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Research Article

Can economic development be a driver of food system sustainability? Empirical evidence from a global sustainability index and a multi-country analysis

Roles Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Supervision, Validation, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation The Alliance Bioversity–International Center for Tropical Agriculture, Cali, Valle del Cauca, Colombia

Roles Formal analysis, Writing – original draft, Writing – review & editing

Affiliation Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States of America

Roles Data curation, Formal analysis, Investigation, Visualization

Roles Formal analysis, Methodology, Writing – original draft, Writing – review & editing

• Christophe Béné, 
• Jessica Fanzo, 
• Harold A. Achicanoy, 

• Published: May 23, 2022
• https://doi.org/10.1371/journal.pstr.0000013
• Reader Comments

Despite representing a growing element of the international community’s discourse, the sustainability of food systems and the challenge of its empirical measurement are still highly debated. In this paper, we propose to address this gap by computing a global food system sustainability index which we then use in a cross-country analysis covering 94 countries in low-, middle- and high-income regions. The analysis reveals a strong non-linear but positive correlation between the food system sustainability index and countries’ individual GDP per capita. This relationship suggests some possible degree of endogeneity between food system sustainability and economic development. We then use the Shared Socioeconomic Pathways framework and Individual Conditional Expectations modeling techniques to explore how the sustainability of food systems is projected to evolve in the future as countries move up the economic development ladder. The projections indicate that for lower income countries, the change is usually more significant than for higher income countries. The analysis also reveals that the different dimensions of sustainability will not all contribute equally to future improvements in food system sustainability. In particular, investments targeting social and food security & nutrition dimensions are projected to have a greater effect on the sustainability of food systems than investment/interventions aiming at the environment or economic domains. For countries located at the lower end of the economic development spectrum, this would imply that, even with limited resources, policy-makers could substantially improve the sustainability of countries’ food systems by prioritizing (sub)national policies and interventions focused on social and food security & nutrition domains.

Author summary

How sustainable are our food systems? Answering this question is important from both a research and a policy perspective. Without a better understanding of how sustainable (or unsustainable) our current food systems are, and what drives this (un)sustainability, decision-makers are left with little information on what to do -or what to prioritize- to overcome malnutrition and hunger while at the same time reducing the environmental or social impacts of our food systems’ economic activities. In this paper we aim to address those questions. For this purpose, we build a global food system index that “gauges” how sustainable food systems are, and we apply this index to a set of low-, middle- and higher-income countries across the globe. We then use modeling techniques to predict how the sustainability of food systems as we observe them today may evolve in the future as lower income countries move up the economic development ladder. We conclude with specific reflections on the importance of this work for policy prioritization amongst the trade-offs that characterize food system interventions.

Citation: Béné C, Fanzo J, Achicanoy HA, Lundy M (2022) Can economic development be a driver of food system sustainability? Empirical evidence from a global sustainability index and a multi-country analysis. PLOS Sustain Transform 1(5): e0000013. https://doi.org/10.1371/journal.pstr.0000013

Editor: Prajal Pradhan, Potsdam Institute for Climate Impact Research (PIK), GERMANY

Received: October 5, 2021; Accepted: March 29, 2022; Published: May 23, 2022

Copyright: © 2022 Béné et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: Data available at Harvard Dataverse, https://doi.org/10.7910/DVN/GYEG59 .

Funding: CB, HAA and ML received financial support from the flagship Food Systems for Healthier Diets under the CGIAR Agriculture for Health and Nutrition Program. The funders however had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors declare no competing interests.

Introduction

Now more than ever the question of the sustainability of our food systems is at the core of the international development discourse. Sustainable food systems are increasingly central to the United Nations’ 2030 Sustainable Development Goals (SDGs), with the achievement of many SDGs tied closely to the performance of local and global food systems [ 1 – 3 ]. This link between SDGs and the sustainability of food systems was restated more recently through the vision of the UN Food System Summit where there were promises to make “progress on all 17 Sustainable Development Goals (SDGs), each of which [relying] on healthier, more sustainable and more equitable food systems” [ 4 ].

Yet, despite representing a growing part of the international community’s discourse, ‘sustainable food systems’ are still a contested concept debated by a multitude of actors using different—and sometimes substantially divergent—views and frameworks [ 5 – 7 ]. Although some elements of consensus are emerging on what a sustainable food system should look like [ 2 , 8 ], researchers and analysts still struggle with one basic question: How can we define and empirically measure food systems’ sustainability?

This question of defining and measuring food systems’ sustainability is critical [ 9 ]. In a global environment with increasing calls for food system transformation, e.g., [ 10 – 12 ], one needs to know not just the meaning of transformation [ 13 – 15 ] but also the direction and outcomes one should be aiming at [ 16 ]. Without a good understanding of what exactly food system sustainability entails and how to measure or to monitor progress towards it, it will be difficult for decision-makers to make appropriate decisions or to design suitable policies to nudge food systems in the direction of a more sustainable global outcome for all [ 9 ].

Along with this question of measuring sustainability lie many other key challenges, including the identification and prioritization of relevant intervention areas for transformation. Indeed, if food system sustainability depends on so many dimensions—nutrition, food security, environment, e.g., [ 17 , 11 ], but also economic development, social/equity [ 18 – 20 ] or even cultural dimensions [ 21 ]—then how can we help decision-makers navigate those different outcomes and their trade-offs? For countries with scarce resources and capacities, this question is even more critical as it is not just about better understanding of what drives the sustainability of their food systems, e.g., [ 2 , 18 , 22 ], but also about how to make choices, sequence, and (re)direct limited resources toward the most judicious interventions. In this context, the role of economic development in contributing to the sustainability (or unsustainability) of food system is of central importance. Can countries simply rely on industrial modernization of food and agricultural sectors to expect to see their food systems become more sustainable, or should they instead invest in more specific interventions?

Building on some of the most recent food system sustainability frameworks [ 3 , 17 , 23 – 26 ], the objective of this paper is to address these important questions. To tackle this challenge, the paper starts by unpacking some of the elements and dimensions of food systems, looking in particular at the potential key determinants of their sustainability, and then explores more thoroughly the respective contributions that each of those different dimensions makes in relation to the system’s holistic outcomes. The analysis, however, does not just revisit and expand the many theoretical frameworks that have been proposed recently, e.g., [ 8 , 27 ]. Instead, it aims to ground the discussion more empirically into the real world. For this, it uses data from a cross-country database covering 94 countries and expands an existing global food system sustainability index. Following this analysis, we critically discuss our assumptions and explore some of the policy implications that emerge from our findings, with the objective to contribute to the rapidly growing body of literature that discusses the challenging task of linking food systems with sustainability.

Empirical food system sustainability indices–a rapid review

A large and rapidly growing body of literature is now available which proposes various frameworks and/or metrics aiming at defining or measuring food systems’ sustainability, e.g., [ 8 , 27 – 30 ]. The majority of these frameworks reflects a holistic approach and embraces the multi-sectoral and multi-outcome nature of food systems. Yet, while several of those frameworks are based on empirical data, e.g., [ 31 ], a larger number of them remain essentially conceptual or theoretical, e.g., [ 8 , 27 ], and as such do not provide the empirical elements which are necessary to measure concretely food systems’ sustainability.

Within this literature, a smaller number of papers propose to tackle the measure of food system sustainability more concretely. Chaudhary and his colleagues [ 25 ], for instance, build on several years of collaboration with other experts—see, e.g., [ 17 , 32 , 33 ]—to develop a framework that combines several dimensions and their associated indicators aimed at quantifying empirically food system sustainability. Expanding Gustafson et al. [ 17 ]’s earlier work beyond the original nine countries for which the metrics had been initially computed, Chaudhary et al. [ 25 ] proposed to measure the sustainability of food systems in 156 countries. The lack of data in several of those countries forced these authors, however, to rely on regional extrapolations for several of their proposed indicators.

The Food Sustainability Index (FSI) developed by the Economist’s Intelligence Unit is another attempt to advance empirical research on food system sustainability measurement based on three specific dimensions: food loss and waste; sustainable agriculture; and malnutrition [ 24 ]. The ambition of the FSI has been limited however by the low data availability that characterizes many regions of the world. As a consequence, the FSI has so far been computed only for 67 countries—essentially high-income countries for which data availability is generally better than in lower income countries. Beyond this issue of representativeness, some would also argue that the three domains included in the FSI (food loss and waste, sustainable agriculture and malnutrition) capture only partially food system sustainability and that other dimensions such as social or economic considerations should also be considered [ 21 , 34 ].

In parallel to those endeavors, Fanzo and her colleagues recently developed a new tool, the Food System Dashboard [ 35 ] with the objective to offer a holistic overview of the key components of countries’ food systems. For this purpose, the Dashboard includes over 215 indicators covering most food system components. It does not provide, however, any clear or explicit normative element leading toward food systems’ sustainability (it simply provides a snapshot of the current situation); nor does it attempt to combine the different indicators it collates into a single combined index.

A few other papers explore alternative approaches to measure food system sustainability. Most of these studies, however, offer indices that don’t cover well the entire food system. Zhang et al. [ 31 ] for instance develop a multi-dimensional sustainability index that focuses on the agricultural sector only, thus, overlooking the other components of food system (processing, storage, distribution, etc.). Other studies propose to work at the local or subnational scales, e.g., [ 30 , 36 ], and, as such, are not suitable for global multi-country assessments. In some other cases, while offering an international dimension, the proposed indices don’t embrace the multi-dimensional nature of the concept of sustainability. Fridman and his colleagues [ 37 ], for instance, integrate four food staples (wheat, rice, maize, and soybeans) but they consider only the inter-country trade impact of those four staples on the environment (measured in terms of land and water usage). Their framework therefore only accounts for one dimension of sustainability (the environment), subsequently missing other key dimensions as well as a significant number of other commodities beyond the four staples considered.

In this paper, we propose to build on Béné and his colleagues’ global sustainability index. Béné et al. [ 26 ]’s index considers four dimensions of food system sustainability (food security & nutrition, environment, economic and social dimensions) and covers 97 countries from low, middle and high-income regions. As such, it offers one of the most systemic indices of food system sustainability. One limitation of this index, however, is that the four dimensions are not equally represented, with both the economic and social dimensions depending on a limited number of indicators. In the present paper, we propose to build an extended version of Béné’s sustainability index by adding several indicators to the two dimensions where the representativity was weak: the social and economic dimensions. We then use the newly created extended index to explore some of the key questions raised earlier in the introduction. In particular, we investigate whether all four dimensions of the index contribute equally to the change observed in the sustainability of food systems across countries, or whether some dimensions are more important than others, and if so, which dimension(s) and for which (group of) countries.

As part of this research, the question of the relationship between food system sustainability and economic development will receive a particular attention. Until recently, policy debates have often raised the question of whether positive changes in societies could ‘naturally’ follow economic development. A first example of this is the Kuznets curve where it was posited that, after an initial increase, inequality in societies would progressively decline as countries’ economies develop further [ 38 ]. Expending this initial idea beyond income inequality, an environmental Kuznets curve hypothesis was later proposed, e.g., [ 39 , 40 ], whereby environmental health indicators would also follow a U-shaped curve and eventually improve as per capita income and GDP rise. Although those assumptions have not been confirmed empirically, see, e.g., [ 41 ], a question rises as whether a similar pattern could be observed with food systems sustainability. Is it indeed possible to envisage that countries within the high-income group (e.g., OECD countries) perform better in terms of aggregated food system sustainability than countries in the lower-income country group, especially if the social or economic dimensions of food system sustainability are considered? Or, is it possible that higher-income countries have a much more unsustainable food systems than lower-income countries, especially when one considers consumption of ultra-processed food per capita or even, perhaps, the environmental food print of their respective food systems?

To explore those different questions, the paper will follow a two-step approach. First, a series of descriptive analyses built around the computation of the ‘extended’ global food system sustainability index (GFSSI) will be presented. We will use this part of the analysis to also highlight some of the strengths of the GFSSI. Then, in a second part, we will use modeling techniques to explore how the sustainability of food systems is likely to evolve in the future as countries move up the economic development ladder. Underlying these analyses is our desire to better understand the determinants and dynamics of food systems, in the hopes that answers to these interrogations can provide useful and policy-relevant insights into decisions made regarding the transformation of food systems toward sustainability [ 9 , 12 , 16 ].

GFSSI computation

The starting point of our approach was to build on and expand the global food system sustainability index (GFSSI) developed by Béné et al. [ 26 ]. In its original version, the GFSSI employed a clear and rigorous inclusion/exclusion process based on 10 criteria ( Table 1 ) to select indicators. These included conventional criteria such as ‘clear methodology’ and ‘conceptual relevance’ (see detailed definition in Table 1 ), but also other, more specific, criteria that were deemed to be instrumental to build the GFSSI such as ‘global scale’—reflecting the fact that the indicators needed to be available for at least 70 countries to be considered as ‘global’—or the ‘cross-correlation’ criterion where only one indicator amongst a group of indicators known to be cross-correlated (e.g. wasting and stunting) would be included in the index, in order to avoid misspecification. Those inclusion/exclusion criteria were initially compiled by Béné et al. [ 26 ] to address some of the most common and important issues encountered in the literature on food system sustainability indices, including: (i) lack of representativeness (that is, the fact that, because of data availability issues, a large proportion of the countries included in those analyses are often high-income countries -as in, e.g., [ 24 ]; (ii) lack of conceptual clarity on how the different dimensions of food system sustainability are constructed and delimited, see, e.g., [ 25 , 31 , 37 ]; and (iii) replication and/or strong cross-correlation amongst indicators, see, e.g., [ 24 , 32 ].

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https://doi.org/10.1371/journal.pstr.0000013.t001

One of the important advantages of using such a set of inclusion/exclusion criteria is that all the indicators that were eventually included in the index are global and tractable, meaning they have measurable values that are publicly available for all countries included in the GFSSI. Another important consideration was the directionality of these indicators. Were excluded indicators that do not have a clear directionality (positive or negative) within the dimension to which they were associated. The objective was to ensure the coherence of the aggregated GFSSI. Here, ‘coherence’ does not refer to conceptual coherence, but to the statistical property of the aggregated index, in the sense described in [ 42 ]: if two or more of the dimensions were negatively correlated with each other, this would mean that a change in the aggregated index in one direction (increase or decrease) could happen while some of the dimensions within the index are moving in the opposite direction. This would indicate a flaw in the construction of the GFSSI [ 42 ].

Finally, a central property of the GFSSI was the explicit ambition to offer a true, systemic, framework and, in doing so, to embrace a holistic interpretation of sustainability. As such, the GFSSI does not consider only trade-offs between the need to produce more healthy/nutritious food and the urgency to reduce the environmental impacts of such activities, e.g., [ 11 , 43 ]. Rather the GFSSI comprises the four key dimensions that are more generally recognized to constitute food system sustainability, namely food security & nutrition, environmental, social and economic dimensions.

Each of four dimensions was then disaggregated into individual sets of sub-dimensions included to ensure the conceptual comprehensiveness of the indicators. For instance, for the environmental dimensions, the sub-dimensions considered include quality of air, water, soil & land, and level of biodiversity, while for the food security & nutrition dimension, the sub-dimensions include indicators that reflect the four pillars of food security (availability, access, utilization and stability–[ 44 ], complemented by key indicators capturing the other dimensions central to this dimension of sustainability: food safety, food waste and losses, diet quality, obesity and micro-nutrient deficiency [ 45 – 48 ]. Those dimensions and sub-dimensions are presented in Table 2 and their details are provided in S1 Table in Supporting material .

The * symbols indicate indicators that have been ‘flipped’ to ensure the coherence of the GFSSI (see details in text). Source of the individual datasets indicated in S1 Table .

https://doi.org/10.1371/journal.pstr.0000013.t002

At the same time, some of the GFSSI strengths (such as the inclusion of those four dimensions of sustainability) also constitute its main weakness, at least in the original version proposed by Béné and his colleagues [ 26 ]. In that initial version, both the social and economic dimensions were represented through one indicator only. We addressed this by adding nine new indicators to increase the representativity of these two dimensions. This raises the total number of indicators in the expanded version of the GFSSI to 29, thus achieving a more ‘balanced’ representation between the four dimensions: six indicators for the environmental dimension; seven indicators for the economic dimensions; four indicators for the social dimension; and 12 indicators for the food security and nutrition dimension.

Expanding the number of indicators to 29, however, means we had to drop three countries for which some of those new indicators’ datasets were not available. The new GFSSI proposes therefore a sustainability index covering 94 countries (instead of the initial 97) across the range of low (N = 17), middle (N = 49) and high-income countries (N = 28). Importantly the process was designed so that the GFSSI is calculated with the exact same set of 29 individual indicators for every country, making those 94 countries strictly comparable in terms of their individual index. The datasets used to build the GFSSI were retrieved from the Harvard Dataverse [ 49 ] where they are stored, to which we added the datasets for the nine new indicators. The six new economic indicators focus essentially on the economic performances and efficiency of food systems to produce nutritious (and non-nutritious) foods. This speaks directly to the recent attention paid in the international community to the issue of ‘affordability of healthy diets’ [ 50 ]. The three new indicators added to the social dimension of the GFSSI refer to the existence of particular policies assumed to contribute positively to the sustainability of the index’s social dimension. For those, we did not, however, simply use a binary value (absence = 0; presence = 1) but used instead the number of years since these policies were first implemented (thus, the earlier the beginning of the implementation in a country, the higher the indicator values for that country).

A Box Cox transformation was applied to the most skewed indicators–i.e., those with a |Skew(x)– 0| > 2 –to improve the normality of distribution and avoid potential issues related to heteroskedastic dataset distributions. Once transformed, the indicators were normalized using a standard (rescaling) min-max transformation with a [0, 1] range. Indicators expected to have a negative effect on sustainability within their own dimension were then ‘flipped’ (i.e., inverted) so that all indicators had the same directionality–a critical condition to ensure the coherence of the approach in the case of a composite index (test of internal consistency–see [ 42 ]). For the few indicators for which a ‘middle value’ is considered optimum (e.g., water pH around 7), data were transformed to measure the distance away from that optimum value in both directions.

Modeling sustainability of food systems and Gross Domestic Product

The modeling analysis aimed to explore the possible association between sustainability of food systems and Gross Domestic Product (GDP) per capita (used as a proxy for economic development). To explore this possibility, we developed a two-step modeling approach, building on some of the results obtained in the first part of the paper, and used the ‘Middle of the Road’ scenario (SSP2) from the Shared Socioeconomic Pathway [ 53 ] to assess how changes in GDP per capita may affect countries’ food system sustainability in the future.

The Shared Socioeconomic Pathways (SSPs) framework provides narratives describing alternative socio-economic developments up to 2100, based on projected changes in world population, urbanization, and GDP per capita [ 54 ]. The Middle of the Road scenario (i.e., SSP2 in the SSP five-scenario framework) was chosen as it is equivalent to assuming a continuation of current economic development path (i.e., a business-as-usual scenario) in the future. We used the change in GDP per capita as projected between 2015 and 2050 by the SSP2 as input in our modeling analysis.

