Are Chinese provincial carbon emissions allowances misallocated over 2000–2017? Evidence from an extended Gini-coefficient approach

索引(排版) 经济 失真(音乐) 中国 基尼系数 温室气体 北京 泰尔指数 不平等 数学 地理 万维网 经济不平等 放大器 考古 生态学 数学分析 工程类 生物 CMOS芯片 计算机科学 电子工程
作者
Weijun He,Di Liu,Cheng Wang
出处
期刊:Sustainable Production and Consumption [Elsevier]
卷期号:29: 564-573 被引量:12
标识
DOI:10.1016/j.spc.2021.11.007
摘要

Carbon emission allowances (CEAs) are critical to regional economic growth against the background of tackling global climate change, and CEA misallocation may be detrimental to productivity and carbon emission performance. However, whether Chinese provincial CEAs are misallocated over the past decades has not yet been thoroughly investigated. For this purpose, this study first defines CEA misallocation based on the concept of provincial CEA marginal outputs; then we develop a distortion index to measure CEA misallocation by extending the conventional Gini coefficient method. Finally, an empirical analysis of Chinese provincial CEA misallocation throughout 2000–2017 is presented. The results indicate the existence of Chinese provincial CEA misallocation, as the distortion index increases from 0.229 to 0.279 over 2000–2017, implying that Chinese provincial CEA misallocation is aggravated. At the regional level, we find that the CEA misallocation of the western area is relatively the most serious, while that of the central area is not obvious. The CEA misallocation in the western area aggravates the CEA misallocation of the entire nation. We further discuss how to alleviate CEA misallocation by investigating the distortion index in different carbon emission reduction scenarios. We find that the distortion index of 2017 can be reduced to 0.272 compared with 0.279 in the actual scenario if the provinces with CEA marginal outputs lower than the national level reduce their emissions by 3%. The results indicate that controlling the emissions of the provinces with lower CEA marginal outputs may be an effective way to alleviate CEA misallocation.

科研通智能强力驱动
Strongly Powered by AbleSci AI

祝大家在新的一年里科研腾飞
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
Nagi参上完成签到,获得积分10
刚刚
刚刚
Yiy完成签到 ,获得积分0
3秒前
3秒前
5秒前
khan发布了新的文献求助10
5秒前
sky发布了新的文献求助10
5秒前
Zookie完成签到,获得积分10
10秒前
12秒前
xiayil完成签到,获得积分10
12秒前
今后应助sky采纳,获得10
12秒前
天天快乐应助123采纳,获得10
14秒前
研友_VZG7GZ应助HU采纳,获得10
14秒前
脑洞疼应助xx采纳,获得10
18秒前
小情绪完成签到 ,获得积分10
18秒前
lei完成签到,获得积分20
19秒前
丑小鸭发布了新的文献求助30
19秒前
Mic完成签到,获得积分0
20秒前
23秒前
李爱国应助糊涂的小天鹅采纳,获得10
24秒前
25秒前
ling_lz完成签到,获得积分10
26秒前
WW发布了新的文献求助10
27秒前
科研通AI6.2应助biiii采纳,获得10
29秒前
她说肚子是吃大的i完成签到,获得积分10
30秒前
123发布了新的文献求助10
30秒前
31秒前
34秒前
左云山完成签到,获得积分10
35秒前
36秒前
星辰大海应助123采纳,获得10
36秒前
关尔匕禾页完成签到,获得积分10
37秒前
38秒前
科研通AI6.1应助a1313采纳,获得10
38秒前
39秒前
腼腆的溪流完成签到,获得积分10
41秒前
DHW1703701完成签到,获得积分10
42秒前
菠萝发布了新的文献求助30
42秒前
gaomeigeng发布了新的文献求助10
43秒前
Owen应助花花采纳,获得10
43秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Les Mantodea de guyane 2500
Signals, Systems, and Signal Processing 510
Discrete-Time Signals and Systems 510
《The Emergency Nursing High-Yield Guide》 (或简称为 Emergency Nursing High-Yield Essentials) 500
The Dance of Butch/Femme: The Complementarity and Autonomy of Lesbian Gender Identity 500
Differentiation Between Social Groups: Studies in the Social Psychology of Intergroup Relations 350
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5884481
求助须知:如何正确求助?哪些是违规求助? 6611303
关于积分的说明 15700130
捐赠科研通 5005114
什么是DOI,文献DOI怎么找? 2696414
邀请新用户注册赠送积分活动 1639880
关于科研通互助平台的介绍 1594878