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Identification and Frequency Domain QML Estimation of Linearized DSGE Models

Author

Listed:
  • Zhongjun Qu

    () (Department of Economics, Boston University)

  • Denis Tkachenko

    () (Department of Economics, Boston University)

Abstract

This paper considers issues related to identification, inference and computation in linearized Dynamic Stochastic General Equilibrium (DSGE) models. We first provide a necessary and su¢ cient condition for the local identification of the structural parameters based on the (first and) second order properties of the process. The condition allows for arbitrary relations be- tween the number of observed endogenous variables and structural shocks and is simple to verify. The extensions, including identification through a subset of frequencies, partial iden- tification, conditional identification and identification under general nonlinear constraints, are also studied. When lack of identification is detected, the method can be further used to trace out non-identification curves. For estimation, restricting our attention to nonsingular systems, we consider a frequency domain quasi-maximum likelihood (FQML) estimator and present its asymptotic properties. The limiting distribution of the estimator can be di¤erent from results in the related literature due to the structure of the DSGE model. Finally, we discuss a quasi- Bayesian procedure for estimation and inference. The procedure can be used to incorporate relevant prior distributions and is computationally attractive.

Suggested Citation

  • Zhongjun Qu & Denis Tkachenko, 2010. "Identification and Frequency Domain QML Estimation of Linearized DSGE Models," Boston University - Department of Economics - Working Papers Series WP2010-053, Boston University - Department of Economics.
  • Handle: RePEc:bos:wpaper:wp2010-053
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    References listed on IDEAS

    as
    1. Christiano, Lawrence J. & Vigfusson, Robert J., 2003. "Maximum likelihood in the frequency domain: the importance of time-to-plan," Journal of Monetary Economics, Elsevier, pages 789-815.
    2. Consolo, Agostino & Favero, Carlo A. & Paccagnini, Alessia, 2009. "On the statistical identification of DSGE models," Journal of Econometrics, Elsevier, vol. 150(1), pages 99-115, May.
    3. Iskrev, Nikolay, 2010. "Local identification in DSGE models," Journal of Monetary Economics, Elsevier, vol. 57(2), pages 189-202, March.
    4. Altug, Sumru, 1989. "Time-to-Build and Aggregate Fluctuations: Some New Evidence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 30(4), pages 889-920, November.
    5. Chernozhukov, Victor & Hong, Han, 2003. "An MCMC approach to classical estimation," Journal of Econometrics, Elsevier, vol. 115(2), pages 293-346, August.
    6. Berkowitz, Jeremy, 2001. "Generalized spectral estimation of the consumption-based asset pricing model," Journal of Econometrics, Elsevier, vol. 104(2), pages 269-288, September.
    7. Hansen, Lars Peter & Sargent, Thomas J., 1993. "Seasonality and approximation errors in rational expectations models," Journal of Econometrics, Elsevier, vol. 55(1-2), pages 21-55.
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    Citations

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    Cited by:

    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. repec:fip:feddgm:00013 is not listed on IDEAS
    3. repec:fip:feddar:y:2011:p:2-12 is not listed on IDEAS
    4. Zhongjun Qu, 2011. "Inference and Speci?cation Testing in DSGE Models with Possible Weak Identification," Boston University - Department of Economics - Working Papers Series WP2011-058, Boston University - Department of Economics.
    5. Qu, Zhongjun & Yoon, Jungmo, 2015. "Nonparametric estimation and inference on conditional quantile processes," Journal of Econometrics, Elsevier, pages 1-19.

    More about this item

    Keywords

    Infinite dimensional mapping; Local identification; MCMC; Non-identification curve; Rank condition; Spectral domain;

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • E1 - Macroeconomics and Monetary Economics - - General Aggregative Models

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