The hardest hit: Going beyond the mean

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1 The hardest hit: Going beyond the mean A report by CSE on the impact of energy policy on consumers bills Consumer Futures

2 Consumer Futures Consumer Futures represents the interests of consumers across essential, regulated markets. We use compelling evidence, expert analysis and strong argument to put consumer interests at the heart of policy-making and market behaviour. Consumer Futures is the statutory representative for consumers of postal services across the United Kingdom, for energy consumers across Great Britain and for water consumers in Scotland. It maintains the powers, responsibilities and duties of Consumer Focus. In April 2014 Consumer Futures will become part of the Citizens Advice service. Consumer Futures

3 Preface The Government s energy policies will have a positive impact on many consumers energy bills. For example, they will help fund energy efficiency, microgeneration and bill discounts and thus reduce consumers exposure to high energy prices. These policies are largely funded by consumers through their energy bills. However, consumers who do not receive measures or bill discounts will bear the full weight of policy costs without receiving any of the benefits. Consumer Futures, working with the Government s Fuel Poverty Advisory Group, set up a working group to investigate the impact of energy policy on consumers bills. We wanted to know who benefits and who loses from policy and how losing households might be compensated. We commissioned the (CSE) to assess these issues in detail. This report outlines the results of CSE s research. The report makes for disturbing reading. It finds that consumers with electric heating 11 per cent of all consumers are most affected by Government policies, yet tend to have lower incomes than those with other forms of heating. These consumers pay 19 per cent of the total cost of energy policies yet only receive 7 per cent of the benefits. Only 27 per cent of consumers with electric heating receive some form of benefit, compared to 40 per cent of all consumers. Consumers with electric heating who do not receive any benefits face an average annual bill increase of 282 in Perhaps this is not surprising. The vast bulk of the Government s policies are funded through electricity bills; thus households with electric heating face a disproportionate share of the costs. The research therefore investigated how consumers hardest hit might be compensated. It identified two groups that are both adversely affected by energy policies and are likely to live on a low income: consumers in purpose built flats with electric heating and consumers in any type of property with electric heating but with at least one pensioner householder. There are 1.7 million households in these two categories, 70 per cent of whom are in the bottom two fifths of households with respect to expenditure. The hardest hit

4 The conclusion of the report is clear, if not surprising. The best way of protecting these households is to provide energy efficiency measures that reduce their energy costs. It is not surprising because it is widely accepted that comprehensive energy efficiency measures are the most cost effective way of cutting consumption and bills. Reduced energy consumption both improves the affordability of energy and helps protect consumers from rising energy prices due to rising wholesale oil and gas prices and the cost of overhauling our aging energy infrastructure. The evidence in this report should convince the UK Government to take steps in the current Energy Bill, forthcoming Fuel Poverty Strategy and forthcoming Heat Strategy to protect those vulnerable consumers who would otherwise be most adversely affected by its energy policies. William Baker, Head of Fuel Poverty Policy, Consumer Futures Consumer Futures

5 The hardest hit: Going beyond the mean Ian Preston, Vicki White, Emma Sturtevant: Darryl Croft: Abelscroft EI May

6 Acknowledgements The team would like to thank the Fuel Poverty Advisory Group for their support and advice in producing this report. Contacts for further information Ian Preston Senior Analyst 3 St Peter's Court Bedminster Parade Bristol BS3 4AQ William Baker Head of Fuel Poverty Policy Consumer Futures Fleetbank House Salisbury Square London EC4Y 8JX 2

7 Contents 1 Introduction Rationale Study aims and objectives Approach Policy background: updating energy costs Identifying vulnerable consumers Consumer vulnerability and risk factors Policy target groups and vulnerability Distributional impacts of policy Headline results Distributional policy impacts Characterising the hardest hit Identifying low-income, worse-off households Designing a compensation package Alternative policy solutions Why does equity matter? Moving fixed costs on to unit costs Customer credits and protected blocks An equity charge universal compensation payment Reducing demand - sustainable energy measures Comparing compensation packages Impact of modelling scenarios on groups hardest hit by energy policy Conclusion Annex I: Risk factors for vulnerability Annex II: Further charts and tables Annex III: Vulnerable groups: pen portraits Annex IV: Examples of targeting approaches

