Evaluating the Impact of Energy Poverty in a Multidimensional Setting

Delugas E., Brau R., 2021 – The Energy Journal

In the European Union, there are a significant number of individuals struggling to afford essential goods and services, particularly those related to energy usage. The latest data from the European Observatory on Energy Poverty (EPAH) reveals that, in 2021, approximately 34 million citizens faced inadequate heating in their homes or lived in a state of energy poverty. Energy poverty traditionally entails a situation where a significant portion of one’s income is allocated to heating expenses, resulting in inefficient and unhealthy housing conditions. This condition can severely affect health, social inclusion, and family well-being.

Traditionally, energy poverty has been viewed as a component of income-related poverty. In recent times, there has been a growing consensus regarding the need to address this issue independently and analyse it in its own right. Recent advancements in economic analysis have introduced the use of multidimensional indicators to evaluate energy poverty, encompassing subjective measures of well-being. Objective and subjective measures have been employed to gauge the extent of energy deprivation.

In their recent study titled “Evaluating the Impact of Energy Poverty in a Multidimensional Setting,” published in The Energy Journal, the authors Erica Delugas and Rinaldo Brau aim to provide a comprehensive and detailed understanding of the challenges linked to energy poverty and its consequences for affected individuals.

The authors devise the Multidimensional Energy Poverty Index (MEPI) to examine energy poverty in Italy and assess its impact on individual well-being. Drawing upon the methodology employed to construct the UNDP Multidimensional Poverty Index by Alkire and Foster (2011), the authors adapted a set of objective and subjective indicators available in the European Survey on Income and Living Conditions (EU-SILC, 2014) for use in Italy. The MEPI offers insights at the individual or household level, considering various facets of energy poverty and providing a more comprehensive grasp of the experiences of energy deprivation. The methodology enables the analysis of both the frequency and intensity of household energy poverty, particularly suitable for scenarios where energy deprivations are represented categorically or ordinally.

The MEPI is constructed based on the following survey questions and records:

  • Has the household been in arrears due to financial difficulties with utility bills for the main dwelling?
  • Has the dwelling any problems with the dampness on walls, floors, ceilings or foundations?
  • Has the dwelling any problems with damaged roofs, ceilings, doors, windows or floors?   
  • Absence of any heating expenditure.                
  • Can your household afford to keep its home adequately warm?

First, The MEPI is calculated using different combinations and thresholds. Through a sensitivity analysis, the authors test the MEPI’s responsiveness to individual components used in its construction and various energy poverty thresholds by comparing incidence and intensity.

Secondly, the authors undertake a comparative analysis between the incidence of energy poverty calculated using MEPI and that of “affordability” indicators, which assess an individual’s ability to pay for energy expenses relative to their income. Individuals identified as energy-poor solely through “affordability” indicators generally face income-related poverty or high energy costs. Conversely, the multidimensional measure encompasses all individuals residing in inefficient housing, including those who are unable to meet even the minimum threshold of energy expenditure or declare to feel unable to keep their home adequately warm. As a result, these individuals would not be identified through “affordability” measures.

The study is concluded by conducting an econometric exercise to establish the causal relationship between energy poverty and life satisfaction. Taking into account subjective indicators of energy poverty makes this index endogenous in its association with subjective well-being. Hence, the authors propose estimating the relationship at the individual level using an ordered bivariate probit model, given the ordinal nature of the MEPI and the subjective well-being variable, along with exclusion restrictions. The results validate the theoretical predictions, revealing a significant negative correlation between subjective well-being and the intensity of energy poverty. Moreover, the findings point to the superior predictive capacity of multidimensional energy poverty indicators in predicting the levels of subjective well-being, vis-à-vis traditional “affordability” measures.

Identifying those citizens living in energy poverty has become paramount in light of the remarkable surge in energy prices experienced in 2022 and the proposed European directive on energy performance in buildings. The directive’s objective is to achieve zero emissions by 2050 while also reducing greenhouse gas emissions and energy consumption by 2030. In this context, developing an energy policy that supports individuals during this transition is essential. Consequently, identifying those people facing energy poverty becomes a priority, as they will be most deeply affected by this structural change.

Go to the published article