source of foreign exchange, which helps in
easing the balance of payment constraint on economic growth. Moreover,
it also supplements domestic investment resources required to thrust
economic growth. This widely held perception regarding the foreign
investment resulted in changing the policy environment of the economies
to attract FDI. In the 1980s and 1990s, China and Southeast Asian
countries made remarkable improvement in economic growth through
the use of large amounts of FDI. In the early years of their independence,
South Asian countries followed a restrictive policy regime and changed
their regime in the last two/three decades to make it conducive to foreign
investment. With dominant role being assigned to the state in the
development process, focus of import substituting industrialisation
policies was promoted to attain self-reliance in such early period.
However, economic growth achieved in these countries was rather
subdued. Following the success of Southeast Asian countries, South
Asian countries also followed economic reforms with emphasis on
market economy and aimed at integrating their economy with rest of the
world.
South Asian countries have the potential to attract FDI as they possess
various advantages to offer to foreign investors such as vast domestic
market, single digit inflation, increasing proportion of skilled personnel,
emerging entrepreneurial class and constantly improving financial
systems (Sahoo, 2006). In the present scenario, South Asian countries
have emerged as potential destination for investment. Thus, it becomes
crucial to identify the impact of FDI inflows on the economic performance
of these countries.
Chaudhury et al.
53
Current Scenario and Trend in FDI
In the last two decades, global FDI inflow has increased by more than
five times (USD 341 billion in 1995 to USD 1.76 trillion in 2015). Over
time, share of developing countries in global FDI inflow has increased,
while the share of developed countries has declined (till 2014). In 2000,
the share of developed countries was as high as 82.5 per cent, while that
of developing countries was 17 per cent only. In 2014, the share of
developing countries was approximately 55 per cent, and the share of
developed countries declined to 41 per cent. In 2015, the share of
developing and developed countries in global FDI inflow was 43 per
cent and 54 per cent respectively. During 2010–2015, the average growth
rate of global FDI inflow was 6.2 per cent. In this period, growth of FDI
inflow was 4.2 per cent for developing countries and 12 per cent for
developed countries. However, after the 1990s, when the process of
liberalisation started in most of the South Asian countries, the share of
Asian countries varies within a range of 60–70 per cent of FDI inflow in
all developing countries. Within Asia, most important FDI destination
was the South-East Asia region. However, the share of South Asian
countries varied in the range of 8–10 per cent in the last five years. In this
period, average growth rate of FDI inflow in South Asian countries was
9.5 per cent (World Investment Report 2016).
In South Asia, the largest FDI destination is India. It has a share
ranging between 75 and 87 per cent in total South Asian FDI inflow.
Bangladesh and Sri Lanka are the other two important FDI destinations
in South Asia. The share of remaining four countries (Afghanistan,
Bhutan, Nepal and Pakistan) is small (individual share less than one per
cent). In the last five years, average growth rate of FDI inflow in India
was 13 per cent. However, within the region, highest growth was
observed in Bangladesh (21%) followed by Maldives (19%) in the same
period.
In 2014, the share of FDI inflow in global GDP was about 1.7 per
cent, while it was 2.6 per cent for developing and 1.1 per cent for
developed countries. In case of South Asian countries, the share of FDI
inflow in regional GDP was 1.4 per cent. The corresponding figure was
1.7 per cent for India, 1.3 per cent for Sri Lanka and 12.2 per cent for
Maldives in 2014. On the other hand, per capita global FDI inflow was
USD 180.6, while it was USD 129.2 and 474.4 for developing and
developed countries, respectively. Per capita FDI inflow was USD 23.2
for South Asian countries and 27.2 for India in particular in the year
2014. Per capita FDI inflow was highest in Maldives (USD 1,033.3)
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Review of Market Integration 12(1–2)
followed by Sri Lanka (USD 44) within the South Asian region. In case
of Maldives, total FDI inflow was 111 per cent of its merchandize trade
in 2014. The corresponding figures were 6.9 per cent in the global
context, 8.9 per cent for developing countries, 9.8 per cent for developed
countries, 8.6 per cent for the South Asian countries and 10.7 per cent in
case of India. Similarly, FDI inflow contributed more than 50 per cent
(average of 2010–2014) of gross fixed capital formation for Maldives.
