# 4. Conclusion and Recommendations

**In this paper, we review existing energy poverty indicators in the academic literature, white papers, and policy reviews and then explore the employability of these indicators in Bulgaria's case.** Energy poverty is a complex concept that lacks a common definition and is multidimensional by nature. It involves multisectoral and multilevel approaches. Based on these factors, measuring energy poverty is complex, and there are many different approaches to its measurement. In the work at hand, we review existing approaches and then explore their applicability to the concept of Bulgaria based on data availability and quality.

**We show that Bulgaria's energy poverty incidence rate fluctuates significantly by definition.** The 10 percent measure deviates significantly from the other expenditure-based indicators, resulting in an approximately five times larger incidence rate. This could be related to the measurement issues and the criticism raised in the literature about this indicator. The rest of the monetary measures fluctuate between 9 and 13 percent. The incidence rates of consensual measures are slightly larger, varying between 11 and 47 percent.

**Our evidence demonstrates that the monetary poor and energy poor only partly overlap.**<sup>44</sup> By construction, the monetary poor are also energy poor in the low-income-high-cost measure. If they report energy expenditure shares above the national median, this is not necessarily true for the rest of the measures. We find that, depending on the measure, only 1 to 12 percent of the population is affected by monetary and energy poverty. This has important implications for the targeting of policy interventions. As the monetary and energy poor only overlap partly, traditional social protection strategies might not target those who are energy poor, and additional policy instruments should be implemented when governments try to tackle energy poverty.

**In addition, we show that different subsets of the population face different dimensions of energy poverty.** This means that the government might want to include a different population set for interventions that target energy poverty in the short and long-run, for example. Those needing renovation programs and interventions that increase their energy efficiency might differ from those who cannot afford their energy bills.

**Based on our literature review, we recommend moving away from single-indicator energy poverty metrics toward multiple-indicator approaches, which are consistent with previous studies.** We show that the incidence rate of energy poverty fluctuates significantly depending on the underlying methodology. Based on this pattern of results, we recommend moving away from single-indicator energy poverty metrics towards multiple-indicator approaches. This recommendation is in line with recommendations made previously in the literature (see, for example, Herrero (2017) and SiksnelyteButkiene (2021)). It is also consistent with the latest EC recommendation developed by the Energy Poverty Advisory Hub, which emphasizes the importance of utilizing a mixed indicators approach that covers all contributing factors and accurately identifies vulnerable populations, given the complex nature of energy poverty<sup>45</sup> . One example would be to follow previous pilots like the Belgium Energy Observatory or the French National Energy Poverty Observatory (ONPE), which both track more than one indicator. The operationalization of energy poverty measures should involve a cooperative approach between several ministries, academics, and local communities. In addition, big data sources

> 44 Importantly, results differ from some of the results detailed in Rude and Robayo-Abril (2024) because we use income from the EU-SILC after a statistical matching procedure in this case, while we rely on income measures reported in the HBS in the work at hand.

> 45 Source: Energy Poverty Advisory Hub (2023).

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