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Energy Policy 35 (2007) 6354–6363

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Energy productivity improvements and the rebound effect:An overview of the state of knowledge

John Dimitropoulos�

51, 6 Whitehorse Road, Croydon CR0 2AX, UK

Received 14 April 2007; accepted 26 July 2007

Available online 18 September 2007

Abstract

The ‘rebound effect’ from more efficient use of energy has been well investigated, with plenty of evidence suggesting that the ‘direct’

rebound effect is relatively small for most energy services—typically less than 30%. However, the same conclusion may not apply to

‘indirect’ and ‘economy-wide’ rebound effects. Here, several authors suggest that improved energy efficiency may increase energy

consumption in the medium to long term, a view that undermines the rationale for energy efficiency as an instrument of climate-related

energy policy and has been ardently debated. One of the main reasons behind the debate is the lack of a rigorous theoretical framework

that can describe the mechanisms and consequences of the rebound effect at the macro-economic level. Proponents of the rebound effect

point to ‘suggestive’ evidence from a variety of areas including economic history, econometric measurements of productivity and macro-

economic modelling. This evidence base is relatively small, highly technical, lacks transparency, rests upon contested theoretical

assumptions and is inconclusive. This paper provides an accessible summary of the state of knowledge on this issue and shows

how separate areas of research can provide relevant insights: namely neoclassical models of economic growth, computable general

equilibrium (CGE) modelling and alternative models for policy evaluation. The paper provides a synopsis of how each approach may be

used to explain, model and estimate the macro-economic rebound effect, criticisms that have been suggested against each, and

explanations for diversity in quantitative estimates. Conclusions suggest that the importance of the macro-economic rebound effect

should not be underestimated.

r 2007 Elsevier Ltd. All rights reserved.

Keywords: Macro-economic rebound effect; Energy productivity; Energy efficiency

1. Introduction

The nature and magnitude of the rebound effect hasbeen debated for decades. The issue is whether moreefficient use of energy would result in net decreases inenergy demand. In recent years, this debate seems toconcentrate especially on the macro-economic side of theissue, where empirical evidence is almost non-existent andthere is no single widely accepted methodology that candepict rebound in higher levels of aggregation.

The main concern behind the debate in the macro-level isthat energy efficiency initiatives pose prominently as‘win–win’ policy instruments in energy policy agendas, like

e front matter r 2007 Elsevier Ltd. All rights reserved.

pol.2007.07.028

86648476.

ess: mail@johndimitropoulos.co.uk

the one published recently for the UK. The existence andpotential importance of the rebound effect in the macro-level directly undermines the rationale and effectiveness ofsuch policy instruments. Hence, the rebound debate hasbeen revived, following the recent, yet keen, interest ofpolicymakers, stakeholders and energy practitioners withinthe contemporary climate policy discourses.The purpose of this paper is to provide a comprehensive

overview of this debate and assess objectively the state ofscientific knowledge that currently exists, regarding theimportance of the rebound effect in the macro-level.Section 2 provides a brief background on the debate,which is followed by a critical summary of the state ofknowledge from neoclassical growth theory, as comingfrom a number of theoretical contributions. This stateof knowledge is validated with cross examination of

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econometric evidence that has been used in support ofinsights from growth models. The third part outlinesstudies that have approached the rebound effect from ageneral equilibrium approach and provides a synopsis ofresults from simulations, as well as potential reasons fordiversity in estimates. The fourth part is an overview ofresults from alternative models that have been used forinvestigation of potential rebounds in the macro-level. Thepaper concludes by stressing the lack of sound theory andthe need for more robust evidence for the size andimportance of the economy-wide rebound effect.

2. Background and context

A striking feature of the rebound effect debate, especiallyin the macro-level, is that published concerns for itsimportance have been expressed as support for verydifferent arguments: from the comparative advantagesof nuclear power (Brookes, 1984, 1990) and the failure ofenergy conservation (Inhaber, 1997) to the virtues ofecological economics and industrial ecology (Wackernageland Rees, 1997; Tharakan et al., 2001; Hertwich, 2005), thechallenge of sustainability (Sanne, 2001), behaviouralchange (Wilhite and Norgard, 2004) and the extremeecological urgencies of ‘decroissance’ (de-growth inFrench) (Schneider, 2003). It is very hard to find anythingelse common to the views of these authors, other than theconcern for high rebound and the potential usefulness ofenergy efficiency. The main reason for this otherwiseinexplicable coincidence is that little is known for themacro-economic rebound effect with certainty; hence,authors with different viewpoints are able to use the samephenomenon to support very different arguments. Thespecial issue of Energy Policy, vol. 28 (2000) containsseveral key contributions to the rebound debate.

