Wednesday, July 22, 2020

A social–ecological analysis of the global agrifood system

Elisa Oteros-Rozas, Adriana Ruiz-Almeida,Mateo Aguado, José A. González, and Marta G. Rivera-Ferre

PNAS December 26, 2019 116 (52) 26465-26473; first published December 16, 2019 https://doi.org/10.1073/pnas.1912710116


Edited by B. L. Turner II, Arizona State University, Tempe, AZ, and approved November 7, 2019 (received for review July 23, 2019)


Significance

The failure to end hunger and the environmental deterioration underpinning food systems have prompted a paradigm shift around food security. We propose a social–ecological approach and carry out a quantitative analysis of 43 indicators of food sovereignty and 28 indicators of the sociodemographic, social wellbeing, and environmental sustainability situation in 150 countries. The results highlight the existence of an agrifood debt among countries (i.e., disequilibria in the natural resources consumed, the environmental impacts, and the social wellbeing in regions that play different roles within the globalized agrifood system). Three spotlights underpin this debt: 1) interregional contrasts in food security, 2) a concern about the role of agrifood trade, and 3) a mismatch between regional biocapacity and food security.

Abstract

Eradicating world hunger—the aim of Sustainable Development Goal 2 (SDG2)—requires a social–ecological approach to agrifood systems. However, previous work has mostly focused on one or the other. Here, we apply such a holistic approach to depicting the global food panorama through a quantitative multivariate assessment of 43 indicators of food sovereignty and 28 indicators of sociodemographics, social being, and environmental sustainability in 150 countries. The results identify 5 world regions and indicate the existence of an agrifood debt (i.e., disequilibria between regions in the natural resources consumed, the environmental impacts produced, and the social wellbeing attained by populations that play different roles within the globalized agrifood system). Three spotlights underpin this debt: 1) a severe contrast in diets and food security between regions, 2) a concern about the role that international agrifood trade is playing in regional food security, and 3) a mismatch between regional biocapacity and food security. Our results contribute to broadening the debate beyond food security from a social–ecological perspective, incorporating environmental and social dimensions.
agrifood system
food sovereignty
hunger
social wellbeing
sustainability development goals

Agrifood systems, given their place among the most vulnerable coupled nature–human systems (1, 2), have multiple interactions with global environmental change and play a major role in the present and future of humanity (3, 4). They contemporarily sustain and challenge social wellbeing and human life on the planet (4) by providing food while contributing to global greenhouse gas emissions, land degradation, eutrophication, and water quality depletion (57). Five of the 7 planetary boundaries are directly linked to agrifood systems (8, 9). However, in a context in which enough calories are produced to feed the entire human population (10), chronic hunger still affects 1 in 9 people in the world (11). The evident failure of policies to end hunger and the environmental deterioration underpinning agrifood systems have prompted a paradigm shift in the way that food security is approached both scientifically and in policy terms: from being mostly focused on the technical and agrarian aspects of food production (1, 5, 12, 13) to adopting a social–ecological systems approach (14) and more precisely, an agrifood system approach, including both environmental sustainability and social wellbeing (4, 6, 1418). This systemic perspective allows emphasis on the use of natural resources for primary production as well as food transformation, commercialization, and consumption, therefore connecting pieces within agrifood systems that previous analyses had studied separately.

Likewise, the multiple social and ecological dimensions of food security are transversal to 14 of the 17 United Nations’ 2030 Sustainable Development Goals (SDGs) (19). The SDGs aim to eradicate poverty, establish socioeconomic inclusion, and protect the environment (20), and therefore, the need for an integrative approach to address them has already been discussed (21). However, critical studies have elicited an incompatibility between the environmental and the social and economic aspirations of the SDGs (22).

While food security is commonly defined as the physical, social, and economic ability to access sufficient, safe, and nutritious food (23), SDG2 implicitly recognizes that a broader approach to food security is needed to end hunger. Indeed, for the first time, SDG2 links the objectives of zero hunger, food security, and improved nutrition (subgoal 1) with the need to promote sustainable agriculture (subgoal 2) (19). SDG2 explicitly refers to the global moral imperative to eradicate hunger while respecting environmental sustainability. However, this entails controversy about the tradeoffs between achieving food security mainly through increasing food production (24, 25), addressing and minimizing the environmental impacts of agriculture and food (6), and adapting to climate change (26). Therefore, actions toward the transformation of agrifood systems need to account for the synergies and tradeoffs that exist between SDG2 and other SDGs (27), which need to be identified through social–ecological systems approaches.

The international debate around the social–ecological sustainability of food systems is prolific, and different authors have recently suggested a change from the land sparing/sharing debate to a focus on human wellbeing (4); proposed “leverage points” for improving global food security and environmental sustainability (6); argued for sustainable healthy diets to keep food systems within the planetary boundaries (28); developed assessments of the environmental impacts of food systems (29, 30); applied metrics for the assessment of the sustainable nutrition outcomes of food systems (31); and provided valuable systemic analyses of global food systems (18). However, although it is widely acknowledged that the social and environmental costs and benefits associated with environmental change are not distributed equally among actors and regions (32), how this phenomenon occurs is still poorly understood, because less than 6% of food security publications in the past 25 y included equity or justice as part of their analysis (14).

A tipping point in these international debates was the 2012 32nd Regional Conference for Latin America and the Caribbean (33), where the United Nations Organization for Food and Agriculture (FAO) agreed to initiate discussions about alternative approaches to address hunger and the unsustainability of agrifood systems. One such approach was food sovereignty (FSv) (33). FSv emerged in the late 1990s, arguing that hunger is not merely a matter of food availability and quality but that equally or more critical issues are political aspects harnessing equity and justice within food systems. Some of those political aspects may include agricultural trade liberalization, power relations between different actors (from small producers to large transnational corporations and consumers, therefore within and between countries), a lack of wide social participation along the whole food chain, or access to the means of production (34, 35). FSv, as a political concept, was coined by La Via Campesina, an international movement of farmers, peasants, and landless workers, and has been developed and discussed at large by civil society organizations, farmers’ trade unions, academia, governments, and international institutions (36) to become a well-rooted concept (37). Within this approach, food is framed as a human right, including its environmental and sociocultural aspects, which are viewed as both drivers and outcomes of food security and where small farmers are considered to play a central role (34).

However, progress toward ending hunger needs to be measurable through indicators that aid societies in assessing their performance (20). Gustafson et al. (31) and Ruiz-Almeida and Rivera-Ferre (38) expressed the need to address food security from a systems perspective that incorporates social–ecological sustainability, and to do so, they provided comprehensive sets of indicators at the national scale. Ruiz-Almeida and Rivera-Ferre (38) proposed a panel of 97 indicators, but they did not perform any analyses on data. Gustafson et al. (31) suggested 23 indicators but applied them only to 9 countries. Chaudhary et al. (18), based on Gustafson et al. (31) and adding 2 additional indicators on biodiversity impacts and health-sensitive nutrient intake, applied descriptive analyses to quantify 156 nations performance.

However, achieving SDG2 requires not only measuring performance but also, understanding the social–ecological relations among different countries beyond national patterns. Therefore, based on data for the set of indicators proposed by Ruiz-Almeida and Rivera-Ferre (38), we analyze here the global agrifood system from a social–ecological perspective.

While previous works advanced in the same direction, we believe that our contribution constitutes a step farther in 2 ways. First, with the multivariate analysis of 43 indicators of FSv, 150 countries are grouped according to their relative scores. Hence, a picture of the dynamics of the global agrifood system at a larger scale is provided. Second, we enlarge the social–ecological approach by incorporating the description of world regions according to 7 demographic and economic indicators, 4 social wellbeing indicators, and 17 environmental sustainability indicators.

