1. Introduction
Energy poverty can be observed in many regions of the world. Due to its multidimensional nature, it is not just the domain of poor or developing countries. It may seem that in developed, industrialised, and highly electrified European countries, that energy poverty problems are not present. In these countries, the degree of access to electricity, as defined by the World Bank [
1], is 100%. However, it is estimated that more than 50 million households in the European Union experience fuel poverty [
2]. It is a problem that affects all European countries to varying degrees. It is important to remember that energy poverty is defined differently in developing countries (i.e., as access to energy sources other than solid fuels including lack of access to modern energy sources) [
3,
4], and in developed countries (i.e., as economic affordability, referring to high energy costs) [
5,
6]. In general terms, therefore, energy poverty means that households experience inadequate levels of basic energy services, relating to the provision of heating, cooling, lighting, and energy to run domestic appliances. This situation is related to economic factors that influence the emergence of fuel poverty. In theory, the phenomenon of lack of access to energy should not occur, and it should not be a problem for European countries. A significant problem in developed countries is the amount of money spent on energy, combined with low household income. In addition to income, inefficient buildings and appliances and the specific energy needs of energy consumers affect energy costs. Access to basic energy services, whether for heating, lighting, or appliances, contributes to ensuring an adequate standard of living and health for citizens, and the need for this access should guide different policies and the search for solutions to reduce energy poverty. When identifying energy poverty, we need to ask ourselves whether and how it can be avoided, and whether there are differences in the extent of its occurrence for different social groups in countries that implement sustainable economic and climate policies.
With an understanding of how to measure energy poverty, one can look for correlations and relationships, not only between indicators but also between countries, to draw conclusions and make recommendations to eliminate the problem. It is possible to show how the situation has changed over the years and what the causes are. It is necessary to indicate what actions in the field of sustainable development eliminate energy poverty because it affects the functioning of entire economies and is directly related to negative consequences in terms of health and wellbeing (e.g., cardiovascular diseases, respiratory diseases, and/or stress). It can also have an indirect impact on many areas of national economic and climate policy, as well as those related to health, the environment, and economic factors. It is therefore directly linked to the principles of balanced and sustainable development. In this respect, correlations, dependencies, and linkages should be sought, indicating the impact of actions which are aimed at addressing these negative phenomena.
This study aims to examine the correlations that may exist between the implementation of sustainable development principles, based on environmental and macroeconomic indicators, and energy poverty. The analysis seeks to broaden knowledge, identify determinants, and pinpoint causes of energy poverty in Europe. We also consider the possibility of eliminating energy poverty based on a comparison of energy poverty indicators and the implementation of environmental governance in selected European countries. It is of value to consider the reasons for energy poverty in developed countries versus highly industrialised ones: assessing awareness of climate risks, promoting sustainable development and renewable energy, and seeking to identify the causes of energy poverty, as well as potential solutions for the elimination of this phenomenon over time.
The discussion is guided by certain research questions that were chosen for their relevance to the selected European countries, including: (1) Are high energy poverty rates related to household income, expenditure on electricity, heating/cooling, or lighting of households? (2) What relationships exist between the magnitude of energy poverty indicators and sustainable development, in terms of environmental governance in the countries studied (using an indicator for renewable energy sources)? (3) Are there differences in the situation between European countries, and, if so, why?
