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Quasi-Monte Carlo application in CGE systematic sensitivity analysis

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  • Theodoros Chatzivasileiadis

Abstract

The uncertainty and robustness of Computable General Equilibrium (CGE) models can be assessed by conducting a Systematic Sensitivity Analysis (SSA). Different methods have been used in the literature for SSA of CGE models such as Gaussian Quadrature and Monte Carlo methods. This article explores the use of Quasi-random Monte Carlo methods based on the Halton and Sobol’ sequences as means to improve the efficiency over regular Monte Carlo SSA, thus reducing the computational requirements of the SSA. The findings suggest that by using low-discrepancy sequences, the number of simulations required by the regular MC SSA methods can be notably reduced, hence lowering the computational time required for SSA of CGE models.

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  • Theodoros Chatzivasileiadis, 2018. "Quasi-Monte Carlo application in CGE systematic sensitivity analysis," Applied Economics Letters, Taylor & Francis Journals, vol. 25(21), pages 1521-1526, December.
    • Handle: RePEc:taf:apeclt:v:25:y:2018:i:21:p:1521-1526
    DOI: 10.1080/13504851.2018.1430322
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    Cited by:

    1. Jared C. Carbone & Linda T.M. Bui & Don Fullerton & Sergey Paltsev & Ian Sue Wing, 2022. "When and How to Use Economy-Wide Models for Environmental Policy Analysis," Annual Review of Resource Economics, Annual Reviews, vol. 14(1), pages 447-465, October.

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