4.6 Article

Factor decomposition of China's industrial electricity consumption using structural decomposition analysis

Journal

STRUCTURAL CHANGE AND ECONOMIC DYNAMICS
Volume 51, Issue -, Pages 67-76

Publisher

ELSEVIER
DOI: 10.1016/j.strueco.2019.08.002

Keywords

Structural decomposition analysis; Electricity consumption; Input-output analysis

Categories

Funding

  1. National Natural Science Foundation of China [71873075, 71733003, 71904192]
  2. Tsinghua University Independent study Plan [20151080359]
  3. China Postdoctoral Science Foundation [2019M650939]

Ask authors/readers for more resources

We analyzed changes in China's industrial electricity consumption using a structural decomposition model based on input-output analysis. China's industrial electricity consumption changes during 2007-2012 were decomposed into four factors: electricity intensity, technology-input structural, final demand structure and total final demand. The results showed that changes in total final demand contributed most to increases in China's industrial electricity consumption, which increased electricity consumption by 2091.34 billion kW h. As for aggregate demand, increased investment, urban residential consumption, and exports all played major roles. However, increases in total rural residents' consumption and total inventory had little effect on the electricity consumption of various industrial sectors. The key reason for reductions in industrial electricity consumption was the decrease in electricity intensity in the heavy manufacturing industry, the service industry, and the energy industry. The decline in electricity consumption intensity in China reduced electricity consumption by 446.21 billion kWh. (C) 2019 Elsevier B.V. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available