Energy efficiency improvement (EEI) benefits the climate and matters for energy security. The potential emission and energy savings due to EEI may however not fully materialize due to the rebound effect. In this study, we measure the size of rebound effect for the two energy types fuel and electricity within the four most energy intensive sectors in Swedenpulp and paper, basic iron and steel, chemical, and mining. We use a detailed firm-level panel data set for the period 2000-2008 and apply Stochastic Frontier Analysis (SFA) for measuring the rebound effect. We find that both fuel and electricity rebound effects do not fully offset the potential for energy and emission savings. Furthermore, we find 2 CO intensity and fuel and electricity share as the two main determinants of rebound effect in Swedish heavy industry. Our results seems to imply that it matters both to what extent and where to promote EEI, as the rebound effect varies between sectors as well as between firms within sectors.

Energy efficiency improvement (EEI) benefits the climate and matters for energy security. The potential emission and energy savings due to EEI may however not fully materialize due to the rebound effect. In this study, we measure the size of rebound effect for the two energy types fuel and electricity within the four most energy intensive sectors in Swedenpulp and paper, basic iron and steel, chemical, and mining. We use a detailed firm-level panel data set for the period 2000-2008 and apply Stochastic Frontier Analysis (SFA) for measuring the rebound effect. We find that both fuel and electricity rebound effects do not fully offset the potential for energy and emission savings. Furthermore, we find 2 CO intensity and fuel and electricity share as the two main determinants of rebound effect in Swedish heavy industry. Our results seems to imply that it matters both to what extent and where to promote EEI, as the rebound effect varies between sectors as well as between firms within sectors.

Energy inefficiency in production implies that the same level of goods and services could be produced using less energy. The potential energy inefficiency of a firm may be linked to long-term structural rigidities in the production process and/or systematic shortcomings in management (persistent inefficiency), or associated with temporary issues like misallocation of resources (transient inefficiency). Eliminating or mitigating different inefficiencies may require different policy measures. Studies measuring industrial energy inefficiency have mostly focused on overall inefficiencies and have paid little attention to distinctions between the types. The aim of this study was to assess whether energy inefficiency is transient and/or persistent in the Swedish manufacturing industry. I used a firm-level panel dataset covering fourteen industrial sectors from 1997-2008 and estimated a stochastic energy demand frontier model. The model included a four-component error term separating persistent and transient inefficiency from unobserved heterogeneity and random noise. I found that both transient and persistent energy inefficiencies exist in most sectors of the Swedish manufacturing industry. Overall, persistent energy inefficiency was larger than transient, but varied considerably in different manufacturing sectors. The results suggest that, generally, energy inefficiencies in the Swedish manufacturing industry were related to structural rigidities connected to technology and/or management practices.

Energy efficiency improvement (EEI) is generally known to be a cost-effective measure for meeting energy, climate, and sustainable growth targets. Unfortunately, behavioral responses to such improvements (called energy rebound effects) may reduce the expected savings in energy and emissions from EEI. Hence, the size of this effect should be considered to help design efficient energy and climate targets. Currently, there are significant differences in approaches for measuring the rebound effect. Here, we used a two-step procedure to measure both short- and long-term energy rebound effects in the Swedish manufacturing industry. In the first step, we used data envelopment analysis (DEA) to measure energy efficiency. In the second step, we use the efficiency scores and estimated a derived energy demand equation including rebound effects using a dynamic panel regression model. This approach was applied to a firm-level panel dataset covering 14 sectors in Swedish manufacturing over the period 1997–2008. We showed that, in the short run, partial and statistically significant rebound effects exist within all manufacturing sectors, meaning that the rebound effect decreased the energy and emission savings expected from EEI. The long-term rebound effect was in general smaller than the short-term effect, implying that within each sector, energy and emission savings due to EEI are larger in the long run compared to the short run. Using our estimates of energy efficiency and rebound effect, we further performed a post-estimation analysis to provide a guide to policy makers by identifying sectors where EEI have the most potential to promote sustainable economic growth with the lowest environmental impact.