Scholarship & Research
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Item Price relationships in the U.S. nitrogen fertilizer industry(Montana State University - Bozeman, College of Agriculture, 2018) Gumbley, Thomas J.; Chairperson, Graduate Committee: Anton BekkermanThis study estimates the price dynamics in the U.S. nitrogen fertilizer industry, measures information flow efficiency in spatially separated fertilizer markets, and measures to what extent structural changes in corn and natural gas markets may have altered these price dynamics and information flow relationships. A vector error correction model is used to measure the short-run and long-run relationships between nitrogen fertilizer markets, natural gas markets, and corn markets. The results show that price information flows from the central market of New Orleans to inland regional markets. The efficiency of this information flow increased in the period after the Renewable Fuel Standards increased the demand for corn.Item The effect of three drying temperatures on the germination of corn harvested at three stages of maturity(Montana State University - Bozeman, College of Agriculture, 1971) Wobil, JosiahItem Relationships of factors affecting the growth and composition of corn forage on irrigated soils in Montana(Montana State University - Bozeman, College of Agriculture, 1964) Watkins, Richard EarlItem Satelite production forecasts : vauled with simulated futures and options trading(Montana State University - Bozeman, College of Agriculture, 2005) Martin, Lucanus Earl; Chairperson, Graduate Committee: Joe Atwood.Both the USDA and private firms are allocating substantial capital towards providing accurate and timely crop production forecasts. Production forecasts based on satellite imagery have been suggested as a means of making forecasts earlier, more frequent, and cheaper. This thesis attempts to determine if satellite data increases information with respect to crop condition and final production. If so, does the additional information have value and can it be used to make profitable trades in the futures market? These questions are answered using NDVI data for Iowa and Illinois. Jackknifed out-of-sample crop production estimates are calculated for both corn and soybeans for the individual states. A variety of models were used, each including different bi-weekly periods. USDA crop condition scores are also tested in some of the models. A model based on the current stocks-to-use ratio for each commodity is used to predict the market's expected production level. When the satellite forecast differed from the market's expectation a trade was made in the futures markets. Both futures and option strategies were tested. Results suggest that satellite based production forecasts may result in profitable soybean trades, particularly when downside risk can be reduced by trading options. Further work should focus on refining the satellite images used in the model and exploring more complex option trading strategies.