Renewable Energy Consumption-Economic Growth Nexus in Saudi
Arabia: Evidence from a Bootstrap ARDL Bounds Testing Approach
HAKIM BERRADIA
Department of Accounting, College of Business,
Jouf University, Skaka,
SAUDI ARABIA
MEHDI ABID
Department of Finance and Investment,
College of Business, Jouf University, Skaka,
SAUDI ARABIA
ZOUHEYR GHERAIA
Department of Business Management, College of Business,
Jouf University, Skaka,
SAUDI ARABIA
RAJA HAJJI
Faculty of Economics and Management,
Sousse University, Sousse,
TUNISIA
Abstract: The paper investigates the relationship between Saudi economic growth, renewable energy
consumption and trade openness during the 1980-2017 period. By using the Bootstrap Autoregressive
Distributed Lag (BARDL) approach and the Granger causality analysis, the results prove the existence of a
cointegration relationship between the considered variables. In order to test for Granger causality in the
presence of cointegration among the variables, the results indicate that there is a short-run unidirectional
causality running from GDP to trade openness. Thus, a bidirectional causality is detected both between (REC-
TOP) and between (PIB-REC). In contrast, in the long run, there is a one-way causal relationship running from
renewable energy consumption, trade openness to economic growth. These new findings will help
policymakers and government officials better understand the role of renewable energy and economic growth in
Saudi Arabia's development.
Keywords: Trade openness, Renewable energy consumption, Economic growth, Bootstrap ARDL, Saudi
Arabia.
Received: June 29, 2022. Revised: October 12, 2022. Accepted: November 13, 2022. Published: January 18, 2023.
1 Introduction and Literature Review
Today, global warming, which is caused by the
accumulation of greenhouse gases, is one of the
major environmental concerns. Indeed, the energy
sector, based on the consumption of fossil fuels-
which are the main cause of these gases- has been
undergoing structural changes for several years in
terms of energy efficiency and the introduction of
renewable energies. Guaranteeing access for all to
reliable, sustainable, modern and affordable energy
services, The United Nations Development
Program (UNDP, 2015) is one of the seventeen
Sustainable Development Goals endorsed in
September 2015 by the General Assembly United
Nations to succeed the Millennium Development
Goals. For this to be achieved, it is recommended
to double the rate of improvement in energy
efficiency and to promote the energy transition by
2030.
The Kingdom of Saudi Arabia has for some years
started an energy strategy aimed at the deployment
of renewable energies. Indeed, the country has
known for years a growing energy demand, and has
been forced to meet it by importing energy given its
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lack of conventional energy resources. The
Kingdom’s interest in the deployment of renewable
energies is therefore motivated by several factors.
Indeed, the main objective of this new strategy is to
participate in the reduction of greenhouse
emissions and to respect international commitments
in terms of environmental protection, but also to be
able to reduce energy dependence by stimulating
the production of clean energies, to ensure energy
security and to allow widespread access to energy
in rural areas. As for Saudi economic growth, this
is mainly volatile. This volatility is linked to the
concentration of production in a small number of
sectors, namely those of raw materials and
agriculture, which are highly dependent on world
markets and weather vagaries.
Given the need to design efficient energy policies,
the causal link between energy consumption and
economic growth could be a decisive element.
Indeed, in recent years, the debate on the causal
link between the consumption of renewable
energies and economic growth, closely followed by
advances in econometric theory, energy economics
and the economy of the environment, caused a lot
of ink to flow. However, despite all this research,
the state of knowledge still remains undetermined
and controversial. Indeed, the study by [1], [2], in
which the authors examined the causality of the
relationship between energy consumption and
economic growth for the United States of America,
represents the pioneering study which served as a
wealth of empirical research using different
econometric methodologies and variables.
Indeed, four possible hypotheses concerning the
direction of the causal link between the
consumption of renewable energies and economic
growth are possible: (I) The hypothesis of
neutrality or absence of causality: this hypothesis
maintains that there is no causal relationship
between GDP growth and energy consumption.
