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Identifying Structural Vector Autoregressions Via Changes in Volatility☆This article was written while the author was a Bundesbank Professor at the Freie Universität Berlin. An earlier version of the paper was published as DIW Discussion Paper 1259 –http://www.diw.de/sixcms/detail.php?id=diw_0.1.c.412678.de

In: VAR Models in Macroeconomics – New Developments and Applications: Essays in Honor of Christopher A. Sims

Author

Listed:
  • Helmut Lütkepohl

Abstract

Identification of shocks of interest is a central problem in structural vector autoregressive (SVAR) modeling. Identification is often achieved by imposing restrictions on the impact or long-run effects of shocks or by considering sign restrictions for the impulse responses. In a number of articles changes in the volatility of the shocks have also been used for identification. The present study focuses on the latter device. Some possible setups for identification via heteroskedasticity are reviewed and their potential and limitations are discussed. Two detailed examples are considered to illustrate the approach.

Suggested Citation

  • Helmut Lütkepohl, 2013. "Identifying Structural Vector Autoregressions Via Changes in Volatility☆This article was written while the author was a Bundesbank Professor at the Freie Universität Berlin. An earlier version of the ," Advances in Econometrics, in: VAR Models in Macroeconomics – New Developments and Applications: Essays in Honor of Christopher A. Sims, volume 32, pages 169-203, Emerald Group Publishing Limited.
    • Handle: RePEc:eme:aecozz:s0731-9053(2013)0000031005
    DOI: 10.1108/S0731-9053(2013)0000031005
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    More about this item

    Keywords

    Markov switching model; vector autoregression; heteroskedasticity; vector GARCH; conditional heteroskedasticity; C32;
    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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