In particular, we carried out a principal component analysis (PCA) of indicators (variables) describing the agrifood system (SI Appendix, Tables S3–S7) in countries (observations). Some indicators were originally published as indexes or proportions, while others needed to be transformed in relative terms with respect to country area or population size in order to adjust magnitudes and allow comparison between countries (details of the definitions, sources, and data transformations are given in SI Appendix, Tables S1 and S2). Using the standardized coordinates of the most significant PCA factors, we performed a hierarchical cluster analysis (HCA) based on the Euclidean distance and Ward’s agglomerative method. Finally, we used Kruskal–Wallis and χ2 tests to characterize each cluster of countries according to its performance in terms of FSv, social wellbeing, and environmental sustainability (a more detailed description of statistical methods and results can be found in SI Appendix). This approach aims to contribute to other ongoing efforts to provide indicators for monitoring SDG progress (http://indicators.report).

Through the proposed analyses, we 1) identify world regions formed by countries under similar conditions of FSv, 2) relate the state of FSv of the different regions with their state of social wellbeing and environmental sustainability, and 3) critically reflect on the implications for SDG2 of an agrifood debt between world regions that has been so far poorly addressed. Within-countries agrifood debt and inequalities can be also relevant to provide a complete picture, but their analysis is out of the scope of this paper.

Results

The State of Food Sovereignty: Who Is Who in the Global Agrifood System.

The 150 countries analyzed were statistically clustered into 5 groups (Fig. 1 and SI Appendix, Table S8) according to their performance in the 43 indicators across the 6 pillars of FSv (Figs. 1 and 2). By also characterizing them according to their bioregional context (SI Appendix, Table S9), socioeconomic characteristics (SI Appendix, Table S10), FSv (SI Appendix, Table S11), environmental sustainability, and social wellbeing (SI Appendix, Table S12), we grasp who is in the global food system and what relation with the ecological and sociopolitical dimensions of food the different groups of countries have.

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Fig. 1.

World map with the countries colored according to the groups that emerged from the PCA and the HCA: purple is group 1, blue is group 2, green is group 3, yellow is group 4, red is group 5, and gray indicates the countries excluded from the analysis due to a lack of data.


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Fig. 2.

Box plots of FSv indicators in the 5 clusters identified. Only indicators with statistically significant differences between the groups are represented. The 6 pillars of FSv are separated into (A) access to resources, (B) productive models, (C) commercialization, (D) food security and food consumption, (E) agrarian policies and civil society organizations, and (F) gender. The letters at the top of each box plot (A–D and combinations) correspond to the statistically significant differences in the pair comparisons (more details are in SI Appendix).


Landgrabbed and Undernourished: Agricultural Exporters but Food Importers.

The first group includes 45 countries (SI Appendix, Fig. S4 and Table S8) mostly from eastern, middle, and western Africa (Fig. 1 and SI Appendix, Table S9). The countries in this group show the lowest gross domestic product (GDP) per capita and very low income (SI Appendix, Table S10). The food systems in the countries of this group are characterized by a productive model based on the largest rural and agricultural population of the sample, the smallest cultivated area per farmer, the largest total economically active population in agriculture, a limited use of fertilizers, and a low production of meat (Fig. 2 and SI Appendix, Table S11). Agriculture is responsible for a high share of the GDP of these countries, which are, on the one hand, the largest exporters of agricultural products (significantly different from all other groups) and on the other hand, the largest importers of food (although only significantly different from groups 4 and 5), showing net reception of official development assistance for food and agriculture (SI Appendix, Table S11). This group of countries ranks first in suffered landgrabbing (SI Appendix, Table S10). The population in the countries of this group shows the lowest levels of access to resources, such as electricity, sanitation, and drinking water; the most severe food deficits; and significant vulnerability, which is consistent with the lowest protein supply and adequacy of the dietary energy supply among the groups (Fig. 2 and SI Appendix, Table S11). That is, the value added of the agricultural products produced is not retained, exporting huge amounts of agricultural products while failing to feed large shares of their population. These countries also show the lowest degree of economic, social, and political globalization, despite some of them being among the biggest exporters of luxury commodities, like coffee and cocoa. The indicators of social wellbeing are coherent with the former, as this group of countries has the worst scores for all of the indicators analyzed, including significantly shortest life expectancy and worse life satisfaction (Fig. 3 and SI Appendix, Table S12). In terms of environmental sustainability, these countries are associated with the lowest ecological footprint and low CO2 emissions and water withdrawal from agriculture (Fig. 3 and SI Appendix, Table S12).

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Fig. 3.

Box plots of environmental sustainability (A) and social wellbeing (B) indicators in the 5 clusters identified. The letters at the top of each box plot (A–D and combinations) correspond to the statistically significant differences in the pair comparisons (more details are in SI Appendix).


Diverse Intensive Producers of Crops.

The second class is the largest and most heterogeneous group, clustering together 49 countries, mostly from Asia and the Americas (Fig. 1 and SI Appendix, Tables S8 and S9). In comparison with the other groups, these countries have the largest population densities and low–medium income (SI Appendix, Table S10). These countries show medium levels of rural and agricultural populations, however, with the smallest agricultural area and production of mammals (Fig. 2 and SI Appendix, Table S11). What they have in common is that they are characterized by intensive production models based on a large use of fertilizers and agricultural water withdrawal (also used for wheat, maize, and/or rice production, for which some of the countries in this group, such as China and India, are among the largest producers in the world) and the vastest surfaces of permanent crops (as percentage of agricultural area) that are dedicated partly to fruit production (mostly in Southeast Asia and Central and South America). They are large food exporters (Figs. 2 and 3 and SI Appendix, Table S11), and also, they are characterized by the second highest food deficit, low energy and protein intake (Fig. 2 and SI Appendix, Table S11), and overall intermediate levels of social wellbeing (Fig. 3 and SI Appendix, Table S12).

Least Ecologically Wealthy and Landgrabbers.

The 18 countries clustered in this class are not geographically or ecoregionally grouped (Fig. 1 and SI Appendix, Tables S8 and S9). They show medium population densities and GDP per capita (SI Appendix, Table S10). Countries in this group show a limited proportion of agricultural area and forests as well as overall very little cereal, meat, and fruit production but the greatest use of fertilizers per hectare (Fig. 2 and SI Appendix, Table S11). Little of the population lives in rural areas or is dedicated to agriculture, and overall, the population in these countries seems to have good access to all resources except renewable water (the group includes several island states) (Fig. 2 and SI Appendix, Table S11). These countries have limited exports of agricultural products, and they are net food importers, with limited value added to agriculture (Fig. 2 and SI Appendix, Table S11). Most of these countries coincide with those in which the importance of food imports has increased in recent years. They show an intermediate level of food security and consumption in comparison with the other groups, despite limited subsidies invested in supporting agriculture (SI Appendix, Table S11). Overall, they seem to have a good situation in terms of social wellbeing (Fig. 3 and SI Appendix, Table S12). Two significant characteristics of this group are the largest biocapacity deficit in comparison with the other 4 groups (Fig. 3 and SI Appendix, Table S12) and the largest area of land grabbed abroad as a percentage of its total area (SI Appendix, Table S10).

Intensive Food Producers and Exporters.

The fourth group clusters 8 vast countries from Oceania and the Americas with the largest intragroup variance (Fig. 1 and SI Appendix, Tables S8 and S9). This group exhibits high income and the largest GDP per capita alongside the smallest population densities (SI Appendix, Table S10). Access to resources is high in these countries, and the agrifood system is focused largely on a model of intensive production of cereals, fruit, meat, and biofuels dependent on large inputs of pesticides and with very low rural and agricultural populations (Fig. 2 and SI Appendix, Table S11). However, organic agriculture (as a percentage of total agricultural area) scores high in this group due to Uruguay and the United States. Countries in this group seem to be the “breadbasket of the world”: they show a large share of food and agricultural exports while indicating limited food imports (Fig. 2 and SI Appendix, Table S11). In fact, some of them, such as Australia, Argentina, Canada, the United States, and most recently, Brazil dominate global food exports. This group also shows the largest financial support for agriculture (Fig. 2 and SI Appendix, Table S11). Food deficit is quite low, and the protein supply is high, consistent with the high level of energy adequacy (Fig. 2 and SI Appendix, Table S11). Another common feature of countries in this group is their large ecological footprints and agricultural CO2 emissions as well as a large biocapacity that sustains their large biocapacity reserves (Fig. 3 and SI Appendix, Table S12). Furthermore, they have the best records for all social wellbeing indexes (Fig. 3 and SI Appendix, Table S12).

