Assessing China's rural household energy sustainable development using improved grouped principal component method

Ming Zhang and Bin Su

Energy, 2016, vol. 113, issue C, 509-514

Abstract: The purpose of this paper is to assess the status and progress of rural household energy sustainable development in China. A new composite indicator, rural energy sustainable development index (RESDI), is developed based on the improved grouped principal component analysis method (GPCA) which is the combination utilization of principal component analysis (PCA), factor analysis (FA), and entropy weight method. The improved grouped principal component analysis method keeps the advantages of principal component analysis and factor analysis. To capture the characters of rural energy sustainable development, ten indicators selected based on the criteria presented by OECD are designed to construct the RESDI. The main results are as follows. The RESDI increased from 0.185 in 1991 to 3.189 in 2012. However, the curve of RESDI can be divided into three phases: a slow increase stage between 1991 and 1996, a rapid decrease stage from 1997 to 1998, and a rapid increase stage between 1999 and 2012.

Keywords: Rural household energy consumption; Factor analysis; Principal component analysis; China (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (18)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544216309951
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:113:y:2016:i:c:p:509-514

DOI: 10.1016/j.energy.2016.07.071

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().