IDEAS home Printed from https://ideas.repec.org/p/yon/wpaper/2026rwp-293.html

Exact identification, robust inference, and shock masquerading in sign-restricted SVARs

Author

Listed:
  • Hyeon-seung Huh

    (Yonsei University)

  • David Kim

    (University of Sydney)

Abstract

We propose an alternative sampling scheme for sign-restricted SVARs that addresses two fundamental challenges in the standard approach: prior dependence and shock masquerading. The key idea is to utilize a direct sampling of structural coefficients in the SVAR combined with the robust inference of Giacomini and Kitagawa (2021). The scheme delivers large sets of exactly identified models, and the rotation matrix is uniquely solved via a direct, non-iterative linear algorithm. Sign restrictions are then used as a post-identification filter to ensure economic plausibility. This design is capable of eliminating prior dependence concerns, tightening the credible bounds, mitigating shock masquerading, and improving computational efficiency. We demonstrate the practical utility of the alternative sampling scheme through an application to the U.S. SVAR of Peersman (2005).

Suggested Citation

  • Hyeon-seung Huh & David Kim, 2026. "Exact identification, robust inference, and shock masquerading in sign-restricted SVARs," Working papers 2026rwp-293, Yonsei University, Yonsei Economics Research Institute.
  • Handle: RePEc:yon:wpaper:2026rwp-293
    as

    Download full text from publisher

    File URL: http://121.254.254.220/repec/yon/wpaper/2026rwp-293.pdf
    Download Restriction: no
    ---><---

    More about this item

    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
    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:yon:wpaper:2026rwp-293. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: YERI (email available below). General contact details of provider: https://edirc.repec.org/data/eryonkr.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.