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Pertanika J. Soc. Sci. & Hum. 26 (3): 2085 - 2100 (2018)
ISSN: 0128-7702
e-ISSN 2231-8534
SOCIAL SCIENCES & HUMANITIES
Journal homepage: http://www.pertanika.upm.edu.my/
Article history:
Received: 15 October 2017
Accepted: 25 June 2018
Published: 28 September 2018
ARTICLE INFO
E-mail addresses:
halsamman@du.edu.om (Hazem Al Samman)
syed_jamil@du.edu.om (Syed Ahsan Jamil)
* Corresponding author
© Universiti Putra Malaysia Press
The Impact of Foreign Direct Investment (FDI) on Stock Market
Development in GCC countries
Hazem Al Samman* and Syed Ahsan Jamil
Accounting and Finance Department, College of Commerce and Business Administration, Dhofar University,
P. O. Box 2509, PC 211, Salalah, Sultanate of Oman
ABSTRACT
Despite the huge number of studies in relation to the FDI, studies on the nexus between
FDI and stock market development in GCC are still limited. This paper investigates the
impact of FDI on stock market development in Gulf Cooperation Council countries that
have become an important economic trading bloc after inclusion of Saudi Arabia in the
G-20, leading to a big increase in stock prices and FDI in recent years. This research
utilised data from 2002 to 2015 for all the six GCC countries i.e. Bahrain, Kuwait, Qatar,
Saudi Arabia, the United Arab Emirates and Oman. Using four control variables, economic
growth, economic size, openness and domestic credit to private sector and utilising the
panel unit-root test, panel co-integration analysis and panel error-correction model, the
research concludes that foreign direct investment has played a long-term signicant role in
stock market development in GCC countries. Moreover, the research results on short-term
impact concludes that FDI affects stock market development positively but not signicantly.
From a policy perspective, the research evidence convincingly supports the increasingly
growing initiative of GCC governments to attract ow of FDI towards non-oil based sectors
to diversify their economies and develop stock markets.
Keywords: Error correction model, foreign direct investment, Gulf Cooperation Council, Johansen Fisher panel
co-integration test, stock market development
INTRODUCTION
Foreign direct investment (FDI) plays a
substantial role in economic development
of emerging countries by contributing in a
variety of ways such as transfer of technology,
creation of employment opportunities,
increase in overall productivity, decrease
in dependence on imports and enhancement
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of export potential, thus leading to overall
increase in economic growth (De Mello,
1999). In the past two decades, increasing
volumes of direct investment has been
flowing between and into developed
countries (Vu & Noy, 2009). In 2015, FDI
increased by 40% to USD1.8 trillion, the
biggest increase in FDI since the nancial
crisis of 2008. Also, the FDI of developing
countries reached USD765 billion in 2015,
increasing by 9% compared with 2014
(United Nations Conference on Trade and
Development [UNCTAD], 2016). Therefore,
most developing countries try to increase
their share of FDI by simplifying investment
procedure, granting tax incentives, ushering
in economic liberalisation and stabilising the
economy. In addition, the nancial system
has been developed to include the nancial
market in order to direct foreign investment
as this is crucial in the overall development
of the economy. The positive response of
all previous procedure in attracting FDI
must be reflected in the development of
the stock market (Adam & Tweneboah,
2009; Yartey, 2008). Therefore, the stock
markets are considered a mirror that reects
the health and strength of the economy
(Ramady, 2013). Empirical studies prove
that institutional and regulatory reform,
adequate disclosure and listing requirements
and fair trading practices promote foreign
direct investment in financial markets,
leading to expansion and development of
domestic markets. (Yartey, 2008).
There is a huge volume of studies in
the literature that investigated the role of
FDI on the host economy. Nevertheless,
the role of FDI has been debated among
researchers as well as between researchers
and policymakers . It should also be noted
that many researchers such as Djankov
and Bernard (1999); Kawai (1994), and
Mencinger (2003) have also recorded the
negative and null effect of FDI in developing
countries. Despite the extensive research
regarding foreign direct investment, most of
the studies have concentrated on the nexus
between FDI and growth of GDP. However,
only a limited number of research studies
have investigated the direct link between
FDI and development of the financial
market.
