Macroeconomic Rebound Effect of Energy Efficiency Policies

Transcription

1 Macroeconomic Rebound Effect of Energy Efficiency Policies Terry Barker and Tim Foxon Cambridge Centre for Climate Change Mitigation (4CMR), Dept. of Land Economy EPRG Lunchtime Seminar, 27 February 2006

2 Outline Energy efficiency policies for addressing climate change Are there likely to be significant rebound effects? Macroeconomic implications of energy efficiency improvements The Brookes-Grubb debate and recent literature Modelling the macroeconomic rebound effect using MDM-E3 Findings so far

3 UK energy efficiency policies Significant part of 2000 UK Climate Change Programme and 2003 Energy White Paper review of UK CCP launched in Sept 04 - due to report soon Updated DTI projections for CO 2 emissions (including CCL, 9% renewables, excluding EU ETS): MtC Projection for MtC (10% reduction) Target for MtC (20% reduction) Carbon gap MtC

4 Effect of Climate Change Programme measures Source: DTI, UK energy and CO 2 emissions projections, Feb 2006

5 Energy efficiency policies included in projections Target sector Domestic Business Public Sector Transport Total Policy/measure Building Regulations Energy Efficiency Commitment Warm Front Appliance Standards and Labelling UK ETS CCL package CCAs Building Regulations Public Sector measures VA Package 10 Year Transport Plan CO 2 savings in 2010 (MtC)

6 Rebound effects Direct rebound effects ( comfort taking ) increase in demand for energy service resulting from effective reduction in price of energy service Taken into account in projections: Energy Efficiency Commitment 30% Warm Front 75% VA package for transport 25% Other policies small What about indirect and macroeconomic rebound effects?

7 Macroeconomic rebound effects Indirect effects: Energy efficiency improvements change the demand for other goods and services Lower costs of output from one sector affect the production costs of other sectors, leading to further substitution and output effects Macroeconomic effects: Cumulative impact of energy efficiency improvements on energy prices and investment, and hence on energy demand, outputs and economic growth

8 What is size of macroeconomic effect? The Government s proposition that improvements in energy efficiency can lead to significant reductions in energy demand and hence in greenhouse gas emissions remains the subject of debate among economists. The Khazzoom-Brookes postulate, while not proven, offers at least a plausible explanation of why in recent years improvements in energy intensity at the macroeconomic level have stubbornly refused to be translated into reductions in overall energy demand. The Government has so far failed to engage with this fundamental issue, appearing to rely instead on an analogy between micro- and macroeconomic effects. (HoL Science and Technology Committee, 2005, Paragraph 7)

9 Jevons (1865) paradox It is a confusion of ideas to suppose that the economical use of fuel is equivalent to diminished consumption. The very contrary is the truth. The reduction of the consumption of coal, per ton of iron, to less than one third of its former amount, was followed, in Scotland, by a ten fold increase in total consumption, between the years 1830 and 1863, not to speak of the indirect effect of cheap iron in accelerating other coal-consuming branches of industry'.

10 Debate on macroeconomic effects Khazzoom (1987), Brookes (1990): Energy productivity improvements, historically But substitution of energy for labour and capital leads to total factor productivity growth Hence, increase in total energy consumption Grubb (1990): Significant difference between naturally-occurring efficiency improvements and efficiency improvements stimulated by incentives The latter can focus on areas dominated by market failures, where implicit price falls have little effect on activity levels

11 Market failures/barriers to energy efficiency improvements Lack of knowledge, knowhow and technical skills Separation of expenditure and benefit Limited capital, often arising from external restrictions on capital budgets Rapid payback requirements Impact of electricity and gas tariff structures Lack of interest in peripheral operating costs Legal and administrative obstacles

12 Key issues All agree that energy-saving technological change contributes to economic growth by stimulating structural changes in economic activity, i.e. new activities that were not previously economically viable But energy efficiency policies primarily address market failures/barriers which prevent currently most energy efficient technology or system being used Empirical evidence suggests that a high level of costeffective energy efficiency improvements can be found when attention is focussed Question: are induced energy efficiency improvements mainly reducing economic inefficiencies, or are they likely to stimulate significant increased economic activity?

