Comment on "A Monte Carlo filtering application for systematic sensitivity analysis of computable general equilibrium results"
Davit Stepanyan (),
Harald Grethe and
Khalid Siddig ()
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Davit Stepanyan: Humboldt University of Berlin
Khalid Siddig: Humboldt University of Berlin
Economics Bulletin, 2019, vol. 39, issue 3, 1925-1929
In a recent article published in the Journal of Economic Systems Research, Mary et al. (2018) introduced an interesting approach to systematic sensitivity analysis applied in a Computable General Equilibrium (CGE) modelling framework. This approach offers a systematic method of identifying the model parameters that have the greatest impact on the uncertainty of model output. According to the authors, moreover, it increases the quality of the approximated results by decreasing the dimensionality of the problem. This article contributes to a recent set of studies discussing the accuracy and appropriateness of different uncertainty analysis methods in economic simulation models. While the focus of the article is on a more efficient way of sensitivity analysis, we see a problem in using an arbitrary rotation of Stroud`s octahedron as a benchmark for assessing Monte Carlo simulations.
Keywords: Systematic sensitivity analysis; Monte Carlo filtering; Gaussian quadratures; parameter uncertainty; CGE model (search for similar items in EconPapers)
JEL-codes: C6 Q0 (search for similar items in EconPapers)
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