Aggregate data are commonly used to determine returns to storage. However, recent studies have shown that aggregating data may lead to underestimated returns. This article compares aggregate and elevator data from Oklahoma to determine if aggregate data underestimate returns. We find no difference between the mean returns estimated with aggregate data and the mean returns estimated with transaction level data from grain elevators in Oklahoma.

Key Words: aggregate data, data collection, information loss, returns to storage

JEL Classifications: Q13

There has been a long debate in both finance and agricultural economics literature as to when it pays to store grain (i.e. Chang; Musser, Patrick, ...

Related newspaper, magazine, and journal articles:

;

See all results. Or, try our Advanced Search.

We're searching over:

• 60 million articles
• 3,500 publications