Reevaluating Economic Drivers of Household Food Waste: Insights, Tools, and Implications Based on European GDP Correlations

Abstract

This article examines the relationship between household food waste and Gross Domestic Product (GDP) in various European regions, aiming to determine how economic prosperity influences the levels of household food waste. Using comparative analysis of secondary and tertiary data, a synthetic indicator (IpFW) was developed to assess the interaction between GDP per capita and household food waste per capita. Linear correlation analysis was also applied for better interpretation of the data. Despite expectations, higher GDP is not consistently correlated with lower household food waste, challenging economic prosperity and environmental stewardship assumptions. This research highlights the complexity of the interaction between economic factors and household food waste management, revealing a lack of significant correlation even at the regional level. The findings indicate a need to re-evaluate current policies and highlight that improving food supply chains and influencing consumer behavior can promote more sustainable consumption patterns, which is in line with the Sustainable Development Goals.

1. Introduction

The United Nations’ Sustainable Development Goals (SDGs) represent an integrated and collaborative approach to global development that involves governments, the private sector, civil society, and individual citizens. Achieving these goals requires an interdisciplinary approach and strong collaboration between all mentioned stakeholders. The implementation of the SDGs requires strong commitment and coordinated action from all countries, including underlying social and economic parties [1].

SDG 12: Responsible Consumption and Production is one of the 17 Sustainable Development Goals (SDGs) adopted by the UN in September 2015. All 17 goals are interconnected and aim to address the most pressing global issues, including poverty, hunger, health, education, inequality of gender, access to energy, climate change, and environmental protection. These goals are part of the UN’s 2030 Agenda for Sustainable Development, which aims to achieve a more sustainable and prosperous future for all people and for our planet [2].

Within SDG 12:Responsible Consumption and Production, there is a specific objective (12.3) meant to reduce worldwide food waste per capita by half until 2030 (this objective takes into account household levels). The target includes reducing food waste through measures such as downsizing the amount of food purchased, storing and preserving food properly, planning food purchases more carefully, sharing and donating surplus food to those in need, and using cooking techniques that minimize waste [3,4].

Reducing food waste at the household level is equally essential for achieving the specific goal of SDG 12.3: Food Loss and Waste, as well as the general goals of SDG 2: Zero Hunger and SDG 13: Climate Action, as it can contribute to reducing greenhouse gas emissions and increasing the efficiency and sustainability of food supply chains [5,6].

Given the current context, it is obvious that a strong and better-coordinated government policy is more feasible if supported by a stronger economy, with a high Gross Domestic Product (GDP), as the government has the financial and human resources required to effectively implement and monitor public policies. This statement is especially valid for complex and interdisciplinary policies, such as those aimed at reducing food waste [7].

A number of additional studies have shown that a strong and more stable economy can create a more favorable environment for the implementation of effective public policies, including policies to reduce food waste. Druckman et al. show that higher economic growth can help finance the investment needed to reduce food waste in households and other sectors [8].

Furthermore, recent research highlights how economic stability can facilitate the adoption of advanced technologies and efficient waste management systems, contributing to significant reductions in food waste. This growing body of literature underscores the importance of economic factors in shaping effective waste reduction strategies and supports the notion that sustainable economic policies can play a crucial role in minimizing household food waste.

In addition, based on the abovementioned premises, the EU adopted the Common Agricultural Policy (CAP), which has been in operation for over 60 years, with the aim of ensuring food security in the Member States of the European Union, while taking into account access to food at affordable prices for consumers. According to the European Court of Auditors (2016), the EU budget for the financial years 2021–2027 holds food security as the most important objective for the financial support of agriculture through the CAP [9,10].

Food waste, including household food waste—a valid phenomenon in consumer behavior around the world, is a determinant factor for food security [11]. On a theoretical scale, we appreciate that as more adults waste food, more people die or suffer from hunger. At the same time, as more children are overly selective about their food, even more children die of hunger or malnutrition [12,13,14].

Food waste is one of the major concerns of every EU Member State and the EU as a whole. To this end, the measures that have been and are being adopted both at the level of each EU Member State and at the EU level are increasingly important and consistent. Yet, despite all this, the abovementioned measures have been proven to be ineffective [15]. Household food waste, a behavior in which each consumer engages within the confines of their homes, is a widespread phenomenon, present on all continents, in all geographical regions, and in all countries, which occurs due to a large variety of factors [16]. In sub-Saharan Africa and Southeast Asia, for example, the reason for food waste can be attributed to the poor infrastructure of the relevant industries [14], while in Europe and, especially, the EU, the situation is completely different [17].

According to the Food and Agriculture Organization of the United Nations, quoted by Global Food Waste Statistics, 1.3 billion tons of edible food, or 1/3 of global production, are wasted annually worldwide, which would be enough to feed approximately 2 billion people [18]. At the same time, this trend is growing, with the amount of food waste worldwide expected to increase to two-thirds of global food production by 2030 [19,20].

Food waste can be reduced mainly at the household level [3,21,22,23]. In essence, household food waste is the largest contributor to this phenomenon. Food waste manifests itself in several stages of the food chain, but the most important sectors are households, food service, and retail. According to the United Nations Environment Program-Food Waste Index Report 2021 [23], high-income countries with a high gross domestic product (GDP) annually contribute an average of 79 kg/capita of household food waste, 26 kg/capita of food service waste, and 13 kg/capita of retail food waste.

