4.7 Article

Effective ways to reduce CO2 emissions from China's heavy industry? Evidence from semiparametric regression models

期刊

ENERGY ECONOMICS
卷 92, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.eneco.2020.104974

关键词

CO2 emissions; The heavy industry; Semiparametric regression models

资金

  1. National Natural Science Foundation of China [71974085]
  2. State Grid Corporation technology project [521104170015]
  3. Ministry of Education of China [10JBG013]

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Using China's province-level panel data from 2005 to 2017, this article uses a semiparametric regression model to investigate CO2 emissions in China's heavy industry. Empirical results show that while economic growth exerted carbon reduction effects in the eastern region, it stimulated the growth of CO2 emissions in the central and western regions. This is mainly due to regional differences in industrial structure and the high-tech industry. Energy efficiency has made a greater contribution to reducing CO2 emissions in the central region because the R&D investment and patent rights granted in this region has grown faster. The energy consumption structure has a more complex impact. It exerts a pulling first, then restricting (boolean AND-shaped) nonlinear effect on CO2 emissions in the eastern and western regions, but an inverted N-shaped effect in the central region. This is mainly due to the differences in the composition of energy consumption across regions. Environmental regulations have a positive U-shaped nonlinear impact on CO2 emissions in the eastern and western regions. It means that environmental regulations help cut down CO2 emissions in the early stage, and the facilitation effect gradually disappears at the later stage. Conversely, environmental regulations produce an inverted U-shaped impact in the central region. (C) 2020 Elsevier B.V. All rights reserved.

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