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Inference for structural impulse responses in SVAR-GARCH models

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  • Stefan Bruder

Abstract

Conditional heteroskedasticity can be exploited to identify the structural vector autoregressions (SVAR) but the implications for inference on structural impulse responses have not been investigated in detail yet. We consider the conditionally heteroskedastic SVAR-GARCH model and propose a bootstrap-based inference procedure on structural impulse responses. We compare the finite-sample properties of our bootstrap method with those of two competing bootstrap methods via extensive Monte Carlo simulations. We also present a three-step estimation procedure of the parameters of the SVAR-GARCH model that promises numerical stability even in scenarios with small sample sizes and/or large dimensions.

Suggested Citation

  • Stefan Bruder, 2018. "Inference for structural impulse responses in SVAR-GARCH models," ECON - Working Papers 281, Department of Economics - University of Zurich.
    • Handle: RePEc:zur:econwp:281
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    File URL: https://www.zora.uzh.ch/id/eprint/150862/1/econwp281.pdf
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    References listed on IDEAS

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    Cited by:

    1. Lütkepohl, Helmut & Schlaak, Thore, 2019. "Bootstrapping impulse responses of structural vector autoregressive models identified through GARCH," Journal of Economic Dynamics and Control, Elsevier, vol. 101(C), pages 41-61.

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    More about this item

    Keywords

    Bootstrap; conditional heteroskedasticity; multivariate GARCH; structural impulse responses; structural vector autoregression;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • 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

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