Our work on fuel and transport poverty in the UK energy transition (FAIR) set out to examine the intersections of fuel poverty (energy poverty) and transport poverty in the UK’s transition to a net-zero society. The aim was to identify:
- who could potentially be vulnerable (the overlapping socio-demographic and spatial factors)
- how it impacts them
- where these people are and
- which policies could help.
Methodology and data collection
We examined the literature on energy poverty and transport poverty, specifically focusing on the socio-demographic groups that are vulnerable to each problem, i.e. face ‘double energy vulnerability’. We interviewed 59 households in all four nations of the UK investigating their lived experiences of fuel poverty and transport poverty. The interviews were carried out in partnership with the Energy Saving Trust and their local networks which were key to finding these hard-to-reach people. To provide quantitative and statistically significant evidence on double energy vulnerability in the UK, we have collected data via a national household survey (approximately 1,400 participants).
We developed a Geographically Weighted Regression (GWR) model to create maps to explore the spatial variation of both fuel and transport poverty patterns across the UK. To examine the implications (distribution, fairness and pros and cons) of different policy options from various policies, Cambridge Econometrics applied its macro-econometric model E3MEOpens in a new tab to model three alternative policy pathways for the UK to meet net-zero by 2050. As part of our wider policy work, we also undertook public focus groups to get the general public’s view on fuel poverty and transport poverty. We held eight online focus groups in early 2022, two in each nation with a total of48 participants. Our final data source was 42 interviews with experts to get their views on fuel poverty and transport poverty and related policy measures.
Key findings from our work on fuel and transport poverty in the UK energy transition
People living in fuel and transport poverty
Energy and transport poverty is caused by a mix of reasons including financial and infrastructural inequalities such as low incomes, poor housing quality, use of expensive technology such as prepayment meters, lack of public transport and ‘forced’ ownership of expensive personal cars.
Many of the people and places identified at greatest risk of energy and transport poverty are the same groups who experience discrimination, disadvantage and exclusion in multiple other facets of social life (including in some cases greater vulnerability morbidity and mortality from COVID-19). This suggests that vulnerability to energy and transport poverty is deep-rooted in the structure of societies, extending beyond only the energy and transport domains.
The effects of fuel and transport poverty on peoples’ lives
Lack of sufficient energy and transport services is detrimental to quality of life, causing stress and missed opportunities like cutting out certain foods or leisure trips. Affordable energy and transport services that are available to all, would reduce the need for people to cut back on essentials and improve peoples’ quality of life.
The lived experience of someone in energy and transport poverty is a daily stress and cause of worry over choosing between different energy and transport services: e.g. when to use the heating or electricity at home, and how to travel to work, school, the shops or medical appointments.
Geographic modelling to map the distribution of double energy vulnerability
The availability of data on energy and transport poverty statistics vary significantly across the four devolved nations with inconsistent definitions and limited disaggregated data. This lack of harmonised data on energy and transport is a severe impediment in understanding socio-spatial variants of energy and transport poverty.
We developed an original method for analysing energy and transport poverty in the UK and constructed two unique metrics:
- The energy poverty metric combines data on heating burdens, energy efficiency and social vulnerability
- The transport poverty metric is constructed on the basis of access and social vulnerability
Energy and transport equations:
Energy Poverty Index
Central Heating [0.25] + Energy Cost [0.25] + Energy Performance Certificate [0.25]+ Income [0.25]
Transport Poverty Index
Accessibility [0.33] + Car Ownership [0.33] + Income [0.33]
When we map both energy and transport poverty the results show a clear north-south and urban-rural divide. In the energy poverty domain, one of the surprising findings was the high degree of energy poverty in peri-urban areas, possibly due to higher energy costs and lower Energy Performance Certificate (EPC) values. The transport poverty showed high values in inner-city areas outside of London, possibly as a result of poor accessibility and car ownership scores. The greatest vulnerability to double energy poverty can be found in isolated rural communities that have a high proportion of residents who are disadvantaged in socio-economic and demographic terms.
What policies could help to reduce fuel and transport poverty
We have used a macroeconomic model to assess three policy scenarios, based on GDP and employment outcomes across the whole of the UK economy.
- A Net Zero Strategy scenario (NZS): replicating policies from the UK government’s Net Zero Strategy, published in autumn 2021, with no predefined emissions outcome.
- A market-based instruments scenario (MBI): UK net-zero achieved through a carbon tax only
- A regulation scenario (Regulation): UK net-zero achieved through a range of regulatory policies.
The results demonstrate two important high-level findings:
- Implementation of climate policy generates positive outcomes for the environment, economy and society as a whole, creating a win-win situation in which emissions are reduced, while at the same time the economy grows and new employment opportunities are created. All the modelled net-zero policy pathways lead to better outcomes for GDP and employment compared to the business-as-usual scenario.
- There are significant differences in the distributional impact on real disposable income between the The Regulation scenario produces the ‘fairest’ outcome (lower-income groups benefit more than higher-income groups) and the MBI scenario leads to increased real income for all if 100% of the tax revenue raised from carbon pricing is recycled, but if no revenues are recycled it is the worst outcome across all the scenarios. This demonstrates that it is important that carbon revenues are put back into the economy to avoid strongly negative outcomes, and that the way the Government chooses to do this has an impact on distributional outcomes.
Focus group ranking of policy options
The focus group participants tended to mistrust landlords and large energy firms as intermediaries intended to deliver policy mechanisms: they are not perceived as neutral actors, but self-interested ones and part of the problem. However, when asked to rank energy poverty policy options, focus group participants gave first priority to requiring landlords to improve the energy efficiency of their homes. They gave second priority to increasing the level of support given under the Warm Homes Discount scheme; and they gave third priority to ensuring that new homes are much more energy efficient.
In terms of transport poverty, focus group participants gave high priority to making bus and train fares and ticketing simpler and cheaper; restoring bus services post COVID-19 was a second priority; followed by resourcing local authorities so that they can install electric vehicle charging.
Banner photo credit: Rex Pickar on Unsplash