Renewable Energy Consumption, CO2 Emissions
and Economic Growth in Indonesia
Hadi Jauhari, Evada Dewata, Sari Lestari Zainal Ridho, Neneng Miskiyah
Politeknik Negeri Sriwijaya, Palembang, Indonesia
Keywords: Renewable Energy Consumption, Economic Growth, Johansen co-integration, Granger causality
Abstract: This paper aims to examine the causation between renewable energy consumption, CO2 emissions and
economic growth in Indonesia using time series data from 2000 to 2016. Economic growth and renewable
energy consumption are endogenous variables, while CO2 emissions, and world oil prices as variables
exogenous. Johansen co-integration, Granger's causality, and VAR model are used to measure the causalities
effects of renewable energy consumption, CO2 emissions and economic growth. The results show that There
is no one or two-way causality relationship between economic growth and consumption of renewable energy
and CO2 emissions. There is one-way causality between renewable energy consumption and CO2 emissions
but not vice versa, and there is no one or two-way causality between renewable energy consumption and world
oil prices.
1 INTRODUCTION
Indonesia is faced with the energy crisis of fossil
fuel and the national energy supply crisis. The
depletion of petroleum reserves and increasing public
awareness of environmental conservation becoming
opportunities for renewable energy development in
Indonesia. According to Agency for The Assessment
and Application of Technology, in 2014, petroleum
reserves of 3.6 billion barrels, natural gas of 100.3
TCF and coal reserves of 32.27 billion tons.
Assuming if no new reserves are found, based on the
R/P ratio (Reserve/Production) of 2014, the
petroleum will be exhausted in 12 years, natural gas
in 37 years, and coal in 70 years (Agency for The
Assessment and Application of Technology, 2016).
To overcome this problem, the concept of renewable
energy as antithetical to the use of fossil energy
should be encouraged. Indonesian Government has
issued a series of policies in the field of development
of renewable energy sources since the beginning of
2006 that is in Presidential Regulation Number 5 of
2006 on National Energy Policy. Renewable energy
is believed to be more environmentally friendly, safe
and also affordable by the community and quite a
number of renewable energy sources that are feasible
to be developed to meet energy needs, especially in
Indonesia that includes water energy, geothermal,
biofuels, waste/biomass, solar, and wind. Final
energy consumption by type during the year 2000-
2014 is still dominated by fuel (gasoline, solar oil,
diesel oil, kerosene, fuel oil, avtur, and gas).
Furthermore, the consumption of renewable
energy and economic growth have a very close
relationship and a very decisive policy that must be
taken. Al-Mulali et al. (2013) had proved mixed
results regarding the long-term bi-directional
relationship between renewable energy consumption
and GDP growth in both upper-middle income, lower
middle income and high-income countries. So (2014)
stated that one of the factors affecting the failure of
the implementation of energy conservation policy
was the factor of economic growth. On the contrary,
Dogan and Ozgur (2015) stated that renewable energy
consumption could explain the role of renewable
energy in stimulating economic growth. In Indonesia,
many have researched on energy consumption such
as Suryanto (2013) which examined the relationship
between economic growth and electricity
consumption in Indonesia. The result is no long-term
relationship between economic growth and energy
consumption. Susanto and Laksana (2013) also stated
that energy consumption had no effect on economic
growth, even energy supply was not an inhibiting
factor for economic growth.
Another problem that also needs to get serious
attention is about CO2 emissions in Indonesia.
Hwang and Yoo (2014) in his research in Indonesia,
stated the existence of energy conservation and/or
CO2 emissions reduction policies could be initiated
without the consequent destructive economic side
Jauhari, H., Dewata Dr, E., Lestari Zainal Ridho, S. and Miskiyah, N.
Renewable Energy Consumption, CO2 Emissions and Economic Growth in Indonesia.
DOI: 10.5220/0008436500290036
In Proceedings of the 4th Sriwijaya Economics, Accounting, and Business Conference (SEABC 2018), pages 29-36
ISBN: 978-989-758-387-2
Copyright
c
 2019 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved
29

effects. The occurrence of environmental degradation
in the world especially in Indonesia becomes an
important issue, given the increasing number of
protests against environmental damage. The level of
world dependency including Indonesia in fossil fuels
has a serious impact on the environment. Carbon
dioxide (CO2) emissions from fossil fuels are a major
cause of global warming ( Ozturk and Acaravci,
2010). Wang, Fang, and Zhou (2016) showed a two-
way causal relationship between economic growth
and energy consumption, and a direct causal
relationship between energy consumption and CO2
emissions. Apergis and Payne (2011) and Apergis &
Danuletiu (2014) showed a two-way causal
relationship between renewable energy consumption
and short-term and long-term economic growth.
