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RunMONASH: Automating A Dynamic, Recursive CGE Model

Author

Listed:
  • Jill Harrison
  • Glyn Wittwer

Abstract

RunMONASH, a software program, written by Ken Pearson, is used to solve the CGE model, MONASH. RunMONASH produces a base case forecast for a set of years in sequence. In response to some additional policy shocks, RunMONASH calculates a policy deviation from this base case, again for the same sequence of years. This paper outlines the reasons for writing RunMONASH and the basic ideas of the solution method. It gives an overview of the dynamic CGE models for which RunMONASH can be used. A brief introduction to the Screen interface is included. However, the main documentation of RunMONASH is the Online Help file that accompanies the software.

Suggested Citation

  • Jill Harrison & Glyn Wittwer, 2003. "RunMONASH: Automating A Dynamic, Recursive CGE Model," Centre of Policy Studies/IMPACT Centre Working Papers c14, Victoria University, Centre of Policy Studies/IMPACT Centre.
  • Handle: RePEc:cop:wpaper:c14
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    References listed on IDEAS

    as
    1. Philip D. Adams & J. Mark Horridge & Brian R. Parmenter, 2000. "MMRF-GREEN: A Dynamic, Multi-Sectoral, Multi-Regional Model of Australia," Centre of Policy Studies/IMPACT Centre Working Papers op-94, Victoria University, Centre of Policy Studies/IMPACT Centre.
    2. Peter B. Dixon & K.R. Pearson & Mark R. Picton & Maureen T. Rimmer, 2002. "Rational Expectations for Large Models: A Practical Algorithm and a Policy Application," Centre of Policy Studies/IMPACT Centre Working Papers ip-81, Victoria University, Centre of Policy Studies/IMPACT Centre.
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    More about this item

    Keywords

    dynamic CGE model; GEMPACK software;

    JEL classification:

    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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