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Environmental efficiency analysis of the Yangtze River Economic Zone using super efficiency data envelopment analysis (SEDEA) and tobit models

Nengcheng Chen, Lei Xu and Zeqiang Chen

Energy, 2017, vol. 134, issue C, 659-671

Abstract: Environmental efficiency (EE) assessment is an efficient way to evaluate the degree of coordination between economy and environment. Most of the studies measured country- or region-level EEs, while the EE disparities among cities were not well investigated. By incorporating the socioeconomic and remote sensing data, this study measured the static and dynamic EEs of 11 provinces and 131 cities in the Yangtze River Economic Zone (YREZ) in China based on a super efficiency data envelopment analysis (SEDEA) and Malmquist index (MI) methods during 2003–2014. The influential factors of EE imbalance in the YREZ area were explored by the panel tobit model. Results show that large gaps exist in city's environmental efficiency. Cities in the Yangtze River Delta (YRD) show higher EEs than that in the Chengyu Urban Agglomeration (CUA) and Urban Agglomeration in the Middle Reaches of the Yangtze River (UAMR) areas. 15 cities have an EE below 0.2 and only 2 cities above 1 in 2014. The overall average EE exhibited a declining trend during 2003–2014. The number of cities below the average environmental efficiency increased from 70 (53.4%) to 83 (63.4%) over the time period studied. The MI results indicate that management and scale optimization level is the main factor hindering total factor productivity (TFP) growth. The tobit experiment reveals that GDP per capita played a negative impact on EE for most of the YREZ area during 2003–2014. The degree of opening up and industrial structure acted positively on city's environmental efficiency. These conclusions may be a helpful reference for decision makers to coordinate the economy and environment in the YREZ area.

Keywords: Yangtze River Economic Zone; Environmental efficiency; Super efficiency; Data envelopment analysis (search for similar items in EconPapers)
Date: 2017
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