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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.
    2. Ricardo Reis & Vasco Curdia, 2009. "Correlated Disturbances and U.S. Business Cycles," 2009 Meeting Papers 129, Society for Economic Dynamics.
    3. Hodrick, Robert J & Prescott, Edward C, 1997. "Postwar U.S. Business Cycles: An Empirical Investigation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 29(1), pages 1-16, February.
    4. Marco Del Negro & Frank Schorfheide, 2009. "Monetary Policy Analysis with Potentially Misspecified Models," American Economic Review, American Economic Association, vol. 99(4), pages 1415-1450, September.
    5. Lan, Hong & Meyer-Gohde, Alexander, 2014. "Solvability of perturbation solutions in DSGE models," Journal of Economic Dynamics and Control, Elsevier, vol. 45(C), pages 366-388.
    6. Anderson, Gary S., 2010. "A reliable and computationally efficient algorithm for imposing the saddle point property in dynamic models," Journal of Economic Dynamics and Control, Elsevier, vol. 34(3), pages 472-489, March.
    7. Klein, Paul, 2000. "Using the generalized Schur form to solve a multivariate linear rational expectations model," Journal of Economic Dynamics and Control, Elsevier, vol. 24(10), pages 1405-1423, September.
    8. Massimiliano Croce, Mariano, 2014. "Long-run productivity risk: A new hope for production-based asset pricing?," Journal of Monetary Economics, Elsevier, vol. 66(C), pages 13-31.
    9. Frank Smets & Rafael Wouters, 2007. "Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach," American Economic Review, American Economic Association, vol. 97(3), pages 586-606, June.
    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.

    More about this item

    Keywords

    DSGE models; ARMA; VAR; Likelihood function;

    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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