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

The Value Of Enso Information To Agriculture: Consideration Of Event Strength And Trade

  • Chen, Chi-Chung
  • McCarl, Bruce A.

The agricultural value of El Nino-Southern Oscillation (ENSO) phase knowledge is measured in a value-of-information framework using economic models. We examine the value of considering the full distribution of ENSO phase strength effects as opposed to average ENSO phase strength effects, as well as the implications of considering ENSO impacts on the rest of the world (ROW). A stochastic U.S. agricultural sector model linked with a global trade model is used to assess the value of ENSO phase information. When the full distribution of ENSO phase strength is considered, the value of phase information increases twofold with respect to the average ENSO effects.

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/30887
Download Restriction: no

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

Volume (Year): 25 (2000)
Issue (Month): 02 (December)
Pages:

as
in new window

Handle: RePEc:ags:jlaare:30887
Contact details of provider: Web page: http://waeaonline.org/

More information through EDIRC

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as in new window
  1. Lambert, David K. & McCarl, Bruce A. & He, Quifen & Kaylen, Michael S. & Rosenthal, Wesley & Chang, Ching-Cheng & Nayda, W.I., 1995. "Uncertain Yields In Sectoral Welfare Analysis: An Application To Global Warming," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 27(02), December.
  2. Spreen, Thomas H., 2006. "Price Endogenous Mathematical Programming Models and Trade Analysis," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 38(02), August.
  3. James W. Mjelde & Harvey S.J. Hill & John F. Griffiths, 1998. "A Review of Current Evidence on Climate Forecasts and Their Economic Effects in Agriculture," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(5), pages 1089-1095.
Full references (including those not matched with items on IDEAS)

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:30887. 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.