Crop Yield Distributions: A Reconciliation of Previous Research and Statistical Tests for Normality
AbstractThis 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. Copyright 2009, Oxford University Press.
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Bibliographic InfoArticle provided by Agricultural and Applied Economics Association in its journal Review of Agricultural Economics.
Volume (Year): 31 (2009)
Issue (Month): 1 ()
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- Niklaus Lehmann & Robert Finger & Tommy Klein & Pierluigi Calanca, 2013. "Sample Size Requirements for Assessing Statistical Moments of Simulated Crop Yield Distributions," Agriculture, MDPI, Open Access Journal, vol. 3(2), pages 210-220, April.
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