Forecasting national CO2 emissions worldwide.

Urgent climate action, especially carbon emissions reduction, is required to achieve sustainable goals. Therefore, understanding the drivers of and predicting [Formula: see text] emissions is a compelling matter. We present two global modeling frameworks-a multivariate regression and a Random Forest Regressor (RFR)-to hindcast (until 2021) and forecast (up to 2035) [Formula: see text] emissions across 117 countries as driven by 12 socioeconomic indicators regarding carbon emissions, economic well-being, green and complexity economics, energy use and consumption. Our results identify key driving features to explain emissions pathways, where beyond-GDP indicators rooted in the Economic Complexity field emerge. Considering current countries' development status, divergent emission dynamics appear. According to the RFR, a -6.2% reduction is predicted for developed economies by 2035 and a +19% increase for developing ones (referring to 2020), thus stressing the need to promote green growth and sustainable development in low-capacity contexts.

An R&D perspective on international trade and sustainable development.

Research and Development (R&D) is the common denominator of innovation and technological progress, supporting sustainable development and economic growth. In light of the availability of new datasets and innovative indicators, in this work, we introduce a novel perspective to analyse the international trade of goods through the lenses of the nexus R&D-industrial activities of countries. We propose two new indices, RDE and RDI, summarizing the R&D content of countries' export and import baskets-respectively-and investigate their evolution in time, during the period 1995-2017, and space. We demonstrate the potential of these indices to shed new light on the evolution of R&D choices and trade, innovation, and development. In fact, compared to standard measures of countries' development and economic growth (e.g., the Human Development Index among the others tested), these indices provide complementary information. In particular, tracing the trajectories of countries along the RDE-HDI plane, different dynamics appear for countries with increased HDI, which we speculate can be reasoned with countries' availability of natural resources. Eventually, we identify two insightful applications of the indices to investigate further countries' environmental performances as related to their role in international trade.

Measuring node centrality when local and global measures overlap.

Centrality metrics aim to identify the most relevant nodes in a network. In the literature, a broad set of metrics exists, measuring either local or global centrality characteristics. Nevertheless, when networks exhibit a high spectral gap, the usual global centrality measures typically do not add significant information with respect to the degree, i.e., the simplest local metric. To extract different information from this class of networks, we propose the use of the Generalized Economic Complexity index (GENEPY). Despite its original definition within the economic field, the GENEPY can be easily applied and interpreted on a wide range of networks, characterized by high spectral gap, including monopartite and bipartite network systems. Tests on synthetic and real-world networks show that the GENEPY can shed light about the node centrality, carrying information generally poorly correlated with the node number of direct connections (node degree).

Role of trade agreements in the global cereal market and implications for virtual water flows.

Understanding the dynamics of food trade, which involves a corresponding virtual trade in environmental resources, is relevant for its effects on the environment. Among the socioeconomic factors driving the international food market, trade agreements play a significant yet poorly understood role in facilitating access to worldwide trade. Focusing on the global trade of grain from 1993 to 2015, we investigate the role of trade agreements in activating new linkages and increasing traded volumes and their environmental implications. Through a data-driven approach, we show that the activation of a trade agreement among countries induces a more than six-fold increase in the probability of establishing a new link. Also, the presence of a trade agreement over time, not just its activation, relates to a more stable market since it reduces the probability of link deactivation by more than half. The trade links covered by agreements show larger flows and smoother inter-annual fluctuations. Furthermore, trade agreements encourage the development of more water-efficient flows by stimulating the exchange of crops with high water productivity values. The average economic water productivity of crops traded under trade agreements increases by 62% when considering total virtual water and even by 93% when focusing on blue water.

Compliance with EAT-Lancet dietary guidelines would reduce global water footprint but increase it for 40% of the world population.

The EAT-Lancet Commission has proposed a global benchmark diet to guide the shift towards healthy and sustainable dietary patterns. Yet it is unclear whether consumers' choices are convergent with those guidelines. Applying an advanced statistical analysis, we mapped the diet gap of 15 essential foods in 172 countries from 1961 to 2018. We found that countries at the highest level of development have an above-optimal consumption of animal products, fats and sugars but a sub-optimal consumption of legumes, nuts and fruits. Countries suffering from limited socio-economic progress primarily rely on carbohydrates and starchy roots. Globally, a gradual change towards healthy and sustainable dietary targets can be observed for seafood, milk products, poultry and vegetable oils. We show that if all countries adopted the EAT-Lancet diet, the water footprint would fall by 12% at a global level but increase for nearly 40% of the world's population.

