How high the hedge: Relationships between prices and yields in the federal crop insurance programAuthor(s): A. Ford Ramsey; Barry K. Goodwin; S. Ghosh
Source: Journal of Agricultural and Resource Economics
Publication Series: Scientific Journal (JRNL)
Station: Southern Research Station
PDF: Download Publication (6.0 MB)
The theory of the natural hedge states that agricultural yields and prices are inversely related. Actuarial rules for U.S. crop revenue insurance assume that dependence between yield and price is constant across all counties within a state and that dependence can be adequately described by the Gaussian copula.We use nonlinear measures of association and a selection of bivariate copulas to empirically characterize spatially-varying dependence between prices and yields and examine premium rate sensitivity for all corn producing counties in the United States. A simulation analysis across copula types and parameter values exposes hypothetical impacts of actuarial changes.
- You may send email to firstname.lastname@example.org to request a hard copy of this publication.
- (Please specify exactly which publication you are requesting and your mailing address.)
- We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
- This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
CitationRamsey, A. Ford; Goodwin, Barry K.; Ghosh, S. 2019. How high the hedge: Relationships between prices and yields in the federal crop insurance program. Journal of Agricultural and Resource Economics 44(2): 227-245. Online supplement added to the end of publication.
Keywordscopulas, dependence, revenue insurance, risk management
- Sustainability of corn stover harvest strategies in Pennsylvania
- Response surface methodology (RSM) to evaluate moisture effects on corn stover in recovering xylose by DEO hydrolysis
- Assessing the impacts of crop-rotation and tillage on crop yields and sediment yield using a modeling approach
XML: View XML