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A procedure for combining zero and sign restrictions in a VAR-identification scheme

Author

Listed:
  • Alex Haberis

    (Bank of England
    Centre for Macroeconomics (CFM))

  • Andrej Sokol

    (Bank of England)

Abstract

In this paper we describe a procedure for implementing zero restrictions within the context of a sign restrictions identification scheme for VARs. The procedure introduces an additional step into the algorithm outlined in Fry and Pagan (2011) and Rubio-Ramirez et al. (2006) for implementing sign restrictions. This extra step involves rotating a candidate identification matrix using Givens rotation matrices to introduce zero restrictions. We then check whether the elements of the candidate matrix satisfy the sign restrictions as usual. We illustrate how our procedure works by generating artificial data from the theoretical model of An and Schorfheide (2007), which implies certain restrictions on the impact of its structural shocks on the model's endogenous variables. We exploit our knowledge of that pattern to identify structural shocks from the reduced-form errors of a VAR estimated on the simulated data.

Suggested Citation

  • Alex Haberis & Andrej Sokol, 2014. "A procedure for combining zero and sign restrictions in a VAR-identification scheme," Discussion Papers 1410, Centre for Macroeconomics (CFM).
    • Handle: RePEc:cfm:wpaper:1410
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    References listed on IDEAS

    as
    1. Jesús Fernández-Villaverde & Juan F. Rubio-Ramírez & Thomas J. Sargent & Mark W. Watson, 2007. "ABCs (and Ds) of Understanding VARs," American Economic Review, American Economic Association, vol. 97(3), pages 1021-1026, June.
    2. Sungbae An & Frank Schorfheide, 2007. "Bayesian Analysis of DSGE Models—Rejoinder," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 211-219.
    3. Jonas E. Arias & Juan Rubio-Ramirez & Daniel F. Waggoner, 2013. "Inference Based on SVARs Identied with Sign and Zero Restrictions: Theory and Applications," Working Papers 2013-24, FEDEA.
    4. Renée Fry & Adrian Pagan, 2011. "Sign Restrictions in Structural Vector Autoregressions: A Critical Review," Journal of Economic Literature, American Economic Association, vol. 49(4), pages 938-960, December.
    5. Ravenna, Federico, 2007. "Vector autoregressions and reduced form representations of DSGE models," Journal of Monetary Economics, Elsevier, vol. 54(7), pages 2048-2064, October.
    6. Christiane Baumeister & