GTAP Resources: Resource Display
| GTAP Resource #6897 |
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"Towards consistent systematic sensitivity analysis in the GTAP model" by Ivanic, Maros and Hitesh Shah Abstract Systematic Sensitivity Analysis (SSA) is an important complement to GTAP CGE analysis. While tools in RunGtap/RunGEM allow for SSA in the GTAP model, they are limiting in more complicated scenarios: i) the GUI SSA tool only allows for varying either shocks or parameters but not both at the same time (enhancements allow simultaneous variation but require modifying TABLO model file, limiting the appeal to a wider user-base) ii) the choice of statistical distributions for capturing input uncertainty is restricted to the triangular or uniform distributions and iii) the number of multiple simulations is not in users’ control rendering Monte Carlo type analysis infeasible. In this paper we introduce an R package that overcomes some of the limitations of currently available off-the-shelf SSA tools. By allowing R to control the GTAP model--including its variables and parameters--it is possible to bypass the technical limits of the GEMPACK models and vary any variable or parameter simultaneously using any distribution (including empirical ones). Though not the first R package in this area -- the rgtap package (Villoria 2017) provides greater flexibility for SSA but does not appear to be up to date and requires refitting for addressing some of the above limitations -- rssa offers some practical advantages like minimal need for changing TABLO or R code for example. To demonstrate the value of our software tool, we undertake a Monte Carlo-type analysis using the standard GTAP model, incorporating variation in shocks and parameters where uncertainty is captured via normal and uniform distributions. |
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- Software and modeling tools |
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Public Access  GTAP Resource 6897 (539.7 KB) Replicated: 0 time(s) GTAP Resource 6897 (87.9 KB) Replicated: 0 time(s)Restricted Access No documents have been attached. Special Instructions No instructions have been specified. |
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Last Modified: 9/15/2023 2:05:45 PM