This implies that energy consumption is not
correlated with GDP growth and therefore policies
of energy scarcity and conservative energy use do
not affect economic growth. (II) The conservation
hypothesis: according to this hypothesis, there is a
unidirectional causality going from GDP growth to
energy consumption. This assumption implies that
GDP growth drives energy consumption. It also
suggests that an economy that operates in such a
relationship is less dependent on energy; therefore,
any conservation policy regarding energy
consumption will have little or no negative effect
on economic growth. (III) The Growth Hypothesis:
this hypothesis implies that there is a unidirectional
causality running from energy consumption to
GDP. This implies that energy consumption drives
GDP growth. The growth hypothesis suggests that
the abundant availability of energy sources at a
reasonable price promotes economic growth. In this
sense, while increasing energy consumption can
contribute to further economic growth, a reduction
in energy consumption can have negative effects on
growth. (IV) The feedback hypothesis: according to
this hypothesis, there is a bidirectional causality
between GDP and energy consumption. Energy use
drives GDP growth, and that same growth drives
energy use.
Findings from the literature on the relationship
between energy consumption and economic growth
therefore support four possible conclusions
regarding the direction of the causal link. Recently,
other studies have also looked at the relationship
between renewable energy consumption and
economic growth. Indeed in [3], the authors
examined the causal link between renewable
energy consumption and economic growth in South
Africa for the period 1990-2014. The authors used
the ARDL model to explore the long-term
relationship between the variables and the vector
error correction model to determine the direction of
causality. The authors also incorporated carbon
dioxide emissions, capital formation, and trade
openness as additional variables to form a
multidimensional framework. The results of the
study validated the existence of a long-run
relationship between the variables. Moreover, a
unidirectional causality running from renewable
energy consumption to economic growth was
confirmed for the long run. On the other hand, the
short-run results suggest unidirectional causality
running from economic growth to renewable
energy consumption. The results then confirm that
all the variables are co-integrated and support the
validity of the long-run growth hypothesis and the
short-run conservation hypothesis.
In [4], the authors investigated the long-run causal
relationship between renewable energy
consumption and economic growth in different
countries. Indeed, the authors classified the various
countries studied into four categories: low-income
countries, lower-middle-income countries, upper-
middle-income countries and high-income
countries. However, study results are mixed across
countries. The results revealed that the long-run
bidirectional relationship between the variables is
more significant in high-income countries. Indeed,
79% of countries were found to have a positive,
long-run, bidirectional relationship between
renewable energy consumption and economic
growth, thus confirming the feedback hypothesis.
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However, 19% of the countries showed no long-run
relationship between the variables, thus confirming
the neutrality hypothesis. Since renewable energy
consumption plays an important role in GDP
growth for most of the countries studied, the
authors then underlined the importance of
investments in the sector, and underlined the role of
the latter in strengthening energy security, thanks to
its contribution to the reduction of imported fossil
fuels. The authors also highlighted the role of
renewable energy in job creation.
In [5], the authors studied the short- and long-run
relationships as well as the direction of Granger
causality between energy consumption from non-
renewable and renewable sources and economic
growth in MENA countries for the period 1980-
2012. They included capital and labor as
explanatory variables. The empirical results support
the existence of a long-run relationship between
economic growth, renewable and non-renewable
energy consumption, labor and capital. Granger's
causality results confirm the feedback hypothesis
between the two types of energy used and
economic growth. This suggests that both energy
sources are vital for economic growth. Meanwhile,
in [6], the authors assessed the impact of renewable
energies on the economic growth of 15 West
African countries over the period 1995-2014. The
results of the study demonstrated that the
consumption of renewable energy slows down
these countries’ economic growth. Indeed, the
authors attribute these results to the fact that
biomass, which is generally impure and highly
polluting, is the most widespread source of energy
in these countries; unlike solar or wind energy,
which are much less used in West Africa. The
study therefore recommends the use of an increased
share of other renewable energy sources such as
solar, wind and geothermal. In [7], the authors
analyzed and compared the short- and long-term
causality between renewable energy consumption
and economic growth in 12 European Union
countries, using a vector error correction model and
the Granger causality test for the 1990 to 2014
period. The results of the study indicate the
presence of a unidirectional causality from
economic growth to renewable energy consumption
in the short run. However, in the long run, the
results of the study support the existence of a
bidirectional relationship between the variables in
question and therefore confirm the feedback
hypothesis between the long-run variables.
