Average Rebound Effect Research Articles

CO2 Emissions in China: Does the Energy Rebound Matter?

Enhancing energy efficiency is globally regarded as an effective way to reduce carbon emissions. In recent years, the energy efficiency of China has gradually improved; however, energy consumption and CO2 emissions are still increasing. To better understand the reasons for this, we evaluated the energy rebound effect (RE) of 30 provinces in China over the period 2001–2017 by employing stochastic frontier analysis (SFA) and the system generalized method of moments (system-GMM) approach, and explored the extent to which the RE affects CO2 emissions. Asymmetric and regional heterogeneity analyses were also conducted. The results indicate that the national average RE was 90.47% in the short run, and 78.17% in the long run, during the sample period. Most of the provinces experienced a partial RE, with a backfire effect occurring in some provinces such as Guangxi and Henan. The RE was associated with significant increases in CO2 emissions; specifically, a 1% increase in the short-run RE led to an increase in CO2 emissions of approximately 0.818%, and a 1% increase in the long-run RE resulted in an increase in CO2 emissions of approximately 0.695%. Moreover, significant regional differences existed in the impact of the RE on CO2 emissions; in regions with high emissions and a high RE, the CO2 reduction effect from the marginal decline in the RE was much more pronounced than that in other regions.

How does market-oriented reform influence the rebound effect of China’s mining industry?

Carbon neutrality is the future development direction of China. Achieving the goal of carbon neutrality requires the combined efforts of all industries, especially heavy industries. As one of the heavy industries, the mining sector contributes significantly to China’s national economic development. This paper calculates China’s mining sector’s rebound effect and explores the impact of market-oriented reform on its rebound effect. We use the Shephard energy distance function to measure energy efficiency and analyze the effect of marketization on the rebound effect with the threshold model. Based on our results, the mining sector’s average rebound effect is 46.4%. Moreover, with the increase in the decision-making flexibility of mining enterprises, the rebound effect presents an upward trend. We conclude by urging policy-makers to implement energy price reforms and promote energy consumption permits

Measurement of the direct rebound effect of residential electricity consumption: An empirical study based on the China family panel studies

The rebound effect is a potential threat to energy efficiency related policies to save energy. Based on data from China family panel studies over the period 2010–2018, this paper measures the energy efficiency and direct rebound effect of residential electricity consumption by using the stochastic energy demand frontier model. The result shows that the average value of efficiency is 0.491, and the average rebound effect is 48%. It means that there is still room for improvement in China’s household electricity consumption efficiency. But the expected electricity- saving after improving efficiency can only achieve 52%. Besides, we find that electricity price and household size have a negative impact on the rebound effect, while the impact of income is inverted U-shaped. Finally, the rebound effect varies between before and after the implementation of the increasing block pricing policy, considering rural and urban residents and different regions. These findings provide some policy implications for the residential electricity pricing system under the background of energy conservation and climate change.

Estimating the Rebound Effect of the U.S. Road Freight Transport

The United States (U.S.) road freight sector has continued to grow over recent decades. Growth in road freight could result in more fuel consumption and hence increased greenhouse gas emissions. Policymakers have attempted to manage the growth of energy usage through improved fuel economy based on technological advances. However, such improvements may not lead to anticipated goals because of the rebound effect, where improvements in energy efficiency trigger more travel and energy consumption that offsets energy savings. Thus, this study aims to determine the potential rebound effect from improved energy efficiency in the U.S. road freight sector. Eight fuel cost models are applied and asymmetric price response is incorporated in estimating the U.S. road freight sector’s rebound effect from 1980 to 2016. In addition, a recently developed data envelopment analysis is applied to determine the annual rebound effect in the road freight sector. The results suggest that, after accounting for the asymmetric price response, the average rebound effect of the U.S. road freight sector ranges from 6.9% to 8.8%, a level considerably less than that found for several industrialized countries and emerging economies. However, a considerable increase in the rebound effect has been seen in more recent years. The findings suggest that overlooking the rebound effect in environmental policies could impede the goal of reducing total energy consumption and accompanying emissions. Policymakers should incorporate the rebound effect from efficiency enhancement in policy development and utilize some potential programs to reduce the adverse influence of rebound effect in related policies.

Is the energy efficiency improvement conducive to the saving of residential electricity consumption in China?

