A representative survey of the Lithuanian population was conducted to collect empirical data on household expenditures related to electricity, natural gas, and heating in order to evaluate the level of energy inequality in Lithuania. This method aids in the assessment of the correlation between energy costs and household affordability, thereby elucidating the financial burden that energy expenses impose on households. The study identifies disparities in energy access, consumption, and costs across various demographic and socio-economic segments of the population by analyzing the data. The insights acquired provide a more profound comprehension of the economic burden that households encounter.
Household electricity expenses. In the questionnaire, respondents were asked what their monthly household electricity expenses are, on average. Out of 1,000 consumers surveyed, 993 provided their responses, while 7 did not specify their spending. The responses of the 993 respondents were distributed as shown in Table 1.
|
Number of respon-dence
|
Share of respon-dence %
|
Mid-point (Eur)
|
Total
|
% from total
|
Cumulative
|
Cumulative (normalized)
|
Up to 14 Eur
|
74
|
0,075
|
7
|
518
|
1,59
|
0,0745
|
0,0159
|
15-20 Eur
|
193
|
0,1944
|
17,5
|
3377,5
|
10,36
|
0,2689
|
0,1195
|
21-30 Eur
|
216
|
0,2175
|
25,5
|
5508
|
16,90
|
0,4864
|
0,2885
|
31-50 Eur
|
269
|
0,2709
|
40,5
|
10894,5
|
33,43
|
0,7573
|
0,6228
|
51 and more Eur
|
241
|
0,2427
|
51
|
12291
|
37,72
|
1
|
1
|
Table 1. Distribution of monthly household electricity expenses among respondents
Having performed cumulative calculations as indicated above, this enables us to attempt to calculate the Gini coefficient and at least theoretically try to assess energy inequalities on a scale measured by household electricity expenses. The Gini coefficient is derived from the Lorenz curve, which plots income distribution against the cumulative percentage of the population. It is a statistical measure used to quantify the level of inequality within a population, ranging from 0 to 1. A Gini coefficient of 0 represents perfect equality, while a coefficient of 1 indicates perfect inequality (higher values signify greater inequality). Thus, the Figure 1 below graphically represents the level of energy inequality as assessed by cumulative household electricity expenses and their distribution among respondents.
In order to calculate the Gini coefficient, it is necessary to calculate the definitive integral (0; 1) of the function Y = 0.7685*X^2 + 0.2362*X - 0.0025
The obtained results and calculated Gini coefficient of 12.8233% for household electricity expenses indicates a relatively low level of inequality in how these expenses are distributed among households. This low value suggests that most households have similar electricity expenses, with only minor differences between them. Economically, this could mean that households tend to consume similar amounts of electricity or that their energy needs are fairly uniform. However, this does not mean that energy inequality is absent. Energy inequality can still be present in various forms.
Natural gas expenditure. In the questionnaire, respondents who use natural gas were asked about their expenditure on it in the last year. Out of 1,000 respondents, 460 provided their expenditures, while 21 did not specify and 519 did not have such costs. The responses of the 460 respondents were distributed as indicated in Table 2.
|
Number of respon-dence
|
Share of respon-dence %
|
Mid-point (Eur)
|
Total
|
% from total
|
Cumulative
|
Cumulative (normalized)
|
Up to 30 Eur
|
56
|
0,1217
|
15
|
840
|
35,77
|
0,1217
|
0,0358
|
31-60 Eur
|
129
|
0,2804
|
45,5
|
5869,5
|
24,99
|
0,4022
|
0,2857
|
61 and more Eur
|
275
|
0,5978
|
61
|
16775
|
71,43
|
1
|
1
|
Table 2. Distribution of natural gas expenditures among respondents in the last year
The calculated data allows for plotting the Lorenz curve (Figure 2) and subsequently calculating the Gini coefficient as well as for calculation of the Gini coefficient, it is necessary to calculate the definitive integral (0; 1) of the function Y = 0,4936*X^2 + 0,5209*X - 0,0133
The obtained results and calculated Gini coefficient of 8.835% for the distribution of natural gas expenditures among respondents indicate a relatively low level of inequality. This suggests that expenditures on natural gas are quite evenly distributed among the respondents, meaning most people spend similar amounts on natural gas with few extreme differences in spending levels. Economically, this low level of inequality implies that natural gas is relatively affordable and accessible to the majority of the population surveyed. If natural gas were expensive or difficult to access for lower-income households, we would expect to see a higher Gini coefficient, indicating greater inequality. The even distribution of expenditures might reflect homogeneity in the consumption patterns of natural gas among the respondents, potentially due to similar household sizes, similar heating and cooking needs, or uniform pricing policies across the surveyed population.