The corresponding figure varied in the range of 8–9 per cent for global,
developing and developed countries. However, it was 4–5 per cent for
the South Asian region and India.
The section ‘Literature Review’ reviews the relevant theoretical and
empirical literature on growth impacts of FDI with special reference to
differential impacts in different sectors. The section ‘Methodology’
describes the methodology used in the study as well as the data used
along with their sources. The section ‘Empirical Results’ presents and
analyses the empirical results obtained from the econometric modelling
exercise. The section ‘Conclusion’ concludes this article and also draws
some policy implications.
Literature Review
Post 1990s, most of the South Asian countries initiated the process of
liberalisation and opened up their economy to foreign capital flows. As a
result, the recent years witnessed a tremendous rise in FDI in this region,
but the impact of FDI on economic growth remains ambiguous.
Consequently, researchers and policy makers have initiated paying
attention to the studies concerning the impact of FDI with respect to
these economies. In view of the ambiguity about the role played by FDI,
present study enters the stream investigating the impact of FDI and other
determining factors in case of South Asian economies.
There is lack of consensus regarding the impact of FDI on economic
growth. There are two contrasting views regarding the impact of FDI on
growth. First is the modernisation theory, which argues that FDI has
positive impact by providing capital for investment and via knowledge
transfer. The second view is of dependency theory, in accordance to
which FDI has negative impact on economic growth. It is based on the
premise that FDI creates monopolies, which prevents full utilisation of
domestic resources and thereby weakening the potential multiplier
effect.
Chaudhury et al.
55
Some studies (e.g., Blomstrom et al., 1994; Borensztein et al., 1998)
argue that inflow of FDI might help to stimulate a country’s economic
performance via technology transfer and spill over efficiency. The spill
over efficiency occurs when domestic firms are able to absorb the
tangible and intangible assets of multinational corporations embodied in
FDI. In contrast to this, some studies (like Bloomstorm & Kokko, 2003)
argue that spill over of foreign technology and skills to local industry are
not an automatic consequence of inflow of FDI. Benefits can be realised
only if the local industries already have the capacity to absorb such spill
over effects.
However, there are many studies (e.g., Griffin, 1970; Singer, 1950)
that recognised the negative impacts of FDI on economic growth in case
of developing countries. In a recent study, Saqib et al. (2013) confirmed
that foreign investment had negative effect on the economic performance
of the Pakistan economy while domestic investment benefits the
economy more. Herzer (2012) found out that FDI has negative impact on
the growth rate of developing countries over the period of 35 years. He
concluded that removal of market distortionary policies, natural resource
dependence and enhancement of economic and political stability can
protect countries from negative consequences of FDI and promote FDI
led growth in the long run. On the other hand, Minhaj et al. (2007) also
concluded that FDI inflows improve the socio-economic condition of the
economy both in the short run and long run.
Trade openness also has been identified by many studies (e.g.,
Agrawal, 2000; Balasubramanyam et al., 1996; Iqbal et al., 2014) as a
pre-requisite condition to reap positive benefit of FDI. This largely stems
from Bhagwati’s hypothesis that FDI has greater impact on GDP in an
export oriented economy. Iram and Nishat (2009) studied the FDIgrowth nexus in case of manufacturing and service sectors of Pakistan
economy. They found out that macroeconomic stability and privatisation
policies play crucial role in realising the impact of FDI on economic
growth and also there is a need to devise export oriented policies. Tintin
(2012) analysis also supported the FDI-growth positive nexus but
showed that impact is higher in case of developing countries compared
to developed and least developed countries. He puts emphasis on proFDI policies and on improvement in quality of institution as they are
inter-linked with growth and development. Similar recommendations
were made by African Development Bank (2015) in case of North Africa.
The study also suggested that, to reduce inequality, investment should be
made in labour-intensive and pro-poor sectors such as agriculture,
fishing and so on.
