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ARGEMmy: An Intermediate DSGE Model Calibrated/Estimated for Argentina: Two Policy Rules are Often Better than One

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  • Guillermo Escudé

    () (Central Bank of Argentina)

Abstract

The purpose of this paper is to advance in the construction and calibration/estimation of an intermediate DSGE model with two policy rules for Argentina and explore to what extent two policy rules can be better than one. The BCRA´s research department currently uses a very small and non-micro founded model with two policy rules which I designed a few years ago (MEP: Modelo Económico Pequeño (see Elosegui, Escudé, Garegnani and Sotes Paladino 2007)) as the backbone for a system of macro and monetary projections. During 2006-07 I constructed the much larger DSGE model ARGEM, mainly for research purposes. It seemed that there was need for an intermediate sized DSGE model that could be of help in bridging the gap between the two. ARGEMmy is the result of this new effort. Hopefully, it will help in bringing the DSGE modeling strategy closer to the policy environment.

Suggested Citation

  • Guillermo Escudé, 2009. "ARGEMmy: An Intermediate DSGE Model Calibrated/Estimated for Argentina: Two Policy Rules are Often Better than One," BCRA Working Paper Series 200942, Central Bank of Argentina, Economic Research Department.
  • Handle: RePEc:bcr:wpaper:200942
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    File URL: http://www.bcra.gov.ar/pdfs/investigaciones/WP_42_2009i.pdf
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    References listed on IDEAS

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    Cited by:

    1. Escudé, Guillermo J., 2014. "The possible trinity: Optimal interest rate, exchange rate, and taxes on capital flows in a DSGE model for a small open economy," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy (IfW), vol. 8, pages 1-58.

    More about this item

    Keywords

    Argentina; Bayesian estimation; DSGE models; policy rules;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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