Trade of economically and physically scarce virtual water in the global food network.

The virtual water (VW) trade associated to food is composed by the quantity of water utilized for the production of the crops exchanged on the global market. In assessing a country's water abundance or scarcity when entering the international VW trade, scholars consider only physical water availability, neglecting economic water scarcity, which indicates situations in which socio-economic obstacles impede the productive use of water. We weight the global VW trade associated to primary crops with a newly proposed composite water scarcity index (CWSI) that combines physical and economic water scarcity. 39% of VW volumes is exported from countries with a higher CWSI than the one of the destination country. Such unfair routes occur both from low- to high-income countries and among low- and middle-income countries themselves. High-income countries have a predominant role in import of CWSI-weighted VW, while low- and middle-income countries dominate among the largest CWSI-weighted VW exporters. For many of them economic water scarcity dominates over physical scarcity. The application of the CWSI elicits also a status change from net exporter to net importer for some wealthy countries and viceversa for some low- and middle-income countries. The application of CWSI allows one to quantify to what extent VW exchanges flow along environmentally and economically unfair routes, and it can inform the design of compensation policies.

A network approach to rank countries chasing sustainable development.

In 2015, the United Nations established the Agenda 2030 for sustainable development, addressing the major challenges the world faces and introducing the 17 Sustainable Development Goals (SDGs). How are countries performing in their challenge toward sustainable development? We address this question by treating countries and Goals as a complex bipartite network. While network science has been used to unveil the interconnections among the Goals, it has been poorly exploited to rank countries for their achievements. In this work, we show that the network representation of the countries-SDGs relations as a bipartite system allows one to recover aggregate scores of countries' capacity to cope with SDGs as the solutions of a network's centrality exercise. While the Goals are all equally important by definition, interesting differences self-emerge when non-standard centrality metrics, borrowed from economic complexity, are adopted. Innovation and Climate Action stand as contrasting Goals to be accomplished, with countries facing the well-known trade-offs between economic and environmental issues even in addressing the Agenda. In conclusion, the complexity of countries' paths toward sustainable development cannot be fully understood by resorting to a single, multipurpose ranking indicator, while multi-variable analyses shed new light on the present and future of sustainable development.

Correction: Shock transmission in the International Food Trade Network.

[This corrects the article DOI: 10.1371/journal.pone.0200639.].

Reconciling contrasting views on economic complexity.

Summarising the complexity of a country's economy in a single number is the holy grail for scholars engaging in data-based economics. In a field where the Gross Domestic Product remains the preferred indicator for many, economic complexity measures, aiming at uncovering the productive knowledge of countries, have been stirring the pot in the past few years. The commonly used methodologies to measure economic complexity produce contrasting results, undermining their acceptance and applications. Here we show that these methodologies - apparently conflicting on fundamental aspects - can be reconciled by adopting a neat mathematical perspective based on linear-algebra tools within a bipartite-networks framework. The obtained results shed new light on the potential of economic complexity to trace and forecast countries' innovation potential and to interpret the temporal dynamics of economic growth, possibly paving the way to a micro-foundation of the field.

Charting out the future agricultural trade and its impact on water resources.

International agricultural trade triggers inter-dependency among distant countries, not only in economic terms but also under an environmental perspective. Agricultural trade has been shown to drive environmental threats pertaining to biodiversity loss and depletion and pollution of freshwater resources. Meanwhile, trade can also encourage production where it is most efficient, hence minimizing the use of natural resources required by agriculture. In this study, we provide a country-level assessment of the future international trade for 6 primary crops and 3 animal products composing 70% of the human diet caloric content. We set up four variegate socio-economic scenarios with different level of economic developments, diets habits, population growth dynamics, and levels of market liberalization. Results show that the demand of agricultural goods and the correspondent trade flow will increase with respect to current levels by 10-50% and 74-178% by 2050, respectively. The largest increase in the amount of traded goods is expected under the Economic Optimism scenario that will see an average trade flow of 2830 kcal/cap/day (i.e., nearly doubling the current per-capita flow). Most of the increase will be driven by the trade of crops for animal feeding, particularly maize will be the most traded crop. The trade networks architecture in 2050 and 2080 will be very different from the one we actually know, with a clear shift of the trade pole from the Western toward the Eastern economies. The dramatic changes of global food-sources and trade patterns will jeopardize the water resources of new regions while exacerbating the pressure in those areas that will continue serving food also in the future. In spite of this, trade may annually save around 40-60 m3 of water per person, compared to a situation where countries are self-sufficient.