A spatial Bayesian approach to weather derivatives
AbstractPurpose – While the demand for weather-based agricultural insurance in developed regions is limited, there exists significant potential for the use of weather indexes in developing areas. The purpose of this paper is to address the issue of historical data availability in designing actuarially sound weather-based instruments. Design/methodology/approach – A Bayesian rainfall model utilizing spatial kriging and Markov chain Monte Carlo techniques is proposed to estimate rainfall histories from observed historical data. An example drought insurance policy is presented where the fair rates are calculated using Monte Carlo methods and a historical analysis is carried out to assess potential policy performance. Findings – The applicability of the estimation method is validated using a rich data set from Iowa. Results from the historical analysis indicate that the systemic nature of weather risk can vary greatly over time, even in the relatively homogenous region of Iowa. Originality/value – The paper shows that while the kriging method may be more complex than competing models, it also provides a richer set of results. Furthermore, while the application is specific to forage production in Iowa, the rainfall model could be generalized to other regions by incorporating additional climatic factors.
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Bibliographic InfoArticle provided by Emerald Group Publishing in its journal Agricultural Finance Review.
Volume (Year): 70 (2010)
Issue (Month): 1 (May)
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Other versions of this item:
- Paulson, Nicholas D. & Hart, Chad E. & Hayes, Dermot J., 2010. "A Spatial Bayesian Approach to Weather Derivatives," Staff General Research Papers 31339, Iowa State University, Department of 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.:
- Gautam, Madhur & Hazell, Peter & Alderman, Harold, 1994. "Rural demand for drought insurance," Policy Research Working Paper Series 1383, The World Bank.
- Chad E. Hart & Bruce A. Babcock & Dermot J. Hayes, 2001.
"Livestock Revenue Insurance,"
Center for Agricultural and Rural Development (CARD) Publications
99-wp224, Center for Agricultural and Rural Development (CARD) at Iowa State University.
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- Jerry R. Skees, 2008. "Challenges for use of index-based weather insurance in lower income countries," Agricultural Finance Review, Emerald Group Publishing, vol. 68(1), pages 197-217, September.
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