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Item Pea in Rotation with Wheat Reduced Uncertainty of Economic Returns in Southwest Montana(2015-01) Miller, Perry R.; Bekkerman, Anton; Jones, Clain A.; Burgess, Macdonald H.; Holmes, Jeffrey A.; Engel, Richard E.Pea (Pisum sativum L.) is increasingly being rotated with wheat (Triticum aestivum L.) in Montana. Our objective was to compare economic net returns among wheat-only and pea–wheat systems during an established 4-yr crop rotation. The experimental design included three wheat-only (tilled fallow–wheat, no-till fallow–wheat, no-till continuous wheat) and three no-till pea–wheat (pea–wheat, pea brown manure–wheat, and pea forage–wheat) systems as main plots, and high and low available N rates as subplots. Net returns were calculated as the difference between market revenues and operation and input costs associated with machinery, seed and seed treatment, fertilizer, and pesticides. Gross returns for wheat were adjusted to reflect grain protein at “flat” and “sharp” discount/premium schedules based on historical Montana elevator schedules. Cumulative net returns were calculated for four scenarios including high and low available N rates and flat and sharp protein discount/premium schedules. Pea–wheat consistently had the greatest net returns among the six systems studied. Pea fallow–wheat systems exhibited greater economic stability across scenarios but had greater 4-yr returns (US$287 ha–1) than fallow–wheat systems only under the low N rate and sharp protein discount schedule scenario. We concluded that pea–wheat systems can reduce net return uncertainties relative to wheat-only systems under contrasting N fertility regimes, and variable wheat protein discount schedules in southwestern Montana. This implies that pea–wheat rotations, which protected wheat yield and/or protein levels under varying N fertility management, can reduce farmers’ exposure to annual economic variability.Item The role of simulations in econometrics pedagogy(2014-12) Bekkerman, AntonThis article assesses the role of simulation methods in econometrics pedagogy. Technological advances have increased researchers' abilities to use simulation methods and have contributed to a greater presence of simulation-based analysis in econometrics research. Simulations can also have an important role as pedagogical tools in econometrics education by providing a data-driven medium for difficult-to-grasp theoretical ideas to be empirically mimicked and the results to be visualized and interpreted accessibly. Three sample blueprints for implementing simulations to demonstrate foundational econometric principles provide a framework for gauging the effectiveness of simulation analysis as a pedagogical instrument.