Journal of Agricultural and Resource Economics
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Search and browse every article in the JARE archive, from 1992 to today. Filter by issue or author, read abstracts, and bookmark articles to come back to.
JAREVol. 51 · No. 3September 2026
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Volume 44, Issue 3 · September 2019
This paper re-evaluates practical methods of forecasting corn and soybean basis in the eastern Corn Belt. The accuracy of forecast methods differs over the course of the crop-marketing year. At harvest, historical moving average forecasts perform best. Post-harvest forecasts may be improved at short forecast horizons (<8'12 weeks ahead) by combining historical moving averages and recent basis levels. Results suggest that using 3-to-5-year moving average forecasts for corn basis and a 2- or 5-year moving average for soybean basis from harvest through April. The accuracy of these corn and soybean basis forecasts decreases markedly during the summer months.
Volume 35, Issue 1 · April 2010
This article uses national, quarterly data to examine U.S. meat demand using the Rotterdam model. We investigate the effect of multiple information indices linking different health concerns with diet, changes in household dynamics, and meat recall information. Medical journal articles linking iron, zinc, and protein with health and diet increase beef and poultry demand, whereas articles dealing with fat, cholesterol, and diet concerns reduce beef demand. Increasing consumption of food away from home enhances pork and poultry demand while reducing beef demand. Combined, these results provide a more complete and current understanding of the impact of multiple information factors faced by U.S. consumers.
Volume 29, Issue 2 · August 2004
Successful risk management strategies for agribusiness firms based on futures and options contracts are contingent on their ability to accurately forecast basis. This research addresses three primary questions as they relate to basis forecasting accuracy: (a) What is the impact of adopting a time-to-expiration approach, as compared to the more common calendar-date approach? (b) What is the optimal number of years to include in calculations when forecasting livestock basis using historical averages? and (c) What is the effect of incorporating current basis information into a historical-average-based forecast? Results indicate that use of the time-to-expiration approach has little impact on forecast accuracy compared to using a simple calendar approach, but forecast accuracy is improved by incorporating at least a portion of current basis information into basis forecasts.
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