PRODUCTIVITY IN THE PEANUT PRODUCTION IN ALABAMA AND THE SOUTHEAST AFTER THE QUOTA SYSTEM ELIMINATION: IDENTIFYING KEY CONTRIBUTORS TO THE YIELD AND EFFICIENCY GAINS

Ever since the elimination of marketing quotas in 2002, the U.S. peanut production sector has been undergoing significant structural changes including significant locational shifts in the production with a considerable amount of peanut planting relocating from the Southwest and the Virginia/North Carolina regions to the Southeast, which is emerging as the dominant peanut base. This is particularly relevant to Alabama agriculture, given that peanuts are among the top four crops (by value) in the state. At the same time, owing to no longer subsidized and thus lower prices of food-use peanuts, the peanut acreage has declined substantially since the elimination of quotas; but the yields are up. USDA heuristically attributes these yield improvements to a systemic shift in the peanut production to more efficient farmers and more productive lands, which is however not self-evident and requires formal scientific examination. The gap in our knowledge on drivers of these better-than-ever yield improvements is important to address because the knowledge of primary contributors to increases in peanut yields has a significant potential to benefit both the peanut producers and regulators. Since the yield, which effectively measures the overall productivity of land, has a direct intensive-margin-type link to farmers' profitability, the understanding of underlying yield-enhancing factors can help peanut growers in Alabama and, more generally, in the Southeast to better adapt to post-quota-system realities and remain economically viable in the new market environment.The project will utilize high-quality farm-level data from USDA Economic Research Service Agricultural Resource Management Survey, which is to be merged with the data on climate and soil conditions. The statistical/econometric analysis of the data will rely on novel and robust methods including the recently developed tests of stochastic dominance for the estimated data with dependence as well as state-of-the-art moment-based and distributional decomposition techniques. This research project will ultimately result in an increase in our knowledge of the U.S. peanut production sector and its structure.