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					Fuel Poverty in London: Figures and
tables illustrating the challenge of
tackling fuel poverty
Final report
Copyright

The Greater London Authority
September 2008

Published by
The Greater London Authority
City Hall
London, SE1 2AA




This report is available on the Greater London Authority web pages, which are available from:
www.london.gov.uk



Written by

Association for the Conservation of Energy          Impetus Consulting

Westgate House                                      12 Abbeville Mews
2a Prebend Street                                   88 Clapham Park Road
London N1 8PT                                       London SW4 7BX

020 7359 8000                                       020 7819 2430
pedro@ukace.org                                     joanne.wade@impetusconsult.org.uk

Richard Moore                                       Centre for Sustainable Energy

40, The Avenue                                      3 St Peter’s Court
Cheam                                               Bedminster Parade
Surrey SM2 7QE                                      Bristol BS3 4AQ

020 8661 2630                                       0117 934 1400
rm003d1171@blueyonder.co.uk                         ian.preston@cse.org.uk


The views in this report are the authors’ own and do not necessarily reflect those of the Greater
London Authority.
Fuel Poverty in London



Executive summary
This report presents figures and tables to illustrate the challenge of tackling fuel poverty in London.
It is based in large part on a model taking the English House Condition Survey as its basis, which by
updating households’ incomes, dwellings’ energy efficiency and fuel prices provides reliable
estimates of the incidence of fuel poverty in London in 2008. The report also presents the findings of
a survey of local authorities and the results of using the Centre for Sustainable Energy’s Fuel Poverty
indicator to map the incidence of fuel poverty in London.

Housing stock
The energy efficiency of London’s housing stock is consistently being improved, but more activity will
be necessary to ensure that the proposal in the Mayor’s 2004 Energy Strategy that ‘there should be
no occupied dwelling in London with a SAP rating less than 30 by 2010, and less than 40 by 2016’ is
achieved. The implementation of Energy Performance Certificates, coupled with the provision of
this data to the Home Energy Efficiency Database, should contribute significantly to improving
targeting of such activity.

Fuel prices
The very low retail gas and electricity prices experienced in 2003 are unlikely to recur in the short or
medium term, implying that fuel prices will continue to be the strongest determinant of fuel
poverty, under all of four fuel price scenarios developed to assess future incidence of fuel poverty in
London. Based on short-term predictions, by October 2008 the highest fuel price scenario will be the
most accurate.

Incidence of fuel poverty
Three definitions of income have been used to assess the incidence of fuel poverty in London. The
full income (central government’s) definition, the residual income (Energy Strategy) definition, and
the equivalised income definition. Under the residual income definition – which lowers disposable
household incomes because it is after housing costs – the incidence of fuel poverty in London
increases from ten per cent of households (318,000 under the full income definition) to 24%
(760,000) in 2008. The increases are particularly marked in the rented tenures (which constitute a
minority – albeit a significant one at 41.5% of London’s households, with the remainder being
owner-occupied). At the same time, London’s ‘ranking’ amongst English regions changes from last
(lowest incidence of fuel poverty) to fifth out of nine.

Survey of local authorities
There were a significant number of respondents (40%) who either had no estimate of the level of
fuel poverty in their borough, or had so little confidence in the estimates they did have that they
were unwilling to share them. Therefore the results of this work could be very useful to them, if they
have confidence in the output. The data sources used by many of the authorities who are willing to
estimate levels of fuel poverty are consistent with the ones used for this report. Therefore there is a
good chance that the results of the modelling will be recognised as offering ‘best available’
estimates.




Association for the Conservation of Energy
Fuel Poverty in London


Mapping the incidence of fuel poverty in London
The spatial distribution of fuel poverty in London, using the Centre for Sustainable Energy’s Fuel
Poverty indicator, found that fuel poverty is generally more concentrated in London’s eastern
boroughs. At the intra-borough level, the maps reveal a more variable picture. These maps use the
full income definition.

Demographics
Over two million of London’s 3,180,000 households are defined as vulnerable. The incidence of fuel
poverty in this group is above-average, with 12.2% (254,000) fuel poor under the full income
definition and 27.5% (572,000) under the residual income definition. Allowing for household size and
composition using the equivalised income definition (which is otherwise the same as residual
income, i.e. income after housing costs), markedly more households with children under the age of
16, constituting one of the groups categorised as ‘vulnerable’, fall into fuel poverty (35.7%, as
opposed to 6% and 23% under the full and residual income definitions respectively). In Black, Asian
and Minority Ethnic (BAME) compared to White households, the difference in the levels of fuel
poverty are not statistically significant under the full income definition. However, under the
equivalised definition, the incidence of fuel poverty in BAME households is approximately twice as
high as in White households. Finally, under the full income definition, a large minority of fuel poor
private sector households (85,000 of 204,000) are not in receipt of any of the passport benefits that
would make them eligible for Warm Front grants. This proportion increases under the other
definitions of income.

Synthesis
On average, households spending proportionately more of their income on fuel face higher unit
energy costs, have lower incomes and live in less energy efficient dwellings than households who
spend a lower proportion of their income on fuel.

Pre-payment meters
The number and proportion of London households paying for their energy bills via pre-payment
meters is growing. For example, 20% of households pre-pay for their standard electricity tariff. Given
that pre-payment customers pay on average more than credit or direct-debit customers do, the
growth in the number of these meters poses strong challenges in the context of rising levels of fuel
poverty.

Assessing relative importance of contributory factors
Using regression analyses, the relative importance of factors contributing to fuel poverty were
assessed. Income was identified as the most important causal factor, with London households in the
lowest income quintile over 117 times more likely to be in fuel poverty than households that are not.
Similarly, households living in the least energy efficient fifth of homes are nearly three times as likely
to be fuel poor than others. The 20% of households with the most space per adult are also nearly
three times as likely to be in fuel poverty.




Association for the Conservation of Energy
Fuel Poverty in London



Contents
Executive summary .................................................................................................................................. i

Contents ................................................................................................................................................. iii

1      Introduction .................................................................................................................................... 1

2      Results ............................................................................................................................................. 1

    2.1        Housing stock .......................................................................................................................... 1

       2.1.1           Heat loss of typical London property types .................................................................... 1

       2.1.2           Energy ratings ................................................................................................................. 2

       2.1.3           Insulation standards........................................................................................................ 5

    2.2        Fuel prices ............................................................................................................................... 7

    2.3        Incidence of fuel poverty ........................................................................................................ 9

       2.3.1           Current and future incidence of fuel poverty in London ................................................ 9

       2.3.2           Incidence of fuel poverty in 2016 by wall type ............................................................. 10

       2.3.3           Proportion of households in fuel poverty by English region ........................................ 11

    2.4        Survey of local authorities .................................................................................................... 12

       2.4.1           The survey ..................................................................................................................... 12

       2.4.2           Current levels of fuel poverty ....................................................................................... 13

       2.4.3           Accessing national grant programmes.......................................................................... 14

       2.4.4           Local authority activities ............................................................................................... 16

       2.4.5           Future cooling requirements ........................................................................................ 17

       2.4.6           Government policy........................................................................................................ 17

       2.4.7           Implications of the survey findings ............................................................................... 18

    2.5        Mapping the incidence of fuel poverty in London ................................................................ 19

    2.6        Demographics ....................................................................................................................... 19

       2.6.1           Fuel poverty in vulnerable households ......................................................................... 19

       2.6.2           Black, Asian and Minority Ethnic households in fuel poverty....................................... 20

       2.6.3           Eligibility for Warm Front .............................................................................................. 20


Association for the Conservation of Energy
Fuel Poverty in London


   2.7        Synthesis ............................................................................................................................... 21

   2.8        Pre-payment meters ............................................................................................................. 22

   2.9        Assessing relative importance of contributory factors ......................................................... 23

Appendix I – Definitions of fuel poverty ............................................................................................... 25

   Introduction ...................................................................................................................................... 25

   Overall frequency of fuel poverty ..................................................................................................... 26

   Incomes and Fuel Costs..................................................................................................................... 27

Appendix II – Fuel price scenario development .................................................................................... 32

   Historical fuel prices and fuel price scenarios .................................................................................. 32

   International context ........................................................................................................................ 33

   EU context ......................................................................................................................................... 33

   UK context......................................................................................................................................... 34

   Conclusion ......................................................................................................................................... 35

Appendix III – Modelling fuel poverty: the Fuel Prices Model.............................................................. 36

   Overview of the Model ..................................................................................................................... 36

   Determining trends in fuel prices ..................................................................................................... 37

      Price rises to Q2 2006 ................................................................................................................... 37

      Price Rises since Q1 2006.............................................................................................................. 38

      Price rises since Q1 2007 .............................................................................................................. 39

   Determining trends in energy efficiency........................................................................................... 39

      Dwellings improved ...................................................................................................................... 39

      Extent of improvement ................................................................................................................. 40

      Improvement rates ....................................................................................................................... 41

   Determining income trends .............................................................................................................. 42

      The 2004 EHCS Income Model ...................................................................................................... 42

      Updating the 2004 incomes .......................................................................................................... 42

Appendix IV – Equivalising EHCS incomes ............................................................................................ 47



Association for the Conservation of Energy
Fuel Poverty in London


Appendix V – Datasets and other statistics used for this report .......................................................... 49

Appendix VI – Glossary ......................................................................................................................... 50

   Decent Home standard (DHS) ........................................................................................................... 50

   Eligibility for Warm Front .................................................................................................................. 50

   SAP .................................................................................................................................................... 51

   Under-occupancy .............................................................................................................................. 51

   Vulnerable household ....................................................................................................................... 51

Bibliography .......................................................................................................................................... 52




Association for the Conservation of Energy
Fuel Poverty in London




1 Introduction
This document presents a series of attractive and easy to read tables, figures and accompanying
notes and appendices that convey a clear message and a current understanding as to how key
variables coalesce to cause fuel poverty in London now and in the future. Their primary purpose is to
inform the Mayor of London’s forthcoming Climate Change Mitigation and Energy Strategy.
Subcontractors involved in this work were Dr Richard Moore, Impetus Consulting and the Centre for
Sustainable Energy.


2 Results
Where figures are dated 2005 or earlier, these are estimates based directly on English House
Condition Survey (EHCS) data, which is a survey of 15,874 homes in England, carefully structured to
be representative. Within this sample, 2,133 homes are in London. Estimates for 2008 and beyond
are projections. Where appropriate, confidence intervals at the 95% confidence level are indicated
throughout by error bars in the charts. These mean that we can be 95% sure that the sampling
errors are within the range of the error bars. The source for charts and tables (for 2008 and beyond)
in this report is the Fuel Prices Model, unless otherwise stated. The Fuel Prices Model takes the EHCS
as its starting point and generates projections by updating household incomes, fuel prices and
improvements in energy efficiency to provide up-to-date snapshots of fuel poverty. The model is
described and explained in depth in Appendix III and was developed, under peer-review over the last
three years, using numerous data sources in addition to the EHCS.

2.1 Housing stock

2.1.1 Heat loss of typical London property types
The chart presents the most typical London property types, representative of more than 90% of
London dwellings. The remaining 10% of ‘non-traditionally’ constructed, property types1 would
typically have rates of heat loss in between the pre- and post-war categories (before any energy
efficiency improvements are carried out). Solid walls are represented by the ‘pre-war’ columns and
(un-insulated when constructed) cavity walls are represented by the ‘post-war’ data series. Solid
walls have not been constructed since the 1940s.
                                                            2
Figure 1: Rates of heat loss for typical London property types ; detached homes constitute approx. 6% of
London’s homes; 26% semi/end terrace; 19% mid-terrace; 49% flats

For the mid-terrace, top-flat and lower flat property types, the rate of heat loss implied by the Code
for Sustainable Homes is the same as for the 2006 Building Regulations. This is because the Code
does not set specific requirements for each element of the properties’ fabric in the way the Building
Regulations do. Rather, it requires compliance with a Heat Loss Parameter (HLP), which is expressed
as heat loss per square metre of floor area. This is translated into Watts per degree Celsius and
would be the same value for properties of the same floor area, regardless of their built form. As all

1
 For example with in situ concrete, concrete panel, timber panel or metal sheet walls.
2
 U values used to calculate heat loss from typical pre- and post-war dwellings based on peer-reviewed model
base buildings employed in Fuel Prophet (www.fuelprophet.org) and the accompanying report (Smith, Wu and
Pett 2005).

Association for the Conservation of Energy
Fuel Poverty in London


property types in the chart have been adjusted to the same floor area of 72m2, the maximum heat
loss rate stipulated by the Building Regulations 2006 is actually lower than the Code’s, in the case of
the intrinsically more efficient property types (mid terrace, top and lower flats). Given that
complying with the Code for Sustainable Homes is not an alternative to compliance with the Building
Regulations, the latter’s stipulated rate of heat loss, being lower, has been chosen for these three
property types (light blue columns). What Figure 1 illustrates is that the Code for Sustainable Homes
standards are much easier to achieve in flats than in (say) detached properties of the same size3.

2.1.2 Energy ratings
Throughout this section, with the exception of the figures illustrating the percentage of the occupied
London housing stock below the SAP thresholds 30 and 40, the latest SAP 2005 ratings are used. The
SAP 30 and 40 thresholds are based on SAP 2001 ratings to allow comparison with the same
benchmarks used in the Mayor’s Energy Strategy in 20044.

What emerges in Figure 2 is a pattern which is the same nationwide, with housing association stock
being the most energy efficient, and homes owned outright being the least efficient. The same
‘energy efficiency hierarchy’ of tenures is repeated throughout the various assessments of energy
ratings in this section.

  Number of
households in        289,000            486,000            531,000          1,155,000            717,000
 each tenure
Figure 2: Average SAP rating in London by tenure in 2008

Figure 3 presents the same information as above in terms of the distribution of energy performance
certificates (EPCs). EPCs are rated from A (most) to G (least efficient) and are based on bandings of
SAP 2005 ratings, and contain information on cost-effective energy improvements – including their
impact on fuel bills and CO2 emissions.

EPCs are required when a building is constructed, sold or rented out. They are valid for ten years,
except for sales of homes which are subject to the Home Information Pack Regulations 2007, where
a Home Information Pack (HIP) is required. In these cases an EPC must be no more than twelve
months old when the property is first marketed.

When the construction of a new building is completed, the builder or person responsible for the
construction is responsible for obtaining the certificate and providing it to the owner. This is a duty
under Building Regulations. This will also apply if a building is converted into fewer or more units and
there are changes to the heating, hot water provision or air conditioning/ ventilation services. Since
April 6 2008, homes require an EPC on construction or such conversion. For existing buildings that
are to be sold, the building's owner is responsible for ensuring a certificate is made available to all

3
  Varying levels of the Code require a percentage improvement over the Building Regulations’ Dwelling
Emissions Rate (DER). Whilst in practice much of this improvement will be achieved by constructing dwellings
with much lower rates of heat loss than stipulated by the Regulations, not all of it will – low to zero carbon
(LZC) technologies will also be used to achieve the reduced DER. This mix of energy efficiency and LZC will vary
depending on the construction, which is why Figure 1 considers only the Code’s required heat loss parameter.
4
  Though the differences between SAP 2005 and SAP 2001 are numerous, the clearest illustration of their
‘incompatibility’ can be made on the basis of the former operating on a scale from 1 to 100, and the SAP 2001
rating system going up to 120.

