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Energies 2016, 9(5), 329; doi:10.3390/en9050329

Forecasting the Allocative Efficiency of Carbon Emission Allowance Financial Assets in China at the Provincial Level in 2020

1,3,* , 1,2,3
,
1,3,4,* , 1,3,* and 1
1
Economics & Management School, Beijing University of Technology, Beijing 100124, China
2
Changping North Seven Branches, Beijing Branch, Agricultural Bank of China Co., LTD., Beijing 102209, China
3
Finance and Economics Development Research Center, Economic Management School, Beijing University of Technology, Beijing 100124, China
4
Irish Institute for Chinese Studies, University College Dublin, Belfield, Dublin D4, Ireland
*
Authors to whom correspondence should be addressed.
Academic Editor: Carl-Fredrik Lindberg
Received: 12 February 2016 / Revised: 27 March 2016 / Accepted: 22 April 2016 / Published: 4 May 2016
(This article belongs to the Special Issue Low Carbon Economy)
View Full-Text   |   Download PDF [752 KB, uploaded 16 May 2016]   |  

Abstract

As the result of climate change and deteriorating global environmental quality, nations are under pressure to reduce their emissions of greenhouse gases per unit of GDP. China has announced that it is aiming not only to reduce carbon emission per unit of GDP, but also to consume increased amounts of non-fossil energy. The carbon emission allowance is a new type of financial asset in each Chinese province and city that also affects individual firms. This paper attempts to examine the allocative efficiency of carbon emission reduction and non-fossil energy consumption by employing a zero sum gains data envelopment analysis (ZSG-DEA) model, given the premise of fixed CO2 emissions as well as non-fossil energy consumption. In making its forecasts, the paper optimizes allocative efficiency in 2020 using 2010 economic and carbon emission data from 30 provinces and cities across China as its baseline. An efficient allocation scheme is achieved for all the provinces and cities using the ZSG-DEA model through five iterative calculations. View Full-Text
Keywords: carbon emission allowance; non-fossil fuels; efficiency; zero sum gains data envelopment analysis (ZSG-DEA); iteration carbon emission allowance; non-fossil fuels; efficiency; zero sum gains data envelopment analysis (ZSG-DEA); iteration
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Zeng, S.; Xu, Y.; Wang, L.; Chen, J.; Li, Q. Forecasting the Allocative Efficiency of Carbon Emission Allowance Financial Assets in China at the Provincial Level in 2020. Energies 2016, 9, 329.

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