Allocating on coal consumption and CO2 emission from fair and efficient perspective: empirical analysis on provincial panel data of China

This paper considers a problem of how to allocate resource effectively and equitably among provinces. To address the problem, a total factor resource input-oriented data envelopment analysis (DEA) model is used to evaluate the energy and environmental efficiency for 30 provinces in China during 2009–2013 in this paper. Based on the evaluation results, from efficient and fair perspective, a revised DEA-based resource allocation model is established. It is worth pointing out that the model takes the input orientation and output orientation into account at the same time and can be used to allocate coal consumption and carbon emission by 2020 for 30 provinces in China. Results indicate that if the Chinese government wants to fulfill the CO2 emission reduction targets of 40–45% by 2020, and coal consumption intensity reduction target during 13th Five-Year Plan, inefficient provinces will undertake more coal consumption and carbon emission intensity reduction obligation share. And provinces with historical high coal consumption and high CO2 emission intensity will have greater potential of coal consumption and carbon emission intensity reduction. In addition, this paper set several scenarios of gross domestic product (GDP) growth rate, under the scenarios analysis, finds the growth rate of GDP has negative effect on reduction of coal consumption and carbon dioxide emissions intensity. This research provides more realistic practical significance for achieving sustainable economic development.