The two-step modeling approach included a first step where the effects of change in GDP per capita on the individual dimensions of the GFSSI were estimated using a series of Generalized Additive Models (GAM) run between the GDP per capita and the four dimensions of the GFSSI considered separately. GAM were initially chosen because they allow semi-parametric fits with relaxed assumptions on the actual relationship between dependent and explanatory variables, thus providing potential for better fits to data than purely parametric models (potentially with some loss of interpretability -see [ 55 , 56 ]). For three of the four models this approach turned out to be effective and the GAM provided the best fitted model. The Akaike information criterion (AIC) was used to confirm this against a whole set of other parametric models (see S2 Table ). For the food security and nutrition dimension, however, a fitted log-model generated a better fit. That log-model was therefore used in the rest of the analysis for the food security and nutrition dimension along with the GAM models used for the three other dimensions.

Once those different models were estimated, we used them in the second step of the modeling analysis to compute the effects of the changes in each dimension on the GFSSI aggregated value, using Individual Conditional Expectations (ICE) computations [ 57 , 58 ]. The one-dimensional profiles constructed with those ICE models was used to estimate the dependence of the conditional expectation of the dependent variable (the aggregated GFSSI) on the values of the particular explanatory variables (the four dimensions of the GFSSI) taken individually. The idea was to determine the respective contribution of each dimension of the GFSSI ( ceteris paribus ) to the overall change in its aggregated value over time. The computations were made using the command DALEX in R (version 4.0.2). Underlying this analysis was the key assumption that the relationship as we observe it today between food system sustainability and GDP per capita across countries (used in step 1) is a reasonable proxy for the way it will evolve over time at country level (used in step 2). In other terms, we assumed that lower income countries will continue to evolve in the future along a path which is not too different from the path that higher income countries have followed so far.

Descriptive analysis

The first step in the analysis was to check the statistical coherence of the aggregated GFSSI by confirming that the four dimensions of the index all vary in the same direction [ 42 ]. Fig 1 shows the cross-correlation matrix between the four dimensions of the GFSSI. It indicates that the four dimensions positively correlate with each other (with values varying from +0.11 to +0.69), confirming the coherence of the index, thus allowing us to continue the analysis.

Numbers represent Pearson correlation coefficients; ellipses represent the strength and direction of the correlation.

https://doi.org/10.1371/journal.pstr.0000013.g001

Fig 2 shows the GFSSI for the 94 countries for which data were available. Several key observations emerge from this global map. First, the index ranges from very low values (dark red) in some countries (e.g., Egypt, Mali, Pakistan, Myanmar) to middle range values (orange) in countries such as Brazil, India, Indonesia, to high or very high values (light beige) in others (e.g., Canada, France, Spain), suggesting a heterogeneity in terms of the level of food system sustainability across the world. Second, although the GFSSI could not be calculated for several countries in Africa and West Asia, a clear trend emerges, with low- and middle-income countries displaying, on average, lower sustainable values than countries belonging to the higher-income country group.

Red = lower level of sustainability, beige higher level of sustainability (map source: https://gadm.org/ ).

https://doi.org/10.1371/journal.pstr.0000013.g002

This apparent trend is also observable in Fig 3 in the form of a clear positive relationship between the GFSSI (Y-axis) and the GDP per capita (X-axis). The correlation is highly significant (Spearman coefficient ρ = 0.81, p <0.001) and considered “very strong” ( ρ ≥ 0.8) [ 59 ]. The relationship does not appear strictly linear, however, but log-shaped, indicating that, while countries’ food system sustainability scores increase very rapidly with GDP per capita amongst the ‘poorest’ countries, the relationship then plateaus and countries with higher GDP per capita are characterized by a much flatter relationship.

The correlation is highly significant (Spearman coefficient ρ = 0.81, p<0.001) and ‘very strong’ (as per [ 59 ]’s 5-scale system). The blue line corresponds to the fit of a logarithmic regression model (adjusted R 2 = 0.6391). Five countries (Sudan, Ecuador, Czech Republic, Switzerland, Norway) have been highlighted for illustration purpose.

https://doi.org/10.1371/journal.pstr.0000013.g003

Categorizing the countries using either the World Bank’s low-, middle-, and high-income categories or grouping them by income terciles confirms the positive relationship between food system sustainability and GDP per capita: countries with higher GDP per capita are, on average, characterized by higher food system sustainability scores (see Fig 4 ). Non-parametric Kruskal-Wallis tests confirm that the differences are statistically significant for both World Bank (χ 2 (0.95,2) = 44.2; p < 0.001) and tercile groupings (χ 2 (0.95,2) = 57.79; p < 0.001) despite some relatively large variances, especially for middle-income and tercile 2 groups respectively. For the World Bank grouping, note also that the proportions of low, middle, and high-income countries amongst the 94 countries are 18% (L), 52% (M), and 30% (H), which is remarkably close to the proportions observed for the 218 countries and other regions listed in the World Bank 2019 list, respectively: 14% (L); 49% (M); 37% (H), thus suggesting that, if any, the risk of selection bias affecting our findings is relatively low.

Level of countries’ food system sustainability scores (means and 95% confidence intervals) for countries grouped according to (a) the World Bank’s low, middle, high-income groups (left) or (b) by terciles (right). (World Bank groups: N = 17, 49, and 28 for low, middle, and high-income countries respectively. Terciles: N = 31 for terc_1 and terc_2; and N = 32 for Terc_3). Non-parametric Kruskal-Wallis tests conducted on both World Bank and tercile groupings confirm that the differences are statistically significant for both groupings: χ 2 (0.95,2) = 44.2; p< 0.001 for World Bank; and χ 2 (0.95,2) = 57.79; p< 0.001 for tercile grouping.

https://doi.org/10.1371/journal.pstr.0000013.g004

Fig 5 examines the contribution of each of the 29 individual indicators to the aggregated GFSSI. Since the 29 indicators had been transformed and, when necessary, ‘flipped’ to ensure an appropriate directionality (that is, an increase in any of those indicators would theoretically be associated with a higher sustainability score in their own dimension), we would have expected the correlation coefficients between all 29 indicators and the aggregated index to be positive. The results indicate however that three indicators display negative coefficients: ( i ) the (flipped) retail value of ultra-processed food sales per capita; ( ii ) the relative caloric price of salt-rich foods and soft drinks and ( iii ) the (flipped) prevalence of obesity. What this indicates is that, as countries’ overall sustainability indexes improve (essentially as countries move up the economic development ladder and increase their GDP per capita), these three indicators are moving in the opposite direction, suggesting that they are not improving with the aggregated sustainability index. This means that the changes in these three indicators (ultra-processed food sales; consumption of salt-rich foods and soft drinks; and obesity prevalence) are negative (i.e., getting worse) as countries’ GDPs per capita increase and the countries’ overall GFSSIs improve.

Cross-correlation matrix of the 29 indicators and the GFSSI (last column one on the right). Note the only three negative (and relatively strong) correlations observed between the GFSSI and (1) the retail value of ultra-processed food sales per capita; (2) the relative caloric price of salt-rich foods and soft drinks and (3) the prevalence of obesity.

https://doi.org/10.1371/journal.pstr.0000013.g005

Dynamic analysis

The next step in the analysis was to revisit some of those results from a dynamic perspective. For this, we used the two-step modeling approach described in the methodology section. First, the effects of change in GDP per capita on each of the four individual dimensions of the index were estimated using Generalized Additive Models ( S1 Fig ). The results were then used in the second step to calculate the effects of future changes in each of those dimensions on the aggregate index for the period 2015–2050 under a ‘business-as-usual’ SSP2 scenario. Fig 6 shows the results of the SSP2 projection. The four graphs display the projected changes in countries’ sustainable index, broken down by dimensions (food security & nutrition, environment, economic and social dimensions) between 2015 and 2050. To facilitate the analysis, countries have been grouped into geographical regions: South Asia, sub-Sahara Africa, East Asia and the Pacific, Latin America and the Caribbean, Europe and central Asia, Arab states, and a group of ‘developed’ countries (Individual countries results are displayed in S2 Fig ).

Green dots: 2015 values, red dots: 2050 projected values. Eco = economic dimension; Env = environmental dimension; FS&N = food security & nutrition; Soc = social/policy dimension.

https://doi.org/10.1371/journal.pstr.0000013.g006

Fig 6 shows that amongst the four dimensions of the index, social dimension and food security & nutrition are the two dimensions for which a larger number of countries across the different regions/groups show significant improvements in their individual sustainability scores. This suggests that the projected increase in GDP per capita under the SSP2 scenario is associated with the largest changes in the GFSSI through the improvements induced in the social and food security & nutrition dimensions. In comparison, the projected changes on environment and economic dimensions are much more modest across all countries’ regional groups.

More specifically, Sub-Sahara Africa, South Asian, and East Asia and the Pacific are the regions for which the improvements in the food security & nutrition and social dimensions are projected to be the largest. The group of Arab States is also projected to show significant improvement in their social dimension. In contrast, the group of developed countries display almost no improvement in their individual sustainability index for all four dimensions. In fact, for the economic dimension, they even show a slight decline in the GFSSI (top-left quadrant).

In this paper, we explore the empirical question of the sustainability of food systems and its measurement, and how this sustainability may evolve as countries move along their economic development paths. Several approaches have been proposed recently in the literature to measure or to assess food systems’ sustainability at a global, multi-country level, see e.g., [ 3 , 17 , 24 – 26 ]. A review of those analyses reveals, however, a number of methodological or conceptual challenges that impede or slow down progress. Several of those challenges relate to the fact that those analyses often adopt a relatively narrow interpretation of sustainability and/or of food systems, either by focusing only on the trade-offs between the need to produce and consume more nutritious food and the resulting environmental impacts (thus overlooking the more social and economic/policy-related aspects e.g., [ 11 ]), or by considering ‘sustainable diets’, e.g. [ 23 , 60 , 61 ], as opposed to ‘sustainable food systems’, e.g. [ 25 , 26 , 35 ]. Some comprehensive frameworks exist, e.g., [ 8 , 27 ], but those are mostly theoretical or conceptual and many of their proposed indicators don’t have associated (publicly) available datasets, making these frameworks non-operational and of lower relevance for decision-makers [ 7 ].

In this context, one of the ambitions of this analysis was to show it is possible to build a holistic index that embraces the multi-dimensional nature of food systems’ sustainability, yet remains representative not just of a few (higher-income) countries but more globally of a number of low-, middle- and high-income countries. To do so, we expanded Béné et al. [ 26 ]’s initial framework by adding nine new indicators to the two dimensions of their global index for which the number of indicators was the lowest (social and economic dimensions), while managing to retain 94 of their initial 97 countries. We argue that those different features make the GFSSI comprehensive yet operational. It is comprehensive in the sense that four different dimensions of sustainability are considered (food security & nutrition; environmental, social/policy and economic dimensions), each of them broken down further into a combination of sub-dimensions that ensure the conceptual coherency of the indicators. At the same time, the GFSSI remains operational and tractable as all those indicators have measurable values that are publicly available for all 94 countries -70% of those 94 countries being low- or middle-income countries. Finally, the selection of these indicators relied on a rigorous and transparent protocol based on a set of ten clear inclusion/exclusion criteria.

Some caveats need to be kept in mind before discussing the results. First, this analysis presents data at the global aggregate level. Disaggregated data at the sub-national level is scant, and there is a need for more data granularity by geographic location at sub-national levels [ 62 ]. Second, and most importantly, correlation does not mean causality. In this context, the relationship observed between countries’ level of food system sustainability and GDPs per capita remains at this stage an empirical correlation. In other terms, we do not claim that GDP per capita is a driver of food system sustainability (and we paid attention throughout the paper not to make this confounding statement). In fact, like in the case of the environment, e.g. [ 41 ], there is growing evidence that economic growth does not necessarily result in beneficial outcomes from a food system perspective. In particular, in some high-income countries, obesity and diet-related non-communicable diseases, and environmental sustainability remain significant issues [ 63 – 65 ].

Our analysis, however, also indicates that, when the sustainability of the food system is conceptualized not just based on food security/nutrition and environment outcomes but with a more holistic framework that also encompasses social and economic considerations, countries characterized by high economic development levels (measured through GDP per capita) are also amongst the group of countries with higher food system sustainability scores. In contrast, countries at the ‘bottom’ of the food system sustainability ranking also appear to belong to the low-income country group ( Fig 1 ). Furthermore, because this result is based on a large but relatively balanced number of indicators between the four dimensions of the index, it indicates that this cross-country pattern is relatively ‘robust’ and not just an artifact of the composition of the index.

Sustainability and GDP

It is not the first time that the question of the sustainability of food system and its correlation to GDP is raised. Chaudhary et al. [ 25 ] for instance discuss this relationship in their food systems’ multi-indicator sustainability analysis (see in particular their Table 1 p.2). These authors however only consider the correlations between GDP per capita and the 25 individual indicators included in their analysis. They find that several of those indicators are strongly correlated to GDP per capita (either positively, e.g., Food Availability Score or Food Safety Score, or negatively, e.g., per-capita GHG emissions); but they do not attempt to extrapolate what this would mean for an aggregated sustainability index.

The empirical correlation observed in our analysis between GDP per capita and the aggregate GFSSI suggests some possible degree of endogeneity between food system sustainability and economic development. From a macro-economic perspective, the presence of this potential endogeneity is an important result. It does not imply any form of direct causality (see above); but it suggests that some of the internal processes and variables driving GDP per capita may also be driving food system sustainability. To some extent, this result is not completely unexpected given that some of the key variables known to be important drivers of GDP per capita -such as income or foreign investments- have also been shown to be important drivers of food system transition [ 2 , 18 ]. What was unclear until now, however, was how the combination of all those different variables influence the overarching, emerging sustainability of food systems. Taken individually, some economic, social or environmental variables that are generally observed (or expected) to improve with economic development (such as gender and social equity, decency of jobs, reduction in undernutrition) are also assumed to contribute positively to the sustainability of food systems, e.g., [ 25 , 66 ]. Other processes, however, which also increase with economic development are known to contribute negatively to the sustainability of food systems (e.g., GHG emission, deforestation, prevalence of obesity) [ 43 , 67 ]. What our study shows is that the overarching sustainability of food systems that emerges from this combination of 29 different indicators is eventually positively aligned with economic development. In essence, our analysis suggests that food system sustainability and economic development coevolve over time. The term coevolution is used here purposively to refer to the empirical observation by which both processes appear interrelated and are moving simultaneously in the same direction as time passes.

The data revealed, however, that this coevolution is not a strict linear relationship. Although higher-income countries do have on average higher food system sustainability scores than countries in the lower-income groups ( Fig 4 ), the positive trend observed between GDP per capita and food system sustainability flattens relatively rapidly ( Fig 3 ) and the sustainability of food systems eventually stops improving for the economically more advanced countries.

Beyond the non-linearity of this relationship, the data also reveals that the coevolution of food system sustainability and economic development is not ‘infallible’. Some countries appear as ‘outliers’ and fall well outside the trend. In particular, a certain number of countries display a much higher GFSSI than one would have predicted based on their level of GDP per capita; this is the case of Malaysia in the middle-income country group and Canada in the high-income countries ( Fig 7 ). In contrast, some countries are doing worse than would be expected: Saudi Arabia and Kuwait are two examples amongst the high-income country group. Because each indicator and each dimension has been weighted equally in the computation of the aggregated GFSSI (see methodology section), the large divergence observed for those particular countries cannot simply be explained by the effect of one or two ‘outlying’ indicators; it suggests instead an overall difference (either positive or negative) across the 29 indicators. Exploring more thoroughly why particular countries fall well aside the general trend would require country-specific analyses and, as such, is beyond the scope of this initial analysis. Studying positive or negative deviants could, however, unveil important information.

https://doi.org/10.1371/journal.pstr.0000013.g007

The data also revealed that some particular indicators can diverge from the positive trend linking global food system sustainability and economic development. In our case, the retail value of ultra-processed food sales per capita, the relative caloric price of salt-rich foods and soft drinks, and the prevalence of obesity all show negative correlations with their aggregate GFSSI ( Fig 5 ). These results suggest that the respective contributions of those three indicators to food system sustainability are negative, and eventually that these indicators move in the opposite directions as countries move up the economic development ladder. This observation is in line with the rest of the literature where sales of ultra-processed food, consumption of salt-rich foods and soft drinks, and prevalence of obesity are usually observed to increase in high-income countries -even though those global trends are being increasingly observed in low- and middle-income countries as well [ 68 , 69 ].

Dynamics of food system sustainability

Building on those various empirical results, Individual Conditional Expectations (ICE) models were then used to explore further the dynamics of food system sustainability. Through this modeling we were especially interested in determining how the sustainability of food systems will evolve in the future as lower-income countries continue their economic development, and whether all dimensions of their GFSSI (food security & nutrition; environment; social; and economic dimensions) would contribute equally to the projected changes in these countries’ food systems sustainability. Underlying all those different interrogations was the quest for a better understanding of the determinants and dynamics of food systems sustainability.

Our results are contingent on some strong assumptions—especially the hypothesis that food systems in lower income countries will continue to evolve in the future along a transitional path relatively similar to the path that food systems have followed in higher income countries. Looked at from close range, this assumption is somewhat questionable if we agree that countries’ food systems generally follow distinct and individual transitional paths that are unique and specific to each country, reflecting the strong cultural, historical and socially-defined identity associated with food [ 70 , 71 ]. But we also know that beyond those specificities, food systems are all moving in similar directions and showing disturbing similarities/convergences across countries, including the “Westernalization of diets” [ 72 ], the “homogenization of crops” [ 73 ], the increased dependence on Genetically Modified Organisms [ 74 ], the general increase in consumption of ready-to-eat, convenient, cheap, and often ultra-processed foods [ 75 , 76 ] or the quasi-universal increase in demand/consumption of animal-based protein triggered by income rise [ 77 ]. The assumption of food system future transition perpetuating (or reproducing) the current trends is therefore not totally unrealistic and in the absence of any alternative grounded theory, this assumption can be seen as a reasonable starting point to (better) understand what will drive food system (un)sustainability in the future,—even if we stress that this interpretation needs to be made with caution.

The ICE models show that countries are not projected to improve their food system sustainability in an identical manner. For lower income countries, the improvement is usually more significant than for higher income countries ( Fig 6 ). For those higher income countries, the extent to which food system sustainability is projected to improve appears relatively limited. The analysis also reveals that the different dimensions of food system sustainability will not all contribute the same way to the change in GFSSI. Investments and interventions targeting social and food security & nutrition dimensions are projected to have a greater effect on the sustainability of food systems than investment/interventions aiming at the environment or economic domains ( Fig 6 ). In sum, despite the fact that the sustainability of food systems appears to coevolve with countries’ GDP per capita (a variable generally assumed to be closely related to economic dynamism), social and food security & nutrition are the dimensions where the effects of interventions are projected to be the largest.

Policy relevance

If our results are confirmed by other similar analyses, they will point at important policy implications. In particular, for countries located at the lower end of the economic development spectrum, this would imply that, even with limited resources, policy-makers would still be able to substantially improve the sustainability of their countries’ food systems by prioritizing (sub)national policies and interventions focused on social and food security & nutrition domains. These could include restricting marketing and advertising of ultra-processed foods to children [ 78 , 79 ], improving governance, policies and planning to support the role of informal actors in urban poor population’s food security, e.g. [ 19 , 80 ], or instituting labeling and fiscal policies such as taxation [ 81 – 83 ].

