文献类型：期刊文献

英文题名：Carbon price prediction under output uncertainty

作者：Liu, Na[1];Song, Futie[1]

机构：[1]East China Univ Sci & Technol, Business Sch, Shanghai 200237, Peoples R China

年份：2022

卷号：29

期号：15

起止页码：21577

外文期刊名：ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH

收录：;EI(收录号：20242616391034);WOS:【SSCI(收录号:WOS:000717429100008)，SCI-EXPANDED(收录号:WOS:000717429100008)】；

基金：This research was funded by the National Natural Science Foundation of China (grant number 71371073).

语种：英文

外文关键词：Output growth uncertainty; EZ climate model; Carbon price; Marginal abatement cost; Population growth rate; Per capita output growth rate

摘要：Output growth uncertainty is a key issue in climate economics, involving the full range of impacts from emissions, through temperature changes to economic damage. The current study introduces output growth uncertainty into the EZ climate model, in which the predicted global carbon emissions under output growth uncertainty are used as weighted input. The objective of the present study is to calculate the future carbon prices represented by marginal abatement cost (MAC), to maximize social welfare. Moreover, the sensitivity of the two output growth uncertainty parameters, namely population growth rate and per capita output growth rate, is analyzed. Lastly, the significance and influence of output uncertainty for carbon price are also discussed. The results exhibit that (1) the optimal prices of per ton CO(2)e emission permits in the years 2020, 2030, 2060, 2080, and 2095 are $294.9, $285.3, $238.0, $143.3, and $15.4, respectively. (2) Population growth rate and per capita output growth rate both positively increase the future carbon prices, while the per capita output growth rate has a greater effect. (3) Compared with the performance under output certainty, carbon prices are estimated to be lower with output uncertainty; the high degree of uncertainty about carbon price is also primarily due to the high degree of output uncertainty. These results highlight the importance of research on output growth uncertainty, thus underpinning the EZ climate model for reducing carbon price and improving policymaking.