Industrial energy consumption and pollutant emissions: Combined decomposition of relative performance and absolute changes.

Combined decomposition of relative productivity growth and absolute changes in input/output variables helps to identify the driving forces of energy conservation and emission reduction. This paper proposes a framework based on the Luenberger productivity indicator (LPI) and the logarithmic mean Divisia index (LMDI) approach to analyze the energy–economy–environment nexus. The empirical case of the China's industrial sector for 2006–2014 is analyzed. Following this approach, we present a variable‐specific decomposition framework which attributes the overall productivity change and its sources to individual input/output variables. Empirically, we examine the relationships between the productivity growth and energy consumption within the LPI–LMDI framework across China's province‐level regions. The results show important spatial variation in the productivity measures. The LPI–LMDI decomposition implies that the industrial energy consumption increased with productivity growth appearing as the only mitigating factor. As regards the industrial SO2 emission, the individual productivity growth effect and the efficiency change effect remained as suppressing factors for emission abatement. These results can be used for evidence‐based decision making. [ABSTRACT FROM AUTHOR]