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
This study develops a multivariate, nonnormal density function that can accurately and separately account for skewness, kurtosis, heteroskedasticity, and the correlation among the random variables of interest. The statistical attributes of the underlying random variables and correlation processes are examined. The potential applications of this modeling tool are discussed and exemplified by analyzing and simulating Corn Belt corn, soybean, and wheat yields. While corn and soybean yields are found to be skewed and kurtotic and exhibit different variances through time, wheat yields appear normal but also heteroskedastic. A strong correlation is detected between corn and soybean yields. Copyright 1997, Oxford University Press.
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.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 79 (1997)
Issue (Month): 1 ()
|Contact details of provider:|| Postal: 555 East Wells Street, Suite 1100, Milwaukee, Wisconsin 53202|
Phone: (414) 918-3190
Fax: (414) 276-3349
Web page: http://www.aaea.org/
More information through EDIRC