Dynamic relationship between energy and economic growth: evidence from D8 countries.
Razzaqi, Sarwat ; Bilquees, Faiz ; Sherbaz, Saadia 等
Energy sector has a vital influence on an economy, on both demand
and supply sides. Therefore, energy production and consumption bear
great importance for the developing world. The oil embargo of
1970's and its impact on major macroeconomic variables throughout
the world attracted many economists to examine the relationship between
energy and economic prosperity. The researchers have been unable to
establish a definitive direction of causality between the two variables.
The purpose of this study is to empirically investigate the dynamic
relationship between energy use and economic growth in the D8 countries.
The evidence gathered through application of VAR Granger Causality,
Johansen Cointegration and VECM proves existence of short-run and
long-run correlation between energy use and economic development in all
countries. The results supported either uni-directional or
bi-directional causality in the D8 countries except for Indonesia in
short-run where non-causality was established between the two variables.
JEL classifications: C22; Q43.
Keywords: Energy Use, Economic Growth, D8, VAR Granger Causality,
Cointegration, VECM.
INTRODUCTION
Energy is vital to economic growth and it was best demonstrated
during the 1973-1974 oil embargo. When oil-producing nations of the
Middle East restricted the output, prices increased fourfold in a span
of a few months, 'resulting in serious disruption in the
industrialised countries as well as the supplies of raw material from
the developing countries.
The energy crisis of the seventies attracted significant
investigation into the relationship between energy consumption and
economic growth. Overtime, numerous studies conducted to examine this
relationship have produced conflicting results: some studies suggest
that energy use is highly positively correlated with GDP growth [for
example; Chebbi and Boujelbene (2008), Jumbe (2004), Siddiqui (2004)
etc.], others support a negative relationship [for example; Okonkwo and
Gbadebo (2009), Noor and Siddiqi (2010) etc.]. Similarly, while some
studies report non-causality of the relationship [for example; Sarkar,
et al. (2010), Yusma and Wahilah (2010) etc.], others have reported
bi-directional causality [for example; Pradhan (2010), Loganathan, et
al., (2010), Omotor (2008) etc.]. Thus, the empirical evidence is
varying and conflicting about direction of causality.
D8, also known as Developing-8, is an arrangement for development
of cooperation among the following Muslim countries: Bangladesh, Egypt,
Indonesia, Iran, Malaysia, Nigeria, Pakistan and Turkey. The idea of
cooperation among major Muslim developing countries was raised during a
seminar on "Cooperation in Development" held in Istanbul in
October 1996. It was after a series of preparatory meetings that D-8 was
set up officially and began its activities with the 'Istanbul
Declaration' issued at the end of 'The Summit of Heads of
State and Government' held in Istanbul on June 15, 1997.
The energy sector is likely to play a vital role in the development
of the D8 countries. The complexity of relationship among the variables
of energy use and economic activity requires a re-examination of
long-term and short-term linkages between energy consumption and real
output in the D8 because if the causality in these countries runs from
energy to GDP, the energy constraints can have serious implications for
the pace of development in these economies. The main objective of this
study is to investigate the dynamic correlation between energy
consumption and economic growth in the D8 countries.
I. ENERGY AND ECONOMIC GROWTH: REVIEW OF LITERATURE
This section reviews some of the previous studies on the
relationship between energy and economic growth along with the role of
energy sector in economic growth as discussed in the mainstream economic
literature.
1.1. Theoretical Background
Although business and financial economists pay significant
attention to the impact of oil and other energy prices on economic
activity, the conventional theory of economic growth pays little or no
attention to the role of energy or any other natural resources in
facilitating or promoting economic growth [Stem (2003)]. A fully worked
out model of the growth process in which energy is explicitly recognised
as a determinant does not seem to exist in economic literature but
extensive empirical work has examined the role of energy in the growth
process.
Energy is an essential input for growth and development and energy
use is also expected to be a limiting factor to economic growth, as
other factors of production cannot work properly without energy. It can
also be argued that the impact of energy use on growth depends on the
structure of the economy, energy intensity and the stage of economic
growth of the country concerned. Some service activities may not require
the direct processing of materials. However, this can only be true at
the micro level and at the macro-level all economic processes require
the direct and indirect use of materials, in either the maintenance of
labour or the production of capital.
Although the classical economists did not explicitly recognise
energy per se as a factor of production, they understood clearly the
limits which land (nature) imposes on economic activities, especially in
agriculture. When classical economists speak of the "fertility of
nature" (Adam Smith), "the productive and indestructible
powers of the soil" (David Ricardo), "the natural and inherent
powers of the soil" (John McCulloch), or speak of the earth as
"a wondrous chemical workshop wherein many materials and elements
are mixed together and worked on (Jean-Baptiste Say)," their
language conveys a clear understanding of the contributions of nature to
the economy [Alam (2006)]. Hall, et al. (1986) argued that energy is the
primary factor of production, and labour and capital are intermediate
factors of production. Primary is used in the sense of 'cannot be
produced or recycled from any other factor' [Hall, et al. (1986)].
As discussed by Stem (2003), the neoclassical economists do not
even implicitly include energy into their macro-economic framework. The
argument is based on the rejection of land as a factor of production
since the neoclassicals subsume land under capital. Energy from
non-human sources e.g., coal, oil, electricity, food or fertiliser etc,
enters the economy only as an intermediate input. The basic model of
economic growth, the Nobel-prize winning work by Solow (1956), does not
include resources at all in the basic framework. Also, the extensions of
this model, that include energy in any form, are only applied in the
context of debates about environmental sustainability, not in standard
macro-economic functions [Stem (2003)].
Nicholas Georgescu-Roegen (1972, 1976) was one of the first to
comment on the absence of energy in economic thinking of the Marxists
and neoclassical economists as they take resources and energy flows for
granted and ignore the economy's output of wastes. Roegen (1976)
argued that standard economics does not recognise that "terrestrial
resources of energy and materials are irrevocably used up and the
harmful effects of pollution on the environment accumulate."