13 Literature review 1. Growth theory, most important theoretical work on the rebound by Harry Saunders: Fuel Conserving Production Functions. Draft 3, Jan A calculator for energy consumption changes arising from new technologies. Topics in Economic Analysis & Policy 5/1 (2005). 2. General Equilibrium, important papers from: Nick Hanley et al. (2005). Do increases in resource productivity improve environmental quality? [Scotland] Sverre Grepperud and Ingeborg Rasmussen (2004). A general equilibrium assessment of rebound effects. [Norway] Peter Vikström (2004) Energy efficiency and Energy Demand [Sweden]. 3. Energy-economy-environment models Barker et al., MDM-E3

14 Growth theory approach Uses aggregate production function Saunders (2006) shows mathematically that of the four popular aggregate production function forms -- Cobb- Douglas, CES (Solow), Generalized Leontief, and Translog nearly all can produce backfire (rebound >1). Strongly dependent on fuel elasticity of substitution: Low elasticity of substitution low rebound High elasticity of substitution backfire (rebound > 1) Saunders: Most researchers to date have chosen by serendipity just the right model specifications to prevent backfire.

15 General Equilibrium approach Aggregate production function central to analysis Mixed results on rebound effect, all agree assumptions on elasticity and substitution crucial: Hanley shows (long-term 20+ years) backfire in future CO 2 in Scottish economy-- because of increased electricity exports with England. Grepperud shows Rebound <1, with only large impact in industries with limited substitution possibilities. Vikstrom testing his model against historic data, rebound was about 60%, but poor predictor of fuel use.

16 Problems in using aggregate production functions The relationship between the capital-output ratio and the rate of profit is not identifiable (Cambridge re-switching) the micro-production function cannot be meaningfully aggregated (Felipe and Fisher, 2003) the estimated production function is no more than an aprroximation to an accounting identity at the macro and sectoral levels (Felipe and McCombie, 2005) Apparent constant returns to scale No extra empirical content, as results could equally come from quasi-randomly-generated data i.e. completely misleading

17 Estimation of the aggregate production function in CGE modelling The practice of drawing parameter estimates from the literature is ad hoc which ones (from direct estimates or traditional energy deman equations? short- or long-run estimates? same parameters, same data: but different functional forms yield different policy outcomes (McKitrick, 1998) Functional forms are chosen for tractability and stable unique solutions Time-series data are generally ignored Calibration of the models rules out testing against data, so no falsification is possible

18 The approach using MDM-E3 (Multisectoral Dynamic Model extended to cover the energy-environment-economy system) MDM is a multisectoral regional econometric model of the UK economy developed in an ESRC project in the 1990s MDM-E3 incorporates sub-models for: Energy markets and atmospheric emissions Electricity supply industry CHP Domestic energy appliances Transport energy use and emissions The solutions are dynamic, integrated and consistent across the model and submodels

19 MDM-E3 theory and data Econometric, dynamic, structural, post-keynesian based on time series and cross-section (input-output data from ONS) cointegration techniques identify long-run trends in 22 sets of equations Structural: 41 industries, 13 energy users, 11 energy carriers Assumptions Social groups (not representative agents) i.e. parameters vary across sectors and regions Variable returns to scale and degrees of competition across sectors Path dependency and emphasis on history rather than equilibrium Short-term and long-run solutions With induced technological change Technological Progress Indicators (TPI) (incl. R&D) in many equations e.g. in energy-use, export, import, price, employment equations

20 MDM-E3 : the treatment of energy demand No explicit production function Energy demand as derived from demand for heat, power etc and in turn from demand for products 2-level hierarchy: aggregate energy demand equations and fuel share equations Aggregate demand affected by industrial output of user industry, household spending in total, relative prices, temperature, technical progress indicator Some users aggregate demands are also affected by trends, which are interpreted as due to changes in efficiency or mix of uses (e.g. more air conditioning)

21 Hysteresis in energy demand The finding of a significant permanent announcement effect effect implies hysteresis in energy demand Hysteresis is defined as path dependency or irreversibility and is usually found in labour market analysis, e.g. the effects of the length of unemployment on the employability of the unemployed In energy demand, it indicates that changes in the capital stock brought about by an announcement effect or an energy-efficiency policy leads to permanent reductions in demand, due to more efficient equipment and insulation and better use of energy Emerging literature on asymmetrical effects in energy demand equations (Gately, 1993; Walker and Wirl, 1993; Hogan, 1993; Grubb, 1995; Ryan and Plourde, 1996, 2000 and 2002, Gately and Huntington, 2002).

