Out-of-sample forecasting of annual U.S. per capita food consumption, applying data from 1923 to 1992, is used as a basis for model selection among the absolute price Rotterdam model, a first-differenced linear approximate almost ideal demand system (FDLA/ALIDS) model, and a first-differenced double-log demand system. Conditional-on-price consumption forecasts derived from elasticities are determined to be superior to direct statistical model forecasts. Models with consumer theory imposed through parametric restrictions provide better forecasts than models with little theory-imposition. For these data, a double-log demand system is a superior forecaster to the Rotterdam model, which is superior to the FDLA/ALIDS model. Copyright 1996, Oxford University Press.
The objective of this research is to identify and quantify the motivations for organic grain farming in the United States. Survey data of US organic grain producers were used in regression models to find the statistical determinants of three motivations for organic grain production, including profit maximization, environmental stewardship, and an organic lifestyle. Results provide evidence that many organic grain producers had more than a single motivation and that younger farmers are more likely to be motivated by environmental and lifestyle goals than older farmers. Organic grain producers exhibited a diversity of motivations, including profit and stewardship.
The objective of this study was to determine if site-specific application of postemergence herbicide was economically viable with current technologies. This objective was accomplished by: developing an algorithm that determined the economic optimal postemergence herbicide rate; creating models to determine the impact that postemergence herbicide rate has on yield; and determining whether site-specific application of postemergence herbicide has greater net returns than those from a uniform application of postemergence herbicide. Weed species identification and population counts were done on a regular grid in five fields across Kansas. A decision algorithm was developed to determine the economic optimal rate of postemergence herbicide for each grid cell. The sitespecific herbicide rate and four standard herbicide rates [0, 0.5, 0.75, and full (1·) label rate] were applied according to a split-plot design. Weed population observations made three weeks after application showed that the site-specific treatment controlled the weeds present in the fields. Production functions developed to determine whether postemergence herbicide rate had an impact on yield showed that it had a positive, yet statistically insignificant, effect on yield. The difference in estimated net returns between applications of site-specific rate and uniform full-label rate covered all of the costs associated with sitespecific application of postemergence herbicide. The margin between the estimated net returns for site-specific and uniform application of the economic optimal rate covered only a portion of the costs associated with site-specific application of postemergence herbicide.
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