R Meets GEMPACK for a Monte Carlo Walk

Nelson B. Villoria


This paper discusses two R functions for reading the output of GEMPACK-based CGE models into R. We highlight the potential of coupling GEMPACK and R by conducting systematic sensitivity analysis of model results using Monte Carlo experiments. We also show how R can enhance the analysis of CGE results by allowing for formal hypothesis testing of the effects of policies which outcome depends on stochastic shocks.


Monte Carlo, Systematic Sensitivity Analysis, Gaussian Quadratures, GEMPACK, R, Agricultural Technology.

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DOI: http://dx.doi.org/10.21642/JGEA.020204AF


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Copyright (c) 2017 Nelson Villoria