What is in this article?:
- Lessons from LIBOR
- Olympic average
A close examination reveals a number of structural weaknesses in the LIBOR process. One problem is that LIBOR is based on estimates, not actual transactions.
Once the quotes are compiled, LIBOR uses a trimmed mean process, in which the highest and lowest values are thrown out and the remaining values are averaged. This is sometimes called an “Olympic average” from its use in the Olympics to eliminate the impact of a biased judge on an athlete’s final score. In the case of the 3-Month US Dollar LIBOR, the four highest and four lowest rates are eliminated, with the remaining 10 quotes used to calculate the average. Eliminating the top four and bottom four quotes would be effective if there are no more than four entities with a desire to distort the average. But when all 18 banks in the survey have an incentive to report an artificially low rate, eliminating only the bottom four quotes will do little to deter manipulation.
The amount of borrowing and lending of US dollar-based funds for a 3-month term among the 18 participating banks – in other words, the actual volume of transactions underlying the LIBOR rate – is unknown, but it is likely in the tens or low hundreds of billions of dollars annually. However, the greatest impact occurs from this scandal comes from the indirect or “one-off” use of LIBOR rates to value other financial transactions. These indirect uses dwarf the volume of actual transactions: one estimate puts the amount of investments pegged to the 3-Month US Dollar LIBOR rate at $800 trillion. These indirect users who piggy-backed on transactions conducted by others are the ones who complained the loudest and longest when the distortions in the LIBOR rates were revealed.
What does all this have to do with agricultural producers? As it turns out, most prices paid and received by producers are based in some manner on “reference prices” established by someone else, not transactions in which they were direct participants and therefore contributed to the price discovery process. For example, crop prices are linked to futures prices, livestock prices are frequently tied to prices reported by USDA, and input prices are frequently based on some type of “sheet price” from a newsletter or trade publication. Some of these reference prices are quite robust and easily verified, while others are questionable at best.
When the number and size of transactions underling a reference price is relatively small, the potential for artificial distortions or other unexpected changes is much greater. Entering into any agreement to buy or sell without understanding exactly how the final price will be determined – and how the reference price is determined – can expose producers to unnecessary risks. Asking questions and doing some independent research can be useful in preventing unpleasant surprises.
Paul E. Peterson, Department of Agricultural and Consumer Economics, University of Illinois