Association for the Conservation of Energy
  Fuel Poverty in London


  prospective purchasers at the earliest opportunity. For the marketed sales of homes (since
  December 14 2007), including homes marketed before they are physically complete, Home
  Information Pack (HIP) regulations apply. Where a HIP is required an EPC must be produced as part
  of the pack (for off plan homes this will be an indicative energy assessment). Finally, when buildings
  are to be rented out, the landlord is responsible for ensuring a valid certificate is made available to
  all prospective tenants (from October 1 2008).

  If and when (as is intended) EPC data is incorporated into a national database5, the ability to target
  energy efficiency and fuel poverty programmes effectively should be significantly improved.
  Whether this happens will depend on the appropriate people, such as local authorities, having
  access to the data in addition to the EST.


Number of households in
                               289,000           486,000       531,000        1,155,000          717,000
           each tenure

  Figure 3: EPC distribution by tenure in 2008

  A, B and C ratings have been grouped together due to the numbers of A and B ratings being too low
  to warrant separating them out. Figure 3 again illustrates the differences between the energy
  efficiency of homes in different tenures, but in showing the SAP distributions is more revealing than
  Figure 2. The social-rented sectors are the most energy efficient for a number of reasons, including
  the higher share of flats than in the owner-occupied sector, a higher share of newer dwellings and
  the impact of regulation, management and investment (such as Decent Homes improvements). The
  private-rented sector is not typically the next most efficient. However, in London the share of flats in
  the sector is higher than in other parts of the country, which can explain the average energy
  efficiency to some extent.

  In Figure 4, showing the proportion of homes below SAP 40 (using the 2001 scale; a proxy for failing
  to meet the Decent Homes thermal comfort criteria) the same ‘energy efficiency hierarchy’ of
  tenures emerges, albeit presented in reverse order. What is noteworthy is the clearly different
  distribution in the private-rented sector of homes lower than SAP 30 on the one hand and rated
  between 30 and 40 on the other. This is in part because the sector has both a higher share of pre-
  1918 (less energy efficient) and post-1981 (more energy efficient) dwellings than the other tenures.

   Number of
 households in        717,000            1,155,000         531,000           486,000            289,000
  each tenure
  Figure 4: Percentage of households by tenure below SAP 2001 thresholds 40 and 30 in 2008

  Figure 5 presents estimates of the proportion of homes under SAP 40 and SAP 30 to 20166. These
  projections are based on the assumption that recent improvements rates in domestic energy
  efficiency in London, including those brought about by new housing, (as shown by successive EHCS)
  will continue - in short, by adopting a business as usual scenario. However, it would appear that a
  5
    Likely to be the existing Home Energy Efficiency Database (HEED).
  6
    As with Figure 6 and Figure 7, future energy efficiency improvements in the stock have been modelled by
  determining, from the EHCS distribution of SAP ratings, the improvements in energy efficiency in each tenure
  in London since 2003, applying the same differential rates of improvement to future years and determining the
  consequent new SAP ratings.

  Association for the Conservation of Energy
Fuel Poverty in London


significant step-up of current and projected rates of energy improvements, particularly for solid wall
dwellings in the private sector, is required to achieve the proposal in the Mayor’s Energy Strategy
that:

‘There should be no occupied dwelling in London with a SAP rating less than 30 by 2010, and less than 40 by
2016.’ (GLA 2004)

BERR have noted that in future those living in solid walled dwellings are more likely to remain in fuel
poverty. “This analysis indicates that measures currently available under our main programmes can
generate significant reductions in fuel poverty, but cannot tackle the issue alone. This is because a
significant proportion of those modelled as remaining in fuel poverty in 2010 live in solid-walled
dwellings (around half) or do not have a gas supply (around a quarter).” (UK Fuel poverty strategy,
5th annual progress report, Dec 2007).
                                                                                      7
Figure 5: Percentage of households below SAP 2001 thresholds 40 and 30 over time

In addition to the policy-critical SAP (2001) thresholds of 30 and 40, two additional, important SAP
thresholds have been examined in London and presented in Figure 6 – SAP (2001) 35 and 65. Less
than SAP 35 is the Government’s proxy for a ‘Category I Hazard of Excess Cold’, requiring remedial
action by the owner under the Housing Health and Safety Rating System (HHSRS). The HHSRS gives
local authorities the power to alleviate fuel poverty (while potentially also reducing carbon
emissions) at very little cost to the taxpayer (as landlords can be required to pay for the measures).
Local authorities have a legal duty to arrange for an inspection of any premises to determine
whether there is a hazard following a well-founded complaint or request. However, HHSRS is not
being used nearly as widely or as effectively as it could be8.

For quite some time now, SAP 65 has been regarded as a minimum SAP target after energy efficiency
improvements (particularly in social housing) and a level above which, within reason, the risk of the
occupying household falling into fuel poverty is acceptably low9. Figure 6 shows the percentage of
households below and above SAP 2001 thresholds 35 and 65 over time, based on the same
modelling of energy efficiency improvements underlying Figure 5.
                                                                                                 10
Figure 6: Percentage of households below and above SAP 2001 thresholds 35 and 65 over time

Similarly, Figure 7 illustrates the improvement in energy efficiency of all of London’s housing stock to
2030, presenting both the changing distribution of EPCs and the improving average SAP (2005) rating
on the second vertical axis. In 2030, around 5% of homes are still rated F or below. The rate of
improvement of the least energy efficient properties slows as the more readily achievable energy
efficiency gains are made. These 5% are representative of the hardest and most expensive to treat
dwellings.

Tackling the hardest properties to treat would require new policy and better use of existing policy. It
should also be noted that this SAP figure is before the fuel price rises in 2008.

7
  Years prior to 2008 from respective EHCS surveys.
8
  Impetus Consulting 2008
9
  For example in the analysis of the Energy Efficiency Commitment’s effect on reducing fuel poverty (Defra
2006); or as a ‘high level of energy efficiency’ by the Fuel Poverty Advisory Group as well as the benchmark
Warm Front grants ought to achieve (FPAG 2005).
10
   Years prior to 2008 from respective EHCS surveys.

Association for the Conservation of Energy
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          Number of
       households in   2816   3000     3011     3041    3085     3178
     column (1,000s)
                                                                                                      11
Figure 7: Distribution of EPCs in London housing over time [percentage; each group adds up to 100%]

2.1.3 Insulation standards
The following three tables provide a snapshot of the levels of insulation and double glazing in
Greater London’s homes, based on the latest available EHCS data (2005). The final column of each
table presents the equivalent and latest HEED data12 (dominated by entries up until 2005, i.e. at the
end of EEC-1).

Though geographical coverage is the same, and the dates similar, it is clear that there are large
discrepancies between the EHCS and HEED. Some of these are more readily explained than others –
the differences may primarily result from the EHCS using a carefully structured representative (albeit
much smaller) sample and rigorous surveys, whereas HEED data is collated from surveys that vary in
the level of detail and are probably biased towards homes that undergo improvements. The
comparison between EHCS and HEED data in all three tables is strongly affected by the proportion of
homes in HEED where no data on a specific aspect of a property was collected. For example, the
proportion of London homes in HEED with ‘unknown / not available’ entered as the level or
presence of loft insulation is 73.9%. This may be partly explained by the fact that presently a large
proportion of entries in HEED are based on householders’ own completions of ‘Home Energy Check’
(HEC) questionnaires, usually provided to them by energy suppliers or Energy Advice Centres. These
data are intrinsically less reliable than HECs completed with professional help, by professionals
alone, or fuller surveys, as knowing how to distinguish between (say) cavity and solid walls is not
common knowledge. In the tables below, this proportion in each case has been excluded from the
sample in order to provide a more meaningful comparison with the EHCS. The most glaring
discrepancy is perhaps the ratio of insulated to uninsulated cavity walls in Table 2.

Table 1: Loft insulation in London by tenure – 2005 (all data is from EHCS apart from last column; bold
numbers in grey rows are in 1,000s of households; italics beneath each grey row are corresponding
                               13
percentages for each column)

Although labelled ‘loft insulation’, the EHCS 2005 records roof insulation thicknesses for all
houses/bungalows and top floor flats regardless of whether they have a pitched or flat roof.
Provided they are self-contained, all lower-floor flats, whether converted or purpose built,
are recorded as having no loft and these account for all 30% of homes in London with no loft – or,
more precisely, no immediately adjacent roof. Overestimating the number of properties which have
lofts means that the cost of energy efficiency measures is underestimated. This is because insulating
a roof with no loft is more expensive.




11
   Years prior to 2008 from respective EHCS surveys.
12
   EST 2008
13
   EHCS 2005 and HEED (HEED is source for last column only)

Association for the Conservation of Energy
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                                                             14
Table 2: Cavity wall insulation in London by tenure – 2005
                                                     15
Table 3: Double glazing in London by tenure – 2005

Whilst HEED at present has a number of shortcomings, its increasing importance as a tool for
identifying energy efficiency improvement opportunities cannot be overstated. The database
continues to grow and data collection continues to improve. Importantly, at time of writing, data
from EEC-2 (2005-2008) had not yet been incorporated – which will give HEED a significant boost in
terms of sample size and accuracy. If, as mentioned in section 2.1.2, EPC data is added to HEED, its
reliability will be strengthened still further.




14
     EHCS 2005 and HEED (HEED is source for last column only)
15
     EHCS 2005 and HEED (HEED is source for last column only)

Association for the Conservation of Energy
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2.2 Fuel prices
Historical prices for retail gas and electricity are illustrated in the two figures below, including
forward projections for alternative future fuel price scenarios to 2030. These are employed in the
sensitivity analysis in section 2.3.1. See Appendix II for the background to the development of the
fuel price scenarios. Prices are expressed in 2007 £s.
                                                                         16
Figure 8: Retail gas price (historical and scenarios from now to 2030)

Retail gas and electricity price movements are indirectly related to the price of oil. To illustrate: a
barrel of crude traded on the New York Mercantile Exchange (NYMEX) in 2003 cost $25
(corresponding to the trough in Figure 8 and Figure 9). In late 2007 the price was just under $100.
On July 1 2008, the price was $143.67; however, by August 13, the price was back down to $11317.
These changes illustrate how energy prices fluctuate in the short term, and Appendix II explains
these dynamics in more detail.
                                                                              18
Figure 9: Retail electricity price (historical and scenarios from now to 2030)

The yellow markers in Figure 8 and Figure 9 correspond to the current average gas and electricity
price faced by Londoners. Gas costs on average 12.9% more than it did one year ago, and electricity
costs 12.6% more20. The average London electricity price in 2008 is around 12.5 pence per kWh – up
from about 7.5 pence per kWh in 2003 (the trough in Figure 9). For gas, the price is up from
1.7p/kWh in 2003 to 3.4p/kWh at present. Retail gas and electricity price movements are indirectly
related to the price of oil. To illustrate: a barrel of crude traded on the New York Mercantile
Exchange (NYMEX) in 2003 cost $25 (corresponding to the trough in Figure 8 and Figure 9). In late
2007 the price was just under $100. On July 1 2008, the price was $143.67; however, by August 13,
the price was back down to $113. These changes illustrate how energy prices fluctuate in the short
term, and Appendix II explains these dynamics in more detail.

presents this in terms of actual average annual fuel bills in London for 2007 and 2008. The bills for
2010 and 201619 are estimates based on the medium fuel price scenario for gas and electricity.
                                                                                   20
Table 4: Per unit gas and electricity prices and average annual bills in London

                    Gas [p/kWh]        Gas bill           Elec. [p/kWh]       Elec. bill          Total bill
2007                             3.1              £548                11.1                 £367            £915
2008                             3.4              £619                12.5                 £413           £1,032
2010                             3.7              £671                14.2                 £470           £1,142
2016                             4.1              £739                15.0                 £495           £1,234



Section 2.3.1 presents future estimates of the impact of higher gas and electricity prices on the
incidence of fuel poverty in London, which allow for increases in incomes and improvements in
energy efficiency over time. However, given the short term volatility of energy prices, what might

16
   BERR 2008a and BERR 2008b and ACE
17
   Wikipedia 2008
18
   BERR 2008a and BERR 2008b and ACE
19
   These are the dates by which the Government has a statutory duty to end fuel poverty in vulnerable (2010)
and in all households (2016).
20
   BERR 2008a, for 2007 and 2008 figures. Fuel price scenarios used for 2010 and 2016 figures.

Association for the Conservation of Energy
Fuel Poverty in London


the impact of a sudden and sharp price increase be, without increases in incomes and energy
efficiency improvements? Figure 10 presents an estimate of the relationship between the average
annual energy bill in London and the numbers of households in fuel poverty. The three markers
correspond to the 2008, 2010 and 2016 energy bills as presented in Table 4.
                                                                                21
Figure 10: Estimated relationship between rising energy bills and fuel poverty in London

The important point to note about Figure 10 and the relationship between energy bills and fuel
poverty is that as bills increase, the numbers of additional households falling into fuel poverty does
not increase steadily – rather, it accelerates (which is why the curve in Figure 10 bends upwards).
This is because lower income households generally have lower fuel bills than better off households.
However, the gap in well off and less well off households’ incomes is proportionately larger than the
‘gap’ in fuel bills. In other words, energy bills already constitute a greater share of (not yet fuel poor)
low income households’ expenditure than is the case for higher income households. So any increase
in fuel bills has a disproportionately large effect on a low income household’s budget, as well as the
resultant (accelerating) increase in fuel poverty.




21
  Section 2.3 (next page) presents and explains the different definitions of income used in the estimation of
fuel poverty in London in this report.

Association for the Conservation of Energy
Fuel Poverty in London


2.3 Incidence of fuel poverty
All numbers and percentages in this section refer to the number of households (not people). Three
definitions of income have been used to assess the incidence of fuel poverty22. They are:

        Full income (‘Government’s preferred definition’), meaning disposable income (i.e. after
         tax), but before housing costs;

        Residual income (‘Energy Strategy 2004 definition’), meaning disposable income after
         housing costs;

        Equivalised income, the same as residual income, but adjusting for household size and
         composition (becoming relatively higher for small households, and lower for large
         households).

For a full explanation of the relationship between the income definitions, see Appendix I. For a
separate explanation of the method used to equivalise incomes, see Appendix IV. The first two
definitions have been used throughout the assessment of fuel poverty in London. Under the
equivalised income definition, fuel poverty generally becomes more prevalent in larger households
(i.e. with more people), and less prevalent in smaller households. Section 2.6 looks at the impact of
using the equivalised income definition in more detail.

2.3.1 Current and future incidence of fuel poverty in London
Table 5 provides the headline figures for fuel poverty as of April 2008, comparing London and
England as well as the effects of using the full and residual income in the definition. These figures are
consistent with all subsequent charts and tables.

Table 5: Numbers of households in fuel poverty in London and England (as of April 2008)

The Venn diagram below illustrates the overlap between the number of London households deemed
fuel poor under all three income definitions in 2008. It confirms that if a household is fuel poor on
the full income definition, then it is automatically also fuel poor on the basis of 10% of residual
income, after housing costs have been deducted. However, under the latter definition, a further
442,000 households become newly fuel poor. Equivalising incomes for 2008 adds a further 205,000
fuel poor households, but now excludes 235,000 from fuel poverty.