Various empirical studies have been conducted
and show varying results due to differences in study
objects, research periods, and methods of analysis
used by researchers, and for variable consumption of
renewable energy is still rarely used as research
variables in particular. Also, this study has added
world oil price variable as an exogenous variable to
investigate whether the world oil price has a
significant impact on the consumption of renewable
energy or even a direct effect on economic growth.
Based on that statements, researchers want to test the
causality relationship between renewable energy
consumption, CO2 emissions, and economic growth.
As renewable energy policies continue to be
encouraged and there are several energy issues in
Indonesia, the authors are interested in conducting
similar studies with cases that focus on Indonesia.
2 LITERATURE REVIEW
One hypothesis that can explain the relationship
between economic growth and energy consumption is
a growth hypothesis that shows that energy
consumption is an important component in the
process of economic growth either directly or as a
complement of capital and labor as input production
factors. This growth hypothesis is supported if there
is unidirectional causality from energy consumption
to economic growth. This means that the decline in
energy consumption will cause a decline in real Gross
Domestic Product, energy conservation policy will
have a negative impact on economic growth (Belke et
al., 2010; Jumbe, 2004)
Most previous studies employed the same
methodology to investigate the relationship between
Renewable Energy Consumption, CO2 Emissions,
and Economic Growth. Hwang and Yoo (2014)
examined the causality relationship between energy
consumption, CO2 emissions, and economic growth
using annual data for the period 1965-2006. The
results show that there is a bi-directional causal
relationship between energy consumption and CO2
emissions, meaning that an increase in energy
consumption directly affects CO2 emissions and that
CO2 emissions also stimulate further energy
consumption. Also, the results show unidirectional
causality from economic growth to energy
consumption and CO2 emissions without feedback
effects.
Pao & Fu (2013), to explore the causal
relationships between the real Gross Domestic
Product and four types of energy consumption
(NHREC), total renewable energy consumption
(TREC), non-renewable energy consumption
(NREC) and the total primary energy consumption
(TEC). The results of the vector error correction
model reveal a two-way causal relationship between
economic growth and TREC. These findings suggest
that Brazil is an energy-independent economy and
that economic growth is crucial in providing the
necessary resources for sustainable development.
Lin & Moubarak (2014), examined the
relationship between renewable energy consumption
and economic growth in China for the period 1977-
2011. The results show that there is a bi-directional
long-term causality of Granger between renewable
energy consumption and economic growth, that
economic growth in China is favorable for the
development of renewable energy sector which in
turn helps to promote economic growth. Short run
causality between CO2 and renewable energy
consumption.
Alper & Oguz (2016) investigated the causality
between economic growth, renewable energy
consumption, capital, and labor for new EU member
stated for the 1990-2009 period. The results support
that renewable energy consumption has a positive
impact on economic growth for all countries
investigated and the fact that there is a causal
relationship between economic growth to renewable
energy consumption.
The results of the relationship between energy
consumption, CO2 emissions, and economic growth
are slightly different in developed countries and
developing countries. Alshehry and Belloumi (2015),
investigated the dynamic causal relationship between
energy consumption, energy prices and economic
activity in Saudi Arabia with Johansen's multivariate
cointegration approach. The results show that there is
a long-term relationship between energy
consumption, energy prices, CO2 emissions, and
SEABC 2018 - 4th Sriwijaya Economics, Accounting, and Business Conference
30

economic growth. Furthermore, long-term causalities
originate from energy consumption to economic
growth and CO2 emissions, two-way causality
between CO2 emissions and economic growth, and in
the long run, there is a relationship of causality in the
direction of energy prices to economic growth and
CO2 emissions. In the short run, there is a causal
relationship of CO2 emissions to energy consumption
and economic output and from energy prices to CO2
emissions.