Overall there is a strong link between rising energy use and
economic growth. However, the linkage between these two can be mitigated
by a number of factors including shifting to higher quality fuels and
technological change aimed at general increases in economic
productivity. As explained above there is an inbuilt bias in mainstream
production and growth theory to downplay the rote of energy resources in
the economy. Although there is nothing inherent in economics that
restricts this potential role in the economy but there seems to be no
particular theoretical work in conventional economic literature today
that explicitly recognises this critical role.
II. INVESTIGATING ENERGY USE AND GROWTH LINKAGE: METHODOLOGY
Introduction
Following Soytas, et al. this analysis consisted of three key
steps. The first step was checking for the stationarity of the series,
the second step was testing for cointegration, and the third step was
testing for causality in long and short run by developing a VECM and VAR
Granger Causality respectively.
Rest of the chapter is organised as; Section 1 discusses the test
of stationarity; lag length selection and cointegration test are
explained in Section 2; Vector Error Correction Modeling (VECM) is
established in Section 3; VAR Granger Causality/Block Exogeneity Wald
Tests are discussed in Section 4 and; Section 5 provides the data
description.
II-1. Test of Stationarity
To check for stationarity of the series, the Augmented
Dickey-Fuller (1979) (ADF) unit root test was utilised. Stock and Watson
(1989) and Nelson and Plosser (1982) are among the economists who argue
that the causality tests are very sensitive to the stationarity of the
series and many macroeconomic series are non stationary [Soytas (2001)].
Therefore, before taking any further step in our analyses, it was
necessary to check for the stationarity of Natural Log of Energy Use
(Lneu) and Natural Log of Real GDP (Lngdpc) series. The ADF test was
conducted from the Ordinary Least Squares estimation of the following
equation:
[DELTA][Y.sub.t-1] = [[alpha].sub.0] + [beta]T + ([rho] -
1)[Y.sub.t-1] + [N.summation over (i=1)]
[[alpha].sub.i][DELTA][Y.sub.t-1] + [[epsilon].sub.t] (1)
where Y is the variable of interest, [[alpha].sub.0] is the
intercept, T is a linear time trend, [DELTA] is the first difference
operator, and [[epsilon].sub.t], is the error term with zero mean and
constant variance. The test regression for ADF includes lagged
differences of the dependent variable (Y) as independent variables to
account for higher-order serial correlation. The hypothesis ([H.sub.0]:
[rho]-1=0) that Y is a non-stationary is rejected if the test fails to
reject the alternative hypothesis ([H.sub.1]: ([rho]-1) < 0). If the
ADF test fails to reject the null hypothesis in levels but rejects it in
first differences, then the series contains one unit root and is of
integrated order one I (1). MacKinnon (1991) finite sample critical
values were used to determine the statistical significances.
II-2. Lag Length Selection and Cointegration Test
Given the importance of selecting the appropriate lag length,
selection was based on The Akaike Information Criteria (AIC) and Schwarz
Criteria (SC). Johansen Cointegration test was used to determine the
number of cointegrating vectors. As explained by Rathinam and Raja
(2008), Johansen's methodology takes its starting point in the VAR
of order k given by:
[Z.sub.t] = [A.sub.0][D.sub.t] + [A.sub.1][Z.sub.t+1] +
[A.sub.2][Z.sub.t-2] + ... + [A.sub.k][Z.sub.t-k] + [[member of].sub.t]
(2)
Where [A.sub.i]'s are (n x n) matrix of parameters, Z is an (n
x 1) vector containing all n variables in the system (Lngdpc and Lneu),
D is a vector of all deterministic terms (intercept, trend, etc.), and
[[member of].sub.t], is an (n x 1) vector of white noise error terms.
This unrestricted base VAR could be represented as a VECM as
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII]. (3)
[[GAMMA].sub.j][DELTA][Z.sub.t-j] is the first differenced
component in the VAR system, where [[GAMMA].sub.j] is an (n x n) matrix
of short term coefficients associated with the lagged values of
variables in the system [Z.sub.t]. [PI][Z.sub.t-1] is the
error-correction component, where [PI] is an (n x n) matrix of
cointegrating parameters which characterize the long run relationship
among the variables and long run adjustment coefficients in the VEC
system. Thus [PI] consists of (n x r) dimension matrices [alpha] and
[beta], where [PI] = [alpha][beta]'.
The rank of [PI] matrix indicates the number of possible
cointegrating relationship i.e. long run equilibrium relationship among
the variables in the system. The rank of [PI] can be determined by
[[lambda].sub.trace] or [[lambda].sub.max] test statistics as proposed
by Johansen (1988). If the [PI] matrix has full rank then all the
variables in the system are stationary and the error correction
mechanism does not exists. If the rank of [PI] matrix is zero, the
short-term dynamics depends only on lagged changes in all variables. The
existence of cointegration between the two variables suggests the
presence of causality between the variables in at least one direction
[Engle and Granger (1987)].
II-3. VEC Modeling
As Engel and Granger (1987) suggest, if cointegration exists
between two variables in the long run, then, there must be either
unidirectional or bi-directional causality between these variables, thus
Vector Error Correction Model (VECM) can be applied to study the
direction of long-run relationship between the selected variables as
cointegration test does not specify the direction of causality. The VECM
for this study can take the following form:
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (4)
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (5)
where Lngdpc is the natural log of Real Gross Domestic Product and
Lneu is the natural log of energy consumption. [E.sub.t-1] and
[C.sub.t-1] are the error correction terms, [DELTA] is the first
difference and u's are serially uncorrelated random error terms
with mean zero. (M and N), and (K and L) are the optimal lag lengths.
[C.sub.t-1] is the lagged value of the residuals from the cointegration
regression of Lngdpc on Lneu, and [E.sub.t-1] is the lagged value of the
residuals from the cointegration regression of Lneu on Lngdpc. Equation
(4) can be used to test the causality running from energy use to
economic growth while to test the causation from economic growth to
energy use, Equation (5) can be used.
