Are Current Crop and Revenue Insurance Products Meeting the Needs of Texas Cotton Producers

An empirical procedure was developed to analyze the cost effectiveness of alternative crop insurance products in terms of increasing producer net returns and minimizing variation in net returns. Results indicate that CAT was the overwhelmingly preferred MPCI option for all scenarios. The ranking of the other MPCI options was consistently 50/100, 60/100, and 75/100 in all scenarios. The CRC options, with the exception of one scenario, ranked 50, 60, and 75 percent, respectively. Cotton production contributed an average of $5.27 billion per year to the United States economy from 1988 through 1994 (National Agricultural Statistics Service [NASS], 1999). More than 14.5 million acres of cotton were planted in the U.S. in 1999, with more than 13 million acres harvested and about 16 million bales of cotton produced. Texas accounted for about 42 percent of planted acres, about 39 percent of harvested acres, and over 31 percent of total cotton production in 1999 (Texas Agricultural Statistics Service [TASS], 2000). Cotton production, like any other agricultural enterprise, is inherently risky. Cotton producers are subject to unpredictable, random shocks, such as adverse weather, pest infestations, and other natural disasters, such as drought and flooding. Supply uncertainties, coupled with inelastic demand for many agricultural products, lead to price movements that are generally more volatile for farm products than those commonly experienced in other sectors of the economy (Goodwin and Smith, 1995). In the past, producers have relied on the federal government for protection from price and yield variability. This protection came in the form of a federal crop insurance program, ad hoc disaster payments, and deficiency payments. Deficiency payments were made when the price level of the commodity fell below the target price set by the federal government. The target price acted as a floor price, guaranteeing a level of returns per unit of a commodity. However, significant changes have occurred in U.S. farm policies. The most recent of which are embedded in the Federal Agricultural Improvement and Reform (FAIR) Act of 1996. The elimination of deficiency payment provisions by the 1996 FAIR Act has affected expected returns and the income variability faced by producers (Skees et al., 1998). The lack of deficiency payments to compensate for commodity price variability, coupled with the flexibility of producers to switch crops from year to year, have increased revenue risks for producers. Although the federal government has attempted to reduce its role in providing price and income support, there has been an increasing emphasis on crop and revenue insurance (Skees et al., 1998). Pressure to reform crop insurance products has resulted because of low participation, poor actuarial performance, and the existence of ad hoc disaster payments (Skees et al., 1998). These issues were addressed by the Crop Insurance Reform Act of 1994, which prohibits ad hoc crop disaster programs, unless the funds are appropriated from other agricultural programs. The 1994 act also directed the Federal Crop Insurance Corporation (FCIC) to develop a pilot crop insurance program to provide farmers with coverage against reduced income as a result of reduced yields and/or prices (Miller et al., 2000). Although the movement of agricultural policy in the United States toward less government involvement has left producers exposed to higher levels of production and marketing risk, there are many risk management practices that are available to producers to help substitute for government programs. Some of these practices are forward contracting, hedging with futures and options, and crop insurance. The general objective of this study was to develop and illustrate the application of an empirical procedure to evaluate the cost effectiveness of various crop and revenue insurance products as risk management tools for Texas cotton producers. Methods and Procedures Precise estimates of yield and price distributions are needed to evaluate the cost effectiveness of crop and revenue insurance products and their impacts on a farmer’s net worth. Pooled yield data was used to estimate irrigated and dryland yield distributions at the farm level in three West Texas regions (the Southern High Plains, the Northern High Plains, and the Northern Low Plains) covering thirteen counties. Farm level producer yield data were collected from the Texas Agricultural Extension Service (Fincham, 1999) and included five to ten years of producers’ yield history. The data consisted of the number of acres planted, the actual realized yield in pounds per planted acre, the location of the farm, and the farming practice (i.e., irrigated or non-irrigated). The limited number of years of farm level data available was not sufficient to precisely quantify the trend and other critical features of the yield distributions. Therefore, aggregate time series yield data (TASS, 1970-98) were used to assist in the estimation of the yield distributions and their changes through time. Price data were collected from the National Agricultural Statistics Service (NASS). The state-level data consisted of annual price data from 1934 to 1998, and were used to estimate the price distribution faced by Texas cotton producers. A multivariate parametric model, developed by Ramirez (1997) and expanded by Ramirez et al. (1999), was used to estimate the yield and price distributions. This approach estimates a multivariate, nonnormal distribution that can accurately and separately account for skewness, kurtosis, heteroscedasticity, and the correlation among the random variables of interest, irrigated and dryland cotton yields and prices, in this case. Once the parameters for the price and joint bivariate yield distributions were estimated, they were used to simulate 15,000 draws from each of these estimated distributions. This simulation technique, developed by Ramirez (1997), incorporates, when appropriate, the factors affecting the mean of the yield and price distributions through time and space, as well as heteroscedasticity, autocorrelation, right or left skewness, kurtosis, and the correlation between dryland and irrigated cotton yields. The simulated yield and price series were used to develop an empirical procedure to analyze the cost effectiveness of alternative crop insurance products in terms of increasing producer net returns and minimizing the variation in net returns. To compare different crop and revenue insurance products, net returns per planted acre were estimated over a planning horizon. Total revenue distributions were first calculated by multiplying the simulated yields by the simulated prices: