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Sources of and Solutions for Southern Agricultural Risk: The View from the Coast

Published online by Cambridge University Press:  28 April 2015

Michele C. Marra*
Affiliation:
Department of Agricultural and Resource Economics, North Carolina State University
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Extract

Ray et al. have examined the national agricultural sector impacts of the 1996 FAIR Act using a stochastic simulation model based on the Policy Analysis System (POLYSYS). The model outcomes are predictions of various economic measures, including the coefficient of variation of net returns for corn, wheat, soy-beans, and cotton. Then Knutson et al. use the results of the Ray et al. simulations to predict the distribution of net farm income over the next 10 years for several types of representative southern farms. Any attempt to measure the changes in riskiness in southern agriculture is commendable—even heroic—and I applaud these efforts, both the national modeling effort by Ray et al. and the application to southern representative farms by Knutson et al. This task has a lot in common, I think, with trying to “tease out” the temperature changes associated with the greenhouse effect. The number of factors and mechanisms at work is mind-boggling. It's tough enough to try to get a handle on what might happen to the first moment of net farm income over the next 10 years, let alone the second.

Type
Invited Paper Sessions
Copyright
Copyright © Southern Agricultural Economics Association 1998

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References

U.S. Department of Agriculture, National Agricultural Statistics Service. “Cash Receipts: Top Five Commodities in Each State.” In Statistical Highlights, 1996-97: Farm Economics. USDA/NASS, Washington DC, 1997.Google Scholar