Within the VECM formulation of above equations, energy use does not
cause economic growth if all [beta]s and [alpha] is zero in Equation 4,
and economic prosperity, measured by GDP, does not cause energy use if
all [delta]s and [lambda] is zero in Equation 5. VECM approach allows us
to determine the direction of causality in long run. Significant error
correction terms ([alpha] and [lambda]) implies long-run causal
relationship. Error correction term contains the long-run information
since it is derived from the long-run cointegrating relationship. It
should be noted that the coefficient of error correction term is a
short-run adjustment coefficient correcting long run disequilibrium in
dependent variables in each short period. Thus the stability of long-run
equilibrium can also be judged from the sign and significance of the
error correction term as if it is negatively significant, it shows
convergence towards the equilibrium i.e., a stable long-run equilibrium.
II-4. VAR Granger Causality/Block Exogeneity Wald Tests
The VAR Granger Causality tests were used to determine the short
run causal relationship between the two focus variables; energy use and
real GDP. The VAR Granger Causality test also provides the direction of
causality in short run. In a n-variable VAR of order p, Block-Exogeneity
test looks at whether the lags of any variable Granger-cause any other
variable in the system. Sargent (1976) has proposed a simple procedure
called the direct Granger procedure for testing causality. Consider two
stationary variables Y and X for which the regression equations are
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII]
The Wald test is used to test whether all the lagged values of X in
the Y equation are simultaneously equal to zero. X Granger causes Y if
[summation][beta] [not equal to] 0 and, if both [summation][delta] [not
equal to] 0 and [summation][beta] [not equal to] 0, then there exists a
bidirectional causality between Y and X.
II-5. Data Description
The annual data for the-D8 countries; Bangladesh, Egypt, Indonesia,
Iran, Malaysia, Nigeria, Pakistan, and Turkey from the year 1980 to 2007
is used. The data for energy consumption, measured by energy use (kg of
oil equivalent per-capita) and GDP in million US dollars at year 2000
constant prices is collected from 'The World Development Indicators
(2010)' by the World Bank. The data for total population is also
gathered to convert the energy use (kg of oil equivalent per-capita) to
total energy use (kg of oil equivalent).
III. INVESTIGATING ENERGY USE AND GROWTH LINKAGE: RESULTS AND
DISCUSSION
In this section, the results of the estimation conducted on the
data of all the D8 countries are discussed. The estimation was done
using the statistical package of Eviews 5 and the obtained results are
presented below.
III-1. Results of Stationary Test
The results of ADF test of stationarity are summarised in Table 2.
For all countries, evidence was found in favour of the null hypothesis
that both series contain unit roots at level, as t-statistics for all
variables are less than the critical values at, respectively, 1 percent,
5 percent and 10 percent levels from ADF test. However, we reject the
null hypothesis for the first differences of all series i.e., the
results of the first differenced variables show that the ADF test
statistics for all the series are greater than the critical values at 5
percent and 10 percent levels. Therefore, it is concluded that both
series are integrated of the order 1 i.e., I (1) for all the countries.
Thus cointegration tests can be applied for all countries.
III-2. Lag Length Selection
The optimal lag length selection was based on the results of two
criteria Akaike Information Criteria (AIC) and Schwarz Criteria (SC).
The suggested optimal lag lengths by both the AIC and SC are
presented in the Table 3. Although for most of the countries, the
selected number of lags to be included was same by both criteria like in
the case of Indonesia, Iran, Malaysia, Nigeria and Pakistan, but under
circumstances where there was a discrepancy between the appropriate lag
order, for example in case of Bangladesh, Egypt and Turkey, the selected
lag order for the respective country was chosen on the basis of the
results of SC as it is more accurate and thus is preferred by most of
the economists including Geweke and Messe (1981).
III-3. Results of Short-run Causality between Energy Use and GDP
The results of investigation of short-run relationship between
energy use and GDP by application of VAR Granger Causality/Block
Exogeneity Wald Tests are presented in Table 4.
From the results of VAR granger causality test above, it is
concluded that there is a uni-directional short-run causality from real
GDP to energy use in Bangladesh, Egypt, Malaysia, Pakistan and Turkey,
as the null hypothesis of non-causality is rejected at 5 percent or 10
percent level of significance. However, this is not the case for test of
causality from energy use to real GDP as the null hypothesis cannot be
rejected for these countries. Thus in the short run higher rate of
economic prosperity encourages energy use in Bangladesh, Egypt,
Malaysia, Pakistan and Turkey but higher rates of energy use do not have
an effect on the economic development in the short-run. For the energy
exporters Iran and Nigeria, the opposite direction of causality can be
observed as energy use significantly causes the economic growth even in
the short-run as the null hypothesis of non-causality is rejected at 5
percent or 10 percent level of significance in both states without a
feedback affect. In Indonesia, however, the neutrality hypothesis could
not be rejected in the short-run i.e. neither energy use nor the
economic growth caused each other in the short-run in Indonesia as the
null hypothesis of non-causality could not be rejected at 5 percent
level of significance.
III-4. Results of Long-run Cointegration between Energy Use and GDP
The results of Johansen Cointegration test are summed up in the
Table 5. The Johansen cointegration technique has been used because of
its ability to capture the properties of time series, to produce
estimates of all possible cointegrating vectors and to provide test
statistics for the number of cointegrating vectors.
The estimated cointegration results between energy use and real GDP
for all countries indicate that the two series have at least one
cointegrating relationship in all countries. This is because the null
hypothesis of [H.sub.0]: r = 0 against r [less than or equal to] 1 is
rejected at 5 percent or 10 percent level by either one or both of the
criteria. One cointegrating equation means that there exists either a
uni-directional or bi-directional long run relationship between energy
use and GDP in these countries, and any change in one or both variables
would most likely have implications on each other in the long term.
These results suggest that the annual time series data from 1980 to 2007
appears to support the proposition that in the D8 countries there is a
dynamic relationship between energy use and GDP.
III-5. Results of Long-run Causality between Energy Use and GDP
The VECM results for long-run causality and stability of the long
run equilibrium relationship between energy use and economic prosperity
are displayed in the Table 6.
III-5-i. Bangladesh
For Bangladesh in the long run, there exists a hi-directional
causality between the focus variables, as indicated by the significant
error correction terms. The results also indicate that there is a
positive relationship between energy and economic growth and one time
relative increase in energy use will lead to 0.55 times relative
increase in real GDP, as is indicated by the high level of significance
and positive sign of the coefficient of Lneu.
