Insuring Eggs in Baskets: Should the Government Insure Individual Risks?

Abstract

The vast majority of crop and revenue insurance policies sold in the United States are single-crop policies that insure against low yields or low revenues for each crop grown on a particular farm. This practice of insuring one crop at a time runs counter to the traditional risk management practice of diversifying across several enterprises to avoid putting all of ones eggs in a single basket. This paper examines the construction of wholefarm crop revenue insurance programs to include livestock. The whole-farm insurance product covers crop revenues from corn and soybeans and livestock revenues from hog production. The results show that at coverage levels of 95 percent or lower, the fair insurance premiums for this product on a well-diversified Iowa hog farm are far lower than the fair premiums for the corn crop alone on the same farm. The calculation of premium rates for the whole-farm insurance product is derived from a method for imposing correlations first proposed by Iman and Conover in 1982. DC 20250-9410 or call (202) 720-5964 (voice and TDD). USDA is an equal opportunity provider and employer. AbstractThe vast majority of crop and revenue insurance policies sold in the United States are single-crop policies that insure against low yields or low revenues for each crop grown on a particular farm. This practice of insuring one crop at a time runs counter to the traditional risk management practice of diversifying across several enterprises to avoid putting all of ones eggs in a single basket. This paper examines the construction of whole-farm crop revenue insurance programs to include livestock. The whole-farm insurance product covers crop revenues from corn and soybeans and livestock revenues from hog production. The results show that at coverage levels of 95 percent or lower, the fair insurance premiums for this product on a well-diversified Iowa hog farm are far lower than the fair premiums for the corn crop alone on the same farm. The calculation of premium rates for the whole-farm insurance product is derived from a method for imposing correlations first proposed by Iman and Conover in 1982.

Designing a whole-farm revenue insurance for agricultural crops in Zanjan province of Iran

“…In other words, the whole farm contracts are more efficient as a risk management tools than the combination of the crop-specific contracts. This confirms the results of Hart et al (2006) that concluded the sum of the premiums for individual commodity revenues exceeds the premium for the combined coverage. It also supports the results of Bielza and Garrido (2009) that concluded applying whole farm insurance significantly reduces premiums, in addition to findings of Chalise et al (2011) and Chalise et al (2017) which found that whole farm insurance generates significant risk reduction at much lower cost than the other programs.…”

“…Meuwissen et al (2000) stated that whole-farm insurance is more attractive to the producers in comparison to other insuring products because it is convenient for optimizing the welfare of the farm family. Hart et al (2006) designed whole farm revenue insurance programs and estimated the probability density function of the prices and yields using the Monte Carlo simulation method. Their results indicated that at coverage levels of 95 % or lower, the fair insurance premiums for this type of insurance, are far lower than the fair premiums for corn alone on the same farm.…”

“…For this purpose, in the first step yield and price risk should be estimated accurately. However, the price and yields densities are not often independent (Goodwin and Ker, 2002;Hart et al, 2006). The premium rates for the whole farm revenue insurance are determined by drawing yield and price deviates from appropriately specified distributions.…”

“…Third, the procedure is applicable under any sampling method. Fourth, the moments of the marginal distributions are not influenced by the procedure (Hart et al, 2006).…”

Equilibrium pricing in electricity markets with wind power

“…For the purpose of imposing spatial correlation we employ a method that was introduced by Iman and Conover (IC) in 1982. The method is used in a large variety of applications where there is a need to generate correlated random numbers (see for example, Brus and Jansen 2004, Hart, Hayes and Babcock 2006, Maia and Neto 2004, and Wu and Tsang 2004. The technique is distribution free, preserves the exact form of the marginal distributions on the input variables and simple to use.…”