EconPapers    
Economics at your fingertips  
 

Modeling Conditional Yield Densities

Alan Ker () and Keith Coble ()

American Journal of Agricultural Economics, 2003, vol. 85, issue 2, 291-304

Abstract: Given the increasing interest in agricultural risk, many have sought improved methods to characterize conditional crop-yield densities. While most have postulated the Beta as a flexible alternative to the Normal, others have chosen nonparametric methods. Unfortunately, yield data tends not to be sufficiently abundant to invalidate many reasonable parametric models. This is problematic because conclusions from economic analyses, which require estimated conditional yield densities, tend not to be invariant to the modeling assumption. We propose a semiparametric estimator that, because of its theoretical properties and our simulation results, enables one to empirically proceed with a higher degree of confidence. Copyright 2003, Oxford University Press.

Date: 2003
References: Add references at CitEc
Citations: View citations in EconPapers (56) Track citations by RSS feed

Downloads: (external link)
http://hdl.handle.net/10.1111/1467-8276.00120 (application/pdf)
Access to full text is restricted to subscribers.

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:oup:ajagec:v:85:y:2003:i:2:p:291-304

Access Statistics for this article

American Journal of Agricultural Economics is currently edited by Madhu Khanna, Brian E. Roe, James Vercammen and JunJie Wu

More articles in American Journal of Agricultural Economics from Agricultural and Applied Economics Association Contact information at EDIRC.
Bibliographic data for series maintained by Oxford University Press () and Christopher F. Baum ().

 
Page updated 2021-06-15
Handle: RePEc:oup:ajagec:v:85:y:2003:i:2:p:291-304