Both the error correction terms for Bangladesh are highly
significant. The error correction terms are positive which means that
any exogenous shock in one of the variables will lead to divergence from
equilibrium. An exogenous shock in the energy use will lead to 11
percent movement away from the original equilibrium every year while in
case of a shock in the GDP, there will be 5 percent divergence from
equilibrium per year.
Thus the equilibrium is unstable in case of Bangladesh. Thus it can
be concluded that in the net energy importer Bangladesh, energy use
drives the economic development and the economic progress also has an
influence on the energy use in the long-run.
III-5-ii. Egypt
The VECM results, reported in table, provide evidence of weak
long-run relationship between the two variables for Egypt as the
coefficient of energy use is not significant. The weak relationship can
be attributed to the fact that Egypt's main exports consist of
non-petroleum products such as ready-made clothes, cotton textiles,
medical and petrochemical products, citrus fruits, rice and dried onion,
and more recently cement, steel, and ceramics along with natural gas.
Egypt's main imports consist of pharmaceuticals and non-petroleum
products such as wheat, maize, cars and car spare parts (Wikipedia)
The adjustment coefficient for GDP is significantly negative as it
should be, suggesting that the speed of adjustment of energy use towards
the equilibrium in the long run in case of an exogenous shock is very
high at 60 percent per year. On the other hand the error correction term
for energy use, although negative, is insignificant indicating that all
the adjustment towards the equilibrium is being done by the GDP. Thus it
can be concluded that there is uni-directional causality between the
focus variables in the short as well as long run where causality runs
from GDP to energy consumption in the short-run as well as the long run.
The long run findings are consistent with the findings of Costantini and
Martini (2010) who also found the direction of causality running from
GDP to energy use in the long run for their panel of OECD and non-OECD
countries.
III-5-iii. Indonesia
In the long run in Indonesia, causality runs from the real GDP to
energy use with a feedback affect and one time relative increase in
energy use will lead to 1.15 times relative increase in the GDP. The
error correction terms for GDP and energy use in Indonesia are highly
significant. Thus feedback affect in the long run is found as the error
correction terms (or adjustment coefficients) are significant.
The adjustment coefficient for energy use is positive and the speed
of divergence from equilibrium as a result of an exogenous shock is of
25 percent a year. Also the adjustment coefficient for energy use is
positive and significant. An external shock in GDP in Indonesia will
lead to divergence of 13 percent per year so it can be concluded that in
Indonesia there is bi-directional long run causality between economic
growth and energy use but the equilibrium is unstable. Therefore, in
Indonesia the energy use causes real GDP in the long run with a feedback
affect. The findings for Indonesia are similar to the findings of
Asafu-Adjaye (2000).
III-5-iv. Iran
The results provide a positive link between energy use and economic
growth in case of Iran i-e one time relative increase in energy use will
lead to a relative increase of 0.71 times in GDP. Iran is the second
largest oil and natural gas producer in the world. High oil prices in
recent years have enabled Iran to increase its export revenue and amass
$100 billion in foreign exchange reserves through its exports. Thus an
increase in energy use in the economy would lead to higher exports
revenues (Wikipedia).
The adjustment coefficients are negative in both cases, suggesting
that the speed of adjustment of energy use, in case of an exogenous
shock, towards the equilibrium in the long run is 30 percent every year.
Thus the equilibrium is stable. The error correction term for GDP is
also negative indicating that in case of disequilibrium due to an
exogenous shock, GDP will lead to convergence towards equilibrium at the
rate of 15 percent every year. Thus there is uni-directional causality
between the focus variables where energy use leads to economic growth in
the short- run but bi-directional causality exists in the long run in
Iran.
III-5-v. Malaysia
The VECM results for Malaysia provide evidence in favour of a
significant bidirectional causality between economic development and
energy consumption. The adjustment coefficients are highly significant
advocating the long run bi-directional causality from energy use to real
GDP in Malaysia. Moreover the relationship between the two is positive
i-e onetime relative increase in energy use will bring relative increase
0.55 times in real GDP. The error correction term for a shock in GDP is
highly significant and negative, therefore suggesting there is a
long-run causal correlation from economic growth to energy use and the
per year speed of adjustment towards equilibrium is slow at 2 percent in
case of a disequilibrium caused by an external shock in GDP. The
adjustment coefficient for energy use is also negatively significant.
Thus the long run equilibrium in Malaysia is stable and any
disequilibrium due to an external shock will be corrected at the speed
of 2 percent adjustment every year. Thus it can be concluded that energy
consumption is influenced by economic growth in Malaysia with a feedback
affect. These results are similar to inferences drawn by Loganathan, et
al. (2010).
III-5-vi. Nigeria
In the long run, as suggested by the VECM results, there is
uni-directional causality between the energy use and real GDP where
there is a positive correlation between energy use and GDP and one time
relative increase in energy use leads to a relative increase of 1.69
times in economic development.
The adjustment coefficient for energy use is highly significant,
therefore suggesting there is a long run causal correlation from energy
use to economic growth with no feedback and the per year speed of
divergence from equilibrium is 9 percent in case of a shock in energy
use because the sign of the error correction term for energy use is
positive. Thus the equilibrium is an unstable one for Nigeria as it
shows divergence from equilibrium in the long-run. The adjustment
coefficient of GDP, although insignificant, also has a positive sign
indicating to an insignificant causality from GDP to energy use in long
run.
This can be attributed to the heavy dependence on oil as a source
of revenue exposes the vulnerability of the Nigerian economy to global
energy dynamics. Thus it can be concluded that energy use influences
economic growth in Nigeria where increased energy use boosts GDP but the
equilibrium in the long run is unstable. Adeniran (2009) also
established long-run causality from energy to economic growth in
Nigeria.
III-5-vii. Pakistan
In the long-run, as suggested by the VECM results, there is
bi-directional causality between the energy use and real GDP where there
is a positive correlation between energy use and GDP and one time
relative increase in energy use leads to a relative increase of 1.11
times in economic development as indicated by the positive sign of
energy use coefficient.
