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Revenue Insurance for Georgia and South Carolina Peaches

Published online by Cambridge University Press:  28 April 2015

Stephen E. Miller ,
Kandice H. Kahl  and
P. James Rathwell
Stephen E. Miller
Affiliation:
Department of Agricultural and Applied Economics, Clemson University
Kandice H. Kahl
Affiliation:
Department of Agricultural and Applied Economics, Clemson University
P. James Rathwell
Affiliation:
Department of Agricultural and Applied Economics, Clemson University
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Abstract

We estimate actuarially fair premium rates for yield and revenue insurance for Georgia and South Carolina peaches. The premium rates for both products decrease at a decreasing rate as the mean farm-level yield increases. In general, the premium rate for revenue insurance exceeds the premium rate for yield insurance for a given coverage level and expected yield. Although the revenue and yield insurance rates differ in a statistical sense, they do not appear to differ in an economic sense except at high coverage levels for growers with very high yields.

Keywords

crop insurancepeachesrevenue insuranceyield insurance

Information

Type
Articles
Information
Journal of Agricultural and Applied Economics , Volume 32 , Issue 1 , April 2000 , pp. 123 - 132
Copyright
Copyright © Southern Agricultural Economics Association 2000

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References

Atwood, J., Baquet, A., and Watts, M.. “Rating Procedures for IP Expansion to Fall Seeded Wheat.” Mimeo, Department of Agricultural Economics and Economics, Montana State University, 1997.Google Scholar
Driscoll, J. Personal communication. Risk Management Agency, Federal Crop Insurance Corporation. Kansas City, MO. 1998.Google Scholar
Efron, B., and Tibshirani, R. J.. An Introduction to the Bootstrap. New York: Chapman and Hall, 1993.CrossRefGoogle Scholar
Federal Crop Insurance Corporation. County actuarial tables. Kansas City, MO. 1999. Distributed through web page. Available HTTP: http://www.rma.usda.gov/tools/actdoc/index.htmlGoogle Scholar
Federal Crop Insurance Corporation. Unpublished yield experience data for Georgia and South Carolina peach growers, various years.Google Scholar
Georgia Agricultural Statistics Service. Georgia Agricultural Facts. Various issues.Google Scholar
Goodwin, B., and Ker., A. “Nonparametric Estimation of Crop Yield Distributions: Implications for Rating Group-Risk Crop Insurance Contracts.” American Journal of Agricultural Economics 80(1998a):139-53.CrossRefGoogle Scholar
Goodwin, B., and Ker., A. “Revenue Insurance: A New Dimension in Risk Management.” Choices 13(1998b, Fourth Quarter):24–27.Google Scholar
Greene, W.Econometric Analysis (Third Edition). Upper Saddle River, NJ: Prentice-Hall Inc., 1997.Google Scholar
Houck, J. “The Relationship of Direct Price Flexibilities to Direct Price Elasticities,” Journal of Farm Economics 47(1965):789-92.CrossRefGoogle Scholar
Kahl, K.H.Miller, S. E., and Rathwell, P. J.. “Should Peach Crop Insurance Premium Rates in Georgia and South Carolina Depend on Average Yields”? Contributed paper, Southern Agricultural Economics Association annual meeting, Memphis, TN, 1999.Google Scholar
Kmenta, J.Elements of Econometrics (Second Edition). New York: Macmillan, 1986.Google Scholar
Maddala, G.S.Introduction to Econometrics (Second Edition). New York: Macmillan, 1992.Google Scholar
National Agricultural Statistics Service, U. S. Department of Agriculture. Noncitrus Fruits and Nuts. Washington, DC. Various issues.Google Scholar
Nuckton, C. “Demand Relationships for California Tree Fruits, Grapes, and Nuts: A Review of Past Studies.” Giannini Foundation of Agricultural Economics Special Publication 3247, Division of Agricultural Sciences, University of California, Davis, CA, 1978.Google Scholar
Offutt, S., and Lins, D.. “Income Insurance for U. S. Commodity Producers: Program Issues and Design Alternatives.” North Central Journal of Agricultural Economics 7(1985):61–69.CrossRefGoogle Scholar
Prescott, D., and Stengos, T.. “Bootstrapping Confidence Intervals: An Application to Forecasting the Supply of Pork.” American Journal of Agricultural Economics 69(1987):266-73.CrossRefGoogle Scholar
Skees, J., and Reed, M.. “Rate Making for Farm-Level Crop Insurance: Implications for Adverse Selection.” American Journal of Agricultural Economics 68(1986):653-59.CrossRefGoogle Scholar
South Carolina Agricultural Statistics Service. South Carolina Agricultural Statistics. Various issues.Google Scholar
Stata Corporation. User's Guide (Release Six). College Station, TX: Stata Press, 1999.Google Scholar