Date of this Version
Cornhusker Economics, November 4, 2020
Given the immense effect of weather on agriculture, skillful weather forecasts are of importance to agricultural producers for effective decision making. Weather forecasts affect operational decisions such as whether or not to irrigate (where applicable), when to apply fertilizer, when to spray herbicide and pesticide, and certainly the timing of planting and harvesting. At the seasonal time scale, say in the spring, just before planting, weather forecasts may be used for strategic decision making on outcomes, say from preharvest hedging (hereafter referred to hedging), that will not be realized until the fall or harvest. Historically, the lack of skill in generating seasonal forecasts has led the vast majority of agricultural producers to not have enough confidence to use weather forecasts in the hedging decision. Scientific advancements improving skill and accuracy of seasonal weather forecasts in the 21st century have occurred due to a better understanding of the interplay between atmosphere, land, and oceans, as well as faster and more detailed computer analysis of weather and climate data (Benjamin et al., 2018). Yet, the adoption of weather forecasts in decision making in the agricultural sector has remained low. According to Klemm and McPherson (2018), the lack of adoption of forecasts can be attributed due in part to a lack of stakeholder relevance of the forecast information, a lack of forecast accuracy, or simply because the forecasts are too difficult to understand. The goal of this paper is to motivate the use of a modern-day weather forecast in the hedging decision. We achieve this goal by investigating how modern-day weather forecasts are established and develop a simple hedging model based on the weather forecast.