# **6.  Extending Coverage to Price Risk: Crop Revenue Insurance**

Analysis of agricultural risk is usually concerned with the effects of yield and price uncertainty on revenues. Revenue insurance plans account for the risks associated with uncertain yields and prices. They are used to guarantee producers a minimum level of gross revenues. A number of revenue insurance products have been offered to the U.S. farmers since the late 1990s and have grown greatly in prominence, surpassing standard multiple peril contracts in terms of total liability in many areas for many crops.<sup>12</sup> These plans had their beginnings in crop insurance legislation in 1994 that mandated development of a cost of production plan. A private company offered an insurance scheme that would pay indemnities at harvest time prices rather than at the predicted price, which was determined prior to planting. This product was developed into a revenue insurance plan known as Crop Revenue Coverage (CRC). Indemnities under the CRC plan could be triggered by low prices, low yields, or a combination of the two. In addition, lost yields would be valued at the higher of the predicted or harvest time prices. CRC was the first form of revenue insurance and accounted for a large proportion of liability after it was introduced. Alternative forms of crop insurance were also introduced in the late 1990s. Income Protection (IP) provided a true form of revenue insurance where guarantees were based upon the product of predicted prices and yields. Revenue Assurance (RA) also provided revenue coverage. RA was later expanded to include a “harvest price option” that operated much like CRC in that lost yields were paid at the higher of the predicted or harvest time price. This form of coverage has proven to be quite popular in the U.S.

A key issue is the modeling of revenue risk. Joint distributions and accounting for correlation between two random variables must be addressed. Precise measures of yield risk (the yield density) and price risk (the price density) are first needed. However, the measure of these marginal densities is still incomplete for capturing revenue risk, as yields and prices are rarely independent. To the extent that yields are spatially correlated, yield shortfalls on an individual farm are likely to be correlated with higher prices, meaning that yields and prices tend to be negatively correlated. Any consideration of revenue risk that utilizes measures of price and yield risk must also consider the degree of correlation between yields and prices. In the case of a negative correlation between yields and prices, a “natural hedge” exists such that revenue shortfalls associated with low yields are naturally offset by higher prices. This implies lower risk and premiums for revenue coverage than would be obtained from independently insuring price and yield. Measurement of correlation may not be straightforward since annual data are used (since contracts are annual) and thus data may be limited. Correlation is also location-specific. The empirical evidence suggests that price and yield will be much more highly correlated in major growing regions than is the case as one moves outside of such regions. The U.S. Revenue Assurance plan adopted an innovative parametric assumption when modeling revenue risks. Insurance rates for a particular level of coverage from the standard yield crop insurance program are used as a base measure of risks. A beta distribution is assumed to be appropriate for yields. Using assumptions about the minimum and maximum possible yields, the parameters of the beta function are first estimated. This

> 12 In 2003, revenue insurance products represented about 60% of total crop insurance premium volume and about 55% of total acres insureds (RMA 2004).

26