IDEAS home Printed from https://ideas.repec.org/p/ags/aaea12/126778.html
   My bibliography  Save this paper

Estimation of crop yield distribution and Insurance Premium using Shrinkage Estimator: A Hierarchical Bayes and Small Area Estimation Approach

Author

Listed:
  • Awondo, Sebastain Nde
  • Datta, Gauri S.
  • Ramirez, Octavio A.
  • Fonsah, Esendugue Greg

Abstract

Obtaining reliable estimates of insurance premiums is a critical step in risk sharing and risk transfer necessary to ensure solvency and continuity in crop insurance programs. Challenges encountered in the estimation include dealing with aggregation bias from using county level yield averages as well as properly accounting for spatial and temporal heterogeneity. In this study, we associate some of these challenges as classical small area estimation (SAE) problems. We employ a hierarchical Bayes (HB) SAE to obtain design consistent expected county level yields and Group Risk Plan (GRP) premiums for corm farms in Illinois using quasi-simulated data. Preliminary results show little bias (< 10%) in estimated expected county yields in several counties investigated. We found wide variation in GRP, APH and basis risk across counties for similar level of coverage and scale. Results show that farmers could lower their GRP premiums by as much as 30% by carefully choosing a coverage level and scale combination.

Suggested Citation

  • Awondo, Sebastain Nde & Datta, Gauri S. & Ramirez, Octavio A. & Fonsah, Esendugue Greg, 2012. "Estimation of crop yield distribution and Insurance Premium using Shrinkage Estimator: A Hierarchical Bayes and Small Area Estimation Approach," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 126778, Agricultural and Applied Economics Association.
  • Handle: RePEc:ags:aaea12:126778
    as

    Download full text from publisher

    File URL: http://purl.umn.edu/126778
    Download Restriction: no

    References listed on IDEAS

    as
    1. Vitor A. Ozaki & Sujit K. Ghosh & Barry K. Goodwin & Ricardo Shirota, 2008. "Spatio-Temporal Modeling of Agricultural Yield Data with an Application to Pricing Crop Insurance Contracts," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 90(4), pages 951-961.
    2. Roger Claassen & Richard E. Just, 2010. "Heterogeneity and Distributional Form of Farm-Level Yields," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 93(1), pages 144-160.
    3. Ramirez, Octavio A. & McDonald, Tanya U. & Carpio, Carlos E., 2010. "A Flexible Parametric Family for the Modeling and Simulation of Yield Distributions," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 42(02), May.
    4. Alan P. Ker & Keith Coble, 2003. "Modeling Conditional Yield Densities," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(2), pages 291-304.
    5. Bruce J. Sherrick & Fabio C. Zanini & Gary D. Schnitkey & Scott H. Irwin, 2004. "Crop Insurance Valuation under Alternative Yield Distributions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(2), pages 406-419.
    6. Wolfram Schlenker & W. Michael Hanemann & Anthony C. Fisher, 2006. "The Impact of Global Warming on U.S. Agriculture: An Econometric Analysis of Optimal Growing Conditions," The Review of Economics and Statistics, MIT Press, vol. 88(1), pages 113-125, February.
    7. Octavio A. Ramírez, 1997. "Estimation and Use of a Multivariate Parametric Model for Simulating Heteroskedastic, Correlated, Nonnormal Random Variables: The Case of Corn Belt Corn, Soybean, and Wheat Yields," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(1), pages 191-205.
    8. Sukant K. Misra & Jeannie Nelson, 2003. "Efficient Estimation of Agricultural Time Series Models with Nonnormal Dependent Variables," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(4), pages 1029-1040.
    9. Ramirez, Octavio & Colson, Greg, 2013. "Premium Estimation Inaccuracy and the Distribution of Crop Insurance Subsidies," SCC-76 Meeting, March 14-16, 2013, Pensacola, Florida 152130, SCC-76: Economics and Management of Risk in Agriculture and Natural Resources.
    10. Octavio A. Ramirez & Carlos A. Carpio, 2012. "Premium estimation inaccuracy and the actuarial performance of the US crop insurance program," Agricultural Finance Review, Emerald Group Publishing, vol. 72(1), pages 117-133, May.
    11. Richard E. Just & Rulon D. Pope, 1999. "Implications of Heterogeneity for Theory and Practice in Production Economics," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 81(3), pages 711-718.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Crop Insurance; Small area estimation; Hierarchical Bayes; Farm Management; Research Methods/ Statistical Methods; Risk and Uncertainty;

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:aaea12:126778. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (AgEcon Search). General contact details of provider: http://edirc.repec.org/data/aaeaaea.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.