Abstract:
Based on the panel data of coal consumption, urbanization, advanced industrial structure and rationalization of industrial structure in 17 provinces in the central and western regions in China from 2000 to 2019, this paper constructs a PVAR model to analyze the interactive influence relationship among the four. The results show that urbanization is the Granger cause of coal consumption, and coal consumption firstly has a positive effect on urbanization and then has a negative effect on it in the short term; coal consumption is the Granger cause of advancement of industrial structure. And the coal consumption has more lastingly negative effect on the advancement of industrial structure. The advancement of industrial structure is the Granger cause of urbanization and the rationalization of the industrial structure. It has a long-term negative effect on urbanization and negative effect on rationalization of the industrial structure. Therefore, China should promote the development of high-quality urbanization, adjust the industrial structure and form a virtuous circle to control coal consumption.
Key words:
central and western regions in China,
energy consumption structure,
coal consumption,
urbanization,
industrial structure,
carbon peak,
carbon neutralization
数据平稳性检验结果"
|
变量
|
LLC
|
Breitung
|
PP-Fisher
|
|
t
|
P
|
t
|
P
|
chi-square
|
P
|
|
lnmt
|
1.292
|
0.901
|
4.046
|
1.000
|
9.500
|
1.000
|
|
dlnmt
|
-10.010
|
0.000
***
|
-4.225
|
0.000
***
|
156.518
|
0.000
***
|
|
lnur
|
-2.466
|
0.006
***
|
1.630
|
0.948
|
85.286
|
0.000
***
|
|
dlnur
|
-10.279
|
0.000
***
|
-6.439
|
0.000
***
|
146.200
|
0.000
***
|
|
lnts
|
1.821
|
0.965
|
4.443
|
1.000
|
5.821
|
1.000
|
|
dlnts
|
-10.428
|
0.000
***
|
-30.674
|
0.001
***
|
135.615
|
0.000
***
|
|
lntl
|
-2.423
|
0.007
***
|
-1.102
|
0.135
|
33.485
|
0.492
|
|
dlntl
|
-13.238
|
0.000
***
|
-8.285
|
0.000
***
|
160.978
|
0.000
***
|
PVAR格兰杰因果检验结果"
|
因变量
|
自变量
|
统计量
|
自由度
|
P
|
|
h_dlnmt
|
h_dlnur
|
64.895
|
5
|
0.000
***
|
|
h_dlnts
|
9.003
|
5
|
0.109
|
|
h_dlntl
|
6.640
|
5
|
0.249
|
|
h_dlnur
|
h_dlnmt
|
7.442
|
5
|
0.190
|
|
h_dlnts
|
12.527
|
5
|
0.028
**
|
|
h_dlntl
|
2.737
|
5
|
0.741
|
|
h_dlnts
|
h_dlnmt
|
13.317
|
5
|
0.021
**
|
|
h_dlnur
|
10.632
|
5
|
0.059
*
|
|
h_dlntl
|
0.948
|
5
|
0.967
|
|
h_dlntl
|
h_dlnmt
|
7.834
|
5
|
0.166
|
|
h_dlnur
|
5.510
|
5
|
0.357
|
|
h_dlnts
|
11.695
|
5
|
0.039
**
|
dlnmt和dlnur的方差分解结果"
|
滞后阶数
|
dlnmt
|
dlnur
|
|
dlnmt
|
dlnur
|
dlnts
|
dlntl
|
dlnmt
|
dlnur
|
dlnts
|
dlntl
|
|
1
|
1
|
0
|
0
|
0
|
0.018
|
0.982
|
0
|
0
|
|
2
|
0.961
|
0.004
|
0.034
|
0.002
|
0.030
|
0.963
|
0.001
|
0.006
|
|
3
|
0.906
|
0.007
|
0.035
|
0.052
|
0.036
|
0.918
|
0.038
|
0.008
|
|
4
|
0.881
|
0.007
|
0.049
|
0.063
|
0.035
|
0.898
|
0.056
|
0.011
|
|
5
|
0.867
|
0.007
|
0.053
|
0.073
|
0.034
|
0.859
|
0.094
|
0.013
|
|
6
|
0.867
|
0.007
|
0.052
|
0.074
|
0.038
|
0.821
|
0.129
|
0.012
|
|
7
|
0.866
|
0.007
|
0.054
|
0.073
|
0.047
|
0.810
|
0.131
|
0.012
|
|
8
|
0.865
|
0.007
|
0.054
|
0.074
|
0.050
|
0.800
|
0.138
|
0.012
|
|
9
|
0.865
|
0.007
|
0.054
|
0.074
|
0.053
|
0.794
|
0.141
|
0.013
|
|
10
|
0.863
|
0.007
|
0.055
|
0.076
|
0.055
|
0.789
|
0.143
|
0.013
|
dlnts和dlntl的方差分解结果"
|
滞后阶数
|
dlnts
|
dlntl
|
|
dlnmt
|
dlnur
|
dlnts
|
dlntl
|
dlnmt
|
dlnur
|
dlnts
|
dlntl
|
|
1
|
0.071
|
0.041
|
0.889
|
0
|
0.005
|
0.014
|
0.050
|
0.931
|
|
2
|
0.141
|
0.035
|
0.823
|
0.002
|
0.012
|
0.014
|
0.081
|
0.893
|
|
3
|
0.158
|
0.032
|
0.808
|
0.002
|
0.013
|
0.014
|
0.082
|
0.891
|
|
4
|
0.159
|
0.03
|
0.805
|
0.005
|
0.021
|
0.014
|
0.094
|
0.872
|
|
5
|
0.166
|
0.031
|
0.797
|
0.006
|
0.023
|
0.014
|
0.096
|
0.867
|
|
6
|
0.177
|
0.029
|
0.788
|
0.006
|
0.022
|
0.013
|
0.098
|
0.866
|
|
7
|
0.189
|
0.028
|
0.775
|
0.008
|
0.027
|
0.013
|
0.101
|
0.859
|
|
8
|
0.196
|
0.028
|
0.768
|
0.009
|
0.029
|
0.013
|
0.101
|
0.857
|
|
9
|
0.200
|
0.027
|
0.763
|
0.010
|
0.029
|
0.013
|
0.102
|
0.856
|
|
10
|
0.203
|
0.027
|
0.759
|
0.011
|
0.030
|
0.013
|
0.103
|
0.855
|
