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Estimation of DSGE models: Maximum Likelihood vs. Bayesian methods

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  • Mickelsson, Glenn

    (Department of Economics)

Abstract

DSGE models are typically estimated using Bayesian methods, but a researcher may want to estimate a DSGE model with full information maximum likelihood (FIML) so as to avoid the use of prior distributions. A very robust algorithm is needed to find the global maximum within the relevant parameter space. I suggest such an algorithm and show that it is possible to estimate the model of Smets and Wouters (2007) using FIML. Inference is carried out using stochastic bootstrapping techniques. Several FIML estimates turn out to be significantly diffrent from the Bayesian estimates and the reasons behind those differences are analyzed.

Suggested Citation

  • Mickelsson, Glenn, 2015. "Estimation of DSGE models: Maximum Likelihood vs. Bayesian methods," Working Paper Series 2015:6, Uppsala University, Department of Economics.
    • Handle: RePEc:hhs:uunewp:2015_006
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    References listed on IDEAS

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    1. McCallum, Bennett T. & Nelson, Edward, 1999. "Nominal income targeting in an open-economy optimizing model," Journal of Monetary Economics, Elsevier, vol. 43(3), pages 553-578, June.
    2. Martin Andreasen, 2010. "How to Maximize the Likelihood Function for a DSGE Model," Computational Economics, Springer;Society for Computational Economics, vol. 35(2), pages 127-154, February.
    3. Christiano, Lawrence J. & Trabandt, Mathias & Walentin, Karl, 2011. "Introducing financial frictions and unemployment into a small open economy model," Journal of Economic Dynamics and Control, Elsevier, vol. 35(12), pages 1999-2041.
    4. Lawrence J. Christiano & Martin Eichenbaum & Charles L. Evans, 2005. "Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy," Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 1-45, February.
    5. Goffe, William L. & Ferrier, Gary D. & Rogers, John, 1994. "Global optimization of statistical functions with simulated annealing," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 65-99.
    6. Ireland, Peter N., 2004. "A method for taking models to the data," Journal of Economic Dynamics and Control, Elsevier, vol. 28(6), pages 1205-1226, March.
    7. Frank Smets & Raf Wouters, 2003. "An Estimated Dynamic Stochastic General Equilibrium Model of the Euro Area," Journal of the European Economic Association, MIT Press, vol. 1(5), pages 1123-1175, September.
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    Cited by:

    1. Gelain, Paolo & Manganelli, Simone, 2020. "Monetary policy with judgment," Working Paper Series 2404, European Central Bank.

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    More about this item

    Keywords

    Bayesian methods; Maximum likelihood; Business Cycles; Estimate DSGE models;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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