The locus of action for prioritizing, investing, and implementing improved food system performances falls therefore on national and sub-national actors engaged directly in food system governance. These actors are best positioned to identify, prioritize, and sequence interventions based on the needs of their food systems. Nonetheless, these domestic processes require support from a global architecture to identify common information gaps and promote efforts to fill these, facilitate knowledge exchange on the impacts of policies / interventions across diverse contexts, promote global compacts to hold multinational non-state actors accountable to common standards and ensure access to necessary financial support to implement these approaches particularly in lower-income countries [ 9 ]. Parts of this architecture exist and other components are under discussion in the aftermath of the UN Food System Summit. Moving from paper to practice, however, requires concerted effort from multiple parties over an extended period of time.

Within the wider literature, there is already a recognition that it will be difficult to achieve SDGs without food system sustainability [ 1 , 3 , 22 , 84 , 85 ]. All 17 SDGs are important but with less than ten years to achieve them, a mounting sense of urgency is emerging. In that regard, our work suggests that in order to achieve both the SDGs and the sustainability of food systems, focusing on particular SDGs may be especially important. Beyond (the obvious) Goal 2 devoted to ending hunger and malnutrition or Goal 12 encouraging responsible consumption and production, improvements in social dimensions seems to be key to increase sustainability. This suggests that the synergy between food system sustainability and SDGs will also depend on those other SDGs with specific emphasis on social objectives, such as, e.g., Goal 3 on health and well-being, Goal 5 on gender equality, Goal 8 on decent work, or Goal 10 on inequalities. Without investing in those objectives, countries will struggle to meet not only food system sustainability but their SDGs as well.

Beyond these specific reflections, this work demonstrates the necessity to rapidly develop analyses and tools that can allow exploring more dynamically and comprehensively food systems, investigating what drives them and how the different elements of those systems interact with each other and evolve over time [ 9 , 86 ]. At present, our ability to do so and to assess more holistically the consequences of food systems’ rapid transformations on different outcomes (food security, nutrition, environment, or social dimensions) is limited [ 87 ]. Part of this limitation derives from the generally incomplete, fragmented and static datasets that we have at our disposal at present. More effort and investments will have to be made in the coming years at (sub)national and international levels to address this gap [ 7 , 16 ]. Understanding the dynamics of food systems, how those dynamics affect trajectories toward sustainability, and how to measure this sustainability at the system level is indeed critical if we want to support policy-makers in designing and implementing appropriate policy and interventions.

In this paper, we develop a global food system sustainability index (GFSSI) built on 29 indicators and structured into four dimensions: food security & nutrition, environment, economic and social dimensions. We use this holistic index to assess the sustainability of national food systems across a set of 94 countries covering low, middle and high-income regions. The analysis revealed a strong positive correlation between countries’ food system sustainability and economic development, suggesting that, in general, countries characterized by higher (lower) economic development are also characterized by higher (lower) level of food sustainability. This coevolution is not a strictly linear and perfect one however, and some countries fall well outside (either above or below) the trend, thus emphasizing the need for more data granularity by geographic location at national or even subnational level -especially for large countries. Relying on modeling techniques, we then explore how this relationship is likely to evolve in the coming decades as countries move up the economic development ladder. The analysis reveals that countries are not projected to improve their food system sustainability in an identical manner. For lower income countries in particular, the changes are usually more significant/rapid than for higher income countries. The analysis also reveals that the different dimensions of sustainability considered in the GFSSI will not all contribute equally to future improvements in countries’ food system sustainability. Especially, investments targeting social and food security & nutrition dimensions are projected to have a greater effect on the sustainability of food systems than investment/interventions aiming at the environment or economic domains.

These different results and analyses are part of the emerging body of literature that discusses how to assess and measure food systems sustainability across countries. This literature generally aims at capturing the holistic nature of food systems while embracing the complex set of outcomes, driver metrics and trade-offs that characterize these food systems. Achieving consistent measurements of food system sustainability at a global scale remains challenging due to data limitations, methodological concerns and our nascent understanding of how different components interact with each other to deliver (or not) sustainable outcomes. Despite these challenges, the need for policy-relevant tools continues to grow as the recent UN Food System Summit highlighted. Governments still need to develop food system upgrading strategies -even with imperfect or decontextualized information- that can help them move towards greater sustainability while accounting for difficult trade-offs, specific development needs and limited investment capacities in the context of the SDGs. Tools that embrace the holistic nature of this challenge, based on consistent indicators and improved understanding of how components of the food system interact can help decision-makers see around the corner and design policies that are more effective. No one tool delivers all that is needed, but the global food system sustainability index (GFSSI) presented here, hopefully, takes an important step in this direction.

Supporting information

S1 fig. step 1 of the modeling: the four generalized additive models run between the gdp per capita and the four dimensions of the gfssi..

95% confidence intervals highlighted in grey. Social dimension adjusted R-squared: 0.4518; Food & nutrition adjusted R-squared: 0.81; Environment adjusted R-squared: 0.1448; Economic adjusted R-squared: 0.0953.

https://doi.org/10.1371/journal.pstr.0000013.s001

S2 Fig. Step 2 of the modeling: Projected changes in country sustainability index under a SSP2 scenario (Individual country’s results).

Green dots: 2015 values, red dots: 2050 projected values. Eco = economic dimension; Env = environmental dimension; Fnt = food security & nutrition; Soc = social/policy dimension.

https://doi.org/10.1371/journal.pstr.0000013.s002

S1 Table. The 29 indicators and their sources.

https://doi.org/10.1371/journal.pstr.0000013.s003

S2 Table. Akaike information criterion (AIC) (and adjusted R2 and level of significance in brackets) for the different models tested as part of step 1 of the modeling analysis.

In shade gray the models which were retained based on their AIC scores.

https://doi.org/10.1371/journal.pstr.0000013.s004

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• Published: 31 October 2022

Food insecurity

Nature Climate Change volume  12 ,  page 963 ( 2022 ) Cite this article

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Climate change is a confounding factor that can affect agriculture and food security in many different ways. Climate-resilient food systems are needed to ensure food security and to support mitigation efforts.

World Food Day — 16 October, with the theme this year of ‘leave no one behind’ — is an appropriate time to reflect on global progress toward Sustainable Development Goal 2: Zero Hunger. The 2022 Global Hunger Index, released October 2022 ( https://www.globalhungerindex.org/ ), highlights that progress has stagnated, with the war in Ukraine, climate change and related extreme events, and the related increased price of food, fuel and fertilizer all contributing. The 2022 Global Hunger Index report 1 highlights that 44 countries are currently suffering serious or alarming levels of hunger, although there is large within-country variability. The report estimates that 828 million people are currently undernourished, with parts of Africa south of the Sahara and South Asia having the highest hunger levels, and being the most vulnerable to future shocks.

Climate change can affect crops in different ways and the impacts of climate change due to higher levels of atmospheric CO 2 are often deleterious. While higher levels of atmospheric CO 2 may enhance photosynthesis and growth in some crops 2 , there isn’t a clear picture on the overall effects on crops. Further, it has been reported that plants grown under higher CO 2 levels have changed nutritional value 3 .

Warming temperatures due to climate change also impact crop productivity, with an example discussed in this issue of Nature Climate Change . In an Article , Peng Zhu and colleagues consider how warming temperatures affect cropping frequency and yields. They find that warmer temperatures are increasing productivity and the possibility of multiple cropping seasons in cold regions, but increased temperatures in warm regions are causing decreases that outweigh the cold-region increases for an overall loss in crop productivity. The authors note that irrigation can offset the losses in warm regions, but water availability and the infrastructure needed suggest that the required 5% expansion of irrigation areas would be difficult to achieve.

Research has highlighted the risks of concurrent regional droughts; for example, work looking at 26 main crop-producing countries that found the probability under a high-emissions scenario to be at least 5% compared with 0% in the historical period 4 , as well as work showing increases by 40–60% for 10 global regions, with disproportionate risk increase across North America and the Amazon region 5 . With many regions relying on rain-fed agriculture, drought is a major risk to crop failure.

The shifting of seasons, in particular wet periods, can also affect planting. The northern USA had heavy spring rains this year that limited corn planting. This reduced planting led the US Department of Agriculture to lower the predicted yield per acre by 4 bushels, which equals more than 9 million tonnes less corn crop across the country. This lower yield, alongside lower-than-expected grain harvests in China, India, South America and part of Europe, reduced the available produce, not only for consumption but also for stock feed.

As well as their impact on production, extreme events can be a major disruption of supply chains. Yet, international trade has been highlighted as a possible way to mitigate climate change impacts on food security. It has been shown that high-emissions climate scenarios lead to increased hunger risk of 33–47% when trade is restricted, but decreases to 11–64% when trade is open 6 . However, production for export does need to be carefully considered to minimize negative effects in the producing region 7 .

The need to transform food systems to ensure resilience to climate change and other external pressures is well recognized, yet in climate change discussions it has not always been at the fore; at COP27, there will be a Food Systems Pavilion for the first time. How to achieve food systems transformation needs careful consideration and discussion, but work needs to begin now to push past the current stagnation and to ensure that no one is left behind.

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Needed: A Climate-Smart Food System That Can Feed 10 Billion

A Better Food System for Healthier People, Planet and Economy

Story highlights.

• Agriculture, forestry and land use account for about a quarter of greenhouse gas emissions driving climate change.
• The world’s food systems will have to become much more productive by 2050 to feed a global population of 10 billion while also reducing emissions and protecting the environment.
• Through the Climate Change Action Plan, the World Bank will step up support for policies and technological innovations that promote climate-smart agriculture.

On the steep hillsides of Karongi, Rwanda, farmers remember when crops failed and people went hungry. Today, fruits and vegetables grow on the terraced and irrigated hills in Karongi and elsewhere in the country. In the decades following the Rwandan genocide, efforts to revive agriculture have paid off in Rwanda. Controlling erosion, restoring degraded landscapes, diversifying crops, irrigating hilly terrain, and training farmers in new techniques have boosted high value horticulture and trade, improved incomes and diets, and helped make Rwanda one of the fastest growing countries in the world prior to the COVID-19 pandemic.

But like the rest of the world, Rwanda faces the growing impacts of climate change: landslides and droughts caused by heavy and erratic rainfall have taken a toll.

Climate change is increasingly visible on every continent. In the future, declining agricultural productivity will be a key factor in people’s decisions to migrate within their own countries, according to the World Bank’s new Groundswell report , which estimates that 216 million people in six regions of the world could become internal climate migrants by 2050.

Agriculture’s Impact on GHG Emissions

Agriculture, forestry and land use account for about a quarter of the greenhouse gas emissions driving climate change. The largest agricultural emissions come from land conversion, such as clearing forests for farms; methane from livestock and rice production; and nitrous oxide from the use of synthetic fertilizers.  

Agriculture is also the largest consumer of land and water, with impacts on forests, grasslands, wetlands, and biodiversity. Food and land use systems generate environmental, health, and poverty costs estimated at almost $12 trillion per year .

Agriculture and food production are key sources of employment and livelihoods for large numbers of people around the world, yet 3 billion people are unable to afford healthy diets, according to recent estimates. Low incomes, high prices and a system that favors staples like wheat, rice, and maize over fruits and vegetables conspire to keep fresh and nutrient-rich food out of reach of many. 

Current agricultural policies and public support often exacerbate the problem. When governments favor input subsidies or price supports over investment in agricultural research or environmental services, the results can be negative : excessive use of fertilizers, over-pumping groundwater with cheap or free electricity, inefficient use of underpriced water, or agricultural systems that focus on a single crop.

"Agriculture, forestry and land use account for about a quarter of the greenhouse gas emissions driving climate change."

Food systems: the scale of the challenge.

The world’s food systems will have to become much more productive to feed a projected global population of nearly 10 billion by 2050 while also reducing emissions and protecting the environment. Studies estimate the cost of food systems transformation would be about $300-350 billion per year over the next 10 years.

“The scale of this challenge exceeds the capability of any single institution,” said Martien van Nieuwkoop, Global Director for the Agriculture and Food Global Practice at the World Bank . “For that reason, collaboration is needed to make sure the right incentives are in place and the financing is mobilized to make that happen.”

Through the World Bank Group’s Climate Change Action Plan (2021-2025), the Bank will step up support for policies and technological innovations that promote climate-smart agriculture – an approach to managing landscapes that increases productivity, builds resilience, and reduces emissions by avoiding deforestation and identifying ways to absorb carbon from the atmosphere.  

"The world’s food systems will have to become much more productive to feed a projected global population of nearly 10 billion by 2050 while also reducing emissions and protecting the environment."

Crop diversification approaches.

In Uzbekistan, for example, the Bank is working with the government to help shift from cotton and wheat toward a farming system that is more diversified and resilient to climate shocks . Cotton and wheat consumed 72% of arable land and 90% of irrigation water and agricultural public expenditures but generated only 23% of total agricultural output. A new strategy aims to make more efficient use of land and water – and create jobs -- by developing the horticulture sector while reducing State involvement in wheat and cotton. The effort removed production subsidies for low-yield soils which have suffered the most environmental damage and ended child and forced labor to harvest cotton. Cotton growing declined from 1.3 million hectares in 2016 to 0.9 million hectares in 2020. High-value horticulture exports increased from $570 million in 2017 to $1.2 billion in 2019.   “Better incentives for producing horticulture products generate multiple climate co-benefits, both for mitigation and adaptation,” said Sergiy Zorya, Lead Agricultural Economist for the World Bank’s Europe and Central Asia region .

GHG Emissons: Addressing Fertilizer Imbalance

In Pakistan , the SMART Punjab Program aims to empower small scale farmers to grow more climate-resilient, profitable and nutritious crops than wheat. The program enabled farmers to buy improved seeds (oilseed, cotton, rice) and fertilizers (phosphatic and potash) at reduced cost through e-vouchers they could redeem through branchless banking operators. In doing so, the program addressed an imbalance in the use of fertilizers. About 77% of fertilizer sold in Punjab is urea, which is produced through energy intensive methods and has much higher GHG emissions per unit than the other fertilizers available. The SMART program subsidizes other fertilizers like phosphates and potash with the aim to increase their current market share of 22% and 1% currently. “Improving fertilizer management can reduce GHG emissions. It is also likely to have significant sustainable development benefits, including increased crop yields and profitability,” said Asad Rehman Gilani, Secretary, Agriculture Department, Government of the Punjab, Pakistan .

Reducing Food Loss and Waste

Between 30%-40% of all food produced each year is lost or wasted. In developing countries, food is typically lost during the harvest or in storage – a problem that could be addressed in developing countries by investing in infrastructure, transportation, and technology for storage and sustainable cooling .  

In the Philippines, where destructive weather events disproportionally affect the poor, the Philippines Rural Development Project  constructed over 1,200 km of farm-to-market roads, with more underway, as well as other crucial rural infrastructure, such as bridges and communal irrigation systems, and investments along the value chains, including storage and processing facilities.

During the COVID-19 pandemic, the Kenyan government collaborated with IFC client Twiga Foods and other companies using mobile-based digital commerce platforms to match farmers with transport and storage facilities. The Bank is addressing policy options and trade-offs involved in tackling food loss and waste and will implement farm-to-fork food system diagnostics to identify cost-effective climate mitigation and adaptation priorities across the value chain.

Nature Based Solutions and Carbon Sinks

Nature-based solutions to environmental challenges could deliver 37% of climate change mitigation necessary to meet the goals of the Paris Agreement. Conserving the large volumes of carbon stored in natural forests, grasslands, and wetlands is important for climate change adaptation and mitigation and is essential to increasing the resilience of ecosystems. Soils, too, are among the planet’s largest reservoirs of carbon and soil carbon storage. Nature-based solutions can also be applied in coastal areas to stabilize shorelines and reduce flooding and erosion, which helps to maintain fisheries -- a key source of food security and nutrition for about 3.2 billion people.

"Nature-based solutions to environmental challenges could deliver 37% of climate change mitigation necessary to meet the goals of the Paris Agreement."

Nature-based solutions can enhance ecosystem functions in landscapes affected by agricultural practices and land degradation, improving water availability and quality, productivity of crop systems, and livestock health. In Colombia , farmers planted 3.1 million trees and adopted silvopastoral techniques combining trees/shrubs with pasture: these techniques increased carbon sequestration and improved the availability and diversity of food sources, resulting in improved productivity and higher resilience.

The Turkey Resilient Landscape Integration Project will combine nature-based solutions with resilient infrastructure to address seasonal flooding, droughts, soil erosion and landslides in the Bolaman and Cekerek river basins -- two areas marked by high poverty rates and vulnerability to climate change impacts. The project will restore forest landscapes, train farmers in sustainable agriculture, build infrastructure for irrigation and water supply, and increase livelihood opportunities for poor rural households. The project also aims to help lay the foundation for a national strategy to build resilience in vulnerable rural regions in support of Turkey’s sustainable recovery from COVID-19 and green transition.

Delaying Action ‘No Longer an Option’

Delaying action on food systems is “no longer an option,” said Geeta Sethi, Advisor and Global Lead for Food Systems at the World Bank . “It is an imperative to transform our food systems to improve the health of people, the health of the planet, and the health of our economies.”

• Publication: Food Finance Architecture: Financing a Healthy, Equitable and Sustainable Food System
• Climate Stories: How Countries and Communities Are Shaping A Sustainable Future
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• World Bank - Agriculture and Food

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Food Security, Agricultural Productivity, and the Environment: Economic, Sustainability, and Policy Perspectives

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The UN’s Sustainable Development Goal SDG 2 aims to ‘end hunger, achieve food security and improved nutrition and promote sustainable agriculture’. In particular, SDG 2.4 aims to ‘ensure sustainable food production systems and implement resilient agricultural practices that increase productivity and ...

Keywords : food demand, sustainable development goals, agricultural productivity, sustainable agriculture, climate smart agriculture, land use change

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Harvard Research Addresses Food Waste, Hunger, and Climate Crisis in Indonesia

The global foodbanking network and the harvard law school food law and policy clinic identify policy recommendations designed to decrease food waste, support food donation, and combat climate change in indonesia..

September 15, 2022 (Indonesia) —Today,  t he Harvard Law School  Food Law and Policy Clinic  (FLPC) and  The Global FoodBanking Network   released a new analysis on food donation laws and policies in Indonesia and recommendations designed to help  reduce food waste, feed people experiencing hunger, and combat climate change . The research and recommendations are part of  The Global Food Donation Policy Atlas , which maps laws and policies affecting food donation around the world.

About 20 million people in Indonesia, or 8% of the population, are unable to meet their nutritional needs every year, and stunting affects one-third of children under five years old. Yet, 48 million tons of food is either lost or wasted in Indonesia annually, worth between USD$15-39 billion or 4-5% of Indonesia’s GDP. Not only would redirecting edible food to food banks support people experiencing hunger and chronic malnutrition, but it would also help reduce greenhouse gas emissions produced from food ending up in the landfill.

While the Indonesian government has prioritized hunger reduction and food security, including by publishing  a report on food loss and waste in 2021 , no national plan or law has been adopted to prevent food loss and waste or promote food donation. The new resources from FLPC and GFN identify four key opportunities to help reduce food loss and waste, thereby addressing both food insecurity and climate change, including:  

• Indonesia could amend its food safety law to include a donation-specific chapter or draft new regulations that elaborate on food safety for donations. The government could also produce and disseminate clarifying guidance on food safety requirements relevant to donation.
• Indonesia could amend the law to establish a dual date labeling system that clearly distinguishes between safety-based and quality-based date labels. The government could also amend the law to permit food donation after the quality-based date.
• Indonesia could enact national legislation that establishes clear and comprehensive liability protection for food donors and food recovery organizations when they donate food that meets all safety rules.
• Indonesia could update its income tax deductions to provide a tax incentive for in-kind donations of food; to eliminate a current financial barrier to donation, it could also amend its VAT scheme to exempt donated foods from VAT.