In the macro-economic level, the main concern of mostauthors is not the rebound effect arising from energysavings taken back in the form of increased welfare (thedirect rebound), but the income effect arising fromintroduction of efficiency improvements in energy servicesthat are close to saturation. This income gain will stimulateconsumption and energy demand. This interpretation isparticularly favoured by authors in ecological economicsliterature, since it relates the indirect energy intensity ofconsumption with income gains. A number of studies(Jalas, 2002; Carlsson-Kanyama et al., 2005; Cohen et al.,2005; Takase and Kondo, 2005) indicate that the actualindirect energy requirements of households are bigger thanthe direct energy requirements, and that income effects cangive rise to indirect energy consumption.

Although this concern is reasonable, it should be notedthat income effects arising from energy efficiency improve-ments are minute as compared with those happening inother technology processes like learning-by-doing orinvestments in R&D or even technical progress in otherinputs. This paper will not discuss this literature for tworeasons: first, income effects arising from technology gains

are universal within the economy, with only a small percentattributed to energy efficiency; technical progress thatgenerates value-added is not a rebound effect. Second, thisinterpretation is not consistent with the original definitionsfor the direct effect under the policy context of improvingenergy efficiency alone. Interested readers are referred tostudies that explore growth engines (Ayres and Warr, 2005;Ayres and van der Bergh, 2005) with natural resources,which should not be confused with the rebound fromimprovements in energy efficiency.

3. Neoclassical growth models

A theoretical framework that can describe improvedimpacts of more productive energy has been the well-established Solow–Swan model for economic growth, asapplied by Saunders (1992), who offered a much moreelaborate investigation of the issue. Saunders used aCobb–Douglas and a nested CES function to simulate whatwill happen to output and energy consumption followingcontinuous improvements in energy productivity at the rateof 1.2% per year. Based on a number of assumptionsregarding the values of several parameters, Saunders showedthat simulated energy productivity improvements with aCobb–Douglas function within a neoclassical growth frame-work do not realise in any energy savings. Energyconsumption growth rate locks with output growth rate,and so energy efficiency always leads to an increase in energyconsumption. In other words, the Cobb–Douglas functionproduces backfire, for whatever value of the parametersinvolved, as also shown by Wei (2007).Since the Cobb–Douglas function did not seem to be

able to replicate impacts of energy efficiency improve-ments, Saunders conducted similar simulations with anested CES function. Results from Saunders’ simulations,although not proving the existence or truthfulness of veryhigh rebounds, suggest the theoretical possibility thatenergy efficiency improvements might not contribute toenergy conservation and can help stimulate, not mitigate,energy demand.The theoretical assumptions of this approach were

questioned by Howarth (1997), on the basis that energyis not a direct raw input in the production function of theneoclassical growth model. Energy services, not energyitself, actually enter the production process. Using a formalmodel of economic growth with Cobb–Douglas produc-tion, and based on many of Saunders’ initial assumptions,Howarth showed that unless other costs of providingenergy services are zero, energy efficiency improvementswill always yield energy savings. Capital costs in theprovision of energy services have been a critical omission inrebound research even in the earlier work by Khazzoom.This assumption is discussed further elsewhere (Dimitro-poulos and Sorrell, 2006).Moreover, Howarth (1997) placed an additional condi-

tion for the existence of backfire: if the elasticity of energyservices with respect to energy intensity is below 1 in

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absolute terms, then energy savings are possible. If demandfor energy services with respect to energy intensity is elastic(higher than unity), then energy efficiency improvementscan increase energy demand. Although the argumentbehind this condition is somewhat micro-economic,following the same aggregation rationale for aggregateproduction functions, we can say that this elasticityprovides a very rough approximation of the rebound inthe macro-level.

Howarth’s criticisms, however, were not left unchallengedby Saunders. In a reply, Saunders (2000a) showed thatHowarth’s theoretical results stem from the use of a Leontief(fixed-proportion) style of cost function for energy services.Saunders’ argument in this case emphasised the limitedmodelling capability of the Solow model, since theoreticalresults are so diverse with different functional forms.