The adjustment coefficients are highly significant for energy use
and GDP, therefore suggesting there is a long-run causal correlation
from economic growth to energy use with feedback. The per year speed of
divergence of adjustment coefficient of real GDP from equilibrium is 27
percent in case of an external shock because the sign of the error
correction term of GDP is positive. Thus the equilibrium is an unstable
one for Pakistan as it shows divergence from equilibrium in the
long-run. The adjustment coefficient of energy use is also positively
significant indicating to an unstable relationship between the two in
long-run. Any external shock in the energy use will disturb the
equilibrium and will lead to 45 percent divergence every year.
This can be attributed to the fact Pakistan is net importer of oil
and virtually imports most of its fuel from other countries. The heavy
dependence on oil imports to keep the production afloat exposes the
vulnerability of the Pakistani economy to global energy dynamics. Thus
it can be concluded that energy consumption and economic growth are
influenced by each other in Pakistan where increased energy use boosts
GDP but the equilibrium in the long run is very unstable. These results
are in coherence with the findings of Pradhan (2010).
III-5-viii. Turkey
In the long-run there is evidence of bi-directional causality from
the VECM results for Turkey, where causality runs from real GDP to
energy consumption with a feedback affect. The relationship is also
positive and highly significant i.e., onetime relative increase in the
energy consumption will bring a relative increase of 1.04 times in real
GDP.
The error correction terms are highly significant and both are
positive. These results indicate that there is a long run bi-directional
causality between energy use and economic growth but the long run
equilibrium is not stable as suggested by the positive sign of the error
correction terms. Thus any external shock will lead to a divergence in
GDP of 82 percent every year and even higher in energy use. In the long
run the economic situation of Turkey and energy use both affect each
other. Moreover, for the period of 1980-2007, Turkey's long run
equilibrium is very unstable. The same direction of causality was found
by Aktas and Yilmaz (2008).
III-6. The Essence of Gathered Evidence
Apergis and Payne, (2009) synthesised the often conflicting results
obtained by the literature into four hypothesis. According to the
"growth hypothesis", energy consumption is a complement of
labour and capital in producing output and, as a consequence, it
contributes to growth. The "conservation hypothesis" implies
that real GDP is not affected by energy conservation policies aiming at
curtailing energy consumption and waste and improving energy efficiency.
If the "neutrality" hypothesis holds energy consumption and
real output will not have a significant connection. Finally, the
"feedback" hypothesis suggests that more energy consumption
results in increases in real GDP, and vice versa.
From the gathered evidence, in the short run, the "growth
hypothesis" is true for Iran and Nigeria, both energy exporters,
where support for the hypothesis that energy use contributes to growth
has been established. Thus energy use is an important determinant of
economic development in both of these countries in the short-run and a
shortage of energy would have serious repercussions for the pace of
development and prosperity.
The "conservation hypothesis" where GDP is not affected
by the energy use but itself has implications for energy use has been
proved for Bangladesh, Egypt, Malaysia, Pakistan and Turkey in the
short-run. In these countries, energy use does not have an influence on
the growth process while GDP has an effect on energy use. Therefore, in
these five countries, energy conservation may be viable without being
detrimental to economic growth in short-run.
The estimation results support a "neutrality hypothesis"
for Indonesia in the short-run pointing out that for the selected
sample, the energy use and real GDP did not have significant
implications for each other at least in the short-run. While in no case
a support of the "feedback hypothesis" was established in the
short-run.
In the long run, the results confirm that the "growth
hypothesis" is true for the sample period in Nigeria. Therefore in
Nigeria energy consumption has important insinuations for the growth and
prosperity of the economy. Nigerian economy, as explained in the
situation analysis, is overwhelmingly dependant on the exports of oil.
Despite its huge energy reserves, the country faces acute shortage of
financial resources and infrastructure to fully utilise them and as a
result is still an under-developed economy. The Nigerian government
heavily relies on the oil exports as they form the principal contributor
in the total national revenue. The results of estimation suggest that in
Nigeria, energy conservation policies may hinder economic growth in the
long-run. Thus it is not a superior choice for Nigerian government to
adopt energy conservation policies without diversifying the
manufacturing and export base.
The "conservation hypothesis" is true for Egypt according
to the long run investigation of the correlation between energy and
economic growth for the selected years. Thus, it implies that in Egypt
energy use does not determine pace of economic development and growth.
The rationale of such result is that Egypt's main exports consist
of non-petroleum products such as ready-made clothes, cotton textiles,
medical and petrochemical products, citrus fruits, rice and dried onion,
and more recently cement, steel, and ceramics along with natural gas.
The exports of petroleum products are minimal as compared to other
exports. Egypt's main imports consist of pharmaceuticals and
non-petroleum products such as wheat, maize, cars and car spare parts
(Wikipedia). Therefore energy sector does not play the leading role in
Egyptian economy and thus, energy conservation policies will not harm
pace of economic development in Egypt.
The "feedback hypothesis" was established by the results
of estimation of long run causality for Bangladesh, Indonesia, Iran,
Malaysia, Pakistan and Turkey. This finding leads to the conclusion that
energy sector is a major player in these economies and it has huge
impact on the national income and development of the economies. Both of
the variables have dynamic effect on each other. These findings are
appropriate for these countries as Iran and Indonesia are major energy
exporters and are prominent members of OPEC (1) while Malaysia and
Turkey are among the fastest growing energy markets. The economies of
these countries are, thus, massively dependent on their energy export
revenues and thus there is a bi-directional causality between the real
GDP and energy use as more energy production (i.e., a part of energy
use) results in more national income with a feedback affect i.e.,
increased economic prosperity results in increased energy production and
use. The economies of Pakistan and Bangladesh are facing energy
shortages but are in developing phase where economies rely heavily on
the energy use to ensure economic development. Both countries are net
importers of energy. Therefore import payments have significant
implications for the national income and any change in energy use will
lead to a change in GDP and vice versa.
The evidence of "neutrality hypothesis" was not found in
case of any of the D8 countries in the long-run. Thus the outcomes of
estimation support the evidence that energy sector is an important part
of the economies of the developing countries and it has dynamic affect
on the economic standing of these countries. The energy sector thus
needs proper attention of the governments of these countries as flawed,
defective and misguided policies can injure the economy gravely for a
long period of time.
