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Canadian Monetary Policy Analysis using a Structural VARMA Model

Author

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  • Mala Raghavan

    ()

  • George Athanasopoulos

    ()

  • Param Silvapulle

    ()

Abstract

This paper builds a structural VARMA (SVARMA) model for investigating Canadian monetary policy. Despite the support for a VARMA model for monetary policy analysis, the traditional VAR and SVAR models have predominantly been used in the literature mainly due to difficulties associated with the identification and estimation of such a model. Using the scalar component model (SCM) proposed by Athanasopoulos and Vahid (2008a), this paper first identifies a VARMA model and then constructs a SVARMA model for Canadian monetary policy. We included the SVAR model in our study for a comparison purpose. Relative to this model, the impulse responses generated by the SVARMA model appear to be consistent with those predicted by various economic theoretical models, and solves the economic puzzles found commonly in the empirical literature on monetary policy. The successful construction and implementation of the SVARMA model for Canadian monetary policy analysis along with its promising impulse responses, indicate the suitability of this framework for small open economies.

Suggested Citation

  • Mala Raghavan & George Athanasopoulos & Param Silvapulle, 2013. "Canadian Monetary Policy Analysis using a Structural VARMA Model," Monash Econometrics and Business Statistics Working Papers 4/13, Monash University, Department of Econometrics and Business Statistics.
    • Handle: RePEc:msh:ebswps:2013-4
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    References listed on IDEAS

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    Cited by:

    1. Georgiadis, Georgios & Jančoková, Martina, 2017. "Financial globalisation, monetary policy spillovers and macro-modelling: tales from 1001 shocks," Working Paper Series 2082, European Central Bank.
    2. repec:bla:ecorec:v:93:y:2017:i:302:p:465-483 is not listed on IDEAS

    More about this item

    Keywords

    VARMA models; Identification; Impulse responses; Open economy; Transmission mechanism;

    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

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