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Impulse Response Matching Estimators for DSGE Models

Author

Listed:
  • Pablo Guerron-Quintana
  • Atsushi Inoue
  • Lutz Kilian

Abstract

One of the leading methods of estimating the structural parameters of DSGE models is the VAR-based impulse response matching estimator. The existing asymptotic theory for this estimator does not cover situations in which the number of impulse response parameters exceeds the number of VAR model parameters. Situations in which this order condition is violated arise routinely in applied work. We establish the consistency of the impulse response matching estimator in this situation, we derive its asymptotic distribution, and we show how this distribution can be approximated by bootstrap methods. Our analysis sheds new light on the choice of the weighting matrix and covers both weakly and strongly identified DSGE model parameters. We also show that under our assumptions special care is needed to ensure the asymptotic validity of Bayesian methods of inference. A simulation study suggests that the in-terval estimators we propose are reasonably accurate in practice. We also show that using these methods may affect the substantive conclusions in empirical work.

Suggested Citation

  • Pablo Guerron-Quintana & Atsushi Inoue & Lutz Kilian, 2016. "Impulse Response Matching Estimators for DSGE Models," CESifo Working Paper Series 5730, CESifo Group Munich.
  • Handle: RePEc:ces:ceswps:_5730
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    File URL: https://www.cesifo-group.de/DocDL/cesifo1_wp5730.pdf
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    References listed on IDEAS

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    Cited by:

    1. Minford, Patrick & Wickens, Michael & Xu, Yongdeng, 2016. "Comparing different data descriptors in Indirect Inference tests on DSGE models," Economics Letters, Elsevier, vol. 145(C), pages 157-161.

    More about this item

    Keywords

    structural estimation; DSGE; VAR; impulse response; nonstandard asymptotics; bootstrap; weak identification; robust inference;

    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
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)
    • E50 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - General

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