In [8], the authors studied the effects of renewable
energy consumption on economic growth from
1991 to 2012 in a sample of 38 countries. The
results of the study indicate that the consumption of
renewable energy has a positive and significant
impact on the economic output of 57% of the
selected countries. The authors believe that these
results are because these countries could not
effectively use renewable energy sources in the
production process, which therefore has almost no
impact on economic production. In [9], the authors
relied on the ARDL approach to examine the causal
link between economic growth, renewable energy
consumption, capital and labor for the new EU
member countries for the period 1990-2009. The
results of the study confirm that the consumption of
renewable energy has positive effects on the
economic growth of all the countries studied.
However, the impact on economic growth is only
statistically significant for Bulgaria, Estonia,
Poland and Slovenia. On the other hand, no causal
link was found and therefore the neutrality
hypothesis was confirmed for Cyprus, Estonia,
Hungary, Poland and Slovenia. For the Czech
Republic, the conservation hypothesis- stating that
there is a unidirectional causality from economic
growth to renewable energy consumption- was
confirmed. Also, the causality from renewable
energy consumption to economic growth was
confirmed for Bulgaria. The growth hypothesis is
therefore confirmed for this country.
In [10], the authors analyzed the causal link
between renewable energy consumption and
economic growth in 17 emerging countries from
1990 to 2016. The results of the study demonstrated
that the neutrality hypothesis is valid for all the
countries studied, with the exception of Poland,
thus the growth hypothesis is confirmed. The
authors estimate that energy saving policies have
no harmful influence on the growth rates of these
16 emerging economies. However, for Poland,
energy saving policies can have adverse effects on
the country's economic performance level.
According to the authors, the absence of causality
does not necessarily imply that renewable energies
do not represent a crucial contribution to economic
growth. This indicates, however, that the level of
investment in the renewable energy sector is not yet
sufficient to drive these economies’ economic
growth rates. This also indicates that there is a
given threshold beyond which renewable energy
consumption will begin to stimulate economic
growth.
This article therefore aims to provide empirical
results on the impact of renewable energy
consumption on economic growth in Saudi Arabia,
highlighting the role of capital and labor in the
deployment of the sector.
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The rest of the paper is structured as follows.
Methodology, data and sources are presented in
section 2. Results and discussion of findings are
presented in section 3. The last section concludes
and suggests some policy implications.
2 Data and Methodology
2.1 Data
The variables used in this study are gross domestic
product per capita (GDP), renewable energy
consumption per capita (REC), trade openness
(TO) and human capital (HC).
These variables are examined for the case of Saudi
Arabia during the period 1980-2017. Table 1
presents the data sources and measurement for this
study.
Table 1. Description and source of the variables
Variables
Description
Sources
GDP per capita (GDPP)
GDP per capita (constant 2015 US$)
[11]
Renewable energy consumption
(REC)
Renewable energy consumption (% of total
final energy consumption)
[11]
Gross fixed capital formation for
capital (HC)
gross fixed capital formation in billions of
constant 2010 U.S. dollars for capital
[11]
Trade Openness
Trade (% of GDP)
[11]
To provide an overall understanding of the chosen
variables, Table 2 below presents the descriptive
statistics and the relative correlation relationship
between the different variables. Table 2 shows that
the GDP per capita is on average 19,381.26 US$
with a maximum value of 21,399.11 US$.
Renewable energy consumption ranges between
20.45 and 77.6% of total final energy consumption.
Trade openness ranges between 56.088% and
96.102% of economic growth. The development of
human capital increases by 21.2% with a maximum
value of 2.667, which means that the growth rate of
human capital development is related to the
consumption of renewable energy.
The analysis of the correlation matrix in this table
indicates that the highest correlation is between
economic growth and renewable energy
consumption. In addition, the latter is positively
correlated with human capital and trade openness,
which means that an increase in renewable energy
consumption leads to promoting economic growth
without deteriorating the environment.
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Table 2. Summary statistics and correlations
GDPP
HC
TOP
REC
Mean
19409.09
1.25E+11
74.637
60.109
Median
19315.07
1.34E+11
71.765
51.712
Maximum
21399.11
2.09E+11
96.102
77.610
Minimum
16696.41
4.75E+10
56.088
20.452
Std. Dev.
