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A Density‐Ratio Model of Crop Yield Distributions
Author(s) -
Yvette Zhang Yu
Publication year - 2017
Publication title -
american journal of agricultural economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.949
H-Index - 111
eISSN - 1467-8276
pISSN - 0002-9092
DOI - 10.1093/ajae/aax021
Subject(s) - crop insurance , estimator , yield (engineering) , monte carlo method , poisson distribution , density estimation , distortion (music) , probability density function , transformation (genetics) , statistics , poisson regression , econometrics , mathematics , computer science , agriculture , ecology , amplifier , computer network , materials science , biochemistry , chemistry , population , bandwidth (computing) , demography , sociology , gene , metallurgy , biology
This paper proposes a density ratio estimator of crop yield distributions, wherein the number of observations for individual distributions is often quite small. The density ratio approach models individual densities as distortions from a common baseline density. We introduce a probability integral transformation to the density ratio method that simplifies the modeling of distortion functions. We further present an implementation approach based on the Poisson regression, which facilitates model estimation and diagnostics. Monte Carlo simulations demonstrate good finite sample performance of the proposed method. We apply this method to estimate the corn yield distributions of ninety‐nine Iowa counties, and to calculate crop insurance premiums. Lastly, we illustrate that we can employ the proposed method to effectively identify profitable insurance policies.