The objective of this study is to evaluate and model the risks of corn and soybean production. This study focuses on the risk of revenue variability that arises from changes in prices, yields shortfalls or both. There are several models for price and yield risk factors for corn and soybeans. For...

This research develops a mixture regression model that is shown to have advantages over the classical Tobit model in model fit and predictive tests when data are generated from a two step process. Additionally, the model is shown to allow for flexibility in distributional assumptions while...

The purpose of this study is to evaluate the risks faced by fed cattle producers. With the development of livestock insurance programs as part of the Agricultural Risk Protection Act of 2000, a thorough investigation into the probabilistic measures of individual risk factors is needed. This...

The objective of this study is to evaluate and model the yield risk associatedwith major agricultural commodities in the U.S. We are particularly concernedwith the nonstationary nature of the yield distribution, which primarily arisesbecause of technological progress and changing environmental...

This article focuses on the modeling of agricultural yield data using hierarchical Bayesian models. In recovering the generating process of these data, we consider the temporal, spatial and spatio-temporal relationships pertinent to the prediction and pricing of insurance contracts based on...

The objective of this study is to evaluate and model the spatial dependence of systemic yield risk. Various spatial autoregressive models are explored to account for county level dependence of crop yields. The results show that the time trend parameters of yields are correlated across spaces and...

This article focuses on the modeling of agricultural yield data using hierarchical Bayesian models. In recovering the generating process of these data, we consider the temporal, spatial and spatio-temporal relationships pertinent to the prediction and pricing of insurance contracts based on...

This research develops a mixture regression model that is shown to have advantages over theclassical Tobit model in model fit and predictive tests when data are generated from a two stepprocess. Additionally, the model is shown to allow for flexibility in distributional assumptions while nesting...

The objective of this study is to evaluate and model the risks of corn and soybean production. This study focuses on the risk of revenue variability that arises from changes in prices, yields shortfalls or both. There are several models for price and yield risk factors for corn and soybeans. For...