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Defining the Rebound Effect
Abstract
This paper gives rigorous definitions of the rebound effect, not only in the well described single commodity case (Khazzoom, 1980. The Energy Journal 1(4), 21–40.), but also for a multiple commodity case. It is shown that the familiar laws for the single case do not hold for the multiple case. The paper describes the state of the art of empirical estimation of the rebound effect, with special focus on the estimates done for the Netherlands. We conclude that according to every definition, empirical evidence shows that the RE is probably small: between 0 and 15%.
... It posits that the expected energy savings resulting from improvements in energy efficiency may not be fully realized (Ouyang et al., 2018). It is formally defined as the unrealized segment of potential energy savings resulting from enhanced energy efficiency (Berkhout et al., 2000). This notion is intricately linked to the behavioral and systemic responses triggered by the enhanced utilization efficiency of resources facilitated by the adoption of new technologies, as elucidated by various researchers (Greening et al., 2000;Ouyang et al., 2010;Saunders, 1992;Wang et al., 2012). ...
... Table 3 displays the 10 most-cited articles regarding the "rebound effect" that were included in the analysis. The most cited references are Greening et al. (2000), with 1359 total citations; Sorrell et al. (2009), with 647 total citations; and Berkhout et al. (2000), with 585 total citations. Taking into account the Google Scholar database, which is not limited to the WoS or Scopus indexes, the most cited papers in the table received a total of 11,467 citations. ...
... The blue cluster represents basic conceptual studies (e.g., Barker et al., 2009;Berkhout et al., 2000;Binswanger, 2001;Brookes, 1990;Dimitropoulos, 2007;Grepperud & Rasmussen, 2004;Roy, 2000;Saunders, 1992;Schipper & Grubb, 2000;Wei, 2010). In this cluster, pioneering studies that attempt to create a conceptual framework for the rebound effect stand out. ...
The energy rebound effect, characterized by increasing energy use despite enhanced efficiency, has emerged as a complex interdisciplinary topic in the literature, reflecting its significance in both production and consumption sustainability. Recognizing the pivotal role of academic research in shaping energy management strategies and policies, this study conducted a comprehensive bibliometric review, accessing 530 articles from major citation indexes. This analysis provides insights into the evolution of the energy rebound field and potential future directions. Understanding the existing literature on the rebound effect serves as a valuable foundation for forthcoming research endeavors, addressing the intricate challenge of reconciling energy efficiency with sustainable energy consumption and production. The review explores the extensive literature on the energy rebound effect, highlighting a predominant focus on residential (e.g., cooling, heating, lighting, transportation) and industrial energy consumption in the majority of studies. Empirical applications primarily emphasize the measurement of the energy rebound effect, with a notable trend of increasing research concentration in China in recent years. Additionally, there is a growing body of economy‐wide analyses in this field. However, the literature exhibits complexity in both the analyses conducted and the methods employed for measuring the rebound effect. Research gaps are apparent, numerous studies tend to concentrate solely on the rebound effect at the overall energy consumption level, neglecting variations in energy types and the behavioral patterns of economic actors. Furthermore, despite consistent findings of a higher rebound effect in developing nations, there is a noticeable lack of scholarly literature addressing this issue about these countries.
This article is categorized under: Sustainable Energy > Energy Efficiency
Human and Social Dimensions > Behavioral Science
Policy and Economics > Governance and Regulation
... Brookes added a macroeconomic viewpoint, monitored greenhouse gas and CO 2 emissions, and discovered that the RE theme responded to the green surge. Researchers have noted the complexity of the RE, with direct or first-order effects causing indirect or second-order effects [18]. Furthermore, the literature identifies three categories of REs: direct, indirect, and economy-wide [19][20][21]. ...
... Platform effects emerge when new services are made available, influencing the underlying factors that determine production and consumption levels and patterns. REs have been extensively studied in economics and are typically defined as those resulting from changes in relative prices: when a product or service becomes more efficient, its operating costs per unit decrease, which may lead to greater utilisation [18]. ...
... Figure 1 illustrates the total percentage of each category. studied in economics and are typically defined as those resulting from changes in relative prices: when a product or service becomes more efficient, its operating costs per unit decrease, which may lead to greater utilisation [18]. ...
A product–service system (PSS) is a concept concerning sustainability, as it offers the opportunity to decouple economic success from material consumption, thereby reducing the environmental impact of economic activities. However, researchers have identified significant barriers frequently impeding sustainability potential, which are called rebound effects. Unfortunately, the existing studies are insufficient, and there are few published studies on the actual avoidance of the rebound effect, which is a significant limitation for practical applications for decision-makers and policymakers. Therefore, this study aims to conduct a comprehensive bibliometric review of the relationship between the rebound effect and PSSs, including its drivers and mitigation strategies. This study incorporates multiple perspectives to map and analyze the landscape of rebound effect research in the context of PSSs and used 152 articles from a systematic literature review covering all publication years. Using the Scopus and Web of Science database, journals, citations, authors, and keywords were identified. This study identified the annual trend of research, listed the most influential articles, and uncovered six research topic clusters related to the rebound effect and PSSs. As an innovative feature of this study, it categorised the identified drivers based on their contextual dependencies to elucidate their interrelationships. This study also presents a categorisation of mitigation strategies based on the type of approach. This study is expected to support decision-makers and practitioners in developing sustainable PSS implementation strategies.
... The magnitude of the rebound effect is measured as the fraction of reduced FLW offset by increased consumption 39,40 . Similar to previous theoretical models 32 , we assume that reducing food loss increases supply (because previously lost food now goes to market) and ...
... 45), sometimes exceeding this [46][47][48][49] in a condition known as 'backfire'. However, other studies suggest that energy backfire effects are rare [36][37][38][39] . Energy rebound effects appear to increase in magnitude with the level of aggregation 45,46 and with the number of stages in the supply chain 50 . ...
... In general, the greater the flexibility of the economy to adjust production (and consumption) to accommodate energy efficiency gains, the larger the rebound magnitude 46,51 . Magnitudes of rebound effects can also vary substantially according to the type of goods or services involved, the economic and policy context 39,40,52 , and the stage of economic development 53 . Figure 3 shows the distribution of projections of waste and loss avoided as well as the change in the quantity traded (in units of mass: Mt yr −1 ), by SDG-defined region, for cereals, fruits and vegetables, and meat (Supplementary Table 8b-d shows these results for all food types). ...
Reducing food loss and waste (FLW) could lessen the environmental impacts of food systems and improve food security. However, rebound effects—whereby efficiency improvements cause price decreases and consumption increases—may offset some avoided FLW. Here we model rebounds in food consumption under a scenario of costless FLW reduction. We project that consumption rebound could offset 53–71% of avoided FLW. Such rebounds would imply similar percentage reductions in environmental benefits (carbon emissions, land use, water use) and improvements in food security benefits (increased calorie availability), highlighting a tension between these two objectives. Evidence from energy systems suggests that indirect effects not included in our analysis could further increase rebounds. However, costs of reducing FLW would reduce rebounds. Rebound effects are therefore important to consider in efforts aimed at reducing FLW.