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The empirical evidence of FDI impacts on economic growth at the
firm level and at the national level still remains ambiguous and varies
across economy and time period. Several studies (Aitken & Harrison,
2000; Katerina et al., 2004; Wiboonchutikula & Tubtimtong, 2010)
have rejected the hypothesis that presence of foreign firms has positive
spill over effect on domestic firms. In contrast to this view, Agrawal
(2000) finds the existence of complementarity and inter-linkage effects
between foreign and national investment in case of five South Asian
countries; India, Pakistan, Bangladesh, Sri Lanka and Nepal. Findlay
(1978) and Ray et al. (2015) also highlighted the positive effect through
technology spill overs, which has the strongest potential to enhance
economic growth in the host country. The studies concludes that investor
companies have brought with them global best practices and also
contributed significant knowledge transmission from the home country
to the host country in the form of advanced software, internal training
programmes, etc.
To explore the role of sectoral composition of FDI, Ingham et al.
(2020) has acknowledged the heterogeneous sectoral growth effect of
FDI in case of Egypt. They found that, sectoral destination of FDI plays
significant role in development of the economy. In case of Egypt, while
FDI in manufacturing sector had positive growth effect, FDI in service
sectors (like finance, retail and telecom) resulted in adverse impact. On
the other hand, Khan and Khan (2011) found that sectoral composition
of FDI has been important in Pakistan also. They found that FDI in
primary and service sector resulted in economic growth but FDI had
very limited role in manufacturing sector. But, in case of Nepal, Phuyal
and Sunuwar (2018) found that FDI in all sectors had positive and
significant effect on economic growth. Based on disaggregated sectoral
analysis, the study suggested that government should give priority to
export oriented FDI over domestic demand oriented FDI to foster
economic growth.
Some studies also came to the conclusion that there is no evidence of
significant effect of FDI on economic growth. Lund (2010) investigated
the data for both developed and developing and found out that FDI does
not act as a catalyst in promoting growth of developing countries as it
has been advocated in many other studies. He also emphasised that
certain level of development is a pre-requisite for reaping the maximum
benefits of FDI. In case of Nigeria, Uwubanmwen and Ajao (2012)
found that FDI does not have significant effect on growth and
development but advocated that vital role is being played by stable
macroeconomic variables and trade openness to promote growth and
Chaudhury et al.
57
development of Nigerian economy. Lean (2008) did not find long-term
relationship between FDI and GDP in manufacturing sector in case of
Malaysia. Asheghian (2011) did not find any evidence in support of FDIled growth in Canada over a period of 33 years, but identified total factor
productivity and domestic investment as major determinants of economic
growth. Blomstrom et al. (1994) and Blomstrom and Kokko (2003) also
advocated the argument that FDI inflows benefit developing countries
with an educated work force through significant technology spill overs.
Thus, the existing literature reveals that there is a lack of consensus
regarding the role played by FDI in promoting economic growth. It also
indicates that composition of FDI may be important to determine level
and pattern of economic growth. FDI inflow in manufacturing sector
may have different economic impact vis-à-vis FDI in service sector.
Thus, other than analysing the role of overall FDI, sectoral composition
of FDI may be crucial to strategize the desired growth policy. Hence,
analysing the impact of overall FDI may not be sufficient, and it is
required to identify and measure the impact of sectoral (primary versus
secondary versus tertiary sector) FDI also. This study addressed this
information gap and analysed the role of FDI composition (sectoral
destination) in economic growth in the context of select South Asian
countries. The next section illustrates the methodology used in the study.
Methodology
This article analysed the panel data of eight South Asian countries over
a period of 25 years (1990–2014)) to measure the impact of FDI (overall)
on economic growth. The study also tried to identify the factors which
play important role to augment or retard the influence of FDI and
analysed the nature of their influence. However, we dropped labour as
explanatory variable given the fact that the entire sample of countries are
labour surplus economies. Again, due to lack of availability of sufficient
data on infrastructure (especially for Afghanistan and Bhutan), we are
also needed to drop infrastructure as an explanatory variable. Since, FDI
investment needs some time to influence economic growth; we have
introduced lagged value of FDI. The number of lags required has been
identified by literature. Moreover, choosing lagged FDI will also help
the study to overcome the influence of economic growth on FDI. The
following two sections will discuss the empirical model and the variables
considered in this study for the overall and sectoral analysis of the study.