In the last two decades, policymakers
in the GCC countries have recognised the
importance of increasing FDI to achieve
economic growth so as to depart from
sole dependency on natural resources.
In addition, recent years have witnessed
a big increase in stock prices, market
capitalisation and trading volumes in GCC
countries (Ramady, 2013). Hence, this
research attempted to measure the impact
of FDI on stock market development for all
Gulf Cooperation Council (GCC) countries
from the period 2002 to 2015 using panel
data techniques. The importance of this
research is twofold: Firstly, it provides
new and recent evidence of the impact of
FDI on stock market development in GCC
countries. Secondly, it helps policymakers
in directing FDI to contribute to achieving
economic objectives and increasing the
optimal uses of FDI in GCC economies.
The rest of this paper is ordered in
the following way: Part 2 describes the
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FDI, stock market and economy of the
Gulf Cooperation Council (GCC). Part 3
summarises the literature review, while
Part 4 lays down the research methodology,
including the data and research model
used in the study. Part 5 presents the
empirical results and Part section 6 offers
the conclusion.
FDI, Stock Market and Economy of
Gulf Cooperation Council (GCC)
The Gulf Cooperation Council (GCC)
is a political and economic alliance
established in May 1981 by six Arab
oil-exporting countries i.e. Oman, Saudi
Arabia, the United Arab Emirates, Qatar,
Kuwait and Bahrain. These countries
have the same historical and cultural
background and share the same economic
characteristics. The GCC countries are
considered the wealthiest countries in the
world as per capita GDP, their economies
are highly reliant on hydrocarbon exports
and public expenditure in these countries
is mainly financed by oil revenue. GCC
countries aspire to reduce the exposure of
their economies to oil price changes by
diversifying their economies so as not to
rely solely on oil revenue (Ramady, 2013).
FDI plays an important role in implementing
diversification strategies. Under certain
circumstances, FDI can bring expertise,
technological capacity and skills in addition
to capital to economies that are not able
to develop certain sectors on their own
(Kurtishi-Kastrati, 2013). Empirical studies
in relation to FDI have proved that FDI
will be more benecial in weak diversied
economies such as the GCC countries than in
highly diversied economies. (Nicet-Chenaf
& Rougier, 2008). GCC countries have
recognised the importance of this and have
adopted new measures aimed at attracting
and encouraging foreign direct investment.
Policymakers of the GCC countries have
provided new incentives in the last two
decades to attract FDI to increase economic
growth and develop their stock markets.
These incentives include the establishment
of a regulatory, institutional and legal
framework to govern foreign investments.
In addition, the GCC increased foreign
ownership to 100%, reduced corporate taxes
and improved foreign investors’ access to
local stock markets (Ramady, 2013).
Table 1 summarises FDI in GCC
countries in 2005, 2010 and 2016. The GCC
countries received a big share from FDI in
the Arab world, reaching 64.86% in 2010.
The table shows that from 2005 to 2010,
Saudi Arabia was the biggest recipient of
FDI among the GCC countries amounting
to 64.39% in 2010. In 2016, FDI inows
fell to 38.28% compared with previous
years. The United Arab Emirates has
become the major recipient of FDI among
GCC countries, with FDI reaching 46.16%.
Overall, the two largest recipients of FDI
among GCC countries have been Saudi
Arabia and the United Arab Emirates. Over
the past decade, GCC countries have sought
to benet greatly from FDI and to develop
their nancial markets as a policy priority
among GCC countries. (Ramady, 2013).