... On the other hand, while technological progress can promote the synergistic development of carbon emission reduction and economic growth, improving energy efficiency [124], it may also lead to the 'Jevons Paradox: Energy Rebound Effect' [96,125]. The rebound effect implies that the anticipated energy-saving effects from improved energy efficiency are offset by increased energy demands, diminishing the effectiveness of environmental policies [126,127]. Studies confirm the impact mechanism of the energy rebound effect on industrial development and the variability of different paths of energy rebound effects through internalizing energy efficiency and simulating the impact of different types of energy efficiency improvements on energy consumption [128][129][130][131]. High-energy-consuming sectors, like the steel [132], construction [133], and transportation [126] industries, are significantly affected by the energy rebound effect. Moreover, in some countries, like Denmark [134], Norway [135], the United Kingdom [136], and China [129], the energy rebound effect in the transportation sector typically encompasses long-term and shortterm effects. ...
... The rebound effect implies that the anticipated energy-saving effects from improved energy efficiency are offset by increased energy demands, diminishing the effectiveness of environmental policies [126,127]. Studies confirm the impact mechanism of the energy rebound effect on industrial development and the variability of different paths of energy rebound effects through internalizing energy efficiency and simulating the impact of different types of energy efficiency improvements on energy consumption [128][129][130][131]. High-energy-consuming sectors, like the steel [132], construction [133], and transportation [126] industries, are significantly affected by the energy rebound effect. Moreover, in some countries, like Denmark [134], Norway [135], the United Kingdom [136], and China [129], the energy rebound effect in the transportation sector typically encompasses long-term and shortterm effects. ...
Green development in the transportation industry is a new type of development. As the huge energy consumption and carbon emissions generated by the transportation industry have caused many environmental problems, the healthy and environmentally friendly mode of industrial development has received more and more attention. However, the quantification of green development in the transportation industry varies in terms of boundaries, scope, and methods. Due to digital empowerment, the degree of influence and direction of the factors affecting the green development are not fixed. The prediction of future development prospects is relatively single-minded, lacking a comprehensive simulation scenario setting from multiple perspectives. This paper systematically reviews the research progress of green development of the transportation industry from three aspects: development performance assessment, influence mechanism analysis, and development path exploration. After a critical analysis, this study concludes that (1) a clear methodology is needed to assess the direct and indirect non-desired output results of the transportation industry; (2) considering the endogenization of the level of technology, the influence of the interaction between the influencing factors, etc., on the degree and direction of the role of the factors, a more scientific econometric model should be established for in-depth discussion; (3) resident travel options are an important factor affecting environmental issues in transportation. Carbon emission projections and analyses of emission reduction scenarios should integrate the multiple possibilities of residential preferences and policy incentives. The findings of this paper provide valuable references to the energy saving and emission reduction goals of the transportation industry, and the coordinated development of the industry and the economy.
... Their study obtained that patents on fossil energy technologies have no significant effect on CO 2 emissions, while patents on carbon-free energy technologies have a significant inhibitory effect on CO 2 emissions, which is more significant in the eastern region. Berkhout (2000) [56] proposes a new definition from a microeconomics and macroeconomics perspective. When technological progress leads to an increase in energy efficiency, the energy consumption for producing the same unit of product will decrease. ...
... Their study obtained that patents on fossil energy technologies have no significant effect on CO 2 emissions, while patents on carbon-free energy technologies have a significant inhibitory effect on CO 2 emissions, which is more significant in the eastern region. Berkhout (2000) [56] proposes a new definition from a microeconomics and macroeconomics perspective. When technological progress leads to an increase in energy efficiency, the energy consumption for producing the same unit of product will decrease. ...
Innovation in new energy technologies is a key driver in China’s efforts to achieve its environmental goals. However, the ability of different regions to develop and utilize new energy technologies may depend on their level of economic development. Based on a two-way fixed-effects panel data model, this paper empirically analyses the industry carbon emission reduction effect of new energy technology innovation and its heterogeneous performance at different stages of economic development, using data from 30 provinces and cities in China from 2000 to 2019. The results show that new energy technology innovation generally promotes CO2 emissions in China. The specific effects are closely related to the characteristics of the industry and the stage of economic development. At the same time, the implementation of environmental regulations will inhibit this positive effect, while the adjustment of the industrial structure may promote this positive effect. This paper discovers the mechanism of heterogeneity in new energy technology innovation among different provinces with different levels of economic development. This finding helps to fully assess the carbon emission reduction capacity and potential of different provinces and facilitates the rational disaggregation and formulation of climate policy goals among regions.
... They do not necessarily (or at least not exclusively) lead to more demand for the very good that is being more efficiently produced. Monetary savings from the more efficient production of a good or service can be spent on different energyand resource-consuming activities, for example-this is known as the 'income effect' [ 10 ]. Additionally, a lower price makes a product relatively more affordable than other similar products, for which it may subsequently partly substitute-a phenomenon known as the 'substitution effect'. ...
... Additionally, a lower price makes a product relatively more affordable than other similar products, for which it may subsequently partly substitute-a phenomenon known as the 'substitution effect'. The increased consumption can thus propagate to other goods and sectors [ 10 ], making income and substitution effects prime examples of what is often called 'indirect rebound effects' [ 22 ]. ...
As part of global climate action, digital technologies are seen as a key enabler of energy efficiency savings. A popular application domain for this work is smart homes. There is a risk, however, that these efficiency gains result in rebound effects , which reduce or even overcompensate the savings. Rebound effects are well-established in economics, but it is less clear whether they also inform smart energy research in other disciplines. In this paper, we ask: to what extent have rebound effects and their underlying mechanisms been considered in computing, HCI and smart home research? To answer this, we conducted a literature mapping drawing on four scientific databases and a SIGCHI corpus. Our results reveal limited consideration of rebound effects and significant opportunities for HCI to advance this topic. We conclude with a taxonomy of actions for HCI to address rebound effects and help determine the viability of energy efficiency projects.
... On the other hand, relying on just WCSTs implementation as water conservation policy may present some 'side-effects' as increased energy consumption and increased water consumption at the water-basin level (i.e. 'rebound effect') (Berkhout et al., 2000;Sorrell and Dimitropoulos, 2008). More precisely, irrigation is closely related to the energy consumption increase (Espinosa-Tasón et al., 2020) that may be palliated by increasing the use of renewables, mainly solar photovoltaic systems (Hilarydoss, 2021). ...
