Crop Yield Distributions: A Reconciliation of Previous Research and Statistical Tests for Normality
Ardian Harri,
Cumhur Erdem,
Keith Coble and
Thomas O. Knight
Review of Agricultural Economics, 2009, vol. 31, issue 1, 163-182
Abstract:
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.
Date: 2009
References: Add references at CitEc
Citations: View citations in EconPapers (29)
Downloads: (external link)
http://hdl.handle.net/10.1111/j.1467-9353.2008.01431.x (application/pdf)
Access to full text is restricted to subscribers.
Related works:
Journal Article: Crop Yield Distributions: A Reconciliation of Previous Research and Statistical Tests for Normality (2009) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:oup:revage:v:31:y:2009:i:1:p:163-182
Ordering information: This journal article can be ordered from
https://academic.oup.com/journals
Access Statistics for this article
More articles in Review of Agricultural Economics from Agricultural and Applied Economics Association Oxford University Press, Great Clarendon Street, Oxford OX2 6DP, UK. Contact information at EDIRC.
Bibliographic data for series maintained by Oxford University Press ( this e-mail address is bad, please contact ) and Christopher F. Baum ().