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Heteroskedastic Proxy Vector Autoregressions

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  • Helmut Lütkepohl
  • Thore Schlaak

Abstract

In proxy vector autoregressive models, the structural shocks of interest are identified by an instrument. Although heteroskedasticity is occasionally allowed for, it is typically taken for granted that the impact effects of the structural shocks are time-invariant despite the change in their variances. We develop a test for this implicit assumption and present evidence that the assumption of time-invariant impact effects may be violated in previously used empirical models.

Suggested Citation

  • Helmut Lütkepohl & Thore Schlaak, 2020. "Heteroskedastic Proxy Vector Autoregressions," Discussion Papers of DIW Berlin 1876, DIW Berlin, German Institute for Economic Research.
    • Handle: RePEc:diw:diwwpp:dp1876
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    References listed on IDEAS

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    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Yayi Yan & Jiti Gao & Bin Peng, 2021. "On Time-Varying VAR Models: Estimation, Testing and Impulse Response Analysis," Papers 2111.00450, arXiv.org.
    2. Boer, Lukas & Lütkepohl, Helmut, 2021. "Qualitative versus quantitative external information for proxy vector autoregressive analysis," Journal of Economic Dynamics and Control, Elsevier, vol. 127(C).
    3. Martin Bruns & Helmut Luetkepohl, 2023. "Have the Effects of Shocks to Oil Price Expectations Changed? Evidence from Heteroskedastic Proxy Vector Autoregressions," University of East Anglia School of Economics Working Paper Series 2023-03, School of Economics, University of East Anglia, Norwich, UK..
    4. Martin Bruns & Helmut Luetkepohl, 2022. "Heteroskedastic Proxy Vector Autoregressions: Testing for Time-Varying Impulse Responses in the Presence of Multiple Proxies," University of East Anglia School of Economics Working Paper Series 2022-02, School of Economics, University of East Anglia, Norwich, UK..
    5. Yayi Yan & Jiti Gao & Bin Peng, 2021. "On Time-Varying VAR models: Estimation, Testing and Impulse Response Analysis," Monash Econometrics and Business Statistics Working Papers 17/21, Monash University, Department of Econometrics and Business Statistics.
    6. Lukas Boer & Helmut Lütkepohl, 2020. "A Simple Instrument for Proxy Vector Autoregressive Analysis," Discussion Papers of DIW Berlin 1905, DIW Berlin, German Institute for Economic Research.
    7. Bruns, Martin & Lütkepohl, Helmut, 2022. "Comparison of local projection estimators for proxy vector autoregressions," Journal of Economic Dynamics and Control, Elsevier, vol. 134(C).
    8. Fengler, Matthias & Polivka, Jeannine, 2021. "Identifying structural shocks to volatility through a proxy-MGARCH model," Economics Working Paper Series 2103, University of St. Gallen, School of Economics and Political Science, revised May 2021.

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    More about this item

    Keywords

    Structural vector autoregression; proxy VAR; identification through heteroskedasticity;
    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

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