IV. CONCLUDING REMARKS AND POLICY IMPLICATIONS
Energy plays a critical role in an economy on both demand and
supply sides. On the demand side, energy is one of the products a
consumer decides to buy to maximise his or her utility. On the supply
side, energy is a key factor of production in addition to capital,
labour and materials. This implies that there should be a causal
relationship running from energy consumption to national income or GDP
as well as vice versa. Consequently, governments as well as individuals
and firms, motivated by financial or humanistic interests and who value
access to energy as one of the basic human rights, are now making
progress to provide energy to higher percentages of population
throughout the world.
Keeping in mind the vital and critical role of energy in the
process of development, this study aimed at developing the link between
energy consumption and real output for the D8 countries including
Bangladesh, Egypt, Indonesia, Iran, Malaysia, Nigeria, Pakistan and
Turkey in both short as well as the long-run. The study was based on
annual data covering the period 1980- 2007 for all countries. VAR
Granger causality test was applied for the investigation of short-run
causality between energy use and economic growth in all countries while
to determine the long-run causal relationship, cointegration test based
on Johansen technique and Vector Error Correction Model (VECM) were
employed.
The short-run estimates of the VAR Granger causality provides
support for 'growth hypothesis' in Iran and Nigeria, of the
"conservation hypothesis" in Bangladesh, Egypt, Malaysia,
Pakistan and Turkey, and of a "neutrality hypothesis" for
Indonesia for the selected years. The 'evidence of a 'feedback
affect' in the short-run, could not be found in any case.
The Cointegration tests supported the evidence of cointegration
among the real output; measured by GDP and energy use in all the member
countries. The VECM results confirmed that in the long-run, the
"growth hypothesis" is true for the sample period in Nigeria
while "conservation hypothesis" is true for Egypt. The
"feedback hypothesis" was established by the results of
estimation of long-run causality for Bangladesh, Indonesia, Iran,
Malaysia, Pakistan and Turkey. The results based on the long-run
analysis by VECM suggest that energy consumption plays an important role
in enhancing productivity in all the countries except Egypt in long-run
and energy use has important implications for these developing countries
in the long-run. The results support the evidence of causality running
in either one or both directions between energy consumption and GDP in
all the countries in the long as well as in the short-run except
Indonesia in the short-run. On the whole, results suggest that the
economies of most countries are energy dependent and shortage of energy
may negatively affect the economic growth which eventually results in a
fall in income, employment and broadly, social welfare.
The important policy implications drawn from this study are that in
order to achieve rapid economic growth, members of the D8 should adopt a
policy of energy sector development on priority basis. The results of
estimation reveal that there is energy sector has uni-directional or
bi-directional long-run implications for the economic growth in these
countries. These D8 countries are, as concluded by the situation
analysis, rich in renewable resources of energy like tidal, air, solar,
biomass etc. Therefore, there is need to build new dams, installation of
wind power plant and tidal energy projects to expand the energy
production capacity especially in the countries facing energy crunch
such as Bangladesh, Pakistan and Turkey.
Bangladesh, Pakistan and Turkey should try to avoid or minimise the
import of crude oil at massive costs which are resulting in depletion of
foreign currency reserves. For the achievement of this objective, the
masses in these countries should be educated about the use of renewable
energy to decrease dependence on fossil and traditional sources of
energy. Moreover, policy orientation needs a drastic modification to
focus on utilisation of endogenous resources. There must be short-term
and long-term planning regarding the .energy demand and supply in the
economy. Finally these countries should pursue energy conservation
policies in such a way that is not detrimental to on economic growth.
As for the energy exporting countries, the results show that energy
consumption plays an important role in these economies in short as well
as long-run. These countries need to reduce their over dependence on the
energy sector for the economic growth and development and diversify
their economies. The analysis of the current situation exposes the
overdependence of these economies on the energy exports. The countries
such as Iran and Nigeria need to broaden their industrial and export
base from only natural resources to varying energy intensive industrial
products. Furthermore, Nigeria should develop the domestic
infrastructure and make sure of an environment conducive for foreign
investment. Iranian and Malaysian governments have historically been
giving huge amounts in respect of subsidies to the energy sector, as
mentioned in the overview of the energy sector of the respective
countries. These countries need to adjust their prices in accordance
with the international market prices.
As for Malaysia and Indonesia, two of the fastest growing economies
in East Asia, the demand of energy is growing at very fast pace in these
countries. These countries, it is feared, will have to face energy
crunch in near future. As it has been established by the outcomes of the
estimation, energy has long-run insinuations in both economies
therefore, the respective governments should plan ahead to avoid
possible chaos due to energy crisis. For that purpose, there is a dire
need of popularising the use of renewable energy, which might be the
only solution to problems related to energy demand and supply.
While this analysis conclusively demonstrates dynamic causal
linkages between energy consumption and economic growth, it should be
stressed that the usual production function also includes capital and
labour. Hence, in future work, the techniques employed in this study can
be readily extended to other multivariate systems, where energy
consumption and real income are exposed to other economic factors such
as capital stock and employment to improve the model. The sample size of
28 years may also be increased for better inferences.
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(1) For the sample period, i.e., 1980-2007. Indonesian membership
of OPEC was suspended in 2008.
Sarwat Razzaqi <
[email protected]> is Student of M.
Econ, Fatima Jinnah Women University, Rawalpindi. Faiz Bilquees
<
[email protected]> is Professor/Chairperson, Fatima Jinnah
Women University, Rawalpindi. Saadia Sherbaz
<
[email protected]> is Lecturer, Fatima Jinnah Women
University, Rawalpindi.
Table 1
Evidence from Some Previous Studies
Author(s) Analysed Variables Methodology Findings/
Countries Used Causality
and Periods
Khan and Pakistan, real output, Bound test energy
Qayyum Bangladesh, energy, ARDL consumption
(2007) India, Sri capital and to GDP
Lanka labour
(1972- energy
2004) consumption
and income
Asafu- India, Granger short-run:
Adjaye Indonesia, causality, from energy
(2000) Philippines cointegration to income
and and ECM long-run: 2
Thailand cointegrating
(1973- vectors,
1995) energy and
price
effects were
weak.