Overnourished Agricultural Importers.

The fifth group is the most homogeneous group and includes 30 countries (SI Appendix, Fig. S4 and Table S8), mostly in Europe (Fig. 1 and SI Appendix, Table S9), and it features the largest population densities, the second largest GDP per capita, and high income (SI Appendix, Table S10). Access to resources is satisfactory in these countries (Fig. 2 and SI Appendix, Table S11). Agriculture is quite intensive, with little rural and agricultural populations, little presence of women who are economically active in agriculture, and a large use of fertilizers (Fig. 2 and SI Appendix, Table S11). These are the largest importers of agricultural products, however, with little imports and exports of food (Fig. 2 and SI Appendix, Table S11). People in these countries are overall food secure but have a diet mostly based on a large consumption of proteins (Fig. 2 and SI Appendix, Table S11). These countries are in a biocapacity deficit because of the ecological footprint of the built-up land and the croplands, instead showing the lowest grazing footprint and agricultural water withdrawal but large CO2 agricultural emissions (Fig. 3 and SI Appendix, Table S12). These are the countries with the largest degree of globalization and net contribution of official development assistance for food and agriculture as well as overall high levels of social wellbeing (Figs. 2 and 3 and SI Appendix, Tables S11 and S12).

Discussion

The FSv indicator framework (38) used here to analyze agrifood systems from a social–ecological systems perspective (14) contributes to systematically and quantitatively assessing environmental, social, and economic relationships between countries within a globalized world. It allows us to measure progress through periodical monitoring: ideally, countries should not be so easily clustered, and if they are, the groups should not show significant differences in terms of their sociodemographic characteristics, environmental sustainability, and social wellbeing. The current cluster might help countries to 1) be conscious of the impacts of their national agrifood policies in other countries and on their social–ecological sustainability; 2) evaluate the dependence of their food security, social wellbeing, and environmental sustainability on other countries; and therefore, 3) allow governments to make sensible changes to agrifood policies to contribute to SDG2. In addition, these results might also provide guidance to development banks and other financial institutions.

Winners and Losers: Agrifood Debt.

The International Council for Science critically pointed toward the internal inconsistency between ecological sustainability and socioeconomic progression in the SDG framework (39), and there is scientific quantitative evidence about the nature and extent of this incompatibility of sustainability and development (3941). Our results provide evidence of the challenges to end hunger in a globalized agrifood system, which is far from equitable from both socioeconomic and environmental perspectives. Certain countries, such as Australia, Brazil, Argentina, and those in Europe and North America, hold a critical stake and should reduce overconsumption, while other countries, such as most of Africa, would benefit from improving their self-sufficiency. Consistent with previous research, our results suggest that intertwined and nested material flows in global agrifood systems result in interregional social inequities in the distribution of both costs and benefits of producing, trading, and consuming food, hence affecting social wellbeing, unevenly distributing environmental impacts, and challenging environmental sustainability.

In line with the concept of “ecological debt,” which was coined by academics in 1992 and further adopted and developed by civil society organizations and governments (42), the results presented here illustrate an agrifood debt (i.e., the interregional social–ecological disequilibria in the natural resources consumed, the environmental impacts produced, and the social wellbeing attained by populations in regions that play different roles within the globalized agrifood system). Given that a substantial proportion of the world's 815 million people who are unable to meet daily food needs are food producers, such as small-scale farmers and fishers (11), our results are consistent with and strengthen the conclusions of extensive previous research showing that food security is largely a matter of redistribution, entitlements, food access, and access to services and means of production (22, 43). Globalization poses complex tradeoffs for food system resilience across scales due to high social, economic, and ecological interconnectedness, tradeoffs, and, hence, vulnerability (14). We suggest that this agrifood debt, which has been poorly addressed to date, should be recognized, assessed, and monitored through 3 spotlights: 1) a severe contrast in diets and food security between regions, 2) a concern about the role that international agrifood trade is playing in regional food security, and 3) a mismatch between regional biocapacity and food security.

Nutritional and Environmental Contrasts in Diets and Food Security between Regions.

An unbalanced food system features a contrast between high rates of undernutrition (group 1) vs. overnutrition (in groups 4 and 5), leading to increasing overweight and obesity (11), which highlights the need to promote dietary changes in many countries of the Global North (18, 28, 29, 44). Divergences in diets are reflected by the differences in carbon footprints between the groups: mean dietary carbon footprints vary from ca. 0.7 kg CO2 eq. per capita per day for certain African countries (all in group 1) to 4 kg CO2 eq. per capita per day for New Zealand, Australia, the United States, France, Austria, Argentina, and Brazil (all in groups 4 and 5) (18). If current crop production used for animal feed and other nonfood uses, such as biofuels (particularly in the United States, China, Western Europe, and Brazil), were used for direct human consumption, ca. 70% more calories would be available, potentially satisfying the basic needs of 4 billion people (26). Our results confirm that most countries with high nutritional quality show high ecological footprints, and therefore, changes in the diets in North America (group 4) and Europe (group 5) would entail the largest reductions in environmental impacts of the global agrifood system (18, 45, 46). The nutrition transition, however, is also affecting the Global South (47, 48). Hence, concerns about nutrient density and public health must be incorporated into considerations around the environmental impacts of food and consequently, integrated into agricultural policies (14, 18, 49). The point at which the higher carbon footprint of some nutrient-dense foods is offset by their higher nutritional value is a priority area for additional research.

Therefore, “doubling the agricultural productivity of small-scale food producers,” as stated by SDG2, is per se not the way to eradicate hunger in a context where the world is already producing food to feed 12 billion people (50, 51). On the contrary, only increasing agricultural productivity has led to reduced prices (ultimately harming farmers) and created health problems and the associated costs (52). It might be even ecologically counterproductive unless other agrifood policies are adopted, such as the reduction of the demand side and particularly, animal-sourced food in the diets of countries in groups 4 and 5 and of some countries in group 3, the diminution of impacts of the supply chain, and the incentive of low-impact and crop-diversifying farming systems (14, 18, 29, 45, 46).

International Agrifood Trade, Food Security, and Environmental Sustainability.

International trade plays an important role in food security (50), and the promotion and maintenance of certain lifestyles and diets rich in calories have been possible thanks to the global food trade (53); SDG2 states that “access to financial services, markets and opportunities to value addition” is needed. However, unless regulated and complemented with other policy instruments, the global agrifood trade entails tradeoffs in terms of social equity and environmental sustainability (54, 55). In fact, securing the food supply through imports occurs only in strong-enough economies (46, 53). In a globalized and financialized system, food tends to flow toward money and power, not toward hunger, and therefore, international agrifood trade can contribute to increase social inequality in the form of food insecurity by facilitating food being exported/traded away from the hungry (51). The results presented here show how certain groups of countries lose (groups 1 and 2) with respect to others (4, 5). In particular, the first group of countries (mostly in Africa) is a clear example of this: despite their large exports of agricultural products and the largest imports of food, undernutrition remains a critical constraint.

More than one-fifth of global calorie production is exported, mostly from countries in group 4 (the United States, Canada, Brazil, and Argentina) (56). Industrialized countries with high GDP per capita tend to be major net importers of biodiversity, while tropical countries, such as Argentina and Brazil, suffer habitat degradation and biodiversity loss as a result of producing crops for exports (57). Land use for export production is responsible for 25% of the projected global extinctions and related biodiversity loss (57, 58), ∼20% of global harvested cropland area is devoted to export production (56), and most of the new cropland expansion is globally attributed to the production of crops for export (59). International food trade has been related to a virtual transfer of water (60), carbon (61), nitrogen (62), and phosphorus (63), while the environmental impacts of agricultural production tend to remain in the producing countries (64).

Mismatch between Regional Biocapacity and Food Security.

