The global warming and climate change becomes a major policy issue in the world. To partly deal with the climate change issue from economics and business strategy, this study proposes a use of Data Envelopment Analysis (DEA) as a methodology for productive and environmental efficiency assessment. The proposed DEA approach has been long serving as an important methodology to evaluate the performance of various organizations. Recently, many researchers have applied the DEA to various environmental issues. A contribution of the previous DEA studies on environmental assessment was that they found the importance of an output separation into desirable (good) and undesirable (bad) outputs such as CO2 emission and air pollution substances from economic activities. Acknowledging a contribution of these previous studies on DEA environmental assessment, this study classifies efficiency measures into three categories according to the treatment of undesirable outputs. That is, production efficiency, environmental efficiency under natural disposability and environmental efficiency under managerial disposability. The first efficiency measure does not incorporate undesirable outputs into efficiency measurement whereas the second and third measures apply undesirable outputs to the DEA assessment. This study incorporates an amount of energy used as an input to examine energy efficiency. Using a dataset regarding manufacturing and non-manufacturing industries of 47 prefectures in Japan, this study examines their productive and environmental efficiencies and discusses policy implications for these industries.
Mika Goto, Central Research Institute of Electric Power Industry, Japan
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