Crop Yield Expectation Stochastic Process with Beta Distribution as Limit, A
AbstractThe modeling of price risk in the theory and practice of commodity risk management has been developed far beyond that of crop yield risk. This is in large part due to the use of plausible stochastic price processes. We use the PÃ³lya urn to identify and develop a model of the crop yield expectation stochastic process over a growing season. The process allows a role for agronomic events, such as growing degree days. The model is internally consistent in adhering to the martingale property. The limiting distribution is the beta, commonly used in yield modeling. By applying binomial tree analysis, we show how to use the framework to study hedging decisions and crop valuation.
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Bibliographic InfoPaper provided by Center for Agricultural and Rural Development (CARD) at Iowa State University in its series Center for Agricultural and Rural Development (CARD) Publications with number 09-wp501.
Date of creation: Nov 2009
Date of revision:
crop insurance; growing degree days; martingale; PÃ³lya urn; stochastic process.;
This paper has been announced in the following NEP Reports:
- NEP-AGR-2009-11-14 (Agricultural Economics)
- NEP-ALL-2009-11-14 (All new papers)
- NEP-IAS-2009-11-14 (Insurance Economics)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Bailey Norwood & Matthew C. Roberts & Jayson L. Lusk, 2004. "Ranking Crop Yield Models Using Out-of-Sample Likelihood Functions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, Agricultural and Applied Economics Association, vol. 86(4), pages 1032-1043.
- Octavio A. Ram�rez & Tanya McDonald, 2006. "Ranking Crop Yield Models: A Comment," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, Agricultural and Applied Economics Association, vol. 88(4), pages 1105-1110.
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