The Supplemental Coverage Option (SCO), Stacked Income Protection Program (STAX) insurance and county Agricultural Risk Coverage (ARC) programs in the new farm bill are novel risk protection products. All three cover a band of shallow losses and leave the producer exposed to more severe losses unless otherwise protected by crop insurance or by some other means. Shallow loss programs are new, but most people understand the concept of layering risk protection. What is less clear is how well people can evaluate county- versus farm-triggered programs. County-triggered programs are not new. They have been around for decades in the form of area coverage insurance. This type of insurance is currently known as Area Risk Protection Insurance (ARPI) and was formerly called the Group Risk Plan (GRP) and Group Risk Income Protection (GRIP). ARPI is a county-triggered alternative to farm-triggered insurance whereas STAX, SCO, and ARC are supplements to farm-triggered insurance (e.g., Yield Protection and Revenue Protection). Over the years we have probably studied and evaluated area risk protection products as much as anybody. So here are a few pointers.
- For an area triggered program to exist, county yields must be estimated and reported. In the past ARPI programs have been based solely on NASS county yield estimates. A historical series is used to predict expected yield and an actual yield is necessary to determine actual yield (or revenue) shortfalls in the insured year. NASS does not report county yields for every commodity in every county. They are unlikely to report in counties where the commodity is grown on relatively few acres and/or where few farms produce the commodity. To increase the availability of STAX and SCO it is likely that RMA will, at least in some crops/areas, use aggregated yield reports from farm-triggered crop insurance policies to construct county yields. It is less clear what FSA will use for ARC calculations. The bottom line is no county yield equals no program.
- Risk protection from area products all depends on correlation. Correlation is a statistical concept that simply means, two variables are related to each other rather than independent. For area shallow loss programs, this may be translated to, “To what degree does county revenue go up (or down) when my farm revenue goes up (or down). What we find is that this relationship is driven by the farm-county yield relationship. Typically county yield and farm yield move up and down together, but not perfectly. Further we find wide differences across farms in the relationship between farm yield and county yield. Think of a farm using typical production practices on the predominant soil type in the center of a county versus a farm using an atypical practice on a less common soil type at the edge of the county. The correlation of farm-county yields will likely be less for the atypical farm and a county triggered program will provide poorer risk protection. Some have suggested that with the availability of county-triggered shallow loss products, growers should reduce the coverage level on their underlying farm-triggered insurance. Before making this decision growers should think very carefully about how correlated their yields are with the county yield. Likewise, a number of shallow loss “decision aids” are becoming available and more will likely follow. Growers should determine whether these decision aids allow for differences across farms in the correlation between farm yield and county yield. Ideally they would also help in measuring that correlation. Unfortunately, this is not that easy to do and many of the decision aids we have seen implicitly assume that farm-yield and county-yield are independent. Growers should be aware that any decision aid that does not adequately address correlation is likely to provide erroneous guidance on decisions about shallow loss programs.
- What is not very important is whether your average yield is higher or lower than the county average. With both farm-triggered crop insurance products and county-triggered shallow loss programs, payments occur when the realized percentage shortfall exceeds the percentage deductible. The percentage deductible is just 100% minus the coverage level (thus a crop insurance policy with a 75% coverage level has a 25% deductible). The percentage shortfall and percentage deductible are both calculated relative to the expected yield or revenue. For county-triggered programs it doesn’t really matter whether your excepted farm yield is higher or lower than the expected county yield. What matters is how closely the percentage shortfall on your farm matches with the percentage shortfall at the county level. If the county experiences a 25% revenue shortfall and your farm also experiences a 25% revenue shortfall then the county-triggered program should do a nice job of covering your losses. However, if your revenue falls 25% but the county revenue only falls 15% you will not be fully covered.
- County yields are less variable than the average variability of farms in the county. This is the result of the county yield being an average of all the farms in a county. Past research typically finds the average farm is about 30% riskier than the county in which it resides. What does this mean for STAX, SCO, and ARC? It means that, all else equal, a layer of county-triggered coverage will pay less than the same layer of farm-triggered coverage for the typical farm. This is actually the motivation behind the scale option in ARPI and STAX products.
- Get ready for differing USDA estimates of county yields. FSA, RMA, and NASS may each use different data and different procedures for estimating realized county yields. Thus, it is quite possible that these various USDA agencies will generate different estimates of the realized county yield in a given year and these different estimates will be used to determine payments for different programs. If that seems strange, know that the 2014 Farm Bill did not define how these county yields would be developed. Good luck to the USDA officials who have to explain the differences.
Recent Comments