Table 1
Input-output indicators
Indicators
|
Category
|
Specific indicators
|
Input indicators
|
Labor
|
Total number of the year-end employees
|
|
Energy consumption
|
Total energy consumption and is converted into standard coal equivalent
|
|
Capital
|
Fixed asset investment[1]
|
Output indicators
|
Desirable output
|
The actual GDP and is converted into the 2000 base period price
|
|
Undesirable output
|
Carbon emissions calculated by Eq.(6)
|
Table 2
Variables in measuring the CRP
Indexes
|
Category
|
Specific indicators
|
Development equity
|
Per capita regional carbon emissions
|
The ratio of carbon emissions to population
|
|
Per capita GDP
|
The real GDP per capital
|
Carbon abatement efficiency
|
Carbon emission intensity
|
The ratio of carbon emissions to GDP
|
|
Carbon shadow price
|
Carbon shadow price calculated by Eq.(2)-(5)
|
Table 3
Influencing factors of CRP
Explanatory variables
|
Abbreviation
|
Unit
|
Remarks
|
Population size
|
POP
|
-
|
The logarithm of population
|
Economic development
|
GDP
|
100 million yuan
|
Real GDP
|
Industrial structure
|
IND
|
%
|
The proportion of the secondary industry to the tertiary industries
|
Low-carbon innovation
|
GREEN
|
-
|
The logarithm of the number of patent applications plus one
|
Energy structure
|
ES
|
%
|
The ratio of coal consumption to energy consumption
|
Energy efficiency
|
EE
|
%
|
The GDP created by the energy consumption per unit.
|
Economic opening rate
|
OPEN
|
%
|
The ratio of total import and export to GDP
|
Table 4
China’s regional MCRP and ranking in 2001, 2006, 2011, and 2017
Region
|
Province
|
2001
|
Rank
|
2006
|
Rank
|
2011
|
Rank
|
2017
|
Rank
|
Mean
|
Eastern
|
Beijing
|
0.355
|
8
|
0.386
|
8
|
0.262
|
14
|
0.273
|
15
|
0.305
|
|
Tianjin
|
0.375
|
5
|
0.417
|
6
|
0.349
|
7
|
0.362
|
8
|
0.365
|
|
hebei
|
0.337
|
12
|
0.378
|
9
|
0.346
|
8
|
0.295
|
12
|
0.335
|
|
Liaoning
|
0.382
|
4
|
0.418
|
5
|
0.389
|
3
|
0.375
|
6
|
0.384
|
|
Shanghai
|
0.395
|
3
|
0.441
|
4
|
0.381
|
4
|
0.417
|
3
|
0.396
|
|
Jiangsu
|
0.281
|
23
|
0.325
|
20
|
0.345
|
9
|
0.371
|
7
|
0.313
|
|
Zhejiang
|
0.273
|
27
|
0.328
|
18
|
0.305
|
11
|
0.308
|
10
|
0.284
|
|
Fujian
|
0.281
|
24
|
0.322
|
21
|
0.251
|
17
|
0.276
|
14
|
0.269
|
|
Shandong
|
0.293
|
19
|
0.345
|
14
|
0.373
