Decomposition of energy intensity in Chinese industries using an extended LMDI method of production element endowment. (15th April 2021)

• Record Type: Journal Article
• Authors: Zhang, Wei; Wang, Nan
• Is Part Of: Energy. Volume 221(2021)
• Publication Date: 2021-04-15
• Subjects: Extended LMDI -- Energy intensity -- Chinese industry -- Production element endowment -- Development mode -- R&D expenditure; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2021.119846
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: The purpose of this paper is to decompose the impacting factors of production element endowment (PEE) on energy intensity in China's industries in 2000–2015. This is vital for China's policy-making in terms of the development of low-energy-consumption (LEC) industries under relatively rapid industrialization and urbanization. This study contributes to the comprehensive investigation of PEE's impact on energy intensity (EI), which can bridge the existing literature gap. A PEE extended logarithmic mean Divisia index (LMDI) method was developed to decompose the changes in the Chinese industrial EI into three PEE, two intensity, and two structure factors. These driving factors include the energy–capital ratio (EK), capital–labor ratio (KL), labor–technology ratio (LT), R&D intensity (RI), investment intensity (II), energy mix (ES), and share of provincial industrial output (OS). The results demonstrated the following. (1) Overall, the effects of LT and EK are the two leading contributors to the decline in EI in Chinese industry. Moreover, OS exerted a negative effect on EI, and ES showed a marginal negative effect on EI. KL, II, and RI played roles in the increase in Chinese industrial EI. (2) In terms of the cumulative effects at the provincial level, LT and KL had the largest curbing and stimulating effect on the EI of all provinces, respectively. EK, II, RI, and OS had positive or negative effects on EI in all provinces with some fluctuations. Among all factors, the ES effect was the weakest and demonstrated mixed results in different provinces. (3) In the eastern, central, and western regions, LT, EK, and OS decreased Chinese industrial EI. KL, II, and RI were the three major contributors to the improvement in EI. Finally, the policy recommendations for EI reduction in Chinese industry are presented on the basis of the empirical results. Highlights: LT and EK are the two leading contributors to the decline of EI. II, RI, and OS had positive or negative effects on EI with some fluctuations. LT, EK, and OS decreased Chinese industrial EI in the three regions. KL, II, and RI improved of EI in the three regions. ES was the weakest factor influencing EI.