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Evaluation of Selected USDA WAOB and NASS Forecasts and Estimates in Corn and Soybeans

The United States Department of Agriculture (USDA) has a number of agencies that are involved in collecting, analyzing, forecasting, and disseminating information about the production and consumption of the corn and soybean crops. Market participants rely heavily on estimates and forecasts provided by these agencies in order to form price expectations and to make business decisions. In spite of on-going efforts to maintain the quality of information provided and the transparency of the methodology used, misunderstanding, concerns, or complaints about the information provided periodically arise. More recently (since 2006) those concerns have centered on the accuracy of the quarterly estimates of corn inventories and to a lesser extent on the methodology and accuracy of early season yield forecasts. It is in that context that this review of USDA forecasts and estimates for corn and soybeans was conducted.
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Poor Convergence Performance of CBOT Corn, Soybean and Wheat Futures Contracts: Causes and Solutions

The lack of consistently acceptable convergence performance for Chicago Board of Trade (CBOT) corn, soybean, and wheat contracts since late 2005 has been widely discussed (e.g., Henriques, 2008).1 Convergence performance is summarized in Figure 1, depicting delivery location basis levels on the first delivery date of each contract for the three commodities over January or March 2000 through March 2009. Extended periods of lack of convergence since late 2005 are obvious, although variable over time and by commodity. Performance has been consistently weakest in wheat, with futures prices at times exceeding delivery location cash prices by $1.00/bu., a level of disconnect between cash and futures not previously experienced in grain markets.
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Empirical Confidence Intervals for WASDE Forecasts of Corn, Soybean, and Wheat Prices

This study investigates empirical methods of generating prediction intervals for WASDE forecasts of corn, soybean, and wheat prices over the 1980/81 through 2006/07 marketing years. Empirical methods use historical forecast errors to estimate forecast error distributions, which are then used to predict confidence limits of forecasts. Five procedures were used to estimate empirical confidence limits, including histograms, kernel density estimation, logistic distribution, quantile regression, and quantile regression with stocks-to-use ratios.
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Weather, Technology, and Corn and Soybean Yields in the U.S. Corn Belt

The purpose of this study was to investigate the relationship between weather, technology, and corn and soybean yields in the U.S. Corn Belt. Corn and soybean yields, monthly temperature, and monthly precipitation observations were collected over 1960 through 2006 for Illinois, Indiana, and Iowa. Multiple regression models were developed based on specifications found in studies by Thompson (1962 1963 1969 1970 1985 1986 1988). Estimated models explained at least 94% and 89% of the variation in corn and soybean yields for each state, respectively.
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The Adequacy of Speculation in Agricultural Futures Markets: Too Much of a Good Thing?

The objective of this report is to re-visit the “adequacy of speculation” debate in agricultural futures markets. The Commodity Futures Trading Commission makes available the positions held by index funds and other large traders in their Commitment of Traders reports. The results suggest that after an initial surge from early 2004 through mid-2005, index fund positions have stabilized as a percent of total open interest. Traditional speculative measures do not show any material changes or shifts over the sample period. In most markets, the increase in long speculative positions was equaled or surpassed by an increase in short hedging. So, even after adjusting speculative indices for index fund positions, values are within the historical ranges reported in prior research. One implication is that long-only index funds may be beneficial in markets traditionally dominated by short hedging. Attempts to curb speculation through regulatory means should be weighed carefully against the potential benefits provided by this class of speculators.
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