1344.880
5.84E+10
11.207
10.063
GDPP
1
HC
0.890
1
TOP
0.912
0.863
1
REC
0.966
0.963
0.925
1
Indeed, the temporal evolutions of the series can
change the results of the unit root test. Therefore, it
is important to conduct several tests that take into
consideration the structural break and the
integration of trend at the level of the series. Figure
1 shows if there are any structural breaks.
Obviously, the graphs show the absence of trend in
all the variables except the log of renewable energy
consumption (LnREC) and the log of human capital
(LnHC) which maintain a constant upward trend
during the period studied. However, there is
evidence that affirms the existence of structural
breaks in the series given their upward and
downward movements. The breaks are associated
with periods of political and economic events in the
country such as global efforts towards efficient
energy use and environmental sustainability. In
particular, the decrease in TOP during the 1980s
could be explained by the oil price shock in 1985
which reduced the growth rate in Saudi Arabia.
However, the increase in capital during the 2000s
could be attributed to steady economic growth
resulting from increased individual consumption of
goods and services.
2.8
3.2
3.6
4.0
4.4
4.8
5.2
5.6
6.0
1980 1985 1990 1995 2000 2005 2010 2015
lnREC
13.6
14.0
14.4
14.8
15.2
15.6
16.0
1980 1985 1990 1995 2000 2005 2010 2015
lnHC
4.0
4.1
4.2
4.3
4.4
4.5
4.6
1980 1985 1990 1995 2000 2005 2010 2015
lnTO
9.8
10.0
10.2
10.4
10.6
10.8
11.0
11.2
11.4
11.6
1980 1985 1990 1995 2000 2005 2010 2015
lnGDP
Fig.1: The series time profiles
2.2 Methodology
Our objective is to highlight the relationship between
renewable energy consumption and sustainable
development over the period 1980-2017 in Saudi Arabia.
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,
1 0 0 0
q
m k k
t i t i j t j j t j r t r
i j j r
t
y y x z
To do this, we use GDP as a well-being indicator and we
start from the following relationship:
ln ln ln
t t t t
GDP REN X
(1)
Where 𝑙𝑛𝐺𝐷𝑃𝑡 and 𝑙𝑛𝑅𝑒𝑛𝑡 denote respectively
economic growth and renewable energy
consumption expressed in natural logarithm. 𝑋𝑡 is a
vector of control variables including human capital
and trade openness ; 𝜀𝑡 denotes the error term and
,
and
are the cointegrating parameter
vectors to be estimated.
The long-run relationship between trade openness,
human capital, renewable energy consumption and
economic growth is then examined by applying the
autoregressive distributed delay (BARDL)
bootstrap test proposed by [12].
The ARDL model is presented as follows:
(2)
i
and
j
are the indicators of the lag period,
1, 2, 3, ..., mi
;
0, 1, 2, ..., kj
;
0, 1, 2, ..., qr
.
t
designs time
1, 2, 3, ..., Tt
. The
t
y
in the equation is the
explanatory variable,
t
x
and
t
z
are the explanatory
variables; and
t
is a dummy variable. The
parameters
i
,
j
, and
j
are the coefficients of
the lag of
t
y
,
t
x
, and
t
z
. The error term is
t
.
Equation (1) is developed in the equation below:
(3)
Where
1
1
1
m
i
i
,
2
0
k
j
j
and
3
0
k
j
j
; other parameters are the function
values of the original parameters. The authors in
[12] present the bootstrap method to ARDL
cointegration tests and propose a cointegration that
requires testing the following three hypotheses:
The
statistic
F
test which is based on all the relevant
error-correction terms:
0 1 2 3
1 1 2 3
:0
:0
statistic
H
FH
The
indep
F
test which is based on all of the
explanatory variable s’ terms:
0 2 3
1 2 3
:0
:0
indep
H
FH
The
dep
t
which is based on the lagged dependent
variable:
01
11
:0
:0
dep
H
tH
After testing the long-term relationships, we
conclude that the short-term causal relationship will
be determined by Granger causality tests if there is
no cointegration relationship between
t
x
,
t
y
and
t
z
. We used the Granger causality test to
t
x
and
t
z
, which should include the delayed difference on
t
x
or
t
z
, and we tested
0
j
or
0
j
in
equation (3). On the other hand, if the dependent
variable and the independent variable are
cointegrated, then a fixed linear combination will
be determined between these variables. In this case,
the short-run relationship test should include the
hysteresis difference of
t
x
or
t
z
and the hysteresis
level of
t
x
or
t
z
, i.e., test
2
and
j
or
3
and
j
.