“Indonesia can feed people experiencing hunger, reduce food waste and loss and help arrest climate change,” said Emily Broad Leib, clinical professor of law at Harvard Law School and faculty director of FLPC. “Indonesian leaders, like others around the world, can help by implementing good food donation policies. Our hope is that they read our research and are guided by our recommendations–developed in collaboration with Indonesian stakeholders–and take action.”

“In five years we distributed more than 490 tonnes of food, feeding more than 60,000 people from across the country from various backgrounds and needs. These numbers came from the collaboration between FoodCycle as a food bank and the private sector such as FMCGs, food retailers, restaurants, FnB industries, etc,” said Astrid Paramita, CEO and Co-founder of FoodCycle Indonesia. “We believe that the government participation could bring a catalyst effect to encourage more communities to be aware of the problems and also conduct an integrated plan to solve hunger, food loss, and waste in Indonesia.”

“Scholars of Sustenance Indonesia has always been committed to feeding communities in need in Bali and Indonesia through the collection and redistribution of edible surplus food from hospitality partners including hotels, restaurants, bakeries, and food manufacturers,” said Minni Vangsgaard, General Manager of Scholars of Sustenance Indonesia. “Since the beginning of our operations in 2016 (Bangkok) and 2017 (Bali, Indonesia) we managed to distribute globally a total of around 25 million meals. We believe that good food donation policies in Indonesia will encourage more food donations as well as encourage corporations, communities, and organizations to participate in tackling hunger, food loss, and food waste issues and addressing climate change.” “An estimated 702-828 million people are facing hunger globally, and that number is likely to rise as food price spikes, supply chain issues, and climate change continue to strain our food systems,” said Lisa Moon, president and CEO of The Global FoodBanking Network. “Food banks help ensure more people have access to food while also reducing food loss and waste. Strong food donation policies are absolutely critical to this work—they help food banks serve their communities in the most effective and efficient way.”

The Global Food Donation Policy Atlas ,  supported by Walmart Foundation, identifies existing laws and policies that support or hinder food recovery and donation in a comprehensive Legal Guide and offers Policy Recommendations for strengthening frameworks and adopting new measures to fill existing gaps. The analysis featured in these country-specific reports are also encapsulated in an  interactive atlas tool  that allows users to compare policies between countries participating in the project.

Atlas  project research   is currently available for 18 countries, with more underway: Argentina, Australia, Canada, Chile, Colombia, Costa Rica, the Dominican Republic, Guatemala, India, Indonesia, Kenya, Mexico, Nigeria, Peru, Singapore, South Africa, the United Kingdom, and the United States. An interactive map, Legal Guides, Policy Recommendations, and Executive Summaries for each country are available at  atlas.foodbanking.org .

About The Harvard Law School Food Law and Policy Clinic The Harvard Law School Food Law and Policy Clinic   (FLPC) serves partner organizations and communities by providing guidance on cutting-edge food system issues, while engaging law students in the practice of food law and policy. FLPC’s work focuses on increasing access to healthy foods, supporting sustainable and equitable food production,   promoting community-led food system change,    and reducing waste of healthy, wholesome food. FLPC is committed to advancing a cross-sector, multi-disciplinary and inclusive approach to its work, building partnerships with academic institutions, government agencies, private sector actors, and civil society with expertise in public health, the environment, and the economy. For more information, visit  chlpi.org/food-law-and-policy .

About FoodCycle Indonesia FoodCycle Indonesia aims to break the hunger cycle of underprivileged communities by re-distributing untouched surplus food, re-processing imperfectly perfect produce, and recycling food waste. In connecting with those communities, we develop their knowledge, attitude, skills, and habits to positively impact themselves and to create a better society of Indonesia. For more information, visit  foodcycle.id .

About Scholars of Sustenance Scholars of Sustenance is a food rescue foundation redefining the way food is distributed in order to tackle the food deficit issue and put good nutrition into the hands of those who need it. For more information, visit  scholarsofsustenance.org .

About The Global FoodBanking Network The Global FoodBanking Network supports community-driven solutions to alleviate hunger in nearly 50 countries. While millions struggle to access enough safe and nutritious food, nearly a third of all food produced is lost or wasted. We’re changing that. We believe food banks directed by local leaders are key to achieving Zero Hunger and building resilient food systems. For more information, visit  foodbanking.org .

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• Published: 21 September 2023

Supporting agriculture in developing countries: new insights on the impact of official development assistance using a climate perspective

• Maria Teresa Trentinaglia 1 ,
• Lucia Baldi   ORCID: orcid.org/0000-0002-2791-9127 1 &
• Massimo Peri 1  

Agricultural and Food Economics volume  11 , Article number:  39 ( 2023 ) Cite this article

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Agriculture is a major source of food and income for poor and rural households living in developing countries; yet, agricultural systems are increasingly threatened by changing climate conditions that compromise their productivity and resilience. Over time, international aid has provided support to the agricultural systems of recipient countries, though the literature is not unanimous in confirming their effectiveness.

To shed light on this issue, the purpose of this work is to assess the efficacy of these aid in increasing the agricultural productivity of recipient nations, employing original approaches.

First, to adopt a climate change perspective, we conduct our analysis using a recent classification adopted by the Official Development Assistance—the Rio Markers—which distinguishes aid between adaptation and mitigation to climate change.

Second, taking into account that the starting conditions of recipient countries can significantly impact aid effectiveness, we classify 115 developing countries into four subgroups according to their vulnerability and readiness to climate change, as evaluated by the ND-Gain indicators.

We perform a two-stage instrumental variable approach within the context of panel models to investigate the potential growth-enhancing impact that different types of agricultural aid may exert on the agriculture Total Factor Productivity in recipient countries.

Our findings show that aid to agriculture, especially adaptation aid, has a positive impact on agricultural productivity growth. We also observe that countries with a higher climate readiness benefit the most from aid, whereas countries highly vulnerable and heavily dependent on the agricultural sector are less able to leverage the aid received to the same extent.

Overall, our analysis confirms the importance of international aid to the agricultural sector and suggests that accurate impact assessment analyses should also consider a climate perspective to distinguish adaptation from mitigation aid.

Introduction

In developing countries, the livelihood of rural and poor households largely depends on agriculture, which provides them with food, income, and employment. In some of these countries, agriculture even accounts for up to 70% of total employment, and its contribution to the overall GDP is often even higher (International Labour Organization 2021 ). Also, in the least developed countries, agriculture can be the engine of growth (Ravallion and Datt 1996 ), also adding up to growth in other sectors (Tiffin and Irz 2006 ; Kaya et al. 2013 ), and can thus have a deep effect at reducing poverty (Irz et al. 2001 ; Christiaensen and Martin 2018 ).

Agriculture also provides critical inputs to other non-agricultural economic sectors, such as industry and services, and is a significant source of foreign exchange through exports of agricultural products (World Bank 2007 ; Christiaensen et al. 2011 ). Moreover, by providing food at reasonable prices in urban areas, agriculture can help improve food security for urban populations (Dethier and Effenberger 2012 ).

However, the impact of agriculture on economic growth in developing countries is complex and depends on various factors. In many developing countries, rural communities are often marginalized and suffer from a lack of basic services, making rural development a crucial aspect of overall development efforts. Furthermore, these countries are often constrained by a variety of factors, such as lack of access to technology, inputs, and markets. In addition, climate change, with the increased frequency and intensity of extreme weather events, changes in precipitation patterns, and rising temperatures (Mbow et al. 2017 ) is expected to have a significant impact on agricultural production especially for developing countries (Mendelsohn 2009 ; Chen et al. 2016 ; Zaveri et al. 2020 ). The expected reduction in agricultural productivity resulting from climate change coupled with farmers’ increased difficulty adapting to changing conditions (Thornton et al. 2018 ) could have a significant impact on overall economic growth and food security (Mbow et al. 2017 ; FAO, IFAD, UNICEF, WFP and WHO 2020 ).

To moderate the adverse impact of changing climate conditions, farmers’ resilience must be strengthened and supported: for this purpose, international aid can provide the funding and resources needed for programs and initiatives that can help farmers increase their adaptive capacity. This international assistance can include investment in infrastructures (roads, water systems, storage facilities), and training in sustainable agricultural practices (such as conservation agriculture, agroforestry, and integrated pest management) (FAO 2018 ). In addition, granting farmers access to innovative cultivation systems and technologies that are more resistant to extreme weather conditions can help improve agricultural productivity and reduce the risk of crop failure (Fisher et al. 2015 ; Makate et al. 2019 ; Tóth et al. 2020 ; Adzawla and Alhassan 2021 ). Enhanced agricultural productivity and improved resilience could in turn improve farmers’ living standards and confirm the effect on overall economic growth and poverty reduction that has been observed in the past (Ravallion and Datt 1996 ; Kaya et al. 2013 ).

One of the most relevant forms of international assistance is the flow of economic resources from the official sectors of countries belonging to the OECD Development Assistance Committee (DAC). This flow of economic resources, also known as Official Development Assistance (ODA), promotes economic growth and social welfare in least developed countries at concessional terms and can play a critical role in strengthening the resilience of developing countries, particularly in the face of the challenges posed by climate change. Since their introduction, ODA has increased over time; yet, the amount of aid directed to the agricultural sector has decreased even though this sector was a major recipient of aid in the past. Moreover, despite the positive intent behind international aid, studies on their effectiveness have yielded contrasting results. Indeed, alongside positive impacts, these aids have also given rise to adverse effects in recipient countries.

In light of these considerations, the focus of this paper is on that component of ODA specifically directed to agriculture, with the aim of assessing whether and where it contributes to increasing the level of agriculture productivity and, consequently, to help contrast climate change and to reduce the level of poverty and thus food insecurity.

Compared to current studies, we contribute to the literature on the effectiveness of international aid through a climate change perspective using original approaches. First, we estimate the impact of agricultural aid using a recent classification used by the Rio Markers (OECD 2016 ), which distinguishes aid between adaptation and mitigation to climate change. To the best of our knowledge, this classification system has not been yet used to evaluate the effectiveness of ODA in fostering the agricultural productivity of recipient countries. Provided that the effectiveness of agricultural aid is often questioned, we exploit this recent classification system to provide a more accurate assessment of agricultural aid.

Second, we assess the effectiveness of agricultural aid in 4 subsamples of countries identified by their vulnerability and readiness to climate change using the Notre Dame Global Adaptation Initiative (ND-GAIN) composite indexes (Chen et al. 2015 ) that combine multiple indicators into scores reflecting a country's overall level of climate characteristics. The literature has shown that aid effectiveness depends largely on the conditions in which the recipient country is, but no work has related aid to country characteristics related to climate change.

This article is structured as follows: Sect. " Literature review " discusses the related literature on international aid; Sect. " Data and methods " presents the data used in the analysis and the empirical methods; Sect. " Econometric results " presents the results that are discussed in Sect.  Discussion and Sect. " Concluding remarks " concludes.

Literature review

Ever since its beginning, ODA gained considerable attention in the academic debate. The effectiveness of ODA in general has been explored with regard to different issues: economic growth, civil conflicts, food security, agricultural productivity, and characteristics of aid-receiving countries. Nonetheless, despite the widespread debate on the role of ODA as a promoter of economic growth and social welfare in recipient countries, a clear consensus is still missing, as the evidence regarding their actual effectiveness is often contrasting.

A comforting evidence of the effectiveness of ODA can be found in Burnside & Dollar ( 2000 ), who found a positive effect of foreign aid on growth only in those recipient countries with good fiscal, monetary, and trade policies. This aid-growth nexus has been later confirmed in the literature review of Arndt et al. ( 2010 ), at least in the long run. The recent quasi-experimental approach of Galiani et al. ( 2017 ) found further proof of the positive effect that foreign aid can have on economic performance: in their analysis, a 1 percentage point increase in aid received raises per capita growth by 0.35 percentage points. As for the impact on the incidence of conflicts, the work of Mary & Mishra ( 2020 ) stated that a 10 percent increase in total humanitarian food aid reduces the frequency of civil conflicts by 0.2 percent; a similar negative effect is observed on the duration of conflicts.

The ability of ODA to promote food security and agricultural productivity was first identified in the seminal work of Norton et al. ( 1992 ), where it is found that foreign assistance from 1970 has improved agriculture in Asia and, to a lesser extent, in sub-Saharan Africa but not in the Middle East or Latin America. Still, a study by Alabi ( 2014 ) investigated the impact of foreign agricultural aid on agricultural GDP and productivity in Sub-Saharan Africa (SSA) concluding that these aid had a positive impact more when are bilateral rather than multilateral. Work by Ssozi et al. ( 2019 ), Barkat & Alsamara ( 2019 ) and Kornher et al. ( 2021 ) also found positive relationships between aid and growth in agriculture. A positive growth-enhancer effect has been observed also in Kaya et al. ( 2013 ), where foreign aid to agriculture reduces both directly and indirectly the poverty headcount ratio of recipient countries, a result that confirms the poorest welfare-enhancing effect of aid to agriculture. Recently, a positive nexus between agricultural ODA and Foreign Direct Investments in the agri-food industry of recipient countries has also been uncovered (Tian 2023 ).

In terms of promoting economic growth in recipient countries, the existence of an aid-growth nexus has been instead contested by other authors (Rajan and Subramanian 2008 ). Similarly, the instrumental variable approach by Dreher & Langlotz ( 2020 ), based on donors’ country fractionalization, found a positive though insignificant role of foreign aid on recipient per capita income growth. ODA, and humanitarian aid in particular, has been also blamed for increasing the frequency and duration of intra-state civil conflicts in recipient countries (Nunn and Qian 2014 ). The ability of aid to contrast food security has been equally criticized (Petrikova 2015 ). For instance, in Mary et al. ( 2020 ), agricultural aid only have a limited impact on reducing child stunting: a 10% increase in agricultural aid only reduces child stunting by 0.5%. Last but not least, the lower than expected returns from aid to agriculture might explain the sharp reduction in aid to the primary sector that took place over time (Mattoo et al. 2020 ) as displayed in Fig.  1 .

Official Development Assistance (ODA) sectoral allocation from the 1970s Source: authors’ elaboration using OECD statistics

A critical point in the study of the use of ODA, which could pave the way for new strands of studies, concerns the type of classification used to categorize these aids. In 2010, the OECD introduced an ODA classification system using Rio markers encompassing aspects related to climate change. In particular, these markers distinguish mitigation interventions, aimed at minimizing the impact of human activity on polluting emissions, from adaptation ones, that provide individuals with the tools to cope directly with the effects of climate change and natural hazards (OECD 2016 ).

As of today, studies employing the mitigation-adaptation classification only investigate the characteristics of recipient countries, rather than delving into the assessment of aid effectiveness. Halimanjaya ( 2015 ) for instance observed that recipient countries with a high CO2 intensity, large carbon sinks, and good governance receive mitigation aid, whereas adaptation aid are allocated to countries with lower CO2 emission intensities. Weiler et al. ( 2018 ) used this classification method to identify the donors’ underlying motive for allocating adaptation aid to recipient countries. Their analysis indicated that recipient countries’ governance quality is an aid attractor; yet, perhaps more importantly, donors seem to privilege countries that could become trade or business partners. More recently, Iacobuţă et al. ( 2022 ) observed that the gap between mitigation and adaptation aid is shrinking, since donors, considering adaptation as a public good, are re-evaluating the importance of adaptation assistance. With the growing importance of the climate perspective in gauging the efficacy of global aid efforts, our study addresses specifically this literature gap by quantifying the growth in agricultural productivity within developing countries resulting from both adaptation-oriented and mitigation-oriented aid.

Another strand of research has attempted to investigate the effectiveness of ODA based on the attributes of beneficiary nations. In this case, the literature has shown that aid effectiveness depends largely on the conditions in which the recipient country is (Hudson & Mosley 2001 ; Mosley et al. 2004 ; Dalgaard et al. 2004 ; Maruta et al. 2020 ); among these, institutional quality is one of the most relevant determinants for a good project outcome (Baliamoune-Lutz & Mavrotas 2009 ; Denizer et al. 2013 ) and is relevant for enhancing agricultural productivity, too (Lio & Liu 2008 ; Lio & Hu 2009 ). Nevertheless, as far as we are aware, there has been no research conducted on the impact of aid on agricultural productivity while considering the specific traits of the aid-receiving countries concerning their responsiveness to climate change.

A highly appealing method for categorizing countries within the context of climate change is offered by the Notre Dame Global Adaptation Initiative (ND-GAIN). This initiative offers two indicators that pertain to the country's current vulnerability to climate disruptions and the country's readiness to leverage private and public sector investment for adaptive actions. These indicators have been extensively employed in the literature primarily to establish a relationship between the characteristics of countries and the aid they have received. For instance, Robertsen et al. ( 2015 ) highlight that the countries in Africa most vulnerable to climate impacts are not necessarily the ones receiving the highest amount of aid. Delving further into this matter, the study by Jain and Bardhan ( 2023 ) investigates the connections between ODA disbursements and climate vulnerability. Additionally, it examines the intermediary function of adaptation readiness within 119 developing nations, thereby suggesting a lack of adaptation mainstreaming into ODA disbursement with respect to vulnerability and readiness. The same conclusion is arrived at by Savvidou et al. ( 2021 ), who emphasize the inadequacy of aid in countries that are most susceptible and least responsive to the impacts of climate change.

In our study, we go beyond the analysis of the distribution of aid based on country characteristics related to climate change. Instead, we advance the literature by employing ND-GAIN indexes to investigate whether the climate vulnerability and readiness of recipient countries significantly influence adaptation aid effectiveness, particularly in the context of agricultural productivity—an aspect that, to the best of our knowledge, has not been previously explored in the literature.

Data and methods

Regarding international aid data, the Official Development Assistance (ODA) collected by the OECD-Development Assistance Committee (DAC) was taken into consideration. The flow of ODAs started in the 1960s (Hynes and Scott 2013 ) and currently targets different areas of intervention, such as humanitarian assistance, food aid, social infrastructures and services, and agriculture. As can be observed from Fig.  1 , total aid has increased over time; yet, agriculture, which was one of the major recipient sectors in the past, has been gradually allocated with a declining amount of aid over time. The agricultural sector was in fact a major recipient of assistance in the 1970s and 1980s (Cabral and Howell 2012 ) but the contributions received gradually declined over time and now account for only 5% of total contributions. Social infrastructure and services is now the largest recipient sector.

In 1998, the OECD-DAC introduced a first classification system (Rio markers) to group ODA into these three categories: biodiversity, climate change mitigation, and desertification. In 2010, a fourth marker dedicated to climate change adaptation aid was introduced. The Rio markers for climate change now distinguish mitigation interventions, aimed at minimizing the impact of human activity on polluting emissions, from adaptation ones, that provide individuals with the tools to cope directly with the effects of climate change and natural hazards (OECD 2016 ). Adaptation and mitigation aids are further classified into principal or significant. An activity is principal when “the objective is explicitly stated as fundamental in the design of, or the motivation for, the activity”; it is classified as significant whenever the “objective is explicitly stated but it is not the fundamental driver or motivation for undertaking it” (OECD 2016 ).