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Review of Market Integration 12(1–2)
While the overall FDI impact was measured for all eight South Asian
countries, sectoral impact was measured only for Bangladesh, India,
Pakistan and Sri Lanka due to unavailability of sectoral FDI data for
other neighbouring countries.
Measure the Impact of Overall FDI
To measure the nature and degree of FDI impact on economic growth,
the following empirical model has been selected:
Ygt = b0 + bf* FDIt-m+bk*Kt-m +bp*Pt + Be*ETt + Bc*CVt + Ɛ
where
br (r=0/f/k/p/e/c) represents the coefficients that measure the
degree of impact of each independent factors on dependent
variable and its sign represents nature of impact.
t represents time period and m represents time lag (m=1,2,3,…).
Yg represents economic growth measured in terms of growth of
GDP.
FDI represents total FDI inflow which can be measured by net
FDI inflow–GDP ratio.
K represents capital investment which can be measured by gross
domestic capital formation.
P represents inflation which can be measured by GDP deflator/
change in WPI or CPI.
ET represents the external trade which can be measured by total
export/total import/net export.
CV represents any other control variable like status of livelihood
(measured by HDI) or level of education or human capital factor
(like gross enrolment ratio/mean year of school/literacy rate) and/
or any health indicator (like health expenditure per capita/health
expenditure-GDP ratio/health output like maternal mortality rate/
infant mortality rate).
Ɛ represents the error term, which is the residual impact not being
captured by any of the explanatory variables.
Measure the Impact of Sectoral FDI
Based on literature, this study has measured the effect of the sectoral FDI
on economic growth through the following empirical model specification:
Chaudhury et al.
59
Ygt = b0 + bf* JFDIt-m+bk*Kt-m +bp*Pt + Be*ETt + Bc*CVt + Ɛ
where
br (r=0/f/k/p/e/c) represents the coefficients which measures the
degree of impact of each independent factors on dependent
variable and its sign represents nature of impact.
t represents time period and m represents time lag (m = 1,2,3,…).
Yg represents economic growth measured in terms of growth of
GDP.
JFDI represents (primary/secondary/tertiary) sectoral FDI inflow
which can be measured by net sectoral FDI inflow to GDP ratio.
K represents capital investment which can be measured by gross
domestic capital formation.
P represents inflation which can be measured by GDP deflator/
change in WPI or CPI.
ET represents the external trade which can be measured by total
export/total import/net export.
CV represents any other control variable like status of livelihood
(measured by HDI) or level of education or human capital factor
(like gross enrolment ratio/mean year of school/literacy rate) and/
or any health indicator (like health expenditure per capita/health
expenditure-GDP ratio/health output like maternal mortality rate/
infant mortality rate).
Ɛ represents the error term which is the residual impact not being
captured by any of the explanatory variables included in the model.
Based on the above specified empirical models and panel data, this
study has measured the impact of FDI (overall and sectoral) on economic
growth. The influences of other important factors on economic growth
were also identified and their influence measured. Once the impact of
FDI is identified, we checked for the presence of specification error, if
any occurred due to assuming the simple model specification. The results
of the empirical analysis have been discussed in the next section.
Data Source and Data Period
The data are collected for the period from 1990 to 2014. Cross country
data on variables such as GDP growth, inflation, mean year of schooling,
gross capital formation, exports and health expenditure is taken from
World Economic Outlook (World Bank database). Overall FDI flow data
were retrieved from UNCTAD FDI statistics. Sectoral FDI flow data
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Review of Market Integration 12(1–2)
were extracted from International Trade Centre database complemented
by individual country Central Bank or ministry of commerce/trade or
other secondary sources.