In the European Union and in Europe in general, household food waste is and has been constantly present at various levels. There is no quantitative benchmark for ‘low household food waste’ set by any international regulation or national act of law in any country within our sample population. For the purpose of this study, we arbitrarily established that ‘low household food waste’ can be represented by the value for Slovenia, which has the lowest household food waste in our sample, amounting to 34 kg per capita per year, as indicated by the data analyzed in the subsequent sections. Currently, there is a large variance in food waste across European geographical areas, to the extent that it may not be homogenous among the different areas, even within a certain group of countries. Therefore, in some regions of Europe, in a group of countries with higher GDP than other European countries, the average per capita household food waste is high. A high value of GDP per capita largely implies a wealthy population [24,25]. This fact should reflect the level of education and citizens’ concern for the natural resources and labor used in the production process of food that is wasted [26].

In consequence, this paper aims to test the hypothesis that countries with high economic performance, in terms of GDP/capita, yield a lower quantity of household food waste. In order to reach our goal, we used data from a number of European countries within and outside of the European Union. To deal with various socio-cultural differences, the first step of our method was to divide the continent into four major groups and test the validity of the abovementioned statement for each geographical region by taking into consideration the various underlying background differences. Once each sub-hypothesis is addressed, at the regional level, our analysis broadens its specter toward answering the larger research question that concerns Europe at a macro level. The assumption that high economic prosperity leads to a better-educated citizen, which, in turn, makes the individual more aware of food waste and environmental issues, is supported both by international bodies responsible for the management of natural resources and food security and by researchers studying the food chain [27,28]. However, this hypothesis has never been tested previously. Based on our findings, we wish to present a more educated opinion on the matter, grounded in facts and figures, to the end of changing an existing status quo regarding the fashion in which public policies mitigate the problem of food waste.

Lastly, we anticipate a number of limitations for the present research paper, which potential decision-makers and academic peers should take into consideration. While we do address the correlation between economic wellbeing and household food waste, any further discussions regarding points of action toward reducing food waste are complicated by various factors. Although the UN’s 2030 Agenda, specifically, SDG 12—target 12.3, explicitly aims to halve per capita global food waste at the retail and consumer levels and reduce food losses along production and supply chains, these measures may not be entirely effective. One reason for this potential inefficiency is the lack of uniform implementation and enforcement across different countries and regions, which can lead to inconsistent progress. Additionally, while we have a generic sense of what food waste implies, there is still no universally accepted definition that differentiates between waste generated by legitimate household consumption and waste generated by households involved in family businesses. This ambiguity makes it challenging to design and implement targeted and effective interventions. Therefore, despite the established measures, achieving significant reductions in household food waste remains a complex and multifaceted challenge.

2. Materials and Methods

Comparative analysis of secondary and tertiary data is a method used in economics to assess the differences and relationships between two or more variables in different countries or regions. We use the same method to understand the differences and possible relationships between household food waste per capita, GDP per capita, and linked tertiary sets of data from European countries. Regarding the mentioned tertiary data, we chose various related indicators published in [23] by the World Bank-International Monetary Fund World Economic Outlook [29] and the World Bank Report 2018 (for Andorra, Faroe Islands, Isle of Man, Liechtenstein, and Monaco) [30,31,32,33,34] and data published by the CIA’s World Factbook [35].

The regional classification of European countries (North, South, East, and West) was performed to reflect the socio-economic, cultural, climatic, and legislative differences that influence household food waste practices and rates, thus providing a more nuanced and relevant analysis of the phenomenon.

2.1. Comparative Analysis

First, we use comparative analysis to assess the amount of household food waste per capita (HFW_{kg/capita/year}) in each European country, followed by a regional analysis from a univariate statistical stand point. This allows the identification of significant differences in HFW_{kg/capita/year} between European countries. Furthermore, the approach maps out regional tendencies in household food waste, which in turn justifies further correlation analysis for Europe as a whole. To this end, we divided Europe into four major regions, in terms of two representative variables: gross domestic product per capita and household food waste per capita. To better point out potential cultural and economic differences, we encoded the abovementioned quantitative variables into qualitative variables to group countries in terms of low, medium, and high economic prosperity and food waste. The following method was employed: using the IBM SPSS statistics software for each individual region, we calculated the minimum value, maximum value, median, mean, and standard deviation for each variable. In consequence, we encoded the quantitative variables into different variables for each country based on the following conditions:

-

low economic prosperity and low household food waste tendencies if GDP per capita and HFW_{kg/capita/year} ⊆ [min, median − 1σ)

-

medium economic prosperity and medium household food waste tendencies if GDP per capita and HFW_{kg/capita/year} ⊆ [median − 1σ, median + 1σ]

-

high economic prosperity and high household food waste tendencies if GDP per capita and HFW_{kg/capita/year} ⊆ (median + 1σ, max]

2.2. Creation of the Synthetic Indicator I_pFW

For better preliminary conclusions at regional levels and to further evaluate the relationship between the two variables, we created a synthetic indicator I_pFW (Personal Food Waste Indicator). This indicator is calculated by relating GDP_{thous.USD/capita/year} to the amount of HFW_{kg/capita/year} in each country. In this manner, we were able to identify the best- and worst-performing countries in terms of the relationship between the level of economic prosperity and the amount of food wasted. It is important to consider the ratio between the two when analyzing the correlation between GDP and the level of household food waste, especially since a high economic performance in terms of GDP has previously been linked to a higher average level of education for the country in question, which, in turn, is believed to yield a lower level of food waste [2,11]. Therefore, an indicator resulting from the following equation is expected to have a value well above 1 for countries that display a medium to high level of economic prosperity:

I_pFW = GDP_{thous.USD/capita/year}/HFW_{kg/capita/year}

(1)

where I_pFW is the Personal Food Waste Indicator (HFW_{kg/capita/year} depending on GDP_{thous.USD/capita/year}), GDP_{thous.USD/capita/year} is the GDP in relation to a single citizen of the country, and HFW_{kg/capita/year} is the household food waste in relation to a single citizen of the country.

