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Solving and estimating linearized DSGE models with VARMA shock processes and filtered data

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  • Meyer-Gohde, Alexander
  • Neuhoff, Daniel

Abstract

We derive recursive solutions to linearized DSGE models with VARMA exogenous driving forces of arbitrary order without inflating the state vector. Representing the solution in the frequency domain, we calculate the likelihood of a sequence of observations from the model, as well as its nonrecursively filtered (e.g., Hodrick–Prescott or Baxter–King) variant straightforwardly.

Suggested Citation

  • Meyer-Gohde, Alexander & Neuhoff, Daniel, 2015. "Solving and estimating linearized DSGE models with VARMA shock processes and filtered data," Economics Letters, Elsevier, vol. 133(C), pages 89-91.
    • Handle: RePEc:eee:ecolet:v:133:y:2015:i:c:p:89-91
    DOI: 10.1016/j.econlet.2015.05.024
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    References listed on IDEAS

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    10. King, Robert G. & Rebelo, Sergio T., 1993. "Low frequency filtering and real business cycles," Journal of Economic Dynamics and Control, Elsevier, vol. 17(1-2), pages 207-231.
    11. Meyer-Gohde, Alexander, 2010. "Linear rational-expectations models with lagged expectations: A synthetic method," Journal of Economic Dynamics and Control, Elsevier, vol. 34(5), pages 984-1002, May.
    12. Schmitt-Grohé, Stephanie & Uribe, Martín, 2010. "Evaluating the sample likelihood of linearized DSGE models without the use of the Kalman filter," Economics Letters, Elsevier, vol. 109(3), pages 142-143, December.
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    Cited by:

    1. Alexander Meyer-Gohde & Daniel Neuhoff, 2015. "Generalized Exogenous Processes in DSGE: A Bayesian Approach," SFB 649 Discussion Papers SFB649DP2015-014, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Morris, Stephen D., 2016. "VARMA representation of DSGE models," Economics Letters, Elsevier, vol. 138(C), pages 30-33.

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    More about this item

    Keywords

    DSGE models; ARMA; VAR; Likelihood function;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications

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