Download Empirical Analysis on Impact of Energy Consumption on Economic

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Empirical Analysis on Impact of Energy Consumption on Economic
Growth in Inner Mongolia
WANG Lijuan, XU Ye
School of Economics and Business, Shijiazhuang University of Economics, Shijiazhuang, China,
050031
[email protected]
：
Abstract In this paper, the relationship between economic growth and energy consumption in Inner
Mongolia is analyzed by using 1997-2007 GDP and total energy consumption data of Inner Mongolia
Autonomous Region and by constructing cointegration equation, error correction model and Granger
causality relation. The results show that there exists cointegration relationship between economic growth
rate and energy consumption rate of Inner Mongolia, and exists unidirectional causality from energy
consumption rate to economic growth rate. Therefore, the government should be careful in formulating
energy and environmental policies so as to avoid adverse effects on economic growth.
Keywords Energy Consumption, Economic Growth, Cointegration Analysis, Granger Causality Test
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1 Introduction
On the relationship between foreign trade and economic growth, researchers domestic and abroad have
conducted huge amount of studies. Foreign researchers study the relationship between trade and
economic growth from the perspective of developed countries. Their applications require re-examination
on China, a major developing country, as China’s dependence on trade is continuously increasing.
Domestic researchers take few considerations on the stability of economic data when conducting studies,
which impacts on the accuracy of model estimation. Therefore, this paper applies cointegration theory
and Granger Causality Test method, takes into consideration the impact of variables’ short run
fluctuation on variables long run equilibrium, and analyzes the relationship between China’s energy
consumption and economic growth. This is of great significance to the sustainable economic
development, the formulation of energy development strategies and relevant policies and regulations of
Inner Mongolia.
2 Positive Analyses
2.1 Data Selection and Processing Instructions
In this paper, 1997-2007 data is used for the empirical analysis on Inner Mongolia’s energy consumption
and economic growth, data is sourced from the 2008 Statistical Yearbook of Inner Mongolia. The model
applies major analytical variables with Inner Mongolia real GDP (Gross Domestic Product) and total
energy consumption (E). To eliminate the heteroscedasticity existed in time series, various variables are
switched with logarithm. The switched variables are lnGDP and lnE respectively.
2.2 Positive Analysis
2.2.1 Correlation Analysis
To test the relationship between the variables on a preliminary level, Eviews5.0 is applied in the
calculation of correlation coefficient. The correlation coefficients of the various variables are thus
generated. as shown in table 1.
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Table 1 Correlation Coefficients between lnGDP and lnE
GDP
E
lnGDP
lnE
495.9027
3708.95
6.2064
8.2185
548.7199
3440.06
6.3076
8.1432
597.1909
3634.88
6.3922
8.1983
661.3988
3937.54
6.4944
8.2783
732.1685
4453.48
6.5960
8.4014
828.5553
5190.12
6.7197
8.5545
976.8668
6612.77
6.8844
8.7968
1177.124
8601.81
7.0708
9.0597
1457.28
10764.9
7.2843
9.2840
1734.163
12805.52
7.4583
9.4576
2065.388
1469.39
7.6331
9.5922
Year
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2.2.2 Stationary Analysis
Most of the economic data are non-stable variables, as they have strong change tendency with the
change of time. If regression equation is established on these data, the issue of “Fake Regression” will
emerge. Therefore, this paper applies unit root test to determine whether the variable is stable before
establishing proper regression equation.
Variable
lnGDP
lnE
lnGDP
lnE
2
lnGDP
2
lnE
△
△
△
△
Table 2 ADF Unit Root Test Result
ADF value
1%TLV
5%TLV
2.3089
-3.8067
-3.0199
2.1117
-3.8067
-3.0199
-0.7218
-3.8304
-3.0294
-1.2403
-3.8304
-3.0294
-3.2894
-3.8572
-3.04
-3.1939
-3.8572
-3.04
Test form
（C,0,1）
（C,0,1）
（C,0,1）
（C,0,1）
（C,0,1）
（C,0,1）
p.s. (C, T, K) represent the constant, time trend and lagging rank figure in the model.
second-order difference
△: first-order difference, △2:
△
△
△
△
The results of Table 2 show that, although the variables lnGDP, lnE, lnGDP, and lnE all have shown
non-stationary nature, their second-order differences 2lnGDP and 2lnE rejected the null hypothesis
of existence of unit root at 1% significance level, they all belong to the second-order stationary
sequences. Hence, cointegration analysis can be conducted on the difference of the original data.
2.2.3 Cointegration Analysis
To investigate whether there exists long-term stable equilibrium relation between lnGDP and lnE, that is,
whether these two variables are cointegrated, Johansen maximum likelihood estimation is used to test
the cointegration relation of each variable. Test results are shown in Table 3.
Table 3 Johansen Cointegration Analysis table
Cointegration
equation
eigenvalue
Trace
statistic
1%TLV
5% TLV
N=0*
0.5305
16.3704
20.04
15.41
N
0.1422
2.7613
6.65
3.76
≦1
From Table 3 we can see that, the null hypothesis with no cointegration equation is rejected at 5%
significance level, and the null hypothesis with at most one cointegration equation is accepted.
