Pushing carbon footprint reduction along environment with carbon-reducing information asymmetry

信息不对称 碳足迹 比较静力学 私人信息检索 背景(考古学) 碳纤维 业务 政府(语言学) 利润(经济学) 产业组织 微观经济学 经济 环境经济学 计算机科学 温室气体 哲学 复合数 生物 古生物学 语言学 计算机安全 生态学 算法
作者
Jing Xia,Wenju Niu
出处
期刊:Journal of Cleaner Production [Elsevier BV]
卷期号:249: 119376-119376 被引量:27
标识
DOI:10.1016/j.jclepro.2019.119376
摘要

Pushing carbon footprint reduction (CFR) by means of carbon regulation has received increasing attention. However, extant research primarily focuses on the design of carbon regulation under complete information, neither the feature of carbon regulation under asymmetric information nor the role of private information in the government-firm relationship has been explored. In this paper, we investigate the issue of government-firm contracting for CFR in the context of carbon-reducing information asymmetry. Two cases are considered: The single asymmetric information case where the firm’s carbon-reducing effort is privately known to himself, and the dual asymmetric information case in which neither the firm’s carbon-reducing capacity nor his effort is visible to the government. Carbon contracting model in each case is developed by mechanism design and game theory. To examine the effectiveness of these carbon contracts, the benchmark with complete information is further studied. Comparative statics and sensitive analysis show that the carbon contracts under information asymmetry can efficiently motivate the firm to reduce carbon footprint. In particular, under single asymmetric information, the government appropriately adjusts the optimal contractual configurations to maximize the expected welfare, leaving the firm to get the reservation profit. Under dual asymmetric information, the government’s best choice is to offer a menu of carbon contracts which enables the firm to obtain extra information rent that is increasing in his carbon-reducing capacity. We explicitly identify conditions under which the screening mechanism works and reveal that the menu of carbon contracts not only induces the firm to reveal his true carbon-reducing capacity but also motivates him to make the best effort to reduce carbon footprint. Our findings provide the government with a theoretical basis regarding carbon regulation under information asymmetry, as well as help firms make appropriate selections when signing low-carbon contracts with the government.

科研通智能强力驱动
Strongly Powered by AbleSci AI
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
王金金发布了新的文献求助10
1秒前
大笨笨完成签到,获得积分0
2秒前
Ezio_sunhao完成签到,获得积分10
4秒前
5秒前
Xiaofei完成签到,获得积分10
5秒前
Jasper应助科研采纳,获得10
6秒前
简单妖妖发布了新的文献求助10
6秒前
时舒完成签到 ,获得积分10
8秒前
8秒前
junkai发布了新的文献求助10
9秒前
汉堡包应助张慢慢采纳,获得30
9秒前
10秒前
研友_ZzaKqn完成签到,获得积分0
11秒前
帅气之双完成签到 ,获得积分10
11秒前
soelo发布了新的文献求助10
12秒前
满意的伊发布了新的文献求助10
12秒前
LIN96T完成签到 ,获得积分10
13秒前
14秒前
义力古玛发布了新的文献求助10
14秒前
卜君浩发布了新的文献求助10
17秒前
感动惜珊发布了新的文献求助10
18秒前
18秒前
biiii完成签到,获得积分10
18秒前
18秒前
科研通AI6.3应助xszhang采纳,获得10
19秒前
潇洒的血茗完成签到 ,获得积分10
19秒前
Anthony完成签到,获得积分10
20秒前
先字母完成签到,获得积分10
21秒前
小满xiaoman完成签到,获得积分10
24秒前
幸福的糖豆apple完成签到,获得积分10
24秒前
qdong发布了新的文献求助10
25秒前
QXS完成签到 ,获得积分10
26秒前
281911480完成签到,获得积分10
26秒前
victory_liu完成签到,获得积分10
28秒前
29秒前
panchaoteng发布了新的文献求助10
29秒前
小爱完成签到,获得积分10
31秒前
浮尘完成签到 ,获得积分0
31秒前
神奇五子棋完成签到 ,获得积分10
32秒前
33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
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Picture this! Including first nations fiction picture books in school library collections 1500
Signals, Systems, and Signal Processing 610
Unlocking Chemical Thinking: Reimagining Chemistry Teaching and Learning 555
Photodetectors: From Ultraviolet to Infrared 500
Cancer Targets: Novel Therapies and Emerging Research Directions (Part 1) 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6359264
求助须知:如何正确求助?哪些是违规求助? 8173237
关于积分的说明 17213576
捐赠科研通 5414355
什么是DOI,文献DOI怎么找? 2865433
邀请新用户注册赠送积分活动 1842799
关于科研通互助平台的介绍 1690962