资源科学 ›› 2018, Vol. 40 ›› Issue (10): 2118-2131.doi: 10.18402/resci.2018.10.19
收稿日期:
2017-11-07
修回日期:
2018-06-13
出版日期:
2018-10-25
发布日期:
2018-10-20
作者简介:
作者简介:王倩,女,吉林辽源人,教授,博士生导师,主要研究方向为碳金融。E-mail:
基金资助:
Received:
2017-11-07
Revised:
2018-06-13
Online:
2018-10-25
Published:
2018-10-20
摘要:
当各地区减排成本增速高于经济增速时,单一碳排放效率指标已无法完整刻画减排情况。本文基于全局非径向方向性距离函数(Global NDDF)及其对偶原理测算得出2010—2015年中国全要素碳排放效率总体呈上升趋势,其中东部地区效率最高,而东北与西部地区效率最低;全国各地区总的碳减排成本增长率与经济增速比值呈波动上升趋势,且大部分地区总减排成本增速大于经济增速。这表明碳排放效率提升是以高于经济增速的减排成本投入实现的。数理推导结论表明,解决减排成本增速远超GDP增速的困境,需满足碳影子价格增速小于碳生产率增速。计量模型进一步证明,中国碳影子价格增长速度高于碳生产率增速导致了减排成本增速快于经济增速的困境。为解决这一问题,应以多元指标体系替代单一的碳排放效率指标,全面衡量减排能力;构建全国碳交易市场以缓解各地区碳影子价格异质性现象;持续推动结构性改革和产业结构转型升级,提高能源利用效率。
王倩, 高翠云. 中国省际碳影子价格与碳生产率非线性关联研究[J]. 资源科学, 2018, 40(10): 2118-2131.
Qian WANG, Cuiyun GAO. Research on the nonlinear correlation between provincial carbon shadow price and carbon productivity[J]. Resources Science, 2018, 40(10): 2118-2131.
表1
2010—2015年中国省际投入产出变量的描述性统计"
变量/单位 | 均值 | 标准差 | 中位数 | 最大值 | 最小值 |
---|---|---|---|---|---|
资本/亿元 | 10 906.66 | 9 503.04 | 7 911.50 | 52 981.52 | 638.33 |
劳动/万人 | 2 679.91 | 1 751.10 | 2 165.80 | 6 636.08 | 307.65 |
能源/万t | 14 294.48 | 8 509.10 | 11 361.06 | 39 969.77 | 1 390.24 |
GDP/亿元 | 4 362.28 | 3 641.85 | 3 248.42 | 17 818.91 | 232.37 |
CO2/万t | 33 121.28 | 21 659.93 | 25 409.91 | 90 366.86 | 2 724.91 |
表3
2011—2015年中国省际碳排放效率"
地区 | 2011年 | 2012年 | 2013年 | 2014年 | 2015年 |
---|---|---|---|---|---|
北京 | 0.714 | 0.754 | 0.795 | 0.858 | 1.000 |
天津 | 0.428 | 0.450 | 0.462 | 0.507 | 0.580 |
河北 | 0.174 | 0.188 | 0.178 | 0.198 | 0.212 |
山西 | 0.116 | 0.121 | 0.120 | 0.129 | 0.149 |
内蒙古 | 0.107 | 0.112 | 0.129 | 0.137 | 0.154 |
辽宁 | 0.311 | 0.285 | 0.280 | 0.292 | 0.313 |
吉林 | 0.221 | 0.251 | 0.274 | 0.296 | 0.348 |
黑龙江 | 0.463 | 0.434 | 0.426 | 0.369 | 0.335 |
上海 | 0.742 | 0.822 | 0.742 | 1.000 | 1.000 |
江苏 | 0.485 | 0.516 | 0.504 | 0.548 | 0.603 |
浙江 | 0.449 | 0.465 | 0.504 | 0.545 | 0.595 |
安徽 | 0.646 | 0.587 | 0.534 | 0.549 | 0.590 |
福建 | 0.646 | 0.703 | 0.703 | 0.679 | 0.738 |
江西 | 0.367 | 0.412 | 0.353 | 0.379 | 0.403 |
山东 | 0.281 | 0.301 | 0.347 | 0.365 | 0.398 |