2.3. Rank Correlation Test

We conducted a correlation analysis to observe the data and performed an interpretation to smooth the resulting problems and observations. The correlation between the statistical data series GDP_{thous.USD/capita/year} and HFW_{kg/capita/year} was tested using the non-parametric Kendall’s tau-b test using the SAS procedure Studio Correlation Analysis. This was first used for all European countries and then for countries grouped by the geographical position criteria: North, South, East, and West of Europe. In addition, Pearson’s linear correlation coefficient was used to test the relationships between the two series (GDP_{thous.USD/capita/year}; HFW_{kg/capita/year}) for all European countries. The graphic representation of the linear regression functions is a result of the Scatter plot regression procedure in SAS STUDIO.

Since GDP, according to its definition, is the total market value of all final goods and services produced in a country each year and is a representative indicator of a country’s economic level in terms of production, its use in this study is justified (World Bank, 2020). Each country reports its own data in its own currency, and to be able to compare the data, it is necessary for each country’s national statistics to be converted into a common currency. The World Bank uses the US dollar as its conversion currency, which is also the currency of choice for our study.

2.4. Simple Ordinary Least Squares Linear Regression Model

We used a simple ordinary least squares linear regression model. By using the IBM SPSS Statistics software, we extended our analysis with a goodness-of-fit test to highlight the results for the overall sample, thereby providing a more comprehensive understanding of how well the observed data align with the expected distribution. This additional test allowed us to assess the adequacy of our model and ensure that the conclusions drawn are robust and statistically significant across the entire dataset. We anticipate that the R-squared value will not contradict the correlation analysis result from the previous step, as far as the relationship between the two variables is concerned. On the other hand, expressing this relationship in a mathematical form, in terms of the y-intercept and slope, has the potential to better explain the current result.

3. Results

3.1. Household Food Waste and GDP in European Countries

In the following section, we will treat each European major cardinal area as an individual case study in relation to economic wellbeing and food waste, covering the following values (

Table 1. Independent variable values at the regional level.

Country		GDP 1	HFW 2	IpFW
Northern Europe	Denmark	58.60	81	0.72
	Estonia	23.13	78	0.30
	Faroe Islands	63.85	76	0.84
	Finland	48.10	65	0.74
	Iceland	61.22	76	0.81
	Ireland	82.18	55	1.49
	Isle of Man	88.33	76	1.16
	Latvia	17.27	76	0.23
	Lithuania	19.90	76	0.26
	Norway	68.29	79	0.86
	Sweden	52.71	81	0.65
	United Kingdom	39.07	77	0.51
Southern Europe	Albania	4.88	83	0.06
	Andorra	40.77	84	0.49
	Bosnia and Herzegovina	5.74	83	0.07
	Croatia	13.70	84	0.16
	Gibraltar	*	84	*
	Greece	18.60	142	0.13
	Holy See (Vatican)	*	*	*
	Italy	30.50	67	0.46
	Malta	32.45	129	0.25
	Montenegro	7.89	83	0.10
	North Macedonia	6.02	83	0.07
	Portugal	21.61	84	0.26
	San Marino	41.46	84	0.49
	Serbia	5.94	83	0.07
	Slovenia	24.77	34	0.73
	Spain	26.58	77	0.35
Eastern Europe	Belarus	6.07	68	0.09
	Bulgaria	9.65	68	0.14
	Czechia	22.68	70	0.32
	Hungary	15.51	94	0.17
	Poland	15.35	56	0.27
	Moldova	2.78	76	0.04
	Romania	12.86	70	0.18
	Russian Federation	9.92	33	0.30
	Slovakia	18.71	70	0.27
	Ukraine	3.23	76	0.04
Western Europe	Austria	48.34	39	1.24
	Belgium	43.70	50	0.87
	France	39.27	85	0.46
	Germany	45.27	75	0.60
	Liechtenstein	181.70	72	2.52
	Luxembourg	112.02	90	1.24
	Monaco	185.10	72	2.57
	Netherlands	51.84	50	1.04
	Switzerland	82.73	72	1.15

¹ thous. USD/capita/year. ² kg/capita/year. * No data.

):

3.1.1. Household Food Waste and GDP in the Countries of the Northern European Region

Northern European countries are generally wealthier than countries in many other parts of Europe, where even the countries with low economic prosperity, by regional standards, are above the continental mean. More specifically, the GDP per capita varies between USD 17.27 thous. and USD 88.33 thous. per year. The level of HFW_{kg/capita/year} varies between 55 and 81 kg per capita per year. It should be noted that in the case of the Northern Europe region, the country with the highest GDP in terms of US dollar amount per capita per year is also the country with the lowest level of household food waste, which is Ireland. This may prove to be an exception, since in spite of the better overall economic performance, our data indicate that the region is not a model for proper household food waste management (

Table 2. Univariate statistical analysis for Northern Europe.

