Dynamic response forecasting and optimising paths of energy efficiency Online publication date: Sat, 06-Feb-2016
by Xiaoling Wang; Chunyou Wu; Jatin Nathwani
International Journal of Computational Science and Engineering (IJCSE), Vol. 12, No. 1, 2016
Abstract: Enhancing energy efficiency is a major concern of product design as well as policy responses to augment resource supply and environmental carrying capacity simultaneously. Based on empirical data from China, total factor energy efficiency is evaluated using a nonparametric linear algorithm called data envelopment analysis (DEA), followed by efficiency determinants identification. Dynamic inter-responses of energy efficiency and the determinants are forecast, simulated, and analysed with the help of the panel vector auto-regression (PVAR) and the Monte Carlo simulation technique. The findings indicate that positive effect of energy efficiency is strong initially but unsustainable over time; administrative interventions and the existing energy mix pose significant barriers to efficiency improvement; and enhancement of openness can facilitate an energy-efficient scenario by stimulating technological progress. Specific optimising paths for China's efficiency optimisation are then suggested according to the simulation outcomes.
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