In this study, we analyze the environmental efficiency performance and its determinants of 29 manufacturing industries in China from 2006 to 2011 by employing a two-stage DEA (data envelopment analysis)-Tobit model. For providing comparative and robust evidence, the 29 manufacturing industries are classified into three groups based on the pollution intensity. In the first stage, a SBM (slacks-based measure)-DEA model is applied to assess economic efficiency and environmental efficiency scores to illustrate the effects of the environmental factors, while taking into consideration the undesirable output. In the second stage, utilizing these calculated environmental efficiency scores as dependent variables, we employ a Tobit regression model to study the determinants of the environmental efficiency by selecting three independent variables including the industry scale, the openness degree and the energy structure. It turns out that the environmental factors have a positive effect on the lightly polluted industries and a negative effect on the moderately polluted industries, the heavily polluted industries, and the overall industries, while the openness degree, the industry scale, and the energy structure can be effective measures to improve environmental efficiency. Based on these findings, we propose policy measures to enhance the environmental efficiency of manufacturing in China.
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