There has been a strong decoupling between regional biocapacity and food consumption. The global telecoupling (65) and increasing interdependence among countries in regard to availability and access to food sources and the genetic resources supporting their production (66) result in the increasing reliance of some regions on social and natural resources from other regions of the world, which also increases agrifood debt. A clear example of this phenomenon is land grabbing, which is largely exerted by companies mostly from countries in groups 3 (the Middle East), 2 (e.g., China), and 5 (e.g., Europe) on countries from group 1 (e.g., Africa) (67, 68). For example, restrictions on agricultural production and changes in bioenergy demand have nurtured the dependence of the European Union (group 5) on the appropriation of biological productivity outside its boundaries, with increasing reliance on Latin America as the main supplier (59). Additional evidence in that direction is related to food loss and waste: industrialized Asia (China, India, and North Korea), Europe, North America, and Oceania have the highest per capita carbon footprint of food loss and waste, while sub-Saharan Africa has the lowest (69).

Limitations.

The intricacy and complexity of the currently globalized food system are impossible to fully disentangle with a purely statistical exercise, like the one presented here. For instance, certain dimensions of FSv, such as power relations between different actors within the agrifood system, cannot be easily assessed at a national scale. Nonetheless, new data sources that might contribute to the monitoring of FSv are continuously appearing, such as the Land Matrix project (https://landmatrix.org) for large-scale land acquisitions. A participatory, qualitative assessment with stakeholder collaboration could improve both the selection of indicators and the interpretation of results, for example, to be tailored at the national or regional levels, therefore also improving the usability of the knowledge generated (70). Clustering 150 countries into 5 groups entails that intragroup variance remains large, therefore providing a relevant picture at a global scale but not illustrating regional differences. Moreover, using the country scale as a unit of analysis implies that environmental, social, and nutritional inequities cannot be accounted for. For example, data on ethnic minorities, regional groups, indigenous populations, slum dwellers, and women aged 50 and over are rarely collected (20). A further constraint is the limited quality and/or availability of data: while data on economic indicators are widely available for most countries, data on environmental and social indicators of contested phenomena (e.g., land grabbing) are incomplete and of poor quality (20). However, given the international legitimacy of the data sources (e.g., Food and Agriculture Organization’s Statistical Database [FAOSTAT], World Development Indicators [WDI]) and their broad use in previous scientific research, we are confident that data quality/availability issues do not undermine the main conclusions of this research.

Conclusions

In the last 4 decades, there has been an intense debate about the best policies needed to achieve what is currently stated in SDG2. Between the mid-1960s and the early 2000s, food availability improved globally, and global per capita exports of agricultural products almost doubled, but food self-sufficiency did not change significantly (53). The global population increased 2.5 times between 1961 and 2016, while calorie production increased by more than 4 times by 2013 (71). While the need to increase food production has been repeated like a mantra in many instances (6, 72), old policies focused on productivity, favoring agricultural industrialization, trade liberalization, privatization, and deregulation, have failed to end hunger (73). As this study corroborates, undernutrition is not only a matter of food availability and access (14, 53). Instead, the eradication of hunger would be facilitated by a redistribution of current consumption levels (74, 75). Furthermore, the challenges and responsibility for achieving SDG2 as well as other SDGs, still within planetary boundaries, are not evenly distributed across the globe (6, 20). Providing quantitative agrifood system metrics at the global scale using FSv indicators together with other sociodemographic, social wellbeing, and environmental indicators allows the identification of tradeoffs in environmental and social justice within the global agrifood system and is currently largely ignored (76) but needed in order to comprehensively address SDGs. On a global scale, our results are consistent with previous extensive research and with what we would expect to see if wealthy countries are exporting environmental degradation to import cheap food that is largely wasted and overconsumed: groups 4 and 5 (European and North American countries) should play a prominent role in the transformation of the global agrifood system toward one that is more environmentally sustainable and socially equitable.

There is no fundamental tradeoff between eradicating hunger, achieving environmental sustainability (76), and social equity. However, for the achievement of SDG2 through transformational, socially fair, environmentally sustainable, and resilient food systems, our results point to the following key wedges: biodiversity conservation through environmentally friendly agrifood practices (77), the reduction of agrifood waste (14), the regionalization of food distribution (14), and the adoption of healthy and sustainable diets (26). We need to make these steps fast enough to advance SDG2 while preserving environmental sustainability and social wellbeing.

Materials and Methods

Data Collection.

Ruiz-Almeida and Rivera-Ferre (38) compiled data on 97 indicators for 223 regions (countries or officially recognized territories) between 1961 and 2012 and followed a 6-step methodology to select the most suitable indicators according to data availability, quality, and representativeness of the 6 categories of FSv (more detailed information is provided in SI Appendix, Fig. S1). Indicators were collected from open source databases compiled by international organizations with recognized legitimacy, such as public institutions, agencies, and programs related to the United Nations organization (FAO, United Nations Development Program [UNDP], and United Nations Environmental Programme [UNEP]), international financial institutions (World Bank), and other international organizations (e.g., Organization for Economic Co-operation and Development [OECD] and World Trade Organization [WTO]). Nine indicators were selected to describe the pillar of “access to resources,” 16 were selected for “productive models,” 8 were selected for “commercialization,” 5 were selected for “food security and consumption,” 3 were selected for “agrarian policies and civil society organization,” and 2 were selected for “gender.” For the objectives of this research, we selected indicators following 4 main steps (SI Appendix, Fig. S3): 1) we retrieved the historical data available from all indicators; 2) we selected the indicators for which the last data available referred to the timeframe between 2008 and 2012—for 223 countries or territories, there were 92 indicators that fulfilled these criteria; 3) we debugged the database to reduce the extrapolation of data as much as possible and to avoid outliers due to country or population size; and finally, 4) we incorporated extra data characterizing the bioregional location of the country, the social wellbeing, and the environmental sustainability of each country. The debugging process, which included 4 steps, reduced the initial database to 150 countries and 43 FSv indicators (SI Appendix, Fig. S3). In the final database, 200 missing values (3.1% of the full database) were estimated through the nonlinear iterative partial least squares algorithm. To relate the state of FSv of the groups of countries with their state of social wellbeing and environmental sustainability, further indicator selection was conducted. We scanned more than 200 indicators of social wellbeing and environmental sustainability and selected 17 indicators for environmental sustainability (SI Appendix, Table S3) and 4 indicators for social wellbeing (SI Appendix, Table S4) based on the following criteria: 1) capacity to express the required information, 2) availability of the information for a sufficient number of countries, 3) availability of the information for the selected timeframe (2008 to 2012), and 4) veracity of the data according to internationally legitimized sources. For the description of the demographic and economic contexts of each country, another 7 indicators were selected (SI Appendix, Table S6). For the bioregional characterization of the groups, we used a synthesis of the classification of the world ecoregions (i.e., the 26 categories included 14 terrestrial, 7 inland water, and 5 marine ecoregions) (70) (SI Appendix, Table S7).

Data Analysis.

Tests for the normality of the distribution of all 43 indicators of FSv were performed. Only 1 indicator proved to follow a normal distribution and was standardized (n − 1). The indicators that did not follow a normal distribution or show negative values were transformed through ln(x) or ln(x + 1) when the indicator (x) showed a value equal to 0. The indicators that did not follow a normal distribution and showed negative values were first rescaled (0 to 100) and then transformed through ln(x + 1).

For the identification of groups of countries, we carried out a PCA [covariance (n − 1)] based on the matrix of countries (observations) and indicators (variables). We followed the Kaiser criterion (eigenvalue >1) to determine the significant number of components. To identify possible groups of countries with similar values of FSv indicators, we carried out an HCA based on the Euclidean distance (percentage of distance similarity at a 95% level of confidence) and Ward’s agglomerative method (71) using the standardized coordinates of the most significant factors of the PCA. Finally, to characterize each group resulting from the HCA in terms of ecoregions, socioeconomic characteristics, FSv, social wellbeing, and environmental sustainability indicators, we performed Kruskal–Wallis and χ2 tests. All statistical analyses were run with XLSTAT69.

The characterization of the groups of countries clustered together in the HCA was represented in a world map (Fig. 1) and 2 sets of box plots (Figs. 2 and 3).

Data Availability.