Heating costs. In the questionnaire, we asked respondents about their heating costs over the last year. Out of 1,000 respondents, 960 provided their costs, while 40 did not specify. The responses of the 960 respondents were distributed as shown in Table 3.
|
Number of respon-dence
|
Share of respon-dence %
|
Mid-point (Eur)
|
Total
|
% from total
|
Cumulative
|
Cumulative (normalized)
|
Up to 250 Eur
|
74
|
0,2083
|
125
|
25000
|
5,06
|
0,2083
|
0,0506
|
251-400 Eur
|
193
|
0,1802
|
325,5
|
56311,5
|
11,40
|
0,3885
|
0,1647
|
401-800 Eur
|
216
|
0,3000
|
600,5
|
172944
|
35,03
|
0,6885
|
0,5149
|
801 and more Eur
|
269
|
0,3115
|
801
|
239499
|
48,51
|
1
|
1
|
Table 3. Distribution of annual heating costs among respondents
The calculated data allows for plotting the Lorenz curve (Figure 3) and subsequently calculating the Gini coefficient.
In order to calculate the Gini coefficient, the definite integral from 0 to 1 of the function Y = 0,8939*X^2 + 0,1182*X - 0,0063 has to be calculated.
The obtained results and calculated Gini coefficient of 14.92% for heating costs suggest that there is relatively low inequality in how heating expenses are distributed among the respondents. This means that most respondents likely experience similar heating costs, with only minor differences. The Gini coefficient is a measure of inequality, where 0 represents perfect equality (everyone has the same amount) and 100 represents perfect inequality (one person has everything). A lower Gini coefficient, such as 14.92%, indicates a more even distribution of costs among individuals. Several factors could contribute to this low level of inequality. For example, if respondents live in similar types of housing with comparable heating needs, their costs might be more uniform. Additionally, if heating costs are regulated or subsidized in the area where the respondents live, this could lead to more consistent expenses. Similarly, if respondents use similar heating systems, their costs would likely be more similar.
The low Gini coefficients for household electricity expenses (12.8233%), natural gas expenditures (8.835%), and heating costs (14.92%) indicate relatively low levels of inequality in these specific areas of household spending. Economically, these findings suggest that energy costs are fairly evenly distributed among households, implying several underlying factors at play. Firstly, the affordability and accessibility of these energy sources are likely significant contributors to the low inequality. For electricity, a Gini coefficient of 12.8233% suggests that electricity expenses are quite uniform across different households. This could imply that electricity is priced at a level that is affordable for most households, thus reducing significant disparities in consumption and expenditure. Similarly, the even lower Gini coefficient of 8.835% for natural gas expenditures suggests that natural gas is even more uniformly affordable and accessible. This low level of inequality indicates that households, regardless of their income levels, are able to consume similar amounts of natural gas. Heating costs, with a Gini coefficient of 14.92%, show slightly higher inequality but still remain low. This suggests that heating costs are relatively uniform among households, possibly due to similar heating needs.
