Revisiting rebound effects of energy use and pollutant emissions: The role of technological change

Measuring the rebound effect (RE) of energy use and pollutant emissions is fundamental to characterizing the effects of technological progress on energy conservation and emissions reduction. This paper presents a total -factor RE model that combines the Fixed effects (FE) model, Data Envelopment Analysis (DEA), and Luen-berger Productivity Indicator (LPI). The proposed model takes into account two types of disposability for variable-specific decomposition for LPI. The model includes two general indices, static inefficiency performance and dynamic inefficiency performance, which can be used to assess performance in the industrial sector and measure technological change and RE. The results show that switching from natural to managerial disposability improves energy RE by 12% but reduce RE of NOx and SO2 emissions by 22% and 24%, respectively. These findings suggest that cleaner energy expansion can promote energy RE, while reducing environmental RE.

Automated summary

This paper proposes a total-factor rebound effect model that combines the Fixed effects model, Data Envelopment Analysis, and Luen-berger Productivity Indicator. The model can assess performance in the industrial sector and measure technological change and rebound effect. The results show that switching from natural to managerial disposability improves energy rebound effect while reducing NOx and SO2 emissions rebound effect.