NASA Harvest-funded research recently published by consortium partner and former USDA Chief Economist Joseph Glauber (IFPRI) in collaboration with agricultural economics expert Mario Miranda (Ohio State University) explores a new modeling methodology considering a bi-hemispheric asynchronous cycle of crop production. Titled “A Model of Asynchronous Bi-Hemispheric Production in Global Agricultural Commodity Markets,” the team presents a structural model that can provide insights into intraseasonal patterns of storage, trade, and market prices. Due to rapid expansion of agricultural land use and increased cereal crop productivity throughout South America over the past decade, the continent is now firmly established as the world’s largest exporter of soybean and maize which has far-reaching impacts on the global food market. The authors highlight that the uptick seen in crop production throughout the Southern Hemisphere has led to increased supplies helping to meet growing food consumption needs and has simultaneously reduced the global crop growing cycle timeline.
This has come to fruition due to more balanced production between Northern and Southern regions, with both hemispheres producing nearly equal amounts of crops at different times of the year. This asynchronous production pattern has essentially shortened the traditional growing season from one year to six months, providing an opportunity for adjustments to be made to planned production estimates semi-annually. This is to say that evaluations of food availability can and should be made twice in a year as compared to many existing modeling techniques which only consider an annual cycle of production.
As Earth’s land surface area becomes increasingly dedicated to agricultural production, it is critical to capture agrifood system patterns that are generally missed by current annual-based modeling techniques. With this in mind, the authors present a “semi-annual stochastic spatial–temporal equilibrium model” of a typical agricultural market which considers two major exporting regions (North and South) that plant and harvest at different times of the year. Knowing that new food supply comes to market every six months, it is critical to use a model that captures cross-hemispheric trends in agricultural production that have taken place over the past few decades. Increased frequency in the analysis of crop production statistics can ultimately lead to more stable food supply and decreased price volatility. This type of model can also be applied to gain insight on how land use changes in this time period have affected seasonal stockholding and exporting, as well as how these trends are expected to affect future global food markets. By applying a model that takes these factors into account, we can better answer questions about how shifts in production and consumption affect seasonal patterns of trade between the northern/southern hemispheres and the rest of the world.
Furthermore, we can draw informed conclusions about seasonal incentives to maintain cereal inventories as well as import/export changes throughout a given year. Simulating the model under counterfactual polar scenarios, the authors were able to make a comparison between a once per year producer/exporter scenario and the more realistic scenario of two equally-sized producer/exporters planting and harvesting at different times of year. In the latter balanced-world scenario, it can be deduced that “the global demand for exports can be met primarily by new production in the harvesting region, thereby reducing end-of-harvest-season inventories that might otherwise be held to meet demand during the planting season.” At a high level, we must recognize and incorporate new patterns that develop as the world’s food supply dynamics change in order to remove biased analyses of the state of global food security.
Read the full publication titled “A Model of Asynchronous Bi-Hemispheric Production in Global Agricultural Commodity Markets” in the American Journal of Economics to further explore the model methodology and applications.