With a second article, in the same special issue of EnergyPolicy, Saunders (2000b) re-iterated the theoretical possi-bility of backfire, as coming from improvements inproductivity of other inputs. Saunders also stressed thatconventional energy-intensity indicators (like the energyratio) are very unreliable in assessing the impact of energyefficiency improvements, since relative forces that influenceenergy consumption and output are not transparent by justlooking at energy ratios. However, the use of the growthmodels for simulation of energy productivity improve-ments involves essentially energy ratios.

In addition, Saunders presented a separate analysis forshort-run and long-run impacts of energy efficiency onoutput, as approximated by national income. For the shortrun, Saunders used a Cobb–Douglas function, assumingfixed real energy price. Under neoclassical assumptions andunitary elasticity of substitution, a 20% improvement inenergy efficiency leads to 1–2% increase in output. Thelong-term impact was simulated to be around 14% higherthan in the short term, with a maximum gain in output of2.28%, from a one-off, non-price-induced, improvement inenergy productivity. However, Saunders’ calculations forthe long-term impact on output have been found to containan error by Wei (2007). The actual long-term impact onoutput and energy with a Cobb–Douglas, according toWei, is as high as 3.6%, in partial equilibrium.

The Solow model has been extended to account fortechnical progress endogenously with energy (Azar andDowlatabadi, 1999; Loschel, 2002). ‘New’ growth theory,based on the revival of growth macro-economics withendogenous technology (Romer, 1990; Aghion and Howitt,1998) has generally neglected energy-related issues, and tothe best of our knowledge, no author has approached therebound question with an endogenous growth model.However, energy policy objectives have been approachedwith endogenous growth models (Smulders and de Nooij,2003; Van Zon and Yetkiner, 2003). Although evidencefrom these studies does not relate directly to the reboundeffect question, it complements existing evidence fromneoclassical ‘old’ growth models that have been used forexploring the rebound effect. Simulations on endogenous

growth models with induced technical change revealed thatenergy-conservation policies, which either reduce the levelof energy use or the growth rate of energy use, result inreductions of income per capita levels, declining cost sharesfor energy and declining energy ratios. Although thesefindings seem very interesting, little connection to therebound has ever been established.

4. Econometric evidence

The only econometric ‘suggestive’ evidence offered insupport of the insights coming from growth models hasbeen a body of empirical work from Jorgenson andcolleagues (Jorgenson and Fraumeni, 1981; Hogan andJorgenson, 1991; Jorgenson, 1998). Using standard pro-ductivity theory, Jorgenson developed an econometricmodel to describe producer behaviour with a four-inputfunction (capital, labour, energy and materials) for 35sectors in the US. A critical result, reached by Jorgensonand colleagues in a number of papers, is that the bias oftechnical progress (as defined therein) on energy was foundto be positive in the majority of US industries. Theimplication of this result is that technical change ‘uses’energy in most industries, or that the rate of technicalchange of energy decreases with increasing energy prices.Alternatively, Jorgenson’s findings might be interpreted asindications that technical change increases the share ofenergy in the value of output, in most US industries.The actual way that technical progress is modelled in

econometric models can make a great difference in resultsobtained and conclusions drawn for biased technicalchange. Key differences, besides datasets and estimatingtechniques, are assumptions regarding the nature andtemporal evolution of embodied and disembodied technicalprogress, total factor productivity and factor biases.Jorgenson’s models assume implicitly that technical pro-gress is disembodied, since capital is assumed to adjustalmost instantaneously to changes in prices; technicalbiases are fixed throughout the sample and the rate oftotal factor productivity is allowed to vary with time andrelative factor prices.These assumptions are justified, for most of the models

that Jorgenson and colleagues have run, following theirobjective to examine what was the (short-term) effect offactor prices on total factor productivity, as the interest ofproductivity economists in that period was to explain thephenomenal productivity slowdown of the late 1970s andits relationship to high energy prices. The extent to whichchanges in assumptions alter results is largely an empiricalissue, as can be seen in several other contributions(Norsworthy, 1981; Berndt and Hesse, 1986; Sue Wingand Eckhaus, 2004). Results from these papers do notsupport all findings of Jorgenson’s work, hence affectingthe robustness of Jorgenson’s results.Compelling evidence also comes from an important

contribution by Gardner and Joutz (1996). These authorsspecify an econometric model that tests Saunders’ theoretical

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results with real US data. They use a VAR model andcointegration theory to account for stochastic trends in thedata. The authors crucially recognise that technical change(in their data measured as stock of patent activity) is nottaking place only in a single input, but collective technologyappreciates multiple inputs simultaneously through im-proved capital vintages. Their model accounts for both thelong-run and short-run adaptations of output from changesin technology and implicit energy prices, since embodiedtechnical change (as embedded on capital stock) is unlikelyto affect output in the short run. In addition, the authorsestimate an alternative specification that allows for asym-metric output responses from volatile energy prices; thisspecification is justified by the widely accepted hypothesisthat investment on more efficient capital stock is non-reversible (Dargay, 1992; Gately, 1992).