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Table1
FDI in GCC countries
FDI in USD in Each County FDI in Each Country as
Percentage (%) from GCC
FDI in Each Country as
Percentage (%) from Arab World
Economy 2005 2010 2016 2005 2010 2016 2005 2010 2016
United Arab
Emirates 10899931926 8796769641 8985705000 38.48 19.37 46.16 38.48 12.57 23.30
Bahrain 1048601306 155771009.2 281914893.6 3.70 0.34 1.45% 3.70 0.22 0.73
Kuwait 233904109.6 1304627500 291958795.3 0.83 2.87 1.50% 0.83 1.86 0.76
Oman 1538361508 1242652796 1680894668 5.43 2.74 8.63% 5.43 1.78% 4.36
Qatar 2500000000 4670329670 773901098.9 8.83 10.29 3.98 8.83 6.67 2.01
Saudi Arabia 12106749694 29232706667 7452533333 42.74 64.39 38.28 42.74 41.76 19.33
GCC Countries 28327548545 45402857283 19466907790 100.00 100.00 100.00 61.57 64.86 50.48
Arab World 46007410075 70001307553 38562350207 162.41 154.18 198.09 100.00 100.00 100.00
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LITERATURE REVIEW
There is a large volume of research that
has investigated the inuence of FDI on
the host economy especially in terms of
economic growth. Choe (2003) investigated
the impact of FDI on the growth of the
gross domestic product (GDP) using the
Granger causality test in 80 developed and
developing countries in the period from
1971 to 1995. The results showed that
FDI led to growth of the GDP. Also, the
bidirectional causality relationship between
FDI and growth in GDP was documented by
Al-Iriani (2007) for Kuwait, Oman, Bahrain,
the United Arab Emirates and Saudi Arabia.
Similar results on positive influence of
FDI on growth of GDP were documented
by Faras and Ghali (2009), Umoh et al.
(2012) and Szkorupova (2014), while
Srinivasan et al. (2011) studied the long-
and short-term effects of FDI on growth
of GDP in ve ASEAN economies using
advanced econometric techniques, including
causality tests, co-integration and the error
correction model. The results proved the
existence of short-term causality between
FDI and GDP and provided evidence of
long-term inuence of FDI on the growth
of GDP. Also, Sothan (2016) studied the
direct inuence of FDI on the growth of
GDP on long- and short-term periods. He
used samples from 21 Asian countries and
utilised panel co-integration and the Granger
causality analysis to conclude on the existing
bidirectional causality relationship between
FDI and growth of GDP. In addition, he
proved the long-term inuence of FDI on
the growth of GDP.
The null effect of FDI on growth
of GDP has also been documented by
many researchers such as Chowdhury and
Mavrotas (2006); Manuchehr and Ericsson
(2001), and Sarkar (2007). Others such
as Djankov and Bernard (1999); Kawai
(1994), and Mencinger (2003) have also
documented the negative inuence of FDI .
Although the literature records
considerable investigation into the direct
link between FDI and GDP in the host
country, a few studies have investigated the
direct link between FDI and development
of the financial market in developing
countries, especially in the Arab world.
Adam and Tweneboah (2009) measured
the inuence of FDI on the development
of Ghana’s financial market. They used
the co-integration technique and the
error correction model, and their results
conrmed the long-term link between FDI
and the development of Ghana’s nancial
market. They concluded that shock to FDI
impacted on the development of Ghana’s
financial market. In a similar study, Al
Nasser and Soydemmir (2011) examined
the link between FDI and the development
of 14 Latin American financial markets
from 1978 to 2007. The results showed the
existence of a bidirectional link between
FDI and development of the financial
market, and the researchers concluded
that FDI allowed for and enhanced the
development of the financial market. In
another recent study, Shahbaz et al. (2013)
provided evidence of the direct inuence
of FDI on the development of the Pakistani
nancial market. Fauzel (2016) studied the
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role of FDI in development of the nancial
market. He used samples from small island
countries for the period 1990 to 2013. The
study found that FDI had a significant
inuence on the development of nancial
markets.
Raza and Jawaid (2014) utilised
advanced techniques in econometrics,
including the causality test and error
correction model to capture the effect
of FDI on the development of 18 Asian
nancial markets from 2000 to 2010. They
found that FDI negatively affected long- and
short-term market capitalisation, and they
concluded that FDI can mislead investors.