... In the context of buildings, the introduction of energy-efficient technologies could trigger increased energy demand due to reduced costs (Massié and Belaïd, 2024). This ultimately leads to reduced overall energy savings (Berkhout et al., 2000;Dimitropoulos, 2007;Gillingham et al., 2016;Belaïd et al., 2020, Belaid et al., 2020. Furthermore, the concept of the "direct rebound effect" refers to the modification in energy consumption behavior that occurs as a result of both the substitution and income effects on the demand for energy-efficient services, as defined by Sorrell et al. (2009). ...
The rebound effect refers to the phenomenon where energy efficiency improvements lead to increased energy
consumption, offsetting some of the expected energy savings. This article aims to estimate the direct rebound
effect of residential electricity consumption in Saudi Arabia and explores potential solutions to mitigate its
impact. Understanding the magnitude of the rebound effect is crucial for policymakers to develop effective
energy conservation strategies. This study employs a time-series modeling approach, using a dataset covering 31
years, 1990–2021, and four regions within Saudi Arabia, incorporating various socioeconomic and energyrelated variables. The magnitude of the rebound effect in residential electricity consumption in the Kingdom,
which varies across regions, ranges from 41% to 71%. Since the inception of the first wave of the energy price
reform in 2016, the Kingdom has witnessed a power consumption rebound in the residential sector totaling 39.02
TWh (6.5 Twh per annum), and a total of 28.13 Mt. in CO2 equivalent emissions (4.69 Mt. in CO2 equivalent per
annum) during the period of 2016–2021. These findings add to the existing literature on the rebound effect,
further enriching our understanding of this complex phenomenon and its implications. They also provide
valuable insights for policymakers and energy planners in Saudi Arabia, helping them develop effective strategies
to minimize the rebound effect and promote energy conservation.
... RE is defined in the energy economic sector as an improvement in energy efficiency that leads to a reduction in the price of products or services and an unexpected increase in consumer demand (Berkhout, Muskens and W. Velthuijsen, 2000). These unintended and unavoidable increases in demand reduce the predicted environmental benefits as a negative consequence of enhanced efficiency (Zink and Geyer, 2017). ...
Circular economy (CE) strategies are largely adopted in the manufacturing sector. Nevertheless, the benefits of circular strategies could be reduced by the occurrence of the rebound effect (RE), defined as resource overuse due to improved efficiency in a system. Understanding the causes, mechanisms, and characteristics of CE’s REs is therefore crucial for the effective implementation of CE strategies in the manufacturing sector. The main gap concerns the limited understanding of the occurrence of RE within CE in manufacturing. To this concern, five domains (i.e., business models, drivers, product lifecycle management (PLM), circular manufacturing ecosystem, and socio-economic aspects) have been initially identified in the twofold CE-RE domain. Starting from these, the paper aims to investigate and map the relations among these dimensions and unveil the related type of RE for each of them. To address this objective, a conceptual map, grounded on a systematic literature review (SLR), has been obtained to explore the five dimensions. The conceptual map showed the relations between the five di- mensions and the possible occurrence of RE types (i.e., direct, indirect, economy-wide, and transformational). It turned out that the five dimensions are closely related. For example, socio-economic aspects were influenced by the adoption of circular business models and have a role in PLM strategies. Instead, from a RE perspective, socio- economic aspects dimension, linked to business model and PLM ones, could generate direct and indirect RE. The driver dimensions related to circular manufacturing and business models could cause economy-wide and transformational RE. The map of the relations obtained offers an initial framework to be exploited to prevent and mitigate possible CE’s REs occurring in manufacturing.
... Consequently, this leads to an increase in consumer demand and subsequently higher levels of consumption. Nevertheless, this augmented demand can have the unintended consequence of elevating overall energy consumption, thereby offsetting the energy conservation advantages initially derived from technological advancements (Hanley et al., 2009;Turner & Hanley, 2011;Frondel et al., 2008;Hymel et al., 2010;González, 2010;Berkhout et al., 2000). ...
Industrial robot applications’ influence on energy consumption is a significant area of concern in both theoretical and practical sectors. This study used panel data from 2006 to 2019, covering multiple Chinese provinces. It applied panel regression and various statistical methods to investigate the potential impact of industrial robot deployment on energy consumption. Additionally, the research incorporated spatial variables, including adjacency matrices, inverse geographical distance matrices, inverse economic distance matrices, and inverse industrial scale matrices. These spatial components were used in spatial Durbin models, spatial Durbin models with quadratic terms, and spatial Durbin models with lag terms. The analyses aimed to examine the spatial spillover effects of industrial robots on energy consumption, explore nonlinear characteristics in these effects, and distinguish between short-term and long-term impacts. The research findings are as follows. Firstly, energy consumption can be greatly reduced by industrial robot applications, and there are heterogeneous effects based on geographical location and income levels. Secondly, industrial robot applications have spatial spillover effects that reduce energy consumption in the neighborhood, as well as the energy consumption of other regions that border each other, are physically close together, have less economic inequality, and have similar industrial scales. Thirdly, the geographic spillage impacts of industrial robots demonstrate nonlinear characteristics, displaying a distribution pattern that resembles an inverted U shape when analyzed through the anti-economic distance matrix. Lastly, industrial robot spatial impact spillovers primarily have short-term effects with negligible long-term implications. These results provide new insights and evidence for research on the environmental impacts of industrial robots, factors influencing energy consumption, and spatial planning for industrial development.
... This claim corresponds to the understanding of sustainable innovations as bundles of novelties (Dabard and Mann 2023), and more generally, it is linked to the argument that purely technological solutions will not suffice for achieving sustainability (Grunwald 2007;Sterman 2008), as the depletion of natural resources is at best postponed by new technologies (Goncz et al. 2007), which is also reflected in time lags of market-driven diffusion and application of new technologies (Jacobsson and Bergek 2011). Furthermore, rebound effects can offset efficiency gains from new technologies (Berkhout et al. 2000). They can even lead to Content courtesy of Springer Nature, terms of use apply. ...
Innovations incorporating environmental and social considerations can address many sustainability challenges. Such sustainable innovations emerge in networks often comprising actors from business, academia, civil society, and government. The crucial interactions here are the (co-)creation and transfer of knowledge, mutual learning, and experimentation in different environments. To better understand these knowledge processes and hence the eventual outcome of sustainable innovations, we analyze the actors’ relationships with the help of proximity and its five dimensions, namely geographical, cognitive, institutional, organizational, and social proximity. Building upon findings from sustainability science and innovation system theory, we present a refined proximity framework, introducing a differentiation of institutional proximity into micro- and macro-institutional proximity and a differentiation of cognitive proximity into systems-cognitive, normative-cognitive, and transformative-cognitive proximity. Analyzing examples from the literature by applying this framework, we see that all proximity dimensions and their interdependencies help to better understand knowledge processes and innovations in sustainability-oriented innovation networks. We find that such networks often depict low levels of micro-institutional and systems-cognitive proximity, which coheres with the prevalence of inter- and transdisciplinary approaches and the wide inclusion of relevant stakeholders for addressing sustainability issues. Our framework further reveals that successful networks show high levels in other proximity dimensions, with normative-cognitive proximity appearing to play a crucial role, highlighting the importance of shared goal orientations. Our results provide valuable input for the formation of sustainability-oriented innovation networks by pointing out the necessary combination of distances that allow for creativity and learning, combined with appropriate proximities for exchange and mutual understanding.