3 Results and Discussion
Testing the stationarity of the variables is a
necessary step before any cointegration test. To
ensure this, we will apply the Augmented Dickey-
Fuller, [13], and Phillips Perron, [14], tests to study
the properties of the unit root of each series. The
results presented in Table 3 show that the series
TOP and HC are stationary in level while GDP and
REC are stationary in first difference, and
consequently none of them is integrated of order 2.
This confirms our choice of the ARDL model.
1
1 1 2 1 3 1
1
11
,
1 1 1
z
m
t t t t i t i
i
q
kk
j t j j t j r t r t
j j r
y y x z y
x
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(ADF)
Levels
First
differenc
e
Levels
First
differenc
e
TOP
-
5.145*
_
-
10.655
*
_
HC
-
7.235*
*
_
-
12.364
_
GDP
0.128
-2.364**
-3.928
-8.099*
REC
0.556
-2.927**
-3.310
-5.365*
Note: * and ** symbolize statistical significance at the 1% and
5% thresholds, respectively.
In the second step of our analysis, the bootstrap
ARDL bound test for cointegration was performed.
The empirical results of this test are reported in
Table 4. Using the bootstrap ARDL test, the
diagnostic tests indicate that the adopted
specifications are globally satisfactory. The Jarque-
Bera (JB) normality tests do not allow us to reject
the errors normality hypothesis. The Breusch-
Godfrey LM tests make it possible to reject the null
hypothesis of the absence of serial autocorrelation
in the 4 regressions. Thus, according to the tests
studied, we conclude that the 4 dependent variables
are stable over time (Fig. 2 and Fig. 3). The delay
number is selected with Akaike Information
Criteria (AIC).
-15
-10
-5
0
5
10
15
1995 2000 2005 2010 2015
CUSUM 5% Significance
Fig. 2: CUSUM.
-0.4
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1995 2000 2005 2010 2015
CUSUM of Squares 5% Significance
Fig. 3: CUSUM of squares.
Indeed, the results show that their evolutions do not
exceed the confidence interval in red. This stability
is explained by the presence of the different
explanatory variables integrated into this model. In
addition, the columns Fstatistic, tdep, Findep present
values for the significance level of 1%, and 5%,
generated by the ARDL bootstrap procedure. The
bootstrap ARDL presents the joint tdep, Findep, and
Fstatistic tests. The Fstatistic, and tdep tests take into
account the values lagged by one period for all the
independent variables and the dependent variable,
respectively. The Findep test takes into account the
one period lagged value for the independent
variable. This shows the advantage of bootstrap
ARDL over traditional ARDL to study the
cointegration relationship between series. Indeed,
Table 4 shows that the Fstatistic and tdep, Findep tests
can reject the null hypothesis of absence of
cointegration between economic growth, renewable
energy consumption and trade openness. This
indicates that the Fstatistic and tdep, Findep tests show
the presence of three cointegrating vectors. The
value of R2 varies from 0.756 to 0.867, which
shows that all the independent variables
simultaneously explain the dependent variables.
Table 5 presents the Granger causality results. We
show a unidirectional causality running from
renewable energy consumption to real GDP. This
result confirms the growth hypothesis that
renewable energy consumption contributes in the
short run to economic growth in Saudi Arabia. This
implies that, alongside other determinants of
economic growth, any change in renewable energy
consumption will affect economic growth. These
results differ from those of in [15] who the authors
found evidence of a unidirectional causality from
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Table 2. Unit Roots tests
Variabl
e
Augmented
Dickey Fuller
PP
renewable energy consumption to economic growth
in Saudi Arabia.
Table 5 also shows the existence of a unidirectional
causality running from trade openness to real GDP,
which means that trade openness boosts economic
growth in Saudi Arabia. This evidence is consistent
with several studies, such as [16] for South Korea
and Taiwan, [17] for South Korea, Pakistan and
Thailand, [18] for Malaysia and Thailand;, [19] for
Pakistan; and Rahman and [20] for Australia.