|
6
|
0.381
|
5
|
0.336
|
|
Guangdong
|
0.256
|
30
|
0.311
|
25
|
0.317
|
10
|
0.324
|
9
|
0.283
|
|
Hainan
|
0.273
|
28
|
0.297
|
28
|
0.146
|
30
|
0.168
|
27
|
0.221
|
|
Mean
|
0.318
|
-
|
0.361
|
-
|
0.315
|
-
|
0.323
|
-
|
|
Central
|
Shanxi
|
0.506
|
1
|
0.605
|
1
|
0.47
|
2
|
0.57
|
1
|
0.534
|
|
Jilin
|
0.335
|
13
|
0.359
|
12
|
0.255
|
16
|
0.234
|
18
|
0.284
|
|
Heilongjiang
|
0.345
|
11
|
0.369
|
10
|
0.288
|
12
|
0.261
|
16
|
0.309
|
|
Anhui
|
0.315
|
15
|
0.316
|
23
|
0.218
|
20
|
0.212
|
19
|
0.257
|
|
Jiangxi
|
0.286
|
22
|
0.302
|
27
|
0.171
|
27
|
0.168
|
26
|
0.222
|
|
Henan
|
0.301
|
17
|
0.33
|
17
|
0.284
|
13
|
0.243
|
17
|
0.284
|
|
Hubei
|
0.299
|
18
|
0.319
|
22
|
0.228
|
19
|
0.211
|
20
|
0.252
|
|
Hunan
|
0.28
|
25
|
0.311
|
24
|
0.205
|
22
|
0.192
|
23
|
0.235
|
|
Mean
|
0.333
|
-
|
0.364
|
-
|
0.265
|
-
|
0.261
|
-
|
|
Western
|
Chongqing
|
0.291
|
20
|
0.307
|
26
|
0.204
|
23
|
0.207
|
21
|
0.238
|
|
Sichuan
|
0.269
|
29
|
0.294
|
29
|
0.214
|
21
|
0.2
|
22
|
0.238
|
|
Guizhou
|
0.36
|
7
|
0.386
|
7
|
0.194
|
24
|
0.187
|
24
|
0.281
|
|
Yunnan
|
0.29
|
21
|
0.333
|
16
|
0.182
|
26
|
0.151
|
30
|
0.23
|
|
Shaanxi
|
0.306
|
16
|
0.334
|
15
|
0.246
|
18
|
0.295
|
13
|
0.282
|
|
Gansu
|
0.35
|
9
|
0.351
|
13
|
0.191
|
25
|
0.173
|
25
|
0.259
|
|
Qinghai
|
0.32
|
14
|
0.327
|
19
|
0.162
|
29
|
0.161
|
29
|
0.234
|
|
Ningxia
|
0.499
|
2
|
0.484
|
2
|
0.378
|
5
|
0.382
|
4
|
0.418
|
|
Xinjiang
|
0.348
|
10
|
0.367
|
11
|
0.258
|
15
|
0.3
|
11
|
0.305
|
|
Inner Mongolia
|
0.369
|
6
|
0.442
|
3
|
0.48
|
1
|
0.468
|
2
|
0.431
|
|
Guangxi
|
0.277
|
26
|
0.292
|
30
|
0.169
|
28
|
0.161
|
28
|
0.213
|
|
Mean
|
0.334
|
-
|
0.356
|
-
|
0.243
|
-
|
0.244
|
-
|
|
All
|
Mean
|
0.334
|
-
|
0.373
|
-
|
0.311
|
-
|
0.312
|
-
|
|
Table 5
China’s regional FCRP and ranking in 2001, 2006, 2011, and 2017
Region
|
Province
|
2001
|
Rank
|
2006
|
Rank
|
2011
|
Rank
|
2017
|
Rank
|
Mean
|
Eastern
|
Beijing
|
0.298
|
5
|
0.345
|
7
|
0.278
|
12
|
0.316
|
11
|
0.298
|
|
Tianjin
|
0.304
|
4
|
0.372
|
4
|
0.380
|
6
|
0.426
|
4
|
0.361
|
|
hebei
|
0.247
|
10
|
0.301
|
8
|
0.311
|
9
|
0.289
|
15
|
0.284
|
|
Liaoning
|
0.296
|
6
|
0.352
|
6
|
0.380
|
4
|
0.395
|
6
|
0.35
|
|
Shanghai
|
0.347
|
3
|
0.413
|
2
|
0.401
|
3
|
0.478
|
3
|
0.398
|