Sow and Wolde-Rufael (2010) explored the
causal relationship between CO2 emissions,
renewable and nuclear energy consumption and real
Gross Domestic Product for the US for the period
1960-2007. The findings indicate a direct causal
relationship from the consumption of nuclear energy
to CO2 emissions. That nuclear energy consumption
can help reduce CO2 emissions, but so far, the
consumption of renewable energy has not reached the
level at which it can contribute significantly to
emissions reductions.
Shahbaz, et al. (2013) examined the linkages
between economic growth, energy consumption,
financial development, trade openness, and CO2
emissions during the period 1975Q1-2011Q4 in
Indonesia. The empirical findings show that
economic growth and energy consumption increase
CO2 emissions. The VECM causality analysis has
demonstrated a feedback hypothesis between energy
consumption and CO2 emissions.
Saboori and Mohd (2012) tested the long-term
and short-term causality relationship between
economic growth and carbon dioxide (CO2)
emissions for Malaysia with data from 1980 to 2009.
The empirical results indicate a long-term
relationship between CO2 emissions per capita and
Gross Domestic Product per capita real. Granger
Causality Test based on the Vector Error Correction
Model (VECM) shows no causality between CO2
emissions and economic growth in the short term, and
there is unidirectional causality between economic
growth and long-term CO2 emissions.
Neitzel (2017) examining renewable energy and
economic growth from 22 OECD Countries.
Granger's Causality test results show a two-way
causal relationship between economic growth and
renewable energy.
3 METHODOLOGY
This study applies empirical analysis and focuses
on some variables such as GDP is Gross National
Product Real (at constant 2010 prices), RE is the
consumption of renewable energy (in a million kWh
or GWh), CO2 is carbon dioxide emissions (per
capita metric ton), P is the world oil price. The type
of data of this research is secondary data that is time-
series data in period 2000-2016. Data sources are
obtained from The World Development Indicators
(WDI) compiled by the World Bank.
Researchers used a system of simultaneous
equations to find out various socioeconomic
elasticities. Referring to previous literature such as
Omri (2013) and Taghavee, Aloo & Shirazi (2016),
Menyah & Wolde-Rufael (2010); Apergis and Payne
(2012); Omri (2013), then there are two similarities
in which economic growth and renewable energy
consumption are endogenous variables, while CO2
emissions and world oil prices as predetermined
variables are exogenous. The equation model is as
follows:
Ln GDP
t
= β
01
+ β
11
LnRE
t
+ γ
11
LnCO2
t
+ ε
1t………………
(1)
Ln RE
t
= β
02
+ β
12
LnGDP
t
+ γ
12
LnCO2
t
+
γ
22
LnP
t
+ ε
2t……..
(2)
Where:
GDP is the Real Gross Domestic Product
Representing Economic Growth
RE is the Renewable Energy Consumption
CO2 is the Carbon Dioxide Emissions
P is the World Oil Price
4 DATA ANALYSIS AND
RESULTS
Table 1 that the highest standard deviation of
economic growth (LNGDP) and renewable energy
consumption (LnRE) is the lowest. Jarque-Bera
statistics show that all variables used in the analysis
have a normal log distribution. Summary statistics of
the variables are presented in Table 1.
Table 1: Descriptive Statistical Analysis
LnGDP
LnRE
LnCO
LnP
Mean
14.861
3.706
0.534
4.066
Median
14.548
3.697
0.567
4.101
Maximum
16.333
3.819
0.879
4.605
Minimum
12.894
3.639
0.219
3.398
Std. Dev.
1.053
0.058
0.185
0.415
Skewness
-0.339
0.677
0.220
- 0.300
Kurtosis
2.203
2.179
2.216
1.672
Jarque-Bera
0.776
1.778
0.573
1.504
Observations
17
17
17
17
Renewable Energy Consumption, CO2 Emissions and Economic Growth in Indonesia
31

4.1 Stationary Test
The first stage in testing cointegration is to test to
determine the existence of stationary on the data. The
method used in this stationary test is the Unit Root
Test or Augmented Dickey-Fuller (ADF) Test. The
value of the test results with Augmented Dickey-
Fuller Test (ADF) is shown by the statistical value of
t on the observed variable regression coefficient (X).
If the ADF value is greater than the test value of
MacKinnon's critical values at Level 1%, 5%, or 10%,
then the data is stationary. Table 2 below is the result
of Stationeries test.