To evaluate the effectiveness of ODA at stimulating agricultural productivity growth, this analysis considers a sample of 115 countries (see Table 5 in Appendix ) that have received ODA in terms of “principal” adaptation or mitigation aids dedicated to “agriculture”. We collected annual data from 2010 to 2020, obtaining 1170 observations. The data are publicly available in the Creditor Reporting System Database and are in 2020 USD. Our definition of agricultural aid slightly departs from that of Kornher et al., ( 2021 ) as it excludes food aid and aid targeting environmental protection from the definition of agricultural aid; we include instead aid targeting water supply and sanitation, which can respectively improve irrigating systems, and thus agricultural productivity, and living standards and food storage of rural households.

Our variable of interest is agricultural Total Factor Productivity (TFP) estimated and collected by USDA, which is defined as the amount of agricultural output produced from the combined set of land, labour, capital, and material resources employed in farm production. If total output is growing faster than total inputs, then the total factor productivity is increasing.

In this paper, we have chosen to focus on an aggregate measure of agricultural productivity, without delving into the differentiation of various input factors, in order to accommodate the concept of substitutability among them. Total Factor Productivity (TFP) has been specifically formulated to address the constraints and biases associated with the application of partial productivity measures, as elucidated by seminal literature (Christensen 1975 ), and it is recommended for cross-country comparative analyses (Shumway et al. 2016 ). Each TFP data series is an index with a base year of 2015, such that the value of TFP for each country or region is set to 100 in 2015. Thus, the value of the index in any year is the level of TFP relative to 2015. An international comparison of TFP in different countries does not indicate where productivity levels are higher or lower, but rather where agricultural productivity has grown faster over time.

The classification of countries according to a climate perspective was carried out by the Country Index of the Notre Dame Global Adaptation Initiative (ND-GAIN), a freely accessible index that displays a country’s existing vulnerability to climate-related disturbances. Moreover, it evaluates a nation's readiness to utilize investments from both the private and public sectors for adaptive actions. The ND-GAIN Country Index compiles over 40 core indicators of 182 United Nations member countries from 1995 to the present.

To analyze the effect of aid in relation to the characteristics of recipient countries, we then divide our sample into 4 groups according to indicators that express the country's current vulnerability to climate disruptions and its readiness to leverage private and public sector investment. Both vulnerability and readiness indexes combine multiple indicators into a single score to reflect a country's overall level of climate readiness and vulnerability. Specifically, vulnerability expresses “ The propensity or predisposition of human societies to be negatively impacted by climate hazards ”; Chen et al. 2015 ) and is based on three components: the exposure of the economic sectors to climate-related or climate-exacerbated hazards; the sensitivity of to the impacts of the hazard and the adaptive capacity to cope or adapt to these impacts. Readiness means a country’s ability to “ Make effective use of investments for adaptation actions thanks to a safe and efficient business environment ” (Chen et al. 2015 ). It comprises other three components: economic, governance, and social. While economic readiness apprehends the national business environment based on which adaptation reduces sensitivity and improves adaptive capacity, governance readiness focuses on institutional strength to ensure proper investment. Social readiness deals with social inequality, education, information systems, and innovation that affect investment and promote adaptation actions.

By applying the ND-GAIN climate indicators to our sample of recipient countries, we can distinguish four different combinations of climate vulnerability and readiness, which are displayed in Fig.  2 below (see Table 6 in the appendix for the detailed list). Each point is a combination of vulnerability and readiness levels, weighted by the ratio between agricultural value added and GDP: the greater this ratio, the greater the size of the point in Fig.  2 . In the left top panel, there are those countries with high vulnerability and low readiness. Countries in the bottom right of the matrix have low values of vulnerability and high values of readiness; the top right panel identifies countries with high vulnerability but also high levels of readiness. Last, countries in the bottom left have low levels of vulnerability and low levels of readiness.

Countries climate vulnerability and readiness indexes weighted by the Agricultural Value Added (% of GDP) Source: Authors’ elaborations to re-adapt the climate matrix data of Chen et al. ( 2015 ) to the sample data used in the analysis. The Agricultural Value Added as a share of GDP is retrieved from the World Bank and refers to the Value Added of Agriculture, Forestry, and Fishing. The cut-offs used to sort countries into high or low climate vulnerability or readiness are the sample median values

Figure  2 also shows the country's dependence on the agricultural sector. Interestingly, the countries that depend mainly on agriculture activity (larger points) are also the most vulnerable and have the lowest readiness. Conversely, countries, where agriculture has a lower impact on economic activity (smaller points), are the least vulnerable and the most able to adapt to climate change and its potential to improve its adaptive capacity in the future.

We also consider some control variables previously used in the literature in the assessment of foreign aid effectiveness (Burnside and Dollar 2000 ; Dreher et al. 2021 ) that could compromise or reinforce the effectiveness of foreign aid. These are the ratio between broad money and GDP, the Food Consumer Price Index, weather variables (temperatures and precipitations), political stability, received personal remittances, and trade openness. All these variables are in fact able to influence agricultural productivity as explained below.

A positive relation between money supply and agricultural productivity has been observed in the literature (Kargbo 2007 ; Gil et al. 2009 ). The ratio between broad money and GDP can in fact proxy money supply and thus monetary policy. Expansionary monetary policies reduce the interest rate and thus the cost of investments, favouring in turn capital accumulation also in the primary sector.

Food prices are linked to agricultural productivity. Higher food prices can encourage farmers to increase their market involvement and invest in agricultural technologies (Benfica et al. 2017 ). However, high prices in certain cases can reduce investment capacities and exacerbate food insecurity, especially in low-income countries reliant on agriculture that can barely react to international shock prices (Pingali 2007a ; Ivanic and Martin 2008 ; Warr 2014 ). For instance, during the 2008 food price crisis, many developing countries were unable to respond effectively to changing agricultural prices (Wodon and Zaman 2010 ).

The role of weather conditions in influencing agricultural output has been well documented in the literature, both in developed and developing countries, where adverse weather shocks reduce agricultural productivity (Grace et al. 2015 ; Chavas et al. 2019 ).

Political stability, which is also a proxy for institutional quality, improves a country’s ability to attract foreign investments and development assistance (Burnside and Dollar 2000 ; Weiler et al. 2018 ). Better governance can also boost agricultural productivity by favouring the accumulation of agricultural capital (Lio and Liu 2008 ; Lio and Hu 2009 ).

Remittances can have a profound positive or negative effect on agricultural productivity: they can compensate for the reduction in agricultural labour supply and reduce liquidity constraints (Rozelle et al. 1999 ; Taylor et al. 2003 ; Wonyra and Ametoglo 2020 ), but they can also reduce working incentives and thus labour productivity by increasing the reservation wage (Amuedo-Dorantes and Pozo 2006 ). To avoid a confounding interpretation of the effectiveness of aid on agricultural productivity, remittances are thus included in both robustness specifications.

Trade openness and increased exports could sustain agricultural development in different ways: countries with a comparative advantage in agriculture, just like most ODA recipients are, become exposed to international competition, and could greatly benefit from having access to foreign markets; also, domestic consumers would have access to an enriched gamma of food products and their diversified preferences would favour the nutrition transition (Pingali 2007b ). Even though trade openness seems to support agricultural productivity growth (Hassine and Kandil 2009 ; Gáfaro and Pellegrina 2022 ), most vulnerable countries, such as Sub-Saharan Africa countries, are characterized by very uncompetitive and unproductive agricultural systems (Pingali 2007b ). In this sense, higher trade flows might increase food imports and thus compromise agricultural development. In terms of food security, trade might compensate for insufficient domestic production (Porkka et al. 2013 ), at the cost of increasing countries’ exposure to shocks in foreign prices, though remittances and foreign aid might offset such effect (Combes et al. 2014 ).

The descriptive statistics of all variables for the sample period 2010–2020 are reported in Table 1 .

Econometric specification: an instrumental variable approach

Empirical analysis that examines the effectiveness of foreign aid or ODA on certain outcomes, such as agricultural productivity, must deal with a significant level of endogeneity. A source of endogeneity is reverse causation, by which ODA is allocated to countries with particularly low levels of agricultural productivity. In this case, standard OLS estimates are biased and do not capture the actual effect of aid on agricultural productivity.

In order to deal with this potential source of endogeneity, we perform a two-stage least square (2SLS) instrumental variable approach. In such a setting, for the first stage, the chosen instrument has to be related to the instrumented variable but not to the dependent variable. In other words, a suitable instrument is related to ODA but not to agricultural productivity in recipient countries.

In particular, to identify the instrumental variable we consider the interaction between a time-series variable and a cross-section indicator following Nunn and Quian (2014) approach.

The time-series variable used is the Federal Reserve USA Industrial Production Index, that can proxy global real economic activity and can consequently influence the amount of assistance provided by donor countries (recalling that OECD donor countries are asked to allocate up to 0.7% of the Gross National Income to ODA). The cross-sectional dimension in our case is the recipient country’s probability of receiving assistance, computed as the ratio between the number of years in which foreign aid have been received over the total number of years included in the sample. Thus, the instrument now varies by country and time period, which allows us to control for year fixed effects. We allow the time effects to differ across countries and control for countries and year fixed effects.

Provided that the instrument cannot be correlated with the error term of the explanatory equation, conditionally on the other covariates, the exclusion restriction (i.e., the instrument affects productivity only through aid) would be violated as long as the probability of receiving agricultural assistance influences agricultural productivity; yet, in our analysis, we control for country and year fixed effects to make sure that the instrument is an exogenous variable with no effect on agricultural productivity other than the effect it has on ODA. Provided that our econometric approach resembles a Diff-in-Diff approach (Nunn and Qian 2014 ; Dreher and Langlotz 2020 ; Dreher et al. 2021 ), our identifying assumption thus states that agricultural productivity in countries with different probabilities of receiving aid is not affected differently by changes to the industrial production index other via the impact of agricultural aid whilst controlling for country and year fixed effects.

To visually test this, we inspect the trends in the Industrial Production Index as well as the trends in agricultural productivity and aid received (Christian and Barrett 2017 ) among “Regular” and “Irregular” recipient countries, i.e., countries that have received respectively more or less aid than the sample median probability of receiving aid. Such trends are displayed in Fig.  3 .

Trends in aid received and in agricultural productivity changes in Regular and Irregular recipient countries Source: authors’ elaboration on OECD data (total agricultural ODA received), USDA data (agricultural TFP), Federal Reserve Economic Data (for the US industrial production index). Note: Regular and Irregular recipient countries are defined with respect to the sample median probability of receiving total agricultural aid

Following Christian and Barrett ( 2017 ), from the visual inspection of the trends pictured in Fig.  3 we have little reason to believe that the parallel trends assumption is violated. The trends in aid received and the trends in agricultural productivity are in fact largely parallel across the two groups.

In light of these results, we can formulate our empirical specification by introducing the two regression equations below:

where Eqs. ( 1 ) and ( 2 ) are respectively the second and first-stage equations of the 2SLS system. In particular, in Eq. ( 1 ) \({y}_{it}\) is the agricultural productivity (TFP) in recipient country i at year t ; \({aid}_{it}\) denotes agricultural aid received to recipient country i in year t . In this analysis, we consider three different measures of total, adaptation, and mitigation agricultural aid: their logged total financial value, the total number of projects financed each year, and the logged average financial value. All these measures are introduced considering their value two years before so that we let aid have sufficient time to affect agricultural productivity.

\({X}_{it}\) is a vector of recipient country- year variables of control, that is: broad money, food consumer price index, temperatures, precipitations, political stability, remittances, and trade openness; \({\gamma }_{i}\) and \({\delta }_{t}\) are the country and year fixed effects (FE), and \({\varepsilon }_{it}\) is the error term.

In Eq. ( 2 ), as explained earlier, aid is instrumented with the interaction between the same-year US Industrial Production Index at time t , \({IPI}_{t-2}\) , and the cross-sectional probability of receiving total, adaptation or mitigation agricultural aid, that is \({prob}_{i}\) . In Eq. ( 2 ) we introduce the same set of controls as of Eq. ( 1 ), \({X}_{it},\) together with country and year fixed effects (FE), \({\delta }_{i}\) and \({\sigma }_{t}\) .

β 1 is the coefficient of interest and represents the estimated effect of an additional unit of aid (total financial value, or total number of projects financed each year, or average financial value) on agricultural productivity. A positive coefficient indicates that, on average, an increase in the provision of ODA increases the Total Factor Productivity.

Econometric results

This section reports the empirical results of the analysis. In particular, Eqs. ( 1 ) and ( 2 ) have been estimated three different times. In the first case, we considered total agricultural aid, so as to assess the aggregate effect of agricultural aid (Table 2 ). Then, the two equations have been estimated again introducing this time two different types of agricultural aid: mitigation agricultural aid and adaptation agricultural aid (Table 3 ). Lastly, we performed a third estimation considering exclusively the adaptation component and segmenting recipient countries into four groups based on their climate vulnerability and readiness following the ND-GAIN indicators.

Table 2 reports the results of the two-stage estimates when considering total agricultural aid (their total financial value, the total number of projects financed, and the average value). Specifications (1) and (2) in the columns report the result of the first and second-stage regressions respectively.

The first-stage regressions show an expected positive coefficient of the instrument: increases in the US industrial production index proxy positive business cycles, and encourage donor countries to provide more financial assistance to developing countries. The under-identification (Kleibergen–Paap F-test) is satisfactory for the total number of projects financed, suggesting the strength of our instrument, but is rather weak when the total or average financial values are considered.

The second-stage results indicate that an increase in total agricultural aid increases agricultural TFP in recipient countries. The magnitude of this effect changes depending on the definition of aid considered and ranges from 0.018 for the number of projects to 0.064 when the average value is considered, though in this last case, the effect is significant at only 10%. The effect of the total number of projects is instead statistically significant at 1%.

In order to isolate the effect of mitigation interventions from that of adaptation ones, in the second estimation we decompose total assistance using the Rio markers classification scheme for climate change aid. The results of this analysis are reported in Table 3 .

The first-stage regressions for the mitigation agricultural aid indicate an unsatisfactory under identification test and reveal a negative regression coefficient, which is only marginally significant when the number of agricultural mitigation projects is considered. Similarly, in the second stage, we observe that agricultural mitigation aid negatively affects agricultural TFP, though none of the coefficients is statistically significant.

For adaptation agricultural aid, the first-stage regression results and the Under-identification test (Kleibergen-Paap F-test) confirm instead the validity of our instrument. Also, the second stage results indicate that adaptation aid have a positive and statistically significant effect on agricultural productivity growth in each specification considered (total financial value, number of projects, average financial value).

In the last estimation, we focused only on adaptation agricultural aid and its total financial value (Table 4 ). In this analysis, the control variables typical of the literature on aid effectiveness described in Sect. " Data " are introduced. The effectiveness of agricultural adaptation aid is initially tested on the entire sample. Then, we exploit the ND-GAIN matrix that divides countries into four different groups, depending on their combination of climate vulnerability and climate readiness (see Fig.  2 ). In particular, the following groups are identified: high vulnerability and low readiness; high vulnerability and high readiness; low vulnerability and high readiness; low vulnerability and low readiness.

When the entire sample is considered (regression 1 of Table 4 ), the validity of the instrument is highly satisfactory, and the effectiveness of adaptation agricultural aid is found to be robust to the introduction of the different control variables. The regression coefficient, though significant at 10%, is in fact equal to 0.008, in line with the regression coefficients observed in the baseline specification of Table 3 . The only control variables that positively and significantly affect agricultural TFP are temperatures and money supply.

The empirical specifications 2–5 of Table 4 allow us to evaluate and compare the effectiveness in recipient countries with different combinations of vulnerability and readiness. The values of the under-identification test show that our instrument explains aid in specifications 2, 3, and 4 but not in specification 5. Footnote 1 Aid is effective in all sub-samples, with the exception of low vulnerability and high readiness countries (specification 4), i.e., in those countries that are more equipped to deal with climate change. In terms of magnitude, results are highly heterogeneous. The effectiveness of aid in more vulnerable and less ready countries (regression 2 ) is the lowest (0.011) one. The coefficient increases noticeably in specification 3 (0.042), i.e., in the sub-samples of high vulnerability—high readiness countries.

With regard to the control variables, which will be discussed in more detail in the next session, it was found that money supply exerts a positive effect in all specifications considered, apart from the specification on the sub-sample of low vulnerability and low readiness countries. The Food Consumer Price Index only negatively affects agricultural TFP in specifications 2 and 3, that is, in highly vulnerable countries. In specifications 3 and 4, the coefficient of temperatures is positive and significant, whereas precipitations are always non-significant in all specifications. Non-significant coefficients are also found in all equations for the variable expressing political stability. Remittances only partially increase agricultural TFP in the sample of high vulnerability and high readiness countries (specification 3). In the other country classifications, remittances have no effect on agricultural TFP. Last, trade openness reduces agricultural productivity in both sub-samples of vulnerable countries, regardless of their climate readiness (specifications 2 and 3).

Our analysis sheds some light on the debate about the economic impact of ODA, showing that agricultural aid has a positive effect on agricultural productivity. Our results are robust to the use of different measures of aid adopted (total financial value, number of projects, average financial value) as there is no significant difference across the measures considered. This finding appears to align with a segment of the literature that identifies a positive correlation between international aid and agricultural productivity (Norton et al. 1992 ; Alabi 2014 ; Ssozi et al. 2019 ; Kornher et al. 2021 ) or, more broadly, with economic growth (Arndt et al. 2010 ; Galiani et al. 2017 ; Mary & Mishra 2020 ). Nonetheless, our study has endeavoured to add a climate change perspective to the results, a dimension previously absent in the existing literature, with the aim of enriching the ongoing discourse. In pursuit of this objective, we have observed that results remain stable when we differentiate agricultural aid into the two Rio Marker climate change components: a closer inspection of adaptation agricultural aid reveals in fact that it remains effective at stimulating agricultural growth in recipient countries. On the other hand, agricultural mitigation aid has no short-term effect on agricultural productivity. This latter outcome is not surprising considered that mitigation aid, by its intrinsic nature, does not aim at increasing agricultural productivity, but rather acts like as a potential competitor for resources needed for agriculture. Responding to climate change through the deployment of low-emission agricultural technologies would put pressure on food security through the potential reduction of food production.

Our work also shows the relevance of the starting conditions of countries receiving subsidies in adaptation, as reported by numerous studies in the literature (Hudson and Mosley 2001 ; Dalgaard et al. 2004 ; Mosley et al. 2004 ). The first group of countries analysed is the most vulnerable and least ready, also in great need of investment to improve readiness and with great urgency for adaptation action. Despite their most unfavourable starting conditions (i.e., reduced capacity to react and severe exposure to the intemperance of climate change), this group is yet able to exploit the benefits of aid, which increase agricultural productivity, albeit to a lesser extent than other countries. It should be noted, moreover, that in these countries the ratio of agricultural value added to GDP exceeds 40 percent, so the increase in productivity in agriculture affects directly the entire economy of the country. This is an important message for donors, who should not be discouraged from allocating aid to these countries, mainly located in Sub-Saharan Africa but also in the Middle East and in Latin America (see Table 6 in Appendix).

