energy carriers Energy efficiency Energy efficiency rating of built fabric and equipment Poor indoor air quality – humidity and mould Deterioration of built fabric and worsened energy performance Needs Household type Additional energy needs Worsened physical and mental health Practices Lack of policy recognition Rationing of energy services Low take up of support schemes Unjust pricing and taxation schemes These general approaches translate into three main methods of measurement: Expenditure approach – where examinations of the energy costs faced by households against absolute or relative thresholds provide a proxy for estimating the extent of domestic energy deprivation; Consensual approach – based on self-reported assessments of indoor housing conditions, and the ability to attain certain basic necessities relative to the society in which a household resides; Direct measurement – where the level of energy services (such as heating) achieved in the home is compared to a set standard. The subsequent section is arranged thematically according to the main approaches that can be used to measure energy poverty: expenditure, consensual, and direct measurement. For each approach the key features and requirements are outlined, followed by a discussion of how the approach can be applied at the EU level, ending with a presentation of key studies. Expenditure approach Key features, requirements and approaches
Table 6 Summary of available expenditure data Survey Household Budget Survey Relevant energy poverty variables Household expenditure on energy (actual) – this is often disaggregated by energy source or service. Household income Energy vulnerability factor(s) addressed Affordability Access Coverage (non-EU in brackets) EU28 (in addition to Macedonia, Turkey, Norway and Switzerland) Cross-sectional or longitudinal Cross-sectional Sample size HBS are not harmonised across EU. Sampling varies by country, with no minimum standards. In the 2005 HBS round, the achieved sample sizes ranged from 1,570 (NL) to 52,217 (DE). See Eurostat (2009) for details. As detailed in Table 6, the only energy vulnerability factors that the HBS can be used to interrogate are affordability, by calculating if there is a high ratio between the cost of energy and household incomes, and access, given that energy expenditure is disaggregated by energy carrier within the microdata – although it offers no insight into whether the energy carriers used in the home are appropriate to meet household needs. Within some national HBS micro datasets, the energy affordability ratio (otherwise termed the energy burden) can be examined at the regional (NUTS 2) level, thus allowing for spatial considerations to be incorporated within analyses. Available indicators 1. Energy burden
Energy vulnerability factor(s) addressed Affordability Energy efficiency (indirectly) Needs (indirectly) Energy efficiency Needs Affordability Energy efficiency (indirectly) Needs (indirectly) Affordability Energy efficiency (indirectly) Energy efficiency (indirectly) Needs Affordability Energy efficiency (indirectly) Affordability Needs Coverage (non-EU in brackets) EU27 since 2007, and EU28 since 2010 (in addition to IS, NO, CH and TR) EU28 (in addition to IS, NO and CH) EU28 EU28 EU28 (in addition to IS, XK, MK, ME, RS and TR) AT, BE, BG, CZ, Estonia, FR, DE, HU, IT, LT, NL, PL, RO (in addition to AU, GE, JP, NO, RU) or longitudinal Both types are available Cross-sectional Cross-sectional Longitudinal Sample size Minimum pan-EU sample of 121,000 households for and 90,750 households Minimum pan-EU sample of 121,000 households Standard sample of 1,000 individuals per country. Smaller countries (e.g. LU) have a smaller Standard sample of 1,000 individuals per country. Smaller countries (e.g. LU) have a smaller Minimum of 1,000 individuals, except in the 8 largest countries, which have samples of between Average of 9,000 respondents per country
longitudinal sample, whilst larger countries (e.g. DE) have a larger sample of around 6,000 people. sample, whilst larger countries (e.g. DE) have a larger sample of around 6,000 people. 1,500 to 3,000 people.