8 Executive Summary Introduction The Government s Energy Bill is designed to reform the electricity market to deliver secure, clean and affordable electricity for all consumers. Contracts for Difference (CfD) are a fundamental part of the proposals. CfD will work in combination with a new Capacity Market and the Emissions Performance Standard to deliver Government aims and objectives for decarbonisation while minimising costs to consumers and risks to the security of supply. However, the Bill s proposals, as with other Government energy policies, will have significant implications for consumers energy bills. Consumer Focus the predecessor body to Consumer Futures therefore commissioned this research to support the work of the Government s Fuel Poverty Advisory Group on energy tariffs. The study is designed to assess the impact of the Energy Bill and other social and environmental policies on consumers bills, with particular attention to those not likely to benefit from ameliorative measures; and to explore potential solutions to protect those worst affected. Overall impact of energy policies on bills The research found that Government energy policies (the central policy scenario ) will reduce the average household energy bill in 2020 by 31, or 2%, compared to the average bill without policies. This decrease assumes all consumers will benefit substantially from EU products policy, which is designed to improve the efficiency of appliances. However, if product policy fails to drive savings at the scale assumed, then bills could potentially increase on average by 93 or 7% above the no policy 2020 scenario. DECC recently published its own estimates of the impact of energy policies on energy prices and bills 1. The report shows an average saving due to energy policy of 166 in 2020 considerably greater than the 31 reported in this study, despite both using CSE s DIMPSA modelling tool. However, the methodology used by the two studies differs. For example, DECC s analysis backdates savings to policies introduced in 2002 (EEC-1, EEC-2 and all of CERT) which equate to a 97 saving. It also includes savings from building regulations (boiler replacement), also introduced in 2002, which equate to a 81 saving. This research only includes savings from measures introduced after The modelling therefore produces lower savings from CERT and boiler replacement, of 34 and 38 respectively. The hardest hit A core objective of the research was to identify households hardest hit by energy policies. The graph below shows the impact of policies on 2020 household energy bills by household heating fuel for DECC s central policy scenario. Consumers that use electricity to heat their homes see an average increase in their bill relative to the no policy bill, while all other consumers see a decrease on average. 1 DECC, Estimated impacts of energy and climate policies on energy prices and bills. 4

9 Furthermore, the difference between electrically-heated winners (defined as households that get support and benefit from policy) and electrically-heated losers (households that do not get any support) is stark, at over 500. Figure A.1. Impact of policies on energy bill by heating fuel and those who do and do not receive support 400 Impact of policies on energy bill in Electric Gas Lpg Solid fuel Biomass Oil Households that do not get support Average Impact Households that get support Heating fuel Electricity is subject to the majority of policy costs. Households reliant on electricity for heating are likely to have higher than average levels of electricity consumption, compared to the rest of the population, and therefore bear a disproportionate share of policy costs. These households might expect to receive measures to offset the particularly high costs they face, but this does not appear to be the case. The research found that a lower proportion of electrically-heated households (27%) benefit from policies when compared to all households (40%). Across all households that do not benefit from energy policy, electrically-heated homes are subject to the largest increase of 282, while households using non-metered fuels experience a decrease (regardless of whether or not they benefit from policy). This is because the benefits of products policy outweigh the total policy costs for this group of consumers (the Government assumes all consumers benefit from products policy). In 2020, electrically-heated households: represent 10.5% of the total share of heating fuel by type pay 18.9% of the total cost of domestic energy policy receive 6.8% of all measures deployed. Furthermore, these householders contribute a significant amount towards large scale infrastructure projects designed to deliver energy security and renewable energy. When combined, the Electricity Market Reform (EMR) and historical legacy of the Renewables Obligation represent the largest share some 35% of total policy costs of 4.8 billion in