Our analysis indicates also that climate readiness is the key element for successfully transforming received aid into actual agricultural growth: in most vulnerable countries but with high levels of climate readiness, the impact of agricultural aid on agricultural productivity is the highest. This should come as no surprise since readiness reflects the ease of doing business and measures a country’s ability to leverage investments and transform the same into adaptation intervention, taking into account economic, governance, and social variables.

A noteworthy finding pertains to the effectiveness of aid in facilitating adaptation in countries with low vulnerability levels. In this scenario, foreign aid appears to exert a not significant influence on the growth of agricultural productivity. This observation holds true for countries with both high and low readiness levels. Additionally, in the formers, a significant proportion of these countries (see Fig.  2 and Table 6 in the Appendix) report a lower quota contribution of agricultural Value Added relative to their Gross Domestic Product (GDP).

As for the control variables, we observe that money supply generally has a positive role in stimulating agricultural productivity: a larger money supply tends to reduce the interest rate, thus favouring investment and capital accumulation. Altogether, these elements could foster agricultural productivity. Greater trade openness tends instead to reduce agricultural productivity in the most vulnerable countries, regardless of their level of readiness. This could be caused by a number of factors as increased competition from imports; a shift to non-agricultural sectors and a lack of investment in agriculture from both the private and public sectors. With regard to food consumer prices, price variation appears significant only in the most vulnerable countries and has a negative impact: higher food prices reduce productivity growth. Food prices are strictly related to agricultural productivity: rising food prices can motivate farmers to increase their market participation (especially when they generally are subsistence-orientated) and to invest in agricultural technologies that can increase in turn agricultural productivity (Benfica et al. 2017 ). Nonetheless, during the food price crises of 2008, many developing countries reduced their agricultural trade surplus and eventually became food net importers: local rural farmers, typically constrained by small landholdings and input costs, and distant from markets (Wodon and Zaman 2010 ), and were not in fact flexible enough to respond to the change in agricultural relative prices (Pingali 2007a ). Hence, in those low-income countries that largely rely on agriculture as a source of income, high food prices reduce farmers’ investment capacities and thus the chances to experience agricultural productivity growth. It is nonetheless worth stressing that the overall effect of increased food prices is that of impoverishing poor households and exacerbating food insecurity (Ivanic and Martin 2008 ; Warr 2014 ).

Focusing on weather, temperatures might positively influence agricultural productivity, though the effect is mainly limited to low vulnerable countries that are less exposed to heatwaves. It is worth stressing that this definition of temperature simply refers to average temperatures, and does not identify temperature shocks.

Concluding remarks

The agricultural sector is facing different challenges. Weather conditions are threatening entire crops in both advanced and developing countries. In this context, foreign aid and development assistance become more and more relevant to preserve productivity and minimize food insecurity.

Considering that developing countries, and their agricultural sectors, are among the most vulnerable to climate change, it is important to analyze the actual effectiveness of international aid. Provided that the available evidence is often contrasting, this paper aims to contribute to the existing debate on aid effectiveness focusing on the impact of agricultural subsidies on agricultural productivity growth from a climate perspective.

To this purpose, we adopt the Rio Marker 2010 classification system that distinguishes aid into adaptation and mitigation to climate change, and we perform a two-stage instrumental variable approach to account for the potential endogeneity that aid could have on recipient countries’ agricultural productivity. We build a sample of 115 recipient countries and evaluate how instrumented agricultural adaptation and mitigation aid differently impact the agricultural Total Factor Productivity in the short-medium run.

To further advance the analysis of aid effectiveness, we have classified the recipient countries into four sub-groups based on indicators developed by ND-GAIN index, which primarily considers their vulnerability and preparedness towards climate change.

Our findings confirm that aid in agriculture has a positive impact on agricultural productivity, with a significant role played by aid in adaptation. We also found an interesting relationship between the starting characteristics of the recipient countries and aid effectiveness.

Specifically, countries that have a higher readiness and high vulnerability to climate change tend to benefit the most from aid, while those that are more vulnerable to climate change and with low readiness are not able to leverage the aid received to the same extent. Nevertheless, it is worth noting that even in these vulnerable countries, the relationship between aid and growth remains positive.

The results of this analysis not only confirm the importance of global international aid to agriculture but also suggest the importance of distinguishing between adaptation and mitigation​ flows. A more precise definition of aid may indeed improve aid impact analyses, providing more accurate results than in the past.

However, it is important to acknowledge certain limitations in this work. Firstly, although the utilization of an aggregate indicator like agricultural TFP enabled us to conduct a cross-country analysis, the model employed does not facilitate an exploration of the partial productivity dynamics of individual production factors. Additionally, our analysis was exclusively centred on the agricultural sector, without considering the potential reallocation of factors of production to other productive sectors. This aspect assumes particular significance for less developed countries, where agricultural labour permanently exhibits lower productivity compared to other economic sectors. In future research, it would be valuable to investigate whether international aid also exerts an influence on the broader economy in these countries. Footnote 2

Future work could also explore the effectiveness of adaptation aid in hot and dry countries,​ and assess the capacity of stabilizing agricultural productivity also following extreme weather events, such as temperatures heatwaves or droughts. In addition, given that the impact of aid tends to accumulate over the long term, it would be beneficial to extend the time period under consideration and employ models that capture the cumulative effect of aid.

Availability of data and materials

Data used are available on OEDC statistics, USDA statistics, ND-Gain site and World Bank statistics. Elaborations produced in the paper are available upon request.

As for specification (3), the F-statistic is equal to 6.4 and larger than the Stock Yogo critical value (5.53) for a 25% distortion. Hence, we can reject the null hypothesis that the maximum size distortion is greater than 25%.

We express our gratitude to the anonymous reviewer for their valuable insight into this aspect.

Adzawla W, Alhassan H (2021) Effects of climate adaptation on technical efficiency of maize production in Northern Ghana. Agric Food Econ 9(1):14. https://doi.org/10.1186/s40100-021-00183-7

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Acknowledgements

We would like to express our gratitude to the Editor and the anonymous reviewers for providing constructive and valuable suggestions that have significantly improved the quality of this work. The authors would also like to thank the participants to the 17th Igls Forum and to the LVIII SIDEA annual conference. We also extend our thanks to Professor D. Cavicchioli for offering helpful insights during the paper's revision phase.

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Conceptualization: MTT, LB, MP. Formal analysis: MTT, MP. Methodology: MTT, MP. Data collection: MTT. Analysis and Interpretation: MTT, LB, MP. Writing—original draft: MTT, LB. Writing—review: LB, MP. Supervision: LB. All authors read and approved the final manuscript.

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Trentinaglia, M.T., Baldi, L. & Peri, M. Supporting agriculture in developing countries: new insights on the impact of official development assistance using a climate perspective. Agric Econ 11 , 39 (2023). https://doi.org/10.1186/s40100-023-00282-7

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Artificial Intelligence and Technology for Sustainable Food Production and Future Consumption

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Food is vital for the sustenance of the global population that is growing rapidly from its current 7.7 billion to its peak by 2100 for an estimated of 11 billion (Adam, Nature 597(7877):462–465. https://doi.org/10.1038/d41586-021-02522-6 , 2021), making it key to ensure that food can be provided continuously and sustainably especially during disasters without compromising the current condition of natural resources which show decreasing trend. Issues related to food insecurity have become a dilemma for many developing countries and have unfavorably affected the livelihood of people notably the vulnerable groups such as low-income family. Thus, sustainable food production and consumption is required to ensure that global food security can be met, and the sustainability of the environment can be preserved for future generations. Studies have demonstrated that AI technology can be integrated into many aspects of the food industry such as agricultural cultivation, food processing and manufacturing, quality control, distribution and logistics, work labor, and consumer food consumption. Supportive policies from governments and strong collaboration among stakeholders are imperative to promote the embedded AI technology in the food supply chain system to achieve sustainable food production and consumption as promoted by the United Nations.

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Wang, S.L., Teh, S.Y., Ng, T.F. (2022). Artificial Intelligence and Technology for Sustainable Food Production and Future Consumption. In: Leal Filho, W., Azul, A.M., Doni, F., Salvia, A.L. (eds) Handbook of Sustainability Science in the Future. Springer, Cham. https://doi.org/10.1007/978-3-030-68074-9_55-1

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Developing Sustainable Food Systems in Europe: National Policies and Stakeholder Perspectives in a Four-Country Analysis

Alina zaharia.

1 Department of Agrifood and Environmental Economics, The Bucharest University of Economic Studies, 010371 Bucharest, Romania; [email protected] (A.Z.); [email protected] (M.-C.D.)

Maria-Claudia Diaconeasa

Natalia maehle.

2 Mohn Centre for Innovation and Regional Development, Western Norway University of Applied Sciences, 5063 Bergen, Norway; [email protected]

Gergely Szolnoki

3 Department of Wine and Beverage Business Research, Geisenheim University, 65366 Geisenheim, Germany; [email protected]

Roberta Capitello

4 Department of Business Administration, University of Verona, 37129 Verona, Italy

Associated Data

The data presented in this study are available in English language in Table A2 and Table A3 in Appendix A .

To address climate change, health, and food-related challenges at the international and regional level, policy makers and researchers are starting to acknowledge the importance of building and developing sustainable food systems (SFSs). This study aims to discuss the drivers of, barriers to, and policy recommendations for developing sustainable food systems in four European countries (Germany, Italy, Norway, and Romania). We used critical frame analysis to investigate national policy documents on sustainable food systems and conducted in-depth interviews with various national stakeholders representing policy makers, agrifood businesses, and civil society. The novelty of this research lies in comparing national policy approaches and stakeholders’ opinions on SFS development in a multi-country analysis. These European countries have different conditions in terms of geography, socioeconomic situation, environmental performance, and sustainability orientation. Several cross-cultural differences and gaps in the existing national policies for sustainable food systems were identified, and solutions that help overcome these issues have been suggested. The first step in developing SFS should focus on interdisciplinary and trans-sectorial policy integration combined with increasing stakeholder collaboration across all sectors of the economy. We also recommend more active involvement of consumers in the food system, developing information-sharing networks, and increasing collaborations within the food supply chains.

1. Introduction

The past century has seen a rapid increase in global challenges, both environmental and socioeconomic. This has resulted in the emergence of sustainable development rhetoric emphasising the need for systemic changes in the relationship between nature and humanity. Since 1987, when the Brundtland report institutionalised a sustainable development concept [ 1 ], various actors have combined their efforts to develop sustainable policies in different sectors, including agriculture and the food industry. International sustainability efforts were officially initiated at the 1992 Earth Summit in Rio de Janeiro and were recently globally extended through the 2030 Agenda for Sustainable Development and the 17 Sustainable Development Goals (SDGs) [ 2 ].

In this context, the European Union (EU) adopted several policies to increase sustainability in the food system—for example, promoting a circular economy, increasing resource efficiency, introducing sustainability ‘from farm to fork’, and ecosystem preservation and restoration [ 3 ]. Despite this, the European Commission [ 4 ] finds that its member states are still performing poorly on several of the SDGs, especially SDG 12 ‘Responsible consumption and production’ and SDG 14 ‘Life below water’. The EU governance structures seem to be ill-adapted to the systemic nature of food-related challenges, stressing the need for coherent policies stimulating more sustainable food practices [ 5 , 6 ].

While recognising the actions taken so far, the recent literature emphasises the gaps in European food policies. For example, several studies call for vertical and horizontal policy integration, improving coordination between the involved actors and increasing feedback loops within the multi-level governance [ 7 , 8 ]. It is also necessary to understand different issues related to building a holistic food system (e.g., introducing sustainable food standards and metrics), while at the same time taking into consideration regional differences [ 9 , 10 ]. Therefore, further investigation is required concerning the contribution of the different stakeholders involved in sustainable food systems (SFSs).

There is still a lack of research in this field. One of the few existing studies analysing stakeholders’ perspective involves EU agency representatives and researchers [ 6 ]; nevertheless, it ignores policy makers, businesses, and civil society at the national and regional levels. This study finds that existing policy focuses mainly on food producers and consumers, while neglecting retailers. It also demonstrates low participation of food producers in policy making. The other available studies have a number of limitations. One study [ 11 ] examines various local, national, and international stakeholders but only analyses written public communications (e.g., food advertisements or articles from specialised periodicals). Domingo et al. [ 12 ] emphasize the connection between food security and SFSs from the perspectives of local community leaders. However, their study only touches upon the issues of how the sustainable food system is understood or what its challenges are. Another study [ 13 ] analyses the challenges and successes in developing a local sustainable food system, but it is limited to one country (Australia).

The current study aims to address the aforementioned research gaps by discussing the drivers of, barriers to, and policy recommendations for developing sustainable food systems (SFSs) in four European countries representing different economic, geographical, and cultural contexts.

Our study objectives are threefold:

• (1) identify the dimensions of food sustainability addressed in the four involved countries;
• (2) analyse the main drivers of and barriers to developing SFSs;
• (3) analyse and propose common and specific national solutions for developing SFSs.

To reach these objectives, we analyse national policy documents related to food and sustainability and conduct interviews with various groups of stakeholders in four European countries (Germany, Italy, Norway, and Romania).

Our research objectives are in line with the holistic SFS approach proposed by [ 9 , 14 ], which suggests considering the interconnections between food system members and SFS components, as well as the whole system. For this reason, unlike previous studies [ 6 , 10 , 12 , 13 ], this research investigates both national policy documents and stakeholder perspectives on SFSs in a multi-country comparison. The selected stakeholders represent public actors and non-profit and commercial organisations, which is a desirable combination for collaborative SFS efforts [ 8 ]. Overall, this paper provides new knowledge on the European national SFS attempts and, by comparing them, lays a foundation for the development of a coherent SFS policy framework.

The paper has the following structure. First, we provide a brief overview of the theoretical perspectives on sustainability-related issues in the food system. Then, we present our methodological approach and the main findings on national SFS policy discourses and stakeholder perspectives. Based on this, we discuss policy implications and recommendations. Finally, we indicate the limitations of this study and suggest future research directions.

2. Theoretical Background

2.1. food sustainability and sfss.

Environmental issues on a larger scale were first acknowledged in the United States in the 1950s, when decision makers and the public had to reflect on the negative environmental impact of economic practices due to a series of scandals related to the use of chemicals in agriculture [ 15 ]. The concept of sustainability, which highlights the importance of nature for the socioeconomic system as a result of constant population growth and limited resources, emerged in the 1970s [ 16 ], while the notion of sustainable development was first mentioned in 1987 [ 1 ]. Although sustainability encompasses three acknowledged pillars—economic, social, and environmental— Béné and colleagues [ 17 ] argue for a larger focus on the environmental dimension.

The concept of SFSs appeared in the 1980s and addressed the negative impact of agricultural practices on the quality of food and human health [ 18 ]. In the 2000s, the SFS took its current form, representing a socially accepted, holistic, and adaptive complex food system that focuses on achieving sustainability [ 14 , 19 ].

According to the Food and Agriculture Organization [ 20 ] (p. 1), an SFS ‘delivers food security and nutrition for all in such a way that the economic, social and environmental bases to generate food security and nutrition for future generations are not compromised’. Moreover, an SFS ‘is one that contributes to all three pillars of sustainability in a balanced manner, and requires the system to be fair’ [ 6 ] (p. 31). Additionally, an SFS should focus on food security and safety, sustainable and healthy diets, trade-offs, multi-actor acknowledgement, feedback loops, complexity, and resilience to shocks [ 17 ].

To summarise, an SFS consists of an efficient, balanced, and fair system of production, distribution, consumption, and disposal of food based on the three pillars of sustainability (environmental, social, and economic) and the interactions and collaborations between different stakeholders.

Many studies address the consumption side of SFSs by examining individual factors that influence sustainable food choices (e.g., consumer preferences, personal beliefs, and willingness to pay) [ 21 , 22 , 23 , 24 , 25 ]. The majority of the studies indicate that knowledge [ 26 ] and price [ 27 ] are the most common factors influencing consumer preferences for sustainable products. However, there is a need to consider a wider range of determinants of sustainable food choices—individual factors being only one of them. Macro and structural causes of sustainable consumption are considered even more important than individual-level attitudinal variables for the transition towards SFSs [ 28 ]. According to Kearney’s study [ 29 ], urbanisation, trade liberalisation, and transnational food retailing have contributed to unsustainable food consumption. Moreover, Bricas et al. [ 30 ] address the role of cities in supporting rural communities for developing SFSs, through investments, collaboration policies, local market development, and public procurement from rural communities’ nearby cities. Furthermore, the societal context and policies influence the transition towards SFSs through education, infrastructure, and regulations [ 23 ].

Production is another important SFS element. Most studies focus on different topics related to agriculture [ 31 , 32 ], and only a few have examined the role of industrial producers [ 33 ]. Several studies address specific drivers, such as food waste valorisation in manufacturing, biosensors, nanotechnologies, innovation, and information technology [ 34 , 35 , 36 , 37 , 38 ]. Additionally, other studies [ 12 , 13 ] point out the importance of locally produced food for ensuring food security and sustainability of the food system.

Few studies approach sustainability from both the production and consumption perspectives to identify the best solutions for SFS development. For example, Lorenz and Veenhoff [ 39 ] highlight the role of solidarity and consumer empowerment in stimulating changes in production methods, while Allen et al.’s study [ 40 ] points out the need to rebalance the price of unsustainable food with its true costs, which include the negative effects of agrifood practices on the environment.

In addition, few studies focus on the distribution system as part of an SFS. Existing studies present solutions related to energy consumption, carbon footprint, and cost or time efficiencies [ 41 , 42 , 43 , 44 ].

Furthermore, food waste management is considered one of the solutions for developing SFSs. For instance, some studies focus on methods of food disposal [ 45 , 46 ], while others analyse the costs attributed to food disposal [ 47 , 48 ] and alternative solutions such as food sharing and donation [ 49 , 50 ].

Overall, many studies on SFSs have recently emerged. However, only a few address the concept of SFS and suggest guidelines for its development [ 6 , 26 , 40 ]. There is also a need for more research focusing on various stakeholders involved in the production, distribution, consumption, and disposal of food, as suggested by the SAPEA report [ 14 ].

2.2. Policies for SFS Development

In the EU, the European Commission [ 4 ] emphasises the need to implement changes in several food-related areas, such as education, research, innovation, finance, and corporate social responsibility. This calls for more integrated food policies.

Similarly, De Schutter et al. [ 5 ] identify several areas for policy improvement, such as coherence across policy areas and governance levels and increasing food democracy. According to these authors, EU policies are ill-equipped to support local ‘alternative food system’ initiatives such as community-supported agriculture schemes and local sourcing for school canteens. There is a need for multi-level governance promoting collaboration and practice-sharing, as well as further support for inclusive, bottom-up initiatives. Food policies should also have an integrated long-term perspective addressing coordinated shifts across the whole food system. Although some tools for SFS development exist (e.g., food schemes and food education), these have not had the desired effect [ 51 ]. More information and knowledge about food should be available to stimulate better consumer choices and increase awareness around their consequences: for instance, communicating environmental footprints to consumers through labels or raising consumers’ awareness about food-related emissions [ 52 , 53 ]. Moreover, giving a default choice of sustainable food in different events or places, through nudging techniques, seems to be considerably effective for pushing the consumer to choose sustainable food. For example, an experimental study [ 54 ] conducted during three conferences showed that the participants were more inclined to opt for the vegetarian buffet instead of the non-vegetarian choice, if the vegetarian menu was the standard lunch, i.e., the default choice. Additionally, another study [ 55 ] conducted on a university campus indicates the positive effect of the nudge in choosing the non-meat food option, by paying attention to the existence of a sustainable default lunch, the default menu configuration, and gender preferences.

