Correlated Order Three Gaussian Quadratures in Stochastic Simulation Modelling

Marco Artavia, Harald Grethe, Thordis Möller and Georg Zimmermann

No 331853, Conference papers from Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project

Abstract: A simple approach to generate correlated order three Gaussian quadratures is presented. It is shown how for stochastic simulation modelling purposes the integration over the ncube as suggested in Stroud (1957) is not necessary and thus, a simpler integration formula is given. The theory of inducing a desired covariance matrix is presented and three possibilities to do so are demonstrated. The approach described is implemented in a stochastic version of the European Simulation Model (ESIM) which includes 42 correlated stochastic terms in the yield functions. Model results are presented to validate the proposed approach compared to a Monte Carlo based approach as well as to demonstrate the relevance of stochastic simulation modelling.

Keywords: Research Methods/Statistical Methods; Research and Development/Tech Change/Emerging Technologies (search for similar items in EconPapers)
Pages: 29
Date: 2009
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://ageconsearch.umn.edu/record/331853/files/4378.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ags:pugtwp:331853

Access Statistics for this paper

More papers in Conference papers from Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project Contact information at EDIRC.
Bibliographic data for series maintained by AgEcon Search ().