10 Identifying the hardest hit The analysis of the impact of Government policies on domestic energy bills by different sociodemographic characteristics highlighted important distributional issues, not least the implications for low-income households with electric heating. The research used Chi-squared Automatic Interaction Detector (CHAID) to further explore and identify the characteristics of those hardest hit. The CHAID analysis found that of the five groups hardest hit by policy costs, four use electricity to heat their home and hence have above average electricity consumption, compared to the population as a whole see box below. The last group is the only one to use gas to heat their homes. Box A. Description of groups predicted to be made worse off by policies Node 38: Average-income, electrically-heated houses in non-urban areas, with high occupancy working-age families. Node 37: Lower-income, but some asset-rich older people in electrically-heated 3-bed houses in less urban areas. Node 35: Low-income, mainly older single adults in small, electrically-heated rented houses. Node 36: Low-income single adults, in small, urban, electrically-heated rented flats. Node 40: Low-income, low-consumption single adults, nearing or retired, in small gas-heated flats. Compensating the hardest hit The research explored a range of approaches for mitigating the impact of policies on those worst affected and producing a more progressive distributional impact that is, to ensure lower income households are proportionally better off compared to higher income households. The application of an equity charge, in which a fixed credit is given to all consumers and the cost of this is recovered through raising the unit cost of energy above the median consumption threshold, provides a fairly effective form of compensation. However, it does not protect the hardest hit since this group typically consists of low-income households with above average electricity consumption. A different approach to compensating those worst affected involves targeting electrically-heated purpose-built flats and households with occupants who are over 65. There are 1.1 million households in electrically-heated purpose built flats. This group are worse off on average by over 100 as a result of policy costs, yet have lower than average income and expenditure. Similarly households with occupants that are over 65 are typically lower income, especially those that use electricity for heating. One approach to compensating these households involves allocating them a lump sum payment. However, the scale of payments required to ensure these households become better off on average is considerable (ranging from 500 to 1,000 per household). Therefore, an alternative approach involves reducing their energy costs by an average of 33 per cent through energy efficiency measures. The distributional impact of this approach is shown in the graph below. 6

11 Figure A.2. Average bill impact in 2020 by expenditure decile for the demand reduction packages Impact of policies on energy bill in Total expenditure decile Bill reduced by 33% by EE (charge funded) Average Impact - DECC Central Bill reduced by 33% by EE (tax funded) Further work is needed to quantify the cost of measures required to deliver the savings across the 1.68 million targeted households. However, the consumer credit package investigated as part of this study generated revenue of 1.1 billion per year from consumer bills, which is similar in scale to the current Energy Company Obligation. Policy implications The research explored a number of options for targeting the hardest hit households. It identified two groups that would benefit from targeting; households in purpose built flats with electric heating and all properties with electric heating containing at least one pensioner. The final stage of this research explored options for compensating these households. The research found that the provision of sustainable energy measures to reduce household energy costs was the most successful approach to protecting these households and was the most progressive option in terms of distributional impact. The review of potential policy options has shown that there remains a significant gap for those hardest hit by energy policy. The Government should consider introducing amendments to the current Energy Bill to compensate these households. It should also make sure that its forthcoming Fuel Poverty Strategy and Heat Strategy develop policies that benefit these households, for example by installing solid wall insulation, heat pumps and/or gas district heating. 7

12 1 Introduction 1.1 Rationale The Government s Energy Bill is designed to reform the electricity market to deliver secure, clean and affordable electricity for all consumers. In 2011 the Government estimated that the full range of energy and climate change policies (some of which are funded through consumers energy bills namely Electricity Market Reform (EMR), Green Deal, Energy Company Obligation (ECO), EU Emissions Trading Scheme (EU ETS), Carbon Price Floor (CPF), Feed-in Tariff (FIT), smart metering, EU products policy (PP), and the Warm Home Discount (WHD) will deliver an overall net saving of 94 (7%) on the average household energy bill in 2020, compared to the average bill in the absence of government intervention 2. However, this estimate did not take into account the most recent policy developments, such as Contracts for Difference (CfD), the Capacity Market and the new Levy Control Framework (LCF). The CfD is a fundamental part of the Government s latest proposals under the EMR package. The Government envisages CfD working in concert with the Capacity Market and the Emissions Performance Standard to deliver its objectives for decarbonisation and security of supply while minimising costs to consumers. The majority of potential increases to consumers bills in the future will be linked to these two policies and the existing Renewables Obligation. In addition, the Government raised the cap on a number of its low carbon and social policies to reflect the new CfD and Capacity Market arrangements, through the LCF agreed between Treasury and the Department of Energy and Climate Change (DECC) in Despite the tripling in size of the LCF, from 2.35 billion to 7.6 billion, the Government argues that the EMR proposals will still lead to a reduction in consumers bills relative to the counterfactual. The Government argues that energy and climate change policies, including those relating to EMR, will reduce consumers average bills due to the positive impact of policies on consumers energy consumption. The Government accepts that some consumers will benefit more and some less from policies. However, it considers that policies will benefit all consumers in the long term they reduce the UK s dependence on imports and vulnerability to volatility in global energy prices and reduce the risk of costly blackouts and consumers overall energy needs. This research examines in detail the winners and losers of energy and climate change policies. It identifies groups that are most likely to be at risk, particularly those on low incomes, and proposes potential solutions to protect these consumers. 1.2 Study aims and objectives The main aims of this research are to: 1 Assess the impact of price rises arising from the Energy Bill and other social and environmental policies on households, with particular attention to those not likely to benefit from ameliorative measures;

