Modeling Crop Yield Distributions from Small Samples

Bharat Mani Upadhyay and Elwin G. Smith

No 34161, Annual Meeting, 2005, July 6-8, San Francisco, CA from Canadian Agricultural Economics Society

Abstract: Accurately modeling crop yield distributions is important for estimation of crop insurance premiums and farm risk-management decisions. A major challenge in the modeling has been due to small sample size. This study evaluated potentials of L-moments, a recent concept in mathematical statistics, in modeling crop yield distribution. Five candidate distributions were ranked for describing the wheat yields. The selected distribution was robust for small sample and was invariant to de-trending. The result was consistent with that from the maximum likelihood and goodness-of-fit method.

Keywords: Crop; Production/Industries (search for similar items in EconPapers)
Pages: 23
Date: 2005
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://ageconsearch.umn.edu/record/34161/files/sp05up01.pdf (application/pdf)

Related works:
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:ags:caes05:34161

DOI: 10.22004/ag.econ.34161

Access Statistics for this paper

More papers in Annual Meeting, 2005, July 6-8, San Francisco, CA from Canadian Agricultural Economics Society Contact information at EDIRC.
Bibliographic data for series maintained by AgEcon Search ().