Appendix I analyses the extent to which each definition of fuel poverty encompasses those
households in London in greatest general poverty and least able to afford their fuel costs.

Figure 11: Venn diagram showing the number (thousands) of fuel poor in London on the three definitions,
2008

Figure 12 shows the proportion of households in fuel poverty in each tenure under each definition in
2008. Under the full income definition, easily the highest incidence of fuel poverty is to be found
amongst owners who own their homes outright. Despite being classed as fuel poor, these owners
often possess large amounts of housing equity – already in 2005, on average, of well over £300,000


22
  A fourth definition of income, not used here, but discussed and considered in the fuel poverty context is
‘basic income’. It is defined as full income excluding housing-related benefits or supplements. Residual income
includes these benefits and supplements but subtracts actual housing costs.

Association for the Conservation of Energy
 Fuel Poverty in London


 with 43% having equities of over half a million pounds. Under the residual and equivalised income
 definitions, the highest rates of fuel poverty shift dramatically away from households owning
 outright to tenants with no equity, renting from private or social landlords (see Appendix I).

Number of households
 in fuel poverty under               318,000                         760,000                       731,000
        each definition
 Figure 12: Percentage of households in fuel poverty by tenure on the three definitions, 2008

 Figure 13 and Figure 14 present the sensitivity analysis – using the four fuel price scenarios in
 section 2.2 – for London’s vulnerable households in fuel poverty in 2010, and all households still in
 fuel poverty in 2016. These are the respective dates by which central government has a statutory
 duty to end fuel poverty.


 Retail gas price [p/kWh] in 2010             3.4              3.2           3.6            3.7              3.9

Retail elec. price [p/kWh] in 2010            12.5            12.7           13.8           14.2             15.2
 Figure 13: Number of London vulnerable households in fuel poverty in 2010


 Retail gas price [p/kWh] in 2016             3.4              3.5           4.0            4.1              5.0

Retail elec. price [p/kWh] in 2016            12.5            13.0           14.5           15.0             17.5
 Figure 14: Number of London households in fuel poverty in 2016

 The fuel price scenarios are inherently uncertain, but what is clear is that significant numbers of
 London households – under both income definitions – are likely to remain in fuel poverty unless
 there is a step change in the level of activity to improve homes and circumstances, and/or fuel prices
 drop significantly in real terms. The modelled improvements in the energy efficiency of the stock are
 the same as those underlying Figure 7 and explained in section 2.1.2.

 2.3.2 Incidence of fuel poverty in 2016 by wall type
 London has the largest share of ‘hard to treat’ dwellings of all English regions in its housing stock.
 ‘Hard to treat’ dwellings have most recently been defined23 as either:

         Dwellings with solid walls
         Dwellings off the gas network
         Dwellings with no loft24
         High-rise flats25




 23
    BRE 2008, p. 3
 24
    Does not include dwellings with separate dwellings above them.
 25
    Includes high-rise flats (defined as having or requiring a lift) with cavity walls, which are deemed hard to
 treat because collective (tenement) agreement and action is required to insulate them.

 Association for the Conservation of Energy
 Fuel Poverty in London




Number of households with wall type           1,336,000               1,752,000               89,000

 Figure 15: Incidence of fuel poverty in London in 2016 (under BAU fuel price scenario) by property wall type

 Dwellings falling into either or both of the first two categories are by far the most common
 nationwide. The majority of London’s ‘hard to treat’ homes are in the solid walls category. When
 placed in the context of London having the highest proportion of hard to treat homes – as well as
 amongst the lowest share of homes off the gas network of any English region26 – the higher
 incidence of fuel poverty in solid wall dwellings is based much more strongly on heat loss than on
 more expensive heating fuels than gas.

 2.3.3 Proportion of households in fuel poverty by English region
 Figure 16: Incidence of fuel poverty by English region and share of income spent on fuel; 2008
 (Government's preferred definition)

 Figure 16 and Figure 16 Figure 17 very clearly illustrate the impact of housing costs on fuel poverty.
 Under the Government’s preferred definition of income (full income), London has the lowest current
 incidence of fuel poverty (Figure 16) amongst English Government Office regions. The incidence of
 fuel poverty increases in all regions using residual income, but London’s is the only ranking which
 changes significantly – from having the lowest level of fuel poverty to being the fifth-highest. This
 reflects London’s disproportionately higher housing costs relative to income. Using residual income,
 the severity of fuel poverty also increases (across all English regions) significantly – as can be seen
 from the ratio of those spending more than 15% of their income on fuel to those spending less than
 15%.

 Figure 17: Incidence of fuel poverty by English region and share of income spent on fuel; 2008 (residual
 income definition)

 As mentioned earlier, applying the equivalised income definition does not make much difference to
 overall levels of fuel poverty compared to the application of residual incomes. Figure 18 shows the
 same ranking of regions as Figure 16, including a similar distribution of the severity of fuel poverty.
 Some regions under the equivalised income definition have a higher incidence of fuel poverty than
 when using unequivalised residual incomes, because these have relatively more large households
 than small households on low incomes. The inverse holds true for regions with a lower incidence of
 fuel poverty than under the residual income definition.

 Figure 18: Incidence of fuel poverty by English region and share of income spent on fuel; 2008 (equivalised
 income definition)




 26
      BRE 2008, p. 9

 Association for the Conservation of Energy
Fuel Poverty in London


2.4 Survey of local authorities

2.4.1 The survey
We aimed to interview a representative from each of the 33 London Boroughs. We completed
telephone interviews with 23 boroughs between 14th April and 2nd May 2008. One of these
subsequently withdrew from the survey as the respondent felt unable to spend the time required to
provide an accurate picture of the borough. We were unable to determine the most appropriate
individual to talk to in two boroughs. One borough provided information in written form too late to
be included in the report. One borough representative who did not have time for an interview
referred us to other information on fuel poverty in the borough but this is not included below as we
are not confident that the information we have is comparable with returns for other authorities. The
remaining eight boroughs either did not respond to repeated attempts to set interview dates.

The 22 boroughs included in the results below are:

       Barnet
       Bromley
       Camden
       Greenwich
       Hackney
       Hammersmith and Fulham
       Haringey
       Harrow
       Havering
       Hillingdon
       Hounslow
       Kingston
       Lambeth
       Lewisham
       Merton
       Newham
       Redbridge
       Southwark
       Tower Hamlets
       Waltham Forest
       Wandsworth
       Westminster

The scripts from each interview were sent to the interviewee for checking and approval. Not all have
returned them (14 of the 22 did, indicating that the interviewee – but not necessarily their council –
approved the contents of the script) and therefore the analysis below is in some cases based on our
understanding from the interview rather than on information verified by the interviewee.

We will not refer to these boroughs individually in the report, as some officers participating in the
telephone interviews requested anonymity.

In addition to interviewing local authority officers we have received information from Eaga on
installation levels in London Boroughs and have interviewed Mark Johnson of Warm Zones.



Association for the Conservation of Energy
Fuel Poverty in London


2.4.2 Current levels of fuel poverty

2.4.2.1 Overall levels
Nine of the 22 boroughs we have spoken to either do not have or are unwilling to provide and
estimate of overall levels of fuel poverty in the borough.

Suggested overall fuel poverty levels, in the 13 boroughs that do have estimates, range from 4% to
78%.

The data sources that boroughs stated they had used to support the estimates are:

        BRE stock modelling27
        The CSE Fuel Poverty Indicator (see section 2.5)
        Local stock condition surveys and housing databases

Confidence in the estimates is mixed. All 13 respondents indicated some degree of confidence in the
data, but two main concerns were expressed:

        Sample size (for example in EHCS) on which numbers were based
        Changes in levels of fuel poverty since the estimates were made28

Four of the 13 boroughs stated that the estimates were based on ‘old’ data, although it is not clear
whether their data were any older than those for other councils.

2.4.2.2 Tenure
Only one borough has information on fuel poverty levels split by tenure, based on data from a local
stock condition survey. A further five boroughs have incomplete information about differences in
fuel poverty between tenures. Seven of the thirteen authorities that had overall data on fuel poverty
did not have any information on how this split between tenures.

A number of boroughs that did not have data on overall fuel poverty levels did have estimates for
one or more tenures. These tended to be informed by local stock condition surveys.

2.4.2.3 Ethnicity
The borough that splits fuel poverty data by tenure also has a split into five ethnic groups. One other
borough has information on levels of unfitness in properties occupied by two particular ethnic
groups and are looking to develop this information further. The remaining eleven have no
information on the split of fuel poverty between different ethnic groups.

2.4.2.4 Vulnerability
Again, only the one borough has information on the split of fuel poverty between vulnerable and
non-vulnerable households. A couple of other boroughs use working estimates based on national
averages or knowledge of general demographics in the borough. One further borough has
information on the number of vulnerable people living in non-decent homes although the reasons


27
   Individual reports for local authorities using data from the English House Condition Survey.
28
   Many of the estimates were based on data from a number of years ago (some estimates were as much as
four or five years old). As fuel prices have risen sharply in the interim (the Fuel Poverty Advisory group report
of March 2008 (FPAG 2008) notes that energy prices are now around 50% higher in real terms than they were
in 2003) the numbers could be a significant underestimate.

Association for the Conservation of Energy
Fuel Poverty in London


for failing the decency standard are not recorded. Nine authorities with information on fuel poverty
do not have information on how this splits between vulnerable and other households.

2.4.3 Accessing national grant programmes

2.4.3.1 Accessing a ‘fair’ share
Nine respondents did not answer this question directly, did not know whether their area accessed a
fair share of national funding or were unwilling to answer the question without a clear definition of
‘fair’.

The thirteen who did express an opinion were split as to whether their residents received their fair
share of funding. Seven respondents felt that residents did not receive a fair share: some considered
this a consequence of a series of inner city issues such as the prevalence of flats, homes with solid
walls and high turnover of residents; others cited issues with the delivery of Warm Front. Four
respondents felt that residents were receiving their fair share of money, usually because the council
participated in a Warm Zone scheme or had its own referral schemes in operation. The remaining
respondents (two) had mixed views, stating that uptake of EEC grants was better than for Warm
Front.

Numbers of homes in receipt of funding
Seven authorities provided no data on numbers of households receiving measures. Seven reported
some overall numbers for both Warm Front and EEC. Seven reported Warm Front data but not EEC,
usually because no data - or only partial information – had been obtained relating to EEC scheme
activity. The remaining one authority reported rough numbers only.

Measures carried out
Eight respondents stated that the majority of measures installed in their area were substantial
heating or insulation measures. Three stated that light bulbs were the main measure provided. Two
authorities did not provide any information on measures carried out, and the remainder (nine)
stated that measures provided included both substantial heating and insulation work and softer
measures like light bulbs.

Data supporting these statements came from a range of sources including from Warm Front and
energy suppliers, and from council HECA reports. Note however that six respondents did not define
the data on which they were basing their answers.

Warm Front data record that, of the 18,638 households in London receiving measures under the
programme in the 12 months between April 2007 and March 2008, 10,940 had a heating or
insulation measure. Note that the data also record that the total number of measures was 30,437,
which included 16,404 light bulbs. Eaga comment that the high number of light bulbs is related to
the high number of properties in London that it is difficult to deliver Warm Front to (i.e. those with
solid walls, flats without loft access and HMOs).

Variations with tenure and ethnicity
Fourteen respondents either did not answer this question or stated that there are no data available
splitting measures installed by tenure or ethnicity. One thought that there may be information
available.


Association for the Conservation of Energy
Fuel Poverty in London


The remaining respondents (seven) held different levels of data on tenure, usually partial
information relating either to one tenure only or to private housing as a whole.

However, some data are available from Warm Zones, covering the boroughs of Brent, Ealing,
Hammersmith and Fulham, Harrow, Hillingdon, Hounslow and Kensington and Chelsea. On average,
85 per cent of households receiving assistance are owner-occupiers, with 14 per cent in the private
rented sector. The data showing how households receiving help break down by ethnicity are
summarised in Figure 19.

Figure 19: Ethnicity of households in receipt of London Warm Zone support [n=1177]

2.4.3.2 Changes in level of activity over the last three years
Seven respondents either did not express an opinion or stated that they did not know whether the
level of activity had changed over the last three years. Six were of the opinion that activity levels had
not changed significantly over the last three years.

The remainder (nine) felt that activity levels had increased over the period. Three reported at least a
doubling between 06/07 and 07/08, due to the introduction of Warm Zones. A further two cited
Warm Zones as the cause of an increase but did not quantify the change.

The remaining four respondents stated that activity had increased somewhat as a result of the
following:

       Council top up funding being available
       Council officer time available for the set up of schemes
       Increased ease of access to EEC funding and more proactivity from energy suppliers
       Greater public awareness of schemes and also rising fuel prices.

Eaga note an increase in activity in London over the last twelve months, based on a developing
relationship with Warm Zones and joint marketing activity. They expect the growth to continue into
the future.

2.4.3.3 Likely changes in activity over the next three years
Only two respondents did not answer this question. All but two of the others believed or hoped that
there would be an increase in activity levels.

A small number of authorities, who are already involved in Warm Zones, were reasonably confident
that significantly higher levels of activity would be maintained. The others were less confident about
the scale or certainty of future increases. Comments made included:

       CERT promotion could help the council to meet its target
       CERT providing measures to anyone over 70 should lead to an increase
       Whether there is an increase will depend on whether solid wall measures are included in
        CERT
       Activity may increase but the proportion of softer measures is likely to increase unless hard
        to treat homes are tackled
       It is likely to increase as we look to do other measures such as installing renewable energy
        solutions
       It remains to be seen how the new performance framework will affect things



Association for the Conservation of Energy
Fuel Poverty in London


       Financial pressures in the council may lead to a decrease in activity – it will be expensive to
        collect data for NI 187
       Levels of activity will have to increase in response to national performance indicators on
        climate change and fuel poverty
       The London ESTAC provides an opportunity
       Disappearance of the locally-based EEAC may have a negative impact as there will be less
        local promotion
       Cost is a strong driver and people will also start to respond more to environmental drivers.

2.4.4 Local authority activities
Nine of the authorities we spoke to will essentially be continuing current activities over the next few
years. A number are beginning to take a more strategic view than previously including:

       Including fuel poverty in new sustainability or climate change strategies (three authorities)
       Improving targeting (four authorities)
       Including a fuel poverty target in the LAA (three authorities)
       Moving to an area-based approach (two authorities)
       Setting up a division specifically to tackle fuel poverty (one authority)

One authority specifically mentioned a focus on hard to treat homes and one noted that, although
the focus of energy activity would be moving towards tackling climate change, there would still be
work done on reducing fuel poverty.

2.4.4.1 Impacts on uptake of national programmes
Fourteen authorities felt that their future plans would lead to an increase in uptake of national
programmes (although some were more confident of this than others). Six respondents either did
not answer this question or stated that they were not sure what the impact would be. Two stated
that they thought there would be no impact.

2.4.4.2 Impacts on council activity
Fifteen respondents felt that their plans would have no impact on council activity beyond
maintaining current levels of intervention. Three felt that there may be an increase in funding
allocated to the area whilst one was concerned that funding might be cut. One stated that the
inclusion of the fuel poverty indicator in the LAA should have a big impact. Two did not know what
the impact on council activity would be.