Chiou-Wei, USA, total energy linear and short-run:
et. al. Taiwan, consumption nonlinear energy
(2008) South and real GDP Granger consumption
Korea, causality causes GDP
Singapore, tests (Indonesia),
Hong Kong, bi-
Indonesia, directional
Malaysia, (Malaysia),
Philippines nonlinear
and causal
Thailand relations
(1954-
2006).
Mehrara Iran, real GDP per ECM and Toda- economic
(2007) Kuwait and capita and Yamamoto growth to
Saudi energy use procedure energy
Arabia per capita consumption
(1971-
2002)
Abbasian, Iran (1967- national VAR, granger natural gas
et al. 2005) income causality and consumption
(2010) consumption also Toda- leads to
of Yamamoto economic
electricity, causality growth
natural gas, tests.
coal,
petroleum,
solid
biomass and
total energy
consumption
Loganathan, Malaysia energy Ordinary bi-
et al. (1971-2008) consumption Least Square directional
(2010) and economic Engel- co
performance Granger, integration
Dynamic effect
Ordinary
Least Square,
ARDL, bounds
test and ECM.
Islam, et Malaysia Energy ARDL and Cointegrated,
al. (2011) (1971-2008) consumption, cointegration economic
population, growth and
aggregate financial
production, development
and cause energy
financial use.
development
Omotor Nigeria National cointegration bi-
(2008) (1970-2005) income, and Hasio's directional
coal, Granger causality
electricity Causality
and oil test
consumption
Adeniran Nigeria Oil granger Cointegrated
(2009) (1980-2006) consumption, causality and and energy
real GDP, cointegration consumption
coal con- causes
sumption, economic
and elec- growth
tricity
consumption
Okonkwo and Nigeria Economic cointegration Cointegrated
Gbadebo (1970-2005) growth and and OLS and positive
(2009) crude oil, relationship
elec- between
tricity and current
coal growth and
energy
Siddiqui Pakistan GDP, capital granger Energy
(2004) (1970-2003) stock, causality and causes
labour ARDL economic
force, human growth
capital,
exports and
energy
(electricity,
natural gas
and
petroleum)
Abosedra Turkey, oil prices cointegration Not
and Ghosh India, and economic and granger cointegrated
(2007) Philippines growth causality Short-run:
and oil prices
Korea(Jan cause
1985 to Jan economic
2005) growth in
Pakistan Pakistan and
(Jun 1994 Philippines.
to Jan
2005)
Pradhan Bangladesh, Economic cointegration energy
(2010) India, growth and and ECM causes
Nepal, energy economic
Pakistan consumption growth
and Sri
Lanka
(1970-
2006)
Soytas, et Turkey GDP and Cointegration energy
al. (2001) (1960-1995) energy and VECM causes
consumption economic
growth
Lise and Turkey GDP and Cointegration Cointegrated
Montfort (1970-2003) energy and OLS, VECM and GDP
(2005) consumption and granger causes
causality energy
consumption
Altinay and Turkey electricity Zivot and Electricity
Karagol (1950-2000) consumption Andrews test, consumption
(2005) and real GDP Dolado- causes
Lutkepohl economic
test and growth
granger
causality
test
Chontanawat, 30 OECD and Energy Hsiao Bi-
et al. 78 non OECD consumption procedure, directional
(2006) countries and GDP cointegration causality in
tests and ECM OECD
countries
Joyeux and seven East Income and Panel Not
Ripple Indian household cointegration cointegrated
(2007) Ocean electricity
countries consumption
(1971-
2001)
Imran and Bangladesh, economic panel Short-run:
Siddiqui India, and growth, cointegration, neutrality,
(2010) Pakistan energy granger long-run:
(1971-2008) consumption, causality and Cointegrated,
capital Dynamic OLS energy
stock and consumption
labour causes
economic
growth
Noor and Bangladesh, per capita Panel short-run:
Siddiqi India, GDP and per cointegration per capita
(2010) Nepal, capita test, granger GDP causes
Pakistan, energy causality test per capita
and Sri consumption and FMOLS energy
Lanka, consumption
(1971-2006) long-run:
negative
relationship
Joyeux and 26 non-OECD income and Panel Cointegrated
Ripple (1971- total cointegration and income
(2011) 2007), 30 electricity and causality causes
OECD (1960- consumption, energy
2007) residential consumption.
electricity
consumption,
total energy
consumption
Table 2
Results of ADF Test
ADF test
Country Variables Level First Order of
diff. Integration
Bangladesh Lngdpc 0.26 -5.68 * I (1)
Lneu 0.34 -3.51 * I (1)
Egypt Lngdpc -0.89 -2.66 * I (1)
Lneu -2.15 -5.07 * I (1)
Indonesia Lngdpc -1.27 -3.77 * I (1)
Lneu -1.00 -5.50 * I (1)
Iran Lngdpc 0.75 -3.86 * I (1)
Lneu -0.21 -7.21 * I (1)
Malaysia Lngdpc -0.51 -4.01 * I (1)
Lneu -0.65 -7.45 * I (1)
Nigeria Lngdpc 1.75 -4.91 * I (1)
Lneu -1.18 -4.91 * I (1)
Pakistan Lngdpc -0.75 -3.31 * I (1)
Lneu -2.14 -4.31 * I (1)
Turkey Lngdpc -0.31 -5.94 * I (1)
Lneu -0.43 -5.89 * I (1)
* Statistically Significant, 5 percent critical value
= -2.981038, 10 percent critical value 2.629906.
Table 3
VAR Lag Order Selection Criteria
Country Lags 0 1 2
Bangladesh AIC -3.26 -10.98 -11.04 *
SC -3.16 -10.69 * -10.56
Egypt AIC -2.97 -8.99 -9.03 *
SC -2.88 -8.70 * -8.55
Indonesia AIC -2.36 -7.16 * -7.15
SC -2.27 -6.87 * -6.67
Iran AIC -1.12 -5.59 -5.99 *
SC -1.02 -5.30 -5.51 *
Malaysia AIC -1.86 -6.67 * -6.62
SC -1.77 -6.38 * -6.13
Nigeria AIC -3.60 -8.94 * -8.66
SC -3.51 -8.65 * -8.18
Pakistan AIC -4.09 -10.84 * -10.68
SC -3.99 -10.55 * -10.20
Turkey AIC -3.84 -8.24 -8.34 *
SC -3.74 -7.95 * -7.85
* Indicates lag order selected by the criterion.