13 2 Assess the impact of potential solutions. The following research objectives are intended to deliver these aims: 1. Provide a detailed distributional analysis of the impact of Government policies on consumer energy bills, to update that carried out for DECC s 2011 Estimated impacts of energy and climate change policies on energy prices and bills and DECC s 2012 Energy Bill Impact Assessment Review Government assumptions on ameliorative measures with a view to assessing the likely impact if some measures are not achieved, e.g. products policy (PP). 3. Identify household types and produce illustrative pen portraits of those likely to be hardest hit by price increases arising from the Energy Bill and other policy measures, with particular attention to those not benefiting from ameliorative measures, such as improved insulation and heating, micro-generation, more efficient appliances, bill discounts and smart metering. 4. Explore the potential for a more equitable approach to recovering policy costs and assess potential policy solutions for households likely to be hardest hit, including: customer credits and protected blocks; moving fixed costs onto unit costs (including those not policy-related such as distribution charges); social tariffs; and tax-funded compensation payments. 5. Provide commentary on the feasibility and regulatory intervention required for each of the proposed policy solutions. 1.3 Approach The methodology applied in this study is outlined below. (i) Updating energy costs with new CfD data CSE and the Association for the Conservation of Energy (ACE) produced a report for Consumer Focus in 2012 looking at six future scenarios for energy costs. 5 Since then, the Government has published additional and revised costs in its final EMR impact assessment. As part of this study the energy prices used in the central scenario were updated to reflect the Government s latest impact assessments (see (ii) below). In addition, a unit cost was calculated and incorporated into the modelling to reflect the cost of the Capacity Market. Section 2 of this report provides further details on how the research calculated policy costs. (ii) Re-running DIMPSA central price scenario with CfD CSE ran its Distributional Impacts Model for Policy Scenario Analysis (DIMPSA) using the updated EMR prices from (i). The modelling uses the central policy and fuel price (wholesale and network costs) scenario produced for the 2012 research report and applies a central strike price for CfD. 4 The bulk of the research was carried out before the Government published its updated assessment of the impact of climate change and energy policies in March However, the report does occasionally refer to this assessment and compares its assessment with the Government s. 5 Croft, D., Preston, I., Guertler, P. and Carrington, J. (2012) Impact of future energy policy on consumer bills. Report to Consumer Focus. 9

