Masters Theses

Date of Award

8-1998

Degree Type

Thesis

Degree Name

Master of Science

Major

Agricultural Economics

Major Professor

James A. Larson

Committee Members

Jeffrey Stokes, Roland Roberts, Burton English

Abstract

Tennessee corn producers may experience increased income volatility due to recent changes in federal government agricultural policies. Consequently, these farmers need information about the expected value and variability of net revenues for alternative crop insurance, futures hedging, and put option strategies to manage risk. The objectives of this study were 1) to evaluate how traditional hedging strategies, existing crop insurance programs, and new income protection strategies affect the expected value and variability of net revenue for a com enterprise in West Tennessee; and 2) to identify from the traditional and new income protection alternatives, the risk - preferred strategies for different levels of farmer risk aversion behavior.

Stochastic simulation and stochastic dominance methods were used to achieve the objectives of the study. Corn yields for Obion County, Tennessee and November cash prices for the Northwest Tennessee market were randomly simulated along with futures prices in November and February. Crop insurance strategies evaluated were Crop Revenue Coverage (CRC), Multiple Peril Crop Insurance (MPCI), and Revenue Assurance (RA) were evaluated in conjunction with futures hedges and put options. Twenty simulations of 192 observations each were generated from random draws using a lognormal distribution. The yield and price data used to specify the expected value, variance, and covariance relationships in the model were for the 1988 through 1994 time period. Premiums for the insurance products were quoted directly from private insurance agents for the 1997 crop year. Fixed equipment and labor costs as well as variable and overhead expenses for 1997 were also subtracted from the simulated gross revenue.

The degree of accuracy for the simulated mean of net revenue as compared to the expected mean of net revenue was calculated in the form of a confidence interval. The simulated net revenue series for each income protection strategy was analyzed in terms of the tradeoffs among expected net revenues, variance of net revenues, and minimum net revenues averaged across twenty simulations. Probabilities of achieving various rates of return on investment were evaluated for each alternative income protection strategy. Simulated net revenue distributions (CDF's) for each strategy were analyzed using first degree stochastic dominance and second-degree stochastic dominance criteria.

The top five strategies in order of descending mean net revenue were; (1) futures hedge on 100 percent of the historical yield average, (2) futures hedge on 50 percent of the historical yield average (3) combination of the 100 percent futures hedge and MPCI with 65% yield coverage at $2.45^ushel, (4) no crop insurance or futures hedging (cash market), and (5) combination of 100 percent futures hedge and MPCI with 70 percent coverage at $2.45/bushel. Producers interested in maximizing profit would not use crop insurance. In general, none of the crop insurance or hedging strategies were very effective in reducing the variability of net revenues and the relative riskiness when compared with not using any yield or price protection. However, RA at the 75 percent coverage level was the most effective strategy in setting a floor on the minimum value of net revenue. As a consequence, extremely risk averse producers may prefer a RA strategy as a way to manage income risk. Moreover, the cash market, RA, CRC, and MPCI strategies were the most likely to cover all of the variable and fixed costs of production in the simulation. The strategies most likely to be in the second-degree stochastic dominance efficient set were: (1) the cash market strategy, (2) RA at the 75 percent coverage level, (3) 100 percent futures hedge on average production, and (4) 50 percent futures hedge on average production. These strategies are risk efficient for risk neutral and risk averse decision makers.

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