Hostname: page-component-78c5997874-fbnjt Total loading time: 0 Render date: 2024-11-05T12:44:38.698Z Has data issue: false hasContentIssue false
  • English
  • Français

Linkages Between Crop Insurance and Pre-Harvest Hedging

Published online by Cambridge University Press:  28 April 2015

Kevin C. Dhuyvetter  and
Terry L. Kastens
Kevin C. Dhuyvetter
Affiliation:
Department of Agricultural Economics, Kansas State University
Terry L. Kastens
Affiliation:
Department of Agricultural Economics, Kansas State University
Get access Rights & Permissions [Opens in a new window]

Abstract

The impact pre-harvest hedging and crop insurance strategies have on expected revenue and associated risk as well as how producers' risk attitudes affect optimal strategies was analyzed for Kansas wheat farms. No insurance, Catastrophic (CAT), Actual Production History (APH), and Crop Revenue Coverage (CRC) were considered. Average revenue was similar across alternatives, but APH and CRC resulted in the least income variability. Risk reduction effects of hedging were small and the advantage of CRC over APH decreases as hedging increases. This historical study provides useful information; however, if future market conditions differ significantly from the past, optimal strategies may change.

Keywords

crop insurancehedgingrevenue insurancerisk management
Type
Articles
Information
Journal of Agricultural and Applied Economics , Volume 31 , Issue 1 , April 1999 , pp. 41 - 56
Copyright
Copyright © Southern Agricultural Economics Association 1999

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Bridge Financial Data Center (CD-ROM). Bridge Financial, 20 South Wacker Drive, Suite 1810, Chicago, IL 60606-7404.Google Scholar
FAPRI. “CRC Expansion: Comparative Government Costs in a Drought Scenario.” Prepared for the Majority Staff of the Senate Committee on Agriculture, Nutrition, and Forestry. November 4, 1996.Google Scholar
Featherstone, A.M., Griebel, J.C., and Langemeier, L.N.. “A Comparison of the Farm Management Association Data to the USDA Farm Cost and Return Survey Data.” Kansas State University Department of Agricultural Economics Farm Management Newsletter, April 1992.Google Scholar
Federal Crop Insurance Corporation (FCIC), Research and Development Division, Risk Management Agency, 9435 Holmes, Kansas City, MO 64131.Google Scholar
Gallagher, P. “U.S. Soybean Yields: Estimation and Forecasting with Nonsymmetric Yields.” American Journal of Agricultural Economics 69(1987):796–803.CrossRefGoogle Scholar
Goodwin, B.K. “Premium Rate Determination in the Federal Crop Insurance Program: What Do Averages Have to Say About Risk?” Journal of Agricultural and Resource Economics 19(2): 382–395.Google Scholar
Goodwin, B.K. and Schroeder, T.C.. “Human Capital, Producer Education Programs, and the Adoption of Forward-Pricing Methods.” American Journal of Agricultural Economics 76(1994): 936–947.CrossRefGoogle Scholar
Gray, A.W., Richardson, J.W., and McClaskey, J.. “Farm-Level Impacts of Revenue Assurance.” Review of Agricultural Economics 17(1995): 171–183.CrossRefGoogle Scholar
Hart, C. and Smith, D.. “Computing Average Per Acre Indemnity Payments for Corn in Iowa.” FAPRI Working Paper 96-WP 163, August, 1996.Google Scholar
Hazell, P.B.R. and Norton, R.D. Mathematical Programming for Economic Analysis in Agriculture. New York: Macmillan Publishing Company, 1986.Google Scholar
Hennessy, D.A., Babcock, B.A., and Hayes, D.J.. “Budgetary and Producer Welfare Effects of Revenue Insurance.” American Journal of Agricultural Economics 79(1997): 1024–1034.CrossRefGoogle Scholar
Hey, J.D.Uncertainty in Microeconomics. New York: New York University Press, 1979.Google Scholar
Kansas Agricultural Statistics. “Agricultural Prices.” Topeka, KS, all monthly reports, July 1973 through July 1995. Kansas Department of Agriculture, Statistics Division. Kansas Farm Facts. Various annual issues.Google Scholar
Langemeier, L.N. “Farm Management Data Bank Documentation.” Kansas State University Department of Agricultural Economics Staff Paper, No. 95-1, August, 1994.Google Scholar
Lapan, H. and Moschini, G.. “Futures Hedging Under Price, Basis, and Production Risk.” American Journal of Agricultural Economics 76(1994):465–477.CrossRefGoogle Scholar
McKenna, C.J.The Economics of Uncertainty. New York: Oxford University Press, 1986.Google Scholar
Moss, C.B. and Shonkwiler, J.S.. “Estimating Yield Distributions with a Stochastic Trend and Non-normal Errors.” American Journal of Agricultural Economics 75(1993):1056–1062.CrossRefGoogle Scholar
Nelson, C.H. “The Influence of Distributional Assumptions on the Calculation of Crop Insurance Premia.” North Central Journal of Agricultural Economics 12(1990):71–78.CrossRefGoogle Scholar
Risk Management Agency, Actuarial Division. Personal communication.Google Scholar
Schroeder, T.C., Parcell, J.L., Kastens, T.L., and Dhuyvetter, K.C.. “Perceptions of Marketing Strategies: Producers vs. Extension Economists.” Journal of Agricultural and Resource Economics 23(July 1998):279–93.Google Scholar
Schurte, B. “The Impact of Size on Yield Variability and Crop Insurance Premiums.” Review of Agricultural Economics 18(1996):415–422.Google Scholar
Tomek, W.G. “Effects of Futures and Options Trading on Farm Incomes.” Cornell University Agricultural Economics Staff paper, 87-9 (1987).Google Scholar
U.S. Government Printing Office, 1938. “Wheat in Your Bin Every Year.” G.I.S. No. 5, October 1938.Google Scholar