University of Illinois Urbana-Champaign

Evaluating yield models for crop insurance rating

Lanoue, Christopher

Content Files
1_Lanoue_Christopher.pdf

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https://hdl.handle.net/2142/16920

Description

Title
Evaluating yield models for crop insurance rating
Author(s)
Lanoue, Christopher
Issue Date
2010-08-20T18:01:56Z
Director of Research (if dissertation) or Advisor (if thesis)
Sherrick, Bruce J.
Department of Study
Agr & Consumer Economics
Discipline
Agr & Consumer Economics
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Date of Ingest
2010-08-20T18:01:56Z
Keyword(s)
  • Yield distributions
  • Crop Insurance
  • Weibull Distribution
  • Beta Distribution
  • Mixture Distribution
  • Burr XII Distribution
  • Out-of-Sample Efficiency
  • Goodness-of-Fit
  • 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.
Graduation Semester
2010-08
Permalink
http://hdl.handle.net/2142/16920
Copyright and License Information
Copyright 2010 Christopher Lanoue

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