Journal
JOURNAL OF CLEANER PRODUCTION
Volume 162, Issue -, Pages 764-775Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2017.06.062
Keywords
Green development performance; Non-radial directional distance function; Quantile analysis
Categories
Funding
- Grant for Collaborative Innovation Center for Energy Economics and Energy Policy [1260Z0210011]
- Xiamen University Flourish Plan Special Funding [1260-Y07200]
- China National Social Science Fund [15ZD058]
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China is at the stage of industrialization and urbanization and because the energy demand and consumption for this process is rigid, coupled with emissions and global warming awareness, China is on a path to cut back emissions as she focuses on alternative and sustainable way to green the economy. This research investigates determining factors in measuring the dynamic changes in green development growth index (GDGI) over a given time frame. By adopting a non-radial directional distance function (NDDF), where more pollutants are added like sulphur dioxide emissions, solid wastes, waste water, and carbon dioxide emissions instead of using only one pollutant in measurement and using a global distance envelop analysis (DEA) to model green performance by considering both desirable and undesirable outputs, the model was decomposed into efficiency change (EC) index, best practice gap change (BPC) index, and technology gap change (TCG) index and these three indexes were employed to measure the green development performance in thirty provinces across china from 2000 to 2012. Results showed that provinces in the eastern region of China are greener than the central and western regions. Analyzing all three calculated dependent variables from a quantile perspective revealed that effects of EC, BPC, and TGC varied across different quantiles of GDGI. The coefficients of BPC were more significant than EC across quantiles, and TGC coefficients only became significant from Q(0.35), and continued on this path until the last observed quantile Q(0.95) however it was less than EC in terms of significance. The values of pseudo R-2 also continued to increase from Q(0.20) until the last observed quantile with 86% accuracy in prediction recorded at Q(0.95). Analyzing the 80th percentile revealed that the coefficient of BPC was highest in this percentile which implies that a unit increase in best practice gap change, will influence green development growth by 102.3 percent, and a unit increase in efficiency change, will accelerate green development growth by 99.41 percent while a unit increase in technical gap ratio change will produce 99.38 percent increase in green development growth of China. (C) 2017 Elsevier Ltd. All rights reserved.
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