14 We refer to this as the new central policy scenario 6. To provide some sensitivity analysis of Government assumptions about improvements in product efficiency, CSE ran this new scenario through DIMPSA but without PP. Energy policy costs are typically passed on to customers as either a fixed cost (per customer) or relative to consumption levels (per unit used). Table 1.1 shows a full breakdown of the policy costs currently levied on consumer s bills. Following the implementation of the Energy Act 2012, the costs of delivering the ECO are now apportioned to suppliers by the volume of energy sold rather than per customer account, as was the case with CERT. The modelling therefore assumes that the costs of the ECO are passed on as a per unit levy. Table 1.1. Policies modelled, mechanisms for cost recovery and benefits (to individual households) Policy Cost pass-through Fuel Benefit Carbon price floor Per unit /kwh Electricity None 7 EU Emissions Trading Scheme Per unit /kwh Electricity None Renewables Obligation Per unit /kwh Electricity None Smart Meters Per unit /kwh Elect. & Gas Efficiency savings Carbon Emissions Reduction Target Per customer Elect. & Gas Measures 8 Feed-in Tariff Per unit /kwh Electricity Measures Warm Homes Discount Per customer Elect. & Gas Reduction on bill Energy Company Obligation Per unit /kwh Elect. & Gas Measures Green Deal N/A N/A 9 Measures Contracts for Difference Per unit /kwh Electricity None Capacity mechanisms Per unit /kwh Electricity None Products policy No cost Efficiency savings Boiler Churn (replacement) No cost Measures Renewable Heat Incentive taxation Measures (iii) Identifying the hardest hit and vulnerable groups In addition to the headline distributional impacts results, further analysis was undertaken to identify: consumers least likely to benefit from the measures that policies offer and the extent to which policy targeting leads to exclusion of certain consumers from policy benefits; consumer groups considered vulnerable and the impact of energy policy costs on these at risk groups. 6 The policies mentioned in section 1.1 include the updated EMR, i.e. which incorporates the CfD, Capacity Market and recently updated LCF. 7 These policies do not have any associated costs savings for individual households, hence the reference to none here. 8 The term measures refers to energy efficiency improvements, heating and renewable energy technologies and gains will only be made by participating/targeted households. Several of these improvement measures applied in combination to the same property are referred to as packages of measures. 9 Measures installed under Green Deal finance are paid through instalments on the energy bill (tied to the property, not householder) linked to the level of finance received to cover the upfront costs of the measures. Only properties accessing Green Deal finance will pay this cost. There is therefore no policy cost. 10

15 Further details on the approach to identifying vulnerable consumer groups and the results of the impacts analysis on these consumers is presented in Section 5 of this report. (iv) Distributional analysis of policy impacts The results of the two DIMPSA model runs described in (ii) above were analysed to assess the impacts of policy on consumer energy bills in 2020 by key socio-demographic descriptors. The results are presented in Section 4. (v) Modelling alternative policy solutions The analysis explored several options for revised pricing and tariff support. These options seek to offset the distributional impacts associated with the Government s proposed policies by either; altering the way that policy costs are passed on to customers; charging customers an additional equity charge per unit consumed and then recycling this; and a tax funded compensation payment. 11

16 2 Policy background: updating energy costs Contracts for Difference The Government envisages CfDs will provide long-term electricity price stability to developers and investors in low carbon generation, for example carbon capture & storage, renewable and nuclear energy. Generators will receive the price they achieve in the electricity market (the reference price ) plus a top up from the market price to an agreed level (the strike price ). Where the market price is above the agreed level, the generator would be required to pay back and thus ensure value for money and greater price stability for consumers. A stable revenue level should in turn reduce investment risk and financing costs, and so drive innovation and development of low-carbon technologies. Competition will then bring down overall costs and, eventually, provide a level playing field in which low-carbon generation without subsidy can compete with other technologies in the electricity market. The CfD is a fundamental part of the Government s proposals under the EMR package. The CfD will work in concert with the Capacity Market and the Emissions Performance Standard to deliver the Government s objectives for decarbonisation and security of supply, while minimising costs to consumers. The cost of CfD to consumers has the potential to vary according to level of the strike price and changes to the underlying reference price. There are additional uncertainties that remain with the CfD design which might affect the cost of the policy and strike prices necessary for technology deployment. The subject is seen by some as controversial as the future of new nuclear generation is predicated upon achieving a strike price of sufficient value. The Bill also contains provisions for Investment Contracts which represent an early version of CfDs and are designed to encourage development of new generating plant before the full CfD system takes effect. Capacity Mechanism The Energy Bill proposes to establish a new Capacity Market to ensure security of supply. The objective of the Capacity Market is to ensure that an adequate and secure level of electricity supply is delivered in a way that is cost-effective and complementary to decarbonisation policies. It is intended to make sure there is sufficient reliable and diverse capacity to meet demand, for example during winter anti-cyclonic conditions where demand is high and wind generation low for a number of days. DECC considers the Capacity Market mechanism is the best way of reducing the risk of voltage reductions (brownouts) and controlled load shedding (blackouts) due to the energy market not bringing forward the economically optimal amount of capacity. It does this by enabling the System Operator, National Grid, to decide the level of capacity it judges is appropriate and then contracting for this capacity through an auction four years ahead. 12