2. Materials and Methods
The study approach was based on different research methodologies. Based on scientific sources [
7], as well as related documents and reports [
8], a systematic and critical analysis of the literature was performed, with the objective of synthesizing guidelines and defining phenomena and processes. The literature analysis provided an understanding of the social and economic phenomena related to energy poverty. On this basis, available knowledge was organised and application of selected indicators allowed for comparative analysis, drawing of inferences, and the formulation of recommendations. The contribution to the development of science is the connection, hitherto unexplored, between indicators of energy poverty and sustainable environmental policies, enabling identification of relationships in the European countries studied. This type of analysis makes it possible to suggest ways of implementing pro-environmental climate policy which can mitigate energy poverty and take into account potential future changes associated with new sources of energy supply in European countries. The originality and added value of the research are that it goes beyond a single country and examines not just countries of the European Union, which provides a more comprehensive analysis. Various countries were considered in terms of geographic location, including those where energy poverty does not imply that there no possibility of heating rooms, for example, where cooling rooms in the summer is instead problematic. In addition, the economic and political circumstances of selected countries was considered. The article provides a synthesis of evidence and recommendations for further action regarding the implementation of sustainable climate policy and the simultaneous reduction of the scope and level of energy poverty. This was based on statistical data and the use of selected indicators on energy poverty and environmental governance. Quantitative and qualitative analyses were carried out using descriptive and mathematical statistics [
9,
10]. The choice of measurement methods for energy poverty depends on many factors, such as the level of measurement (e.g., national, regional, or European), as well as the availability or comparability of data. In order to investigate the research questions, statistical data from public statistical databases was used.
The research methodology to establish the empirical database involved desktop research that comprised a document and database review of available statistics from international sources. The first component of the methodology was a review of academic articles, reports, and legal acts. The second element was statistical analysis, based on the collection of quantitative data. The data for the survey were taken from the Eurostat database, the World Bank database, and the World Health Organization database. The time frame for the research covered 2011–2019 for 35 European economies, 27 of which were members of the European Union; the remainder included Albania, Iceland, Kosovo, Norway, the United Kingdom, Montenegro, North Macedonia, Switzerland, Serbia, and the Ukraine. Such an approach to the research problem, covering up to 37 European countries, allowed for a broader spectrum of research on energy poverty, covering almost the entire population of Europe.
Using available public statistics, a comparative analysis of the countries studied in the period under review was performed in terms of selected characteristics affecting fuel poverty. The following characteristics were compared across countries and time: percentage of households using clean fuel for cooking; inability to keep the home adequately warm; average electricity prices per household; electricity, gas, and other fuel expenditure of households; arrears on utility bills; and the share of renewable energy in final gross energy consumption.
In order to answer the research questions posed, regression and correlation analyses were performed. At the first stage, using correlograms, it was verified if there was no curvilinear relationship between the examined variables. Points of researched features were concentrated along straight lines, therefore the assumption of linearity of relationships was made. Ordinary linear regression is the most frequently used technique for estimating energy poverty factors, and therefore was used in this paper. Not all explanatory variables of energy poverty were available or accurately measured by the available statistical methods. Therefore, several variables were selected. For each of the analysed countries, the impacts of selected independent variables were examined, including: GDP per capita (i.e., the economic dimension of sustainable development); share of renewable energy in gross final energy consumption (i.e., the environmental dimension of sustainable development); electricity, gas, and other fuel expenditure of households; and the energy poverty rate, represented by the inability to keep a home adequately warm. In order to assess the correlations between the dependent variables and the independent variables, the Pearson correlation was used.
where:
cov (x, y)—covariance between the x and y features
Sx, Sy—standard deviations of x and y features.
The correlations obtained between variables included:
- −
GDP per capita and household spending on electricity, gas, and other fuels;
- −
GDP per capita and the share of renewable energy in gross energy consumption;
- −
Household expenditure on electricity, gas, and other fuels and the share of renewable energy in gross energy consumption.
Figure 1 presents framework of correlation between variables.
To verify the relationship between the studied variables, statistical hypotheses and alternative hypotheses were posed to determine if the null hypotheses could be rejected at the alpha level of significance (alpha = 0.05). The null hypothesis tested was:
Hypothesis 0 (H0). Pearson’s correlation coefficient = 0.
Equivalent to no relationship between the analysed variables, against the alternative hypothesis:
Hypothesis 1 (H1).. Pearson’s correlation coefficient ≠ 0.
Which states that there is a relationship between the variables under study.
Then their statistical significance was confirmed using the Student’s t-test at the significance level = 0.05.
Microsoft Excel and Statistica 13.1 (TIBCO Software Inc., Palo Alto, CA, USA) were used to prepare basic statistics and to conduct the correlational analyses.