A similar study by Musa and Ibrahim
(2014) utilised advanced techniques in
econometrics, including co-integration
and the error correction model to measure
the inuence of FDI on the development
of the Nigerian nancial market between
1981 and 2010. They concluded that there
existed no significant role in the long-
run of FDI on the development of the
Nigerian nancial market. In a similar study,
Bayar and Ozturk (2016) studied the link
between FDI and development of nancial
markets in Turkey during the 1974-2015
period. They concluded that there was
unidirectional causality between FDI and
nancial development in Turkey.
In light of these empirical studies, it
can be noted that there is mixed evidence
on the effect of FDI on the host economy.
Moreover, no previous research has studied
the direct effect of FDI on stock market
development. Therefore, this research
lls the gap in the literature by examining
the influence of FDI on stock market
development in Gulf Cooperation Council
countries.
METHODS
Research Data
The research data were collected from the
World Bank database for all the six Gulf
Cooperation Council (GCC) countries from
2002 to 2015. In order to examine the impact
of FDI on stock market development , the
research utilised four control variables that
have been used widely in the literature:
economic growth, economic size, openness
and domestic credit to private sector for
the GCC countries, which are Oman, Saudi
Arabia, the United Arab Emirates, Qatar,
Kuwait and Bahrain.
Stock Market Development
There are different measures for stock
market development in the literature such as
size, market liquidity market concentration
and market volatility, to name only three.
This research used market capitalisation as a
proportion of GDP to measure stock market
development in GCC countries because it is
less arbitrary than other measures of stock
market development (Demirguc-Kunt &
Levine, 1996). This measure is equal to
market value of shares traded divided by
GDP (% of GDP), denoted by ST.
Foreign Direct Investment (FDI)
Foreign direct investment indicates the direct
investment equity flows in the reporting
economy. It is the sum of equity capital,
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reinvestment of earnings and other capital.
Most empirical studies related to FDI use the
net FDI inows as a percentage of GDP (%
of GDP) to proxy FDI (Alfaro et al., 2004;
Azman-Saini et al., 2010; Asongu, 2016.;
Bahri et al., 2017).
Economic Growth
Economic growth is dened as the annual
percentage growth rate of GDP at market
prices based on constant local currency.
This measurement is supported by most of
the empirical studies such as (Alfaro et al.,
2004; Azman-Saini et al., 2010; Bahri et al.,
2017; Bongini et al., 2017). This variable is
denoted by GROWTH.
Openness
Openness usually refers to a unit of the
country’s economic policy measurement,
also expressed as the trade openness index.
Most of the empirical studies proxy openness
as a proportion of the sum of exports and
imports to GDP (% of GDP) such as Gries
et al. (2009) and Yanikkaya (2003). This
research used this measurement to estimate
openness in GCC countries and denoted the
trade openness index as ‘openness’.
Domestic Credit to Private Sector
Domestic credit to private sector indicates
the financial resources provided to the
private sector that establish a claim for
repayment. Domestic credit to private sector
is measured as proportion of GDP (% of
GDP) and denoted by CR. This variable is
widely used in empirical studies (Bahri et
al., 2017; Bongini et al., 2017; Nezakati et
al., 2011).
Economic Size
This research used the natural logarithm
of GDP as proxy of economic size, which
is commonly used in the literature. GDP
is calculated at purchaser’s prices and is
equal to the sum of gross value added by
all resident producers in the economy plus
any product taxes and minus any subsidies
not included in the value of the products
(Anwar & Nguyen, 2010; Sothan & Zhang,
2017). This variable is denoted by ‘size’.
Research Model
Panel data analysis techniques were
utilised to measure the impact of FDI on
the development of the nancial market;
they included the panel unit root test, panel
co-integration test and panel error correction
model (ECM ). The equations below were
used for ECM in the long and short term.
Long-Term model:
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Short-term model:
represents the coefcients in the long
term for the research variables, while
represent sthe coefcients in the short
term, where, i=1,… and N represents
the cross-sectional panel members for
the period t , while is the length of
the lag. ECT is the error correction term
lagged by one period obtained from
the long-term equation. It represents
the adjustment coefcient and must be
signicant, negative and less than one to
prove a long-term relationship. is the
serially uncorrelated disturbance with a
zero mean and constant variance.
