Rate Making for Farm‐Level Crop Insurance: Implications for Adverse Selection

Abstract

This research identifies two problems in the new Federal Crop Insurance that may cause adverse selection: (a) the relationship between rate making and expected yields for individual farmers, and (b) the bias introduced in coverage protection when trends are not used to establish expected yields. A theoretical investigation using the normality assumption demonstrates the potential severity of these problems, and empirical results from farm‐level data lend further support. As crop insurance changes to individualized methods of protection, these issues will be particularly important for developing rates.

Evaluation of the reference yield calculation method in crop insurance

“…4. The assumption of riskiness (and, consequently, rates) having a negative relationship with average yield is supported by previous research (see Skees and Reed, 1986;Goodwin, 1994). However, Goodwin also makes an argument that this relationship may be tenuous, with substantial variation among farms.…”

Crop Insurance as a Tool for Price and Yield Risk Management

“…Moral Hazard • Nelson and Loehrnan ( 1987) • Just and Calvin (1993b) • Chambers ( 1989) • V ercammen and van Kooten ( 1994) • Horowitz and Lichtenberg (1993) • Goodwin ( 1996) • Rarnaswami (1993) • Hennessy ( 1996) • Quiggin, Karagiannis, andStanton ( 1993) • Coble, Knight, Pope, and Williams ( 1997) • Wu (1999) Adverse Selection • Ahsan, Ali, and Kurian (1982) • Luo, Skees, and Marchant (1994) • Skees and Reed ( 1986) • Ker and McGowan (2000) • Nelson and Loehrnan (1987) • Coble (1999) • Goodwin (1994) • Just, Calvin, and Quiggin (1999) …”

Crop Insurance Premium Ratemaking Based on Survey Data: A Case Study from Dingxing County, China

“…This study explores a new ratemaking approach based on survey data. Different from existing studies, this study focuses on the characteristic yields of long-term yield rather than yield figures of specific years as reported by farmers in some existing pricing systems (Skees and Reed 1986;Woodard et al 2011). Although both types of information are from farmers' recollection and can hardly be ''exact,'' characteristic information is more reliable than yields of specific years because it captures the feature of yield distribution (Gong et al 2013).…”

“…Botts and Boles (1958) assumed normal distribution of farm yields around the county average yield with a certain standard deviation. The method was challenged because of its normal distribution assumption (Nelson 1990) and constant deviation (Skees and Reed 1986). Also, the relationship between regional yield and individual farm yields is very complicated (Wang and Zhang 2003).…”