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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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    1. Marianne Baxter & Robert G. King, 1999. "Measuring Business Cycles: Approximate Band-Pass Filters For Economic Time Series," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 575-593, November.
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    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. Meyer-Gohde, Alexander & Neuhoff, Daniel, 2015. "Generalized exogenous processes in DSGE: A Bayesian approach," SFB 649 Discussion Papers 2015-014, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    2. Meyer-Gohde, Alexander, 2024. "Solving and analyzing DSGE models in the frequency domain," IMFS Working Paper Series 207, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
    3. 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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