17 DECC s base case analysis expects that the Capacity Market will cost 0.6 billion in NPV term 10 relative to a scenario of an efficient energy market i.e. where during times of scarcity the energy price reflects the value of lost load. While the impact of the Capacity Market on consumers bills is not clear and could vary significantly, DECC s central assumption within the November 2012 IA is for an average increase of around 14 pa. However, the Capacity Market could vary from a net benefit of 4.2 billion to a net cost of 2.1 billion. The latter would result in an average increase in consumers bills of considerably more than 14 pa. The Levy Control Framework (LCF) In 2012, the Government agreed a cap for its low carbon electricity policies to reflect the EMR package. The LCF budget for such policies in 2012/13 was 2.35 billion. This will increase to 7.6 billion in real terms by 2020/21. Despite the tripling in size of the LCF, the Government argues that the EMR proposals will lead to a reduction in consumers bills relative to the counterfactual of existing policies. In effect, the Government argues that EMR provides a more efficient mechanism for meeting low carbon and security of supply objectives. The LCF does not include other Government policy costs, such as the ECO and Carbon Price Floor, nor those emanating from EU legislation, such as the EU ETS. The Capacity Mechanism is not expected to fall within the LCF, and the 7.6bn excludes any additional budget that might be available for social policies such as the Warm Homes Discount. 10 DECC (2012), Electricity Market Reform Capacity Market, IA No: DECC

18 3 Identifying vulnerable consumers A key aim of this project is to identify consumers least likely to benefit from the ameliorative measures arising from energy and climate change policies which offset the price increases resulting from the Energy Bill and other policies. Drawing on existing literature and a review of Government statutory duties and targets linked to vulnerability and equality, CSE has developed a list of risk factors for identifying vulnerable energy consumers. 3.1 Consumer vulnerability and risk factors A number of recent publications make the case that vulnerability is not necessarily a constant state, but can be dynamic with varying short- and long-term levels of risk. These can affect any consumer at any time 11. CSE has developed a range of common risk factors (characteristics) for vulnerability (Table 3.1), which provide an alternative framework to the static group-based approach. Table 3.1 Risk factors that may indicate energy consumer vulnerability (in no particular order) Low income Unemployment Older age Physical impairment / disability Lone parent Mental health issue Being a carer English not first language Literacy / numeracy difficulties Sudden change in circumstances Rural location Electric heating Off-gas Learning disability Inexperience SAP < 35 Characteristics associated with these risk factors are captured directly in a number of Government household surveys. For example, both the English Housing Survey (EHS) and Living Costs and Food Survey (LCFS) record household income, age of occupants, employment status and household composition etc. Other factors can be derived from household survey data to create proxy measures. For example, the LCFS records information about household income from benefits, such as Carers Allowance and Disability Living Allowance, which indicate the presence of a carer and disabled person in the household. However some risk factors, such as inexperience or sudden change in circumstances, are not possible to quantify with existing available data and/or are considered more subjective, such as restricted capacity to cope and limited choice of deal. These have therefore been excluded from the analysis in this study. For further commentary on vulnerability factors see Annex I. 11 Ofgem,(2012),Proposals for a new Consumer Vulnerability Strategy Consultation Document; Centre for Consumers and Essential Services, University of Leicester on behalf of eaga Charitable Trust (2011), Too many hurdles: information and advice barriers in the energy market; Consumer Focus (2012), Tackling consumer vulnerability an action plan for empowerment. 14

