The optimal carbon tax mechanism for managing carbon emissions

Along Pigouvian lines, the carbon tax not only exceeds the carbon emission damage imposed on society, but ignores the potential cost from deliberate carbon abatement, which in turn challenges the stability and optimality of the Pigouvian solution. For correcting these distortions, this paper amends the standard Pigouvian version by using piecewise tax functions to approximate the social damage curve of carbon emissions. An optimal carbon tax mechanism is designed, where the tax is endogenously determined from social welfare maximization. With the help of a modification instrument, the carbon tax corrects emitters’ non-optimal individual decision and the social optimum is implemented efficiently. How to put the carbon tax into practice is examined under both the deterministic and stochastic modeling settings. In both cases, we demonstrate the structure and effectiveness of the carbon tax in detail. Moreover, a flexible adjustment tax scheme is proposed, which may produce the double-dividend effect that reduces carbon emissions and relieves financial burden of carbon abatement simultaneously. These may improve the application of market-based carbon-reducing tools in public management and pollution regulation.     

环境规制对碳效率的多重路径及门槛模型研究

从结构升级及效率提升两大维度刻画环境规制对碳排放效率的关系及作用机制，研究环境规制是如何提升城市碳排放效率的。基于2006—2019年中国279个城市层面数据，采用非参数百分位自抽法，逐步回归法、Sobel检验和交互调节模型验证影响路径，并利用门槛模型探讨不同路径下环境规制的调节作用。结果表明：(1)环境规制促进城市碳排放效率提升，但存在区域异质性；(2)环境规制通过促进产业结构高度化、绿色技术创新和能源效率升级提高碳排放效率，产业结构合理化及产业集聚“遮掩”了环境规制的激励作用；(3)环境规制对提升碳排放效率存在多种门槛效应和调节机制。发挥环境规制对碳排放效率结构和效率的双重激励时，需注意不同路径的维度问题，以提高准度，把握力度。     

Effects of scenario-based carbon pricing policies on China's dual climate change mitigation goals: Does policy design matter?

Although the carbon pricing policy is a critical driving factor that will help China achieve economic growth, energy transition, and dual climate change mitigation goals, the kind of carbon pricing policy that will complement the country's current development situation remains controversial. We apply the World Induced Technical Change Hybrid (WITCH) model to explore the heterogeneity and synergy of different carbon pricing policies, and the results indicate that it will be challenging to achieve carbon neutrality before 2060. The study find that the combined policy —a mix of carbon tax and carbon market policies — has the optimal emission reduction effect but comes with the highest economic cost, proving to be unsuitable in the long run. The carbon tax policy is an important transitional means to assist in emission reduction, which can serve as an important supplement to carbon market policy and be phased out after the market mechanism matures.     

Fertility and climate change*

A quarter of the total increase in emissions is attributable to the growth of emissions per capita, whereas three-quarters are due to population growth. This evidence notwithstanding, demography in climate–economy models typically follows exogenous trends. We develop a climate–economy integrated model with endogenous fertility through a quality–quantity trade-off. The decentralization of the social optimum requires two complementary instruments: a carbon pricing policy and family planning interventions. Global population increases and reaches a peak, depending on the scenario, between 11.6 billion in the social optimum and 14.6 billion if only carbon prices are implemented. Fertility costs (i.e., the net present value of the climate-related costs per child) are in 2020 estimated to be about 22,000 euros in the “social optimum” scenario, and about 88,000 euros in the “second-best with fertility taxes” scenario. Carbon pricing tends to have a rebound effect as it increases population growth leading to higher future emissions. Our results highlight the effects of fertility choices and global population on climate change, quantifying the cost of neglecting the interaction.     

The price of carbon risk: Evidence from China’s bond market

Using a 2009–2019 sample of Chinese bond issuers, we examine the effect of carbon risk on bond financing costs. Relative to low carbon risk issuers, high carbon risk issuers have substantially larger bond credit spreads, mainly because their credit risk is greater and they invest the funds in non-green projects. This positive relationship is more pronounced for issuers with financing constraints, those not making a green transition and those in cities with stringent environmental regulations. We find a reversed effect during the COVID-19 pandemic. However, China’s carbon peak and carbon neutral goals have renewed the focus on carbon risk. Carbon risk also causes bond issuers to scale back production and negatively affects their likelihood of receiving long-term financial support. Our findings suggest that investors consider carbon risk and charge a corresponding risk premium.     

