IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this article or follow this journal

Rating Crop Insurance Policies with Efficient Nonparametric Estimators that Admit Mixed Data Types

  • Racine, Jeffrey S.
  • Ker, Alan P.

The identification of improved methods for characterizing crop yield densities has experienced a recent surge in activity due in part to the central role played by crop insurance in the Agricultural Risk Protection Act of 2000 (estimates of yield densities are required for the determination of insurance premium rates). Nonparametric kernel methods have been successfully used to model yield densities; however, traditional kernel methods do not handle the presence of categorical data in a satisfactory manner and have therefore tended to be applied on a county-by-county basis. By utilizing recently developed kernel methods that admit mixed data types, we are able to model the yield density jointly across counties, leading to substantial finite sample efficiency gains. Findings show that when we allow insurance companies to strategically reinsure with the government based on this novel approach they accrue significant rents.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://purl.umn.edu/10146
Download Restriction: no

Article provided by Western Agricultural Economics Association in its journal Journal of Agricultural and Resource Economics.

Volume (Year): 31 (2006)
Issue (Month): 01 (April)
Pages:

as
in new window

Handle: RePEc:ags:jlaare:10146
Contact details of provider: Web page: http://waeaonline.org/

More information through EDIRC

No references listed on IDEAS
You can help add them by filling out this form.

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:ags:jlaare:10146. 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: (AgEcon Search)

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.