Their results do not support fully the theoretical insightsarising from the growth model (Saunders, 1992) or existingshort-run rough estimates (Saunders, 2000a, b). In parti-cular, the authors find that implicit energy price decreasesdo not stimulate economic growth in the short run, whileembodied technical progress was not found to bestatistically significant, implying that increasing technologycannot affect output in the short term. Hence, according toevidence from Gardner and Joutz, price or embodiedtechnology effects, in the short run, cannot increase inany case output or energy. Only higher prices can curbdemand and hinder growth. In the long run, the energyprice elasticity of output was found to be�7%, meaningthat a 20% decrease in the implicit energy price wouldimply, ceteris paribus, a long-run increase in output of1.14%, an estimate that is half of that given by Saunders(2000a, b) and almost a third of the figure given by Wei(2007).

5. General equilibrium models

General equilibrium theory can be supplemental togrowth theory, since it offers insights to how energyproductivity gains diffuse within an economy. The impactsof increased energy productivity within an economy havebeen simulated by a number of computable generalequilibrium (CGE) studies, which provide an additionalsource of knowledge for economy-wide rebound effects.Simulations from such studies can also give additionalinformation for a number of parameters that canpotentially inform policy.

A detailed review of the literature has revealed severalstudies that have simulated improvements in the produc-tivity of energy, in either production or consumption.Although these studies follow a similar modelling philoso-phy, they exhibit significant differences in specification,parameterisation, simulation procedure and other crucialassumptions that are likely to determine results. Due tospace limitations, only a short discussion is possible herein.

The earliest study found in literature, by Semboja(1994a), describes potential aftermaths of improvements

in energy productivity in Kenya. The model is based onCobb–Douglas technology with no substitution possibili-ties between capital and other factors. The authorsimulates small improvements (�1%) in productivity ofenergy production and oil use. Although a detaileddescription of the simulations is not given in the paper,the author reports that results show a 3.5% increase inenergy used in production and a 1.7% increase in oilconsumption, indicating rebound above unity in bothcases. No sensitivity analysis was reported from the author.In the similar context of a developing country, Dufour-

naud et al. (1994) apply a CGE model to explore efficiencyimprovements in the household sector of Sudan. The focusof the paper is on efficiency improvements in wood stovesof Sudanese households. The model assumptions andequations are clearly defined, and the model results weresubjected to extensive sensitivity analysis. Householdutility functions exhibit constant elasticity of substitutionand allow for the interaction between energy consumption,leisure and composite goods, making use of householdproduction theory. Results from simulations were incontrast to the ones obtained in Semboja: increasingefficiency in wood stoves by 100–200% yielded reboundeffects in the range of 47–77%.Yet, lower rebounds are predicted from simulations in a

CGE model for the Netherlands, by Van Es et al. (1998).The model is constructed in different modules for produc-tion, consumption, foreign trade and environment. Func-tional forms used for production are nested CES withranging values for elasticities of substitution according tosectors. A useful characteristic of the model is that GHGemissions can be traded within the environment module.As Berkhout et al. (2000) note, the model was not onlybased on standard I–O tables, but also incorporated adetailed bottom-up supply side database for energy-savingtechnologies, which can feed the main model with realengineering data for future energy-efficiency potentials.Explicit attention was taken to modelling energy efficiency,which was modelled both as replacement and as improve-ment of the existing capital stock. Long-run simulations forthe macro-economic rebound effect summed to 15%.Quite different results are reported by Vikstrom (2004),

who applied a CGE model for energy-productivityimprovements in Sweden. He also used a CES function,with explicit treatment for each sector, assuming values forthe constant elasticities of substitution ranging from 0.06 to0.87. The author, based on historical data, constructed auseful exercise where he simulated the counterfactual ofefficiency improvements of 15% in all non-energy-produ-cing sectors, and 12% in energy-producing sectors. Resultsfrom the simulations are compared with the actual data sothat one can determine the degree of confidence that can beplaced on the estimates. With a high degree of confidence,the author reports a significant rebound effect of 60%. Nosensitivity analysis is reported on the results.Similar ranges of rebound effects are reported by

Washida (2004), who examines the impact of 1%

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improvement in the energy productivity of all sectors inJapan. Washida used a multi-level CES productiontechnology for energy and value-added, without allowingsubstitution possibilities between energy/value-added andother intermediate inputs. Some sensitivity analysis fordifferent values of inter-fuel and energy/value-addedelasticities yielded rebounds effects ranging from 35% to70%. An important observation from this paper is thatrebound and value of elasticity of substitution arepositively correlated.