河南 | 0.247 | 0.284 | 0.322 | 0.341 | 0.405 |
湖北 | 0.272 | 0.313 | 0.390 | 0.422 | 0.504 |
湖南 | 0.549 | 0.575 | 0.611 | 0.640 | 0.637 |
广东 | 0.569 | 0.626 | 0.671 | 0.722 | 0.795 |
广西 | 0.250 | 0.264 | 0.277 | 0.305 | 0.360 |
海南 | 1.000 | 0.840 | 0.685 | 0.638 | 0.707 |
重庆 | 0.488 | 0.538 | 0.636 | 0.638 | 0.685 |
四川 | 0.826 | 0.822 | 0.821 | 0.885 | 1.000 |
贵州 | 0.127 | 0.134 | 0.146 | 0.169 | 0.212 |
云南 | 0.197 | 0.206 | 0.229 | 0.278 | 0.369 |
陕西 | 0.289 | 0.296 | 0.297 | 0.313 | 0.377 |
甘肃 | 0.234 | 0.246 | 0.251 | 0.270 | 0.316 |
青海 | 0.173 | 0.173 | 0.166 | 0.177 | 0.196 |
宁夏 | 0.079 | 0.062 | 0.059 | 0.061 | 0.073 |
新疆 | 0.116 | 0.106 | 0.099 | 0.098 | 0.101 |
全国均值 | 0.386 | 0.396 | 0.400 | 0.427 | 0.472 |
东部均值 | 0.549 | 0.567 | 0.559 | 0.606 | 0.663 |
中部均值 | 0.366 | 0.382 | 0.388 | 0.410 | 0.448 |
西部均值 | 0.262 | 0.269 | 0.283 | 0.303 | 0.349 |
东北均值 | 0.332 | 0.323 | 0.327 | 0.319 | 0.332 |
表4
2011—2015年中国省际减排成本增速与经济增速的比值"
地区 | 2011年 | 2012年 | 2013年 | 2014年 | 2015年 |
---|---|---|---|---|---|
北京 | 3.462 | 1.773 | 1.754 | 2.167 | 3.570 |
天津 | 0.324 | 1.431 | 1.242 | 2.075 | 2.678 |
河北 | 1.242 | 1.924 | 0.297 | 2.795 | 2.131 |
山西 | 1.476 | 1.463 | 0.885 | 2.608 | 6.063 |
内蒙古 | -0.016 | 1.472 | 2.815 | 1.844 | 2.808 |
辽宁 | 1.044 | 0.055 | 0.779 | 1.797 | 3.363 |
吉林 | 0.861 | 2.246 | 2.184 | 2.333 | 3.976 |
黑龙江 | 0.616 | 0.323 | 0.735 | -1.522 | -0.693 |
上海 | 1.801 | 2.544 | -0.370 | 6.326 | 1.000 |
江苏 | 1.303 | 1.699 | 0.738 | 2.089 | 2.287 |
浙江 | 0.632 | 1.483 | 2.090 | 2.168 | 2.232 |
安徽 | 1.383 | 0.150 | 0.040 | 1.352 | 1.932 |
福建 | 0.085 | 1.852 | 1.000 | 0.632 | 2.039 |
江西 | 1.263 | 2.243 | -0.563 | 1.848 | 1.738 |
山东 | 1.633 | 1.779 | 2.763 | 1.655 | 2.200 |
河南 | 1.594 | 2.655 | 2.638 | 1.723 | 3.450 |
湖北 | 0.212 | 2.481 | 3.673 | 1.939 | 3.380 |
湖南 | 0.690 | 1.451 | 1.692 | 1.536 | 0.946 |
广东 | -0.172 | 2.319 | 1.923 | 2.035 | 2.373 |
广西 | 1.042 | 1.548 | 1.535 | 2.281 | 3.392 |
海南 | 1.000 | -0.918 | -1.050 | 0.126 | 2.487 |
重庆 | 0.558 | 1.853 | 2.657 | 1.031 | 1.745 |
四川 | 1.951 | 0.956 | 0.995 | 1.998 | 2.769 |
贵州 | -2.471 | 1.415 | 1.847 | 2.618 | 3.569 |
云南 | 1.679 | 1.382 | 2.019 | 3.881 | 5.075 |
