Market-based methods for monetizing uncertainty reduction

被引:4
作者
Cooke R. [1 ]
Golub A. [2 ]
机构
[1] Resorses for the Future, Washington, DC
[2] American University, Washington, DC
基金
美国国家航空航天局;
关键词
Bachelier formula; Black–Scholes-Merton model; Options pricing; SMAP; Value of information;
D O I
10.1007/s10669-019-09748-w
中图分类号
学科分类号
摘要
New measurement systems are often expensive and need a solid economic justification. Traditional tools based on the value of information are sometimes difficult to apply. When risks are traded in a market, it may be possible to use market instruments to monetize the reductions in uncertainty. This paper illustrates such market-based methods with a satellite system designed to reduce uncertainty in predicting soil moisture in the USA. Soil moisture is a key variable in managing agricultural production and predicting crop yields. Using data on corn and soybean futures, we find that a 30% reduction in the weather-related component of uncertainty in corn and soybean futures pricing yields a yearly US consumer surplus of $1.44 billion. The total present value of information from the satellite system for the USA—calculated with a 3% discount rate—is about $22 billion, assuming the system is in operation for 20 years. The global value of the improvements in weather forecasting could be $63 billion. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.
引用
收藏
页码:3 / 13
页数:10
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