|
Jiangsu
|
0.212
|
19
|
0.272
|
15
|
0.327
|
8
|
0.391
|
7
|
0.286
|
|
Zhejiang
|
0.210
|
21
|
0.276
|
14
|
0.291
|
10
|
0.327
|
10
|
0.261
|
|
Fujian
|
0.206
|
22
|
0.255
|
18
|
0.244
|
15
|
0.303
|
14
|
0.241
|
|
Shandong
|
0.217
|
16
|
0.287
|
10
|
0.343
|
7
|
0.387
|
8
|
0.299
|
|
Guangdong
|
0.196
|
26
|
0.258
|
16
|
0.289
|
11
|
0.327
|
9
|
0.253
|
|
Hainan
|
0.190
|
29
|
0.218
|
28
|
0.143
|
30
|
0.185
|
24
|
0.186
|
|
Mean
|
0.248
|
-
|
0.304
|
-
|
0.308
|
-
|
0.348
|
-
|
|
Central
|
Shanxi
|
0.376
|
1
|
0.502
|
1
|
0.442
|
2
|
0.581
|
1
|
0.471
|
|
Jilin
|
0.244
|
12
|
0.280
|
12
|
0.246
|
14
|
0.255
|
17
|
0.246
|
|
Heilongjiang
|
0.254
|
8
|
0.292
|
9
|
0.270
|
13
|
0.273
|
16
|
0.267
|
|
Anhui
|
0.220
|
15
|
0.231
|
24
|
0.188
|
21
|
0.206
|
21
|
0.204
|
|
Jiangxi
|
0.197
|
25
|
0.219
|
27
|
0.149
|
28
|
0.167
|
28
|
0.175
|
|
Henan
|
0.211
|
20
|
0.249
|
20
|
0.243
|
16
|
0.232
|
18
|
0.229
|
|
Hubei
|
0.213
|
17
|
0.240
|
23
|
0.205
|
19
|
0.216
|
20
|
0.208
|
|
Hunan
|
0.194
|
27
|
0.228
|
26
|
0.177
|
23
|
0.189
|
23
|
0.188
|
|
Mean
|
0.239
|
-
|
0.280
|
-
|
0.240
|
-
|
0.265
|
-
|
|
Western
|
Chongqing
|
0.205
|
23
|
0.229
|
25
|
0.192
|
20
|
0.223
|
19
|
0.201
|
|
Sichuan
|
0.185
|
30
|
0.214
|
29
|
0.181
|
22
|
0.192
|
22
|
0.188
|
|
Guizhou
|
0.246
|
11
|
0.278
|
13
|
0.164
|
25
|
0.183
|
25
|
0.218
|
|
Yunnan
|
0.200
|
24
|
0.242
|
21
|
0.156
|
27
|
0.149
|
30
|
0.18
|
|
Shaanxi
|
0.213
|
18
|
0.250
|
19
|
0.224
|
18
|
0.304
|
13
|
0.236
|
|
Gansu
|
0.244
|
13
|
0.257
|
17
|
0.167
|
24
|
0.169
|
27
|
0.205
|
|
Qinghai
|
0.225
|
14
|
0.241
|
22
|
0.160
|
26
|
0.176
|
26
|
0.194
|
|
Ningxia
|
0.368
|
2
|
0.382
|
3
|
0.380
|
5
|
0.417
|
5
|
0.37
|
|
Xinjiang
|
0.254
|
9
|
0.284
|
11
|
0.243
|
17
|
0.313
|
12
|
0.263
|
|
Inner Mongolia
|
0.269
|
7
|
0.367
|
5
|
0.490
|
1
|
0.517
|
2
|
0.404
|
|
Guangxi
|
0.190
|
28
|
0.209
|
30
|
0.148
|
29
|
0.160
|
29
|
0.167
|
|
Mean
|
0.236
|
-
|
0.268
|
-
|
0.228
|
-
|
0.255
|
-
|
|
All
|
Mean
|
0.251
|
-
|
0.305
|
-
|
0.298
|
-
|
0.331
|
-
|
|
Table 6
China’s regional ECRP and ranking in 2001, 2006, 2011, and 2017
Region
|
Province
|
2001
|
Rank
|
2006
|
Rank
|
2011
|
Rank
|
2017
|
Rank
|
Mean
|
Eastern
|
Beijing
|
0.411
|
15
|
0.426
|
13
|
0.246
|
21
|
0.229
|
17
|
0.312
|
