AN INTRODUCTION TO SYSTEMATIC SENSITIVITY ANALYSIS VIA GAUSSIAN QUADRATURE

Channing Arndt

No 28709, Technical Papers from Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project

Abstract: Economists recognize that results from simulation models are dependent, sometimes highly dependent, on values employed for critical exogenous variables. To account for this, analysts sometimes conduct sensitivity analysis with respect to key exogenous variables. This paper presents a practical approach for conducting systematic sensitivity analysis, called Gaussian quadrature. The approach views key exogenous variables as random variables with associated distributions. It produces estimates of means and standard deviations of model results while requiring a limited number of solves of the model. Under mild conditions, all of which hold with respect to the GTAP model, there is strong reason to believe that the estimates of means and standard deviations will be quite accurate.

Keywords: Research; Methods/Statistical; Methods (search for similar items in EconPapers)
Pages: 25
Date: 1996
References: View complete reference list from CitEc
Citations: View citations in EconPapers (109)

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https://ageconsearch.umn.edu/record/28709/files/tp02.pdf (application/pdf)

Related works:
Working Paper: An Introduction to Systematic Sensitivity Analysis via Gaussian Quadrature (1996)
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Persistent link: https://EconPapers.repec.org/RePEc:ags:pugttp:28709

DOI: 10.22004/ag.econ.28709

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