Table 2: Stationery Test Results
Variable
s
ADF
test
At level
ADF test
At First
Differenc
e
Information
Lag
Length
LnRE
-3.982
(0.010)
*
-3.6470
(0.017) *
Stationer 1
st
Difference
2
LnCO
2
-0.1.693
(0.415)
-3.962
(0.010) *
Stationer 1
st
Difference
2
LnGDP
-1.371
(0.569)
-4.286
(0.005) *
Stationer 1
st
Difference
2
LnP
-1.782
(0.374)
-4.594
(0.003) *
Stationer 1
st
Difference
2
Note
* shows the level of significance and value of Critical Value
of 1%, 5%, 10%
Source: Author‟s calculation
Of the four test stationeries on four variables of
renewable energy consumption, CO2 emissions,
economic growth and world oil prices where one
variable is the consumption of renewable energy was
already stationary at the level while the other three
variables stationary on the first different. Thus, the
next use VAR analysis (Vector Auto Regression) by
using difference data (VAR in first difference). The
unique order of integration shows that the
cointegration tests can be investigated. But it is
necessary to first find the maximum lag length. The
results for the selection order criteria are illustrated in
Table 2. Table 2 shows that the optimal lag length of
p*=2 is chosen.
4.2 Co-integration Test Using Johansen-
Juselius Technique
In this study, the cointegration test was conducted
through Johansen Cointegration Test with optimal lag
= 2, according to the SC-based determination
previously performed. If the trace statistic value is
greater than the critical value, then the equation is
cointegrated. Co-integration test is used in this study
to examine the short run and long run relationship
between all variables. Based on the results of the
cointegration test with Johansen's Cointegration Test
method for the three equations can be seen in the
following explanation:
Table 3: Cointegration Test
(Series: LnRE LnGDP LnCO2 LnP)
Unrestricted Cointegration Rank Test (Trace)
Hypothesized
No. of CE(s)
Eigenvalu
e
Trace
Statistic
5%
Critical
Value
Prob.**
At most 1 *
0.820
45.362
35.010
0.002
At most 2 *
0.690
19.623
18.397
0.033
At most 3
0.126
2.023
3.841
0.154
Unrestricted Cointegration Rank Test
(Maximum Eigenvalue)
Hypothesized
No. of CE(s)
Eigenvalu
e
Trace
Statistic
5%
Critical
Value
Prob.**
None *
0.981
59.463
30.815
0.000
At most 1 *
0.820
25.739
24.252
0.031
At most 2 *
0.690
17.599
17.147
0.043
At most 3
0.126
2.023
3.841
0.154
Note: * denotes rejection of the hypothesis at the 0.05 level
and **MacKinnon-Haug-Michelis (1999) p-values
Source: Author‟s calculation
Table 3 shows the value of trace statistic> critical
value, as well as the max eigenvalue statistic value>
critical value, this means that there is a long-term
relationship between renewable energy consumption,
CO2 emissions, world oil prices and economic
growth in Indonesia. In any short-term period,
renewable energy consumption, CO2 emissions and
world oil prices and economic growth are likely to
adjust to each other, to achieve long-term
equilibrium. These results are consistent with the
findings of Sebri and Ben-Salha (2014), Apergis and
Payne (2012), Saboori & Mohd (2012), Lin &
Moubarak (2014) and Alshehry & Belloumi (2015),
after confirming the existence of a long run
relationship among the variables, then the Granger
causality test as shown in table 4.
Based on the causality test with Granger Causality
method, the following results are obtained: firstly,
there are no causality one or two directions between
economic growth and renewable energy
consumption, it indicates that whether or not the
movement of economic growth will not encourage the
consumption of renewable energy to rise in
Indonesia. The findings are in line with Shaari and
Ismail (2012) who disclose any policies on energy
SEABC 2018 - 4th Sriwijaya Economics, Accounting, and Business Conference
32

consumption should be re-evaluated to ensure that it
will not affect economic growth. The results of this
study contradict Ikhide and Adjasi (2015) that there
is one-way causality of renewable energy
consumption and real GDP but not vice versa,
contrary to Alper & Oguz (2016) that there is a causal
relationship from economic growth to renewable
energy consumption, and contrary to Pao and Fu
(2013), Lin and Moubarak (2014), Dogan and Ozgur
(2015) that there is a two-way causality between
economic growth and renewable energy
consumption. These findings have implications for
government management in Indonesia that in
implementing renewable energy conservation
policies it must be ensured that it will not endanger
economic growth because the results show that
energy consumption does not affect economic growth
so that the government can implement renewable
energy saving policies. The results of this study do
not support the growth hypothesis that implies the
importance of renewable energy to economic growth
(Belke et al, 2010; Jumbe, 2004; Alper & Oguz,
2016). These findings suggest that the consumption
of renewable energy is not determined by economic
growth in Indonesia and economic growth is not
determined by the extent of renewable energy
consumption.
