Saying goes that a normal weather is now an average of extremes. According to NOAAb, July 2015 was the warmest month ever recorded for the globe. Growing world population which is often referred to as “Feeding Nine Billion People by 2050” is another global issue. Farming is a reliable source of food supply to feed the world but, it is also known as one of businesses to be largely exposed to such weather-related risks. Governments therefore have traditionally provided unique financial support programs for their farmers such as crop insurances in order to strengthen their food security. Such traditional crop insurances are yet recognized not to be efficient because of moral hazard or adverse selection problem under asymmetric information and are, as a result, fully or mostly subsidized. Weather derivative is one of the promising financial schemes to possibly alternate or supplement the said traditional government agriculture insurance. Most of the past studies have used a simple index based either on rainfall or temperature, summing up the weather information within the main vegetative period of a specific crop in a specific region to explain a correlation with a “crop yield”. Recent researches, however, suggest benefits to more utilize an agronomic point of view and to look into plant requirements at each critical growth stage. This paper illustrates a put option model assigning multiple weather factors to determining an amount of the index which is equivalent to an estimated yield. Challenge of this study is to incorporate local agronomists expertise and insight into a process of developing the yield estimating model and arrive to reasonable fitting. This method is demonstrated in a case study for vegetable seed production in Skagit Valley, Washington, one of the historical seed production areas in the United States.
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