19 3.2 Policy target groups and vulnerability The extent to which targeting of existing Government policies namely the Cold Weather Payment (CWP), Warm Home Discount (WHD), ECO Affordable Warmth (ECO AW) and the Priority Service Register 12 align with the risk factors identified above in Table 3.1 is explored below. Each funding stream was scored according to the extent to which eligibility criteria for the policy target groups overlap with the risk factors of energy consumer vulnerability. The results (Table 3.2) suggest that all of the existing policy target groups exclude at least 9 of the 16 risk factors that are indicative of energy consumer vulnerability. The CWP scores highest and thus overlaps more with our analysis of vulnerability than the others. The WHD scores on only 3 key risk factors, but as it is targeted only at those aged 65 and over (Pension Credit qualifying age) it explicitly excludes all other risk factors. Eligibility for ECO AW aligns with that of the CWP, but there is an additional choice element to consider, as ECO AW represents an opt-in scheme (whereas CWP is issued automatically). Table 3.2. Risk factors for energy consumer vulnerability scored against policy eligibility criteria. See Annex I for the methodology used to determine these scores. Risk factors Cold Weather Payment Warm Home Discount ECO Affordable Warmth Priority Service Register Low income 100% 70% 70% 75% Unemployment 75% 50% 60% 25% Older age 25% 100% 20% 25% Physical impairment / disability 50% 0% 40% 75% Lone parent 25% 0% 40% 0% Mental health issue 50% 0% 30% 25% Being a carer 50% 0% 30% 0% Learning disability 0% 0% 0% 0% English not first language 0% 0% 0% 0% Literacy / numeracy difficulties 0% 0% 0% 0% Sudden change in circumstances 0% 0% 0% 0% Inexperience 0% 0% 0% 0% Rural location 0% 0% 0% 0% Electric heating 0% 0% 0% 0% Off-gas 0% 0% 0% 0% SAP < 35 0% 0% 0% 0% Mean 23% 14% 18% 14% 12 It should be noted that the definition of Priority Service Register varies amongst suppliers. 15

20 4 Distributional impacts of policy 4.1 Headline results The impact of Government energy policies on the 2020 household energy bill (the central policy scenario, i.e. standard DECC assumptions which includes products policy 13 ) is an average net decrease of 31, or 2%, compared the expected bill in 2020 without policies (see Table 4.1). This is lower than the 69 average reduction in 2020 energy bills identified in a similar study undertaken in 2012 (Croft and Preston 14 ). This analysis was completed prior to the publication of the most recent proposals for CfD and Capacity Mechanisms. The analysis carried out for this research takes account of the latest EMR impact assessment. DECC recently published its own estimates of the impact of climate change policies on consumers energy prices and bills, using CSE s DIMPSA tool 15. The report shows that energy policies result in a net average saving of 166 to the average consumer bill in While the average saving revealed by this research is significantly lower than DECC s estimate, despite both estimates using the same DIMPSA tool, different assumptions were used for the two studies. DECC s analysis includes savings from the whole Energy Efficiency Commitment programme (which started in 2002) and all of CERT and estimated this saving to equal 97. It also includes savings from building regulations, namely boiler replacement, which came into effect in 2002, of 81. The research carried out for this report only includes the impact of measures from 2010 onwards. This produces much lower savings for CERT and boiler replacement of 34 and 38 respectively. Table 4.1. Impact of the central policy scenario on average household energy bills EMR with PP EMR without PP Bill without policies 1,142 1,269 1,335 1,142 1,269 1,335 Bill with policies 1,196 1,301 1,304 1,206 1,349 1,427 Impact of policies Impact of policies % 5% 3% -2% 6% 6% 7% Table 4.1 shows that if Government assumptions about improvements in product efficiency standards 16 are removed, the average household energy bill in 2020 appears over 90, or 7%, higher than the bill without policy intervention. Household energy bills in 2020 will be on average around 160 (with products policy) to 220 (without products policy) higher, compared to a 2011 baseline without policies (see Figure 4.1). This illustrates the fact that factors such as wholesale energy costs and network costs are by far the largest driver of price increases. 13 The policy assumptions used for this research are designed to match as closely as possible DECC s latest policy analysis. 14 Croft D. and Preston I. (2012), Impact of energy policy on consumer bills, Consumer Focus 15 DECC (2013), Estimated impacts of energy and climate change policies on energy prices and bills 16 Improvements to the efficiency of lighting, white goods and brown goods 16

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