... These corporations have developed large areas of intensive irrigation leading to prolonged water crisis for other stakeholders (Muñoz, 2016;Schwarz & Mathijs, 2017;Williams & Murray, 2019). Whilst drip irrigation systems have been deployed to increase productivity, the high value of the crops produced has led to a 'rebound effect' (Berkhout et al., 2000;Sorrell & Dimitropoulos, 2008) since the water savings obtained have encouraged expansion of the irrigated area for high value crops, such as asparagus and grapes, increasing the overall withdraw of groundwater rather than conservation of the water resource itself (Berbel et al., 2015;Berbel & Mateos, 2014). ...
The agro-export boom is threatening the sustainability of water resources in many regions around the world. This is the case of the Ica valley in Peru, where in the last decades traditional agriculture has been replaced by big agricultural businesses to meet the growing international food demand. This has led to increasing land concentration by large exporting farms jointly with an increase in groundwater exploitation for irrigation. In this paper, we analyze the effect of land concentration, exporting crop specialization and irrigation intensity on groundwater sustainability using an econometric approach. Our findings highlighted an inverse relation between groundwater sustainability in terms of water withdrawal in the Ica Valley and the intensity of irrigation (drip technology), commodity specialization and concentration of large farms. More research is needed to fully understand the impacts of this very important economic activity on Peru’s natural resources, to ensure its sustainability in the long term.
... This finding is consistent with the research results of Zhou et al. (2023) who all believe that the improvement of technological level has a significant inhibition effect on carbon emissions. The improvement of technological levels will promote energy efficiency (Berkhout et al., 2000;Hanley et al., 2009), accelerate the development and application of new energy, reduce its use cost, and realize the substitution between fuels (Kang et al., 2018). Therefore, by improving the technical level of all stages of the whole life cycle of the construction industry, the current extensive development model with high energy consumption and high carbon emissions can be changed, so as to improve the energy utilization efficiency of the construction industry and reduce the LCCECI. ...
The energy saving and emissions reduction of the construction industry are crucial for China to achieve the “carbon peaking and carbon neutrality” goals. In order to promote the green development of the life cycle of the construction industry and improve the efficiency of emissions reduction. This paper examines the spatial-temporal distribution of life cycle carbon emissions in China’s construction industry (LCCECI) from 2004 to 2018. It uses the SBM-Malmquist total factor productivity (TFP) index to measure technological progress and establishes the spatial econometric model based on the STIRPAT model. The study investigates the driving factors of the LCCECI at the provincial and regional levels, aiming to provide suggestions for low-carbon development in the construction industry. The research results are as follows. ① The growth in the SBM-Malmquist TFP index of the construction industry distinctly curbs the LCCECI. ② Total population and urbanization level are not the primary driving factors for the LCCECI. The growth of per capita GDP significantly induces the LCCECI, while concurrently exhibiting a notable inhibitory effect on the LCCECI of neighboring regions. ③ The improvement of the SBM-Malmquist TFP index is conducive to the reduction of the LCCECI in the three major regions. The per capita GDP has the largest positive driving effect of the LCCECI in the eastern region, and the urbanization level the urbanization rate only significantly inhibits the growth of the LCCECI in the central region.
... Der Begriff "Rebound-Effekt" bezieht sich auf Verluste in der Menge der eingesparten Energie nach einer Steigerung der Energieeffizienz (Berkhout et al. 2000). Aus rein technischer Sicht sollte der Energieverbrauch umgekehrt proportional zu einer Steigerung der Energieeffizienz zurückgehen. ...
... For this situation, Berhout et al. believe that it is due to the existence of the "rebound effect" of energy, that is, although the improvement of technological innovation can improve energy efficiency and save resources, it may reduce the unit production cost and price of products while improving energy efficiency, leading to an increase in product demand and consumption. Ultimately, the energy saved due to the improvement of technological innovation level is offset by the energy consumed by additional consumption 22 . Jiao et al. 23 also demonstrated through empirical analysis that the increase in exports and technological innovation does indeed lead to an increase in carbon emissions. ...
It is of much importance to clarify the impact of technological innovation on carbon emission intensity for the low-carbon transformation of China's economy. This study, based on the panel data of 30 Chinese provinces and municipalities from 2010 to 2020, measures and analyzes the carbon emission intensity and the level of technological innovation, establishing a spatial econometric model to study the spatial spillover effect and a panel threshold model to analyze the nonlinear influence of technological innovation level on carbon emission intensity. The findings are as follows: First, the overall carbon emission intensity in China shows a decreasing trend from 2010 to 2020, with the average dropping from 3.09 in 2010 to 1.98 in 2020; Second, the spatial autocorrelation results reveal that the level of technological innovation and carbon emission intensity in China are obviously aggregated in the global spatial distribution pattern. Third, the regression results of the spatial econometric model show that the direct effect of technological innovation on carbon emission intensity is significantly negative at the level of 1%, that is, the improvement of the technological innovation in a certain area has a significant inhibitory effect on carbon emission intensity. Fourth, based on the level of economic development, there is a significant three-threshold effect of the level of technological innovation on carbon emission intensity in China, and the influence of the level of technological innovation on carbon emission intensity varies in the direction of existence and coefficient values within different threshold intervals. As economic development reaches the third interval, the technological innovation level has the most significant inhibition on carbon emission intensity. These findings enriches the research of the nonlinear relationship between technological innovation and carbon emission intensity, clarifies the spatial spillover effect and threshold effect between among them, and provides inspiration for better promote the low-carbon transformation of economy.
... at 10/19/2023 07:47:58PM by jaumefreire@hotmail.com via Jaume Freire Jaume Freire-González Schipper and Meyers, 1992;Schipper and Grubb, 2000; among others), while some observed that energy efficiency could be counterproductive, increasing energy use (following Brookes, 1979;Saunders, 1992Saunders, , 2000among others). Other important early contributions to the debate were Khazzoom (1989), Wirl (1997), Berkhout et al. (2000), and Binswanger (2001). In a literature review conducted by Greening et al. (2000) of over 75 estimates of the rebound effect, the authors concluded that the range of estimates for the size of the rebound effect was from low to moderate. ...