2.4.4.3 Impacts on other social landlords
Eleven respondents either did not answer this question or stated that they felt there would be little
or no impact beyond that created by current activities. Two were not sure what the impact would
be. The remaining respondents offered a number of different new initiatives in this sector, which
were largely aimed at increasing awareness of the issue or improving the quality (and quantity) of
relevant data collected and shared with the council.

2.4.4.4 Impacts on private landlords
Eight respondents felt that there would be no further impact in this sector beyond what was being
achieved already. Six respondents were unsure of the impact that their plans might have. Five are
aiming to increase awareness in the sector. Two mentioned HHSRS and/or enforcement activity as a
tool that may be increasingly used in the future.



Association for the Conservation of Energy
Fuel Poverty in London


2.4.4.5 Impacts on home owners
Five respondents felt that future activities would continue to engage with home owners as existing
activity has. Three were unsure of the potential impact of their plans. The remaining 14 respondents
felt that future plans would increase awareness and some linked this to a potential increase in action
by homeowners. Two mentioned targeting: in deprived wards and with minority groups. One was
concerned that there would be less action by homeowners in the future because of the slowdown in
the housing market.

2.4.4.6 Overall impact
Thirteen respondents expected to see an overall increase in the rate of energy efficiency
improvement29 although some were more confident in this than others. A number were unsure of
the overall likely impact. One mentioned that a lot of activity in the future will be based around CHP
and district heating and therefore it will be some time before the impact is seen. One other declined
to comment on the likely impact because they felt it was impossible to estimate with confounding
factors such as increasing fuel prices involved.

2.4.5 Future cooling requirements
It is clear from the answers to this question that in general local authority fuel poverty officers have
not yet considered this issue. Few were willing to state an opinion on this and those who did were
more likely to focus on fuel bills than on thermal comfort (e.g. assuming that this will not be a
problem because households in fuel poverty will not be able to afford to purchase air conditioning).
However, a minority did see that this could potentially be a problem, although they did feel that they
did not have the necessary information on future temperatures and on buildings’ thermal
performance in this respect to make an informed statement.

2.4.6 Government policy

2.4.6.1 CERT and Warm Front
A small minority of respondents were not able to answer this question as they were unaware of the
changes from EEC to CERT. The majority felt that the changes were positive and were optimistic
about future activity levels. Note however, that two respondents noted that, even with the
improvements, CERT was unlikely to offset the impact of rising fuel prices. Two respondents raised
the issue of hard to treat homes, with one hoping that increased CERT funding may mean that these
were addressed and the other linking the potential effectiveness of the scheme with whether or not
measures for these homes were included.

One respondent noted that any further cuts in the Warm Front budget would be detrimental. One
also commented that the impact of CERT would be particularly positive when combined with Warm
Zones activity.

2.4.6.2 Suggestions for other policy changes
A number of suggestions were made for other policy changes that would help to tackle fuel poverty
in London boroughs, including:




29
  Note that this is an interpretation of their comments – it is difficult to assess whether they actually meant an
increase in the rate or simply a continued improvement in energy efficiency.

Association for the Conservation of Energy
Fuel Poverty in London


       Action on fuel prices, including removing differentials associated with pre-payment meters
        (five respondents)
       Extending Warm Front eligibility criteria and/or reducing CERT full funding age limit to 60
        (four respondents)
       Removing or increasing Warm Front grant maxima (three respondents)
       More funding and/or increasing the Warm Front budget (three respondents)
       Financial and other support to tackle hard to treat homes (two respondents)
       A number of options suggested by individual respondents: reallocation of Warm Front
        funding to local authority home improvement agencies, action on incomes, nationalising the
        utility companies, giving councils a resourced target to meet, changing to a tax system based
        on carbon emissions and, in the long term, making insulation mandatory.

2.4.7 Implications of the survey findings
The results of the survey suggest a number of implications for the use of the modelling in this report
and the development of GLA policy and support:

       There are a significant number of respondents (40%) who either have no estimate of the
        level of fuel poverty in their borough, or have so little confidence in the estimates they do
        have that they are unwilling to share them. Therefore the results of this work could be very
        useful to them, if they have confidence in the output.
       The data sources used by many of the authorities who are willing to estimate levels of fuel
        poverty are consistent with the ones used in this modelling. Therefore there is a good
        chance that the results of the modelling will be recognised as offering ‘best available’
        estimates.
       Modelled estimates for levels of fuel poverty in boroughs that are active participants in
        Warm Zones may be too high, as this activity seems to be generating a significant increase in
        the level of investment in energy efficiency in the boroughs – an increase that will not yet be
        reflected in official statistics.
       Hard to treat homes remain a key issue; one which requires national and regional policy
        focus.
       Many respondents to the survey were not fully aware of national policy developments:
        there is a need for increased dialogue with local authority officers on this, as opportunities
        to capitalise on changes may be missed otherwise. Warm Zones seem to be providing a
        useful intermediary in this respect in the boroughs where they are active.




Association for the Conservation of Energy
Fuel Poverty in London



2.5 Mapping the incidence of fuel poverty in London
The mapping of fuel poverty using the Centre for Sustainable Energy’s Fuel Poverty indicator (FPi),
provides a very powerful illustration of the spatial distribution of fuel poverty under the full income
definition. The full set of local authority-level maps have been provided separately, including the
associated data tables.
                                                         30
Figure 20: Incidence of fuel poverty in Greater London

The maps are based on the full income definition of fuel poverty and have a resolution at the output
area (i.e. sub-ward) level. ‘Quintiles’ in this context mean that all output areas have been banded
into fuel poverty incidence quintiles – i.e. the 20% of output areas with the lowest levels of fuel
poverty, the 20% with the next highest and so on. In Figure 20, the 20% of output areas with the
highest levels of fuel poverty (the darkest shade of red) range in incidence from 6.1 to 40.9%. Whilst
this is a wide range, the quintiles approach is necessary for mapping purposes whilst the
accompanying tables provide the exact level of fuel poverty incidence in each output area.

2.6 Demographics

2.6.1 Fuel poverty in vulnerable households
As of April 2008, we estimate there to be 2,083,000 vulnerable households31 in London; the number
and proportion of fuel poor amongst this group, according to each of the three income definitions
(defined in section 2.3), is shown in Table 6.

Table 6: Number and proportion of vulnerable households in fuel poverty in 2008 (all income definitions)

                            Full income                       Residual income           Equivalised income
Number (x1000)                                   254                              572                     571
Proportion                                     12.2%                            27.5%                   27.4%


As can be expected, the overall difference in the number of fuel poor households under the residual
and equivalised income definitions of fuel poverty is negligible. The difference emerges when
examining the distribution of fuel poverty within the vulnerable household group32.

     Number of households in fuel
                                            318,000                    760,000                731,000
     poverty under each definition
Figure 21: Percentage of households in fuel poverty amongst different vulnerable groups, 2008 (all income
definitions)

In Figure 21, under the full income definition, 16% of households with one or more occupants over
60 are fuel poor. Furthermore, six percent of households with an under-16 year old and 21% of
households with a long-term sick or disabled person are in fuel poverty.



30
   CSE Fuel Poverty indicator
31
   Defined as having at least one household member being over 60, under 16 or long-term sick or disabled.
32
   Households only classed as ‘Under 16 years old’ if no member also 60 years old or more and ‘Long term sick
or disabled’ if no member also 60 years old or more or under 16 years.

Association for the Conservation of Energy
Fuel Poverty in London


Using the residual income definition primarily increases the incidence, and to some degree, the
distribution of fuel poverty amongst the three vulnerable groups. Households with members under
16 years old or the long-term sick or disabled are proportionately more fuel poor than over-60s
households, due to the greater housing costs they face, reducing their available income. When
household size and composition is accounted for (using equivalised income), the proportionate
increase in the incidence of fuel poverty is greatest for households with under-16s – those
households which are the largest of the three groups. For the over-60s households, fuel poverty
incidence is actually lowest using equivalised incomes – reduced disposable income due to housing
costs having been cancelled out by equivalisation.

2.6.2 Black, Asian and Minority Ethnic households in fuel poverty
There are similar dynamics affecting the incidence of fuel poverty in Black, Asian and Minority Ethnic
(BAME) households compared with vulnerable households. The overall level of fuel poverty is again
similar when the residual and equivalised income definitions are compared. Once more, the
distribution is different.

Figure 22: Percentage of households in fuel poverty amongst different ethnic groups, 2008 (all income
definitions)

Under the full income definition, the differences between the ethnic groups are not particularly
significant. However, excluding housing costs in the definition makes fuel poverty among other
ethnic minorities significantly worse than in other groups. Equivalising incomes slightly decreases the
problem in this group, but increases fuel poverty amongst Black and Asian households to make the
incidence in all three minority groups substantially worse than amongst the majority of ethnically
White households.

2.6.3 Eligibility for Warm Front
The figures in this section are all limited to vulnerable households. In Figure 23, under the full
income definition, the greatest numbers of fuel poor are vulnerable households eligible for Warm
Front grants33, and clearly the lowest number are public housing tenants (separated out because
they not eligible for Warm Front under any circumstances). The main effect of excluding housing
costs and equivalising incomes in the definition is to increase fuel poverty amongst these tenants
such that they now have the highest number. Under the residual income definition, there are more
eligible vulnerable households that are fuel poor than non-eligible (owner-occupier or private-
rented) households, while the reverse is the case for the equivalised income definition, but the
differences are not really statistically significant.

Figure 23: Number of vulnerable fuel poor households according to Warm Front eligibility (2008)




33
   Warm Front is a government-funded subsidy scheme installing applicable energy efficiency measures in low-
income households to alleviate fuel poverty. Private sector (i.e. owner-occupying or private-renting)
households on certain income-related benefits are eligible for support under the scheme. See Appendix VI for
the eligibility criteria. In social housing (i.e. rented from local authorities (LAs) or registered social landlords
(RSLs)), the Decent Homes programme has been the main driver for investment in LA stock, as the range of
ways that LAs have chosen to meet the Decent Homes standard has in some cases included the use of private
finance initiatives and stock transfer to RSLs. The latter are expected to meet the costs of making their housing
stock (and transferred stock) Decent using their own funds.

Association for the Conservation of Energy
Fuel Poverty in London


Figure 24 shows the proportion of vulnerable households not eligible for Warm Front that are fuel
poor under the three income definitions in each of the English regions. Under the full income
definition, London has the second lowest percentage of such households. Excluding housing costs
and then equivalising incomes progressively increases this proportion, more than in other regions.
As a consequence, under the equivalised income definition, London has the third highest proportion
of vulnerable fuel poor households not eligible for grant of any region.
                                                                                     34
Figure 24: Proportion of vulnerable fuel poor households not eligible for Warm Front (2008)

Figure 25 illustrates the proportion of vulnerable households – living in homes that pass the decent
homes standard (DHS); fail the standard on repair, fitness or modernisation; or fail on the thermal
comfort criteria alone – that are fuel poor under each of the definitions. The old standard is used in
this figure, as the EHCS did not collect comprehensive data on the HHSRS35 and thus the current DHS
until the 2006 Survey (the dataset for which has not yet been released).

Under the full and residual income definitions, vulnerable households living in homes that fail the
DHS are more likely to be in fuel poverty than those living in Decent Homes. However, after
equivalising incomes in the definition, the differences are not statistically significant.

Figure 25: Proportion of vulnerable households (all tenures) living in (non-)Decent homes (2008), that are
fuel poor

Finally, Figure 26 combines vulnerable households’ eligibility for Warm Front with living in decent
and non-Decent homes and plots the incidence of fuel poverty in each category. Under all three
definitions, vulnerable households that are eligible for grant show the highest incidence of fuel
poverty. This is irrespective of the DHS rating, although under the equivalised definition, fuel poverty
is higher in ‘Decent’ homes than non-Decent ones. Excluding housing costs in both the residual and
equivalised income definitions substantially increases the proportion of public sector tenants in fuel
poverty, relative to all other groups.

Figure 26: Proportion of vulnerable households, by Warm Front eligibility status and Decent home (2008),
that are fuel poor

2.7 Synthesis
Figure 27 was developed by dividing the London EHCS 2005 household sample up – as extrapolated
to 2008 using the Fuel Prices Model – according to the percentage of their (full) income they paid on
fuel. For each of these groups – i.e. those paying more than 20%, 15-20%, 10-15% and so on – the
corresponding average pence per kWh of energy and average dwelling SAP rating they faced were
both plotted against the corresponding average household income. What Figure 27 highlights is that
on average, households spending proportionately more of their income on fuel face higher unit
energy costs, have lower incomes and live in less energy efficient dwellings than households who
spend a lower proportion of their income on fuel.

Figure 27: Household mean income, unit energy cost, and SAP rating, by fuel poverty group (2008)


34
  Proportion excludes vulnerable fuel poor living in social housing.
35
  The need for a Decent Home to be fit for human habitation, was replaced in 2006 by the need for it to be
free of Category I hazards under the new Housing Health and Safety Rating System (HHSRS). However, local
authorities are currently monitoring both and are likely to do so for the foreseeable future.

Association for the Conservation of Energy
Fuel Poverty in London


Compared to the similar figures based on the 1996 EHCS, Figure 27 is likely to under-estimate the
differences in fuel prices (p/kWh) between the fuel poverty groups. In 1996, the fuel prices used in
calculating fuel poverty were those specific to each household, as collected from the relevant
suppliers in the EHCS fuel survey. Since 1996, BERR’s Quarterly Fuel Prices have been used, and are
only the average prices for all households, depending on the region and method of payment.
However, as indicated in Table 8 below, there is considerable variation in fuel prices even within
each region and payment method. With lower income groups tending to have poorer tariff
arrangements, this change in the government’s methodology is likely to have resulted in the under-
estimation of fuel poverty in official statistics since 1996.

2.8 Pre-payment meters
In Table 7, there are clear discrepancies between the EHCS 2005 findings for pre-payment meters in
London and the figures from the ‘Energy Metering in London’ study, commissioned by the GLA and
carried out by AEA Technology.




Table 7: Pre-payment meters in London (thousands)

                           EHCS 2005                AEA study36
Gas meters                       2,849                              2,630
of which pre-payment               401    (14%)                       307   (12%)
Electricity meters               3,085                              3,267
of which pre-payment               509    (16%)                       462   (14%)


First, AEA’s figures for meters include those in unoccupied dwellings37. As a result, the numbers can
be expected to be higher – though this is not the case for gas meters. One possible explanation for
this is that gas is not metered as consistently separately (i.e. on a per dwelling basis) as electricity.

Figure 28 shows the growth in the numbers of gas and electricity pre-payment meters in London,
based on EHCS data between 2001 and 200538.
                                                            39
Figure 28: Number of households with pre-payment meters

Pre-payment meters in occupied homes have stayed fairly consistent in percentage terms over this
time period. From ten per cent to 13% for gas, and from 15% to 16% for electricity. Since then the
numbers (and percentage) appear to have increased further. According to BERR’s latest quarterly
fuel price statistics40, as of September 2007, 20% of households in London pre-paid for their
standard electricity tariff. Seventeen per cent of customers on Economy 7 tariffs pre-paid as well. In


36
   The figures in AEA’s report are not based on the number of occupied homes (as is the case with the EHCS),
but the total number of meters.
37
   There were 87,218 empty homes in London in April 2006.
38
   EHCS 1996 data is not comparable due to changes in the survey design. Projections for 2008 are not included
because the Fuel Prices Model does not model changes in the method of fuel payment.
39
   EHCS 2001, 2003, 2004 and 2005
40
   BERR 2008a

Association for the Conservation of Energy
Fuel Poverty in London


this data set, information on pre-payment gas meters is less directly comparable because the regions
are divided up differently.