The full database used, with all indicators, is available in Dataset S1.

Footnotes


1E.O.-R. and A.R.-A. contributed equally to this work.
2To whom correspondence may be addressed. Email: elisa.oterosrozas@gmail.com.


Author contributions: E.O.-R., J.A.G., and M.G.R.-F. designed research; E.O.-R., A.R.-A., M.A., J.A.G., and M.G.R.-F. performed research; E.O.-R. analyzed data; and E.O.-R., A.R.-A., M.A., J.A.G., and M.G.R.-F. wrote the paper.


The authors declare no competing interest.


This article is a PNAS Direct Submission.


This article contains supporting information online at https://www.pnas.org/lookup/suppl/doi:10.1073/pnas.1912710116/-/DCSupplemental.


Published under the PNAS license.

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Opinion: At a Crossroads: Reimagining science, engineering, and medicine—and its practitioners

WHITE, BLUE OR PINK THE COLOUR OF YOUR COLLAR NO LONGER MATTERS WE ARE ALL PROLETARIANS NOW

Freeman A. Hrabowski III, J. Kathleen Tracy, and Peter H. Henderson
PNAS first published July 15, 2020 https://doi.org/10.1073/pnas.201358811
The coronavirus disease 2019 (COVID-19) pandemic has cast a bright light on the importance of science and evidence (1). Epidemiologists have provided public health advice informed by experience with epidemics and are sharing best practices for halting the spread of the virus. Biomedical scientists are researching how the virus works, testing treatments, and racing to develop a safe and effective vaccine. This work reinforces previous calls from the National Academies and others for strong investments in science and mathematics education; science, engineering, and medicine research; and the translation of new knowledge into products and processes that improve public health, spur economic growth, and maintain national security (24).

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Recent events have shined a bright light on intractable inequalities in US society. The science enterprise is far from immune. Although there has been progress, the science community can do much more. Image credit: Shutterstock/Tverdokhlib.


Although its high level of contagion means that everyone is vulnerable to the virus, the pandemic has also shined a bright light on intractable inequalities in our society. Several months ago, we, along with others, advocated for release of COVID-19 case data by race, arguing that we could not understand the impact of the virus unless we could see how it affected communities differently. When data were finally made available, the disparities were clear. Elderly and low-income Americans, African Americans, Native Americans, and Hispanics are infected by and dying from the virus in disproportionate numbers. Ibram Kendi has shown that the African American community has been particularly hard hit because of structural racism, economic inequalities, and health disparities (5). To paraphrase others, these differences provided the kindling and police brutality the match for the widespread fire of racial protest that has called for broad policy changes to address structural racism in America.

The pandemic and racial protest have together done something else as well: They have provided an opportunity to reshape our institutional cultures to support the success of students and faculty of all backgrounds and, in turn, enhance science and public health and reduce disparities. In light of the current racial unrest, many are asking “What can I do?” Many of our African American colleagues, in particular, are providing practical advice.


COVID-19 provides a “Sputnik moment,” one that allows us to reimagine the role of science in our society and elevates the importance of inclusion within the scientific community.

By considering and acting on this advice—including what we offer in this article—we can better recruit a broader range of students in science, support their success, and help them succeed in professions that would benefit from greater diversity. When we do so we can enrich scientific, professional, and policy conversations with new information, life experiences, and perspectives that could lead to better health and social outcomes.

Meeting the Moment

In Science: The Endless Frontier, a report released 75 years ago, Vannever Bush re-envisioned the science and engineering enterprise to benefit our economy, health care, and national security (6). His vision provided the template for a federally funded basic research enterprise located in research universities and carried out by faculty in conjunction with their graduate students. Bush’s recommendations led to the establishment of the National Science Foundation in 1950.

Then, in 1957, the successful Soviet launch of Sputnik transfixed America and led us to increase federal investment in scientific education and research. In the decades since, these investments have yielded exponential dividends. We placed a man on the moon, protected the Earth’s ozone shield, created a revolution in computing and telecommunications, developed cancer treatments, decoded the human genome, and much, much more (7).

During the current COVID-19 lockdown, many have expressed a strong longing for a “return to normal.” As New York Governor Andrew Cuomo has argued in his daily briefings, however, the current crisis provides the opportunity for us not to merely reopen our society but also to reimagine it. Life will be different anyway. Our increased use of digital learning, telework, online grocery shopping, telehealth visits, and vote by mail are shifting our perceptions of what is possible and effective. These temporary measures will have permanent long-term consequences for teaching and learning and the nature of work, transportation, retail, healthcare, and democracy.

But we can go beyond these changes to envision and implement structural changes that would create a better society. COVID-19 provides a “Sputnik moment,” one that allows us to reimagine the role of science in our society and elevates the importance of inclusion within the scientific community.




This past January, Holden Thorp, Editor-in-Chief of Science, lamented that although we continually articulate important goals for science, we have not taken the steps to achieve them (8). He wrote that the mantra of the scientific community has been a “diverse scientific workforce; policymakers who recognize the importance of science; a voting public that understands the scientific process.” But, Thorp added, “these words don’t match actions” and inaction is “costing society a generation of researchers, educators, a population that better grasps science, and maybe more.” The lack of progress is not attributable to a lack of proven solutions. Reimagining our work means drawing on models that work to support better outcomes for our students.

Taking the Initiative

The scientific community has understood the problem of underrepresentation in science and engineering for some time; we’ve also observed what works to enhance and sustain diversity and inclusion. Expanding Underrepresented Minority Participation: America’s Science and Technology Talent at the Crossroads, a 2011 report from the National Academies, argued that we are likely as a society to miss out on important innovations unless we draw on the talents of students from underrepresented groups, especially because they are also the fastest growing groups in the U.S. population (9). When we bring more people with different life experiences to the table, we also enrich the conversation with new information, perspectives, and questions. To expand diversity, the Crossroads report called for faculty to redesign introductory college science and mathematics courses to improve teaching and learning and support persistence in science, technology, engineering, and mathematics (STEM) majors. It also argued that universities must, drawing on models that work, create programs that build community, encourage group study, and provide experiential learning for all students, and particularly those from underrepresented groups.

The Meyerhoff Scholars Program at the University of Maryland, Baltimore County (UMBC) began as an experiment in 1989 to support African American undergraduates who would go on to earn doctorates in the natural sciences and engineering. Lessons learned from that program have helped us support students of all races and backgrounds, by instilling high expectations in students, promoting the goal of doctoral study, using a cohort approach to build community, encouraging group study and peer tutoring, providing financial support, and bringing students into faculty research (10, 11).

The results are promising. Forty percent of our students go on to graduate or professional school. Our alumni are now playing important roles during this pandemic. For example, Jerome Adams is the U.S. Surgeon General. Letitia Dzirasa is the Baltimore City Health Commissioner. Kizzmekia Corbett is the scientific lead for COVID-19 vaccine development at the National Institute of Allergies and Infectious Disease (NIAID) in Bethesda, MD; she’s joined by alumnus Olubukola Abiona. Darian Cash is a senior researcher at Cambridge, MA-based Moderna, the firm partnering with NIAID in COVID-19 vaccine development. Kaitlyn Sadtler is leading the NIH study that will estimate the number of adults in the United States who have not had a confirmed infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)—the virus that causes COVID-19—yet have antibodies to the virus. Each of these young researchers can point to teachers, professors, and mentors who supported them at each stage of their journey.

Federal science agencies and national associations have taken steps to support diversity in undergraduate science and engineering since the publication of the Crossroads report. In the past decade, for example, the NIH established the Building Infrastructure Leading to Diversity (BUILD) program providing grants to ten “undergraduate institutions to implement and study innovative approaches to engaging and retaining students from diverse backgrounds in biomedical research.” And the National Science Foundation (NSF) established the Inclusion across the Nation of Communities of Learners of Underrepresented Discoverers in Engineering and Science (INCLUDES) program in 2018 to build on and scale up what works in broadening participation. With funding from INCLUDES, the Association of Public and Land-grant Universities (APLU) and the Center for the Integration of Research, Teaching, and Learning have established the ASPIRE Alliance to identify best practices for preparing, attracting, and retaining underrepresented STEM faculty and help universities adopt them.

