specific point in time is recommended, effectively converting them into an absolute measure. These are referred to as anchored AROP poverty lines.

**In the case of Bulgaria, we construct the low-income-high-cost measure drawing from both observed expenditure and income information gathered as part of the HBS.** We estimate overall household energy expenditure and subtract this amount from the net total household income reported in the household budget survey (HBS).<sup>30</sup> We then compare the remaining household income (the net disposable household income after subtracting energy expenditures) to the official at-risk-of-poverty line (from the EUSILC survey). Income poverty lines and rates are usually estimated using the EU-SILC survey, but this survey does not collect expenditure information.  Therefore, we rely on use income and expenditures from the HBS and the official poverty line from the SILC.  Note that the at-risk-ofpoverty line differs from the official one reported by Eurostat, which relies on data from EU-SILC.<sup>31</sup>

# 2.4. Consensual Approaches

**The set of indicators often denoted as consensual approaches rely on self-reported information by households.** We next explore consensual approaches toward measuring energy poverty. Thema and Vondung (2020) define consensual measures as those that rely on self-reported assessments of housing conditions or the inability to cover basic energy needs because of a lack of access or affordability. Examples of such metrics are the share of households that cannot keep their home adequately warm/cool or those reporting leakages.

**Consensual approaches are direct and personal measures but are subjective.** Consensual approaches are easy to measure and might reflect different energy needs and demands. They also intrinsically capture some of energy poverty's negative social and psychological effects. However, they also suffer from important flaws. First, they are subjective measures, and it might be difficult to compare them across different households, regions, or countries. Next, they might also be influenced by household expectations, preferences, and social norms. These factors might significantly influence the reliability and comparability of consensual approaches.

# 2.5. Outcome-Based Approaches

**Another possibility for measuring energy poverty is to focus on the outcomes that occur because of energy poverty (Thema and Vondung, 2020).** Energy poverty leads to unfavorable health, socioeconomic, and environmental impacts (Halkos and Gkampoura, 2021), and measuring these impacts can then again shed light on the severity of energy poverty experienced by the population of interest. Examples of such measures are the number of cold- or heat-related mortalities or arrears on energy/utility bills.

**Outcome-based approaches might be easy to measure but, at the same time, could be confounded by other factors, such as lack of appropriate public infrastructure or income.** While it might be easy, conceptually speaking, to measure the number of cold-related deaths, these measures might be influenced by other factors that we might not be able to observe, such as the development of the public infrastructure or the available income at the household level.

# 2.6. Multidimensional Measures

**<mark>Given the multidimensional nature of energy poverty, several scholars propose multidimensional indicators to measure energy poverty.</mark>** <mark>Given the multidimensional nature of energy poverty and the</mark>

> 30 As shown later, the AROP estimate based on the HBS is significantly below the estimate from the EU-SILC. 31 The at-risk of poverty rate constructed for this measure is equal to 60 percent of the median value of the equivalized household income after social transfers in the HBS.

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