Empirical Results
Given the data on the eight South Asian countries in the selected time
period (1990–2014) and empirical models (specified in the methodology
section), this article has analysed the models in panel data framework
using econometric software STATA. Using different proxies for each
dependent and independent variables and different combination of
independent variables, the final set of variables, which were found to
have significant influence on economic growth and FDI impact on
economic growth, were tabulated in the appendix section. This section
will analyse the nature and degree of impact of FDI and other control
variables on economic growth. Before this empirical analysis, statistical
test for presence of heteroscedasticity, auto-correlation and multicollinearity have been checked in the above mentioned panel data. It was
ensured that these problems are either absent in the sample data or if
present, then sufficient measures were taken to deal with the problem.
Impact of Overall FDI
FDI (one period lagged, that is FDI of previous year) has significant
positive impact on economic growth measured in terms of GDP growth
(Table 1). The presence of positive significant impact is in line with most
of the studies based on developing country literature (Germidis, 1977;
Mansfield & Romeo, 1980; Minhaj et al., 2007). The effect is robust, that
is, effect remains significant and positive across different combination of
control variables. To complement the impact of FDI, the role of domestic
investment (gross domestic capital formation) is important. In this study,
the role of domestic investment (current period) is positive and consistent
(however not statistically significant). Moreover, the effect of export on
economic growth was found to be mixed, positive in some cases and
inverse in some other cases. Again, this effect is not statistically
significant. Effect of inflation is negative and significant in most cases.
It indicates that the presence of high inflation is detrimental to economic
growth, and it retards the potential impact of FDI. On the other hand, we
found positive and consistent impact of HDI.
61
Chaudhury et al.
Table 1. Impact of Overall FDI on Growth (Dependent Variable: Growth of GDP)
Overall FDI
b/se
FDI (lag 1)
366.152
Inflation
b/se
***
260.102
b/se
***
(85.48)
(72.23)
(100.74)
(76.89)
–0.379*
–0.318
–0.331*
(0.17)
(0.15)
(0.17)
(0.15)
–0.103
–0.033
(0.10)
(0.08)
HDI
14.085
15.091
(10.47)
(14.11)
–0.087
0.03
–0.209
–0.033
(0.12)
(0.09)
(0.14)
(0.10)
0.137
0.072
Domestic investment
Constant
N
217.347**
–0.371*
Domestic investment
(lag 1)
Export
266.385
b/se
**
(0.13)
(0.09)
5.201
9.476***
1.561
7.964**
(4.67)
(2.36)
(6.65)
(2.75)
125
148
124
146
Source: Original calculation of the authors.
Note: 1. *Significant at 1% level, **Significant at 5% level and ***Significant at 10% level.
2. b is regression coefficient while figure in parentheses are standard error (se).
Impact of Sectoral FDI
Based on the stage and status of economic development, different
country attracts FDI in different sectors. However, in many countries
(like India), FDI is restricted in primary sector. Based on different
country experience, this study has explored whether FDI composition
(sectoral destination) has any role in the growth trajectory.
FDI (with one period lag) in tertiary sector has positive robust impact but
the impact is not statistically significant (Table 2). While the effect of current
domestic investment is positive and robust, previous year domestic investment
was found to have mixed effect. However, in all cases, effects are not
statistically significant. Similarly, effect of HDI is neither significant nor
consistent. However, we found, robust and negative impact of inflation as
well as export. But, again, the effects are not statistically significant.
–10.687
(16.25)
53
–0.274
(0.40)
–0.562
(0.38)
57.394
(41.59)
1.37E+08
(2.37e+08)
0.066
(0.19)
b/se
10.063
(8.66)
53
0.732
(17.70)
–0.14
(0.39)
1.76E+08
(2.39e+08)
–0.018
(0.18)
b/se
b/se
–0.184
(0.40)
–0.621
(0.36)
58.649
(40.78)
0.206
(0.18)
–14.345
(15.79)
53
94209487
(2.35e+08)
b/se
–4.182
(17.80)
0.133
(0.18)
8.387
(8.63)
53
–0.047
(0.40)
1.35E+08
(2.39e+08)
b/se
0.139
(0.16)
6.35
(4.91)
56
–0.115
(0.30)
1.74E+08
(1.94e+08)
b/se
Significant at 10% level. 2. b is regression coefficient while
***
9.738*
(4.73)
56
–0.144
(0.30)
1.81E+08
(1.95e+08)
0.014
(0.16)
Note: 1. *Significant at 1% level, **Significant at 5% level and
figure in parentheses are standard error (se).
