The Risk Management Agency (RMA) has now concluded its price discovery period used to determined final prices and volatility factors for federally sponsored corn and soybean crop insurance products for 2013. For the majority of the Midwest, the projected price for corn is $5.65 and the volatility factor relating to the price risk is anticipated to be .20. For soybeans, the projected price is $12.87 and the volatility factor is likely to be .17. For comparison, the 2012 prices (volatility factors) were $5.68 (.22) and $12.55 (.18) for corn and soybeans, respectively.
The projected prices are used to determine the guarantee revenue indexes based on futures prices and do not reflect local basis. The projected price for corn is determined by averaging the closing December futures price during the trading days of February, and for soybeans by averaging the November futures closing prices. The volatility factors are determined by an average of the most recent five trading days' implied volatility estimates, scaled for the interval of time from now until the middle of October – the month during which average prices are used to determine harvest prices. For both corn and soybeans, the volatility factors are considerably lower than in both 2011 and 2012 which has important implications for premiums and for the value of the harvest price options embedded in many products.
Additionally, the projected prices were calculated during a month which witnessed generally falling prices for both corn and soybeans and as a result, the closing prices on the final day of trading in February (the price discovery month) were $5.57 for December corn and $12.595 for November soybeans – thus the insurance prices are higher than current trade estimates of future prices. As a result, there is a somewhat decreased likelihood that the harvest prices will exceed the projected prices compared to a year when projected prices are at or below current futures prices.
Among the other changes complicating insurance evaluation this year, the RMA modified base rates across much of the corn and soybean production region to try to move premiums and loss rates into closer congruence. Additionally, the Trend Adjusted APH Endorsement was implemented last year resulting in significant increases in many producers' APH levels, followed by very low yields in the lower and western portions of the cornbelt that negatively impacted many APH levels. Group policies likewise became more attractive in some regions that had low historic loss rates, while other areas experienced increases. The result again is that producers face a complex array of choices across products and election levels available to manage the risks associated with their crop production.
The perennial question faced at this point in the year is: How can one sensibly evaluate their crop insurance options for their own case, reflecting current insurance information and their own farm's operating conditions? The following materials provide one approach for evaluating the most important crop insurance product and election choices facing corn and soybean producers using the University of Illinois iFARM crop insurance evaluator.
The case presented is for Sangamon Co., a high yielding county in central Illinois (this case, and similar analyses for approximately 675 other counties throughout the midwest for both corn and soybeans under both basic and enterprise elections are available at the farmdoc website in the crop insurance section.
Similar patterns to these results occur with soybeans, although with more muted magnitudes, and in many locations with relatively less valuable group options. These cases and cases involving basic units are also provided at the farmdoc website for most counties covering the majority of the Corn Belt plus Maryland.
Crop insurance is increasingly viewed as providing the cornerstone for active risk management programs, and its importance is elevated in environments with higher input costs and greater margin risk. The differences in underlying rates and starting price and volatility conditions can substantially impact the relative performance of the alternatives from year to year, and across different operations within a given year. Hopefully the iFARM Crop Insurance Tools will provide farmers with insights needed to make informed crop insurance decisions most suitable for their own operations.