Using the BERR data for London, Table 8 shows the average unit prices for gas and electricity and
standardised annual bills (based on consumptions of 18,000 kWh for gas and 3,300 kWh for
electricity) for the period Q4 2006 to Q3 2007. The average is the average for all suppliers while the
largest and smallest are the averages for the company giving the highest and lowest bills in
London41. Not only are the pre-payment prices consistently higher than for credit or direct debit but,
in the case of electricity, the price range is also the widest, the largest pre-payment average being
62% higher than the smallest pre-payment.
                                                                             42
Table 8: Average London fuel prices and bills in 2007 by payment method

Payment type                           Credit                   Direct debit                Pre-payment
London        Bill range     Unit cost      Bill           Unit cost        Bill     Unit cost      Bill
              Largest               3.18            572              2.92      525             3.35           603
Gas           Average*              3.09            556              2.77     499              3.28           590
              Smallest              2.72            490              2.56      460             2.97           534
              Largest              13.58            448            13.58       448            17.18           567
Electricity Average*               11.24            371            10.55      348             11.55           381
              Smallest             10.58            349              9.88      326            10.58           349
*Average series of fuel prices currently used in the calculation of fuel poverty

In light of the fact that pre-payment customers pay on average more than credit or direct debit
customers do, the growth in the numbers of pre-payment meters poses strong challenges to tackling
fuel poverty. At the very least, it is important to ensure that fuel poor households can gain access to
the best available tariff available on their payment method.

2.9 Assessing relative importance of contributory factors
Unsurprisingly, as shown in Figure 29, a disproportionately large share of fuel poor households in
London is under-occupying43. However, this share falls to below the London-wide (all households)
average under the equivalised income definition of fuel poverty – due to it adjusting income for
household size and composition.


Number            122,000                   210,000                    111,000                661,000

Figure 29: Percentage of fuel poor in London who are under-occupying (2008)

Figure 30 illustrates the pattern of under-occupancy amongst fuel poor households by tenure. In
homes owned outright, under-occupancy is a more significant factor, as could be expected. Even
after adjusting income for household size and composition, the share of fuel poor under-occupying is
still the highest in this tenure.

41
   The bills are normalised for average annual gas and electricity consumption. Depending on the energy
efficiency of the home, occupancy and (adequacy of) heating patterns, actual bills vary enormously.
42
   BERR 2008a
43
   In Figure 29 and Figure 30, the definition of under-occupancy is dependent on both the floor area of the
dwelling and number of bedrooms relative to the household size and composition, being the same as that
used for determining appropriate heating regimes in the government’s calculation of fuel poverty. See
Appendix VI.

Association for the Conservation of Energy
Fuel Poverty in London



Number of households in
                                717,000         531,000         1,155,000          486,000          289,000
           each tenure

Figure 30: Proportion of fuel poor under-occupying, by tenure (2008)

In Table 9, under-occupancy is placed into context as a causal factor of fuel poverty. It provides a
series of cross-tabulations of fuel poverty (based on residual income) definition against residual
incomes, SAP ratings, fuel prices (p/kWh) and under-occupation, here simply measured as m2 per
adult (i.e. m2 per potential income). It shows that by far the strongest correlation is with income,
but that under-occupation is also fairly strongly correlated with fuel poverty. The least correlation is
with SAP ratings. Fuel prices are not as strongly correlated as they should be because of the EHCS
methodology of using average rather than actual fuel prices.

Table 9: Fuel poverty (Energy Strategy definition) by residual income, SAP rating, unit fuel price and space
quintiles (2008)*

* numbers in bold; percentages in italics; CI stands for confidence interval

Table 10 gives the standardised coefficients (indicating the importance of each factor) when all the
confounding factors have been accounted for by using linear regression. This table gives a
breakdown for Inner and Outer London44 and also the all England results. It again confirms that
income is the most significant causal factor, but relatively more so in Outer London than Inner
London. In Inner London, under-occupation and fuel prices appear of almost equal importance (but
the sample here is quite small for regression). The importance of fuel prices is again probably under-
estimated in this table, for the above reason.

Table 10: Standardised coefficients for main causal factors of fuel poverty (2008, Energy Strategy definition)

The final table uses logistic regression to determine the probability of being in fuel poverty under the
Energy Strategy definition if a household is in the lowest quintile of incomes or SAP ratings or has
the highest quintile of fuel costs or floor space per adult. Due to the aforementioned issue of
average fuel prices, total actual fuel costs have been used in this regression. In London as a whole, a
household is over 117 times as likely to be in fuel poverty if it falls into the lowest quintile of
income45 than if it does not. However, a household is under three times as likely to be in fuel poverty
if its home lies in the lowest quintile of SAP ratings46, than if it has a higher SAP. It is some 2.7 times
(over three times in Outer London) as likely to be in fuel poverty if it is one of the worst 20% of
under-occupiers in London. However, being in the highest quintile for total fuel costs makes it only
around twice as likely to be in fuel poverty.

Table 11: Odds ratios of being in fuel poverty if in worst quintile of incomes, fuel costs, under-occupation
and SAP ratings (2008)




44
   Sample sizes are too small to draw meaningful conclusions from a higher geographical resolution.
45
   The average residual income in the lowest quintile is £4,383; in the highest quintile it is £63,886.
46
   The average SAP rating in the lowest SAP quintile is 34.6; in the highest quintile it is 78.3.

Association for the Conservation of Energy
Fuel Poverty in London



Appendix I – Definitions of fuel poverty

Introduction
This Appendix compares the number and distribution of households in fuel poverty in London on
three different definitions. Each definition accepts the Government’s view that a household is in fuel
poverty if their total fuel costs for satisfactory heating and other normal energy use exceeds 10% of
their net income, but defines household income in three different ways, as follows:

        Full income before housing costs (BHC) definition - uses full net income, before housing
         costs.

        Residual income after housing costs (AHC) definition - uses full net income, after housing
         costs.

        Equivalised income AHC definition - uses equivalised full income, after housing costs.

The full income BHC definition is the Government’s preferred definition. However, the residual
income AHC definition is more meaningful for, in addition to national and local taxes, this also
excludes main housing costs (rent and mortgage payments)47 that are equally unavailable to be
spent on fuel. This is the definition preferred in the 2004 Energy Strategy. So-called basic income, a
definition not used in this report, is similar to residual income AHC. It deducts housing benefits from
disposable income as a proxy for deducting housing costs, and is thus intrinsically less accurate in
estimating disposable income than residual income AHC.

Arguably, an even more meaningful definition is the equivalised income AHC definition, as this also
allows for the fact that larger households require a larger income than smaller ones (primarily
because the ratio of earning to non-earning members of the household falls) to achieve the same
standard of living. Equivalised income is an internationally accepted index of financial poverty and is
used in the Department of Work and Pension’s (DWP) definitive Households Below Average Income
(HBAI) series. (Appendix IV details the methodology used for the equivalisation of EHCS incomes).

In this section, the official 2005 EHCS dataset is used, without further modelling, as this provides the
most accurate comparison between the three definitions. In this respect, the main purpose of this
particular analysis is to show the comparative extent and different distributions of fuel poverty
produced by the three definitions, rather than determine the absolute number of fuel poor at the
current time.




47
  In the EHCS 2005 local tax includes actual council tax paid. For the 2008 projections, council tax paid is
updated using the London-wide average council tax increase since 2005. Housing costs have been treated in
the same way.

Association for the Conservation of Energy
Fuel Poverty in London


Overall frequency of fuel poverty
Appendix Table 1 compares the total number and percentage of households classified as fuel poor
under each definition in London and in all other regions combined. Excluding housing costs in the
definition increases the number of fuel poor households in London almost fourfold, but by less than
double elsewhere in England. This is a direct result of the capital’s higher housing costs48, for
example, in 2005 a gross average of £5,574 per annum compared to £2,985 elsewhere for
households on low income (defined as less than 60% of the national median).

Equivalising residual income has far less impact on the overall number compared to moving from the
full to the residual income definition. In 2005, it further increases fuel poverty in London by just over
6% (from 464,000 to 493,000 households), but reduces the total by over 8% (from 2,688,000 to
2,464,000 households) elsewhere. This was due to the fact that London then had a higher proportion
of larger households at risk of fuel poverty than most other regions, with, for example, 16% of
households on low residual incomes comprising three or more persons, compared to only 10%
outside London. (Equivalisation lowers the incomes of larger households and thus tends to increase
fuel poverty in this group.) However, increased fuel prices after 2005 have changed the distribution
of London households most at risk, resulting in a slight fall in numbers after equivalisation in 2008.

Appendix Table 1: Frequency of fuel poverty (households x1000) in London and elsewhere by definition,
     49
2005

Fuel         Full income BHC             Residual income AHC        Equivalised income          Total
poverty      definition                  definition                 AHC definition              households
             Not FP      In FP           Not FP      In FP          Not FP      In FP

London
                   2,965          120         2,621           464         2,592          493           3,085
Region
                    96.1           3.9          84.9         15.1          84.0          16.0          100.0
All other
                 16,640         1,410        15,361         2,688       15,585         2,464         18,049
regions
                    92.2           7.8          85.1         14.9          86.3          13.7          100.0

England
                 19,605         1,529       17,982         3,152        18,177         2,957         21,134
Total
                    92.8           7.2          85.1         14.9          86.0          14.0          100.0




48
   Calculated based on actual housing costs data collected from households in the EHCS. Gross rental and
mortgage payments have been subtracted from the full income of each household (which includes housing
benefit and income for support for mortgage interest etc). For 2008, housing costs were updated by applying
the average regional increase in rents (in each tenure) and mortgages.
49
   EHCS 2005

Association for the Conservation of Energy
Fuel Poverty in London


Incomes and Fuel Costs
The next two tables indicate the extent to which the three definitions of fuel poverty cover those
households most in need. Appendix Table 2 shows that despite the much larger number of
households involved, those defined as fuel poor under the residual and equivalised income AHC
definitions are in significantly greater financial poverty generally than those classed as fuel poor
under the Government’s full income definition. The average equivalised income, AHC, of those
deemed to be in fuel poverty drops from some £7,530 to £5,600 after excluding housing costs, and
falls further to some £5,360 after using equivalised incomes in the definition. The proportion of
households in fuel poverty in the most severe category of general poverty (having incomes of under
half the national median) increases from some 51% to 75% and 80% as the definition changes.
Conversely, the percentage of households with incomes of 70% or more of the median, decreases
from 20% to 6%.

Appendix Table 2: Equivalised incomes by fuel poverty in London by definition, 2005 [average income £ in
                                              50
first row only/thousand households/column %]

Equivalised     Full income BHC              Residual income AHC          Equivalised income         Total
incomes         definition                   definition                   AHC definition             households
AHC

                Not FP        In FP          Not FP       In FP           Not FP      In FP

Average
                   21,366          7,531       23,530         5,597         23,772          5,361        20,830
income £

< 50% of               555             61         268              349         221            395           616
median                 18.7           51.4        10.2             75.1         8.5           80.2          20.0
50 - 60% of            246             27         216               56         223             49           272
median                  8.3           22.2         8.2             12.1         8.6            9.9           8.8
60 - 70% of            180               8        166               21         168             20           187
median                  6.1            6.4         6.3              4.5         6.5            4.0           6.1
70% + of             1,985             24       1,971               38       1,980             29         2,009
median                 66.9           20.0        75.2              8.2        76.4            5.9          65.1

London
                     2,965            120       2,621              464       2,592            493         3,085
Totals
                     100.0         100.0         100.0         100.0          100.0         100.0         100.0


Appendix Table 3 shows that on average, households classified as fuel poor under the residual
income definition of fuel poverty have smaller total required fuel costs51 than those fuel poor on the
Government’s definition (£751 compared to £877). However, after equivalisation, the fuel costs for
the AHC definition (at £870) is similar to that for full incomes, before housing costs.

Appendix Table 3: Fuel costs and severity of fuel poverty in London by definition, 2005 [average fuel cost in
                                                  52
first row only £/thousand households/column %]

Fuel costs                     1 full income          2 residual           3 equivalised                  Total
                                                      income               income


50
   EHCS 2005
51
   I.e. required to achieve satisfactory heating and cover other standardised energy use.
52
   EHCS 2005

Association for the Conservation of Energy
Fuel Poverty in London


                            in FP     in FP     in FP on   in FP   in FP on    in FP
                            on        on        defn 2     on      defn 2      on
                            defn 1    defn 3               defn                defn
                                                           3                   3
Average fuel cost £            877                   751                         870              732

Not in fuel poverty               0       52           0    148         177        0            2,592
(<= 10% of income)              0.0      43.9        0.0    31.9        35.8     0.0              84.0
Moderate fuel poverty          102        27        223     122         100     266               266
(10% to 15% income)            85.6      22.6       48.0    26.4        20.3    53.9               8.6
Serious fuel poverty              9         6        84      46          59      73                73
(15% to 20% income)             7.7       5.3       18.2     9.9        12.0    14.9               2.4
Severe fuel poverty               8       34        157     148         157     154               154
(over 20% of income)            6.7      28.1       33.8    31.9        31.9    31.2               5.0

London Totals                  120       120        464     464        493      493             3,085
                              100.0     100.0      100.0   100.0      100.0    100.0            100.0


The lower part of Appendix Table 3 shows that both excluding housing costs from income and
equivalising incomes has a significant impact on the severity of fuel poverty. On the full income BHC
definition, the vast majority (86%) of the 120,000 fuel poor households are in moderate fuel poverty.
Under the equivalised income AHC definition, 44% of these 120,000 households are no longer
classed as fuel poor, but conversely 28% are now in severe fuel poverty. On the Energy Strategy
residual income definition, 464,000 households are fuel poor, of which 34% are in severe fuel
poverty. When AHC incomes are equivalised, 32% of these 464,000 households fall out of fuel
poverty but the number in severe fuel poverty drops only slightly (to 32%). As we have seen,
equivalisation increases the total number of households in fuel poverty in London to 493,000 and of
these 54% are in moderate fuel poverty and 31% are severely fuel poor.

The three Venn diagrams below illustrate how the number of London households deemed fuel poor
under each definition overlap. Appendix Figure 1 confirms that if a household is fuel poor on the
basis of full income, then it is automatically also fuel poor on the residual income definition, when
housing costs have been excluded from income. However, under the latter definition, a further
345,000 households become newly fuel poor. Equivalising incomes adds a further 177,000 fuel poor
households, but now excludes 148,000 from fuel poverty.




