Energy efficiency in Korea: analysis using a hybrid DEA model

Abstract

Given the increasing importance of energy efficiency, we appraise the situation in Korea by analyzing past energy consumption patterns. By using a modified hybrid model of index decomposition analysis, artificial neural network (ANN), and data envelopment analysis (DEA), we predict the optimal energy consumption and estimate the difference between the optimal and real values. We decompose primary energy consumption considering the energy loss in a transformation, correcting the over-fitting problem in ANN, and addressing the negative value issue in DEA. We find that energy consumption was the most efficient between 1993 and 1994, 1994 and 1995, 1997 and 1998, and 1999 and 2000. If the over-fitting and negative value problems are properly controlled, the presented LMDI-ANN-DEA hybrid model can be used to predict energy efficiency. The results of this study would be useful to analyze energy consumption patterns in the benchmark years of Korea and help the government formulate a suitable energy policy.