Additionally, it was assessed how much of the respondents' income is allocated to taxes payable for electricity, gas, and heating, and the Figure 4 analyzing the relative frequency of the provided answers shows that the fluctuations are not very pronounced, and the maximum portion of taxable payments within their income is no more than 27%. The observation that respondents allocate no more than 27% of their income to electricity, gas, and heating costs can be explained by the relatively equitable income distribution within the surveyed population. This means that most households are spending a similar proportion of their income on utilities, leading to less variation in the responses. Additionally, households may adjust their consumption based on their income and utility costs, such as limiting heating during colder months or adopting energy-saving practices, to better manage their expenses. Together, these factors help explain why the portion of income spent on utilities remains relatively stable and does not exceed 27% of respondents' income.
Homogeneity in consumption patterns also contributes to these low Gini coefficients. If households have similar energy needs and usage habits, their expenditures on electricity, natural gas, and heating are likely to be comparable. This could be due to similar household sizes, living conditions, and energy consumption behaviors across the population. Despite the low Gini coefficients indicating low inequality in specific energy expenditures, energy inequality can still exist in other dimensions. Access to different energy sources can vary, with some households lacking access to renewable energy options or more efficient technologies, which provide long-term savings and environmental benefits. Moreover, the concept of energy burden, which refers to the proportion of household income spent on energy, can reveal hidden inequalities. Low-income households might experience higher energy burdens even if their absolute expenditures are similar to those of higher-income households, leading to financial stress and energy inequality. Quality of energy services is another aspect where inequality might be present. Households in underdeveloped areas might face frequent outages or poor-quality energy services, contributing to inequality in energy access and quality. Geographical disparities also play a role, with rural areas potentially facing higher energy costs or limited access to certain energy types compared to urban areas.
In overall, the low Gini coefficients for electricity, natural gas, and heating costs suggest a generally equitable distribution of these energy expenditures among households. The Gini coefficients reflect how evenly the reported expenditures are distributed among those who use these energy sources and have provided their expenditure data. These low values indicate that within this group, energy costs are fairly uniform, implying that most households spend similar amounts on these utilities. This uniformity could be due to effective energy policies, subsidies, and widespread access to affordable energy sources, which help to stabilize prices and make them accessible to a broad spectrum of households. However, focusing solely on Gini coefficients can obscure other forms of energy inequality. For instance, not all households may have equal access to different types of energy. Some households might lack access to natural gas or more efficient energy sources, which can lead to higher relative energy costs or limited energy options, contributing to energy inequality.
Energy burden, which refers to the proportion of household income spent on energy, can also reveal hidden inequalities. Even if absolute expenditures are similar, low-income households might spend a higher percentage of their income on energy, leading to financial stress and higher energy burdens. This indicates energy inequality despite low expenditure inequality. The quality and reliability of energy services can vary significantly. Households in underdeveloped or rural areas might experience frequent power outages, lower-quality energy services, or higher costs for the same services compared to urban areas. These geographical disparities contribute to energy inequality that is not captured by the Gini coefficients. Moreover, not all households have the means to invest in energy-efficient appliances or home improvements. Consequently, some households may spend more on energy due to inefficient usage, leading to higher overall costs and inequality in energy consumption and expenditures. Access to affordable and reliable energy has long-term impacts on health, education, and economic opportunities. Households struggling with high energy costs may face additional challenges, such as inadequate heating or cooling, which can affect their overall quality of life and long-term socioeconomic status.
The low Gini coefficients for each energy source suggest that the distribution of energy costs in Lithuania is relatively equitable, as evidenced by the analysis of household expenditures on electricity, natural gas, and heating. This implies that the financial burdens associated with energy expenses are consistent across the majority of households, indicating that they are widely accessible and affordable. Nevertheless, the uniformity in expenditure distribution suggests that energy costs are equitable; however, it is crucial to acknowledge that energy inequality may continue to exist in other domains, such as access to renewable energy technologies, energy quality, or geographical disparities. Consequently, the results suggest that the energy expenditure landscape is generally equitable. However, policymakers must persist in addressing more profound forms of energy inequality to guarantee that all households have access to sustainable, affordable, and reliable energy services.