Association for the Conservation of Energy
Fuel Poverty in London




                                         2,443

          96
                                                        Full income 120 k

        52       67      249       177                  Residual income 464 k

                                                        Equivalised income 493 k




                                                                                                         53
Appendix Figure 1: Venn diagram showing the number (thousands) of fuel poor in London on 3 definitions

Appendix Figure 2 shows the average equivalised income in each overlapping sector. The households
excluded from full poverty by the equivalisation, have the highest average incomes, those previously
fuel poor under the Government’s definition averaging £11, 428. The new fuel poor added by
excluding housing costs and retained after equivalisation have the lowest incomes at £3,640.



                                         £24,647

         £8273
                                                        Full income £7,531

      £11288 £4,594   £3,640      £8,079                Residual income £5,597

                                                        Equivalised income £5,361




                                                                                               54
Appendix Figure 2: Venn diagram showing the average equivalised income for the 3 definitions

The final Venn diagram illustrates the average total fuel costs in each sector. The fuel poor added
under the equivalised income definition have the highest required fuel costs at £1,032, and those
excluded by this definition, but not fuel poor under the full income definition, have the lowest
average costs, £603.




53
     EHCS 2005
54
     EHCS 2005

Association for the Conservation of Energy
Fuel Poverty in London




                                        £707

         £603
                                                         Full income £877

        £845 £902       £747       £1,032                Residual income £751

                                                         Equivalised income £870




                                                                                       55
Appendix Figure 3: Venn diagram showing the average fuel costs for the 3 definitions

The final Table in this Appendix compares the average housing equity in 2005 of owner occupiers
who are not fuel poor with those classed as fuel poor under each definition. For owners with a
mortgage, those in fuel poverty have slightly higher equities than those not classed as fuel poor,
under all three definitions. The highest equity, over £212,300 is for those fuel poor under the full
income definition, although numbers here are small. As expected, equities are significantly higher
for households who own their homes outright, an average of £334,600 for all households. However,
there is again very little difference in average equity, between those classed as fuel poor and those
who are not, under any of the definitions.

The main differences in the definitions lie in the number of owner occupiers who are fuel poor.
When you look at income after housing costs, households with mortgages are more likely to be in
fuel poverty. This increases further when incomes are equivalised. Excluding mortgage payments
obviously has no affect on the number of outright owners in London who are fuel poor (61,000), but
for 2005, equivalising incomes more than halves this number.




                                                                                                            56
Appendix Table 4: Average housing equity of owner-occupiers in fuel poverty in London by definition, 2005




55
     EHCS 2005
56
     EHCS 2005

Association for the Conservation of Energy
Fuel Poverty in London


Tenure           Full income defn.      Residual income          Equivalised            Household    Sample
                                                                   income                   totals   number

                   Not in      In FP     Not in      In FP      Not in          In FP
                      FP                    FP                     FP

Owned
                 £173,577   £212,342   £173,245   £183,078   £172,433       £184,697      £174,265
mortgage

Number k           1,113         19      1,004        128         957            175         1,132      535

Owned
                 £334,911   £331,531   £334,911   £331,531   £320,731       £354,304      £334,604
outright

Number k             612         61        612         61         645             28          673       311



All owner        £237,730   £305,889   £241,107   £240,139   £238,505       £262,490      £241,012

occupiers          1,725         80      1,616        189       1,602            203         1,805      846




The final Figure shows the distribution of all fuel poor households in 2005 by tenure, under each of
the definitions. Under the government’s definition over half (51%) of all fuel poor households in
London own their home outright, the least number occurring in the privately rented sector. By
excluding housing costs, outright owners are given the smallest share, while those renting social
housing gain the largest share. Under the equivalised income definition, the proportion of all fuel
poor owning outright is reduced further (to under 6%). Outright owners falling out of fuel poverty
are easily replaced by an increase in fuel poverty amongst mortgagees. But under both the residual
and equivalised income definitions, the remaining majority of households in fuel poverty (59%) are
almost equally likely to be renting from a private landlord as living in social housing.
                                                                           57
Appendix Figure 4: Distribution of fuel poor households by tenure (2005)

In conclusion, it is clear that the Energy Strategy residual income definition and, to an even greater
extent, the equivalised income (after housing costs) definition encompasses a larger number and
proportion of households in London in the greatest general poverty, with no housing equity and
least able to afford their fuel costs than the Government’s full income (before housing costs)
definition of fuel poverty.




57
     EHCS 2005

Association for the Conservation of Energy
Fuel Poverty in London



Appendix II – Fuel price scenario development
Factors affecting domestic electricity and gas prices in the UK are numerous, complex, and often
rather oblique. Whereas most price movements over the previous two decades can in large part be
explained by the impact of market-oriented reforms, these upheavals have largely settled, and new
drivers are at work. Today, the origins of pricing pressures are primarily found in two areas: 1)
Climate change, mitigation policies, and the impact of climatic events on energy markets: 2) Energy
security; the forces of supply and demand in a global, relatively open market arena vulnerable to
geo-political forces. These two factors will have the most marked effect on fuel prices in the medium
and long term. Whilst a full explanation of these forces is outside the scope of this project, this
Appendix provides an overview of recent price changes and future factors considered in developing
the scenarios used.

Historical fuel prices and fuel price scenarios
Prices for electricity, gas, heating oil, liquefied petroleum gas, coal, and petrol and oil were analysed
over the period from 1970 to the first quarter of 2008. These were used to elucidate broad fuel price
trends, pricing relationships between fuels and the extent of volatility fuel prices have seen in this
period. It was found that all fuels had experienced periods of both increasing and decreasing real
prices, but the overall trend for all fuels was upwards. Both gas and heating oil prices tended to track
oil prices, although heating oils fluctuated more dramatically, and the latter held true when
compared to all fuels analysed. In line with changes in the energy mix in the UK, changes in
electricity prices have tended to shift from following coal prices, to following those of gas. Coal
prices tend to be the least volatile.

The development of the scenarios was also informed by other similar work, such as that of the
Association for the Conservation of Energy58, the Royal Commission on Environmental Pollution59,
and Chatham House60. The DTI projected trends in fuel prices to between 2005 and 201061, and BERR
has published the 2007 Energy White Paper’s updated energy and carbon emissions projections62
For example:

“It is assumed that oil prices ease post 2006 as new production capacity comes on-stream and
demand growth moderates, leading to an increase in spare production capacity. However, as oil
is increasingly produced from more expensive sources and we assume spare capacity remains
relatively tight, prices are assumed to remain higher than the historic average.” (BERR 2008b)

The IEA 2006 World Energy Outlook projections for fuel price increases through to 2030, estimated
crude oil would cost approximately $100 per barrel, in real terms; an upward revision of $45 over
estimates from the previous year. To varying degrees, these publications take into account more
recent shifts in both local and global market and policy conditions, and have influenced the scenarios
used here accordingly. The more significant conditions considered are outlined below.


58
   Smith, Wu, & Pett 2005
59
   RCEP 2000
60
   RIIA 1998
61
   BERR 2006
62
   BERR 2008b

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International context
Geo-political events can have significant ramifications for wholesale energy prices; however these
will only affect UK domestic prices when sustained over long periods. Disruptions to oil supply lines
in Nigeria, Bolivia’s intention to re-nationalise its gas industries, and continued tension, sanctions
and conflict in the Middle East do coalesce to force up wholesale oil, gas, and to a lesser extent coal
prices – which are eventually reflected in domestic UK energy bills. Direct action, such as Russia’s
recent suspension of gas supplies into Europe due to pricing rows with the Ukraine and Belarus can
trickle down to domestic energy prices: OPEC has recently indicated that it will not raise oil
production to ease prices.

These supply constraints can of course be mitigated or magnified by global demand for energy.
                                                 63
Appendix Figure 5: World primary energy demand

Recent global energy demand has been bolstered by exceptional economic growth in China, and to a
lesser extent, in the USA and India. According to the IEA, these trends are expected to continue, as
global demand increases by more than half over the next quarter of a century63.

Climate change will also increasingly affect global energy prices. On the one hand, warmer winters
will tend to ease demand, suppressing fuel prices, whereas on the other, warmer summers, more
frequent and severe weather events, carbon taxes and pricing, and greater use of currently more
expensive alternative energy technologies (such as wind turbines) will tend to drive up prices.

EU context
Due in large part to the global landscape outlined, the European Commission has decided to develop
policy in a domain previously dealt with at the national level.

In its Energy Policy for Europe, the Commission has broadly suggested that global, market-led forces
will sustain upward pressures on fuel prices, particularly in the case of oil, gas, and coal. In terms of
demand, the Commission estimates that, in a business as usual scenario, electricity demand will
continue to rise by about 1.5% per year, at a time when existing plant and infrastructure are
reaching the end of their useful life. ‘Even with an effective energy efficiency policy, investment in
generation alone over the next 25 years will be necessary in the order of €900 billion’64. Under
existing market conditions, and in view of proposals for further internal energy market reform
including less state intervention, these investment costs imply upward pressure on electricity prices,
too. However, increasingly competitive energy markets across Europe should mitigate against these
forces to some extent.

Whilst tackling energy demand is central to the Commission’s policy by meeting the ‘key goal of
reducing its global primary energy use by 20% by 2020’, arguably its flagship energy efficiency policy,
the Emissions Trading Scheme will impose upward forces on fuel prices. The Strategy concludes that
the EU ETS ‘is critical to creating the incentives to stimulate changes in how Europe generates and
uses its energy’64, indicating that the price of carbon is currently too low. Higher carbon prices will
affect energy prices in two key areas: 1) carbon-emitting energy will cost more to generate (via
higher permit prices), and 2) generators avoiding carbon-emitting energy will have to invest in

63
     IEA 2007
64
     EC 2007

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alternative generation, which is costly. Additionally, the EU Directive on Large Combustion Plant
imposes emission limit values for sulphur dioxide and nitrogen oxides in existing and future coal-
fired plants, which in turn require the installation of costly scrubbing technologies, or the shutting
down of plants where such upgrades are unfeasible (see ‘UK context’ below).

In line with current trends, the EU’s energy import dependence will increase from 50% of total
energy consumption in 2005 to 65% in 2030. Imports of gas are expected to increase from 57% to
84% by 2030, of oil from 82% to 93% – in volume terms, a doubling of today’s imports. The
Commission admits that it is not clear from where, or how these supplies would come, but ‘with
rising dependence on imported hydrocarbons, the EU is becoming increasingly exposed to price
volatility on international energy markets’. Whilst ‘volatile’ price movements generally begin with
upward movements, sustained periods of volatility of themselves attract a risk premium, which will
again be reflected in prices paid by the consumer.

UK context
In addition to price influences brought to bear by global and EU activity, UK domestic energy prices
are of course subject to national factors. One key factor will be the impact of the UK government’s
2007 White Paper. For example in addressing the possibility of new nuclear, the Government
anticipates that a continuation of high fossil fuel prices and the introduction of carbon prices will
enable nuclear to be economically viable. Indeed, it appears to go further, hedging against the EU
ETS pricing carbon (and therefore electricity) at levels viable for nuclear: ‘we will keep open the
option of further measures to reinforce the operation of the [EU ETS] scheme in the UK should this
be necessary to provide greater certainty to investors’65. This suggests that the government will
reserve the right to enforce sufficiently high carbon – and therefore electricity – prices to maintain
the viability of an unsubsidised nuclear generation industry, thereby introducing a ‘price floor’.

Further investment in both production and supply capacity is needed in the UK, and this will have
varying effects on domestic prices. It is estimated that 40% of the UK’s current power stations will be
closed by 2015, through a combination of nuclear plant retirement and EU initiatives such as the
Emissions Trading Scheme (ETS) and the Large Combustion Plant Directive. E.ON estimates that it
will take up to £70bn to build the new power stations and infrastructure needed to meet our future
energy requirements66, and this is most likely to be brought about through higher price signals. On
the other hand, the UK has suffered from supply constraints, in the form of a lack of distribution and
storage capacity. Whilst investment required here will come at significant cost, the recent
commissioning of new gas import terminals in the UK has dramatically moderated increases in
wholesale prices as supply capacity has improved, which should in time be reflected in domestic
energy bills.

In 2004, the Renewables Obligation added around 2% to the price of domestic electricity, and the
DTI projects that, if set at 10% of total generation, the longer-term price impact will be a premium of
about 4%67. Similarly, the Energy Efficiency Commitment (EEC), and its successor the Carbon
Emissions Reduction Target (CERT) (will have) had a ‘small’ effect on gas prices, and will add a 3%
premium to the price of electricity by 2010 (CERT 2008–11, is expected to cost the average

65
   DTI 2007 p. 23
66
   Haigh 2005
67
   BERR 2006

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household approximately £36 per year, Heat Call for Evidence, January 2008). However, this will not
affect all customers, since some will benefit from lower fuel bills due to increased energy efficiency
achieved under EEC and CERT. Implementation of the EU ETS, based on a carbon price of €5-25/tCO2
has been estimated to lead to price increases of between 3-14% in the UK, although the lower-end
impact is more likely67.

Conclusion
Factors affecting future domestic energy prices are likely to include the source and supply of
conventional energy; its reliability, availability, associated production and infrastructure costs, and
global demand. These factors in turn affect, and are affected by, the development and cost of
alternative production, generation and energy-saving technologies stimulated by national and EU
policy. The four scenarios modelled are intended to reflect the range of more probable combinations
of these factors.




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Appendix III – Modelling fuel poverty: the Fuel Prices Model
Below is a very detailed description of the Fuel Prices Model as originally written for ‘The Impact of
Rising Fuel Prices in the Managed Housing Sector’68 and ‘How Much? The cost of alleviating fuel
poverty in England’69 and as recently revised for this project. The existing model produces accurate
predictions of fuel poverty up to January 2007. The timetable and resources for the project did not
allow for fundamental changes to the model, such as updating the 2004 base statistics, this being
currently an extremely labourious and time consuming process. However, for this project, new data
on fuel price changes and income increases since January 2007 have been obtained to project the
estimates further forward to April 2008 and beyond.

Members of the project team have recently secured funding from Eaga PCT to further develop and
update the current Fuel Prices Model to the baseline provided by the 2006 EHCS (scheduled to be
released in September 2008) as part of Improvement Prophet. This work will provide a new, more
user-friendly, more interactive and easily updateable model that will assess the impact of future
changes in fuel prices, incomes and energy efficiency as well as model the necessary improvement
measures and costs needed to achieve chosen energy, carbon and fuel poverty targets. This
computer model, together with guidance on its use, will be made freely available to all stakeholders
and is expected to be launched in summer 2009.

Overview of the Model
The Fuel Prices Model is a sophisticated computer model designed to determine the impact of any
changes in fuel prices, household incomes and housing improvements on fuel poverty. This
predictive model is based on the English House Condition Survey and has been developed over the
last three years, initially with joint funding from energywatch and Unison and subsequently via work
commissioned by the Energy Efficiency Partnership for Homes.

For each EHCS sample dwelling, the fuel costs for space heating, water heating, cooking and lights
and appliances are updated separately according to the energy requirements, existing fuels used or
likely improvements undertaken, the regional location, tariff and supplier type. The net impact of
fuel price rises on the total fuel costs is thereby determined. For each sample household, the existing
income is updated depending on the source of income of each household member, taking into
account their employment, benefits received and marital status, sex and age. Housing costs are
updated depending on the region , tenure or rental sector. Finally, the updated total fuel costs are
related to the updated household incomes to give new fuel poverty estimates. Appendix Figure 6
illustrates how the existing model works for producing current and future estimates.




