Hostname: page-component-586b7cd67f-2plfb Total loading time: 0 Render date: 2024-11-23T23:03:12.987Z Has data issue: false hasContentIssue false
  • English
  • Français

Can Crop Insurance Premiums Be Reliably Estimated?

Published online by Cambridge University Press:  15 September 2016

Octavio A. Ramirez ,
Carlos E. Carpio  and
Roderick M. Rejesus
Octavio A. Ramirez
Affiliation:
Department of Agricultural and Applied Economics at the University of Georgia, Athens, Georgia
Carlos E. Carpio
Affiliation:
Department of Applied Economics and Statistics at Clemson University, Clemson, South Carolina
Roderick M. Rejesus
Affiliation:
Department of Agricultural and Resource Economics at North Carolina State University, Raleigh, North Carolina
Get access

Abstract

This paper develops and applies a methodology to assess the accuracy of historical loss-cost rating procedures, similar to those used by the U.S. Department of Agriculture's Risk Management Agency (RMA), versus alternative parametric premium estimation methods. It finds that the accuracy of loss-cost procedures leaves much to be desired, but can be markedly improved through the use of alternative methods and increased farm-level yield sample sizes. Evidence suggests that the high degree of inaccuracy in crop insurance premium estimations through historical loss-cost procedures identified in the paper might be a major factor behind the need for substantial government subsidies to keep the program solvent.

Keywords

agricultural subsidiescrop insurance premium estimationloss-cost proceduresRisk Management Agency
Type
Contributed Papers
Information
Agricultural and Resource Economics Review , Volume 40 , Issue 1 , April 2011 , pp. 81 - 94
Copyright
Copyright © 2011 Northeastern Agricultural and Resource Economics Association 

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

Barnett, B.J. 2000. “The U.S. Federal Crop Insurance Program.” Canadian Journal of Agricultural Economics 48(4): 539–551.Google Scholar
Carriquiry, M.A., Babcock, B.A., and Hart, C.E. 2008. “Using a Farmer's Beta for Improved Estimation of Expected Yields.” Journal of Agricultural and Resource Economics 33(1): 52–68.Google Scholar
Coble, K.H., Knight, T.O., Goodwin, B.K., Miller, M.F., and Rejesus, R.M. 2009. “A Comprehensive Review of the RMA APH and COMBO Rating Methodology: Draft Final Report.” Actuarial publication submitted to the USDA Risk Management Agency. Available at http://www.rma.usda.gov/pubs/2009/comprehensivereview.pdf (accessed Fall 2009).Google Scholar
Goodwin, B.K. 1994. “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
Harri, A., Coble, K.H., Erdem, C., and Knight, T.O. 2005. “Crop Yield Normality: A Reconciliation of Previous Research.” Working paper, Department of Agricultural Economics, Mississippi State University, Starkville, MS.Google Scholar
Harwood, J., Heifner, R., Coble, K., Perry, J., and Somwaru, A. 1999. “Managing Risk in Farming: Concepts, Research, and Analysis.” Agricultural Economics Report No. 774, Economic Research Service, U.S. Department of Agriculture, Washington, D.C.Google Scholar
Johnson, N.L. 1949. “System of Frequency Curves Generated by Method of Translation.” Biometrika 36(1/2): 149–176.Google Scholar
Ker, A.P., and Coble, K. 2003. “Modeling Conditional Yield Densities.” American Journal of Agricultural Economics 85(2): 291–304.Google Scholar
Ker, A.P., and Goodwin, B.K. 2000. “Nonparametric Estimation of Crop Insurance Rates Revisited.” American Journal of Agricultural Economics 82(2): 463–478.Google Scholar
Knight, T.O. 2000. “Examination of Appropriate Yield Span Adjustments by Crop and Region.” Report prepared for the Economic Research Service, U.S. Department of Agriculture, Washington, D.C.Google Scholar
Lu, Y., Ramirez, O.A., Rejesus, R.M., Knight, T.O., and Sherrick, B.J. 2008. “Empirically Evaluating the Flexibility of the Johnson Family of Distributions: A Crop Insurance Application.” Agricultural and Resource Economics Review 37(1): 79–91.Google Scholar
Milliman and Robertson, Inc. 2000. “Actuarial Documentation of Multiple Peril Crop Insurance Ratemaking Procedures.” Consulting report prepared for the Risk Management Agency, U.S. Department of Agriculture, Kansas City, MO.Google Scholar
Nelson, C.H., and Preckel, P.V. 1989. “The Conditional Beta Distribution as a Stochastic Production Function.” American Journal of Agricultural Economics 71 (2): 370–378.CrossRefGoogle Scholar
Ramirez, O.A. 1997. “Estimation and Use of a Multivariate Parametric Model for Simulating Heteroskedastic, Correlated, Non-Normal Random Variables: The Case of Corn-Belt Corn, Soybeans and Wheat Yields.” American Journal of Agricultural Economics 79(1): 191–205.Google Scholar
Ramirez, O.A., and McDonald, T. 2006a. “Ranking Crop Yield Models: A Comment.” American Journal of Agricultural Economics 88(4): 1105–1110.Google Scholar
Ramirez, O.A., and McDonald, T. 2006b. “The Expanded and Re-Parameterized Johnson System: A Most Flexible Crop-Yield Distribution Model.” Paper presented at the annual meetings of the American Agricultural Economics Association, Long Beach, CA (July 23–26, 2006). Available at http://agecon.lib.umn.edu/ (accessed Fall 2009).Google Scholar
Ramirez, O.A., McDonald, T.U., and Carpio, C.E. 2010. “A Flexible Parametric Family for the Modeling and Simulation of Yield Distributions.” Journal of Agricultural and Applied Economics 42(2): 1–17.Google Scholar
Ramirez, O.A., Misra, S.K., and Field, J.E. 2003. “Crop Yield Distributions Revisited.” American Journal of Agricultural Economics 85(1): 108–120.CrossRefGoogle Scholar
Rejesus, R.M., Coble, K.H., Knight, T.O., and Jin, Y. 2006. “Developing Experience-Based Premium Discounts in Crop Insurance.” American Journal of Agricultural Economics 88(2): 409–419.Google Scholar
Sherrick, B.J., Zanini, F.C., Schnitkey, G.D., and Irwin, S.H. 2004. “Crop Insurance Valuation Under Alternative Yield Distributions.” American Journal of Agricultural Economics 86(2): 406–419.CrossRefGoogle Scholar
Skees, J.R., and Reed, M.R. 1986. “Rate-Making and Farm-Level Crop Insurance: Implications for Adverse Selection.” American Journal of Agricultural Economics 68(3): 653–659.CrossRefGoogle Scholar
Taylor, C.R. 1990. “Two Practical Procedures for Estimating Multivariate Non-Normal Probability Density Functions.” American Journal of Agricultural Economics 72(1): 210–217.Google Scholar