The urbanization process and the continuous upgrading of consumption structure have driven the rapid growth of China’s residential electricity consumption, making it urgent to strengthen energy conservation and emission reduction in the residential sector. Improving the efficiency of electricity use is an effective method to reduce the consumption of electricity, but the rebound effect (RE) also emerges. Is it still conducive to saving electricity? In response to this question, this article selects the relevant data in China during 2010–2016 to construct the panel linear model and the panel threshold model respectively to analyze the direct RE of residential electricity consumption. The results show that: (1) The average RE of China’s residential electricity use is 84.94%. It indicates that energy efficiency improvement can lower residents’ electricity use, but only 15.06% of the expected target can be achieved. (2) The direct RE in high-income regime (PGDP>76023.67) and low-income regime (PGDP≤76023.67) is 59.15% and 80.79% respectively, meaning that energy efficiency measures in the high-income regime are more effective. (3) The direct RE in the high-population regime (POP>6083.28) and low-population regime (POP≤6083.68) is 120.09% and 83.91% respectively, indicating that energy efficiency improvement in the high-population regime has intensified residents’ electricity consumption. Therefore, to maximum energy saving effect, the government should take the inter-provincial heterogeneity of the RE into consideration and introduce market-oriented measures such as price and tax to restrain it.

Economy-wide estimates of energy rebound effect: Evidence from China's provinces

The ongoing debate on the magnitude of China's economy-wide energy rebound effect (RE) entails further investigations not only with more details, but also with more credible methods. In this study, a modified two-stage approach, which could avoid methodological issues regarding RE estimation, is applied to estimate macroeconomic RE with a data panel of 30 provinces in China during the period 1997–2015. In particular, in order to comprehensively measure energy efficiency, we construct a dynamic energy efficiency indicator which considers not only the static efficiency of energy use but also the technical change regarding energy usage. Using dynamic panel data models, we estimate the elasticity of energy consumption with respect to energy efficiency which directly links to the measurement of RE. The short-run and long-run estimates of RE are reported, and the 95% confidence interval was computed for each sample based on the nonparametric bootstrap method to further analyze the macroeconomic RE of different regions. Results indicate that the average RE of all provinces is 88.55% in the short run, and the average long-run RE is 77.50%; the RE in the developed eastern region continuously decreased, while RE in the western region increased to be the largest during the research period.

Energy Rebound Effect Analysis Based on Technological Progress

China’s energy consumption is facing the dual pressure of economic growth and environmental protection. The analysis of energy rebound effect is of great significance to China’s energy efficiency improvement. Based on the LMDI decomposition method, the author established the model for rebound effect calculation and empirically analyzed the energy rebound effect in China from 1997 to 2017. The empirical results show that the improvement of energy efficiency caused by technological progress can save energy consumption, but the rebound effect of energy consumption exists significantly. The rebound effect of energy consumption in China ranged from 3.67% to 134.18%, with an average rebound effect of 34.85%. The impact of technological progress on energy efficiency is a dynamic process. The rebound effect fluctuates in different degrees in different periods.

Does the rebound effect matter in energy import-dependent mega-cities? Evidence from Shanghai (China)

The energy rebound effect is regarded as an obstacle of achieving the expected target of energy-saving policies, especially under a rapid urbanization background in developing counties, such as China. This has become a substantial drag of sustainable development in some cities. Shanghai is the economic center of China, and it is also a typical energy import-dependent mega-city. Investigating the evolution of Shanghai’s energy-saving performance and the energy rebound effect is significant for the implementation of energy-saving policies in other similar cities of China and other developing countries. Using the state space model with time-varying parameters and based on the IPAT identity and the Solow residual approach, this paper is the first study to present a specific estimation on Shanghai’s energy rebound effect caused by technological progress. The results show that, during the period of 1991–2016, the average energy rebound effect of overall economy and secondary industry in Shanghai was 93.96% and 73.10%, respectively, indicating a high partial rebound effect. Most of expected energy saving caused by improved energy efficiency is offset by extra energy consumption caused by technological progress. Regarding tertiary industry, the average rebound effect was 146.61%, indicating a backfire effect. However, the average energy rebound amount of tertiary industry is less than that of secondary industry. In particular, there is an increasingly negative impact of the rebound effect of tertiary industry on energy conservation in recent years, with the sector’s rapid expansion and corresponding increase in energy demand. Furthermore, we estimate the carbon rebound amount (i.e., carbon emissions caused by the energy rebound effect) and find that, on average, the energy rebound effect caused 13.1% and 0.41% increases in carbon emissions in Shanghai and China, respectively. Therefore, mitigating the energy rebound effect can significantly reduce carbon emissions. Due to the substantial impact of the rebound effect, technological progress and energy efficiency improvement should not be the only way to achieve energy-saving target, especially in energy import-dependent mega-cities like Shanghai. Some supporting policies should be implemented to ensure that the expected outcome of energy-saving effort can be realized as far as possible.