However, the same observation could not be made inresults from another analysis with a CGE model byGrepperud and Rasmussen (2004). The authors sketchout a model for production in Norway, based on multi-nested CES production technology that allows for sub-stitutions between electric and non-electric energy. Thestructure of the model permits the comparative analysis ofscenarios, simulating thus the impact of energy-productiv-ity improvements in all sectors, in terms of both energyconsumption and carbon emissions. Scenarios that simu-late increased productivity, for either electricity or oil,across Norwegian sectors yielded a range of values forrebound effects, from mild to very significant and evenbackfire. However, simulations for the overall economyshowed that rebound effects could be weak or even absentif further macro-economic considerations are introduced.The authors showed that higher values of the elasticity ofsubstitution are not necessarily associated with higherrebound effects, as usually suggested in growth models.

This interesting result could not be certified empiricallyin another CGE study for China by Glomsrod and Wei(2005), probably due to the inherent assumption of aunitary elasticity of substitution between composite energycapital and labour. A unique characteristic of this model,which makes it different from all previous ones, is the

Table 1

Summary of characteristics and results from CGE studies

Author/year Country Production ESUB E

Semboja (1994) Kenya CD�L 1 or 0 1

Dufournaud et al. (1994) Sudan CES 0.2�0.4 1

Van Es et al. (1998) Holland CES 0oso1 1

Vikstrom (2004) Sweden CES 0.07�0.87 1

Grepperud and Rasmussen

(2004)

Norway CES 0oso1 1

e

Washida (2004) Japan CES 0.3�0.7 1

Glomsrod and Wei (2005) China CD, L, CES 1 N

Hanley et al. (2005) Scotland CES 0.3 5

Allan et al. (2007) UK CES 0.3 5

Abbreviations: CD: Cobb–Douglas, L: Leontief, ESUB: elasticity of substitution

productivity (per sector), NA: not available.

realistic assumption that labour supply is infinitely elastic.Although the objective of this model was not to simulateenergy efficiency improvements, the authors drew resultsregarding more efficient use of coal. Although specificrebound estimates are not given, the authors say that:‘‘The rebound effect dominates over the initial saving ofenergy in this study’’, implying very high or even aboveunity rebound.Another interesting application of a CGE model for

examination of macro-economic impacts of energy effi-ciency improvements focuses on Scotland (Hanley et al.,2005). This model takes a regional rather than aneconomy-wide approach; therefore, it is entirely differentfrom all other CGE studies exploring economy-wideeffects. However, the model structure is similar to previousmodels, based on nested CES technology and assumingelasticity of substitution between energy and non-energyinputs. A 5% improvement in the productivity of energy inall sectors yielded in simulations a rebound of 122%,expressed in increase of CO2 emissions.This rebound estimate, however, is very different from a

similar version of the same model that has been applied forthe whole of the UK by Allan et al. (2007). Based on datafrom I–O tables for the whole of the UK, this study alsosimulates a 5% improvement in all sectors and similarassumed values for other key parameters. Simulationsyielded a best estimate of 50% rebound in energy use, inthe short run, with long-run values of 30%. This interestingfinding contradicts previous work in growth theory andevidence from econometric studies, namely that short-runrebounds are likely to be lower than long-run rebounds.A summary of basic characteristics and results from

CGE studies is given in Table 1. A quick glance atestimated rebound effects reveals that results are veryinconclusive: estimates range from 15% to 350% on a wide

fficiency % Rebound % Comments

170�350 Simulations for energy production and

use

00�200 54�59 Households only, well structured,

extensive sensitivity analysis

00 15 Bottom-up feed database, explicit

representation of efficiency improvements

2�15 60 Dynamic simulations with counterfactual

efficiency changes

00 AAGR

lectricity or oil

o100 Dynamic simulations with counterfactual

scenarios

35�70 Sensitivity analysis reveals positive

relation of rebound with ESUB

A 4100 Focused on limiting emissions with a tax

on coal use

120 Open region approach with major energy

exports

30–50 Extensive sensitivity analysis

(s), CES: constant ESUB, AAGR: average annual growth rates of energy

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variety of research objectives, methodologies and assump-tions. Some potential explanations for the diversity inresults from CGE studies are discussed below.

