Environmental efficiency evaluation of industrial sector in China by incorporating learning effects.

Concerns about reducing waste gas emissions and the trade-off with economic development dominate government policy worldwide. However, existing data envelopment analysis does little to permit understanding of how environmental efficiency can be improved by learning solutions. Digesting and following effective strategies from elsewhere is intuitive, but to date no evidence has been able to quantify how exactly the inputs and outputs of production are affected. Developing an improved slacks-based measure model, which incorporates learning effects as one part of undesirable outputs for the first time, we reappraise the performance of Chinese regional industrial production systems. Learning effects have significant impacts for three waste gases, especially for sulfur dioxide, advocating policy which gives managers and operatives access to best practice and empowers them to replicate this within their own firms. As well as reducing output there is strong potential to improve environmental efficiency, particularly in the developed eastern area of China. However, in the central and western regions of China it remains optimal to focus efforts on productivity and there caution on placing too much hope on learning activities is cautioned against. We also find that the proposed approach accompanied with traditional data envelopment analysis model can effectively identify the regional inefficiency whether sourced from learning activities, other production activities, or the both. [ABSTRACT FROM AUTHOR]