|
Tianjin
|
0.446
|
7
|
0.463
|
7
|
0.318
|
11
|
0.298
|
10
|
0.368
|
|
hebei
|
0.426
|
12
|
0.455
|
8
|
0.381
|
5
|
0.301
|
9
|
0.386
|
|
Liaoning
|
0.469
|
4
|
0.484
|
5
|
0.399
|
4
|
0.354
|
5
|
0.417
|
|
Shanghai
|
0.443
|
8
|
0.469
|
6
|
0.361
|
8
|
0.357
|
4
|
0.395
|
|
Jiangsu
|
0.349
|
28
|
0.377
|
26
|
0.363
|
7
|
0.35
|
6
|
0.34
|
|
Zhejiang
|
0.336
|
29
|
0.379
|
25
|
0.318
|
12
|
0.288
|
11
|
0.306
|
|
Fujian
|
0.356
|
25
|
0.389
|
22
|
0.257
|
17
|
0.249
|
16
|
0.298
|
|
Shandong
|
0.368
|
22
|
0.403
|
18
|
0.402
|
3
|
0.375
|
3
|
0.374
|
|
Guangdong
|
0.316
|
30
|
0.365
|
30
|
0.345
|
9
|
0.322
|
8
|
0.314
|
|
Hainan
|
0.356
|
26
|
0.376
|
27
|
0.15
|
30
|
0.151
|
29
|
0.257
|
|
Mean
|
0.289
|
-
|
0.417
|
-
|
0.322
|
-
|
0.298
|
-
|
|
Central
|
Shanxi
|
0.637
|
1
|
0.708
|
1
|
0.498
|
1
|
0.56
|
1
|
0.598
|
|
Jilin
|
0.427
|
11
|
0.437
|
12
|
0.263
|
16
|
0.213
|
19
|
0.321
|
|
Heilongjiang
|
0.435
|
10
|
0.447
|
10
|
0.305
|
13
|
0.249
|
15
|
0.351
|
|
Anhui
|
0.411
|
14
|
0.402
|
19
|
0.249
|
19
|
0.217
|
18
|
0.309
|
|
Jiangxi
|
0.376
|
21
|
0.385
|
24
|
0.194
|
27
|
0.169
|
26
|
0.268
|
|
Henan
|
0.391
|
17
|
0.41
|
17
|
0.324
|
10
|
0.254
|
14
|
0.338
|
|
Hubei
|
0.386
|
18
|
0.398
|
20
|
0.251
|
18
|
0.206
|
21
|
0.296
|
|
Hunan
|
0.365
|
23
|
0.393
|
21
|
0.233
|
22
|
0.195
|
22
|
0.283
|
|
Mean
|
0.428
|
-
|
0.448
|
-
|
0.29
|
-
|
0.258
|
-
|
|
Western
|
Chongqing
|
0.377
|
20
|
0.385
|
23
|
0.216
|
24
|
0.191
|
24
|
0.276
|
|
Sichuan
|
0.353
|
27
|
0.374
|
29
|
0.248
|
20
|
0.209
|
20
|
0.288
|
|
Guizhou
|
0.474
|
3
|
0.494
|
4
|
0.224
|
23
|
0.191
|
23
|
0.345
|
|
Yunnan
|
0.38
|
19
|
0.424
|
14
|
0.208
|
26
|
0.154
|
28
|
0.281
|
|
Shaanxi
|
0.399
|
16
|
0.419
|
15
|
0.268
|
15
|
0.286
|
13
|
0.328
|
|
Gansu
|
0.455
|
6
|
0.445
|
11
|
0.215
|
25
|
0.176
|
25
|
0.314
|
|
Qinghai
|
0.415
|
13
|
0.412
|
16
|
0.163
|
29
|
0.145
|
30
|
0.273
|
|
Ningxia
|
0.629
|
2
|
0.587
|
2
|
0.376
|
6
|
0.347
|
7
|
0.466
|
|
Xinjiang
|
0.441
|
9
|
0.45
|
9
|
0.272
|
14
|
0.287
|
12
|
0.348
|
|
Inner Mongolia
|
0.469
|
5
|
0.516
|
3
|
0.469
|
2
|
0.419
|
2
|
0.459
|
|
Guangxi
|
0.364
|
24
|
0.375
|
28
|
0.19
|
28
|
0.162
|
27
|
0.259
|
|
Mean
|
0.433
|
-
|
0.444
|
-
|
0.259
|
-
|
0.233
|
-
|
|
All
|
Mean
|
0.417
|
-
|
0.441
|
-