Table 4: Granger Causality Test
Pairwise Granger Causality Tests
Sample: 2000 2016
Lags: 2
Null Hypothesis:
F-Statistic
Prob.
LnGDP does not Granger Cause
LnRE
0.246
0.785
LnRE does not Granger Cause
LnGDP
0.963
0.414
LnCO2 does not Granger Cause
LnRE
1.160
0.352
LnRE does not Granger Cause
LnCO2
3.669
0.043
LnP does not Granger Cause LnRE
1.310
0.312
LnRE does not Granger Cause LnP
0.357
0.708
LnCO2 does not Granger Cause
LnGDP
1.538
0.261
LnGDP does not Granger Cause
LnCO2
2.799
0.108
LnP does not Granger Cause
LNGDP
7.822
0.009
LnGDP does not Granger Cause
LNP
0.058
0.943
LnP does not Granger Cause
LnCO2
0.629
0.552
LnCO2 does not Granger Cause
LnP
0.202
0.819
Second, there is one-way causality between
renewable energy consumption and CO2 emissions,
indicating that a movement of renewable energy
consumption will reduce CO2 emissions in Indonesia.
So CO2 emissions are influenced by renewable
energy consumption, but not vice versa, CO2
emission reductions do not contribute to renewable
energy consumption. The results of the research have
implications to support the conditions and policies
issued by the government to start switching to
renewable energy that is believed to be more
environmentally friendly, safe and quite a number of
renewable energy sources that are feasible to be
developed to meet energy needs, especially in
Indonesia. The results of this study support Alshehry
& Belloumi (2015), that in the long run there is
unidirectional causality of energy consumption to
CO2 emissions. Even Shahbaz, et al (2013) and
Hwang and Yoo (2014) suggest there is two-way
causality between energy consumption and CO2
emissions, meaning that increased energy
consumption directly affects CO2 emissions and that
CO2 emissions also stimulate further energy
consumption. However, the results of this study
contradict Apergis, Menyah & Wolde (2010) which
indicates that renewable energy consumption does
not contribute to CO2 emission reduction. The same
is expressed by Menyah and Wolde-Rufael (2010)
that renewable energy consumption has not reached
the level at which it can contribute significantly to
emissions reductions.
Third, there is no one or two-way causality
between world oil prices and renewable energy
consumption, indicating that whether or not the world
oil price movement will not encourage renewable
energy consumption up or down in Indonesia. The
results of this study contradict Bekhet and Yusop
(2009) that changes in world oil prices also affect the
total energy consumption in Malaysia. Even though
Indonesia is one of the oil exporting countries but so
far Indonesia has also imported oil. Therefore, if oil
prices increase and an increase in the number of oil
imports will result in the increasing burden of the
Indonesian Government in the provision of fuel
originating from fossil, renewable energy sources that
have not been well utilized related to the limited
process or technology of renewable energy sources,
making renewable energy consumption has not
affected the changes in world oil price movements.
Fourth, there is no one or two-way causality
between CO2 emissions and economic growth,
indicating that CO2 emissions will not encourage
economic growth to rise in Indonesia. By the results
of Saboori and Mohd (2012) that there is no causality
Renewable Energy Consumption, CO2 Emissions and Economic Growth in Indonesia
33

between CO2 emissions and economic growth in the
short term. The results of this study do not support
Shahbaz, et al (2013) Alshehry and Belloumi (2015),
Khanalizadeh and Mastorakis (2014), which revealed
that there is a long-term causality between economic
growth and CO2 emissions, and economic growth
complementary one of the actions of radical energy
conservation.
Fifth, there is one-way causality between world
oil prices and economic growth, indicating that there
is a movement of world oil prices will push economic
growth up in Indonesia. So economic growth is
affected by world oil prices, but not vice versa. The
existence of world oil price movements will have an
impact on price increases in almost all consumer
goods, increase in transportation, increase in basic
electricity rates, and so on. Therefore, it can be said
that the world oil price plays an important role for the
way the wheels of the economy that ultimately affect
the economic growth of one country.
