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An Analysis Of The Impact Of Enso (El Nino/Southern Oscillation) On Global Crop Yields

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  • Ferris, John N.

Abstract

Forecasts of global crop yields prior to planting have generally been single values, based on entirely past trends. Regression analysis testing a combination of data from ENSO (El Nino/Southern Oscillation) and ARMA models suggests that yield forecasting errors can be reduced, generating more normal distributions of these errors.

Suggested Citation

  • Ferris, John N., 1999. "An Analysis Of The Impact Of Enso (El Nino/Southern Oscillation) On Global Crop Yields," 1999 Annual meeting, August 8-11, Nashville, TN 21517, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    • Handle: RePEc:ags:aaea99:21517
    DOI: 10.22004/ag.econ.21517
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    References listed on IDEAS

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    1. Richard M. Adams & Kelly J. Bryant & Bruce A. Mccarl & David M. Legler & James O'Brien & Andrew Solow & Rodney Weiher, 1995. "Value Of Improved Long‐Range Weather Information," Contemporary Economic Policy, Western Economic Association International, vol. 13(3), pages 10-19, July.
    2. Jarque, Carlos M. & Bera, Anil K., 1980. "Efficient tests for normality, homoscedasticity and serial independence of regression residuals," Economics Letters, Elsevier, vol. 6(3), pages 255-259.
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    Cited by:

    1. Shu-Ling Chen & Yu-Lieh Huang, 2014. "Actuarial Implications Of Structural Changes In El Niño-Southern Oscillation Index Dynamics," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 9(02), pages 1-20.

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