|
0.324
|
-
|
0.293
|
-
|
|
Table 7
The Moran's I index of CRP in China (2000-2017)
Year
|
MCRP
|
P-Value
|
FCRP
|
P-Value
|
ECRP
|
P-Value
|
2000
|
0.136**
|
0.032
|
0.166**
|
0.016
|
0.135**
|
0.030
|
2001
|
0.149**
|
0.022
|
0.183***
|
0.010
|
0.145**
|
0.021
|
2002
|
0.143**
|
0.026
|
0.180**
|
0.011
|
0.140**
|
0.026
|
2003
|
0.100*
|
0.066
|
0.123**
|
0.042
|
0.107*
|
0.056
|
2004
|
0.138**
|
0.027
|
0.191***
|
0.007
|
0.126**
|
0.035
|
2005
|
0.187***
|
0.006
|
0.248***
|
0.001
|
0.156**
|
0.013
|
2006
|
0.189***
|
0.005
|
0.253***
|
0.001
|
0.152**
|
0.013
|
2007
|
0.203***
|
0.004
|
0.255***
|
0.001
|
0.171**
|
0.011
|
2008
|
0.286***
|
0.000
|
0.317***
|
0.000
|
0.249***
|
0.001
|
2009
|
0.294***
|
0.000
|
0.321***
|
0.000
|
0.260***
|
0.001
|
2010
|
0.296***
|
0.000
|
0.317***
|
0.000
|
0.265***
|
0.001
|
2011
|
0.295***
|
0.000
|
0.304***
|
0.000
|
0.278***
|
0.001
|
2012
|
0.285***
|
0.000
|
0.294***
|
0.000
|
0.268***
|
0.001
|
2013
|
0.232***
|
0.001
|
0.245***
|
0.001
|
0.217***
|
0.002
|
2014
|
0.251***
|
0.001
|
0.257***
|
0.001
|
0.239***
|
0.001
|
2015
|
0.221***
|
0.003
|
0.225***
|
0.003
|
0.214***
|
0.003
|
2016
|
0.256***
|
0.001
|
0.257***
|
0.001
|
0.250***
|
0.001
|
2017
|
0.234***
|
0.002
|
0.257***
|
0.001
|
0.222***
|
0.003
|
Note: *, **, and *** represent passing significant level of 10%, 5%, and 1%, respectively
|
Table 8
The test of the spatial measurement model
Model
|
Test type
|
MCRP
|
FCRP
|
ECRP
|
Spatial error
|
Lagrange multiplier
|
197.168***
|
245.450***
|
183.139***
|
|
Robust lagrange multiplier
|
21.281***
|
34.657***
|
41.232***
|
Spatial lag
|
Lagrange multiplier
|
228.789***
|
288.402***
|
158.570***
|
|
Robust lagrange multiplier
|
52.902***
|
77.609***
|
16.663***
|
|
LR-SDM-SAR
|
42.280***
|
56.180***
|
37.400***
|
|
LR-SDM-SEM
|
49.380***
|
52.990***
|
48.830***
|
|
Hausman
|
12.260*
|
17.390***
|
20.220***
|
Note: *, **, and *** represent passing significant level of 10%, 5%, and 1%, respectively
|
Table 9
The spatial effect estimation results
Scenarios
|
|
MCRP
|
|
|
FCRP
|
|
|
ECRP
|
|
|
SDM
|
Direct effects
|
Indirect effects
|
SDM
|
Direct effects
|
Indirect effects
|
SDM
|
Direct effects
|
Indirect effects
|
|
(1)
|
(2)
|
(3)
|
(4)
|
(5)
|
(6)
|
(7)
|
(8)
|
(9)
|
GDP
|
0.164***