Analysis	Values	Low	Medium	High
GDP Analysis
Mean	51.89
Median	55.66
Standard deviation	23.39
Intervals		[17.27–33.27)	[33.27–79.05]	(79.05– 88.33]
Frequency (n)		3/12	7/12	2/12
Frequency (%)		25.00%	58.30%	16.70%
Household food waste analysis
Mean	74.67
Median	76.00
Standard deviation	7.41
Intervals		[55–68.59)		[68.59–81.00]
Frequency (n)		2/12		10/12
Frequency (%)		16.70%		83.30%
1 < IpFW > 1 (by GDP interval)		0 countries > 1 3 countries < 1	0 countries > 1 7 countries < 1	2 countries > 1 0 countries < 1

).

Our first observation regarding this sample population is that for household food waste, the mid value plus one standard deviation exceeds the maximum value. Therefore, the creation of three qualitative intervals is not possible; hence, we shall consider the interval ranging from minimum value to mid value − 1σ as being low waste, and the interval ranging from mid value − 1σ to max as being high waste (with a 76 frequency of 5/10). As seen in Figure 1, the expected trend of high economic prosperity being linked to low household food waste does not hold true, except for two countries that rate I_pFW higher than 1. Furthermore, while the Isle of Man may be a perfect example of good practices regarding household food waste, its low nominal GDP and small population certainly makes it an exception more than a rule. Overall, while the Northern European group comprises wealthy countries (75% having medium to high GDP/capita), it also displays a high rate of household food waste (83.3%).

Finally, the weighted average of HFW_{kg/capita/year} for Northern Europe, relative to the total population in this region, is about 49% higher than that for Eastern Europe (absolute values: 51 kg per capita per year for Eastern Europe versus 76 kg per capita per year for Northern Europe), in spite of the fact that the GDP_{thous.USD/capita/year} of these countries is much lower.

3.1.2. Household Food Waste and GDP in the Countries of the Southern European Region

The data presented in this region, unlike those in the region presented above, are not fully reported for 2020 or are not reported at all the last 3 years, but we appreciate that this does not affect the findings of this study because the underlying countries do not have a numerically significant population. Applying the same method used for Northern Europe, we conclude that for Southern Europe, the lack of association between the countries’ economic wellbeing and household food waste is even more obvious. While 50% of the countries in this region have a medium level of prosperity and 75% have a medium level of waste, this is a perfect example of the importance played by the synthetic indicator, which, in this case, is less than 1 for all members of the sample population, regardless of the level of economic wellbeing (

Table 3. Univariate statistical analysis for Southern Europe.

Analysis	Values	Low	Medium	High
GDP Analysis
Mean	20.07
Median	20.11
Standard deviation	13.12
Intervals		[4.88–6.99)	[6.99–33.23]	(33.23–41.46]
Frequency (n)	(missing: 2)	4/16	8/16	2/16
Frequency (%)		25.00%	50.00%	12.5%
Household food waste analysis
Mean	85.60
Median	83.00
Standard deviation	24.11
Intervals		[34.00–58.81)	[58.81–107.19]	(107.19–142]
Frequency (n)	(missing: 1)	1/16	12/16	2/16
Frequency (%)		6.30%	75.00%	12.50%
1 < IpFW > 1 (by GDP interval)		0 countries > 1 4 countries < 1	0 countries > 1 8 countries < 1	0 countries > 1 2 countries < 1

).

An interesting observation is that this region hosts the countries with the first two highest values of household food waste in all of Europe, namely Greece (142 kg per capita per year) and Malta (129 kg per capita per year). In the Southern European region, the significantly higher levels of household food waste per capita in Greece (142 kg per capita per year) and Malta (129 kg per capita per year) compared to other countries can be partly attributed to the substantial role of tourism in their economies. Both Greece and Malta have economies heavily reliant on tourism, similar to Italy and Spain. However, unlike Italy and Spain, where food waste is more evenly distributed between household and food service sectors, in Greece and Malta, the integration of family-run tourist accommodations with households likely leads to a higher reporting of food waste under the ‘household’ category. This unique aspect of their tourism sector, where family homes double as tourist lodgings, can inflate the household food waste figures as food waste generated in these hybrid settings is not easily classified solely as household or food service waste. Although it is difficult to justify this situation, it can be assumed that the high level of household food waste is because the economic activities of the two countries are mainly based on tourism. Their tourist units are family-run, organized as family tourist boarding houses shared with the respective families’ homes, which is why it is possible that food waste was reported in the “household food waste” category and not in the “food service” category. Regardless, the situation in these two countries is worrying (Figure 2).

3.1.3. Household Food Waste and GDP in the Countries of the Eastern European Region

Eastern European countries are countries with a high level of household food waste, which ranges between 33 and 94 kg per capita per year. Again, the case of Eastern Europe proves I_pFW most relevant, especially because all values are not only <1 but rather close to zero. In corroboration with Figure 3 and the overall figures across Europe, we conclude that the present data suggest the opposite, meaning that the poorer the country, the higher the household food waste, with the eastern European countries being the poorest among all the 47 examined states. This, however, has no relevance to our hypothesis. Judging strictly from the present findings for this group, we observe that 80% of the countries have a medium to high level of prosperity by regional standards, and at the same time, 90% of household food waste comes from countries in the same interval (

Table 4. Univariate statistical analysis for Eastern Europe.