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Table 4. Bootstrap ARDL cointegration analysis
Bounds testing approach to cointegration
Diagnostic tests
Cointegration Status
Dependent
variable/independent
variable
Lag length
Break
year
Fstatistic
tdep
Findep
R2
LM(2)
JB
GDP(REN/HC/TOP)
(1,1,2,2)
1990
20.241*
-4.199*
6.411*
0.814
0.364
1.678
Cointegration
REN(GDP//HC/TOP)
(2,0,2,1)
1991
11.259*
-5.622**
2.587*
0.799
2.578
0.821
Cointegration
HC(GDP/REN/TOP)
(1,2,0,2)
2010
2.031
-1.602
-1.034
0.556
2.697
0.134
No-Cointegration
TO(GDP/REN/ HC)
(2,2,1,2,2)
2007
8.147**
-4.765*
3.862**
0.867
0.807
0.813
Cointegration
Note: *, and ** denote significance at 1%, and 5% thresholds, respectively, based on critical values generated from the bootstrap method suggested by [12]. We use
AIC for optimal lag length selection. Fstatistic is F-test for the lagged levels of all variables. Tdepenent is t-test for the lagged dependent variable. Findep is F-test for the
lagged independent variable. The LM and JB refer to Lagrange Multiplier test and Jarque-Bera test.
Table 5. Granger-causality analysis
Variables
ΔlnGDP
ΔlnREC
ΔlnTOP
ECMt-1
ΔlnGDP
_
0.019***
(0.005)
1.421
(0.587)
-0.204
[-4.804]***
ΔlnREC
0.075***
(0.005)
_
0.011**
(0.013)
-0.055
[-1.423]
ΔlnTOP
0.018**
(0.047)
0.012**
(0.024)
_
-0.446
[-1.097]
Notes: p-values are in parentheses. The t-students are the square brackets. Significance thresholds: *** p <0.01,
**p < 0.05, * p <0.10.
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On the other hand, in the short run, the results show
the existence of a unidirectional causality going
from economic growth to trade openness. This
implies that economic growth creates a favorable
environment for business expansion. Similar
empirical results were found for Indonesia, South
Korea, Pakistan and Thailand [21], for Indonesia
and Pakistan, [18] and for Australia, [20]. For the
Granger causality analysis between trade openness
and renewable energy consumption, the results
affirm the existence of a unidirectional causality
going from (REC) to (TOP). This implies that any
strategy to reduce renewable energy consumption
(i.e., a renewable energy conservation policy) will
slow trade openness. This observation corroborates
that of [22] and [23] where a unidirectional
causality from energy consumption to trade
openness was found in the case of Indonesia and
the Philippines.
Nevertheless, Granger's short-run causality tests
(Table 5) indicate that economic growth causes
renewable energy consumption. The conservation
hypothesis is therefore confirmed for Saudi Arabia.
Hence, any strategy to reduce renewable energy
consumption will have no effect on economic
growth. This evidence corroborates that of [24],
who found a unidirectional causality running from
economic growth to renewable energy consumption
for India and Pakistan. This also agrees with the
findings of [19] and [25], who showed the same
result for Pakistan.
Finally, there is a unidirectional causality running
from trade openness to renewable energy
consumption. This means that any fluctuation in
trade openness affects renewable energy
consumption. In addition, any change in trade
openness affects renewable energy consumption.
This result differs from those of [26] and [27] who
found no causality between exports and renewable
energy consumption for Malaysia. However, this is
in line with [23], who confirmed a unidirectional
causality from trade openness to renewable energy
consumption for the case of Pakistan, and with [28]
who found no causality between exports and
renewable energy consumption for Thailand.
4 Conclusion and Policy Implications
This study investigates the relationship between
economic growth, renewable energy consumption,
trade and capital from 1980 to 2017 in Saudi
Arabia. We incorporated natural resources, capital,
and labor as additional determinants of domestic
production. Using the bootstrap ARDL test
developed by [12], the empirical results prove the
existence of cointegration relationships between
economic growth, renewable energy consumption
and trade when these variables are taken as
dependent variables.