行业视角下减排成本估算及减排路径研究

碳达峰碳中和是中国经济发展环境治理的战略目标,减排成本与减排路径是该战略实施中两大现实问题。基于行业视角,利用投入产出方法,对行业减排成本、技术减排效应及减排路径展开研究,基本结论如下：①行业减排成本差异大,整体减排成本逐年上升。在三个代表性年份行业最高与最低减排成本相差40-60倍,减排成本绝对差值在1500-3000$/t。在2000-2010年间, 32个行业减排成本均有不同程度的上升, 全社会整体减排成本上升了56.98%。②技术进步的减排贡献较大,部分行业技术减排有限。在产出固定假设下,2000-2010年技术进步实现累计减排57.09亿t,累计技术减排率达到47.88%；但在旅游、住宿餐饮等行业技术减排率为负,技术因素导致的排放不减反增。③行业减排路径应遵循从高碳到低碳的顺序。基于减排成本与技术减排两大因素的减排路径规划显示,优先和重点减排行业主要集中在能源生产供给、加工制造、交通运输、采矿及设备制造等高能耗高排放行业；可相对延后和非重点减排行业主要为食品烟草等传统加工制造业以及金融、房地产等现代服务业。     

人工智能技术对碳排放的影响

随着新一轮科技革命和产业变革的深入推进，人工智能技术在应对气候变化方面扮演重要角色，并赋能“碳达峰、碳中和”目标的实现。利用2006—2019年中国内地省级面板数据，考察人工智能技术对碳排放的影响。研究发现：人工智能技术与碳排放之间呈倒U型关系，即当人工智能技术达到一定阈值后，其碳减排效应逐渐凸显；人工智能技术主要通过提高能源利用效率实现碳减排；在东部和西部地区，人工智能技术与碳排放之间存在显著倒U型关系，而在中部地区，人工智能技术对碳排放发挥持续促进作用。因此，在推进“双碳”目标过程中，需要以绿色低碳发展为目标开发人工智能技术，正确引导人工智能在碳减排领域的研发应用，针对不同区域实际制定差异化发展政策。     

Dynamic and asymmetric effects between carbon emission trading,financial uncertainties,and Chinese industry stocks: Evidence from quantile-on-quantile and causality-in-quantiles analysis

This paper investigates the dynamic and asymmetric effects between carbon emission trading (CET), financial uncertainties, and Chinese stocks in different industries over the period from 19th December 2013 to 21st March 2022. We utilized a novel quantile framework including rolling window quantile regression method, quantile-on-quantile method, and causality-in-quantiles method to implement this research more comprehensively and accurately. Our contributions and findings, empirical in nature, are as follows: (i) In the early establishing stage of the carbon market, with a bullish market situation, carbon emission trading has a negative impact on most industry stocks. In the developing and improving stage of the carbon market, different industries have different impact situations. (ii) We find that the effects of financial uncertainty on stocks are stronger than CET on stocks. We also find that the dependence structures between CET, financial uncertainty, and industry stocks are asymmetric in most industries, and there are many mutation structures with significant risks in extreme situations. (iii) Carbon emissions trading, crude oil volatility, and US stock volatility all have strong causal relationships with Chinese industry stocks. (iv) We also provide policy suggestions to relevant countries to balance carbon market and stock markets and avoid risks from financial uncertainty in different industries.     

城市创新能否助力低碳经济发展——创新型城市试点政策对碳强度的影响评估及机制分析

创新是城市发展的力量之源，低碳是城市发展的必由之路。将创新型城市试点作为一项准自然实验，利用2005—2018年全国275个城市面板数据，采用多期双重差分方法，评估创新型城市试点对降低碳强度的政策效应及作用机制。研究发现：第一，创新型城市试点政策能够在降低碳强度的基础上推动低碳经济发展，各类试点政策的推动效果依次为碳排放权交易政策>创新型城市政策>智慧城市政策>低碳城市政策>环境保护重点监控政策；第二，创新型城市试点政策可以通过规模经济效应、技术进步效应与结构转型效应3条路径助力低碳经济发展；第三，城市特质会影响创新型城市试点政策效应发挥，创新型城市试点政策对碳强度的抑制效果呈现由东到西递增的地理空间差序格局、由高到低递减的城市等级差序格局，在人口规模与抑制效果之间呈现倒U型作用，并且资源型城市的抑制效果显著大于非资源型城市。     

Why is Japan’s carbon emissions from road transportation declining?

Average fuel efficiency of vehicles improved substantially over the last three decades in Japan. Yet, the carbon emissions from on-road passenger vehicles continued to increase until 2000, and then turned to a steadily declining trend. We empirically investigate this disparity. To that end, we apply an analogue of the Copeland-Taylor decomposition, combined with an empirically estimated behavioral model of car ownership and utilization choice, to economically decompose vehicle carbon emissions into the scale, composition, and technique effects over our study period, 1990–2015. We find that exogenous demographic changes such as population size, driver’s license holdings, or labor migration across regions can only explain this disparity partially. After accounting for endogenous changes in household’s geographically-explicit transport demand by the estimated behavioral model, the predicted emissions match the time path of the observed emissions surprisingly well. Of all the factors in the behavioral model, the fuel cost per unit of driving accounts for the largest share of the total variation in the observed emissions. Our result indicates that 60% of the technique effect is offset by the perverse effect of induced transport demand due to the lower fuel cost. Importantly, the induced demand comes from both the intensive margin (driving) and the extensive margin (car ownership).