Empirical analysis on energy rebound effect from the perspective of technological progress—a case study of China's transport sector

Energy rebound effect is a major issue in energy economics. Global energy and environmental problems have compelled the need for simultaneous attainment of economic development and energy conservation. Technological progress increases energy efficiency and saves energy, but it also causes energy rebound effect which discounts the expected energy conservation. China's transport sector is energy-intensive. Therefore, investigating rebound effect in China's transport sector has a very important significance for energy conservation and the formulation of related policies. Taking China's transport sector as a case study, we used translog production function to measure the contribution rate of technological progress to output growth, and estimated the rebound effect. The results show that the average rebound effect was about 68.3% during 1981–2015. Finally, we provided relevant policy recommendations on the rebound effect based on the characteristics of energy use in China's transport sector.

Estimation of China's macro-carbon rebound effect: Method of integrating Data Envelopment Analysis production model and sequential Malmquist-Luenberger index

Abstract Technology advances are considered to be effective in reducing carbon emissions. However, studies show that the effect of such advances on reducing carbon emissions is not as effective as expected, owing to the existence of the rebound effect (RE). This paper proposes a new method integrating the Data Envelopment Analysis (DEA) production model and the sequential Malmquist-Luenberger (SML) index to calculate China's macro-carbon RE. An extended DEA production model is used to eliminate the impact of input scale, and the SML index is employed to avoid the phenomenon of technology regress. Results show that the carbon RE can be calculated more precisely. The new method is then applied to calculate carbon RE values from 30 Chinese provinces from 1996 to 2015, and results indicate that the carbon RE does indeed exist in China and that national average carbon RE values vary from 7.4% to 43.8%. Furthermore, both the backfire effect and the super conservation effect are evident in some provinces. Based upon the obtained results, certain policy implications are suggested to facilitate China in effectively implementing carbon emission reduction actions.

Technological progress and rebound effect in China's nonferrous metals industry: An empirical study

As one of China's mainstay and six major energy-intensive industries, the nonferrous metals industry faces the intense contradiction between economic growth and energy & environment constraints. Technological progress does not only realize the energy savings, but also causes rebound effect by promoting output growth. Although the rebound effect is an important topic, there is still very little empirical research that focuses on the nonferrous metals industry in China. Using the LMDI method and the total factor productivity model (to calculate parameters), we estimate the size of the rebound effect in China's nonferrous metals industry over the period 1985–2014. According to the results, the average rebound effect is approximately 83.02% with a downward trend, which indicates that most of the expected energy savings are mitigated. The rebounds with a strong fluctuation are comparatively discussed in various periods, suggesting that China cannot count only on technological progress to save energy and reduce emission. Furthermore, the government should apply economic instruments, such as energy pricing mechanism reform, resource tax, and carbon tax, as supplements to realize the targets of energy conservation and emission reduction. Additionally, optimizing sub-sector structure and promoting substitution also play a significant role in the mitigation of the rebound effect.

Rebound effect of efficiency improvement in passenger cars on gasoline consumption in Canada

The fossil fuel-driven transport sector has been one of the major contributors to CO2 emission across the world keeping it on the energy policy agenda for the past three decades. Canada ranks second in gasoline consumption among OECD countries and Canadian gasoline expenditure share has been increasing since the 1990s. Fuel efficiency policies aim to decrease gasoline consumption; however, the effect can be mitigated by changes in consumer behavior such as traveling more distances — a rebound effect. Thus, the effectiveness of fuel efficiency policy is dependent on the magnitude of the rebound effect. In this paper, we estimate the rebound effect for personal transportation in Canada using data from the household spending survey for the period 1997–2009. The model includes a system of expenditure share equations for gasoline, other energy goods, and non-energy goods specified by AIDS and QUAIDS models and estimated by the nonlinear SUR method. Our estimation results show a rather high average rebound effect of 82–88% but with significant heterogeneity across income groups, provinces, and gasoline prices. Specifically, the rebound effect ranges from 63 to 96% across income groups and provinces and increases with gasoline prices.

