Trade plays an increasingly important role in the global food system, which is projected to be strained by population growth, economic development, and climate change. For this reason, there has been a surge of interest in the water resources embodied in international trade, referred to as ''global virtual water trade.'' In this paper, we present a comprehensive assessment of virtual water flows within the United States (U.S.), a country with global importance as a major agricultural producer and trade power. This is the first study of domestic virtual water flows based upon intranational food transfer empirical data and it provides insight into how the properties of virtual water transfers vary across scales. We find that the volume of virtual water flows within the U.S. is equivalent to 51% of international flows, which is slightly higher than the U.S. food value and mass shares, due to the fact that water-intensive meat commodities comprise a much larger fraction of food transfers within the U.S.. The U.S. virtual water flow network is more social, homogeneous, and equitable than the global virtual water trade network, although it is still not perfectly equitable. Importantly, a core group of U.S. States is central to the network structure, indicating that both domestic and international trade may be vulnerable to disruptive climate or economic shocks in these U.S. States.

The world food system is globalized and interconnected, in which trade plays an increasingly important role in facilitating food availability. We present a novel application of network analysis to domestic food flows within the USA, a country with global importance as a major agricultural producer and trade power. We find normal node degree distributions and Weibull node strength and betweenness centrality distributions. An unassortative network structure with high clustering coefficients exists. These network properties indicate that the USA food flow network is highly social and well-mixed. However, a power law relationship between node betweenness centrality and node degree indicates potential network vulnerability to the disturbance of key nodes. We perform an equality analysis which serves as a benchmark for global food trade, where the Gini coefficient = 0.579, Lorenz asymmetry coefficient = 0.966, and Hoover index = 0.442. These findings shed insight into trade network scaling and proxy free trade and equitable network architectures.

We contribute to the debate over globalization and the environment by asking, what is the impact of trade on national water use? To address this question, we employ econometric methods to quantify the causal relationship between trade openness and water use. Specifically, we use the instrumental variables methodology to evaluate the impact of trade openness on domestic water withdrawals in agriculture and industry. We find that trade openness does not have a significant impact on total or industrial water withdrawals. However, we show that one percentage point increase in trade openness leads to a 5.21% decrease in agricultural water withdrawals. We find that trade openness reduces water use in agriculture primarily through the intensive margin effect, by leading farmers to produce more with less water, such as through the adoption of technology. We do not find evidence for extensive margin or crop mix impacts on agricultural water withdrawals. Significantly, these results demonstrate that trade openness leads to less water use in agriculture. This finding has broad scientific and policy relevance as we endeavor to untangle causal relationships in the complex global food system and develop policies to achieve water and food security.

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To contribute to the debate over globalization and the environment we ask the question: what is the impact of trade openness on the nutrient use of nations? We address this question by using econometric methods to quantify the causal relationship between the trade openness and the nutrient use of nations on a global scale. In our empirical analysis we go beyond a cross-sectional analysis. We exploit time-series variation for an unbalanced panel of countries that spans the time period 2001-2014 (1027 total observations). By using a panel data analysis we are able to use fixed effects and better control for unobservable heterogeneity. We also explicitly consider how the openness of a country to trade may interact with its comparative advantage which determines its relative specialization in production, and hence its export strength as well as its import needs. We find that trade openness on average does not significantly impact nutrient use. However, there is evidence that as countries become more open and more capital abundant their nutrient use is reduced. This finding is in line with previous research that shows that trade openness does not have a negative impact on the environment. Our findings have both scientific and policy relevance as we strive to untangle causal relationships in the global food supply chain and determine its environmental impacts.