There is also a growing focus on how to integrate nutrition and health-related aspects into the common agricultural policy (CAP) [ 56 ]. Examples of possible policy solutions in this regard include fiscal measures and restrictions for unhealthy foods, nutrition education in schools, and nutritional labelling [ 51 ]. In terms of environmental issues, Recanati et al. [ 51 ] emphasise the need to align policy objectives with actions and to consider context and resource particularities through diversified measures. Moreover, Baldy [ 52 ] raises concerns about the economic security of small agrifood businesses due to strict EU certification processes, which make large companies more competitive. A reduction in bureaucracy can help address these issues. The literature also acknowledges the role of researchers [ 51 ]. For example, the development of innovative sustainability metrics can enable SFS actors to better assess their sustainability-related actions [ 10 ].

In addition, several studies highlight the importance of increasing collaboration between different stakeholders at all levels of the food system [ 7 , 9 , 12 ]. Moschitz’s study [ 7 ] proposes stronger involvement of the civil society to achieve a coherent sustainable food policy.

Furthermore, the collaboration between urban and rural areas for SFS development is emphasized in the literature [ 30 ] by pointing out the need for local and regional policy development to sustain the rural areas around cities. These could lead to accessible locally produced food for the city inhabitants, lower transportation costs, and higher incomes for farmers, reducing inequalities within the urban population and ensuring food security [ 30 ].

3. Materials and Methods

This study focuses on four European countries (Germany, Italy, Norway, and Romania) that represent different conditions in terms of geography, socioeconomic situation, environmental performance, and sustainability orientation. Norway, representing Northern Europe, had the highest gross domestic product (GDP) per capita in the sample (EUR 69,770 in 2019). Germany, representing Western Europe, had a GDP per capita of EUR 35,970 in 2019, which was over half of Norway’s GDP. Italy, representing Southern Europe, had a GDP per capita of EUR 26,860 in 2019, which was EUR 9000 less than Germany. Romania, representing the former Central and Eastern Communist Bloc, had a GDP of EUR 9130 per capita in 2019 [ 57 ]. Concerning their focus on sustainability, the four countries are also very different. Norway is the only country in the sample that has a reserve of biocapacity, while the other three countries have a debt in biocapacity (calculated as the difference between biocapacity/person and ecological footprint) [ 58 ]. In addition, Norway and Germany are ranked 9th and 10th in terms of the environmental performance index, which assesses national environmental health and ecosystem vitality. Italy and Romania are ranked 20th and 32nd, respectively, of 180 countries [ 59 ].

Our methodological approach involved two parallel stages of analysis. Firstly, we analysed the national policy documents on SFSs in each country by using critical frame analysis. Secondly, we conducted in-depth interviews with various national stakeholders representing policy makers, agrifood businesses, and civil society, and we analysed them with the help of NVivo and MaxQDA software. Both critical frame analysis and content analysis allowed us to extract key themes, barriers, and solutions proposed for the development of SFSs.

3.1. Analysis of National Policy Documents on SFSs

The objective of this analysis was to identify SFS-related issues addressed by the main national policy documents, as well as proposed solutions. The document analysis included two steps: document selection and critical frame analysis.

In the first step, we selected the most representative policy documents related to SFSs in each country. We searched through legislative texts, national strategies, political plans, parliamentary debates, political speeches and declarations, and party programs. The search words included the following: sustainability, sustainable, food, green, environment, organic, and health. The search was carried out in April 2019. Documents were added to the list until they provided no additional information or there were no more documents to add. After skimming through the documents, we selected those that focused on aspects related to both food and sustainability, even if, in some cases, the latter was mentioned only in the background. We ended up with a list of 15–20 documents per country. To ensure diversity within each country, as well as balance and comparability between the countries, we selected the 10 most important documents in each country based on the following criteria: document’s relevance to national policy in the context of food and sustainability; diversity in terms of the type of document; and diversity in terms of topic ( Table 1 ).

Selected policy documents in each country.

Note: L = Law; Dlgs = Legislative Decree; OG = Ordinance of Government; EOG = Emergency Ordinance of Government; MO = Ministry Order; ILR = Information on Laws and Regulations; SP = Strategy Plan; R = Regulation; CL = Circular Letter.

In the second step, the 40 selected national documents were analysed using critical frame analysis, a widely acknowledged approach for analysing policies on health, ethics, and food-related topics [ 60 ]. This approach provided the structure to policy text exploration, and therefore, it contributed to identifying and comparing problems and solutions in the four different analysed countries.

The critical frame analysis was conducted by following two phases.

In the first phase, we thoroughly read the texts of all 40 documents and synthetised the information in the four national languages, based on a supertext template developed by [ 61 , 62 ]. Each template presented information about the text in general, as well as the voice, diagnosis, prognosis, normativity, balance, and further comments (see Table A1 in the Appendix A ).

In the second phase, the 40 supertexts were translated into English, and we then identified the main issue frames in each document and compared the documents investigating the same issues within each country and across countries in line with the research objectives. All five authors of this paper were directly involved in conducting this analysis, while other members of the research project supervised the process. Researchers exposed the frames in the policy texts to explore discourses, context, topics, representations, coherency, inconsistencies, and normativity and to identify problems and solutions in policy debates [ 63 , 64 ].

3.2. In-Depth Interviews with National Stakeholders

The objective of the in-depth interviews with national stakeholders was to explore their opinion on SFS development in each country.

To achieve a heterogeneous set of informants, we selected different stakeholder groups: policy makers at the national and regional levels, agrifood producer associations, institutions responsible for food certification, agrifood consultants, consumer associations, environmental associations, health associations, cultural associations, non-governmental organisations (NGOs), and researchers ( Table 2 ).

Informant type interviewed by country.

The informants interviewed per country had a professional background, experience, and knowledge related to SFSs. The national sets of informants were selected to ensure comparability between the countries. We interviewed ten representatives of the different stakeholder groups in each country.

The interview guide was first developed in English and then translated into the respective languages using back-and-forth translation. The following topics were addressed: the concept of food sustainability and SFSs; drivers of and barriers to SFS development; the role of regulations, policy, education, infrastructure, and technology; the role of SFS actors; and future perspectives. We used a semi-structured interview approach by asking non-exhaustive, open, storytelling, and probing questions to encourage the dialogue.

The interviews were carried out in April to September 2019. They were recorded and transcribed in national languages. All five authors of this paper were directly involved in conducting the interviews and analysing the transcripts; other members of the research project collaborated in conducting interviews, transcriptions, and content analysis. We used the constant comparative method [ 65 ] for text analysis, which is based on the following steps.

In the first step, the content analysis was facilitated using NVivo and MaxQDA software [ 66 ]. In each country, the interview transcripts in the national language were transferred to one of these two software applications.

In the second step, at least two coders read each interview text in each country and coded the text by using the software. The first coder created initial coding categories that reflected the consistencies and main themes emerging in each text. The second coder audited the text, paying careful attention to those areas that the first coder identified as exemplary responses that illuminated the emergent themes [ 67 ]. The coding categories were created in English to allow comparability across all four analysed countries.

In the third step, the categories and themes were compared within the same interview and between interviews [ 68 ].

Lastly, the coded categories were analysed and compared in English between the four countries to identify main common and specific themes related to drivers and barriers, as well as solutions for developing SFSs.

The findings of the policy discourse and stakeholders’ perspective analysis are synthetically illustrated in Figure 1 and Figure 2 .

Understanding of food sustainability; barriers to, drivers for, and solutions for SFS development identified in policy discourse in the four investigated countries.

Understanding of, barriers to, drivers for, and solutions for SFS development identified by stakeholders in the four investigated countries.

4.1. Dimensions of Food Sustainability and SFS

Some dimensions of food sustainability receive considerable attention from both national policies and interviewed stakeholders in all countries (see Table A2 and Table A3 in Appendix A ).

Most of the analysed policy documents focus on the social dimension of sustainability (e.g., D8, D16, D25, D31): on issues such as public health, food safety, correct product information for consumers, and consumer education. However, stakeholders differently approach the social aspects of sustainability in the four countries. Norwegian stakeholders (S23, S29) argue that food sustainability goes beyond reducing emissions and pollution and includes such social aspects as the working and living conditions for employees in the food industry. Some German (S7, S9, S10) representatives further emphasize the social dimension in the whole value chain. German and Norwegian stakeholders (S10, S21–S24) also address the nutritional aspect of sustainable food (e.g., hunger, obesity, affordability, and healthy diet). Food availability, in terms of access and affordability, is a requisite for food sustainability for the Romanian experts (S31, S36, S39). Some Italian informants (S11, S17, S20) highlight the importance of recovering traditional food heritage to generate positive spillovers at both production (e.g., biodiversity conservation and local know-how) and consumption (waste reduction and efficient use of natural resources) levels. One Romanian stakeholder (S32) also emphasises the need to preserve the local food heritage as part of developing an SFS.

Another common dimension of high interest in the four countries is the environmental dimension, e.g., protection of environment, biodiversity, and vulnerable ecological areas. Meanwhile, most stakeholders associate the SFS with the environmental dimension of sustainability. Some stakeholders focus more on eco-labelling (especially the German ones—e.g., S1–S3), protection of natural resources and biodiversity (Italians—S18 and S20), pollution and food waste (Norwegian stakeholders—S22–S30), and, in general, environmental protection and conservation (almost all Romanian interviewees) and planetary boundaries (Germans and Romanians—S4, S6, S36).

However, we also find variations between the countries in terms of addressed topics. In the German policy discourse, there is a strong focus on environmental protection (e.g., soil and water protection and air pollution) and the labelling of organic products, as well as food and resource waste (e.g., D3, D4, D6). In Italy, there is a greater emphasis on the economic dimension of sustainability, e.g., the transition of the whole economic system to a green economy and promoting various territorial collaborations (e.g., rural district, green community—e.g., D12).

In Norway, the focus is on animal welfare, with seven out of ten documents mentioning this issue (D22, D25–D30), and on sustainable growth for aquaculture both in economic and environmental terms (e.g., D21). In Romania, the focus is on food production, labelling rules, and organic agriculture.

Only a couple of Italian and Norwegian informants (S12, S15, S24, S26) discuss the economic dimension of SFSs, while both German and Romanian stakeholders (S7–S8, S33–S34, S37) emphasise that food producers and consumers will only act if it is economically viable for them.

4.2. Drivers for and Barriers to Developing SFSs

One of the main drivers and barriers towards SFS development emerging in both policy discourses and stakeholders’ perspectives for all countries is the need for further understanding and knowledge of how various actors (i.e., producers, intermediaries, retailers, consumers) can contribute to sustainability (e.g., D1, D12, D27, D32, S2, S9, S12, S26, S34). Additionally, according to the stakeholders, the distribution of the right information is another common driver. As pointed out by the Norwegian stakeholders (S26), a lot of information about sustainable food comes from private individuals (e.g., bloggers, YouTubers) instead of governmental officials. Furthermore, most Italian stakeholders highlight the poor quality of information and the lack of reliable institutional information, while German experts mention both the lack of consumer awareness and misleading claims (e.g., S2, S3, S9). Similarly, in Norway, the stakeholders discuss the confusion around the concept of sustainable food (e.g., S22–S24, S26). They (e.g., S26) argue that there is a need to adjust the definition of food sustainability according to local conditions, e.g., it might be sustainable to produce dairy products if the agricultural land cannot be used in any other way due to natural constraints. Additionally, one Romanian expert (S36) emphasizes the negative effect of the conflicting messages shared through the Internet and the lack of positive role models. The communication is often emotionally driven, and the risk is that people end up with a skewed concept of food sustainability (S26). Additionally, there is an incorrect use of information on food products’ labels (D33, D39), i.e., missing, incorrect, and abusive use of information, especially for organic products.

According to both the documents (e.g., D1, D13, D24, D31) and the interviewed stakeholders (e.g., S9, S16, S24, S33), the role of consumers is recognized in the SFS in all four countries; the need for guiding consumers towards a sustainable food choice is mentioned. Additionally, considering the stakeholders’ opinions, what consumers acknowledge as good food may also be an issue. For instance, Norwegian stakeholders (S22, S26, S28) highlighted that consumers need to learn to eat the whole animal and be less critical of expired food to reduce food waste. In contrast, in Romania, the focus is still on developing the infrastructure for food waste management (S31), while consumers’ reluctance to change (S31, S36) and ‘living in the moment’ attitude (S32) are seen as other relevant barriers. Furthermore, some stakeholders (e.g., S1, S17, S22, S36) believe that established food habits and a lack of time prevent consumers from making more sustainable food choices. The age of consumers is another driver. Younger generations can more easily adapt to new sustainable food habits, while older generations have problems changing their food consumption. As discussed by German informants, ‘habits to buy and cook what has always been bought and cooked’ makes the transformation more complicated. Food is a sensitive and individual product, and people do not like to be told what to eat. Norwegian stakeholders also agree that, to a large degree, habits and traditions shape consumer diets and create resistance to change. Meanwhile, culture and history strongly influence consumers’ mentality (e.g., Romanian consumers are used to buying large quantities of food as a result of food deprivations during the communist era). This barrier should be taken into consideration when developing communication strategies for consumers.

Although it is not mentioned in the policy discourses, another common driver and barrier for stakeholders is the availability of sustainable food, in terms of access and affordability. Firstly, in Germany, although the selection of sustainable food—mainly organic-certified—has been steadily increasing, several stakeholders highlight the problem of easy access to sustainable food in retail shops, restaurants, and cantinas (S1, S3–S5). Romanian sustainable food initiatives are limited to only a few types of organic food, which are only sold in supermarkets or online (S34, S39–S40). However, many Romanians obtain their food directly from farmers and their own family gardens, which makes the local supply chain important for gaining access to sustainable food. Norwegian stakeholders (S22, S27, S29) complain about the poor selection of sustainable food in their supermarket chains and blame their limited access on the power of retailers. Similarly, Italian stakeholders (S14–S15) highlight the retailers’ role in influencing consumers’ choices through their store assortments and sales strategies, and they (S16–S19) call for fairer procurement strategies and greater efforts in logistics and product packaging (e.g., reducing the use of plastic packages). Secondly, several stakeholders (e.g., S3–S4, S9–S15, S27, S29, S30, S32, S36, S39) consider the affordability of sustainable food as an important barrier and mention the negative effect of high prices on the demand for sustainable food, which is seen as a luxury by Italians and Romanians. German, Italian, and Romanian stakeholders also highlight the higher cost of producing and marketing sustainable food, which, however, will decrease as sustainable production practices become more mainstream.

Finally, technology, research, and innovation are acknowledged as common drivers of SFS development in both policy discourses and stakeholders’ perspectives (e.g., D20, D35, S5, S13, S18, S20, S27, S36, S37), as they ensure food safety, productivity, economic efficiency, lower environmental impact, better control and information, and higher user convenience.

Some drivers and barriers receive special attention in each country.

In the Italian policy discourses (D12, D17) and German and Romanian interviews (S6, S33), another concern is the competitiveness of national products on international and national markets. Furthermore, German and Romanian informants (e.g., S7–S8, S40) discuss unfairness in terms of sustainable food labelling and production (e.g., extra labelling and production costs that organic producers have to bear while conventional producers do not).

The German documents (D1, D4–D6) identify overusing the Earth’s limited resources as a general problem and emphasise the great potential of household consumption to reduce environmental impacts and food waste, while German stakeholders (e.g., S1, S3) mention the strong conventional agricultural lobby as a challenge towards SFS development.

The Italian documents highlight (D11–D13, D15, D17, D19) the need for a different economic model that focuses on saving natural resources; providing quality food products in terms of safety, health, and environmental protection; and supporting vulnerable producers and rural areas. While Italian stakeholders (S14, S18–S19) identify the lack of a common set of criteria defining sustainable food as a major barrier that leads to several challenges, including proliferation of private certification schemes that are mainly implemented by large producers, the role of certification for consumers’ food choices is marginal, and the interest among retailers to increase the availability of sustainable food is low. Moreover, some Italian stakeholders (S12–S13) claim the oligopolistic power of food retailers, who, paradoxically, continue to adopt unsustainable practices in food procurement, logistics, and packaging, despite producers’ investments in sustainability (e.g., in the case of fruit and vegetable producers).

The Norwegian policy documents (D22, D23, D25-D30) identify a large number of sustainability-related issues as important drivers for building an SFS, including animal welfare; the labelling of organic products and its misuse; the dangers of using genetically modified organisms (GMOs); and the overpopulation of urban areas, leading to reduced development of rural areas and agriculture-related industries. A Norwegian stakeholder (S27) believes that Norwegian food safety regulations prevent the use of leftover foods and therefore lead to more food waste. He also mentions the lack of marketing skills among Norwegian food producers, which complicates the promotion of local sustainable food. The Romanian documents consider the context of sustainable development as having a more voluntary rather than compulsory character. They also identify the problems related to eco-conditionality compliance (i.e., granting funds in exchange for good environmental practices in D31 and D38), food labelling, food waste, and controlling and reducing the use of pesticides in agriculture for pollution and health-related reasons (D32, D36). Romanian stakeholders (e.g., S37–S39) address the absence of a consolidated legislative framework and national strategy for SFS development, food security, and food waste along the supply chain; the lack of interest towards sustainability among food distributors; and the misalignment of economic interests between various actors in the food system (S31, S36). This results in limited administrative facilities and a lack of support and incentives to stimulate interest for sustainable food among both producers and consumers.

4.3. Proposed Solutions for SFS Development

The national policy documents and the stakeholders suggest a number of common solutions for SFS development for all four countries.

A common general solution is to increase collaborations in the food system (e.g., D9, D14–D15, D23, D32, D35, S2, S11, S24, S39). Additionally, the stakeholders discuss various solutions for improving collaboration between different actors. Thus, it is crucial to encourage a variety of different actors to join in, with authorities taking on a coordinator role (e.g., S8, S18, S24, S31). Italian stakeholders (S11, S14) suggest organising different ‘discussion tables’, while Romanian informants (S31, S32, S39) propose creating a national rural development network and associations for sustainable producers. The extended collaboration between different SFS actors will allow the authorities to use one voice to communicate food sustainability, which is an important success condition according to the interviewees (S8, S15, S19, S22, S39, S40).

Another common general measure for developing the SFS is providing correct information for consumers (D1, D19, D24, D38, S1, S11, S24, S38).

