How public environmental concern affects the sustainable development of Chinese cities: An empirical study using extended DEA models.

China is now facing the formidable tasks of saving energy and reducing emissions, so it is very important to analyze China's energy and environmental efficiency. However, previous studies have rarely paid attention to the cross-impacts that different forms of public environmental concern (PEC) have simultaneously on energy and environmental efficiency. To investigate how these two types of efficiency change along with PEC variations, this paper employs six extended programming models which are developed based upon the theory of Data Envelopment Analysis (DEA) and the directional distance function (DDF). An empirical analysis of data from 239 Chinese prefecture-level cities demonstrates the techniques. The empirical results show that PEC variations can significantly affect the environmental efficiency only if the city is experiencing unsustainable development. This work also shows that PEC about input resources may exaggerate the environmental efficiency, implying that the public may be more tolerant of resource over-consumption than of pollutant over-emission.
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