Published January 2021 | Version v1
Journal article

Energy efficiency performance of the industrial sector: From the perspective of technological gap in different regions in China

  • 1. School of Economics, Faculty of Economics and Management, East China Normal University, Shanghai, 200062 (China)
  • 2. School of Management, China Institute for Studies in Energy Policy, Xiamen University, Xiamen, 361005 (China)

Description

Highlights: • Applying SFA method with metafrontier to analyze industrial energy efficiency. • Considering technological heterogeneity in energy efficiency measurement. • The traditional pooled estimation tends to overestimate energy efficiency. • Regional differences exist in industrial energy efficiency and TGRs. The traditional estimation methods tend to result in biased energy efficiency estimates due to the exclusion of heterogeneous production technology. Taking this factor into account, this study uses the metafrontier method combined with the stochastic frontier analysis (SFA) to analyze energy efficiency performance of the industrial sectors in China's 30 provinces during 1997–2016. This study measures energy efficiency by considering the technological gap that can be regarded as a discrete source of energy inefficiency. Different from the traditional classification of different regions in China, we divide regions into three groups by using the cluster analysis based on the indicator of energy intensity. The empirical results are summarized as follows: first, the traditional pooled estimation method, which ignores the technological gap of the industrial sectors among different regions, tends to overestimate energy efficiency performance; second, energy efficiency and technological gap ratios (TGRs) of the industrial sectors are distinct among China's regions; and the industrial sectors of the eastern region maintained higher energy efficiency and TGRs due to more advanced production technology; third, in general, the average score of industrial energy efficiency of China was only 0.4396, implying that there's still plenty of room for energy efficiency improvement.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.energy.2020.118865

Additional details

Identifiers

DOI
10.1016/j.energy.2020.118865;
PII
S0360544220319721;

Publishing Information

Journal Title
Energy (Oxford)
Journal Volume
214
Journal Page Range
vp.
ISSN
0360-5442
CODEN
ENEYDS

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
53108315
Subject category
S32: ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; S42: ENGINEERING;
Descriptors DEI
CLASSIFICATION; CLUSTER ANALYSIS; ENERGY EFFICIENCY; PERFORMANCE; STOCHASTIC PROCESSES
Descriptors DEC
DATA ANALYSIS; DATA PROCESSING; EFFICIENCY; PROCESSING

Optional Information

Copyright
Copyright (c) 2020 Elsevier Ltd. All rights reserved.