Are Crop Yields Normally Distributed? A Reexamination

This article demonstrates that normality test procedures that include individual detrending of short-term panel data can severely reduce the power of normality tests and strongly bias normality tests in a Type II direction. An alternative error component implicit detrending procedure is suggested that demonstrates higher power for the distributions examined. Both procedures are applied to a large data set with normality of yield residuals being rejected. Assuming normality is shown to reduce potential premium rates for a large number of producers in an existing crop insurance product.