Analysis	Values	Low	Medium	High
GDP Analysis
Mean	11.64
Median	11.39
Standard deviation	6.55
Intervals		[2.78–4.84)	[4.84–17.94]	(17.94–22.68]
Frequency (n)		2/10	6/10	2/10
Frequency (%)		20.00%	60.00%	20.00%
Household food waste analysis
Mean	68.10
Median	70
Standard deviation	15.58
Intervals		[33.00–54.42)	[54.42–85.58]	(85.58–94.00]
Frequency (n)		1/10	8/10	1/10
Frequency (%)		10.00%	80.00%	10.00%
1 < IpFW > 1 (by GDP interval)		0 countries > 1 2 countries < 1	0 countries > 1 6 countries < 1	0 countries > 1 2 countries < 1

).

3.1.4. Household Food Waste and GDP in the Countries of the Western European Region

While the data for most previous cases had a relatively normal distribution, the GDP per capita data for Western European countries is highly skewed to the left. Therefore, we opted to establish a low interval ranging from the minimum value to the median and from the medium to high interval, ranging from the median + 1σ and +2σ, respectively. Also, the data structure does not leave room for a medium interval in the case of household food waste since median + 1σ equals 89.15, which is very close to the max value of the data series. Therefore, we labeled the two intervals, as depicted in

Table 5. Univariate statistical analysis for Western Europe.

Analysis	Values	Low	Medium	High
GDP Analysis
Mean	87.77
Median	51.84
Standard deviation	59.01
Intervals		[39.27–51.84)	[51.84–110.85]	(110.85–185.10]
Frequency (n)		4/9	2/9	3/9
Frequency (%)		44.40%	22.20%	33.30%
Household food waste analysis
Mean	67.22
Median	72.00
Standard deviation	17.15
Intervals		[39.00–54.85)		[54.85–90.00]
Frequency (n)		3/9		6/9
Frequency (%)		33.(3)%		66.(6)%
1 < IpFW > 1 (by GDP interval)		1 countries > 1 3 countries < 1	2 countries > 1 0 countries < 1	3 countries > 1 0 countries < 1

.

At first glance, Table 5 is different from the other tables above, displaying three wealthy countries with food waste indices larger than one. However, a closer look at the data structure yields a different conclusion. The three countries that adhere to a high GDP per capita, far greater than 1 I_pFW, as seen in Table 1, are three microstates, with a considerable GDP and a fairly low number of citizens. In contrast to the other countries that make up the sample population, Monaco and Lichtenstein, with populations well under 50000 and a fiscal paradise-like public policy culture, in all fairness, are not representative of the Western Europe sample. Smoothing the analysis by eliminating the two members will not normalize the distribution a great deal but would halve the standard deviation and maximum values for the GDP per capita in the data series. This isolates Luxembourg as the sole country in the high economic prosperity interval, leaving Austria, Belgium, France, and Germany as representatives of countries with low economic prosperity. While these four countries are by no means poor countries, we conclude that Luxembourg is yet another comparison anomaly that is not compatible with countries that have high populations and high governmental expenditure, which may reduce the GDP per capita. In the absence of Luxembourg, France and Germany remain in the low economic prosperity interval, which is truly abnormal. As far as Western Europe is concerned, our unilateral statistical analysis based on the presented variables is inconclusive. Despite these findings, the figures for Western Europe remain relevant for the remainder of our analysis (Figure 4).

3.2. Personal Food Waste Synthetic Indicator (I_pFW) in Europe

If we consider that economic performance implies a higher level of education and, inherently, a higher level of the population’s responsibility towards food, then, the value of the ratio between GDP and household food waste, in terms of the per capita level, should be as high as possible, in the sense that a high economic performance should generate a low level of food waste. This hypothesis was supported by the mentioned literature, which concluded that the higher the GDP is, the lower the household food waste should be, which in turn yields a higher value for the personal food waste indicator. Using the formula for I_pFW (1), we determined the values for all European countries (Table 1).

The assumption that the higher the GDP is, the lower the household food waste should be, which, in turn, brings a higher value for the personal food waste indicator, is not confirmed. Using the I_pFW formula and interpreting these data graphically, it is revealed that the value of this indicator is not high in all European countries with a high GDP, as expected (Figure 5).

To ensure the robustness of our analysis and address concerns regarding statistical significance, we integrated a detailed quantitative analysis into our methodology. After calculating the Personal Food Waste Indicator (IpFW) for each country and dividing countries at the group level into low/median/high-value intervals according to this indicator, we applied Kendall’s tau-b test to evaluate the correlation between GDP per capita and household food waste per capita. This statistical test, chosen for its robustness in handling non-parametric data, revealed that while there are notable variations, the overall correlation between GDP and food waste across Europe remains statistically non-significant, with Kendall tau-b values close to zero for all regional groupings (Northern, Southern, Eastern, and Western Europe). These findings highlight the complexity of the relationship between economic prosperity and food waste behaviors, suggesting that factors other than GDP play a significant role in influencing household food waste patterns.

This situation is not confirmed due to the fact that if GDP_{thous.USD/capita/year} is high, its ratio with a high level of HFW_{kg/capita/year} will not be below one, even if food waste is high, and if GDP is high, the I_pFW value will also be high. So, the hypothesis that a high GDP generates a greater responsibility towards natural resources, implicitly towards food, is not supported by the data.

In this context, we applied another analysis to identify the correlation supported by the SGDs using a different approach.

