EXPLORING THE IMPACTS OF CARBON MARKET LINKAGE ON SECTORAL COMPETITIVENESS: A CASE STUDY OF BEIJING–TIANJIN–HEBEI REGION BASED ON THE CEECPA MODEL

Feng Wang, Beibei Liu and Bing Zhang
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Feng Wang: Business School, Nanjing University of Information Science & Technology, Nanjing 210044, P. R. China†Development Institute of Jiangbei New Area, Nanjing University of Information Science & Technology, Nanjing 210044, P. R. China
Beibei Liu: #x2021;State Key Laboratory of Pollution Control & Resource Reuse, School of Environment Nanjing University, Nanjing 210023, P. R. China§The Johns Hopkins University-Nanjing, University Center for Chinese and American Studies, Nanjing 210093, P. R. China

Climate Change Economics (CCE), 2020, vol. 11, issue 03, 1-24

Abstract: Emission trading could increase the production cost of sectors, and thus has significant impacts on sectoral competitiveness. This study takes the Beijing–Tianjin–Hebei (BTH) region as an example to explore the impacts of different carbon market linkage scenarios on regional sectoral competitiveness by using the CEECPA model, a static multi-region and multi-sector Computable General Equilibrium (CGE) model in China. Results show that carbon market linkage can mitigate the adverse impacts of emission trading on regional sectoral competitiveness across the BTH region. However, carbon market linkage may lead to the imbalances of regional sectoral competitiveness. In particular, energy production and energy-intensive sectors in Hebei would experience higher sectoral competitive losses under the restricted linkage scenario. Revenue recycling can effectively reduce sectoral competitive losses from carbon market linkage. Especially, using revenues to deduct indirect tax can make the sectoral competitive losses in Hebei significantly decrease. Policy implications are proposed to facilitate emission mitigation and balanced industrial development in China.

Keywords: Carbon market linkage; sectoral competitiveness; CEEPCA model; revenues recycling (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1142/S2010007820410055

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