Risk Analysis Under Correlated, Non-Normal Price And Yield Probability Distributions
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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- Bruce A. Babcock & David A. Hennessy, 1996.
"Input Demand under Yield and Revenue Insurance,"
American Journal of Agricultural Economics,
Agricultural and Applied Economics Association, vol. 78(2), pages 416-427.
- Babcock, Bruce A. & Hennessy, David A., 1996. "Input Demand Under Yield and Revenue Insurance," Staff General Research Papers Archive 794, Iowa State University, Department of Economics.
- 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.
- McDonald, James B., 1989. "Partially adaptive estimation of ARMA time series models," International Journal of Forecasting, Elsevier, vol. 5(2), pages 217-230.
- 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.
- Meyer, Jack, 1977. "Choice among distributions," Journal of Economic Theory, Elsevier, vol. 14(2), pages 326-336, April.
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