Therefore, we tested the correlation between the statistical data series GDP_{thous.USD/capita/year} and HFW_{kg/capita/year} using the non-parametric Kendall’s tau-b test in order to check if the same countries that have a medium to high level of economic prosperity are the same countries that have a medium to high rate of household food waste, using the SAS procedure Studio Correlation Analysis, for all European states. The graphic representation of the linear regression functions, as shown in Figure 6, was produced using SAS STUDIO, with the Scatter plot regression procedure, for all European countries.

Furthermore, Pearson’s linear correlation coefficient was used when testing the relationships between the two series (GDP_{thous.USD/capita/year}, HFW_{kg/capita/year}) for the data related to all European countries. Following this test, the analysis performed for all European countries resulted in low values of the correlation coefficients Pearson r = −0.06 and Kendall τ = −0.08, with high p-values of over 0.4. Thus, it is revealed that at the European level, there is no connection of statistical significance between GDP_{thous.USD/capita/year}, and HFW_{kg/capita/year}.

In order to find out if the situation changes at various European regional levels, we tested the correlation between the statistical data series GDP_{thous.USD/capita/year} and HFW_{kg/capita/year} using the non-parametric Kendall’s tau-b test, with the SAS procedure Studio Correlation Analysis software, for the following geographical areas (as defined above): the Northern Europe states, the Southern European states, the Eastern European states, and Western European states. The graphic representation of the linear regression functions, using SAS STUDIO with the Scatter plot regression procedure, is presented in Figure 7 for each European region.

Therefore, the absence of a correlation is also confirmed at regional levels. Thus, in all four groups of countries, the Kendall correlation coefficients are close to 0, ranging between −0.08 and 0.16. Moreover, the p-values are high, exceeding the α = 5% threshold. This indicates the absence of a correlation between the analyzed series. Also, the data do not indicate a significant departure from 0 for the correlation coefficient.

We further used a simple ordinary least squares linear regression model, where GDP/capita/year plays the role of the independent variable and HFWkg/capita/year is the dependent variable. Based on the R and R-squared values, which are very close to zero (GDP/capita explains only 0.5% of the variance in HFW/capita), we conclude that the predicting capacity of GDP/capita in terms of household food waste has very little to no explanatory value (

Table 6. OLS model summary for GDP/Capita–HFW/capita regression.

Model	R	R-Squared	Adjusted R-Squared	Std. Error of the Estimate
1	0.070 a	0.005	−0.018	20.61908

^a Predictors: (Constant), GDP/Capita.

).

In accordance with the previous tests, where the Pearson and Kendall coefficients are negative but so small that any possible negative correlation lacks statistical significance, the OLS coefficient indicates the same conclusion. The results show that household food waste is 77.75 kg for the entire population. Although this makes sense from a mathematical standpoint, it does not reflect any real-life economic scenarios. Furthermore, the following linear regression: HFW/capita = −0.036 × GDP/capita + 77.75 does not support our hypothesis. Although as GDP/capita increases, household food waste decreases, the highly small value of the slope further demonstrates that the relationship between the two variables is not very strong (

Table 7. OLS coefficient for GDP/Capita–HFW/capita regression.

Model		Coefficients a			t	Sig.
		Unstandardized Coefficients		Standardized Coefficients
		B	Std. Error	Beta
1	(Constant)	77.751	4.320		17.998	0.000
	GDP/Capita	−0.036	0.077	−0.070	−0.464	0.645

^a Dependent Variable: HFW/Cap(kg).

).

Overall, the statistical endeavor offers sufficient evidence in order to reject the null hypothesis presented in the introductory part, meaning that the assumption that countries with high economic performance, in terms of GDP/capita, yield a lower quantity of household food waste is false.

4. Discussion

Even if some studies show that a strong and more stable economy can create a more favorable environment for implementing effective public policies, including policies to reduce food waste, this does not happen in practice. Our statistical analysis, both at the regional and macro levels, has proven beyond any reasonable doubt that our hypothesis is rejected. While estimates recommend that higher economic growth can help finance the investment needed to reduce food waste in households and other sectors, this has no concrete effects related to household food waste. We would further like to discuss possible alternatives, which may explain our findings and may prescribe an alternative course of action for public institutions and other non-governmental parties involved in efforts towards finding solutions aimed at remedying the present problem. Responsibility towards food in general materializes in the awareness that food is the source of life, nutrients, and health of every citizen of each country. Viewing things from this perspective makes us realize that in every country there are people, more or less, who are economically disadvantaged and who suffer from lack of food and, implicitly, from hunger. Awareness of this situation can generate a special respect for food [12,13,14,15,16].

Responsibility for environmental protection materializes in the awareness and the assumption that food manufacturing has a negative impact on the environment through generated waste, including household food waste. Household food waste pollutes the environment in various ways, and it is becoming increasingly difficult for society to manage its implicit outcome [36,37,38,39]. Disposing of this waste is the result of employing technologies that affect the environment in ways that are currently unquantifiable. At the same time, intensive agriculture results in a large amount of pollution by stimulating plant and livestock production through various technologies in order to increase output. If food would not be subject to waste, the food needs of the population would decrease, and an increase in food production would not be necessary.

The forms of household food waste materialize in various aspects, in addition to the very frequent action of throwing food in the trash because too much has been bought and exceeded its shelf life. Other forms of household food waste include the overconsumption of food, including products of animal origin, beyond the nutritional needs of the human body. Obesity and overweightness are a consequence of metabolic food waste, except for situations imposed by medical reasons [40]. Meat and meat products, as well as milk and dairy products, are consumed far beyond people’s protein needs, which generates the demand for the intensive exploitation of animals, which also depletes plant resources. Most often, vegetable proteins can successfully replace animal protein for human consumption. If these consumption habits were implemented, it would substantially reduce the negative impact on the environment as well as on the consumers’ health [41,42].

