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Presentation on theme: "COST-BENEFIT ANALYSIS OF DOMESTIC ENERGY EFFICIENCY J. PETER CLINCH, JOHN D. HEALY (2001) Petra Woods."— Presentation transcript:


2 O BJECTIVES To advance the literature and develop a template for ex-ante economic analyses of large-scale domestic energy-efficiency programmes. Provide insights into the methodological difficulties and solutions for addressing the social efficiency of such programmes.

3 Ex-ante economic evaluation of a programme to bring the thermal standards of the Irish housing stock up to the 1997 building regulations over a ten year period – i.e. retrofitting the 1.2million dwellings built prior to 1997 with various technologies and upgrades

4 METHODOLOGY - Model Energy Assessment Model (EAM) Bottom up model – 1824 representative dwellings 8 dwelling types 6 categories of insulation 19 types of heating systems Cost-Benefit Model (CBM) was added to provide monetary amounts. Discount rates 0% to 10% D/Finance 5% key rate

5 CostsMaterialsPriced by QS Labour Numbers Estimated using top-down approach Values Shadow price of labour Skilled: market price Retrained: zero BenefitsEnergy Numbers Literature review – energy saving vs comfort Values Monetary value (current) sensitivity analysis ±1% Environment Numbers EAM: CO 2, SO 2, NO x PM 10 Values Benefits-transfer approach / literature Mortality Numbers Excess winter mortality (CVD and RD) attributable to low thermal performance of housing Values Value of statistical life (willingness to pay to avoid risk – lower in over 65s) (literature) Morbidity Numbers Excess winter morbidity (CVD and RD) Values Cost of illness approach (hospitalisation and drugs) Loss of productivity/willingness to pay to avoid RAD ComfortProportion of energy savings foregone, as a proxy for the value placed on increased comfort

6 COSTS - Materials Treatments chosen and priced with assistance from QS on basis of cost- effectiveness: Fitting of lagging jacket Roof insulation/upgrade Draught-stripping Cavity-wall insulation Central heating Heating control upgrade Low-emissivity double glazing

7 COSTS – LABOUR NUMBERS Tried to develop an efficient mix of skilled workers and retrained unemployed people Year 2000 – skills shortage in construction a big factor, as is very low unemployment rate Some works assumed to be undertaken by people who would be otherwise unemployed, remainder by specialists Estimated approx full-time equivalent jobs over ten years, or 49,000 job years Costs per job year (€51k) somewhat higher than in other comparable studies

8 COSTS: VALUING LABOUR INPUT Shadow price of labour Where the market clears, shadow price = market price (displacement potential) Where there is high unemployment, potential for additionality, shadow price = zero Authors conclude: market price for skilled workers, zero for previously unemployed people

9 C OSTS – SENSITIVITY ANALYSIS Identified 2 competing pressures: Downward pressure on prices caused by increase in competition in the market as more firms enter and specialise Upward pressure on prices caused by capacity constraints 3 Scenarios High cost Medium cost (where upward and downward pressures cancel) Low cost

10 BENEFITS – ENERGY USAGE Consumer welfare will increase as a result of energy efficiency improvements Energy benefits / increased comfort 70-75% in energy savings on average 60% low-income households, (UK studies) EAM attempts to mirror this by assuming benefits are taken as comfort up to average temperature of 17.7ºC and then taken as reduced energy use

11 BENEFITS – ENERGY VALUES Monetary value placed on savings Sensitivity analysis Identified pressures on energy prices Deflationary pressures: improved technology; increased availability of renewables; impending deregulation of sector Inflationary pressures: rapid economic growth/increased demand; carbon taxation/ETS; oil shock etc. 3 scenarios Annual real price increase of 1% Annual real price decrease of 1% No change (upward and downward pressures cancel)

12 BENEFITS - ENVIRONMENT Volume: EAM used to estimate reductions in CO 2, SO 2, No x, PM 10 Value: Used benefits-transfer approach and assigned values on the basis of damage estimates from literature Set estimates and upper and low ranges

13 BENEFITS - MORTALITY More people die in winter than at other times of year – “excess winter mortality: CVD and RD Comparison with Norway Proportion of excess winter mortality attributable to poor thermal standards estimated to be: CDV 50% (381 deaths) RD 57% (271 deaths)

14 BENEFITS - MORTALITY Value of statistical life (VSL) – “ the sum of individuals’ own valuations of reductions in risks to their own lives ” – involves aggregating up from a willingness to pay for risk reduction. On the basis of substantial review of literature: VSL estimate of 3.03million for under-65s and 2.18million for over 65s Do look at age-adjusted VSL – and value of a life year VoLY but note the problems and conclude best to use standard approach.

15 BENEFITS - MORBIDITY Again on basis of CVD and RD Objective is to assess avoided cost to individual who would have been ill if their house was colder Assess the avoided cost to wider society from that person avoiding illness Using those assessments to derive society’s willingness to pay for reducing such morbidity. Hospitalisation and drugs – i.e. cost-of-illness approach Loss of productivity/RAD

16 BENEFITS - COMFORT Difficulties in valuing due to subjectivity Very little empirical work Note from literature that “ evidence demonstrating the positive impact of improved housing on reported psychological distress is now well established ” Benchmark of 17.7ºC as safe and comfortable Proportion of energy savings foregone, as a proxy for the value placed on increased comfort Comfort benefits accrue mainly to low-income households

17 RESULTS For 5% discount rate: Costs = €1,601m Benefits = €4,723m Discount rateCosts Energy CO2SO2NOxPM10MortalityMorbidityComfort Net social benefit 0% % % % %

18 WEAKNESSES Necessary to make assumptions on household behaviour – need to predict combination of energy saving and comfort that will be chosen Future energy prices cannot be predicted with certainty Cannot predict future technological benefits Health benefits particularly difficult Estimate physical numbers of deaths and illnesses attributable to inadequately heated homes Choose appropriate coefficients for reduced risk of death and disease Comfort benefits also very difficult to value


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