Understanding the efficiency evolution for the Chinese provincial power industry: A new approach for combining data envelopment analysis-discriminant analysis with an efficiency shift across periods

To examine a change in unified efficiency of provincial power industry, this study proposes an approach which combines Data Envelopment Analysis-Discriminant Analysis (DEA-DA), DEA environmental assessment and a rank sum test. The proposed approach is designed to overcome the following difficulties: (a) how to classify various decision making units (DMUs) into different groups, (b) how to identify the existence of group heterogeneity across DMUs, (c) how to measure unified efficiencies of power industry in different regions of China, (d) how to separate among various unified efficiency measures, and (e) how to unify these measures into a single measure which expresses total efficiency. To document the practicality, this study applies the proposed approach to examine unified efficiency measures of Chinese provincial power industry from 2009 to 2015. We obtain three empirical findings. First, the unified efficiency measurement identifies an existence of heterogeneity between two groups of provinces in China. Second, profound differences were confirmed in unified efficiency at a provincial level. Special attention should be given to the provinces with poor performance under both natural and managerial disposability. Finally, under both DEA and DEA-DA frameworks, large differences were confirmed between natural and managerial disposability. These two disposability concepts may assist in developing well-designed environmental and energy policy. (C) 2020 Elsevier Ltd. All rights reserved.