Source: Original calculation of the authors.
N
Constant
Domestic investment
Export
HDI
Domestic investment
(lag 1)
Inflation
Tertiary sector FDI
(lag 1)
Tertiary Sector FDI
Table 2. Impact of FDI Flowing into Tertiary Sector on Growth (Dependent Variable: Growth of GDP)
Chaudhury et al.
63
Effect of FDI (with one period lag) in secondary sector on economic
growth is adverse and robust (Table 3). The effect is also significant in
all cases. This indicates that instead of augmenting growth, FDI coming
to the industrial sector might have retarded the growth process. This is
contrary to the conventional wisdom. But if FDI comes in the form of
M&A, it may have repercussions on domestic units. It may result in the
closure of domestic units and employment reduction with replacement of
domestic units and components with foreign units and components
(Nanda, 2008). This study also confirms the above mentioned argument
by indicating the important role played by domestic investment, which
leads to income and job creation for domestic population. As per this
study, we found positive and robust effect (not statistically significant) of
current period domestic investment. We also found robust impact (not
statistically significant again) of inflation, export and HDI. While the
effects of inflation and HDI were found to be positive, effect of export
was found to be negative in this study.
Primary sector FDI (with one period lag) has robust negative effect on
economic growth (Table 4). However, the effect is not statistically
significant. It might be possible that FDI brings more capital intensive
technology, which results in huge job losses. That huge job cut will
negatively affect economy as demand declines due to reduction in their
purchasing power. It can be mentioned here that mainly because of this
reason, many developing countries either restricts or put a ban on FDI in
primary sector. India is a classic example. Even after two decades of
liberalisation, FDI in primary sector is mostly banned and wherever
allowed is strictly regulated (with an exception of mining sector). Current
domestic investment has positive robust impact (but not statistically
significant) on economic growth. Similarly, export and HDI has robust
(again not significant) impact. While impact is positive for HDI, effect is
inverse for export. However, the effect of inflation is neither significant
nor consistent.
A minute comparison of sectoral FDI indicates that economic
growth is negatively affected by FDI in either primary or secondary
sector. On the other hand, FDI in tertiary sector has positive impact on
economic growth. In all cases, effects are robust or consistent for
different control variables. But, among the three sectors, FDI in
secondary sector has shown significant negative impact on economic
growth which may be explained by impact of M&A. FDI in secondary
sector could be mostly through M&A route as implementing a greenfield project in this sector is more challenging due to different regulatory
hurdles. Moreover, secondary sector as a whole did not show good
11.735
(7.44)
53
–2.873
(15.68)
53
3.592
(14.63)
42.701
b/se
b/se
53
(15.32)
–6.892
53
(7.45)
9.825
0.109
(0.17)
0.163
(14.72)
0.512
(0.30)
0.179
(3.34e+08)
–8.287e+08*
(0.17)
(39.01)
45.599
(0.36)
–0.447
(0.32)
0.039
(3.43e+08)
–7.217e+08*
b/se
56
(4.82)
8.908
(0.16)
0.18
(0.13)
–0.062
(0.28)
0.203
(3.30e+08)
–7.316e+08*
Note: 1. *Significant at 1% level, **Significant at 5% level and ***Significant at 10% level. 2. b is regression coefficient while figure in parentheses are
standard error (se).
56
(4.64)
11.893*
(0.13)
(39.73)
–0.024
(0.28)
(0.37)
(0.30)
(0.32)
0.154
(0.17)
0.057
(3.32e+08)
–0.388
0.138
(0.17)
(0.18)
0.008
–0.014
(3.34e+08)
(3.43e+08)
0.042
b/se
–7.666e+08*
b/se
–8.531e+08*
b/se
–7.648e+08*
Source: Original calculation of the authors.