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Therefore, at the 5% significance level, there only exists a long-term equilibrium cointegration
relationship between the variables lnGDP and lnE, this long-term equilibrium relationship can guarantee
any short-term deviation of variables of returning to the long-run equilibrium state because of the
cointegration relationship.
2.2.4 Error Correction Model
Through the error correction model, we can see more accurate long-term equilibrium cointegration
relationship as follows:
1
Ecm = ∆ ln GDP − 0.4723∆ ln E − 0.0671
Equation (1) shows that in the long term, 0.4723 is the flexibility of energy consumption change rate to
the change rate of economic growth, that is, the energy consumption rate did not change about 1 %,
driving positive changes in the economic growth rate by 0.4723 %.
（）
Table 4 Estimation results of error correction model
Error
Model
△
Correction
D( lnGDP)1
△
D( lnE)0
coefficient
T- statistics
coefficient
T- statistics
Ecm
-0.6506
-3.1141
0.6075
-0.5681
D( lnGDP(-1))
0.1047
-0.5496
0.2802
-0.2874
0.2192
-1.2444
-0.3611
-0.4004
-0.0975
-0.9552
-0.3818
-0.7308
-0.0082
-0.1169
0.0656
-0.1835
0.007
-1.6234
0.0056
-0.2509
△
D(△lnGDP(-2))
D(△lnE(-1))
D(△lnE(-2))
C
Adj. r-square
F-statistics
log-likelihood
75.129
AIC
-6.7921
SC
-6.0996
0.5124
0.2989
4.5733
2.4494
Viewing from the estimation results of error correction model (see Table 4), the log-likelihood of model
is large, ACI and SC are small, Adj. r-square are 0.5124 and 0.2989, and F-statistics reach 4.5733 and
2.4494 respectively, indicating that the error correction model 1 and 0 are statistically significant, and the
model's overall explanatory power is relatively strong. Viewing from the parameter estimation results,
the adjustment coefficient of error correction term in equation 1 is negative value and the parameter is
significant, while the adjustment coefficient of error correction term in equation 0 is positive value, their
adjustment directions are opposite. In the short term, the impact of economic growth rate in lag phase I
and II on the current energy consumption rate and economic growth rate is not statistically significant;
the impact of energy consumption in lag phase I and II on the current energy consumption rate and
economic growth rate is not statistically significant. Therefore, in the short term, the impact of energy
consumption rate on economic growth rate is not significant.
2.2.5 Granger Causality Test
There exists long-term equilibrium relationship between economic growth rate and energy consumption
rate, but for whether the two constitute causal relationship needs further testing. Please refer to Table 5
for the test results.
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Table 5 Granger Causality Test table
Null Hypothesis
Number of
lag phases
F-statistics
Prob.
Conclusion
The reason why lnE is not lnGDP
The reason why lnGDP is not lnE
The reason why lnE is not lnGDP
The reason why lnGDP is not lnE
The reason why lnE is not lnGDP
The reason why lnGDP is not lnE
1
1
2
2
3
3
10.9274
5.7413
4.2961
0.8117
3.9653
0.4466
0.0042
0.0284
0.0351
0.464
0.0385
0.7246
Reject
Reject
Reject
Accept
Reject
Accept
The results show that when the number of lag phase is 1, the energy consumption rate and economic
growth rate are mutually causal at 95% confidence level; when the number of lag phases is 2 and 3, at
95% confidence level, energy consumption rate is the reason for economic growth rate, while economic
growth rate is not the reason for energy consumption rate. Combined with the above cointegration
analysis, we can see that in the long term, energy consumption rate is Granger cause of economic
growth rate, while economic growth rate is not the Granger cause of energy consumption rate.
3 Conclusion
In conclusion, in the long term, Inner Mongolia’s energy consumption rate will be faster than economic
growth rate, showing energy consumption-based extensive growth pattern. In the short term, if the
government formulates relatively compact energy policy and environmental policy, it will adversely
affect Inner Mongolia’s economy. Therefore, to reduce the adverse effects of fluctuation of energy
consumption on economic growth, firstly, we should optimize Inner Mongolia’s energy consumption
structure, vigorously develop wind power, hydropower and other clean energies to replace the reliance
on coal energy consumption; secondly, we should increase investment in energy technology, improve
the overall efficiency of energy utilization, accelerate the transformation of economic structure to the
energy-saving and intensive structure to further ensure Inner Mongolia’s sustainable economic
development; at last, accelerate the upgrading of industrial structure, transform Inner Mongolia’s
economic development mode, vigorously develop electronics, biology, and other high-tech industries,
promote Inner Mongolia’s economy to achieve low power consumption, low pollution, and high output
economic development mode.
References
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Economics, 2000(22) 309~317
[2]. Lin Boqiang. Electricity Consumption and Economic Growth of China: Research Based on the
Production Function. Management World, 2003(11):18~27
[3]. Xu Gang, Pan Qizhi. Empirical Analysis on China's Energy Consumption, Economic Growth and
Energy Efficiency Relations. Journal of Central University of Finance & Economics, 2009(5):
63~68
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