4. Results
Analysing the data on access to electricity, in all European countries between 2011 and 2019, access was 100%. However, when looking at the data in more detail, it is important to note that the share of people with access to clean cooking fuels is significantly lower in some countries. Having access to electricity means that a household can use it for basic purposes, such as lighting. However, it may not be able to pay for electricity for more energy-intensive purposes, such as cooking. In this situation, the household uses cheaper fuel, especially wood or coal, to cook. In most European countries, access to clean fuels for cooking is 100%, while in Albania, Bosnia and Herzegovina, Montenegro, and the Ukraine it is much less—46% to 95% of households use them. It should also be noted that access to clean energy is much lower in rural areas in these countries (
Figure 4).
The problem of maintaining an adequate (comfortable) temperature in the home significantly affects the level of energy poverty. When analysing the problem of inability to maintain adequate heat at home, it should be noted that, firstly, this problem has been gradually decreasing between 2011 and 2019, and secondly, very large differences between the studied countries are evident, especially between the countries of the so-called ‘old EU’, the ‘new EU’, and non-associated countries. In 2019, the highest percentages of people in the total population who were in a state of enforced inability to adequately heat their homes were in Kosovo (40.2%), Albania (36.8%), North Macedonia (33.1%), Bulgaria (30.1%), and Lithuania (26.7%). The least affected countries were Switzerland (0.3% of the population), Norway (1%), and Austria (1.8%). The EU-27 average was 6.9%.
Figure 5 presents findings for the ‘inability to stay warm enough at home’ indicator in European countries for 2011, 2015, and 2019.
It is also interesting to look at how this has changed over time across states.
Table 4 presents the changes in the percentage of people having trouble maintaining an adequate temperature at home in 2019 compared to 2011.
Analysing the changes in the problem of maintaining an adequate home temperature, differences are observed between the so-called old EU countries, the new EU countries, and non-EU countries. In 2019 compared to 2011, the percentage of people with this problem decreased more in the so-called new EU countries compared to the so-called old EU countries. This could mean that the common energy policy contributed to member countries gaining more.
An important factor affecting the level of energy poverty is electricity prices. Their levels in 2019 are presented in
Table 5.
An analysis of the data presented in
Table 6 provided some interesting findings. In 2019, the lowest electricity prices were in countries characterized by the highest percentage of people affected by the problem of not being able to maintain adequate heat at home, as well as having difficulty accessing clean energy for cooking. Therefore, to better illustrate the factors influencing the problem of energy poverty, in addition to the price, attention was also paid to the share of household expenditure on electricity, gas, and other fuels (
Figure 6). A household is said to be energy-poor if it spends more than 10% of its income on fuel to keep warm. Therefore, the share of household expenditure spent on energy is another important indicator that has been highlighted in the study of energy poverty.
The highest share of expenditure on electricity, gas, and other fuels in total consumption expenditure is in Slovakia (8.5%), Poland (7.6%), and Serbia (6.9%). The least burdened in this respect are Malta (2%), Iceland (2%), and Luxembourg (2.4%). It should also be noted that, unfortunately, there are no data available on this issue for countries such as Kosovo, Albania, and Montenegro. However, it can be assumed that since there are problems with heating the home or access to clean energy for cooking, spending on these categories of goods can be quite a burden on household budgets in these countries.
High energy costs and/or low household incomes often force people in fuel poverty to default on their utility bills. It is therefore important to indicate the percentage of people in the total population who are in arrears with utility bills.
In 2019, Kosovo, North Macedonia, and Montenegro—the countries with the highest percentage of people affected by the problem of keeping their homes warm—also had the highest percentage of people in arrears with utility payments. In contrast, in countries such as the Netherlands, the Czech Republic, Germany, and Sweden, paying utility bills is a problem for only a small percentage of the total population.
An important indicator, both from the perspective of energy poverty and sustainable development, is the share of renewable energy in gross energy consumption. This indicator measures the extent to which renewable energy has replaced fossil and/or nuclear fuels and therefore contributes to the decarbonisation of economies. The share of renewable energy in the final gross energy consumption is presented in
Figure 7 and in
Table 7.
