Long-term impacts of carbon allowance allocation in China: An IC-DCGE model optimized by the hypothesis of imperfectly competitive market

Qunli Wu, Zhe Ma and Fanxing Meng

Energy, 2022, vol. 241, issue C

Abstract: This study presents the construction of a 14-sector, recursive dynamic CGE model and introduces the hypothesis of imperfect competition as the model's improvement. The novel CGE model (IC-DCGE), which is calibrated with the 2017 social accounting matrix, is used to examine the impact mechanism of free-quota ratios on the economy–energy–environment system. Five simulation scenarios are designed with different free-quota ratios and one BAU scenario as a benchmark. The conclusions drawn from this study are as follows: (i) GDP loss due to the ETS policy is typically underestimated in previous studies using the traditional CGE model with a hypothesis of the perfectly competitive market, and the loss could be alleviated with a high free-quota ratio. (ii) Changes in outputs and commodity prices of the ETS-covered industries are more apparent than those of the remaining industries, and the most conspicuous change occurs in the power industry. (iii) Less free-quota ratios would yield better performance in CO2 mitigation and the optimization of energy structure. Overall, this study suggests that China set a high initial free-quota ratio and gradually decrease it to attain the emission reduction target while decreasing economic losses.

Keywords: Imperfect competition; Dynamic computable general equilibrium (DCGE) model; ETS; Energy consumption; CO2 reduction (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S036054422103156X
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:241:y:2022:i:c:s036054422103156x

DOI: 10.1016/j.energy.2021.122907

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().