RESULTS
Descriptive Statistics
Table 2 displays the descriptive statistics of
FDI in the GCC countries, including central
tendency, dispersion and the normality test.
The table indicates that Bahrain attracted
the highest FDI, while Oman attracted the
least. The results of the Jarque-Bera test
indicates acceptance of the null hypothesis
of normality, except for Bahrain. Therefore,
we can conclude that almost all the times
series for FDI in the GCC countries used
normal distribution.
Table 2
Descriptive statistics of foreign direct investment in Gulf countries
Mean Max. Min. Std. Dev. Skew Kurt Jarque-
Bera Prob.
Bahrain 0.049249 0.157506 0.006058 0.0402 1.5003 5.0085 7.0627 0.0292
Kuwait 0.005754 0.021159 -0.0014 0.0071 0.9511 2.6541 2.0247 0.3633
Oman 0.026167 0.079175 0.001154 0.0231 0.9115 2.9735 1.8007 0.4064
Qatar 0.031225 0.083076 -0.00416 0.0262 0.3332 2.1478 0.6827 0.7108
Arab Saudi 0.030652 0.084964 -0.00326 0.0295 0.5058 1.9579 1.2305 0.5404
United Arab
Emirates 0.032525 0.067672 0.000868 0.0214 0.2702 1.9169 0.7935 0.6724
Unit Root Test
Investigating a long-term relationship
requires integration of all equation variables
in the same order. Table 3 and Table 4
represent the findings of the Augmented
Dickey-Fuller Test and the Phillips-Perron
Test at level and rst difference. The results
indicate rejection of the unit root null
hypothesis at the rst difference for all the
variables, conrming that all the times series
of researched variables were integrated at
the rst order.
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Table 3
Estimation of Panel Unit Root Test (ADF-Fisher)
At level At the rst difference
ADF-Fisher Chi-Square ADF-Fisher Chi-Square
ST 17.0811 32.1710***
FDI 15.7817 43.3986***
GROWTH 20.4261 67.0271***
OPENNESS 4.68334 44.7107***
SIZE 0.99911 23.6452**
CR 1.36557 20.1349*
*** shows signicance at 1% level; ** shows signicance at 5; * shows signicant at 10 %
Table 4
Estimation of Panel Unit Root Test (Phillips-Perron)
At level At the rst difference
PP-Fisher Chi-Square PP-Fisher Chi-Square
ST 17.6241 61.3060***
FDI 15.7796 75.5243***
GROWTH 18.3049 117.274***
OPENNESS 3.33912 53.5031***
SIZE 0.20467 37.3040***
CR 0.94325 31.5916***
*** shows signicance at 1% level; ** shows signicance at 5; * shows signicant at 10 %
Multicollinearity Test
Before proceeding to the co-integration test
and the error correction model, we applied
the tolerance and the Variance Inflation
Factor (VIF) to check for the existence of
multicollinearity in the estimated model.
The results of the tolerance test showed
that all the independent variables had a
low tolerance value, indicating that all
the variables under consideration were
almost the perfect combination of the other
independent variables in the estimated
model. The table shows that the value of
the VIF for all the independent variables
Table 5
Results of Multicollinearity Test
Collinearity Statistics
Tolerance VIF
(Constant)
FDI 0.76 1.316
GROWTH 0.896 1.116
OPENNESS 0.574 1.743
SIZE 0.923 1.083
CR 0.586 1.708
was less than 10, indicating no collinearity
among the independent variables in the
estimated model.
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Co-Integration Test
This paper uses the Johansen co-integration
test to discover existence of a long-term
link between FDI and financial market
development in GCC countries.
The results of the Johansen test based
on a trace test and maximum Eigenvalue
test are listed in Table 6. The results of
the trace test and the maximum Eigen test
indicated rejection at a 5% signicant level;
according to the null hypothesis of Johansen
Fisher Panel Co-integration, there is no co-
integration. Moreover, the ndings of the
Johansen Co-Integration test concludeed
that there was only one co-integration
relationship between the variables. This
indicates existence of a long-term link
between FDI and development financial
market in GCC countries.