In practice, projecting the EHCS baseline estimates forward is done in two stages:




68
     Guertler, Moor & Preston 2007
69
     Moore, Preston & Guertler 2008

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          To provide current estimates of fuel poverty, the most accurate available data on actual fuel
           price changes, income changes and energy efficiency trends are used to effectively provide a
           new updated baseline.

          To project fuel poverty forward into the future, informed but inevitably more speculative
           assumptions are made as to how fuel prices, income and energy improvement rates might
           change from this new current baseline.
                                                                 70
Appendix Figure 6: Simplified diagram of the Fuel Prices Model

The model is validated by projecting its estimated trends in fuel poverty back to previous years and
comparing the results with the published EHCS figures for fuel poverty for those years, as adjusted
for any recent methodological changes.

Determining trends in fuel prices

Price rises to Q2 2006
The 2004 EHCS fuel poverty estimates use average regional gas and electricity prices for each
payment method (direct debit, credit and prepayment) for the two periods Q4 2002 to Q3 2003 and
Q4 2003 to Q3 2004 for the EHCS dwellings surveyed in 2003/04 and 2004/05 respectively.
Depending on the year of the sample, these average prices have been updated to the start of Q2
2006 using the BERR’s Quarterly Fuel Price data (Table 2.2.3 and Table 2.3.3, 2006 issue) for average
regional electricity and gas prices for each payment method for the period Q4 2005 to Q3 2006.

For example, Appendix Table 5 shows the average unit electricity prices for each tariff in each year
for London and the corresponding percentage increases to 2006 for each part of the EHCS sample.
For the comparative estimates for all England, the equivalent price increases are determined for
each of the other ten electricity regions and, for gas prices, for the ten gas distribution zones in
England and applied to the corresponding fuel prices in the 2004 EHCS.
                                                                                   71
Appendix Table 5: Average electricity prices and percentage increases for London

                  Average fuel prices p/kWh & percentage increases
                  Direct Debit                    Standard credit               Pre-payment
EHCS sub-
                     2003/04            2004/05      2003/04          2004/05           2003/04   2004/05
sample

Q4 2002 –
                          7.30                           7.55                              7.67
Q3 2003
Q4 2003 –
                                           7.39                          7.64                        7.58
Q3 2004

Q4 2005 –
                          9.76             9.76         10.27           10.27             10.55     10.55
Q3 2006

Percentage
increases
                        +33.70           +32.07        +36.03          +34.42            +37.55    +39.18
applied to
2004 EHCS

70
     Moore, Preston and Guertler 2008
71
     BERR 2006

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The 2004 EHCS prices for non-metered fuels, such as oil, LPG and various solid fuels, relate to
October 2003 or October 2004, depending on the survey year. These have been similarly updated in
each of four regional groups to May 2006, using average prices from the Sutherland Tables of
comparative heating costs.

Price Rises since Q1 2006
To determine fuel prices after Q1 2006 (for the existing model, then the latest from BERR), data from
energywatch has been used to first determine the gas and electricity price rises introduced since
then by each of the six main fuel suppliers (British Gas, EDF, nPower, Powergen, Scottish Power and
Scottish and Southern Energy) for each tariff type - direct-debit, standard credit and pre-payment –
in each of their home and non-home areas.

The 2004 EHCS samples falling into each of the 10 English gas distribution zones and 11 electricity
regions have been determined. These samples have then been split into sub-samples in proportion
to the percentage of direct debit, credit and prepayment customers in each zone or region who are
with the home supplier or a non-home supplier (as shown for March 2006 in BERR Tables 2.4.1 and
2.5.1, Q1 2006).

Appendix Figure 7 shows how the EHCS sample for London, then representing 3,041,000
households, has been divided according to the percentage of households with each tariff (as shown
by the EHCS) who are with the home supplier for that region or another supplier. The other 10
electricity regions and the 10 gas regions have each been divided in a similar way and all the relevant
fuel price rises applied accordingly.

The EHCS no longer collects information on the particular supplier used by each household, only on
their tariff type. Consequently, within each tariff type, each home or non-home supplier sample has
been randomly chosen (using the EHCS address code), except that the home supplier sample has
typically been allocated around 5% more retired households than the non-home supplier sample, to
reflect the lower propensity of elderly households to switch suppliers or change tariffs.

Appendix Figure 7: Division of EHCS sample and application of electricity price rises since Q1 2006 in London

Each home supplier sample is then allocated the particular fuel price rises appropriate to that home
region and tariff type. Each non-home supplier sample is assumed to be distributed amongst the
non-home suppliers in relation to their overall market share. The average fuel price rises of all non-
home suppliers in each gas zone and electricity region are calculated assuming this distribution.

Before applying the appropriate gas and electricity price rises to each sub-sample, an adjustment is
made to allow for the switching of suppliers or tariffs since March 2006. The appropriate adjustment
is calculated for each tariff type in each zone or region by comparing the fuel price rises between
2004 and 2006, shown by the energywatch data, with the rises over the same period determined
from the average regional fuel price data published by BERR. The generally lower rate of increase
shown by the latter compared with rate of increases from suppliers, can be attributed to households
switching suppliers or tariffs, including the take up of social and protected tariffs, to achieve
generally lower fuel price rises.



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Assuming that the effects of switching supplier between March and January 2007 would have been
proportionately similar to those achieved between 2004 and 2006, the appropriate reduction factors
have been applied to the price increases since Q1 2006. The adjusted gas and/or electricity price
rises are then applied to each home according to its zone or region, tariff type and whether it has
been allocated to a home or non-home supplier.

Price rises since Q1 2007
After January 2007, all of the main suppliers reduced their fuel prices, but these falls have been
more than offset by subsequent price rises in 2008 from all suppliers. Appendix Table 6 shows the
cumulative changes in gas and electricity fuel prices by the six main suppliers since January 2007 up
to and including April 2008. Across the country, total fuel prices are now around 1% higher than
they were in January 2007, mainly due to net increases in electricity prices. The fuel price rises in
London since January 2007 are applied to the model in the same way as the price rises since Q1
2006, as described in detail above. However, BERR Tables 2.4.1 and 2.5.1, for Q1 2007, were now
used to determine the percentage of customers with the home supplier and updated market share
information was also applied.

Appendix Table 6: Summary of cumulative fuel price changes since January 2007

Supplier                                         Percentage change
                                                 Gas                                Electricity

SSE                                                                           3.8                    9.2
nPower                                                                        1.2                    9.7
Scottish Power                                                               -1.5                    8.0
EDF                                                                           2.7                    7.9
British Gas                                                                  -4.5                   -1.2
E.On-Powergen                                                                -1.0                    4.8

Average increase per supplier                                                 0.1                   6.4
Average increase per GB customer1                                            -1.5                   5.9
Average increase in total fuel costs2                                                               1.0
1
    Accounting for market share at January 2008
2
    Accounting for average energy requirements between gas and electricity

Determining trends in energy efficiency

Dwellings improved
In modelling trends in energy efficiency, the first task is to determine which dwellings are most likely
to have been improved since the 2004 EHCS. In the private sectors it is assumed that significant
energy efficiency improvements are only likely to have occurred where, not only low thermal
standards existed, but the household was dissatisfied with the heating or standard of insulation. In
the 2004 EHCS sample, these are represented by those owner occupiers who did not have a recent
heating system and/or lacked wall and/or loft insulation and respectively recorded their heating
and/or insulation as “not very effective”, “not at all effective” or non-existent.

Similar criteria are applied to those privately renting, except that with tenants being more likely to
complain than owner occupiers and private landlords being often more reluctant to take action, only
those cases where the heating was deemed by the tenant to be “not at all effective” or non-existent

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are energy measures assumed. In the public sectors, the assumption is that dwellings failing the
thermal criteria of the decent homes standard (DHS) would have been the first to receive energy
measures. Thus, dwellings are scheduled for improvement after 2004 if they did not then have a
recent heating system and failed the DHS on heating and/or lacked wall and/or loft insulation and
failed the DHS in this regard.

Of the dwellings ‘scheduled’ for improvement, as above, only a proportion are selected for
improvement (randomly from the EHCS address code) to reflect the fact that not all ‘deserving’
dwellings will be improved in practice, and to give rates of improvement comparable with those
actually achieved in each tenure (as shown by EHCS ‘work done’ data and increasing SAP ratings).

Extent of improvement
To determine the likely effect of any energy measures actually applied after 2004, the last
longitudinal sample of the EHCS, containing dwellings surveyed in both 1996 and 2001, has been
analysed72. From this sample, all dwellings showing significant energy efficiency improvements
between 1996 and 2001 were examined. However, any dwelling showing an improvement in their
SAP rating of less than 5 points was omitted, as such a small improvement could result from
differences in the data collected in 1996 and 2001 rather than any significant energy measure.

As shown in Appendix Table , for each decile in the range of SAP ratings existing in each tenure
before improvement in 1996, the average extent by which the SAP rating had risen by 2001 was
determined. As would be expected, those dwellings with the lowest SAP ratings in 1996 generally
showed the greatest improvement and vice versa, and this was the case in all tenures. However,
within each rating band, the greatest average improvements were generally achieved in the social
rented sectors and the least in the owner occupied stock.

These SAP improvements have been applied to the corresponding dwellings in the full 2004 EHCS
sample, selected for likely improvement after 2004 on the above criteria, and the mean SAP ratings
after improvement thereby determined. Using the final algorithms in the standard assessment
procedure, the space and water heating costs before and after improvement have been determined
from the before and after SAP ratings. However, the consequent saving in the heating costs have all
been inflated by a nominal 15% to reflect the application of generally more efficient energy
measures (more efficient new boilers and insulation etc) after 2004 than occurred in the late 1990s.
Revised new SAP ratings have then been calculated to allow for this increase.




Appendix Table 7: Average improvements in SAP rating by original rating by tenure, 1996-2001

Original SAP          Improvement in SAP rating 1996 to 2001
rating                owner occupied        private rented         local authority       RSL


72
  With the 2006 EHCS, a longitudinal sample has now been re-introduced into the Survey, but results from this
will not be available until autumn 2008.

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<SAP 26                             + 20.0              + 26.0               + 30.4                + 32.4
26-35                               + 17.0              + 17.5               + 20.0                + 25.4
35-40                               + 13.5              + 14.3               + 15.2                + 19.9
40-44                               + 15.2              + 16.5               + 16.4                + 15.1
44-48                               + 12.3              + 11.4               + 15.7                + 16.8
48-52                               + 12.1              + 12.8               + 13.7                + 11.9
52-55                               + 10.6              + 12.6               + 12.4                + 15.9
55-60                                 + 9.6             + 14.4               + 13.3                + 12.2
60-66                                 + 8.1               + 7.7              + 10.1                + 13.3
66 plus                               + 6.7               + 7.2                + 8.8                 + 8.3
All improved                        + 14.3              + 16.8               + 18.0                + 18.9



Improvement rates
The first column of Appendix Table shows the average annual rate of major improvements in SAP
ratings achieved between 1996 and 2001. However, increased awareness and concern regarding
domestic energy efficiency is likely to have increased installation rates since the late 1990s. An
indication of equivalent recent improvement rates is given by questions in the 2004 EHCS on work
done by occupiers and/or landlords over the previous 12 months. Using this data, dwellings are
selected which have received significant energy related work (for example, excluding boiler servicing
alone) and now have an above average SAP rating for their particular tenure, age and built form. As
shown in the second column of the Table, the resulting annual rates are all higher than before 2001,
except for the privately rented sector where, for example, through the addition of new ‘buy-to-let’
properties the average SAP rating had already increased substantially.

For the dwellings scheduled for improvement following the 2004 EHCS, the take up rate of energy
measures has been determined up to Q1 2007 from the time (month and year) when each sample
dwelling was surveyed. The resulting average annual rates for each tenure are comparable with
those achieved in the 12 months prior to the 2004 EHCS, as shown by tenure in the third column of
Appendix Table .

Appendix Table 8: Annual % of homes improved 1996-2001, 2003-2004 and 2004-2006

                       Annual % of homes with major SAP rises                            Total Hholds
                       1996 to 2001           2003 to 2004         2004 to 2006*         2004 (x1000)
Owner occupied                          4.5                  5.7                   5.7             14,922
Private rented                          6.2                  4.5                   4.9              2,184
Local authority                         7.0                  7.5                   7.8              2,215
HA/RSL                                  6.3                  7.5                   7.6              1,611
All tenures                             5.3                  5.9                   5.9             20,931
* excludes dwellings built since 2004

Given the increasing priority afforded to energy work, the overall improvement rates since 2004
appear reasonable, as in practice Government programmes such as Warm Front only account for a
relatively small proportion of total energy related work in the private sectors. However, the model
does assume reasonably good targeting of energy work, especially in the social sectors.

In applying the model to the current project, the rate of energy efficiency improvements in each
tenure since January 2007 was assumed to match the average of those between 2004 and 2007.




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Determining income trends

The 2004 EHCS Income Model
The new methodology for updating incomes following 2004 first involves re-constructing the EHCS
income model, so as to determine the many income components making up the three income
variables provided by the public dataset. These are the EHCS basic income for the household
reference person (HRP) and any partner and both the fuel poverty basic and full incomes for each
full household. As no other derived income variables were available from DCLG or BRE, this was
done by re-modelling the large amount of raw income data collected in the 2004 Survey in a 3,215
line syntax program.

The components for each of the three incomes and how the incomes relate to each other, is shown
in the left hand column of
Appendix Figure 8 below. The EHCS Basic Income is made up of the net income from various forms
of employment of the (HRP) and any partner, income from Government schemes, income from
occupational pensions and private pensions and annuities, income from investment and income for
a large raft of different benefits. Frequently, the combined household income of the HRP and any
partner will come from several of these different sources.

Unlike the EHCS basic income, the fuel poverty basic income relates to the whole household and
includes the income from Winter Fuel Payments (WFP) for any eligible person in the household and
the income of any other benefit units in the household. The latter include independent children and
other relatives, lodgers and other families in the home, and their combined income can be
determined relatively easily by subtracting the income from all WFPs from the difference between
the EHCS and fuel poverty basic incomes.

The fuel poverty full income also relates to the whole household and additionally includes income
from Housing Benefit and from Income Support for Mortgage Interest (ISMI) and Mortgage Payment
Protection Insurance (MPPI). However, this final income variable excludes net Council Tax, as it
includes any Council Tax Benefit but deducts Council Tax from the income of all households.

Updating the 2004 incomes
The 2004 EHCS sample comprises households interviewed in both 2003/04 and 2004/05 and these
two parts of the sample are also updated separately, with typically the increase from 2003/04 to the
present day being more than that from 2004/05. How each component of income is updated is as
shown in the right hand column of
Appendix Figure 8.

Any income from self employment, other main employment and any other job is updated separately
for the HRP and any partner using time series data from the Annual Survey of Hours and Earnings
(ASHE). Earnings from the 2004 EHCS are updated according to the income quartile for the
Government region, employee’s sex and hours worked (full or part time) in which the HRP or
partners earnings fall. ASHE shows that all of these factors influence the average increase in earnings
since 2003/04 and 2004/05. Any income from Government Schemes, however, is up-rated in line
with that of the Jobseeker’s Allowance.