22 MDM-E3 : the aggregate energydemand equations Autoregressive distributed lag (ARDL) model energy consumption (Et) depends on energy price (Pt), output (Yt), temperature (TEt) & lagged values: Et=a0+a1Pt+ a2yt + a3tet + a4et-1 + a5yt-1 + a6pt-1 + a7tet-1+εt Re-parametrisation give error-correction mechanism (ECM) model: Et=b0+b1 Pt+ b2 Yt + b3 TEt + b4(et-1 b5pt-1 b6yt-1- b7tet-1) + εt Augmented by time trends and/or accumulated investment to represent energy efficiency improvements ECM model distinguishes between long-term and adjustment parameters

23 MDM-E3: estimated energy demand equation with announcement effects for the commercial sector Sample 1973Q2-2003Q2 Sample 1973Q2-1998Q4 Parameter Estimate t-value Estimate t-value B B B B B B5 Estimated regression B B B0 = intercept B1 = TE, temperature B2 = P, price change B3 = Error-correction B4 = Output B6 = Price B7 = AE permanent effect E t =b 0 +b 1 TE t +b 2 P t + b 3 (E t-1 - b 4 Y t-1 - b 6 P t-1 b 7 PD t-1 ) + ε t

24 Commercial and other energy demand: the fit for change (log (demand/head)) Q3 Other Final Users - Actual vs Fitted (as in the 2nd model run chart C12) 1977Q4 1982Q1 1986Q2 1990Q3 1994Q4 1999Q1 2003Q2 DLE FITTED

25 Comparing the production-function with the traditional-econometric approaches to energy demand Pesaran et al (1998) compare both approaches in estimating energy demand in Asian developing countries a theoretical treatment based on value shares from production functions as in growth theory/cge models with the traditional log-log model adopted in MDM-E3 They conclude: Although the theory suggests an equation determining the value share of energy, the data strongly prefer a traditional equation explaining the logarithm of energy demand, though this may reflect deficiencies in the measure of the share used. The neoclassical production function approach cannot accommodate hysteresis effects without violating the basic assumptions of the model.

26 Modelling the rebound effect Presumption is that the effects of energy-efficiency policies cannot be identified Cumulative combined with price, rebound and service-mix effects Appears in the econometric equation as additional error or in any time trend We have to superimpose the effect by assumption, then calculate the dynamic full-model solution Issues Extra investment in insulation etc (cost of policy?) Time trend of investment effect? Does it matter? Response of final consumers to implied extra released spending power is critical (budgetary habits) Does the policy generate regime shifts? E.g. whole-house heating, new technology cold process

27 Imposing rebound effects in MDM-E3 Method: reference case as outcome/projection , but without DEFRA policies and compared to base case, both as dynamic endogenous solutions Production Lower use of energy for same output Switch to more energy-saving mix of products Lower unit costs of energy so lower costs of production Higher output of energy-saving industries More use of energy and less use of labour and capital Consumption (e.g. household consumers of fuels): Higher imputed income (nominal income and fuel prices almost unchanged, but fuel use less for same energy service) Lower imputed unit cost of energy (for same energy service) Lower prices and higher incomes in general

28 The UK Energy System in MDM-E3 Other industry equipment demand for gas & electricity Commercial buildings CHP top-down driver: demand for energy Energy intensive industry CHP low carbon process demand for electricity Energy demand coal, gas & electricity demand for coal & gas fuel cells Micro CHP Transport vehicles demand for gasoline demand for gas & electricity onboard CHP Household appliances & dwellings Micro CHP Human energy (walking, cycling) Solar energy Electricity CHP prices & availability Solar energy UK & imported coal trade investment & regulation Other energy supply investment & trade investment in new technologies UK & imported oil & gas Energy from Wind, wave, waste, landfill tidal energy mines bottom-up driver: supplies of solar & human energy and of technologies