Improvements in resources efficiency and resources conservation are less effective at reducing resources use than predicted by engineering calculations due to socio-economic and behavioral responses taken by individuals, firms, institutions and governments. The mechanisms activated by these responses produce the so-called ‘rebound effect’, that is, the difference between the potential and the actual environmental benefits. When the response leads to an increase of resources use in relation to the initial situation, the effect is known as ‘Jevons’ Paradox’. In this case, efficiency improvements and resources conservation become counterproductive in environmental terms. After more than four decades of research there is consensus on its existence, but not on its size. This effect may have a profound impact on sustainability targets. Energy, climate, and in general, environmental and sustainability policies need to take into account this effect when they are assessed, designed and implemented.
... 2 This phenomenon is regarded to as the energy efficiency rebound effect and research has been shaped by the works of Berkhout, Muskens, and W. Velthuijsen (2000); Sorrell (2007); Sorrell and Dimitropoulos (2008); Gillingham, Rapson, and Wagner (2016). A deeper analysis of the rebound effect is not within the scope of this paper. ...
The prospect of climate change and the danger of catastrophic global warming have
evoked several climate treaties that aim to find a solution to the public goods dilemma of emission reduction. In this regard, residential energy consumption poses a great opportunity for energy savings and this bachelor thesis provides an overview of the literature that addresses determinants of residential electricity demand, reviews financial and non-financial policy instruments, and analyses possible regulatory actions for energy conservation and the transition to a low-carbon society.
... This study reveals that TP in upstream sectors has stronger rebound effects than mitigation potentials and would lead to global GHG emission increments (e.g. the gas and petroleum and coal products sectors). In a narrow sense, the rebound effect refers to an increase in energy use induced by an improvement of energy efficiency (61). This study observes that an improvement in TFP can also lead to increases in energy use and GHG emissions. ...
Technological progress (TP) is a double-edged sword to global climate change. This study for the first time reveals rebound and mitigation effects of efficiency-related TP in global value chains (GVCs) on greenhouse gas (GHG) emissions. The integrated effects of TP depend on the positioning of sectors in GVCs. The cost-saving TP in upstream sectors would stimulate downstream demand. This produces stronger rebound effects than mitigation potentials and leads to global GHG emission increments (e.g. TP in the gas sector of China and petroleum and coal products sector of South Korea). In contrast, sectors located in the trailing end of GVCs have greater potentials for GHG emission mitigation through TP, mainly due to the reduction of upstream inputs. (e.g. the construction sector of China and dwelling sector of the United States). Global GHG emissions and production outputs can be either a trade-off or a win–win relationship on account of TP than rebound effects, because TP in different sectors could possibly increase or decrease the emission intensity of GVCs. This study could recognize the most productive spots for GHG emission mitigation through efficiency-related TP. It provides a new perspective for international cooperation to promote global GHG emission mitigation.
... The second is the effective prevention of haze through technological innovation, for example, enterprises reduce future haze pollution by improving or retrofitting emission treatment equipment to achieve haze control effects [19]. Khazzoom [20] and Berkhout et al. [21] have pointed out that technological innovation, while improving energy efficiency by enhancing the performance of production equipment, can also result in reduced unit production costs and subsequently lead to increased demand and use of production equipment, thereby potentially elevating overall energy consumption. As a consequence, they argue that technological progress can promote haze pollution to some extent. ...
The rapid economic growth of China has caused significant adverse effects on the environment. Meanwhile, technological innovation, a fundamental driver of economic development and social progress, plays a pivotal role in mitigating haze pollution. This study comprehensively examines the influence of technological innovation on haze pollution in the Yangtze River urban agglomeration, using the STIRPAT model and analyzing research data from 2004 to 2020. Additionally, the study investigates the specific moderating role of urban spatial structure in the relationship between technological innovation and haze pollution. The findings reveal that technological innovation in the middle reaches of the Yangtze River urban agglomeration can effectively curtail haze pollution, and its impact extends to surrounding areas through spillover effect. The polycentric urban spatial structure significantly enhances the haze-reducing effect of technological innovation in the region. Notably, in cities with a strong level of environmental regulation, the urban spatial structure plays a substantial role in augmenting the haze-reducing impact of technological innovation. The policy implications of this research underscore the importance of continuous improvement in technological innovation within the middle reaches of the Yangtze River urban agglomeration. To address haze pollution in future development, the adoption of a polycentric development strategy and the establishment of sound environmental governance policies are recommended.
... Such results indicate that technology advances can, to some degree, improve the efficiency of WEF utilization and therefore decrease WEF consumption per unit of GDP. However, benefits from technology could make resources cheaper and generate new demand, thereby gradually offsetting the impact of technology progress and creating a "rebound effect" [68]. ...
Water, energy, and food are indispensable resources for socioeconomic development, and are highly interwoven in urban activities. Clarifying spatial differences in resource consumption is of great significance for coordinated management. However, there is still a lack of a unified assessment for water–energy–food (WEF) nexus flow analysis. This study proposes a comprehensive framework to investigate WEF utilization based on a modified multi-regional input–output (MRIO) analysis. Taking the case of the Yangtze River Delta region, we first inventoried embodied water–energy–food consumption from 2012 to 2017. Then, decoupling analysis and the Logarithmic Mean Divisia Index (LMDI) method were applied to explore decoupling states and identify driving factors. The results show that overall embodied WEF consumption experienced a downward trend from 2012 to 2017, and different provinces varied significantly. Jiangsu had the largest consumption of water and energy, while Anhui contributed a big chunk to food consumption. The manufacturing sector heavily relied on WEF resources and had a great impact on the ecological environment. The decoupling performance indicated a general trend of weak decoupling and strong decoupling in most provinces, with the mining, electricity, and gas supply sectors contributing most to positive decoupling, and the service sectors devoting the most to negative decoupling. As for resource type, water ecological footprint decoupled more than energy and food ecological footprints. Technology level and industrial structure had a major effect on the realization of decoupling, while economic output and population scale were the main restraining factors. Finally, we provide some differentiated policy recommendations for coordinated resource management.
... At the macroeconomic level, Howells et al. (2010) did incorporate macroeconomic feedback in a rebound analysis for South Korea. Furthermore, Berkhout et al. (2000) investigated multiple single-sector shock scenarios for the Netherlands' rebound effects. Schipper and Grubb (2000) compared the rebound effects for IEA countries by breaking down the economy into 10 manufacturing sectors, 5 transportation sectors, and the service sector. ...
Based on what we know today, there is a strong linkage between solar activity and the energy sector. In this work, we study the linkage between extreme solar events and the US energy sector, utilizing a sectoral supply chain dataset that spans the period 1998–2014. To do so, we propose a novel methodological approach by linking all the sectors of the economy’s supply chain through a network-theoretic production-based framework. We estimate the network system using a global vector autoregressive model that incorporates dominant entities. Additionally, to capture the indirect spillover impact of extreme solar events on the rest of the sectors in the US economy, we develop, for the first time in the literature, the indirect global impulse response functions. We find that solar events affect directly the energy sector and, indirectly, most of the other sectors of the US economy. More precisely, solar phenomena indirectly provoke positive and significant responses in manufacturing, transportation, information and communication, finance and insurance, real estate, and business activities, through the energy sector. Conversely, agriculture, forestry, fishing, and mining sectors exhibit negative and significant responses. Construction, accommodation and food service activities, and wholesale and retail trade sectors do not show any significant response. These results give credence to the impact of solar events on the US sectoral economy, directly and indirectly, through the proposed IGIRFs.