Meanwhile, the Howard Hughes Medical Institute (HHMI) has funded a replication of UMBC’s Meyerhoff program at the University of North Carolina (UNC) in Chapel Hill and Pennsylvania State University (Penn State) in State College. A recent article in Science found that institutional partnerships, such as those between UMBC, UNC, and Penn State, can successfully establish programs in new institutional settings and produce similar educational outcomes for underrepresented groups in science and engineering (12). Informed by these results, HHMI is funding replication at six more universities. The Chan Zuckerberg Initiative (CZI) has committed to replication at the University of California, Berkeley and the University of California, San Diego in La Jolla. The Alfred P. Sloan Foundation has nurtured another program, supporting minority doctoral candidates in engineering and the sciences at eight universities designated as Sloan University Centers for Exemplary Mentoring.




Daunting Statistics

We are encouraged by all these national initiatives, but we must distinguish activities from outcomes. The work the science community has done has moved the needle only slightly with respect to increasing the proportion of underrepresented minorities pursuing advanced science degrees and securing faculty positions. There remains more to do. Whereas African Americans constitute 13% of our nation’s population, they account for just 5% of higher education faculty across all disciplines and 4% of new Ph.D.s in the natural sciences and engineering. Whereas Hispanics constitute 18% of the population, they account for about 4% of higher education faculty and 5% of new Ph.D.s in the natural sciences


The ineluctable question is whether university leaders and faculty are sufficiently committed to broadening participation in STEM so that the professoriate and STEM workforce become more reflective of the American population.

and engineering (13, 14). One analysis estimates that among selective research universities, Blacks constitute 0.7% of the biology faculty and 1.4% in chemistry and Hispanics constitute 3.0% in biology and 2.5% in chemistry (15). Blacks constitute fewer than 2% of researchers at NIH and other federal agencies and Hispanics just 4% (16). A National Academies report on the underrepresentation of women in science and engineering released earlier this year highlights the intersectional challenges for women of color in these fields. Qualitative differences in their experiences urge us to develop further efforts to support these groups (17).

The ineluctable question is whether university leaders and faculty are sufficiently committed to broadening participation in STEM so that the professoriate and STEM workforce become more reflective of the American population. We can do more as institutions and individuals. Changing the culture of our institutions requires persuading the people who have the power—presidents, provosts, deans, and senior faculty—to examine their views, become allies in the work, and pull underrepresented students into the science (18).

At UMBC, Mike Summers, a professor of biochemistry, HHMI investigator, and National Academy of Sciences (NAS) member, has mentored numerous minority and women students in his lab, where they study how HIV-1 and other retroviruses assemble in infected cells. Many of these undergraduate and graduate students have become faculty at research universities and other institutions nationwide. Whenever Summers is invited to speak, he actually gives two separate talks: one on his scientific research, and a second on how to support students of color in science and engineering. It takes researchers to produce researchers, including researchers of color; we must all take this kind of ownership of the problem of creating a diverse science and engineering community.

The ASPIRE Alliance observes in a report released this year that although many universities now have programs to support underrepresented minority students at the undergraduate and graduate levels, “support appears to diminish at the postdoctoral and early career levels.” (19) We have also noted this trend as we observe the career progression of Meyerhoff alumni. Without the connections needed to advance, many talented minority doctorates leave bench science even as colleges and universities say they have difficulty finding minority faculty candidates. We need to do much more to support these students as they make the transition from graduate and postdoctoral programs into their careers.

Crossroads recommended a program like the NSF’s ADVANCE but geared toward underrepresented minorities, a program that would provide institutions with resources for improving the recruitment, hiring, and advancement of underrepresented minority faculty in the sciences and engineering. UMBC received an ADVANCE grant that allowed us to make significant progress in recruiting and promoting women. We held discussions of and workshops on implicit bias and institutionalized faculty recruitment plans; we also developed transparent faculty promotion guidelines and consistent family support plans, provided research support for new women faculty, and facilitated leadership development. We have used lessons learned from that grant to also increase the recruitment and hiring of underrepresented minority faculty (18).

As we reimagine science and engineering in America, let us remind ourselves that success requires each of us to encourage our institutions to build a broader talent pool. Several years ago, Sandy Williams, then dean of the Duke University Medical School in Durham, NC, had serious conversations with Duke faculty about identifying and investing in a more diverse candidate pool. By becoming a champion for diversity and inclusion, Williams created a culture that supported the transition of minority students into the professoriate. A stunning outcome of his leadership is that four of our African American alumni—three who have earned the M.D.-Ph.D. and one who has earned an M.D. and a J.D.—are now on the faculty at Duke Medical School and engaged in cutting-edge work. Kafui Dzirasa, for example, is now a tenured associate professor at Duke in psychiatry and neurobiology with an endowed chair. Last fall, the Society for Neuroscience awarded Dzirasa its Young Investigator Award. This is science reimagined.




Taking Action

When people take action—individually and collectively—that’s when we see results. Now is the time to act as individuals and institutions. We challenge our colleagues and institutions to take these tangible actions.


• We can adopt practices, initiatives, and models that have been successful in supporting students and faculty of color, including those cited in this article (9). We can continue by also being scientific about the problem of diversity and how to address it. A place to start is rigorous analysis of data about students on our own campuses to understand both our challenges and our opportunities (18).


• As individual researchers and engineers we can mentor students of color and become their champions as they make the transition to graduate school, postdoctoral fellowships, and junior faculty positions (9). We can actively recruit applicants of color for faculty positions (18, 20). We can support colleagues of color as we do any colleague by collaborating with them on grants, research, and papers; reading and citing their work; and inviting them to give talks (20).


• As institutions, we can replicate and adapt those practices and programs, setting and working toward goals for significantly increasing the numbers of students and faculty of color who are succeeding (12, 21).


• In the longer term, the scientific community—agencies, funders, research universities—should continue to focus on and invest in the productive work of replicating practices and initiatives that work in undergraduate and graduate education as well as in cases of career advancement for underrepresented minorities (9, 21). Among other steps, we call on the NSF to institute an “ADVANCE program for underrepresented minority faculty” similar to the ADVANCE program for women in science and engineering that was established two decades ago and has delivered results in the years since its establishment (9).

To paraphrase Aristotle, choice, not chance, determines our destiny. In the end, progress depends on the choices we make. If we take advantage, now—of the COVID-19– and antiracism-driven energy in our social dynamic—seizing the opportunity to reduce underrepresentation in science, engineering, and medicine, and take responsibility for the work that needs to be done, then we can finally make real progress in creating and sustaining an inclusive enterprise that delivers benefits to America.

Footnotes
1To whom correspondence may be addressed. Email: hrabowsk@umbc.edu.


The authors declare no competing interest.


Any opinions, findings, conclusions, or recommendations expressed in this work are those of the authors and have not been endorsed by the National Academy of Sciences.


Published under the PNAS license.

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RESEARCH ARTICLE
Brief history of US debt limits before 1939

George J. Hall and Thomas J. Sargent

PNAS March 20, 2018 115 (12) 2942-2945; first published March 5, 2018 https://doi.org/10.1073/pnas.1719687115

Contributed by Thomas J. Sargent, January 19, 2018 (sent for review November 14, 2017; reviewed by Mark Aguiar, Lee Ohanian, and Jesus Villaverde)

Significance

Since 1939, the US Congress has imposed a limit on aggregate federal debt and left the Treasury free to design its securities and manage its portfolio of debts. Congress has increased the aggregate debt limit whenever it threatened to bind. Before 1939, Congress arranged things differently. Congress designed each security and put limits on the amount that could be issued. We construct an implied limit on aggregate debt before 1939 by summing bond-by-bond limits at each date. Before 1939, this implied aggregate limit often declined and led to Congressional actions that produced net-of-interest surpluses that enabled it to reduce federal debt, outcomes rarely observed after 1939.