In today’s digital context, it can be speculated that electronic commerce (e-commerce) could play a transformative role in addressing household food waste, using technology to improve both economic and environmental outcomes. Although traditional economic growth has shown limited direct impact on reducing food waste, e-commerce offers innovative ways to connect surplus food with consumer needs or for more efficient management of perishable food stocks, thereby reducing waste and the associated environmental burden.

Online platforms can facilitate more efficient food distribution systems by matching surplus food with demand in real time, thereby mitigating overproduction and excessive purchases that lead to waste. In addition, e-commerce enables the promotion of awareness campaigns directly to consumers, educating them about sustainable consumption practices and the importance of minimizing food waste. These platforms can also support policy implementation by providing data-driven insights into consumer behavior and waste patterns, providing a powerful tool for policymakers in developing more targeted and effective strategies to combat food waste [43,44,45,46]. Thus, although these ideas were not addressed in detail in this paper, they represent promising directions for future research. E-commerce not only supports economic growth but also encourages more responsible management of resources, highlighting its critical role in achieving sustainable food systems and protecting the environment.

Responsibility for the resources needed to obtain food, which is finally wasted, is another issue that public policymakers should take into account. Water is one of the basic resources in food production, along with energy, land, and labor. The more food we waste in each household, the more water, energy, land, and labor are wasted, and the carbon footprint increases, along with other environmental footprints [47,48,49]. Furthermore, food packaging is also manufactured in a large industry that consumes large quantities of natural resources, in addition to the pollution factor. If food waste were reduced, the consumption of all these natural resources would, in turn, be reduced.

In Europe, as in much of the developed world, household food waste represents a significant challenge to sustainability goals, with economic implications that ripple through societies. Traditionally, Gross Domestic Product (GDP) has been a marker of economic health but does not inherently account for environmental outcomes like food waste. However, the digital era presents new opportunities to redefine the interplay between economic performance and sustainability through the lens of e-commerce.

E-commerce has surged, reshaping consumer behaviors and market dynamics. In the context of GDP and food waste, e-commerce platforms are uniquely positioned to influence both. They can optimize supply chains, reduce excess production, and facilitate the redistribution of food, thus addressing one of the critical points of waste in the food service and retail sectors.

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Streamlining supply chains. E-commerce can streamline food supply chains by enabling more direct interactions between producers and consumers. Platforms can use predictive analytics to gauge demand more accurately, reducing the overproduction that often leads to significant waste. For instance, online grocery stores can adjust orders based on real-time consumer purchasing data, ensuring that only the required food items are harvested and transported. Another advantage of this just-in-time inventory approach reduces waste at the retail level as better date usage leads to a reduction in the amounts of perishable food items that reach expiration dates. This precision reduces the environmental burden and aligns better with sustainable GDP growth by focusing on efficiency over volume.

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Enhancing consumer awareness. Furthermore, e-commerce platforms are powerful tools for consumer education. They can provide information directly to consumers about sustainable practices, such as how to store food properly to extend its shelf life or recipes designed to use leftover ingredients. By integrating sustainability into the consumer experience, e-commerce not only helps reduce waste at the household level but also promotes a culture of responsibility that can have broad implications for GDP. Educated consumers are likely to make purchasing decisions that reflect their values, favoring products and services that align with sustainability goals.

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Facilitating food redistribution. Another significant advantage of e-commerce is its ability to facilitate the redistribution of food that would otherwise go to waste. Platforms can connect businesses with surplus products to consumers or charities that can use these products. This not only helps reduce waste but also supports social welfare programs, indirectly contributing to a healthier economy by alleviating some of the burdens on social services.

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Policy integration. To maximize the impact of e-commerce on reducing food waste and enhancing GDP, policymakers need to integrate digital strategies into broader economic and environmental policies. Regulations that support fair digital marketplaces, data protection, and the promotion of green technologies can enhance the effectiveness of e-commerce in sustainability practices.

In the end, it is essential to compare our main findings to those of other studies and highlight the research gaps addressed by our work. Our study revealed a minimal correlation between GDP per capita and household food waste, consistent with similar research conducted by FAO [4], which found that economic indicators alone do not sufficiently explain variations in food waste at the household level. Moreover, our findings diverge from those of Philippidis et al. (2019) [12], who suggested a stronger link between economic prosperity and lower food waste due to increased awareness and better waste management practices in wealthier countries. This discrepancy underscores the need for more nuanced models that incorporate socio-cultural and behavioral factors. Furthermore, our research addresses the gap in understanding the impact of tourism on household food waste, particularly in countries like Greece and Malta, where tourism plays a significant role. Previous studies, such as those conducted by Balan et al. (2020) [13], have largely overlooked this aspect, focusing instead on industrial and commercial food waste. By highlighting these unique national contexts and integrating tourism-related factors, our study provides a more comprehensive understanding of the determinants of household food waste and opens new avenues for targeted interventions and policy development.

5. Conclusions

Measures to reduce food waste are becoming more pronounced but are still insufficient and inefficient [9,50,51]. Food waste cannot be only associated with certain social or demographic categories or with countries with a certain level of GDP. It is a form of human behavior commonly found not only in regions across Europe but in all countries globally and in all socio-demographic categories [9].