29 Classifications in the energy Energy Users Power Generation Other Transformation Energy industries own use Iron and Steel Mineral Products Chemicals Other Industry Rail Transport Road Transport Water Transport Air Transport Domestic Use (Households) submodel }Energy-Intensive Industries Other Final Demand (including commerce, overnment, agriculture and construction)

30 Classifications in the energy Energy Types submodel Coal and Coke (solid fuels) Motor Spirit Derv Gas Oil Fuel Oil Other Refined Oils Gas (natural gas, coke oven gas, town gas) Electricity (secondary use, pumped hydro, net trade) Nuclear Electricity Heat Other Fuel

31 Imposed effects of DEFRA Energy-efficiency policies (E-E): fuel use for energy (m therm differences baseline from reference case) Power generation Combined heat and power Own use of energy Ind, iron & steel Ind, mineral prod Ind, chemicals Other industry Rail transport Road transport Water transport Air transport Domestic final use Other final use TOTAL Source:CE/4CMR/Defra Mac Reb project MDM95R9 C42BR5-C42RR5/NO_EP

32 Imposed rebound effects of E-E policies: Direct Rebound effect (imposed as %) Power generation Combined heat and power Own use of energy Ind, iron & steel Ind, mineral prod Ind, chemicals Other industry Rail transport Road transport Water transport Air transport Domestic final use Other final use TOTAL Source:CE/4CMR/Defra Mac Reb project MDM95R9 C42BR5-C42RR5/NO_EP

33 Estimated effects of E-E policies: DIFFERENCES IN MACROVARIABLES (per cent differences baseline from reference case) Macrovariable (units) CO2 (mtc-eq) % GHG (mtc-eq) % GDP (1995)m % EMPL (employment th) % HUC (95=1.0) % Source:CE/4CMR/Defra Mac Reb project MDM95R9 C42BR5-C42RR5/NO_EP

34 Estimated effects of E-E policies: fuel use for energy (% differences baseline from reference case) Power generation Combined heat and power Own use of energy Ind, iron & steel Ind, mineral prod Ind, chemicals Other industry Rail transport Road transport Water transport Air transport Domestic final use Other final use TOTAL Source:CE/4CMR/Defra Mac Reb project MDM95R9 C42BR5-C42RR5/NO_EP

35 Estimated effects of E-E policies: fuel use for energy (m therm differences baseline from reference case) Power generation Combined heat and power Own use of energy Ind, iron & steel Ind, mineral prod Ind, chemicals Other industry Rail transport Road transport Water transport Air transport Domestic final use Other final use TOTAL Source:CE/4CMR/Defra Mac Reb project MDM95R9 C42BR5-C42RR5/NO_EP

36 Estimated effects of E-E policies: INDIRECT REBOUND EFFECT (%) DRE=100*(DFCES-DFUJ0)/(DFCGS) Power generation Combined heat and power Own use of energy Ind, iron & steel Ind, mineral prod Ind, chemicals Other industry Rail transport Road transport Water transport Air transport Domestic final use Other final use TOTAL Source:CE/4CMR/Defra Mac Reb project MDM95R9 C42BR5-C42RR5/NO_EP

37 Estimated effects of E-E policies: TOTAL REBOUND EFFECT (%) DRE=100*(DFCGS-DFUJ0)/(DFCGS) Power generation Combined heat and power Own use of energy Ind, iron & steel Ind, mineral prod Ind, chemicals Other industry Rail transport Road transport Water transport Air transport Domestic final use Other final use TOTAL Source:CE/4CMR/Defra Mac Reb project MDM95R9 C42BR5-C42RR5/NO_EP

38 Summary of other results Estimates of rebound effect appear to be robust to changes in assumptions about oil prices and EU ETS allowance prices The effects are more-or-less additive across sectors (small interactions) The higher the direct rebound effects the lower the indirect effects The investments associated with the E-E policies increase the GDP effect, but make little difference to the rebound estimates

39 Conclusions Substantial project, using the simulation properties of MDM-E3 to estimate effects by imposing E-E policies Estimates of macroeconomic rebound effects about 10-30%, which appear to be robust to changes in key assumptions Direct imputation of rebound effect using pricesubstitution elasticities may not be appropriate Macroeconomic rebound effects mainly come from reductions in production costs and imputed increases in consumer incomes