The objective of this paper is to compare the accuracy of crop insurance rating methods based on historical liability and indemnity data (similar to the procedure currently used by the Risk Management Agency) and “yield distribution” approaches. Estimated rates are compared to “true”...

This article explores the impact of the likely levels of inaccuracy associated with two main types of premium estimation methods, under different sample sizes, on the actuarial performance of the US crop insurance program. The analyses are conducted under several plausible assumptions about the...

We demonstrate the use of the small-sample econometrics principles and strategies to come up with reliable yield and acreage models for policy analyses. We focus on demonstrating the importance of proper representation of systematic and random components of the model for improving forecasting...

Production function models for cotton lint yields, seed yields, turnout, and lint quality characteristics are developed for the Texas High Plains. They are used to evaluate the impacts of quality considerations and of climate/weather information on the management decisions and on the...

The distributions currently used to model and simulate crop yields are unable to accommodate a substantial subset of the theoretically feasible mean-variance-skewness-kurtosis (MVSK) hyperspace. Because these first four central moments are key determinants of shape, the available distributions...

This paper develops and applies a methodology to assess the accuracy of historical loss-cost rating procedures, similar to those used by the U.S. Department of Agriculture’s Risk Management Agency (RMA), versus alternative parametric premium estimation methods. It finds that the accuracy...

This paper estimates the costs of buying water use rights from farmers located in the Mafraq-Azraq basin in Jordan. Farmers’ water supply curve is estimated using data gathered from a contingent valuation survey. Estimation results indicate that a total supply of 29 million m3 could be...

This paper explores the impact of error-term non-normality on the performance of the normal-error Generalized Autoregressive Conditional Heteroskedastic (GARCH) model under small and moderate sample sizes. A non-normal-, asymmetric-error GARCH model is proposed, and its finite-sample performance...

This study presents a technique that can jointly model and simulate the expected values, variances, and covariances of sets of correlated time-series dependent variables that are autocorrelated and non-normal (right or left skewed and/or kurtotic). It illustrates the method by applying it to...