Table 4
VAR Granger Causality/Block Exogeneity Wald Tests
Dependent Variable
Lneu
Country Excluded Chi-sq Prob.
Bangladesh Lngdpc 5.26 * 0.02
Egypt Lngdpc 13.14 * 0.00
Indonesia Lngdpc 0.53 0.46
Iran Lngdpc 2.21 0.33
Malaysia Lngdpc 15.50 * 0.00
Nigeria Lngdpc 1.62 0.20
Pakistan Lngdpc 9.02 * 0.00
Turkey Lngdpc 2.95 * 0.08
Dependent Variable
Lngdpc
Country Excluded Chi-sq Prob. Causality
Bangladesh Lneu 0.25 0.61 GDP [right arrow] Eu
Egypt Lneu 0.03 0.86 GDP [right arrow] Eu
Indonesia Lneu 1.53 0.22 Neutrality
Iran Lneu 10.38 * 0.00 Eu [right arrow] GDP
Malaysia Lneu 0.16 0.68 GDP [right arrow] Eu
Nigeria Lneu 25.33 * 0.00 Eu [right arrow] GDP
Pakistan Lneu 0.97 0.32 GDP [right arrow] Eu
Turkey Lneu 0.21 0.65 GDP [right arrow] Eu
* Indicates statistically significant.
Table 5
Results of Johansen's Cointegration Test (between Lngdpc and Lneu)
Trace Critical Max-Eigen
Country No. of CE's Statistic Value Statistic
Bangladesh [H.sub.0]: None * 39.27 20.26 33.15
[H.sub.0]: At most 1 6.12 9.16 6.12
Egypt [H.sub.0]: None * 24.69 23.34 17.11
[H.sub.0]: At most 1 7.58 10.67 7.58
Indonesia [H.sub.0]: None * 21.16 20.26 14.01
[H.sub.0]: At most 1 7.15 9.16 7.15
Iran [H.sub.0]: None * 27.05 20.26 19.55
[H.sub.0]: At most 1 7.51 9.16 7.51
Malaysia [H.sub.0]: None * 13.18 12.32 13.18
[H.sub.0]: At most 1 0.00 4.13 0.00
Nigeria [H.sub.0]: None * 24.87 20.26 15.79
[H.sub.0]: At most 1 9.08 9.16 9.08
Pakistan [H.sub.0]: None * 18.74 20.26 16.30
[H.sub.0]: At most 1 2.43 9.16 2.43
Turkey [H.sub.0]: None * 33.70 20.26 27.85
[H.sub.0]: At most 1 5.85 9.16 5.85
Critical
Country No. of CE's Value Conclusion
Bangladesh [H.sub.0]: None * 15.89 Cointegrated
[H.sub.0]: At most 1 9.16
Egypt [H.sub.0]: None * 17.23 Cointegrated
[H.sub.0]: At most 1 10.67
Indonesia [H.sub.0]: None * 15.89 Cointegrated
[H.sub.0]: At most 1 9.16
Iran [H.sub.0]: None * 15.89 Cointegrated
[H.sub.0]: At most 1 9.16
Malaysia [H.sub.0]: None * 11.22 Cointegrated
[H.sub.0]: At most 1 4.13
Nigeria [H.sub.0]: None * 15.89 Cointegrated
[H.sub.0]: At most 1 9.16
Pakistan [H.sub.0]: None * 15.89 Cointegrated
[H.sub.0]: At most 1 9.16
Turkey [H.sub.0]: None * 15.89 Cointegrated
[H.sub.0]: At most 1 9.16
* Denotes rejection of the hypothesis at the 0.05 or 0.1 level.
Table 6
Summary of VECM Results (Dependent Variable= Lngdpc)
Dependent ECT
Variable
Country =Lngdpc D(Lngdpc) D(Lneu)
Bangladesh 0.55 *** 0.05 *** 0.11 ***
(5.72) (5.30) (3.83)
Egypt 0.11 -0.60 *** -0.47
(1.57) (-4.51) (-1.06)
Indonesia 1.15 *** 0.13 ** 0.249 ***
12.60) (1.97) (3.92)
Iran 0.71 *** -0.15 *** -0.30 ***
(10.28) (-2.22) (-4.34)
Malaysia 0.55 *** -0.02 *** -0.02 ***
(23.67) (-3.58) (-2.49)
Nigeria 1.69 *** 0.05 0.09 ***
(7.40) (1.09) (4.36)
Pakistan 1.11 *** 0.27 *** 0.45 ***
(50.20) (2.21) (4.48)
Turkey 1.04 *** 0.82 *** 1.06 ***
(52.52) (3.73) (5.94)
Country Causality
Bangladesh GDP [left and right arrow] Eu
Egypt GDP [right arrow] Eu
Indonesia GDP [left and right arrow] Eu
Iran GDP [left and right arrow] Eu
Malaysia GDP [left and right arrow] Eu
Nigeria Eu [right arrow] GDP
Pakistan GDP [left and right arrow] Eu
Turkey GDP [left and right arrow] Eu
*, **, *** indicates significant at 10 percent,
5 percent and 1 percent respectively.
t-values in parenthesis.
Table 7
Direction of Short-Run Causality in the D8 Countries
Feedback Growth Conservation Neutrality
Hypothesis Hypothesis Hypothesis Hypothesis
-- Iran Bangladesh Indonesia
-- Nigeria Egypt --
-- -- Malaysia --
-- -- Pakistan --
-- -- Turkey --
Table 8
Direction of Long-run Causality in All D8 Countries
Feedback Growth Conservation Neutrality
Hypothesis Hypothesis Hypothesis Hypothesis
Bangladesh Nigeria Egypt --
Indonesia -- -- --
Malaysia -- -- --
Pakistan -- -- --
Turkey -- -- --
Iran -- -- --