5.1. Aggregation and production technology

While the concept of a production function as ablueprint for production has been proven very useful inthe firm level, the same cannot be said safely for higherlevels of aggregation (Felipe and Fisher, 2003). Beyondaggregation issues that are common to both growth andgeneral equilibrium theories, the production technologyassumed for a sector or a whole economy will determine, toa large extent, results from model simulations. Detailedexamination of commonly used production functions, likeCobb–Douglas or CES, reveals very significant differencesin results obtained from them, even in a general equili-brium context (Wei, 2007).

5.2. Role and substitution possibilities for energy

There is no universally accepted way of including energyin production technology. Many modellers assume theexistence of a nested structure for a CES function, whereenergy is included either as a homogeneous input or asseparate fuels in a lower level of multilevel CES functions.The choice and treatment of energy within productiontechnologies is entirely arbitrary. It should be noted thatsensitivity analysis, which is frequently conducted in CGEmodels, usually aims at establishing a degree of confidencein results for different elasticities of substitution. These arekey parameters that can only be estimated econometrically.Even their estimation is a separate area of research withmany caveats and uncertainties.

5.3. Adjustments of capital, labour and other inputs

It is well known that capital stock, unlike energy, cannotchange significantly in the short term, while energyconsumption embedded in existing capital stock is lockedat a range of utilisation rates until the replacement of oldcapital vintages. Long-run simulations will have to takeassumptions regarding the appropriate depreciation ratesor capital replacement rates. Labour, in contrast to energy,is not a natural resource. Assumptions within the model oflabour supply and wages are likely to determine results,since labour is well known to be a close substitute toenergy. Only a few CGE studies estimate substitutionelasticities specifically for the country or region examined.

5.4. Modelling of energy efficiency and technical progress

The term ‘energy efficiency’ is generic and can havedifferent meanings. For most macro-economic models,energy efficiency is usually assumed to be equivalent toenergy productivity, which encompasses changes in ther-modynamic efficiency and disembodied technical progress.

Following modelling objectives, different definitions forefficient energy use can be attributed to changes inproduction and consumption. The actual way that energyefficiency is modelled within the model structure is notuniversal across studies, since some might simulateimprovements in a single sector while others might simulateimprovements across the economy. The dynamics oftechnical change across sectors are usually neglected(spillovers or contagion effects). In addition, there is nouniversal way of modelling technical progress for the restof the inputs.

5.5. International trade

The structure of trade relations is likely to influenceresults from simulations of improved energy productivity.Regions or countries that are highly dependent on energyimports are prone to supply shocks, while major exportersof energy can benefit more from productivity improve-ments in energy-producing technologies. Assumptions inthis category are unique in each model.

5.6. Government policies

A complete economic structure in a CGE model requiresadditional assumptions about the levels of governmentspending, saving rates and investments. In practice, theseassumptions are summed in scenarios that incorporategovernmental policies on energy, simulating carbon taxes,provision of incentives, stimulation of investments, rebatesand so on. Treatment of government policies is also likelyto be unique in each model.Having these points in mind, one can see that results are

not transferable among models, regions or specific end-useefficiency improvements, while the wide range of estimatesblurs conclusions regarding the potential importance ofmacro-economic rebound effects. CGE models have beenused more as policy informing tools and less as instrumentsfor investigating how rebound works. Although severalauthors have challenged the philosophy and application ofCGE models for policy (Ackerman, 2002; Barker, 2004;Scrieciu, 2007), they still remain a popular tool for policyevaluation, even in the relevant literature. Practitioners andpolicymakers should be aware of the positives andnegatives of CGE models prior to generalising conclusionsfrom existing studies.

6. Hybrid macro-economic models

Although general equilibrium models have been verypopular for policy evaluation, dissatisfaction over severalcharacteristics of this modelling approach has beenexpressed in the literature. From the seminal contributionby Hudson and Jorgenson (1974), econometric techniqueshave been combined with principles of general equilibriumtheory in dynamic general equilibrium models (Jorgensonand Wilcoxen, 1993). Over time, macro-economic simulation

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models have been amalgamated with advanced econo-metric techniques, general equilibrium methodsand bottom-up engineering models. Evolution of energy–economy macro-models in a time of growing environ-mental concerns gave rise to ‘energy–economy–environ-ment’ (E3) models that combine and use principles ofmacro-economics and econometrics, with submodels forenergy and environmental impacts (emissions).

