Crop Yield Distributions: A Reconciliation of Previous Research and Statistical Tests for Normality
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. Copyright 2009, Oxford University Press.
Volume (Year): 31 (2009)
Issue (Month): 1 ()
|Contact details of provider:|| Postal: Oxford University Press, Great Clarendon Street, Oxford OX2 6DP, UK|
Phone: (414) 918-3190
Fax: 01865 267 985
Web page: http://www.aaea.org/
More information through EDIRC
|Order Information:||Web: http://www.oup.co.uk/journals|
When requesting a correction, please mention this item's handle: RePEc:oup:revage:v:31:y:2009:i:1:p:163-182. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Oxford University Press)or (Christopher F. Baum)
If references are entirely missing, you can add them using this form.