Assessing the rebound effect using a natural experiment setting: Evidence from the private transportation sector in Israel

Subsidizing energy-efficient technologies is considered by energy and environmental organizations to be one of the most effective policies for decreasing energy consumption. In the transportation sector such policies are becoming ever more popular, and have been implemented in a considerable number of countries in recent years. Because these policies promote energy-efficient cars with lower usage costs, they may rebound and increase the distances traveled by households that have switched to energy-efficient cars. From an econometric perspective, a subsidization policy can be used as a valid instrument to identify the households’ choice of energy efficiency levels of the cars they own. This identification, in turn, can be utilized to account for endogeneity in the estimation of a rebound effect. The present study uses a natural experiment setting of such a policy implemented in Israel in 2009. The empirical results indicate a fairly large average rebound effect of 40%. The results also indicate that while the policy indeed encouraged the purchase of energy-efficient cars, households that bought a new or used car during the surveyed period did not generate a rebound effect of a different magnitude compared with other households that did not. We discuss the implications of our findings.

The rebound effect in the aviation sector

The rebound effect, i.e., the (partial) offset of the energy efficiency improvement potential due to a reduction in marginal usage costs and the associated increase in consumer demand, has been extensively studied for residential energy demand and automobile travel. This study presents a quantitative estimate of the rebound effect for an air traffic network including the 22 busiest airports, which serve 14 of the highest O–D cities within the domestic U.S. aviation sector. To satisfy this objective, passenger flows, aircraft operations, flight delays and the resulting energy use are simulated. Our model results indicate that the average rebound effect in this network is about 19%, for the range of aircraft fuel burn reductions considered. This is the net impact of an increase in air transportation supply to satisfy the rising passenger demand, airline operational effects that further increase supply, and the mitigating effects of an increase in flight delays. Although the magnitude of the rebound effect is small, it can be significant for a sector that has comparatively few options for reducing greenhouse gas emissions.

Energy Rebound Effect in Guangdong

Since the view that energy efficiency improvement would increase rather than reduce energy consumption, so-called rebound effect, was put forward and has been the focus that is encouraging a fierce debate within mainstream economics. This paper tries to introduce an improved estimation model by efficiency share decomposed from energy intensity, based on IPAT equation to estimate the rebound effect of three major regions in Guangdong, together with redistricting Guangdong applying hierarchical clustering analysis. The result shows the average rebound effect of low-intensity high-yield area, high-intensity low-yield area, and low-intensity low-yield area, is 17.91%, 10.82% and 8.10%, correspondingly. While the empirical study provides support of existence of rebound effect, it does suggest we should not only rely on improving energy efficiency, but also using market instruments such as resources taxes, to reinforce the energy savings.

Heterogeneity in the rebound effect: Further evidence for Germany

Rebound effects measure the behaviorally induced offset in the reduction of energy consumption following efficiency improvements. Using both panel estimation and quantile regression methods on household travel diary data collected in Germany between 1997 and 2009, this study investigates the heterogeneity of the rebound effect in private transport. With the average rebound effect being in the range of 57% to 62%, our results are in line with a recent German study by Frondel, Peters, and Vance (2008), but are substantially larger than those obtained from other studies. Furthermore, our quantile regression results indicate that the magnitude of estimated fuel price elasticities – from which rebound effects can be derived – depends inversely on the household's driving intensity: households with low vehicle mileage exhibit fuel price elasticities, and hence rebound effects, that are significantly larger than those for households with high vehicle mileage.

Heterogeneity in the Rebound Effect – Further Evidence for Germany

Rebound effects measure the behaviorally induced off set in the reduction of energy consumption following efficiency improvements. Using both panel estimation and quantile-regression methods on household travel diary data collected in Germany between 1997 and 2009, this study investigates the heterogeneity of the rebound effect in private transport. With the average rebound effect being in the range of 57% to 62%, our results are in line with a recent German study by FRONDEL, PETERS, and VANCE (2008), but are substantially larger than those obtained from other studies. Furthermore, our quantile-regression results indicate that the magnitude of estimated fuel price elasticities – from which rebound effects can be derived – depends inversely on the household’s driving intensity: Households with low vehicle mileage exhibit fuel price elasticities, and hence rebound effects, that are significantly larger than those for households with high vehicle mileage.

Heterogeneity in the Rebound Effect: Further Evidence for Germany

Rebound effects measure the behaviorally induced offset in the reduction of energy consumption following efficiency improvements. Using both panel estimation and quantile-regression methods on household travel diary data collected in Germany between 1997 and 2009, this study investigates the heterogeneity of the rebound effect in private transport. With the average rebound effect being in the range of 57% to 62%, our results are in line with a recent German study by FRONDEL, PETERS, and VANCE (2008), but are substantially larger than those obtained from other studies. Furthermore, our quantile-regression results indicate that the magnitude of estimated fuel price elasticities – from which rebound effects can be derived – depends inversely on the household’s driving intensity: Households with low vehicle mileage exhibit fuel price elasticities, and hence rebound effects, that are significantly larger than those for households with high vehicle mileage.