In addition, the stakeholders discuss concrete actions required for improving the education and information for consumers and other actors. For example, many stakeholders agree that extended communication efforts are required to increase consumers’ interest in sustainable food—e.g., by including sustainability in the school curriculum (e.g., S8, S15, S28, S32). While communicating with consumers, authorities need to take the lead (S2, S4, S18–S19, S24, S33) and use one voice (S11, S22) to avoid confusion. At the same time, the majority of the German stakeholders (S2, S5) very strongly recommend that public authorities also provide clear and uncomplicated information about sustainable food to producers. They also need to focus more on the environmental dimension of sustainability to bring young consumers on board (S3–S4, S15, S17), refer to scientific studies (S11, S15), and enlarge the concept of sustainable food beyond organic food (S11–S12, S15–S17). Some German stakeholders (S2, S7) also suggest softly influencing (‘nudging’) consumer choices instead of imposing new rules like banning junk food. In addition, learning projects (e.g., comparing an organic field with a conventional field) can help both adults and children to understand the impact and consequences of their decisions and actions on the environment (S6). Italian, Romanian, and Norwegian stakeholders (e.g., S15, S28, S36) also mention the importance of influencers, role models, and positive examples in media communication, especially for promoting sustainable food to younger generations. Some Italian and Romanian stakeholders (e.g., S17, S36) believe in ‘innovative’ communication tools such as apps, ‘smart labels’, transparent labels, and bilateral communication between businesses and consumers.

Likewise, stakeholders argue that distributors have substantial power to influence consumer choices—even simple measures such as product placement can make a big difference. Some stakeholders (e.g., S3, S12, S25, S32) emphasise the role of public procurement in encouraging sustainable food practices. Additionally, Norwegian experts (e.g., S22–S23, S27) want grocery chain stores to take more responsibility by offering and promoting more sustainable foods and explicitly explaining the consequences of choosing or not choosing those foods. One Romanian expert (S34) emphasises the need to develop dedicated sustainable shops and recycling infrastructure in shopping areas. Some Italian stakeholders (S18–S20) address non-sustainable transport and logistics systems. At the same time, German and Italian stakeholders (S8, S16) further argue that consumers can have a strong influence on retailers by expressing their preferences, while retailers may influence producers. For example, an Italian stakeholder (S14) highlights the importance of involving retailers in sustainability discussions and certification.

Additionally, food producers need to be honest and transparent regarding how food is being made, and they should offer certified high-quality products (S3, S7, S26, S29, S32). However, high food quality can also be an issue because it makes food less affordable. To address this issue, Romanian and Norwegian stakeholders (e.g., S27, S28, S33, S40) suggest providing benefits to sustainable food producers—e.g., by reducing taxes and serving their food at all public events—and considering higher taxes on unsustainable food. Several German interviewees (e.g., S1, S9) point out the importance of taxation reform for sustainable food production—e.g., by introducing CO 2 taxation. To make consumers aware of the true costs of food products, German and Italian stakeholders (S8, S15) suggest showing true cost prices at the point of sale.

Both the analysed policy documents and stakeholders acknowledge another general need: that of further developing the regulatory framework through establishing standards of sustainable food production and labelling schemes (e.g., D2–D3, D15, D26–D30, D33, S10, S15, S18, S21, S29, S34, S36).

Specifically, on the one hand, the prevailing solution in the Norwegian policy documents (D22, D25–D30) is strengthening the authorities’ control in food production and its related activities, such as the holding of animals. The documents mainly focus on setting the rules and requirements for the various actors in the food system to ensure food safety, sustainable development, and adherence to ethical concerns. Control is also an important part of the Romanian policy solutions (D32, D34, D37), especially concerning human health and food safety. On the other hand, from the perspectives of stakeholders, the Germans (S5, S10) wish for a change to the standards for animal welfare, while the Norwegians (S27, S29) call for more laws and regulations regarding animal feed, animal products, and food waste. Additionally, it is important to have a national strategy on SFS development with clear objectives, together with a national plan with mandatory implementation and clear indicators, as suggested by Romanian and Italian experts (S11, S14, S32, S36, S39). Moreover, as recommended by one of the Norwegian stakeholders (S24), a sustainable food policy should cover various target areas, such as district/rural, agricultural, and industrial policies.

Both the analysed policies and stakeholders focus on finding solutions to diminish or limit humans’ negative impacts on the environment, such as implementing better food waste management (D4, D13, D36, S6, S13, S23, S24, S25, S34). Public authorities and consumer associations (S2, S8, S18–S20, S25) believe that greater efforts should be made at the distribution level, in terms of increasing food shelf life, recycling, reducing food waste, and organising food donations, while policy documents in all four countries (D1, D14, D22, D35) point out the importance of increasing awareness about biodiversity.

In addition, considering the social dimension in particular, the German documents (D1, D6) suggest that people should lead a sustainable lifestyle. Moreover, the perspectives of German and Norwegian stakeholders (e.g., S1, S3, S7, S25–S27) on health, nutrition, and diets emphasise consumers’ need to adjust to a healthier and more sustainable diet that consists of more fruit, vegetables, and whole grains and less meat, especially in school cantinas and public institutions.

From the perspective of Italian policies (D11–D12, D17), it is important for society to include environmental and social considerations in public decision making to favour the transition to a green and circular economy. However, the documents mostly provide the general principles of this transition, with limited practical applications (D17). An implemented solution is the regulation on green public procurement in order to stimulate sustainable production practices along the supply chain through the national and regional public administrations (D16). Additionally, according to German documents (D3, D9), there is a strong effort to increase the share of organic food in the agricultural sector by introducing a coherent legal framework, improving access to organic farming, making use of and expanding existing demand potential, improving the performance of ecological agricultural systems, and rewarding environmental services. Furthermore, Norwegian stakeholders (S21, S25, S27–S29) believe that consumers should be encouraged to buy more locally produced food by reducing taxes on local food, supporting local farmers, and increasing marketing efforts for local food.

Another important general solution from the point of view of stakeholders is the development of technologies, infrastructure, and innovations for creating SFSs. Thus, stakeholders (S2, S8, S11, S17–S20, S24, S26–S27, S30, S36) argue for the increased use of sustainable innovations and technology throughout SFSs (e.g., aimed at carbon- and water-footprint measurements, packaging, product shelf life, food waste, improving digitality). All Italian stakeholders agree that technology can help food producers improve their sustainable practices (e.g., big data in agriculture or nanotechnology for packaging and product shelf life). The regional Italian authorities (S18–S19) particularly highlight the relevance of entrepreneurial skills in terms of innovation propensity and cooperative business models.

There is also a need for infrastructures such as developing ‘incubators’ and digital platforms where different SFS actors can exchange ideas and knowledge, improving food waste disposal, especially in Romania (S34, S36, S39). Furthermore, German and Italian experts (S5, S16, S18) suggest increasing public investments in research for developing practical sustainable solutions, while Norwegian informants (e.g., S28) stress the need for increased knowledge on biological processes, ecosystems, and agriculture in general, because it is important to have a more research-based approach and to test sustainability-related measures before implementing them on a large scale. Similarly, Romanian stakeholders (S32, S36, S39) suggest establishing professional associations on a global level to analyse risks in the food system.

Furthermore, we find country-specific policy measures. For example, the Italian policy documents relevant for the agrifood sector (D13–D15, D18–D20) include product traceability, financial support for environmental initiatives, biodiversity protection, collaboration networks, and research and innovation. In addition, some Norwegian policy documents suggest measures for achieving sustainable growth in both economic and environmental terms (D21) and further development of rural areas (D23). Other Romanian solutions from the policy discourses aim to reduce the use of pesticides (D32, D37) and reassess the production process to become organic (D31).

5. Discussion

Our results indicate that all pillars of food sustainability (environmental, social, and economic) are perceived as crucial for further SFS development in the four selected countries, despite some variations in importance. Moreover, there is a need to reach a consensus on the definition and understanding of food sustainability, as was also observed by [ 14 , 17 ]. However, similar to [ 69 ], we acknowledge the importance of the national context while providing the recommendations.

Based on the analysis of the common drivers and solutions in the national policy documents, we identify the following existing measures for SFS development. First, the analysed documents in all four countries highlight the need to better understand different actors’ contributions to food sustainability and increase collaborations in the food system, as this can improve the regulatory framework and competitiveness of local products in national markets [ 29 ]. For example, a measure proposed in the Italian documents is to develop collaboration networks, as also discussed by [ 14 ]. Second, national policies aim to increase consumer awareness about biodiversity and provide correct information about sustainable food, which can help consumers to make better-informed decisions [ 52 ]. Third, measures of environmental protection (e.g., reducing overexploitation and food waste, using renewable energy) ensure food sustainability, as also indicated in previous studies [ 9 ].

Additionally, the country-specific measures suggest that rewards or financial support are provided for environmental practices in Germany, Italy, and Romania. Moreover, in Italy and Norway, the policy documents focus on vulnerable producers and the development of agriculture-related industries in rural areas. Italian policies emphasise the need to ensure product traceability and green public procurement [ 41 ]. The Norwegian policies focus on ethical and sustainable principles in food production, especially in relation to animal welfare, similar to [ 70 ]. Better control for food safety and quality (e.g., GMO, pesticide use) is addressed in Italy, Norway, and Romania.

Despite the existing measures discussed above, the transition towards SFSs requires additional policy efforts. Based on our interviews with different types of national stakeholders, we identify several gaps in the existing national SFS policies and indicate how these gaps can be addressed.

First, the stakeholders in all four countries propose several additional measures regarding consumers’ education and communication, similar to the previous studies [ 13 ], but with some differences in the particular sub-themes of the results. For example, on the one hand, while our results consider the involvement of all actors in communicating about sustainable food, Sambell et al. [ 13 ] focus specifically on farmers, researchers, and local communities. On the other hand, a similar solution is to improve the producers’ knowledge about food products. Furthermore, the informants in all four countries recommend that both private individuals and governmental officials provide clear and consistent messages on sustainable food, as also suggested by Blay-Palmer, Sonnino, and Custot [ 26 ]. In addition, they advise developing labelling standards for sustainable food, similar to the study by Vanham and Leip [ 53 ], as these are inadequate [ 13 ]. Furthermore, they propose introducing the sustainability debate into the school curriculum, similar to Allen et al.’s study [ 40 ]. German stakeholders suggest providing clear information about sustainable food to producers [ 13 ], while Norwegian stakeholders argue that local food producers should develop better marketing skills to make sustainable food more attractive. Moreover, as previously discussed [ 71 ], Italian, Norwegian, and Romanian stakeholders believe that sustainable food marketing should focus on this food’s environmental and health benefits, high quality, and altruistic attributes (e.g., animal welfare). They also recommend involving influencers and positive role models and using ‘innovative’ communication tools such as apps and ‘smart labels’. Additionally, German stakeholders suggest using nudging techniques.

Second, despite the existing policy measures, both stakeholders and recent studies [ 6 , 14 ] argue that improving stakeholders’ collaboration is still a desirable objective. The stakeholders argue for the importance of further collaborations between different SFS actors. This will allow the authorities to use one voice to communicate food sustainability, which is an important success condition according to both the interviewed stakeholders and previous research [ 72 ]. As demonstrated earlier [ 73 ], the most effective and trustworthy way of providing information on sustainable food is through the involvement of several actors, e.g., when producers’ unions communicate environmental benefits, health experts communicate health benefits, and public authorities communicate social benefits.

Our findings add several concrete examples of how to involve different actors in developing SFS policies, similar to Moschitz’s study [ 7 ]. For example, Romanian stakeholders suggest developing collaborative networks of agrifood stakeholders, whereas Italian stakeholders suggest organising discussion tables. In Norway, they propose inviting different actors to debates focusing on SFS initiatives and measures, similar to Gruchmann et al.’s study [ 74 ]. However, public authorities should take the lead role in this process. They should also change and consolidate the current regulations and standards for SFS development [ 6 ].

Third, the stakeholders emphasise the role of technology, research, and innovation in stimulating the development of SFSs, as also found in the previous literature [ 6 , 13 , 38 ]. Sustainable policies should cover all aspects of sustainability (e.g., the proximity factor is usually ignored).

Fourth, another valuable recommendation from stakeholders in all four countries is to increase the availability and affordability of sustainable food, as also addressed in previous studies [ 40 , 73 ]. Procurement, distribution and retailers play an important role when speaking about availability, as acknowledged by Italian stakeholders and earlier studies [ 13 , 30 , 74 ]. Thus, there is a need to introduce several measures, such as developing sustainable public procurement based on local sustainable food, establishing sustainable shops and start-ups for SFSs, visible placement for sustainable food, and better recycling infrastructure and food disposal. Additionally, the affordability of sustainable food could be improved by reducing taxes on local food and, as suggested by Bartolini et al. [ 41 ], closing the gap between the prices of unsustainable food and sustainable food (e.g., through a ‘true cost’ policy). The country-specific recommendations focus on supporting local farmers and increasing marketing efforts for local food in Norway and considering higher taxation of unsustainable food in Germany, Norway, and Romania, similar to Bravo et al.’s study [ 71 ]. It can also be relevant to financially incentivise Romanian consumers of sustainable food, as high food quality could potentially increase food prices [ 71 ].

Fifth, SFSs should also focus on healthy diets. However, there is an ongoing debate in the literature [ 17 ] regarding whether a healthy diet is necessarily sustainable. Despite some obvious synergies (e.g., favourable health effect of reducing animal protein in human diets), a healthy diet mainly concerns nutrient intakes, which can be gained from any kind of food, including those foods with high greenhouse gas emissions [ 75 , 76 ]. German and Norwegian stakeholders suggest adopting a truly sustainable plant-based diet due to its health and environmental impacts [ 14 ], while Italian stakeholders emphasise the healthiness of a Mediterranean diet based on local food.

Furthermore, the stakeholders recommend reducing the power of conventional agricultural lobbyists in policy development. Additionally, there is a need to reduce food waste in Norway, similar to [ 50 ]. It is also important in Italy and Romania to implement a national strategy on SFS development with clear objectives, together with a national plan for mandatory implementation and clear indicators [ 6 , 9 , 13 ].

Based on our analysis of the stakeholders’ recommendations in all four countries, we argue that the first step in the further development of SFS policies should focus on interdisciplinary and trans-sectorial policy integration and increasing stakeholder collaboration across all sectors of the economy. Policy makers should take the lead in bringing together representatives from each stakeholder group involved in SFSs. They need to ensure higher consumer involvement by providing better information about sustainable food. Providing a coherent message is imperative to increase knowledge about sustainability and SFSs among all stakeholders, including consumers.

To achieve this, the European countries can develop a common platform at the international level, which can be further adjusted to the national context. The platform can gather information about all sustainable policies and practices, such as new labelling systems and support opportunities for SFS stakeholders. It can also be used to analyse and compare various sustainable inputs and processes, which would provide better transparency for consumers and international cooperation. Thus, the platform can facilitate further partnerships between countries and national and international stakeholders at various levels to ensure a more efficient development of SFSs.

Furthermore, we suggest stimulating technological development, research, and innovation for sustainable practices [ 34 , 35 , 36 , 37 , 38 ], e.g., by providing governmental support to research dedicated to new green technologies and the food companies adopting these technologies. We also recommend increased use of sustainable public procurement, which can help to change the default food option to a more sustainable one. These actions could also help to solve the problems related to the availability and affordability of sustainable food, as the new technologies can reduce the costs of sustainable food production and therefore make it more attractive to various SFS actors.

We also identify several country-specific policy recommendations to address the most pressing issues in each country. It is important to address the affordability of sustainable food in Romania and to develop common standards to define sustainable food in Italy, while in Norway and Germany, the focus should be on educating and informing different SFS stakeholders about sustainable food.

Finally, some of the country-specific best practices can be used to develop shared policies and tools. It is important for different countries to learn from each other, as some policies can be transferrable across countries. For instance, while Romania is at the initial stage of sustainable management of fertilisers and pesticides, Italian legislations are already offering future policy trends in this area by promoting biodistricts. This finding reveals the opportunity to skip some stages in the sustainable management of fertilisers and pesticides in Romania by implementing an adapted Italian practice, thereby achieving policy collaboration as indicated by [ 6 , 9 ]. The same opportunity has also been found in the case of public procurement. Italy is regulating green public procurement, and this could be adapted and implemented by other countries according to their particularities (e.g., Norway and Romania). In contrast, Norway has well-developed regulations on animal welfare and food safety that can be adopted by other countries (e.g., Romania). Furthermore, Germany’s well-developed labelling system of organic food and its national network for donating close-to-expired food are valuable practices that could be adopted in other countries.

6. Conclusions

Based on the analysis of the national policy documents and the interviews with the stakeholders in four European countries, the current study identifies several important gaps in the existing national policies for SFS development and suggests solutions that can help to overcome these issues. For example, to achieve policy integration and stakeholder collaboration across all sectors of the economy, we suggest introducing an international common platform, which could be adjusted to the national context.

To our knowledge, this is the first study to compare national policies and stakeholders’ opinions on SFS development in a multi-country analysis. The previous literature [ 14 , 19 ] indicates the need to build a holistic SFS and calls for further investigation regarding the contributions of the different stakeholders involved in SFSs. Therefore, we contribute to the theoretical development of SFSs by analysing cross-country stakeholders’ perspectives and comparing them with existing food policies, as well as by addressing local stakeholders and more groups of actors compared with the previous studies [ 6 , 10 , 12 , 13 , 14 ].

However, the current study has several limitations. First, we analyse the national policies of only four European countries. We invite future studies to conduct a similar analysis in other European countries to extend the generalisability of the results. Second, in each country, we focus on ten major public policy documents. Despite our careful procedure for the document selection, further research could extend the document sample. Moreover, it would be interesting to discuss SFS development with a broader group of stakeholders. Finally, considering the need for policy integration emphasised in this paper, collaborations among public actors and other stakeholders should be further explored.

Acknowledgments

This paper was written based on the results of the SUSCHOICE project, and thus, we kindly acknowledge the contribution of Gabriel Popescu, Nicolae Istudor, Dan Boboc, Florentina Constantin, Signe Nelgen, Elena Claire Ricci, and Francesca Pedrazza Gorlero for participating in the projects’ activities.

Supertext template for critical frame analysis.

Source: Adapted from Verloo and Lombardo (2007) and Dombos et al. (2012).

Relevant sustainability dimensions, drivers, barriers, and solutions related to SFSs in the national legislative/policy documents according to the critical frame analysis.

Relevant sustainability dimensions, drivers, barriers, and solutions related to SFSs highlighted by interviewed stakeholders according to qualitative content analysis.

Author Contributions

Conceptualization, N.M. and R.C.; methodology, A.Z. and M.-C.D.; formal analysis, A.Z., M.-C.D., N.M., G.S. and R.C.; investigation, A.Z., M.-C.D., N.M., G.S. and R.C.; writing—original draft preparation, A.Z.; writing—review and editing, N.M., G.S. and R.C.; funding acquisition, R.C. All authors have read and agreed to the published version of the manuscript.

This research is part of the project ‘Towards Sustainable Food and Drink Choices among European Young Adults: Drivers, Barriers and Strategical Implications’ (SUSCHOICE) (ID 66). SUSCHOICE is a transnational project and part of the ERA-Net SUSFOOD2 with funding provided by national sources (MUR-Italy, RCN-Norway, FORMAS-Sweden, PM-BLE-Germany, and UEFISCDI-Romania) and co-funding by the European Union’s Horizon 2020 research and innovation program. This work was supported by a grant from the Romanian National Authority for Scientific Research and Innovation, CCDI-UEFISCDI, project number COFUND-ERANET-SUSFOOD2-SUSCHOICE, within PNCDI III, and a grant from the Italian Ministry of University Research (MUR).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Conflicts of interest.

The authors declare no conflict of interest.

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