The highest share of renewable energy in gross final energy consumption occurred in Scandinavian countries: Iceland (78% in 2019), Norway (74%), and Sweden (56%). By contrast, the lowest use of this energy was found in countries such as Luxembourg (7%), Malta (8%), and the The Netherlands (8%).
It is of interest that in Albania and Kosovo, countries with a quite high percentage of households that had problems maintaining an adequate home temperature, the share of renewable energy use (36.6% and 25.6%, respectively) was higher than the EU27 average (19.7%).
Analysing the changes between 2011 and 2019, in most of the countries belonging to the so-called new EU, the increase in the share of renewable energy in total energy has been slower than in most of the countries of the so-called old EU. This may be affected by the different goals of the economic policies pursued by these countries. Moreover, households’ goals may also be different and not necessarily related to investment in this area.
To answer in more detail the research questions posed in the paper, for most of the analysed countries an analysis of relationships was conducted using the Statistica program, considering:
The level of inability to adequately heat the home (which is one of the indicators of energy poverty) and the level of GDP per capita (RQ1);
The correlation between the level of inability to heat the home and the household expenditure on electricity, gas, and other fuels (RQ1);
The correlation between household expenditure on electricity, gas, and other fuel and the level of GDP (QR1);
The correlation between GDP per capita and the share of renewable energy in gross energy consumption (RQ2);
The correlation between the inability to heat the home and the share of renewable energy in gross energy consumption (which is one of the indicators of sustainable development, in terms of environmental governance) (RQ2);
The correlation between household expenditure on electricity, gas, and other fuels and the share of renewable energy in gross energy consumption (RQ2).
Unfortunately, due to the absence or incompleteness of data for the countries most vulnerable to energy poverty (Albania, Kosovo, Montenegro, and North Macedonia), a dependency analysis could not be fully conducted in these countries. The results of the analyses are presented in
Table 8.
(RQ1) The results of the analysis carried out show that, in most of the countries studied, there was a statistically significant, strong negative correlation between the level of GDP per capita and the poverty rate (represented by the level of inability to maintain adequate heat at home). The higher the income level of the population, the smaller this problem became. Weak correlations in this regard occurred in Finland, France, Italy, The Netherlands, Spain, the UK, and Estonia. By contrast, no relationship between these characteristics was found in Denmark or Norway. In the country most exposed to energy poverty, North Macedonia, there was no such relationship either, which is probably related to the low (but growing) level of GDP per capita. This still translates into a low income for the population and consequent difficulties in the payment of basic charges (leading to arrears on utility bills), as shown in
Table 7. North Macedonia is the country with one of the highest percentages of people with this type of problem.
(RQ1) In most of the countries analysed, there was a statistically significant positive correlation between the share of household spending on electricity, gas, and other fuels and the level of inability to heat the home. The greater the share of the budget accounted for by energy expenditure, the greater the problem of maintaining an adequate temperature in the place of residence. Weak correlations between these characteristics were found in Greece, France, Sweden, Estonia, Latvia, and Romania. No relationship was found in Denmark, the Netherlands, Spain, and Sweden.
(RQ1) There was a statistically significant negative relationship between the increase in income, represented by GDP per capita, and household spending on electricity, gas, and other fuels in most of the analysed countries. The share of these expenditures in total consumer spending decreased with increasing wealth. The weakest relationship between these characteristics was found in Greece, France, Italy, Sweden, Norway, Cyprus, North Macedonia, and Serbia.
(RQ2) A statistically significant positive relationship was observed in most countries between GDP per capita and the share of renewable energy in gross energy consumption, one of the indicators of sustainable development, in terms of environmental governance,. This means that as the wealth of a country increased, renewable energy was used more and more. A slight dependence in this respect was observed in Austria, Finland, Portugal, Cyprus, Croatia, Poland, and Romania. By contrast, almost no dependence was shown in Greece, Italy, Slovenia, Northern Macedonia, and Serbia.
(RQ2) The results of the analysis show that, in most of the studied countries, there was a statistically significant positive correlation between the increase in GDP per capita and the use of renewable energy sources. Weak and moderate correlations were found for Austria, Finland, Portugal, Cyprus, Croatia, Poland, and Romania. No correlation was found in Greece, or North Macedonia, one of the countries most exposed to energy poverty; it showed almost no correlation.
