The influence of different allowance allocation methods on China's economic and sectoral development

Abstract

China launched its national carbon emissions trading scheme (ETS) in 2017. The choice of allowance allocation methods can strongly influence the political acceptance of an ETS by enterprises/sectors that are covered by it. This article builds a computable general equilibrium model to conduct a quantitative analysis of the effects of nine common allowance allocation methods on both the macro-economy and the industries covered by the ETS. The results of the model show that national gross domestic product (GDP) decreases by 0.37-0.44% during the 13th Five-Year Plan period against a backdrop of a 2% annual reduction in carbon emissions from the sectors covered by the ETS compared with the business-as-usual scenario. China's total emissions drop by 1.71-1.76%. When auctioning and allocation approaches without ex-post adjustment are used, the allowance price is 40-45 yuan/tCO 2. When the dynamic allocation methods are used, the allowance price increases to 70-75 yuan/tCO 2. Auctioning and allocation approaches without ex-post adjustment exert the same influence on macroscopic indicators (such as GDP and total emissions) and industry indicators (such as output and price). The dynamic allocation methods have a subsidy effect, which can significantly reduce the effect of the ETS on GDP and industry output while significantly increasing the allowance price and decreasing the economic efficiency of the ETS. The cement and steel industries are the most sensitive to the output subsidy effect of the dynamic allocation methods. This article suggests a limit on the use of dynamic allocation approaches to avoid excessively high allowance prices and excessive subsidies for overcapacity industries. Key policy insights. Auctioning and one-off allocation purely based on historical data are most economically efficient; dynamic allocation based on updated or actual output data could reduce the impact of the ETS on enterprises' output, but will increase the allowance price and thus reduce the economic efficiency of the ETS.. Implementing a national ETS will have limited impact on China's GDP, but could promote emissions abatement of the whole economy in an efficient way.. Different allocation methods have almost the same impact on GDP, but the impacts on different sectors are significantly different.

Low-carbon innovation induced by emissions trading in China

“…Its efficiency also helps to link national and regional programs for global mitigation efficiency 2 . In comparison, rate-based allocation subsidizes output by allowing additional emissions and compromises cost-effectiveness 34,35 , which is exacerbated with heterogeneous benchmarks 36 . The innovation impact from the two methods, however, is likely ambiguous 6,33 .…”

Research on the Impact of Output Adjustment Strategy and Carbon Trading Policy on the Response, Stability and Complexity of Steel Market under the Dynamic Game

“…In terms of mechanism and carbon quota design, Zhu et al [18] studied the carbon quota allocation of China's petrochemical, chemical, cement, steel, nonferrous metals, and power industries in 2030. Pang et al [19] conducted a quantitative analysis on the impact of nine common carbon quota allocation methods on China's macro-economy and industries covered by ETS policies. Zhang et al [20] used the carbon trading theory, carbon audit theory, and driving force state response (DSR) model for reference to build a carbon audit evaluation index system, and analyzed the application of this system in China's steel enterprises.…”

“…Yamazaki [7] CGE model Zhu et al [9] Partial equilibrium model Liu et al [12] Partial equilibrium model Dai et al [13] CGE model Lin et al [15] Partial equilibrium model Pang et al [19] CGE model Zhu et al [25] CGE model Wang et al [26] CGE model Wu et al [27] CGE model…”

Designing China’s national carbon emissions trading system in a transitional period

“…Developing allocation methods under the national system requires consideration not only of general issues such as economic efficiency and competitiveness concerns, but also of China's special situation, such as the significant uncertainties surrounding its economic and industrial development, and heavy regulation of the electricity and heat generation sector (Wang, Teng, Zhou, & Cai, 2017). The article by Pang et al (2018) builds a recursive dynamic general equilibrium model in an open economic environment to assess quantitatively the effects of nine allocation methods which have been adopted in existing systems. The results show that the ETS policy will have very limited impact on China's GDP, auctioning and allocation approaches without ex-post adjustment having the same impacts on GDP, and the use of dynamic allocation methods, although preferred by many, should be limited due to their subsidy effects on output or on both output and emissions, and thus their negative impacts on the effectiveness of the system.…”

“…Divergent allocation approaches have been utilized in China's ETS pilot systems because of different considerations, including enhancing short-term political acceptance and coordinating with relevant industrial policies, but in the national system, the selection of allocation approaches will also need to assist the system's transition to a fixed emissions cap in the foreseeable future, possibly well before 2030. The article by Pang, Zhou, Deng and Duan (2018) analyses the influence of nine allocation methods on China's macro-economy, the covered industries, price of allowances and effectiveness of the system. Similar to the practice in the pilot systems (Pang & Duan, 2016), the emissions cap of China's national system will not be a predetermined fixed one and will to a large extent be determined by the allocation approaches, given China's carbon intensity mitigation targets up to 2030 which the national system is designed to achieve.…”