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Risk Analysis Under Correlated, Non-Normal Price And Yield Probability Distributions

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  • Ramirez, Octavio A.
  • Sosa, Romeo
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    Abstract

    Recently developed techniques are combined for modeling mutually correlated crop yields and prices that exhibit heteroscedasticity and autocorrelation, respectively, and follow non-normal probability density functions (pdf's). The importance rigorously modeling these pdf's for financial risk analysis is illustrated through a case study of tropical agroforestry systems for coffee production.

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    File URL: http://purl.umn.edu/21888
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    Bibliographic Info

    Paper provided by American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association) in its series 2000 Annual meeting, July 30-August 2, Tampa, FL with number 21888.

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    Date of creation: 2000
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    Handle: RePEc:ags:aaea00:21888

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    Keywords: Research Methods/ Statistical Methods; Risk and Uncertainty;

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    1. Bruce A. Babcock & Joseph A. Herriges, 1994. "Input Demand Under Yield and Revenue Insurance," Center for Agricultural and Rural Development (CARD) Publications 94-wp127, Center for Agricultural and Rural Development (CARD) at Iowa State University.
    2. Anderson, Jock R., 1974. "Simulation: Methodology and Application in Agricultural Economics," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 42(01), March.
    3. McDonald, James B., 1989. "Partially adaptive estimation of ARMA time series models," International Journal of Forecasting, Elsevier, vol. 5(2), pages 217-230.
    4. Meyer, Jack, 1977. "Choice among distributions," Journal of Economic Theory, Elsevier, vol. 14(2), pages 326-336, April.
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