Exploring the effects of influencing factors on energy efficiency in industrial sector using cluster analysis and panel regression model. (1st September 2018)
- Record Type:
- Journal Article
- Title:
- Exploring the effects of influencing factors on energy efficiency in industrial sector using cluster analysis and panel regression model. (1st September 2018)
- Main Title:
- Exploring the effects of influencing factors on energy efficiency in industrial sector using cluster analysis and panel regression model
- Authors:
- Liao, Nuo
He, Yong - Abstract:
- Abstract: The various industrial sub-sectors in China should require differentiated policy measures on energy conservation and emission reduction. The existing literature lack comprehensive and in-depth investigation on the influencing factors of energy efficiency at the level of industrial sub-sectors. We aim to examine the disparities in energy efficiency and the driving factors of the energy efficiency among industrial sub-sectors. Using super-SBM, cluster analysis and panel regression model, we explore the effects of influencing factors on energy efficiency across the industrial sub-sectors, and examines the entity effects and dynamic evolving characteristics of energy efficiency in various sub-sectors in China from 2005 to 2011. The results indicate that, there indeed exist significant disparities in energy efficiency across the sub-sectors. In the entire industry, technological progress, energy consumption structure and enterprise scale are the determining factors, but marketization degree and labor productivity do not have significant effects. Meanwhile, obvious variations are found in the effects of influencing factors across sub-sectors with different energy efficiency levels. The entity effects and evolving characteristics of energy efficiency across the industrial sub-sectors, and the dynamic effects of the influencing factors on energy efficiency all have distinct variances. Diverse policy implications are presented to the industrial sub-sectors with differentAbstract: The various industrial sub-sectors in China should require differentiated policy measures on energy conservation and emission reduction. The existing literature lack comprehensive and in-depth investigation on the influencing factors of energy efficiency at the level of industrial sub-sectors. We aim to examine the disparities in energy efficiency and the driving factors of the energy efficiency among industrial sub-sectors. Using super-SBM, cluster analysis and panel regression model, we explore the effects of influencing factors on energy efficiency across the industrial sub-sectors, and examines the entity effects and dynamic evolving characteristics of energy efficiency in various sub-sectors in China from 2005 to 2011. The results indicate that, there indeed exist significant disparities in energy efficiency across the sub-sectors. In the entire industry, technological progress, energy consumption structure and enterprise scale are the determining factors, but marketization degree and labor productivity do not have significant effects. Meanwhile, obvious variations are found in the effects of influencing factors across sub-sectors with different energy efficiency levels. The entity effects and evolving characteristics of energy efficiency across the industrial sub-sectors, and the dynamic effects of the influencing factors on energy efficiency all have distinct variances. Diverse policy implications are presented to the industrial sub-sectors with different energy efficiency. Highlights: Industry sub-sectors are classified to three categories with different energy efficiency. Time and entity fixed effect model are set up to explore influencing factors. The entity effect and evolving characteristics of energy efficiency are analyzed. … (more)
- Is Part Of:
- Energy. Volume 158(2018)
- Journal:
- Energy
- Issue:
- Volume 158(2018)
- Issue Display:
- Volume 158, Issue 2018 (2018)
- Year:
- 2018
- Volume:
- 158
- Issue:
- 2018
- Issue Sort Value:
- 2018-0158-2018-0000
- Page Start:
- 782
- Page End:
- 795
- Publication Date:
- 2018-09-01
- Subjects:
- Energy efficiency -- Industrial sector -- Influencing factors -- Cluster analysis -- Time and entity fixed effects model
Power resources -- Periodicals
Power (Mechanics) -- Periodicals
Energy consumption -- Periodicals
333.7905 - Journal URLs:
- http://www.elsevier.com/journals ↗
- DOI:
- 10.1016/j.energy.2018.06.049 ↗
- Languages:
- English
- ISSNs:
- 0360-5442
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3747.445000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 16587.xml