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All occupational pensions and private pensions are assumed to be index linked and are consequently
updated at the 1 April each year in line with the retail price index (RPI). This is likely to be largely true
for occupational pensions, but may over-estimate the increase in some private pensions.

2004 EHCS INCOME MODEL                                 Income updated from (a) 03/04 & (b) 04/05

Income from Employment                                 Up-rate using ASHE data depending on:-

    (1)   For HRS and (2) for partner; from                    Government office region
         Self-employment                                      sex of employee
         Main employment                                      full or part-time work, and
         Other work                                           income quartile for above
                        +                                                         +

Income from Government Schemes
                                                       Assume same up-rating as for Jobseekers Allowance
    (1) For HRS and (2) for partner

                         +                                                      +

Income from Non-State Pensions, from
                                                       Updated assuming all pensions index linked and up-
                                                       rated at 1/04 each year in line with RPI
         Occupational pensions
         Private pension or annuities
                        +                                                       +

Income from Investments                                Assume interest of 4.75% and re-investment of
                                                       interest according to income.
         Interest from savings etc
                         +                                                      +

Benefit Income – workers & families

         Income support*
         Jobseekers allowance*                        Up-rate each benefit using DWP data according to
         Working families tax credit*                 type of benefit, and relevant household composition
         Working tax credit*                          and age criteria etc
         Child tax credit*
         Maternity allowance
         Carers allowance
         Sick pay
                          +                                                     +

Benefit Income – pensioners
                                                       Up-rate each benefit using DWP data according to
         Basic state pension                          type of benefit, and relevant household composition
         Pension credit (IS)*                         and age criteria etc
         Widows pension
         War disablement pension
                         +                                                      +

Benefit Income – disabled

         Incapacity benefit
         Severe disablement allowance                 Up-rate each benefit using DWP data according to
         Industrial injuries benefit                  type of benefit, and relevant household composition
         Attendance allowance                         and age criteria etc.
         DLA – mobility component
         DLA – care component
         Disabled persons tax credit*
         Disability premium with IS*


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          Other disability benefit
                           =                                                    =

                EHCS BASIC INCOME                                  New EHCS Basic Income

        (of HRP & Partner for each household)                      (Updated to present day)




                          +                                                     +

Income from Winter Fuel Payments
                                                      No change in Winter Fuel payments since 2004 EHCS
for all those eligible in household

                          +                                                     +

Income from Other Benefit Units
                                                      Increase according to number, employment, sex, age
                                                      & composition of additional benefit units and average
    Determine average incomes for independent
                                                      size of additional income, imputing from HRP &
    children, lodgers and sharing families re.
                                                      partner data above.
    EHCS data

                          =                                                     =

          FUEL POVERTY BASIC INCOME                            New Fuel Poverty Basic Income

                (for each household)                               ( Updated to present day)

                          +                                                     +

                                                      Up-rate housing benefit using DWP & DCLG data
Income from Housing Benefit
                                                      for region and rental sector.

                          +                                                     +

Income from ISMI & MPPI                               Up-rate benefits using DWP data

                          _                                                     _

                                                      Up-rate Net Council Tax using DCLG data
Deduct Council Tax less any CT Benefit from
                                                      depending on:
income of all households
                                                              Type of local authority (Met etc)
                          =                                                     =

           FUEL POVERTY FULL INCOME                             New Fuel Poverty Full Income

                (for each household)                               (Updated to present day)



Appendix Figure 8: EHCS Income Model and method of updating

An increasing income from investment is produced by assuming that the household’s recorded
savings provide interest, based on an APR of 4.75% per year, and that all or some of this interest is
reinvested. It is assumed that while all of the interest is re-invested by those in the highest quartile
of incomes this reinvestment decreases with income, such that only a half and a quarter is
reinvested by households on below average incomes and in the lowest quartile of incomes,

Association for the Conservation of Energy
Fuel Poverty in London


respectively. In short, it is assumed that for those on low income, the majority of the interest is
taken for daily living.

The 2004 EHCS collects data on some 20 different state benefits provided to workers and families,
pensioners and to persons with a long-term illness or disability. Each of these benefits is separately
updated using up-rating data from DWP, according to the type of benefit received and the
household composition, age and other criteria relevant to each particular benefit.

After updating all of the income components for each household, separately for the 2003/04 and
2004/05 samples, the components are summed to give the total basic income of the HRP and any
partner at the present time.

To determine the fuel poverty related basic income for the whole household, income from winter
fuel payments (WFP) is added without any updating. At the last revision of the model, there had
been no up-rating of WFP since the 2004 EHCS, the additional premium provided to persons over 80
being introduced in 2003/04. EHCS data was used to determine the number and type of additional
benefit units (ABUs) in each household, e.g. independent children, individual lodgers or second
families. Their incomes were then separately updated accordingly to their employment status, age,
number of dependent children and level of income. The updated incomes from the ABUs and that
unchanged from the WFPs, were then added to the updated EHCS basic incomes to get the basic fuel
poverty income for each household at the present time.

The full income used in the calculation of fuel poverty was revised by updating the housing benefit,
ISMI and MPPI received by each household, using regional up-rating data from CLG and DWP. Using
data from DCLG, Council Tax and net Council Taxes, were updated using the average increase in
council taxes since 2003/04 and 2004/05 for the type of local authority in which the household
resided i.e. London Boroughs, Metropolitan areas and Shire areas. Finally, the household income
from housing benefits or ISMI and MPPI were added to the new fuel poverty basic income and the
revised net council taxes deducted, to give the full income of each household at the present time.

   FUEL POVERTY FULL INCOME, BHC                          New Fuel Poverty Full Income, BHC
         (for each household)                                  ( Updated to present day)
                   _                                                       _

 Deduct gross rental payment of tenants or             Update rents and mortgage payments using
  mortgage payments of owner occupiers                 CLG regional data for each tenure and rental
  (actual payments as collected by EHCS)                                   type
                     =                                                       =
         RESIDUAL INCOME, AHC                                 New Residual Income, AHC
           (for each household)                                 ( Updated to present day)
                     >                                                       >
  Equivalise residual incomes AHC using                Equivalise new residual incomes AHC using
     Modified OECD Companion scale                          Modified OECD Companion scale

                    =                                                     =
       EQUIVALISED INCOME, AHC                               New Equivalised Income, AHC
          (for each household)                                 (Updated to present day)

Appendix Figure 9: Residual and equivalised income and method of updating




Association for the Conservation of Energy
Fuel Poverty in London


For this project and the projection of fuel poverty on the residual and equivalised income, AHC
definitions, housing costs have additionally been updated using regional data on rents and mortgage
payments for each tenure in each region (see Appendix Figure 9). To determine income increases
after January 2007, the DWP’s uprating list (HSC-014) for benefits and state pensions for 2007/08, as
published in December 2006, is used. However, for other households, less likely to be at risk of fuel
poverty, incomes after January 2007 have simply been inflated in line with the Retail Price Index.




Association for the Conservation of Energy
Fuel Poverty in London



Appendix IV – Equivalising EHCS incomes
The process of equivalisation involves adjusting the relative income of households according to their
size and composition, following the principle that to enjoy a comparable standard of living a larger
household will need a higher income than a smaller one. Equivalised incomes are generally adopted
in the assessment of household poverty, including in the DWP’s definitive ‘Households Below
Average Income’ (HBAI) series.

The EHCS public datasets only provide equivalised incomes for households before housing costs. To
equivalise incomes, after housing costs (AHC), the EHCS person level data on the age of each
household member is first used to determine the children in each household under the age of 14
years. The results are then aggregated to household level and each household categorised according
to the number of adults and older children and number of children under 14 years of age in the
home.

This information is then used to assign an equivalence factor to each household, using the OECD
‘Companion’ AHC scale given in Table A2 1.0 of Appendix 2 of the latest HBAI Report. This Table,
reproduced below, compares the currently used OECD scales with the more complex McClements
scales that were used to adjust incomes up to the 2004/05 HBAI publication.

Appendix Table 9: Comparison of OECD and McClements equivalence scales

                                 Modified OECD     OECD
                                 Rescaled to       ‘Companion’
                                 Couple            Scale to
                                 without           equivalise AHC     McClements     McClements
                                 Children = 1      results            BHC            AHC
First adult                                 0.67               0.58          0.61           0.55
Spouse                                      0.33               0.42          0.39           0.45
Other Second Adult                          0.33               0.42          0.46           0.45
Third Adult                                 0.33               0.42          0.42           0.45
Subsequent Adults                           0.33               0.42          0.36           0.40
Children aged under 14yrs                   0.20               0.20          0.20           0.20
Children aged 14yrs and over                0.33               0.42          0.32           0.34


Using the OECD derived AHC scale, the equivalence value for each household in the EHCS sample is
next calculated. For example, the AHC value for a household comprising a couple with a 10 year old
and 14 year old child is 1.62, this being simply the sum of the scale values:

        0.58 + 0.42 + 0.20 + 0.42 = 1.62

The total income, after housing costs, for each EHCS sample household is then divided by the
appropriate equivalence value to give a comparable measure of equivalised income, as used in the
HBAI series. The resulting average 2005 EHCS based incomes before and after housing costs and
before and after equivalisation are shown below for each region. For all households, the average
equivalised incomes are lower than the actual incomes. However, because the lowest income groups
tend to be smaller households, the reverse is the case for all households in fuel poverty under the
respective definitions. Consequently, for both full and residual incomes, the national fuel poverty
estimates (but not all regional estimates) are slightly lower when based on equivalised incomes.

Association for the Conservation of Energy
Fuel Poverty in London


Appendix Table 10: Average actual and equivalised BHC and AHC incomes by GO region, 2005

Government           Full income BHC (EHCS data)               Residual income AHC (derived)
Office Region        Actual £           Equivalised £          Actual £          Equivalised £

South East                      28,865               26,072               24,645            22,659
London                          28,358               25,588               22,820            20,830
East of England                 26,222               23,755               22,416            20,531
South West                      23,372               22,053               20,081            19,346
East Midlands                   22,465               20,817               19,458            18,487
West Midlands                   22,936               20,670               20,091            18,338
Yorks & Humber                  22,716               20,792               20,032            18,619
North West                      22,467               20,529               19,747            18,338
North East                      19,265               18,137               16,887            16,261

In fuel poverty                  8,175                9,718                6,202            7,274
All households                  24,773               22,615               21,205           19,677




Association for the Conservation of Energy
Fuel Poverty in London



Appendix V – Datasets and other statistics used for this report
This list complements the sources of data referred to in Appendices II, III and IV.

All 2005 estimates

       CLG, English House Condition Survey, 2005 datasets; obtained from CLG

All 1996 to 2004 estimates

       CLG, English House Condition Survey, 1996 to 2004 datasets; obtained from CLG

Fuel poverty - 2008 projections

       CSE, ACE, RM, Fuel Prices Model, as revised
       CLG, Revised projections of households for the English regions to 2026, February 2008
       BERR, Quarterly Energy Prices, March 2008
       energywatch, Supplier price changes, March 2008

SAP/EPC - 2008 projections

       CSE, ACE, RM, Fuel Prices Model, as revised
       CLG, Revised projections of households for the English regions to 2026, February 2008
       CLG, English House Condition Survey,2006, Headline Report, January 2008

Fuel poverty - 2010, 2016 & 2030 projections

       As for 2008 projections above, plus ACE fuel price scenarios (supplied)

Pre-payment data

       BERR, Quarterly Energy Prices, March 2008
       AEA Technology’s report to the GLA (as yet unpublished)




Association for the Conservation of Energy
Fuel Poverty in London



Appendix VI – Glossary

Decent Home standard (DHS)
A Decent home is one that meets the following four criteria:

    a) It meets the current statutory minimum for housing. (In the DHS used in this report, this is
       the fitness standard, although this has now been replaced by the Housing Health and Safety
       Rating System).

    b) It is in a reasonable state of repair (related to the age and condition of a range of building
       components including walls, roofs, windows, doors, chimneys, electrics and heating
       systems).

    c) It has reasonably modern facilities and services (related to the age, size and layout/location
       of the kitchen, bathroom and WC and to any common areas for blocks of flats, and for noise
       insulation).

    d) It provides a reasonable degree of thermal comfort (related to the insulation sand heating
       efficiency).

Eligibility for Warm Front
In order to qualify for a Warm Front grant, applicants must meet one of the following criteria:

    1. Aged over 60 – householders aged 60 or over in receipt of one or more of the following
       benefits:

            a.   Income Support
            b.   Council Tax Benefit
            c.   Housing Benefit
            d.   Job Seekers Allowance (income-based)
            e.   Pension Credit

    2. Child under 16 or pregnant – householders with a child under 16, or pregnant women with
       maternity certificate MAT-B1, in receipt of one or more of the following benefits:

            a.   Income Support
            b.   Council Tax Benefit
            c.   Housing Benefit
            d.   Job Seekers Allowance (income-based)
            e.   Pension Credit

    3. Householders in receipt of one or more of the following benefits:

            a. Working Tax Credit (with an income of less than £15,460, which must include a
               disability element)
            b. Disability Living Allowance
            c. Child Tax Credit (with an income of less than £15,460)
            d. Housing Benefit (which must include a disability premium)

Association for the Conservation of Energy
Fuel Poverty in London


                e. Income Support (which must include a disability premium)
                f. Council Tax Benefit (which must include a disability premium)
                g. War Disablement Pension (which must include a mobility supplement or Constant
                   Attendance Allowance)
                h. Industrial Injuries Disablement Benefit (which must include a mobility supplement or
                   Constant Attendance Allowance)
                i. Attendance Allowance

SAP
SAP is the energy cost rating as determined by the government’s Standard Assessment Procedure
and is used to monitor the energy efficiency of homes, taking into account such factors as the
efficiency of the heating system and standards of insulation in the dwelling. It is an index based on
calculated annual space and water heating costs for a standard heating regime. Two versions of SAP
are used in this Report. SAP 2001 is expressed on a scale 1 (highly inefficient) to 120 (highly efficient)
while SAP 2005 ranges from 1 (highly efficient) to 100 (highly efficient, with 100 representing zero
energy costs).

Under-occupancy73
A dwelling is considered under-occupied if it is more than large enough for the number (and type) of
occupants living there. The Parker-Morris standard and the Bedroom Standard are used to define
what size of dwelling is large enough. The Parker-Morris standard gives a minimum floor area for a
home depending on the number of occupants and the Bedroom Standard allocates a separate
bedroom to each person (or combination of people – for example a couple) requiring one. It is
assumed that all homes where the floor area is over twice the minimum set down in the Parker
Morris standard and the number of bedrooms is in excess of the Bedroom standard are under-
occupied.

The above government definition is used for the specific analysis of under-occupation, but for
comparing the causal factors of fuel poverty a simpler and more direct measure of under-occupancy
– the number of square metres of floor space per adult – is used.

Vulnerable household
A vulnerable household is defined for the purposes of fuel poverty as being any household with a
member aged 60 years or over, a child under the age of 16 or a member who is disabled or has a
long term illness. This relates to the Government’s target of reducing the number of vulnerable
households living in fuel poverty to zero by 2010, as far as is treasonably practicable.




73
     CLG 2008

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Fuel Poverty in London



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