... 35 Drèze, Sen (1990). 36 Np. Berkhout et al. (2000). wysokich technologii miałyby problem w konkurowaniu z tradycyjnymi, starszymi technologicznie rozwiązaniami. ...
Design thinking (DT, myślenie projektowe) pojawia się dziś w wielu kontekstach – od biznesu, przez edukację, po innowacje społeczne – jako atrakcyjna metoda rozwiązywania szerokiego zakresu problemów. Jednak mimo jego popularności oraz faktu, że podejście to wykorzystuje pojęcia i metody badawcze zapożyczone z socjologii i innych nauk społecznych, zaskakująco mało uwagi poświęca się mu w refleksji socjologicznej. Celem tego artykułu jest uzupełnienie tej luki nie tylko przez omówienie głównych założeń podejścia design thinking, ale przede wszystkim przez dokonanie jego socjologicznej krytyki oraz przedstawienie możliwych wariantów reakcji socjologii jako dyscypliny na popularność tego podejścia. Artykuł ma charakter dyskusyjny i jest inspirowany badaniami z zakresu studiów nad nauką i technologią (STS), podejściem krytycznym w socjologii oraz koncepcją pola instytucjonalnego Pierre’a Bourdieu. Wyniki przedstawionej analizy pokazują, w jakim sensie design thinking może być atrakcyjne dla socjologii jako dyscypliny – nie tylko jako pewien zbiór narzędzi, ale jako odmienna, a przy tym inspirująca perspektywa poznawcza (akceptująca prowizoryczność i pragmatyzm), realizująca w pewnym stopniu program socjologii syntetycznej. Jednocześnie artykuł pokazuje, że podejście to jest podatne na krytykę jako operujące uproszczonymi założeniami, solucjonistyczne i uwikłane w społeczno-ekonomiczne zależności.
The direct rebound effect occurs when the expected decrease in energy consumption incurred by energy efficiency enhancement is partially, or at times even exceedingly, offset by an unexpected increase in energy consumption. One method used to capture its magnitude incorporates the usage of own-price elasticities of energy demand as a proxy. In this study, we explore the suitability of this approach under the context of China, Japan, and Korea for residential electricity. We synthesized the diverse estimates of the own-price elasticity of residential electricity demand and employed a meta-analysis approach to derive a representative estimate corresponding to each country. Our results show that the meta-analytical own-price elasticities of residential electricity demand are \(-0.500\) for China, \(-0.645\) for Japan, and \(-0.318\) for Korea. Using these numbers, we conducted direct comparisons with the magnitude of direct rebound effects, and identified that the effectiveness of using own-price elasticities of electricity demand as a substitute for direct rebound effects varies depending on geographical focus, methodology, and time scale. Also, we argue that viewing estimates of the own-price elasticity of electricity demand as a ballpark estimate for the magnitude of direct rebound effects is a more appropriate approach, than as a mirror.
The circular economy (CE) has risen in prominence as a potential model to improve sustainability. However, the relationship between circularity and sustainability is complex. This chapter reviews the literature debating if and when CE practices lead to sustainability gains. The chapter discusses conceptualizations of CE and sustainability; analyzes mechanisms linking CE implementation to varied, ambiguous, or even contradictory sustainability impacts; appraises common CE and sustainability assessment methods and tools; discusses gaps in evaluating this nuanced relationship; and proposes an integrated assessment framework focused on life cycle thinking, local-to-global scale effects, and capturing unintended consequences of CE activities. Findings indicate that while CE principles hold promise for enabling sustainability, the dynamics between circularity and sustainability are highly case-specific. Developing capabilities to consistently quantify when and to what extent “circular” practices lead to “sustainable” outcomes is an open challenge requiring continued empirical demonstration.
This chapter provides an overview of past, present and future perspectives on the relationship between ICT and sustainable development in research, with a focus on perspectives adopted within WG 9.9. While early research concentrated on the adverse effects of ICT on the environment, including energy usage, hazardous chemicals in production, and electronic waste, the discourse has evolved to emphasize the potential of ICT to promote sustainable development and offer economic, social, and environmental benefits. WG 9.9 emphasizes that ICT can indeed offer sustainability-related benefits, such as dematerialization and optimization. However, technology, including ICT, is currently not geared towards sustainability, and incremental improvements are not sufficient to promote sustainable futures. Instead, a narrow and individualistic focus risks reinforcing an unsustainable status quo. Researchers interested in ICT and sustainable development should take a more critical stance and promote radical societal transformations towards sustainable futures. Among other things, this includes questioning growth, both in terms of technology and the economy, adhering to planetary boundaries, energy and resource limits, and promoting sustainable practices, rather than imposing behavioral changes.
Against the dual backdrop of China vigorously promoting high-speed railways (HSR) construction and establishing an ecological civilization system, HSR as urban transportation infrastructure, is currently gaining growing attention from the academic community due to its environmental benefits as well as its effects in energy conservation and emission reduction. In this context, this research treats the initiation of HSR as a quasi-natural experiment, meanwhile empirically examining the effect of HSR on energy structure restructuring and exploring the micro-level channels through which it operates. The empirical results validate the reduction effect of HSR opening on fuel energy consumption of industrial enterprises, especially the usage of fuel coal. This highlight remains valid across a series of robustness tests. Moreover, it is evident that the “driving effect” of enterprise technological innovation capability and the “industrial upgrading effect” of enterprise relocation are effective transmission pathways in the process of HSR opening influencing the adjustment of energy consumption structure. Moreover, the unique characteristics of enterprise, industry, and region introduce a certain degree of heterogeneity. The low-energy-consumption effect of HSR is more pronounced in high-carbon industry enterprises, technology-intensive enterprises, firms engaged in innovation pilot cities, small to the medium-sized city and resource-based city. This paper provides a new perspective on energy structure adjustment, contributing to offering solid experiences and references for environmental governance in China and other emerging economies.
Green and low carbon transition is a broad and profound economic and social systematic change. Green innovation is a critical way to promote energy saving and emission reduction. Has China continuously promoted a carbon emission trading policy to significantly promote green innovation cooperation? Taking the implementation of the carbon emission trading pilot policy as a “quasi-natural experiment,” this study answers this question by exploring the impact of the policy on green innovation cooperation. Based on data on 274 cities from 2008 to 2020, the multi-time difference-in-differences model is used to evaluate the impact of the policy on green innovation cooperation. The results reveal that the carbon emission trading pilot policy significantly improved inter- and intra-city green innovation cooperation through the upgrading effect of industrial structure and the coverage effect of digital finance compared with the non-pilot cities at the city level. In addition, there are significant differences in the policy effects among cities with different degrees of openness to the outside world and command-and-control environmental regulation.
