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Title:Evaluating yield models for crop insurance rating
Author(s):Lanoue, Christopher
Advisor(s):Sherrick, Bruce J.
Department / Program:Agr & Consumer Economics
Discipline:Agr & Consumer Economics
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):Yield distributions
Crop Insurance
Weibull Distribution
Beta Distribution
Mixture Distribution
Burr XII Distribution
Out-of-Sample Efficiency
Insurance Rating Efficiency
Abstract:Crop insurance performance and loss rates depend directly on underlying crop yield distributions. However, there still exists much debate about how to represent the underlying crop yield distributions. Using farm-level corn and soybean yields from 1972-2008, this study examines in-sample goodness-of-fit measures of both the whole distribution and the insurance tail to compare a set of flexible parametric, semi-parametric, and non-parametric distributions in a meaningful economic context. Simulations are then conducted to investigate the out-of-sample efficiency properties of several competing distributions. The results indicate that more parameterized distributional forms fit the data better in-sample, but are generally less efficient out-of-sample - and in some cases more biased - than more parsimonious forms which also fit the data adequately, such as the Weibull. The results highlight the relative advantages of alternative distributions, in terms of the bias-efficiency tradeoff in both in- and out-of-sample frameworks.
Issue Date:2010-08-20
Rights Information:Copyright 2010 Christopher Lanoue
Date Available in IDEALS:2010-08-20
Date Deposited:2010-08

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