Abstract

Between 1776 and 1920, the US Congress designed more than 200 distinct securities and stated the maximum amount of each that the Treasury could sell. Between 1917 and 1939, Congress gradually delegated all decisions about designing US debt instruments to the Treasury. In 1939, Congress began imposing a limit on the par value of total federal debt outstanding. By summing Congressional borrowing authorizations outstanding each year for each bond, we construct a time series of implied federal debt limits before 1939.
debt ceiling
debt management
fiscal policy

Article 1, Section 8 of the US Constitution assigns Congress authority to incur and manage federal debt. Before 1917, Congress designed all federal securities. After 1939, Congress delegated authority to design securities and manage the composition of total federal debt to the Treasury but put a limit on the par value of total outstanding federal debt. Since 1939, the debt limit has been raised 98 times and lowered 5 times. Before 1939, a synthetic aggregate debt limit implied by Congress’s decisions fell about as often as it rose. This paper synthesizes a pre-1939 aggregate debt limit, explains the data that underlie it, and describes its evolution from 1776 to 1939.

Before 1939, Congress explicitly imposed no limit on the aggregate amount of federal debt outstanding. Instead, it restricted issues of individual securities or sets of securities and gave the Secretary of Treasury little authority to conduct debt management operations. Congress designed each bond and note and prescribed a purpose for the revenue raised by selling it (e.g., to finance a war, to redeem an outstanding bond, or to pay for infrastructure, such as the Panama Canal). Between 1776 and 1920, Congress designed more than 200 different securities. In a typical year, between zero and eight federal securities were outstanding. For each bond and note, Congress set the coupon rate, minimum denomination, term to maturity, unit of account, tax exemptions, and call features. Congress usually directed that a security could not be reissued after it had been redeemed. The main exceptions occurred during wars when, by placing limits on quantities of short-term notes outstanding instead of issued, Congress temporarily permitted the Treasury to roll over its short-term debt. Depreciations and repudiations of government-issued currencies during and after the War for Independence created an enduring distrust of paper money that, until 1913, caused Congress to keep a tight rein on the Treasury’s authority to issue short-term currency-like liabilities.

From records of Congress’s decisions about security design and debt management, we have constructed an implied aggregate federal debt limit before 1939. We summed security-by-security limits stated in the authorizing legislation and tracked quantities of each security issued and retired. The debt limits are stated in units of Spanish dollars before 1791 and US dollars after 1791. We plot the implied aggregate debt limit series (blue lines in Figs. 13) along with the outstanding gross federal debt (red lines in Figs. 13).

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Fig. 1.

Par value of outstanding debt and the debt limit from 1776 to 1835. Nominal debt is the blue line. The red line is the nominal debt limit constructed by summing limits on individual securities.


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Fig. 2.

Par value of outstanding debt and the debt limit from 1840 to 1916. Nominal debt is the blue line. The red line is the nominal debt limit constructed by summing limits on individual securities.


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Fig. 3.

Par value of outstanding debt and the debt limit from 1917 to 1939. Nominal debt is the blue line. The red line is the nominal debt limit constructed by summing limits on individual securities.


In 1790, the first US Congress assumed state governments’ debts and debts that it had inherited from the Confederation Congress and refinanced them by issuing three consols. After issuing those three securities of indefinite maturity, the US Congress issued only bonds of limited maturities and set limited timespans for selling them. After a security had been redeemed, either because it had matured or been refinanced, it could not be reissued.

If no new loans had been authorized in the meantime, our synthesized debt limit declined. For example, as outstanding loans were repaid on schedule or earlier, the overall limit declined after the War of 1812 and again, after the Civil War.§

A consequence of these arrangements and policies was that, before 1930, at least during peace times, the debt limit functioned as an upper bound on total debt to be anticipated over medium to long horizons, making it an informative signal about an important feature of federal fiscal policy, namely the present values of prospective surpluses of federal revenues over net-of-interest expenditures that would be required to service federal debts.

In the next three sections, we briefly describe events that propelled notable movements in our synthetic pre-1939 aggregate debt (i.e., red lines in Figs. 13), and an associated par value of the debt subject to the aggregate limit is depicted in blue lines in Figs. 13.

1776–1935

Fig. 1 shows (i) that the Continental Congress and then, the Confederation Congress issued over $40 million in interest-bearing securities between 1776 and 1783 to help pay for the War of Independence, including a big jump in registered and coupon debt that accompanied the Confederation Congress’s recognition and consolidation of debts to soldiers and contractors in 1783; (ii) between 1783 and 1789, the Confederation Congress’s issues of zero interest-bearing securities called indents in lieu of unpaid interest on Continental debt; (iii) a jump in federal debt that occurred when the First US Congress nationalized (or “assumed”) state governments’ debts in 1790; (iv) a policy of making interest payments on outstanding debt and adding debt by borrowing to finance federal purchases of shares in the Bank of the United States and to build ships during the “big government” Federalist administrations of George Washington and John Adams from 1790 to 1801; (v) the Jefferson and Madison administrations’ “small government” policy of retiring debt until 1812; (vi) the huge increase in debt that the Madison administration issued to finance the War of 1812; and (vii) a postwar policy of gradually retiring federal debt that, by 1836, had driven it to zero.

1840–1916

Fig. 2 shows (i) no big jump in federal debt during the early 1840s when huge state debts that many states had defaulted on in response to adverse macroeconomic shocks of the late 1830s and early 1840s led European creditors and many state governments to pressure the US Congress again to nationalize state governments’ debts, pressure that Congress resisted in several narrowly decided votes; (ii) a moderate increase of federal debt during the Mexican War; (iii) the Buchanan administration’s 1857 reversal of the Taylor and Pierce administrations’ policies of gradually retiring debt, possibly as part of a Southern Democrat strategy to impair the federal government’s fiscal situation at the start of the Civil War in 1861; (iv) a massive increase of federal debt during the Civil War followed by almost 30 years of net-of-interest surpluses that, by the early 1890s, had reduced nominal debt by almost 50% of its 1865 level; (v) a moderate increase in government debt during the 1890s partly coming from the Cleveland administration’s efforts to defend the US gold standard against speculative attacks and partly coming from adverse macroeconomic, tariff, and tax policy shocks; and (vi) a policy of rolling over federal debt at a roughly constant level from the end of the Spanish American War of 1898 until the US entry into World War I in 1917. This period saw episodes in which debt limits set by earlier Congresses constrained subsequent Congresses and Secretaries of Treasury. For example, in the 1890s, debt limits nearly forced the Secretary of Treasury to take the United States off the gold standard, a goal that Friedman (4) said was supported by substantial minorities and at times, majorities of members of Congress.

1917–1939

This transition period saw (i) a huge increase in federal debt between 1917 and 1920 to finance US war expenditures and loans to European allies and associates; (ii) a post war decade of gradual reductions in nominal federal debt until about 1931; (iii) a decade long increase in federal nominal debt caused by an unprecedented sequence of peace time deficits engineered by the Hoover and Roosevelt administrations as consequences of their policies to fight an economic depression as if it were a war; (iv) Congress’s acceptance of the recommendations by Treasury Secretary Mellon during the 1920s and Morgenthau during the 1930s to delegate authority to design and manage securities to the Treasury; (v) some of the last times in US history during which nominal debt limits declined; and (vi) the first times in US history in which declines in our implied federal debt limit failed to be informative about prospective federal debts.

End of Project Finance

Beginning with the Second Liberty Bond Act of 1917, Congress allowed debt to be issued without being tied to a specific project. Consequently, during the 1920s and 1930s, the Treasury acquired, in Andrew Mellon’s words, “freedom in determining the character of securities to be issued.” The Treasury could market securities that were, according to Henry Morgenthau, “best suited to the needs of the investors to whom they are sold.” Congress also gave the Treasury greater control over the maturity structure of the debt. Decoupling of debt issuance from spending coincided with shortening the average maturity of the debt and smoothing the Treasury’s debt service profile.

Epilogue

Fig. 4 shows the counterpart of Figs. 13 drawn with the aggregate debt limit mandated by Congress instead of the synthetic limit depicted in the earlier figures. A comparison of Fig. 4 with Figs. 13 confirms that something about Congress’s attitudes about nominal government debt changed after the 1930s. Understanding those changes is a project for political economy and economic history. Our purpose has been to construct data that contribute to framing patterns and providing clues.

