Crop Yield Distributions: A Reconciliation of Previous Research and Statistical Tests for Normality
Crop Yield Distributions: A Reconciliation of Previous Research and Statistical Tests for Normality
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作物产量分布：先前研究与正态性统计检验的协调
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发表时间：
2009
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影响因子：
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通讯作者：
T. Knight
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作者：
Ardian Harri;C. Erdem;Keith H. Coble;T. Knight
这项研究重新审视了大量但不确定的关于作物产量分布的研究。使用3,852种作物/县组合的竞争技术，我们可以调和以前研究中的一些不一致之处。我们研究线性，多项式和ARIMA趋势模型。进行正态性检验，使用可实施的R检验和多变量检验来解释空间相关性。实证结果表明，收益率的随机趋势的支持有限。结果还表明，正态拒绝率取决于趋势规格。玉米带玉米和大豆的产量是负偏态的，而随着人们远离玉米带，它们往往会变得更加正常。
This study revisits the large but inconclusive body of research on crop yield distributions. Using competing techniques across 3,852 crop/county combinations we can reconcile some inconsistencies in previous studies. We examine linear, polynomial, and ARIMA trend models. Normality tests are undertaken, with an implementable R-test and multivariate testing to account for spatial correlation. Empirical results show limited support for stochastic trends in yields. Results also show that normality rejection rates depend on the trend specification. Corn Belt corn and soybeans yields are negatively skewed while they tend to become more normal as one moves away from the Corn Belt.