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

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  • Zhang, Ming
  • Su, Bin

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.

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  • Zhang, Ming & Su, Bin, 2016. "Assessing China's rural household energy sustainable development using improved grouped principal component method," Energy, Elsevier, vol. 113(C), pages 509-514.
    • Handle: RePEc:eee:energy:v:113:y:2016:i:c:p:509-514
    DOI: 10.1016/j.energy.2016.07.071
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