A version of such a model has been used recently by4CMR (Barker et al., 2007) to estimate the macro-economic rebound effect in the UK economy. The modelis multi-sectoral and dynamic so it accounts for interac-tions across sectors and through time. The model does notrely on assumptions regarding aggregation and productiontechnology, while many of the parameters of interest areestimated with modern econometric techniques.

The economic part of the model involves a system ofequations for the UK economy, disaggregated by industryand based on UK national accounts. The model involvestime-series econometric estimates, drawn from conven-tional cointegration methodologies, with cross-sectioninput–output relationships. An energy submodel is linkedwith the economic model via bottom-up relationships thatenrich the top-down structure of the macro-model.Changes in the use of energy due to energy efficiency arefed in the economic model from the energy submodelthrough the system of input–output coefficients. Specificdata are used also for the power supply industry. Emissionsare simulated in a separate environment submodel.

The overall estimate is 27% rebound by 2010 for existingUK energy efficiency policies. The authors assume anadditive relationship between direct and indirect effects.Several other insights arise from the model: the authorsfind that policies that stimulate energy efficiency lowerinflation and promote economic growth. Finally, emissionsare estimated to decline even more than the reduction inenergy use.

Another macro-economic model that has been used forinvestigation of economy-wide impacts from energy effi-ciency improvements is the NEMO model (Koopmans,1997), for the Dutch economy. The model combines aconventional macro-structure, based on CES productiontechnology, with explicit ‘putty–semi-putty’ responses ofcapital stock to changes in prices. In this structure, part ofthe price response is instantaneous and part of it isgradually taking place in the meso/long run throughinvestment and replacement of the old capital stock withnew vintages. Therefore, the model justifies inherently theempirical finding that short-run price elasticities of energydemand are generally less than the long run priceelasticities, implying similar magnitudes for rebound effects.

In addition, the model is flexible enough to account forasymmetric responses to energy prices. Within thisstructure, the top-down model for energy demand is linkedwith supply data for energy-saving techniques from anengineering bottom-up database. Energy efficiency istaken into account in two separate manners: firstly for

replacement of the existing capital stock and secondlyfor improvement of the existing capital stock. Hence,estimation of own-price elasticities is carried out both forreplacement and for improvement of the capital stock.The NEMO model avoids the rebound taxonomy

(direct/indirect vs. economy-wide) and provides estimatesfor the rebound effect from improvements in energyefficiency for the whole Dutch economy. The overallmacro-economic rebound effect is estimated at 27% inthe long run, which is surprisingly close to the estimatefrom the MDM E3 model.Analogous indications for the macro-rebound are

reached from the NEMS model for the US (Kydes,1997). NEMS is a wholly integrated modular energy–economy model for US energy markets. Although theauthor does not estimate directly economy-wide effects, hegives an indication of estimates. On the high-technologyscenario, energy efficiency improvements stimulate outputand decrease demand for fuel, hence producing a reductionin energy ratio of 24% until 2015. Supply/demandadjustments within NEMS produce a reduction in theprice of fuel, which was found to be slightly higher thanexpected because of rebound effects. Based on thisobservation, Greening and Greene (1998) reach a short-run estimate of 27%. This result, although in accordancewith similar literature, is not very reliable for two reasons:technology assumptions in NEMS hold technical progressfixed in the rest of the world and also the model does notaccount for OPEC country responses to downward pricepressures, given that one-fourth of total global fuel isconsumed in the US.

7. Summary and conclusions

The rebound effect in the macro-level is a controversialsubject that has generated great debates among energyeconomists. While the view that improvements in energyproductivity certainly take back some of the expectedsavings is widely accepted in both the micro- and macro-economy, a number of authors have seriously questionedthe postulated principle that increasing cost effectiveness inthe use and production of energy will lead to net increases,not decreases, in energy demand. The truthfulness of thispostulated principle directly undermines the effectivenessof energy efficiency measures that are used as policyinstruments for meeting CO2 emissions targets.The absence of expert consensus regarding the impor-

tance of the macro-economic rebound is mainly due to tworeasons: firstly, there is lack of a sound theoreticalframework that can explain sufficiently the complexinteractions that accompany energy efficiency improve-ments in the macro-level, where even the definitions ofenergy efficiency are still a questionable subject. Secondly,this lack of theory is complemented by inconclusivehistorical, empirical and econometric evidence.This paper attempts a survey of theoretical and empirical

contributions for the nature and importance of rebound

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effects in the macro-economy, with two additionalobjectives: to offer an overview of existing knowledgeand suggest explanations for the diversity in results fromsimulations and econometric estimations.