According to the UN, half of the fruits and vegetables harvested worldwide are wasted [52]. At the European level, the FAO estimated that in 2013, the quantity of food wasted in Europe could feed 200 million people [17]. The current data show that the actual values far exceed the FAO quotas from 2013. Recent estimates indicate more waste than in previous years due to the fact that the estimation methods are substantially improved as a result of food policy implementation at the state level [2]. Regardless of how food waste is analyzed and how realistic household food waste estimates are obtained, it is well-known that people around the world continue to waste a lot of food. Of course, it is debatable how much of this waste cannot be avoided (inedible parts of vegetables and fruits, as well as meat, unavoidable perishability during storage and transportation, etc.) [53,54]. Regardless, it is an undeniable fact that food waste is present in households in each country across Europe.

If we consider that the level of education of the population is dependent on the economic performance of each state, a higher GDP should generate a more educated population, with increased responsibility for food, environmental protection, and the resources needed to produce these foods [55,56,57]. This does not happen in reality as we demonstrated in this study. In Europe, the level of household food waste varies greatly across countries (between 33 and 142 kg per capita per year), and this fact is not dependent on the GDP of those countries (between USD 2.78 and USD 185.10 thous. per capita per year) as might be erroneously estimated.

The issue of food waste is even more serious since household food waste is not the sole factor that significantly raises its value per capita.

Given these issues, we conclude that the UN’s strategy to combat food waste needs to be more concrete and strengthened. The UN should improve the measures previously taken to reduce food waste and draw up concrete action plans for each country, depending on individual specifics. At the same time, in order to facilitate food donation, the UN should adopt uniform legislation, which clearly regulates the scope and encourages food donation in all forms, including the form of e-commerce, which would otherwise be wasted, even more now. This point of view is strengthened by the recent extraordinary circumstances surrounding the COVID-19 pandemic experience when more people were suffering from a lack of proper food [58].

If there is a certain connection between GDP and food waste at the household level, it is not a direct or simple one. First, a country’s GDP is the result of several factors, such as household consumption, investments, government expenditures, and net exports [59,60]. Therefore, we cannot conclude that an increase or decrease in GDP will automatically have a direct impact on household food waste.

Second, household food waste can be influenced by several internal and external factors, such as living standards, food habits, food education, food infrastructure and services, government policy, etc. These factors can vary from country to country and have a different impact on food waste.

However, there are some possible links between GDP and food waste at the household level. For example, an increase in GDP can bring an improvement in living standards and an increase in income, which can lead to a change in eating habits and a reduction in food waste [26,61]. Likewise, a stronger, more realistically adapted, and better-coordinated governmental policy on food waste management can be supported by a stronger and more stable economy.

In summary, there are some possible links between GDP and food waste at the household level, but these are complex and cannot be generalized without considering the specific context of each country. Overall, each particular context must refer to consumer behavior and consumption practices and habits.

In this context, e-commerce plays a pivotal role not only in enhancing economic efficiency but also in addressing pressing global challenges such as household food waste. As outlined by the United Nations’ Sustainable Development Goals, reducing food waste in general, and household food waste, in particular, is essential for responsible consumption and production (SDG 12.3). E-commerce can be a powerful tool in this fight, offering innovative solutions that optimize food distribution and consumption patterns. For instance, online platforms can help match supply with demand more accurately, reducing overproduction and surplus, which often lead to waste. Moreover, e-commerce facilitates better consumer education on food sustainability through targeted content and smarter purchasing options, potentially leading to more informed consumers who make choices that can reduce waste. The integration of e-commerce into the management of food systems promises not only to enhance economic growth, as evidenced by its correlation with GDP, but also to foster more sustainable consumer behaviors. This dual benefit underscores the importance of further interdisciplinary research into the nexus between e-commerce, economic indicators, and environmental sustainability [43,44,45,46].

Finally, the main potential venue for reducing household food waste is educating the population to develop responsibility and respect for food. For this purpose, the I_pFW indicator should be an important benchmark for the population’s educational level. Thus, the higher the GDP per capita per year will be (in thousands of USD), the lower the household food waste should be (in kg per capita per year). Therefore, assuming that the statement that a high individual financial standing implies a higher level of education is true, the I_pFW indicator proposed in this article should ideally be as high as possible. On the other hand, future research may look to target the behavior of children from a very early age to prevent the development of poor habits regarding food waste, in general, and household food waste, in particular [62,63].

One of the challenges with the SDGs regarding food waste is that while SDG 12 (Responsible Consumption and Production) includes targets for reducing food waste (specifically, SDG 12.3), there are difficulties in implementing efficient monitoring and quantification stages. Although the overall objective of SDG 12 is to ensure sustainable consumption and production patterns and it includes goals related to reducing waste and greenhouse gas emissions, the specific focus on household food waste needs clearer definitions and standardized measurement methods to be effectively addressed.

The SDGs do not provide a clear objective definition of household food waste, leading to varied interpretations across countries. Although SDG 12—target 12.3 addresses food loss and waste, the lack of a universal framework for monitoring and reporting progress makes it challenging to measure reductions accurately. Effective government policies with strong economic support are crucial for minimizing natural resource waste. To improve the effectiveness of the SDGs, a specific measurable target for reducing food waste is necessary, along with a universally accepted definition and robust monitoring system. E-commerce can support this by offering innovative tools for tracking and analyzing food consumption, aiding in setting precise targets and accurately assessing progress.