The carbon emissions trading system (CETS) is a helpful policy instrument for separating carbon emissions from economic expansion, and it significantly impacts energy efficiency (EE). This study uses 30 Chinese provinces from 2007 to 2020 as its research samples, and classifies energy efficiency into single-factor energy efficiency (SFE) and total-factor energy efficiency (TFE), using the difference-in-differences model to examine the effect and mechanism of the CETS on EE. As an additional tool to assess the efficacy of the CETS, the corresponding evolution of the rebound effect of energy-related carbon emissions (RECE) is also calculated. This study shows that the CETS can significantly improve EE in China's pilot provinces. The influence mechanism indicates that the effect of the CETS on EE is influenced by the level of government governance, green innovation, and industrial structure optimization. Further study finds that after the CETS was carried out, the RECE in pilot provinces was higher than that in non-pilot provinces, and 31.4% of carbon emissions reduced by EE improvement rebounded. Therefore, the CETS has yet to realize its full carbon reduction potential. The study offers specific policy proposals for the enhancement of China's CETS in light of the aforementioned findings.
The urgency to address the environmental impacts of the building sector, particularly emissions allocated to building operation, necessitates immediate, informed action. Occupant behaviour is a known driver of building operational emissions. Use of Internet-of-Things (IoT) devices holds great potential in mitigating and distributing occupancy-driven energy demand, ultimately aiming for net-zero emissions. However, a full accounting of the environmental impacts and advantages is still lacking. As the adoption of IoT scales up, what will be the
environmental impact of the tools used, from sensor life cycle to data storage? This study reviews the interdisciplinary literature on life cycle assessment (LCA) of IoT in buildings, encompassing emissions from pre-deployment to end-of-life, as well as savings from reduced building operational emissions. This opens a vital discourse on the opportunities and challenges of building-related IoT.
Highlights
i) There is emerging evidence that the lifecycle impacts of IoT may not be negligible
ii) An adapted LCA framework is suitable for assessing the impacts from IoT in buildings
iii) Key variables: boundaries, units, impact categories, service lifetime, IoT benefits
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The enhancement of energy efficiency stands as the principal avenue for attaining energy conservation and emissions reduction objectives within the realm of road transportation. Nevertheless, it is imperative to acknowledge that these objectives may, in part or in entirety, be offset by the phenomenon known as the energy rebound effect (ERE). To quantify the long-term EREs and short-term EREs specific to China’s road transportation, this study employed panel cointegration and panel error correction models, accounting for asymmetric price effects. The findings reveal the following: The long-term EREs observed in road passenger transportation and road freight transportation range from 13% to 25% and 14% to 48%, respectively; in contrast, the short-term EREs in road passenger transportation and road freight transportation span from 36% to 41% and 3.9% to 32%, respectively. It is noteworthy that the EREs associated with road passenger transportation and road freight transportation represent a partial rebound effect, falling short of reaching the magnitude of a counterproductive backfire effect. This leads to the inference that the upsurge in energy consumption within the road transportation sector cannot be solely attributed to advancements in energy efficiency. Instead, various factors, including income levels, the scale of commodity trade, and industrial structure, exert more substantial facilitating influences. Furthermore, the escalation of fuel prices fails to dampen the demand for energy services, whether in the domain of road passenger transportation or road freight transportation. In light of these conclusions, recommendations are proffered for the formulation of energy efficiency policies pertinent to road transportation.
Green technology innovation (GTI) is one of the most important factors influencing agricultural carbon emission intensity (ACEI). Various studies have explored the impact of GTI on ACEI, but the path mechanism has not been fully explained. This study incorporates GTI and ACEI into the constant elasticity of substitution (CES) production function and constructs a theoretical model to analyse their direct impact mechanisms. Drawing on the substitution effect theory and the Marshall-Arrow-Romer (MAR) externalities theory, this study introduces two regulatory mechanisms: optimization of energy structure and agricultural industry agglomeration (AIG). Additionally , it explores the pathway mechanisms under the influence of spatial spillover effects based on Tobler's first law of geography. Then, taking Jiangsu Province in China as a case study, empirical tests are conducted using LSDVC and dynamic spatial SAR models. The results are as follows. (1) GTI effectively inhibits ACEI directly, and has significantly positive spatial spillover effects on ACEI reduction in the short and long terms. (2) Energy structure optimization positively regulates the effect of GTI on ACEI reduction, and energy structure optimization in nearby cities may help GTI restrain ACEI in the local city in the short term. (3) AIG has a positive regulating effect on GTI reducing ACEI, and the moderating effect of AIG has positive spillover effects in the short term. (4) When both regulatory pathways are employed simultaneously, the moderating effect of AIG in local or neighbouring areas is expected to become ineffective. These findings are useful for solving the problem of ACEI reduction by managing the transfer and distribution of GTI between different regions, considering spatial spillover and moderating effects.
In this chapter, the Jevons paradox is studied in the context of the debate on the limits to Growth. This “Jevons paradox” is part of a more general criticism of William Stanley Jevons to classical economics. For Jevons, when the cost of production declines due to resource efficiency, the marginal utility of commodities that use the given resource declines, increasing directly the consumption of those commodities and indirectly the consumption of other commodities with which they are exchanged. Then, scientific progress and resource efficiency is not a good path to the lesser use of resources. Actually, as coal is a non-renewable energy resource, it may be depleted. Jevons’ line of thought led to new areas in economics that imply that economics cannot be fully split from other sciences. The chapter assesses the current importance of the Jevons paradox in the macroeconomic and the microeconomic level, looking at the relationship between economic growth and energy efficiency. Finally, the chapter comments on the energy policies proposed to avoid the rebound effect, with some concluding remarks on the evolution of the concept.
Coordinated efforts to reduce haze and carbon emissions are important in promoting global climate governance and sustainable development. In this paper, based on prefecture-level data of China from 2005 to 2019, we investigate the impact of environmental regulatory intensity on the emissions of the concentration of PM2.5 and carbon dioxide (CO2). The research indicates that environmental regulation facilitates synergistic governance for PM2.5 reduction and carbon mitigation. Green technological advancement emerges as the primary mechanism through which environmental regulation achieves haze reduction and carbon mitigation. This conclusion remains robust after a series of robustness tests. Furthermore, the results from quantile regression reveal that the haze reduction and carbon mitigation effects of environmental regulation are subject to certain conditional dependencies. Environmental regulation exhibits a significant negative impact on carbon emissions across various quantile points. However, their influence on different quantile levels of PM2.5 concentration displays an asymmetric pattern. Finally, threshold regression findings suggest that there is no significant threshold effect of environmental regulation on CO2 emissions, but there are dual threshold effects on the PM2.5 concentration. Therefore, it is recommended that local governments judiciously implement environmental regulatory intensity, establish interregional policies for haze reduction and carbon mitigation, and fully harness the driving force of green technology to promote a comprehensive green transformation of economic and social development.
