How not to measure fuel poverty: England's flawed definition and how to fix it

Extended abstract 3-077-26

England’s Low Income Low Energy Efficiency (LILEE) fuel poverty definition is known to significantly underestimate the condition, which is, in part, due to a controversial energy efficiency-based criterion. According to this approach, homes exceeding a static energy efficiency threshold cannot be fuel poor, regardless of occupant characteristics (e.g., financial capacity) or macroeconomic shocks (e.g., energy price inflation). This results in the underestimation of fuel poverty in low-income homes with relatively low running costs when compared to traditional expenditure-based metrics (i.e., the 10% definition).

LILEE’s preclusion of 'high efficiency' homes from fuel poverty statistics is increasingly counterproductive given modern levels of energy price volatility and risks giving the impression that household energy efficiency is the cardinal cause of and solution to fuel poverty. To substantiate this position, a sensitivity analysis of fuel poverty trajectories is conducted in two diverging scenarios (‘best’- and ‘worst-case’), using a synthetic sample of homes in Nottingham, UK (N=~105,000). The ‘best-case’ scenario assumes widespread energy efficiency upgrades to the housing stock, while the ‘worst-case’ scenario assumed rapid energy price inflation mirroring the 2020–2022 energy crisis. In each instance, the fuel poverty response is measured by a range of existing and novel metrics: 10%, Low Income High Costs (LIHC), LILEE and an amended version of the Scottish budget standards-based approach.

Across tested definitions, LILEE was least responsive to energy price inflation, showing a relatively stable rate of fuel poverty in the worst-case scenario. Moreover, the LILEE definition produced implausibly low rates of fuel poverty in the best-case scenario, falsely suggesting that fuel poverty could be almost eradicated by modest energy efficiency upgrades. We suggest that the Scottish definition of fuel poverty, which explicitly captures changing economic circumstances (notably, the ratio of energy costs to income), responds more appropriately in each scenario. Further, we propose novel fuel poverty depth indicators to capture the changing proximity of homes to a given fuel poverty threshold over time.

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