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Impulse Response Identification in DSGE Models



DSGE models have become a widely used tool for policymakers. This paper takes the global identification theory used for structural vectorautoregressions, and applies it to dynamic stochastic general equilibrium (DSGE) models. We use this modified theory to check whether a DSGE model structure allows for unique estimates of structural shocks and their dynamic effects. The potential cost of a lack of identification for policy oriented models along that specific dimension is huge, as the same model can generate a number of contrasting yet theoretically and empirically justifiable recommendations. The problem and methodology are illustrated using a simple New Keynesian business cycle model.

Suggested Citation

  • Martin Fukac, 2009. "Impulse Response Identification in DSGE Models," Reserve Bank of New Zealand Discussion Paper Series DP2009/14, Reserve Bank of New Zealand.
  • Handle: RePEc:nzb:nzbdps:2009/14

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    References listed on IDEAS

    1. Iskrev, Nikolay, 2008. "Evaluating the information matrix in linearized DSGE models," Economics Letters, Elsevier, vol. 99(3), pages 607-610, June.
    2. Canova, Fabio & Sala, Luca, 2009. "Back to square one: Identification issues in DSGE models," Journal of Monetary Economics, Elsevier, vol. 56(4), pages 431-449, May.
    3. Iskrev, Nikolay, 2010. "Local identification in DSGE models," Journal of Monetary Economics, Elsevier, vol. 57(2), pages 189-202, March.
    4. Juan F. Rubio-Ramírez & Daniel F. Waggoner & Tao Zha, 2010. "Structural Vector Autoregressions: Theory of Identification and Algorithms for Inference," Review of Economic Studies, Oxford University Press, vol. 77(2), pages 665-696.
    5. Rothenberg, Thomas J, 1971. "Identification in Parametric Models," Econometrica, Econometric Society, vol. 39(3), pages 577-591, May.
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    Cited by:

    1. Andrew Binning & Junior Maih, 2015. "Sigma point filters for dynamic nonlinear regime switching models," Working Paper 2015/10, Norges Bank.

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    JEL classification:

    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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