Carbon congestion effects in China's industry: Evidence from provincial and sectoral levels
Yue-Jun Zhang (),
Jing-Yue Liu and
Bin Su ()
Energy Economics, 2020, vol. 86, issue C
Investigating carbon congestion effect can help identify congestion in production, which is of great significance for the rational use of resources and the effective promotion of carbon emissions reduction. Under this circumstance, this study uses the dual model of radial DEA to explore both undesirable/desirable congestion, returns to damage and damages to return during 2005–2015 from both provincial and sectoral levels. Combined with window analysis, the technical efficiency and emissions reduction potential of China's industrial sectors are also discussed. The empirical results show that: (1) China's industrial carbon congestion is obvious and the congestion effect witnesses a trend of regional agglomeration and evident regional and sectoral heterogeneity. In particular, undesirable congestion mainly occurs in the eastern region, and desirable congestion mainly occurs in the western region, followed by the eastern region; both undesirable and desirable congestions mainly occur in some sectors in the Manufacturing and Power-Gas-Water industries. (2) If all sectors produce on the production frontier, the average annual potential carbon emissions reduction would reach 722.82 million tons, with the higher potential in western region and Shanxi province of central region, as well as Manufacturing and six high-energy-consuming sectors. (3) To achieve the “win-win” of industrial development and carbon emissions reduction, China's western region should focus on green technology innovation, while the eastern region and Power-Gas-Water industry should focus on both input resources optimisation and green technology innovation.
Keywords: Carbon congestion effect; Carbon dioxide emissions; Industry; Radial DEA; China (search for similar items in EconPapers)
JEL-codes: O13 O14 P18 Q00 Q56 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:86:y:2020:i:c:s0140988319304323
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