Table 6
Estimation of Panel Co-Integration (Johansen Test)
Hypothesised Eigenvalue Trace Max-Eigen
No. of CE(s) Statistic Statistic
None * 0.532473 109.4889** 40.29579**
At most 1 0.437423 69.19308 30.48708
At most 2 0.345237 38.70600 22.44454
At most 3 0.205579 16.26146 12.19754
At most 4 0.070223 4.063927 3.858934
At most 5 0.003860 0.204993 0.204993
*** shows signicance at 1% level; ** shows signicance at 5%
Error Correction Model
This research used the error correction model
to capture the inuence of FDI and control
variables on nancial market development.
The results of two equations, the long-
run equation and short-run equation, are
provided in the table below.
As noted in the table, the long-
term elasticity of financial stock market
development to FDI was positive for the
period studied and statistically signicant
at 1%. The long-term elasticity of nancial
market development to economic growth
and domestic credit to private sector was
positive and significant at 1%. On the
other hand, the long-term elasticity of the
nancial market development to openness
and economic size were negative and
signicant at 1%. The results of the short-
term equation showed that the short-term
elasticity of stock market development
to FDI was positive but not statistically
signicant. Likewise, short-term elasticity
of stock market development to openness,
economic size and domestic credit to private
sector was not statistically significant,
while the short-term elasticity of nancial
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market development to economic growth
was positive and statistically signicant at
1%. The results also showed that the value
of error correction conrmed the long-term
link between the independent variables and
FDI.
Table 7
Estimation of Error Correction Model
Co-Integrating Equation Error Correction
ST(-1) 1.000000 CointEq1 -0.100394**
FDI(-1) 0.242105*** D(ST(-1)) 0.390672***
GROWTH(-1) 0.187355*** D(FDI(-1)) 0.007723
OPENNESS(-1) -0.021180** D(GROWTH(-1)) 0.033737**
SIZE(-1) -0.452683*** D(OPENNESS(-1)) -0.005155
CR(-1) 0.058305*** D(SIZE(-1)) 0.640161
C 8.561646 D(CR(-1)) 0.019104
C -0.085872
R-squared 0.301297
Adj. R-squared 0.192609
F-statistic 2.772145
*** shows signicance at 1% level; ** show ssignicance at 5%
Testing for Serial Correlation and
Heteroscedasticity
Serial correlation (also called autocorrelation)
occurs when the error term for one-time
period is associated with the error for the
next period. If the serial correlation exists in
the model, the estimated coefcients will be
biased and inconsistent. In this research, we
applied the Lagrange multiplier (LM) test on
the residual of error correction model. The
null hypothesis of the test was that there was
no serial correlation in the residuals up to
the specied order. Table 8 shows the results
of the Lagrange multiplier (LM), indicating
acceptance of the null hypothesis for this
test. This means that there was no serial
correlation in the estimated model and the
estimated coefcients were unbiased.
Table 8
Lagrange Multiplier (LM) Test
Lags LM-Stat Prob
1 36.67721 0.4373
2 42.84306 0.2011
3 24.19347 0.9333
4 33.47364 0.5893
5 25.96944 0.8913
6 29.64735 0.7636
7 24.70295 0.9226
8 29.94847 0.7510
9 26.39573 0.8793
10 47.07337 0.1024
11 41.60841 0.2397
12 42.78475 0.2028
Null hypothesis: No serial correlation at lag order h
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Table 9
Heteroskedasticity Test
Joint Test:
Chi-Sq df Prob.