The nature of the rebound effect in the macro-level hasbeen explored mainly within growth theory. Prominent inthis area is theoretical work in the context of the traditionalSolow–Swan of economic growth with exogenous technol-ogy. Theoretical predictions depend on the assumptionstaken for the underlying model; however, the existence of acertain rebound is common to all models. Theory alsosuggests the possibility that increased energy productivitycan lead to higher energy demand and hence carbonemissions, providing thus theoretical support to thepostulated principle that rebound is always greater thanunity or backfire.

Empirical and econometric evidence that has been putforward by backfire proponents is outdated and, at best,‘suggestive’. Even if one accepts that there is a link betweentheory and the cited evidence, an up-to-date review of therelevant literature reveals that econometric studies are notconclusive of the existence of energy-using or saving biases,mainly because of different representations of technicalprogress within econometric specifications.

A rough approximation of the macro-rebound effect isthe economy-wide price elasticity of demand for energy,when estimated from models that account for embodiedtechnical progress. Under this approximation, there arevery useful insights coming up, by consensus, from manyempirical studies. One result is that rebound in the shortrun is less important than it is in the long run. Two, theexistence of asymmetric elasticities of demand for energyconfirms that price-induced energy-saving technical pro-gress is actually taking place, regardless of improvementsin energy productivity. This is a well-established result thatsupports the opinions of backfire opponents.

Empirical evidence from CGE studies is also veryinconclusive, with simulated estimates ranging from 15%to 350% in nine studies. In part, general equilibriumstudies provide some support to insights from growththeory. However, CGE studies serve more as evaluationtools for specific policies and contexts, for which modellershave to undertake a wide array of assumptions. In essence,each CGE study is unique and cannot be directly comparedwith another one, while results are not transferable amongstudies. Several explanations are given as to why resultsfrom CGE models are so diverse. Notably, little can belearned regarding the nature of the macro-rebound fromCGE studies. As a consequence, evidence-based policyconsultations cannot be based on surveys of CGE models,since results do not apply universally.

Finally, hybrid energy–economy–environment modelsthat make collective use of theory and historical datahave also been used for estimation of economy widerebound effects. Although research work and evidencefrom these models are still quite scarce, results from threestudies point to rebound estimates of around 30%. The use

of historical information in these models gives them ahigher degree of credibility; however, even from thiscategory of models, results are not transferable amongstudies or countries.Another important conclusion is that macro-economic

rebound effects are expected to decrease as national incomeincreases with time. This is mainly due to the fact thatopportunities for cost-effective improvements in energyproductivity decline as output grows, and new opportu-nities require increasingly more capital costs to realise,especially in the context of developed countries.This paper finds that the theoretical understanding of

economy-wide effects is still quite poor. There are stillmany things to learn regarding the impacts of energyproductivity on energy demand at a theoretical level.Advances in endogenous growth theory, supported bysophisticated novel techniques in econometric methodol-ogy, can document more robustly how embodied anddisembodied technical progress interacts with policyinstruments. Regarding the effectiveness of energy effi-ciency initiatives in reducing emissions, it is safe to say thatthere is a huge potential for reducing carbon intensity inenergy use. Although rebound effects might take backsome of the estimated savings in energy, these are unlikelyto offset all the real gains in carbon emissions. This mightbe true, but only for the short run. Increasing energydemand in the long run might offset completely realisedsavings in carbon emissions. Therefore, energy efficiencypolicies ought to be considered as short-term policyinstruments that cannot, in any case, substitute for long-term policies that promote carbon-free or carbon-neutralenergy sources.

Acknowledgements

The author would like to acknowledge financial supportfrom the UK Research Councils, as part of the Technologyand Policy Assessment (TPA) function of the UK EnergyResearch Centre (UKERC). This study was undertakenwhile the author was Research Fellow in SPRU—Scienceand Technology Policy Research, University of Sussex. Theauthor gratefully acknowledges the contributions of GrantAllan, Michelle Gilmartin, Peter McGregor, Kim Swalesand Karen Turner, who have conducted a comprehensivereview of CGE studies for UKERC. Special thanks toSteve Sorrell and Harry Saunders for creative discussions.The opinions expressed in this paper are of the author’sand do not necessarily reflect those of UKERC.

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