陕西 | 2.674 | 1.210 | 1.037 | 1.599 | 3.806 |
甘肃 | 1.351 | 1.444 | 1.244 | 1.898 | 3.272 |
青海 | 0.349 | 0.991 | 0.582 | 1.783 | 2.413 |
宁夏 | -1.387 | -1.082 | 0.485 | 1.495 | 3.557 |
新疆 | 0.255 | 0.222 | 0.367 | 0.845 | 1.396 |
全国均值 | 0.881 | 1.346 | 1.268 | 1.899 | 2.698 |
东部均值 | 1.131 | 1.589 | 1.039 | 2.207 | 2.300 |
中部均值 | 1.103 | 1.741 | 1.394 | 1.834 | 2.918 |
西部均值 | 0.544 | 1.037 | 1.417 | 1.934 | 3.073 |
东北均值 | 0.840 | 0.875 | 1.232 | 0.869 | 2.215 |
表5
碳影子价格对碳生产率的回归结果"
变量 | 模型1 | 模型2 | 模型3 | 模型4 | 模型5 |
---|---|---|---|---|---|
CP | 0.021 | 0.047 | 0.121** | 0.150*** | 0.138** |
(0.59) | (1.20) | (2.28) | (2.79) | (2.57) | |
(CP)2 | 1.243*** | 1.220*** | 1.084*** | 1.039*** | 1.077*** |
(15.89) | (15.42) | (10.89) | (10.39) | (10.72) | |
IS | 0.021 | ||||
(1.64) | |||||
URB | -0.053** | -0.064*** | -0.038 | ||
(-2.52) | (-3.00) | (-1.56) | |||
EPI | 0.002** | 0.002*** | |||
(2.31) | (2.61) | ||||
ELE | -0.092** | ||||
(-2.09) | |||||
Cons | 0.003 | -0.010 | 0.022*** | 0.023*** | 0.020** |
(0.90) | (-1.18) | (2.68) | (2.79) | (2.45) | |
R2 | 0.928 | 0.929 | 0.931 | 0.933 | 0.935 |
F值 | 948.660 | 640.520 | 657.380 | 508.940 | 417.430 |
Prob>F | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
表6
碳影子价格对碳生产率的稳健性检验"
变量 | 模型1 | 模型2 | 模型3 | 模型4 |
---|---|---|---|---|
CP | 0.119*** | 0.198*** | ||
(5.38) | (2.92) | |||
(CP)^2 | 1.054*** | 0.940*** | ||
(17.10) | (8.42) | |||
lnCP | 2.148*** | 2.053*** | ||
(64.77) | (80.27) | |||
IS | -0.002 | -0.016 | ||
(-0.27) | (-0.96) | |||
lnIS | 0.127 | 0.006 | ||
(0.72) | (0.12) | |||
URB | -0.020*** | -0.039*** | ||
(-4.48) | (-4.08) | |||
lnURB | -0.293*** | -0.140** | ||
(-4.62) | (-2.40) | |||
EPI | 0.001* | 0.001*** | ||
(1.86) | (2.58) | |||
lnEPI | 0.112** | -0.010 | ||
(2.08) | (-0.42) | |||
ELE | -0.047*** | -0.077 | ||
(-3.85) | (-1.60) | |||
lnELE | -0.290*** | -0.108*** | ||
(-4.71) | (-3.86) | |||
cons | 0.008** | 0.023* | -0.021 | 0.096 |
(2.06) | (1.67) | (-0.14) | (1.20) | |
Waldchi2 | 7 304.110 | 31 410.210 | 21 133.230 | 36 578.530 |
Prob>chi2 | 0.000 | 0.000 | 0.000 | 0.000 |
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