Sixth, there is no one or two-way causality
between world oil prices and CO2 emissions,
indicating that whether or not the world oil price
movement will not drive CO2 emissions up or down
in Indonesia.
4.3 Empirical Model in VAR
Table 5 below shows VAR estimation results.
Table 5: Var Estimation Results
LnRE
LnGDP
LnCO
LnP
LnRE(-1)
0.267
-9.089
-2.698
-6.3670
[ 0.684]
[-2.109]
[-1.864]
[-0.941]
LnRE(-2)
-0.407
4.970
-0.792
-11.147
[-0.773]
[ 0.856]
[-0.406]
[-1.223]
LnGDP(-1)
-0.031
0.445
0.069
-0.803
[-1.000]
[ 1.276]
[ 0.589]
[-1.466]
LnGDP(-2)
-0.001
-0.223
-0.117
-0.078
[-0.091]
[-1.243]
[-1.947]
[-0.276]
LnCO2(-1)
0.046
1.664
0.624
0.613
[ 2.617]
[ 1.996]
[ 2.227]
[ 0.468]
LnCO2(-2)
-0.001
0.744
-0.256
2.168
[-0.014]
[ 0.741]
[-0.759]
[ 1.375]
LnP(-1)
-0.031
-0.739
0.049
0.230
[-1.530]
[-3.249]
[ 0.648]
[ 0.644]
LnP(-2)
-0.058
0.588
-0.156
-1.377
[-1.163]
[ 1.055]
[-0.835]
[-1.573]
C
5.056
26.291
14.429
85.462
[ 1.825]
[ 0.862]
[ 1.409]
[ 1.784]
R-squared
0.922
0.967
0.914
0.648
Adj. R-squared
0.818
0.924
0.799
0.179
F-statistic
8.913
22.353
7.978
1.382
From table 5 on the VAR model, there are only 3
relations between variables that pass the t test on the
estimation result of CO2 emission variables and
renewable energy consumption obtained t
count
=
2.617> t
table
= 2.145 or t
count
value which is greater
than t
table
indicates that variable LnCO2 (- 1) have
positive effect on LnRE in year 1. It can be explained
that the CO2 variable takes time to affect Lnre next
year, meaning it takes 1 year to know the impact of
rising carbon dioxide (CO2) emissions on the
consumption of renewable energy in the next stage.
The result of VAR model also shows the result of
estimation of variable of world oil price (LnP) and
Economic growth (LnGDP) obtained by t
count
=
3.249> t
table
= 2,145 or t
count
which is bigger than t
table
indicates that world oil / LnP (-1) negative to
Economic growth (LnGDP) in year 1. It can be
explained that the world oil price variable (LNP)
takes time to affect economic growth (LnGDP) the
next year, meaning it takes 1 year to know the impact
of the ups and downs of the world oil price (LnP) on
economic growth (LnGDP) in the next stage.
The result of estimation of carbon dioxide
emission (CO2) and carbon dioxide emission CO2 (-
1) is obtained t
count
= 2,227> t
table
= 2,145 or t
count
which is bigger than t
table
indicates that variable of
carbon dioxide emission (CO2) have positive effect
to carbon dioxide emission (CO2) in year 1. Can be
explained that carbon dioxide (CO2) emissions can
affect the increase in carbon dioxide emissions (CO2)
in the next year. This means that if this year there is
an increase in carbon dioxide emissions (CO2)
emissions then the next year can directly increase the
expenditure of carbon dioxide emissions (CO2), the
same as the previous year.
5 CONCLUSIONS
1. There is no one or two-way causality relationship
between economic growth and consumption of
renewable energy and CO2 emissions.
2. There is one-way causality between renewable
energy consumption and CO2 emissions but not
vice versa, and there is no one or two-way
causality between renewable energy consumption
and world oil prices.
6 LIMITATION
The use of more data will minimize errors and the use
of other analytical techniques in testing research
SEABC 2018 - 4th Sriwijaya Economics, Accounting, and Business Conference
34

models can be done such as ECM, ARDL model and
so on.
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B. C. (2013). Examining the bi-directional long run
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