Arizona State and Local Government Documents Collection

Proposals for reform of the federal multiple-peril crop insurance program for specialty crops seek to change fees for catastrophic insurance from a nominal fifty-dollar per contract registration fee to an actuarially sound premium. Growers argue that this would cause a significant reduction in participation rates, thus impeding the program’s goals of eventually obviating the need for ad hoc disaster payments and worsening the actuarial soundness of the program. The key policy issue is, therefore, empirical one - whether the demand for specialty crop insurance is elastic or inelastic. Previous studies of this issue using either grower or county-level field crop data typically treat the participation problem as either a discrete insure / don’t insure decision or aggregate these decisions to a continuous participation rate problem. However, a grower’s problem is more realistically cast as one of simultaneously making a coverage level / insurance participation decision. Because the issue at hand considers a significant price increase for only one coverage level (50%), differentiating between these decisions is necessary both from an analytical and econometric standpoint. To model this decision, the paper develops a two-stage estimation procedure based on Lee’s multinomial logit-OLS selection framework. This method is applied to a county-level panel data set consisting of eleven years of the eleven largest grape-growing counties in California. Results show that growers choose among coverage levels based upon expected net premiums and the variance of these returns, as well as the first two moments of expected market returns. At the participation-level, the mean and variance of indemnities are also important, as are several variables measuring the extent of self-insurance, such as farm size, enterprise diversity, or farm income. The results also show that the elasticity of 50% coverage insurance is elastic, suggesting that premium increases may indeed worsen the actuarial soundness of the program. These increases will also cause a significant adjustment of growers among coverage levels.

This paper presents a general method for pricing weather derivatives. Specification tests find that a temperature series for Fresno, California follows a mean-reverting Brownian motion process with discrete jumps and ARCH errors. Based on this process, we define an equilibrium pricing model for cooling degree day weather options. Comparing option prices estimated with three methods: a traditional burn-rate approach, a Black-Scholes-Merton approximation, and an equilibrium Monte Carlo simulation reveals significant differences. Equilibrium prices are preferred on theoretical grounds, so are used to demonstrate the usefulness of weather derivatives as risk management tools for California specialty crop growers.