The Granger causality analysis shows a
bidirectional causal relationship between economic
growth and trade openness in Saudi Arabia. This
relationship supports both the trade openness-
induced growth hypothesis and the growth-induced
trade openness hypothesis. These results confirm
the idea that trade openness was considered one of
the primary factors of economic expansion in Saudi
Arabia, while economic expansion favored trade
openness. In other words, poorly-designed national
economic policies that slow or impede economic
growth will also reduce trade openness.
In the short run, the results show a bidirectional
causal relationship between trade openness and
renewable energy consumption, where any
increases in renewable energy consumption will
lead to increased trade openness, while promotion
of commercial opening also increases the
consumption of renewable energy. Finally, the
Granger causality tests prove the existence of a
bidirectional causal relationship between economic
growth and renewable energy consumption. This
implies that increased renewable energy
consumption stimulates economic growth and vice
versa. This result highlights the Saudi population’s
awareness of the need to protect the environment,
which urges them to use renewable energies. Any
energy conservation policy aimed at environmental
goals will generally promote the use of renewable
energy and hence enhance economic growth.
Another implication is that well-designed national
economic policies that promote economic growth
will also increase renewable energy consumption.
Thus, the empirical results affirm a unidirectional
causality in the sense of Granger going from
economic growth to trade openness. This implies
that economic growth creates a favorable
environment for business expansion.
These findings provide new insights for policy
makers as they seek to design economic, trade and
energy policies to support long-run economic
growth to improve environmental quality. In light
of these results, it is clear that the transition to
renewable energy requires an ambitious political
will. The existence of causality running from
renewable energy consumption to economic growth
and trade openness means that the former is an
important factor for the latter two. On this basis,
policy makers should develop and strengthen
strategies to support renewable energy industries
and technologies. The unidirectional relationship
WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT
DOI: 10.37394/232015.2023.19.4
Hakim Berradia, Mehdi Abid,
Zouheyr Gheraia, Raja Hajji
E-ISSN: 2224-3496
42
Volume 19, 2023
from economic growth and trade openness to
renewable energy consumption indicates the
importance of these factors in the development of
renewable energy. In other words, economic
growth brings additional technologies and
capacities that can support the development of
renewable energy sources and "clean technologies",
while trade openness plays a major role in
facilitating the diffusion of environmentally-
friendly technologies. Of course, this would require
Saudi Arabia’s willingness to remove barriers to
the importation of modern technologies and
environmental services.
Our research has led us to identify the following
policy implications. First, we recommend that the
Saudi government continue to provide incentives
through tax deductions, subsidies, etc.
Consequently, renewable energy sources become
more attractive for businesses, since their economic
impact on both the economy and government
policy regarding alternative energy sources cannot
be ignored over the long term. Secondly, our
findings prove the importance of renewable energy.
Indeed, they ease the pressure on policy-makers to
improve the environment as well as increase Saudi
Arabia’s economic growth. Thirdly, we therefore
recommend that policymakers continue to promote
regional and international trade openness, not only
because it contributes to greater economic
development, as evidenced by the results, but also
because it plays a vital role in the increase in
renewable energy consumption on the long-run.
This in turn contributes to reducing CO2 emissions
and therefore improving the quality of the
environment.
Acknowledgments:
The authors extend their appreciation to the
Deanship of Scientific Research at Jouf University
for funding this work through research grant No
(DSR-2020-02-3636).
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WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT
DOI: 10.37394/232015.2023.19.4
Hakim Berradia, Mehdi Abid,
Zouheyr Gheraia, Raja Hajji
E-ISSN: 2224-3496
44
Volume 19, 2023
Contribution of Individual Authors to the
Creation of a Scientific Article (Ghostwriting
Policy)
The authors equally contributed in the present
research, at all stages from the formulation of the
problem to the final findings and solution.
Sources of Funding for Research Presented in a
Scientific Article or Scientific Article Itself
Conflict of Interest
The authors have no conflicts of interest to declare
that are relevant to the content of this article.
Creative Commons Attribution License 4.0
(Attribution 4.0 International, CC BY 4.0)
This article is published under the terms of the
Creative Commons Attribution License 4.0
https://creativecommons.org/licenses/by/4.0/deed.en
_US
The authors extend their appreciation to the
Deanship of Scientific Research at Jouf University
for funding this work through research grant No
(DSR-2020-02-3636).