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Fig. 4.

Par value of outstanding debt and the debt limit from 1939 to 2014. Nominal debt is the blue line. The red line is the statutory debt ceiling.


Constructing an Aggregate Debt Limit Before 1939

To construct a limit on total federal debt before World War I, we summed limits on outstanding quantities of each security stated in authorizing legislation. During World War I, Congress began to place limits on classes of Treasury securities. When those limits were in place, we summed them.

Between 1776 and 1916, the US Congress authorized the Treasury to issue a total of approximately 200 distinct securities, with no more than 8 distinct ones being authorized in any particular year. Authorizing legislation for each security expressed Congress’s reason for borrowing, a sum to be borrowed, a security’s length, and its coupon rate. Other characteristics, restrictions, and terms, such as tax exemptions and call features, might also be stated. In most cases, Congress expressed a quantity in terms of the par value of the security that could be issued. It also restricted the period during which the security could be issued.

Let b(ℓ)tb(ℓ)t denote the par value of a particular security called ℓ outstanding at date t. Suppose that, at time t, there are NtNt different loans authorized and outstanding. The law of motion of the par value outstanding of security ℓ is
b(ℓ)t=b(ℓ)t−1+i(ℓ)t−r(ℓ)t,b(ℓ)t=b(ℓ)t−1+i(ℓ)t−r(ℓ)t,where i(ℓ)ti(ℓ)t denotes the par value of security ℓ issued at t and r(ℓ)tr(ℓ)t denotes the par value redeemed.#



When Congress authorized the Treasury to issue at most i(ℓ)∗i(ℓ)∗ of security ℓ, that meant that it placed the following restriction on the cumulative sum of issues:
∑ti(ℓ)t≤i(ℓ)∗.∑ti(ℓ)t≤i(ℓ)∗.Let i¯ti¯t denote the time t statutory balance on the quantity of bond ℓ that could be issued. This limit satisfies
i¯t=i(ℓ)∗−∑j=1ni(ℓ)t−j,i¯t=i(ℓ)∗−∑j=1ni(ℓ)t−j,where t−nt−n is the date on which the securities were first issued. Let r∼(ℓ)tr∼(ℓ)t be the amount of type ℓ bonds that must be redeemed by virtue of the bond contract. The implied limit on the par value of the quantity outstanding of security ℓ at time t is
b¯(ℓ)t=b(ℓ)t−1+i¯(ℓ)t−r∼(ℓ)t.b¯(ℓ)t=b(ℓ)t−1+i¯(ℓ)t−r∼(ℓ)t.The aggregate debt limit B¯tB¯t is the sum of these individual limits over all outstanding securities:
B¯t=∑ℓ=1Ntb¯(ℓ)t.B¯t=∑ℓ=1Ntb¯(ℓ)t.



The Temporary Loan of 1793 provides a good example. The Act of February 28, 1793 spelled out federal spending and revenues for the fiscal year. For example, it appropriated $143,591 to pay members of Congress and their staffs. Section 3 of the act authorized the government to borrow $800,000 at 5% interest to cover several of the expenditures listed in earlier sections of the act. Fig. 5, Left plots the amount authorized i(ℓ)∗i(ℓ)∗ as a horizontal green line. Between the second quarter of 1793 and the second quarter of 1794, $800,000 of loans were issued; we plot the cumulative sum of issues as the black solid line in Fig. 5, Left. Due to redemptions, the maximum quantity outstanding on this particular loan at any time was only $400,000 (blue dashed line in Fig. 5, Left). The statutory balance is the vertical distance between the green line in Fig. 5, Left (total issues authorized) and the black line in Fig. 5, Left (the cumulative sum of issues).

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Fig. 5.

The Temporary Loan of 1793. (Left) Authorization, issuance, and quantity outstanding. (Right) Quantity outstanding and implied limit. Q, quarter.


We computed the limit on the quantity outstanding by adding the statutory balance to the quantity outstanding and netting out redemptions. We plot the implied limit in red in Fig. 5, Right. As bonds issued as part of the Temporary Loan of 1793 were gradually redeemed, they could not be reissued. Therefore, the debt limit ratcheted down with redemptions. By the third quarter of 1794, the limit on the quantity issue had been reached, the statutory balance hit zero, and the loan was closed.

When aggregating limits across individual securities, we adhered to the following rules.


We excluded any loans issued solely for the purpose of refunding existing debt or purchasing gold or silver.


When authorization dates were not explicitly stated, we assumed that a security could be issued 30 days after authorizing legislation passed Congress and that issuance “closed” (i.e., authorization expired) 365 days after the final issuance.


When Congress limited a quantity outstanding for an authorized security, we recorded b¯(ℓ)tb¯(ℓ)t directly from the legislation.

The large quantity and variety of different securities issued to finance World War I made placing limits on individual securities impractical. Therefore, as part of the Second Liberty Bond Act of 1917, Congress began placing limits on different classes of Treasury securities. To impute an aggregate debt limit during this period, we deduced the statutory balance for each class of securities and then, aggregated across the various classes. Over the next two decades, Congress gradually merged and relaxed these sublimits, and by 1939, all of the sublimits had been removed, leaving only the aggregate limit.

Acknowledgments

We thank Andrew Abel, Mark Aguiar, Andrew Atkeson, James Alt, Marco Bassetto, Michael Bordo, Randall Calvert, Jeffry Frieden, Lee Ohanian, Ricardo Reis, Hugh Rockoff, and Jesus Fernandez-Villaverde for helpful suggestions. We thank Yuval Yossefy for research assistance and Andrew Young at the US Department of Treasury Library for helping to track down government documents. We thank William Berkley, Don Wilson, the Becker–Friedman Institute of the University of Chicago, and National Science Foundation Grant SES-0417519 for financial support.

Footnotes


1G.J.H. and T.J.S. contributed equally to this work.
2To whom correspondence should be addressed. Email: thomas.sargent@nyu.edu.


Author contributions: G.J.H. and T.J.S. designed research; G.J.H. and T.J.S. performed research; G.J.H. and T.J.S. analyzed data; G.J.H. and T.J.S. assembled the underlying data; G.J.H. and T.J.S. wrote computer codes; G.J.H. and T.J.S. drew interpretations; and G.J.H. and T.J.S. wrote the paper.


Reviewers: M.A., Princeton University; L.O., University of California, Los Angeles; and J.V., University of Pennsylvania.


The authors declare no conflict of interest.


*Four additional times, Congress failed to renew temporary increases in the limit before their expiration dates. In each of these cases, Congress raised the limit shortly thereafter.


†We provide details in Constructing an Aggregate Debt Limit Before 1939.


‡During the War of 1812 and the Civil War, Congress widened the Treasury’s latitude to choose which debt instruments to sell. However, after those wars, Congress quickly reasserted control over both the size and design of the debt.


§Ever since the United States issued its first bond in 1776, debt limits have been presented and measured in terms of face values. Fluctuating interest rates have driven market values away from face values (1, 2). (Market interest rates occasionally included premia for default risk and exchange rate risk.) Congress often paid attention to gaps between market and par values of both directions. Before the introduction of zero-coupon Treasury Bills in 1929, Congress prohibited the Treasury from selling securities for less than their par values. The fact that market values of bonds issued during the Mexican War rose above par motivated Congress to make the famous 5–20s issued during the Civil War callable at the government’s discretion after 5 years at par values. For the period after 1945, ref. 2 presents measures of the marketable US Treasury obligations both marked to market and in terms of face value. We have extended these series back to 1776. Especially after 1880 but also before, the Treasury managed federal debt in ways that made the par value of the debt closely approximate its market value (3).


¶A notable exception to this debt pay-down policy was the $11.25 million borrowed to finance the Louisiana Purchase in 1803.


#The bond contracts made some redemptions mandatory—we will call these r∼(ℓ)tr∼(ℓ)t; others were “early redemptions.”
Copyright © 2018 the Author(s). Published by PNAS.


This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).

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