Sherrick, Bruce J.

April, 2011

By: Woodard, Joshua D.; Sherrick, Bruce J.; Schnitkey, Gary D.
This study examines the actuarial implications of the loss cost ratio (LCR) ratemaking methodology employed by the Risk Management Agency as a component of base rates for U.S. crop insurance programs, and identifies specific conditions required for the LCR methodology to result in unbiased rates when liabilities trend. Specifically, constant relative yield risk resulting in growing absolute variance through time and other restrictive requirements are required for the LCR to result in unbiased rates. These requirements are tested against a large farm-level data set for Illinois corn. Our findings indicate that the conditions required for appropriate use of the LCR methodology are violated for this high premium volume market, resulting in large implied rate biases. The process does not correct itself through time with the addition of longer rating periods as sometimes claimed. A simple correction function is suggested and demonstrated.

April, 2005

By: Diersen, Matthew A.; Sherrick, Bruce J.
Estimates of country-level loan default distributions are developed and used in a loan guarantee model to value the contingent liability of USDA's General Sales Manager (GSM) export credit guarantee portfolio. The results quantify the relationship between increasing guarantee coverage and the resulting actuarial liability to the government. Optimal coverage levels and optimal country-level allocations are determined for given policy objectives and coverage totals. Findings reveal that the government's allocation of country guarantees is risk-inefficient; and guidance is provided for making risk-efficient allocations for any program size.

July, 2002

By: Sherrick, Bruce J.
The accuracy of producers' subjective probability beliefs is examined through a survey of large cash-grain farmers in Illinois. Findings reveal that their subjective probability beliefs about important weather variables are systematically mis-calibrated. The nature and extent of differences between subjective probability beliefs and probabilities based on long-term historic weather data are shown empirically, and through fitted calibration functions. The economic significance of inaccurate subjective probability beliefs is established in the context of insurance valuation. The results demonstrate that significant errors in producers' risk assessments and insurance valuation arise as a consequence of producers' systematically inaccurate probability beliefs.