Humanity is facing complex challenges posed by population growth, climate change, and the need to increase food, feed, fiber, and bioenergy production while confronting the scarcity of natural resources. The transition to a circular economy, characterized by reduced resource use and waste, is being increasingly recognized in academic, business, and policy making circles as essential to meeting these challenges, with the emphasis being on the development of methods and processes that enable and facilitate the transition from a linear to a circular economy. This paper argues the need for an increased emphasis on the economics of the circular economy and presents a general framework that illustrates the transition from a linear to a circular economic system. In addition, the paper highlights the economic issues that arise during the transition to increased circularity and the policy options available to facilitate the successful transition to a more circular economic system.
This article is building the theory for the scientific field of industrial ecology. For this, the industrial ecosystem (IE) concept is used. IE uses the model of sustainable ecosystems in unsustainable industrial systems for making progress towards the vision of the industrial ecosystem. Six controversies are revealed and identified as research challenges. I invite all those who are interested in industrial ecology to respond to this contribution.
Policy and practitioners’ initiatives to stimulate sustainable consumption have so far failed to have notable impact on individuals’ behaviors. The current commentary is a plea to social and sustainability scientists, particularly to economists dealing with sustainable agri-food systems, to dig deeper into the notion of narratives to trigger societal dynamics that stir consumers toward more sufficient lifestyles. As dominant cultural narratives have a critical role in shaping shared meanings and acceptable behaviors, in the future they could guide dramatic changes in individuals’ conduct, triggering drastic modifications of current consumption patterns. Based on the power that concepts as the Circular Economy and the Anthropocene have had in the recent past, a future step to develop an ecological worldview across society, and nourish individual identities deeply committed with the preservation of natural ecosystems, is working on narratives based on the notion of human-nature interdependence .
Since 1996 CPB uses NEMO, a new model of energy de- mand for the Netherlands. It links sectoral energy use to (physical) production, energy prices, technological trends and government policies. A 'putty-semiputty' vintage structure is used, in which price effects are relatively large in the long run but small in the short run. The effects on energy demand of new investments, added investments (retrofit) and good housekeeping are assessed sepa- rately. The most important model parameters can be derived from 'bottom-up' (micro) information. The model will be used for predictions, scenario analysis and policy analysis in the short, medium and long run. Samenvatting Sinds 1996 gebruikt het CPB een nieuw energievraag- model voor Nederland: NEMO. Het model voorspelt het energiegebruik per sector op basis van (fysieke) productie, energieprijzen, technologische trends en over- heidsbeleid. Door het gebruik van een 'putty-semiputty' jaargangenstructuur zijn prijseffecten relatief groot op lange termijn, maar klein op korte termijn. Er wordt onderscheid gemaakt tussen besparingen via nieuwe jaargangen, via toegevoegde investeringen (retrofit) en via 'good-housekeeping'. De belangrijkste coëfficiënten van het model worden bepaald op basis van 'bottom-up' (micro) informatie. Het model zal worden gebruikt voor voorspellingen, scenario-analyses en beleidsanalyses op korte, middellange en lange termijn.
By reducing the fuel costs of travel, motor vehicle efficiency, improvements tend to increase the demand for travel, thereby offsetting some of the energy-saving benefit of the efficiency improvement and creating a "rebound" effect. The key factor is the elasticity of vehicle travel with respect to fuel cost per mile. Past studies offer a wide range of estimates depending on model formulation and time period, with more recent analyses indicating that travel is insensitive to fuel costs and efficiency. This paper analyzes U.S. light-duty, vehicle miles travelled from 1966 89, examining a variety of statistical issuesthat bear on the size of the "rebound" effect, including error structure, functional form, and possible lagged effects. The results consistently confirm that the 'rebound" effect has been quite small, about 5 15%, or less; and that short-run (one year) adjustments accounted for essentially all of the change in travel due to fuel price and fuel economy changes. The findings imply that the energy savings of technical fuel economy improvements to cars and light trucks will be only slightly reduced by increased vehicle travel. They also imply that gasoline taxes would need to be very large in order to stimulate significant reductions in travel.
In the discussion of energy conservation, a great deal of attention has focused on mandated efficiency standards for cars and energy-using household appliances. (In this article, I will use the term "appliance" in a generic sense to cover household durables). Unfortunately, the estimates of energy savings predicted to result from these mandated standards are derived mechanically.' When mandated standards raise the appliance efficiency by 1 percent, demand is predicted to drop by 1 percent; when they raise efficiency by 2 percent, demand is predicted to drop by 2 percent; and so on. Examples of such results are found in reports by the Department of Energy (1979a, 1980) and by the Staff of the California Energy Commission (1979) on energy demand in California in the coming two decades.
Bottom-up modelers typically predict a lower energy demand and a higher energy efficiency than top-down modelers do, leading to the notion of the energy efficiency gap. This difference is often ‘explained’ by combining bottom-up information with unrealistically high discount rates. In this paper we combine the bottom-up and top-down approaches in an energy demand model. The model has a top-down structure, but we employ bottom-up information to estimate most of its parameters, using the discount rate that firms say they use. This new approach provides a partial reconciliation of top-down and bottom-up methods, which proves to be very useful for policy analysis.
Recently, Greene (1992) analyzed vehicle miles travelled for U.S. passenger vehicles over 1966-89 to econometrically estimate the "rebound" effect in fuel consumption resulting from improved fuel efficiency. He found that a static AR(1) model could not be rejected, implying that the rebound effect is small (13%) with no significant long-run adjustments, regardless of the assumed functional form (linear or loglinear). Another look at the data from a different model selection approach shows that while a loglinear AR(1) model is acceptable, the linear version is not. Using either form, a lagged dependent variable model cannot be rejected on statistical grounds yet has insignificant GNP effects, yielding similarly small short-run rebound effects but significant long-run rebound effects of about 30%. Thus, the evidence from these competing models for a significant long-run adjustment process is mixed, so that its presence cannot be completely ruled out.
Vehicle use and fuel economy: how big is the rebound e!ect? Where are we going wrong? Modeling the e!ects of energy technology gains
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De prijselasticiteit van de energie vraaf: stand van zaken 1998, SEO-rapport 483, Stichting voor Economisch Onderzoek
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Parameters for NEMO. CPB discussion paper IV/97/03, Den Haag
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ICARUS-3: The potential of energy efficiency improvement in the Netherlands up to
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Where are we going wrong? Modeling the effects of energy technology gains
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