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Parametric Modeling And Simulation Of Joint Price-Production Distributions Under Non-Normality, Autocorrelation And Heteroscedasticity: A Tool For Assessing Risk In Agriculture

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  • Ramirez, Octavio A.

Abstract

This study presents a way to parametrically model and simulate multivariate distributions under potential non-normality, autocorrelation and heteroscedasticity and illustrates its application to agricultural risk analysis. Specifically, the joint probability distribution (pdf) for West Texas irrigated cotton, corn, sorghum, and wheat production and prices is estimated and applied to evaluate the changes in the risk and returns of agricultural production in the region resulting from observed and predicted price and production trends. The estimated pdf allows for time trends on the mean and the variance and varying degrees of autocorrelation and non-normality (kurtosis and right- or left-skewness) in each of the price and production variables. It also allows for any possible price-price, production-production, or price-production correlation.

Suggested Citation

  • Ramirez, Octavio A., 2000. "Parametric Modeling And Simulation Of Joint Price-Production Distributions Under Non-Normality, Autocorrelation And Heteroscedasticity: A Tool For Assessing Risk In Agriculture," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 32(2), pages 1-15, August.
    • Handle: RePEc:ags:joaaec:15486
    DOI: 10.22004/ag.econ.15486
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    File URL: https://ageconsearch.umn.edu/record/15486/files/32020283.pdf
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    References listed on IDEAS

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    1. Meyer, Jack, 1977. "Choice among distributions," Journal of Economic Theory, Elsevier, vol. 14(2), pages 326-336, April.
    2. Octavio A. Ramírez, 1997. "Estimation and Use of a Multivariate Parametric Model for Simulating Heteroskedastic, Correlated, Nonnormal Random Variables: The Case of Corn Belt Corn, Soybean, and Wheat Yields," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(1), pages 191-205.
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    Cited by:

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    2. Featherstone, Allen M. & Kastens, Terry L., 2000. "Non-Parametric and Semi-Parametric Techniques for Modeling and Simulating Correlated, Non-Normal Price and Yield Distributions: Applications to Risk Analysis in Kansas Agriculture," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 32(2), pages 267-281, August.
    3. Asci, Serhat & VanSickle, John J. & Cantliffe, Daniel J., 2013. "The Potential for Greenhouse Tomato Production Expansion in Florida," 2013 Annual Meeting, February 2-5, 2013, Orlando, Florida 143095, Southern Agricultural Economics Association.

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