|
0.155***
|
-0.207***
|
0.219***
|
0.205***
|
-0.279***
|
0.110***
|
0.103***
|
-0.147*
|
|
(6.232)
|
(5.840)
|
(-2.638)
|
(9.015)
|
(8.276)
|
(-3.509)
|
(3.642)
|
(3.441)
|
(-1.741)
|
IND
|
-0.067***
|
-0.067***
|
-0.027***
|
-0.057***
|
-0.057***
|
-0.030***
|
-0.078***
|
-0.077***
|
-0.025**
|
|
(-7.292)
|
(-7.435)
|
(-2.582)
|
(-6.666)
|
(-6.779)
|
(-2.736)
|
(-7.394)
|
(-7.550)
|
(-2.340)
|
GREEN
|
0.001
|
0.002
|
0.020
|
-0.007*
|
-0.007*
|
0.006
|
0.009*
|
0.010**
|
0.034**
|
|
(0.246)
|
(0.479)
|
(1.607)
|
(-1.861)
|
(-1.730)
|
(0.474)
|
(1.955)
|
(2.214)
|
(2.444)
|
ES
|
0.120***
|
0.131***
|
0.277**
|
0.094***
|
0.111***
|
0.367***
|
0.145***
|
0.152***
|
0.197
|
|
(5.162)
|
(5.448)
|
(2.347)
|
(4.383)
|
(4.889)
|
(3.033)
|
(5.444)
|
(5.602)
|
(1.578)
|
EE
|
0.025***
|
0.026***
|
0.018*
|
0.020***
|
0.020***
|
0.009
|
0.030***
|
0.031***
|
0.026**
|
|
(9.640)
|
(9.782)
|
(1.669)
|
(8.278)
|
(8.207)
|
(0.834)
|
(10.196)
|
(10.458)
|
(2.246)
|
OPEN
|
-0.009
|
-0.008
|
0.024
|
-0.007
|
-0.005
|
0.041*
|
-0.011
|
-0.010
|
0.009
|
|
(-1.301)
|
(-1.073)
|
(1.023)
|
(-1.143)
|
(-0.756)
|
(1.741)
|
(-1.382)
|
(-1.258)
|
(0.363)
|
POP
|
-0.022
|
0.005
|
0.648***
|
0.013
|
0.044
|
0.654***
|
-0.055
|
-0.032
|
0.646***
|
|
(-0.586)
|
(0.133)
|
(6.378)
|
(0.385)
|
(1.237)
|
(6.389)
|
(-1.304)
|
(-0.732)
|
(5.929)
|
W_GREEN
|
0.015
|
|
|
0.007
|
|
|
0.025**
|
|
|
|
(1.534)
|
|
|
(0.768)
|
|
|
(2.157)
|
|
|
W_GDP
|
-0.205***
|
|
|
-0.270***
|
|
|
-0.148**
|
|
|
|
(-3.619)
|
|
|
(-5.188)
|
|
|
(-2.257)
|
|
|
W_ES
|
0.167**
|
|
|
0.213***
|
|
|
0.119
|
|
|
|
(1.992)
|
|
|
(2.735)
|
|
|
(1.241)
|
|
|
W_EE
|
0.006
|
|
|
-0.001
|
|
|
0.013
|
|
|
|
(0.733)
|
|
|
(-0.104)
|
|
|
(1.399)
|
|
|
W_OPEN
|
0.019
|
|
|
0.029**
|
|
|
0.008
|
|
|
|
(1.199)
|
|
|
(2.009)
|
|
|
(0.456)
|
|
|
W_POP
|
0.482***
|
|
|
0.436***
|
|
|
0.519***
|
|
|
|
(5.725)
|
|
|
(5.493)
|
|
|
(5.505)
|
|
|
|
0.290***
|
|
|
0.351***
|
|
|
0.239***
|
|
|
|
(4.110)
|
|
|
(5.018)
|
|
|
(3.352)
|
|
|
|
0.001***
|
|
|
0.001***
|
|
|
0.001***
|
|
|
|
(16.303)
|
|
|
(16.232)
|
|
|
(16.346)
|
|
|
wald
|
42.69***
|
|
|
54.84***
|
|
|
37.80***
|
|
|
|
(0.000)
|
|
|
(0.000)
|
|
|
(0.000)
|
|
|
Note: *, **, and *** represent passing significant level of 10%, 5%, and 1%, respectively
|