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Choosing the variables to estimate singular DSGE models: Comment

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  • Nikolay, Iskrev

Abstract

In a recent article Canova et al. (2014) study the optimal choice of variables to use in the estimation of a simplified version of the Smets and Wouters (2007) model. In this comment I examine their conclusions by applying a different methodology to the same model. The results call into question most of Canova et al. (2014) findings.

Suggested Citation

  • Nikolay, Iskrev, 2014. "Choosing the variables to estimate singular DSGE models: Comment," Dynare Working Papers 41, CEPREMAP.
    • Handle: RePEc:cpm:dynare:041
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    References listed on IDEAS

    as
    1. Fabio Canova & Filippo Ferroni & Christian Matthes, 2014. "Choosing The Variables To Estimate Singular Dsge Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(7), pages 1099-1117, November.
    2. 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.
    3. Bierens, Herman J., 2007. "Econometric analysis of linearized singular dynamic stochastic general equilibrium models," Journal of Econometrics, Elsevier, vol. 136(2), pages 595-627, February.
    4. Nikolay Iskrev, 2010. "Evaluating the strength of identification in DSGE models. An a priori approach," 2010 Meeting Papers 1117, Society for Economic Dynamics.
    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. Nikolay Iskrev, 2018. "Are asset price data informative about news shocks? A DSGE perspective," Working Papers REM 2018/33, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    2. Thorsten Drautzburg, 2020. "A narrative approach to a fiscal DSGE model," Quantitative Economics, Econometric Society, vol. 11(2), pages 801-837, May.

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    More about this item

    Keywords

    DSGE models; Observables; Identification; Information matrix; Cramer-Rao lower bound;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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