319.7379 294 0.1447
Individual Components:
Dependent R-Squared F(14,38) Prob. Chi-Sq(14) Prob.
res1*res1 0.262044 0.963828 0.5055 13.88833 0.4581
res2*res2 0.120844 0.373090 0.9749 6.404715 0.9552
res3*res3 0.274544 1.027203 0.4488 14.55083 0.4095
res4*res4 0.200281 0.679764 0.7789 10.61490 0.7160
res5*res5 0.474076 2.446699 0.0144 25.12603 0.0333
res6*res6 0.248188 0.896039 0.5695 13.15396 0.5144
res2*res1 0.376677 1.640257 0.1123 19.96389 0.1313
res3*res1 0.202156 0.687739 0.7716 10.71426 0.7083
res3*res2 0.209884 0.721014 0.7403 11.12385 0.6763
res4*res1 0.259082 0.949123 0.5191 13.73134 0.4699
res4*res2 0.116905 0.359321 0.9787 6.195985 0.9613
res4*res3 0.123022 0.380760 0.9725 6.520189 0.9516
res5*res1 0.267095 0.989178 0.4824 14.15606 0.4382
res5*res2 0.202974 0.691232 0.7684 10.75763 0.7050
res5*res3 0.206026 0.704321 0.7561 10.91936 0.6924
res5*res4 0.321246 1.284638 0.2613 17.02604 0.2548
res6*res1 0.291308 1.115707 0.3762 15.43932 0.3488
res6*res2 0.607121 4.194419 0.0002 32.17741 0.0038
res6*res3 0.377430 1.645524 0.1109 20.00381 0.1300
res6*res4 0.290044 1.108890 0.3815 15.37234 0.3532
res6*res5 0.228654 0.804608 0.6590 12.11864 0.5968
Heteroscedasticity occurs when variance
of the error term differs across values of an
independent variable. The table shows the
results of the White heteroscedasticity test
on the residual of error correction model.
The results of the joint test and individual
components in Table 9 indicate acceptance
of the null of the heteroscedasticity test that
says that there is no heteroscedasticity in
the residual of the error correction model.
This means that variance of the error term
in the estimated error correction model does
not differ across the value of independent
variables, indicating that the estimated
coefcients in the error correction model
were unbiased, efcient and consistent.
The Impact of FDI on Stock Market Development
2097
Pertanika J. Soc. Sci. & Hum. 26 (3): 2085 - 2100 (2018)
CONCLUSION
This study empirically examined the impact
of FDI on stock market development in GCC
countries from 2002 to 2015. Using panel
analysis techniques including the panel
unit-root test, Johansen panel co-integration
test and panel error-correction model, we
provided evidence that FDI has statistically
signicant positive effect on stock market
development in the long run, meaning
that FDI has contributed in a substantial
role in developing the stock markets in the
long term in GCC countries. This result is
consistent with the new tendency of GCC
governments to encourage FDI and increase
its role in developing the economy. On the
other hand, this result is also consistent with
many empirical studies such as Shahbaz
et al. (2013) and Adam and Tweneboah
(2009). The results showed that in the short
term, FDI has a positive effect on stock
market development but this impact is not
statistically signicant. These results have
important implications that policymakers
in GCC countries can take note of. The
results indicate that policymakers in these
countries should liberalise the hydrocarbon
sector and integrate it to their economies
to benet from the inows of FDI to this
sector and help in further developing their
stock markets.
This research confirms that both the
economic growth and domestic credit to the
private sector have a positively signicant
effect in the long term on stock market
development but a signicant effect only on
short-term economic growth. These results
suggest that GCC countries must adopt
new policies to strengthen the relationship
between domestic investors and the stock
market by improving the laws, regulations
and supervision of stock markets. Domestic
institutional investors also must be promoted
to develop the stock markets in the GCC
countries.
On the other hand, the research results
show that openness and economic size have
a negative long-term impact on stock market
development. This result is consistent with
the tendency of big economies in the GCC
to support and encourage medium- and
small-sized enterprises (SMEs), resulting in
increase to the GDP. However, investment
in SMEs is not reected in the stock market.
These results have two important policy
implications. The rst is that policymakers
in GCC countries must be selective in
attracting FDI; they must attract FDI to
non-oil sectors to achieve their objectives in
diversifying their economies away from oil
revenues. However, policymakers in GCC
countries must liberalise the hydrocarbon
sector and integrate it to their economies to
benet from the inows of FDI to this sector.
The second is that GCC countries have large
domestic nancial resources that must be
directed to nance medium- and small-sized
enterprises (SMEs).
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