N
Constant
Domestic investment
Export
HDI
Domestic investment (lag 1)
Inflation
Secondary sector FDI (lag 1)
Secondary sector FDI
Table 3. Impact of FDI Flowing into Secondary Sector on Growth (Dependent Variable: Growth of GDP)
2.533
(12.54)
47
–18.781
(18.72)
47
19.82
(28.64)
78.933
(48.13)
b/se
b/se
4.237
47
47
(12.66)
–19.392
(18.66)
0.007
(0.23)
0.079
(29.61)
8.328
(0.34)
0.156
(1.15e+09)
–7.81E+08
(0.22)
(48.67)
74.571
(0.38)
–0.641
(0.36)
–0.057
(1.12e+09)
–7.80E+08
b/se
50
(5.21)
7.223
(0.22)
0.164
(0.22)
–0.159
(0.32)
0.167
(9.46e+08)
–2186559
Note: 1. *Significant at 1% level, **Significant at 5% level and ***Significant at 10% level. 2. b is regression coefficient while figure in parentheses are standard
error (se).
50
(5.04)
9.889*
–0.05
(0.22)
(0.32)
0.174
(0.22)
–0.015
(‘9.56e+08)
(0.39)
(0.34)
(0.36)
b/se
–4.07E+08
–0.583
0.151
(0.22)
(0.22)
–0.055
–0.159
(1.12e+09)
–0.073
(1.10e+09)
b/se
–1.19E+09
b/se
–1.15E+09
Source: Original calculation of the authors.
N
Constant
Domestic investment
Export
HDI
Domestic investment (lag 1)
Inflation
Primary sector FDI (lag 1)
Primary sector FDI
Table 4. Impact of FDI Flowing into Primary Sector on Growth (Dependent Variable: Growth of GDP)
66
Review of Market Integration 12(1–2)
performance as compared to tertiary sector which has shown much
faster growth than primary and secondary sectors. As a result, FDI in
secondary sector might have come at the cost of domestic investment
(crowding out) as the slow growth in the sector could not absorb high
level of investment. Often, M&A has a tendency of assets stripping,
reduction of local employment and local resource use. All/some of
these factors can lead to reduction in job creation and income, which in
turn have the potential to retard economic growth. This finding can
also be validated by real scenario of South Asian countries. Even after
two decades of economic liberalisation, which channelised FDI inflow,
none of these countries were able to successfully develop their
industrial sector and induce economic growth.
Conclusion
Based on panel data on South Asian countries, this study has measured
the impact of overall and sectoral (for four selected South Asian
countries) FDI on economic growth. To overcome the influence of
economic growth on FDI and capture the reality (current period FDI has
limited scope to influence economic growth), lagged data on FDI were
used to measure the impact. The role of other factors that contribute to
economic growth were also identified and measured. It indicates
consistent impact of FDI as well as domestic investment. This study
reveals that while the overall FDI have positive and significant impact,
FDI in secondary sector has significant adverse impact on economic
growth. Domestic investment was found to have positive impact which
is significant in some cases. This study indicates that FDI has the
potential to augment economic growth but its composition is crucial. The
possibility that a part of FDI may be detrimental to economic growth
cannot be ignored. But, the study also indicates the important role played
by domestic investment. Therefore, it is important to attract FDI in
targeted sector and arrange complementary domestic investment for
achieving better economic growth. Thus, it is the responsibility of policy
makers to channelize the investment in proper direction and reap
maximum benefit in terms of economic growth.
The study has limitation as well. There are gaps in data on some
indicators for Afghanistan and Bhutan (Nepal and Maldives also in some
cases). The presence of such data gaps could cause significant cost in
empirical estimates in terms of loss of degree of freedom. This in turn
Chaudhury et al.
67
could have reduced the significance level of some of the estimates.
Moreover, due to absence of sectoral FDI data, this study could not
include these four countries in sectoral FDI analysis and finally used
panel data of remaining four countries (Bangladesh, India, Pakistan and
Sri Lanka) only. Better availability of data can significantly improve the
quality of the analysis.
Declaration of Conflicting Interests
The authors declared no potential conflicts of interest with respect to the research,
authorship and/or publication of this article.
Funding
This article received financial support from Asia Network of Economic Research
Institutes under 16th RRC.
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