(RQ2) In about half of the countries analysed, there was also a somewhat negative correlation between the degree of renewable energy use and the inability to maintain a comfortable temperature in the home. The more the use of green energy increased, the more the degree of energy poverty, measured as the inability to heat the home, decreased. Such a correlation was not observed in Greece, Norway, or Slovenia.
(QR2) Analysis of the correlation between household expenditure on electricity, gas, and other fuels, and the share of renewable energy in gross energy consumption revealed a quite strong negative relationship between these variables in half of the countries analysed. By contrast, a moderate relationship was found in Finland, Italy, Portugal, Spain, Sweden, Cyprus, Poland, and Slovakia. No correlation was found in Greece, France, Norway, Romania, or Slovenia. On the other hand, in Serbia and North Macedonia, there was a positive correlation in this regard.
5. Discussion and Limitations
Based on research, as well as analysis of the literature, energy poverty is closely related to income poverty. Fuel poverty affects quality of life, while a lack of access to modern energy sources contributes to an increase in the consumption of conventional energy, and thus to carbon dioxide emissions and greater environmental pollution. Fuel poverty is exacerbated by job loss and falling wages. This is particularly evident among people and households with the lowest and average incomes. The need to use heating appliances, and the increasing number of domestic appliances that use energy to power the home, increase bills, although an increasing number of these appliances, if they are of the new generation of designs, have a lower energy demand. The size and surface area of a dwelling and its energy efficiency have important effects on fuel poverty.
The consequences of fuel poverty are directly related to health. However, they are also linked to other areas, including social exclusion, poor well-being, and lower chances for educational achievement [
63]. Solving the problem of energy poverty, or at least reducing it, would contribute, to a large extent, to reduced medical expenses for citizens, a better quality of life, and/or increased economic activity [
30]. The size and number of energy-excluded households, or those classified as energy-poor, have many causes and are influenced by many, varied factors. The inability to maintain adequate levels of heat results in health problems for families living in poorly heated flats or houses. In addition, low air temperatures also negatively affect housing conditions, which only get worse from season to season. Situations related to the lack of funds for payments create a kind of loop, constantly worsening the situation of households. In general, the socioeconomic consequences of energy poverty relate to economic development in both the short and long term, reducing productivity in the agricultural sector, preventing socioeconomic progress, or negatively affecting the education of children and young people [
36]. Lack of funds for energy charges, or the lack of funds for necessary repairs caused by energy poverty—this situation, unfortunately, often loops from year to year—causes more problems. Energy poverty can be influenced by household characteristics, socioeconomic factors, and environmental factors (including climatic conditions and climate change). This means that a holistic approach is required to seek solutions to minimise energy poverty, considering all the characteristics and factors identified. Indicators of the statistical incidence of energy poverty in individual member states do not reflect the regulatory and policy commitments of national energy and climate plans [
32]. This is also apparent in the results of the studies carried out.
Poverty can be understood both in the microeconomic context (e.g., households), as well as in the macroeconomic context, relating to the whole economy and its implications concerning, inter alia, the use of renewable energy, the construction of support systems for modern solutions, and, consequently, environmental protection and the achievement of sustainable development goals.
The limitation of the study is that it adopts a very general approach to the problem. Many cases of spatial inequalities within national economies have already been described in the literature and the study was limited to one selected indicator. The article does not deal with many aspects that will be subject to further scientific exploration. The research was limited to environmental aspects of sustainable development and aspects related to macroeconomic factors. Social and economic aspects were not considered, as well as trends, or the impact of factors such as the use of technology in households to meet needs, such as those for education, food, or even medicine. These aspects have become particularly important during the COVID-19 pandemic. A further limitation of the study is omission of the energy efficiency of buildings, which can have a very high impact on heat loss and contribute to fuel poverty.
The results of the research are interesting. There is a clear correlation indicating that relatively poorer countries with higher levels of energy poverty are closing the gap faster over the years.