Who Applies for Energy Grants?

08 Jun 2023

The UK will fail to deliver on Net Zero targets for home energy unless there is a massive improvement to the energy performance of the current housing stock. UK households can apply for grants or loans to pay for energy efficiency improvements to their home. Some of these incentives are aimed at wealthy households looking to improve their homes by installing measures such as solar panels. Other schemes target low-income households living in inefficient homes where insulation could be improved, or boilers updated.

However, there has been little investigation as to who actually applies for energy grants. As part of our UKERC funded ‘Whole Person, Whole Place’ project we asked the question ‘Who applies for energy incentives in the UK?’.

A rational explanation would be that applicants are those who can financially benefit the most. However, we suspected that other factors might also influence a household’s ability to access grants. Applying for grants requires knowledge that the grant exists, the ability to get quotes to have work done and a lot of forms to fill in. We thought that middle-class people would be most likely to have the time, agency, money and skills to apply for a grant in comparison to other social groups. This explanation can be described as relational. But when we investigated this, we found our hypothesis to be incorrect.

The characteristics of households who apply for grants

We looked at four schemes: The Energy Companies Obligation (ECO), the Green Deal (GD), the Feed in Tarrif (FiT) and the Renewable Heat Incentive (RHI) (see Table 1). We combined data on  applications for grants from the Energy Performance Certificate (EPC) repository with geodemographic data from the UK Census and the Indices of Multiple Deprivation.

Table 1: Summary of ECO, GD, FiT and RHI domestic energy incentives in the UK 2010-present

We extracted the numbers of applications for ECO, FiT, RHI and GD, by household energy efficiency grade, income, dwelling type and tenure. We then compared these observed counts with what we would expect the numbers to be. The expected rates assume all household apply at the same rate – so if 50% of homes are terraces, then we expect 50% of applications to come from terraces. Then we calculated how many times more than expected rates of applications are for each household characteristic (see Table 2). This is known as a propensity.

The results showed that households that are low income, living in inefficient terraces are more likely to apply for ECO and GD. This is evidence for a strong rational signal at play in the applications for these incentives – people applying for support to improve the efficiency of their homes. Finally, RHI and FiT is applied for by households already living in efficient homes and also see inefficient homes applying for RHI.

Table 2: Propensity of homes to apply for domestic energy incentives by household characteristic. Figures in bold red are over twice the average application rate

Investigating an existing typology

Next, we investigated applications by household types from the Output Area Classification (OAC) (Table 3). The OAC is a neighbourhood level classification of household types constructed using data from the census. We wanted to find out whether using a typology – which uses multiple characteristics – better describes the types of households applying for grants.

Table 3: Propensity of homes to apply for domestic energy incentives by OAC. Figures in bold red are over twice the average application rate

People living rurally are more likely to apply for FiT and RHI. This is not an unexpected finding and this pattern is documented in an early assessment of the RHI scheme. The finding that ethnicity may play a role in likelihood of applying for ECO and GD is unexpected. The schemes have not been designed to target specific ethnic groups and this needs further investigation.

Do we see more applications from the group ‘Challenged Asian Terraces’ because the homes they are living in are the worst performing; because this group is overrepresented in the lowest income decile; because the schemes are designed for the building type they are living in; or is there a strong relational signal as well? The OAC does not have the categories to help us answer these questions because there is no equivalent ‘Challenged White Terraces’ group for us to test our theories about ethnicity.

Developing a typology: the role of ethnicity in ECO applications

We constructed our own typology by subdividing UK neighbourhoods by energy efficiency, dwelling type, tenure and income. Here we focus on ECO applications because the ethnicity finding was strongest for this type of grant. As expected we found high rates of applications in neighbourhoods classified as low income, inefficient, owner occupied, terraces – almost four times the expected rate. This group was known as Type 24 in our classification.

Next we added ethnicity into our neighbourhood classification. Just 2% of GB neighbourhoods are predominantly Asian, yet these neighbourhoods represent one sixth of Type 24. Households of Asian origin that are low income, living in inefficient, owner occupied, terraces apply at a rate twelve times higher than the average GB household’s ECO application rate. This group was known as Type 24a in our classification. Similar neighbourhoods of white or other ethnic origins did not apply at rates higher than expected.

Is there a community effect to applications for ECO in Bradford?

Given this surprising finding, we wanted to dig further still into the uptake of energy grants in one of these predominantly Asian neighbourhoods.  Figure 1 maps type 24a on to neighbourhoods in the city of Bradford and overlays the ECO application data. Clusters of applications for ECO are concentrated in the parts of the city classified as type 24a. But are we seeing high rates of applications for ECO in Bradford due to the fact that households of type 24a are over-represented here or is the application rate even stronger than expected?

Figure 3: Location of Type 24a classified OAs in the Bradford city area with numbers of ECO applications per OA overlaid

If Type 24a households in every local authority (LA) applied in the same proportions that we would expect for this type of household, we would see propensities of 12 for all LAs. In Bradford we find this type of household are over 26 times more likely to apply for ECO than expected. This suggests that geography also has a role in the distribution of applications. Other LAs with rates higher than expected are Calderdale, Kirklees and Leeds – all in the West Yorkshire region.

Evidence suggests that for certain household types in certain parts of the country, rates of application to ECO are greater than expected based on income levels and house types. This suggests a relational and perhaps community effect is in operation. To determine whether this is the case, we have a follow up UKERC funded project, focussing on Bradford, interviewing households about energy grants applications.

What does this mean for energy policy?

Our work shows that it is not always that case that ethnic minority groups are disadvantaged by first-come first-served energy policy. In contrast to most research on energy and ethnicity we find an active and engaged segment of the population adopting energy retrofit measures in ‘Challenged Asian Terraces’ in great numbers in West Yorkshire.

The implication for energy policy is substantial. A ‘first come-first served’ grant does not always disproportionately benefit affluent predominantly white homes. Instead, some groups will benefit more than others. Secondly, we know that the social networks and relations surrounding energy policy very likely play a role in its success and uptake. This has significant implications for energy policy design and implementation. Energy policy that seeks to meet global decarbonisation targets within remaining timeframes would do well to factor in relational, as well as rational, dynamics.

The Social Relations of Applying for Energy Grants Project is led by Ruth Bookbinder, University of Leeds

The key researchers on this project are Anne Owen, Lucie Middlemiss, Donal Brown, Mark Davis, Stephen Hall, Ruth Bookbinder, Marie Claire Brisbois, Iain Cairns, Matthew Hannon, and Giulia Mininni.

You can read the full paper here.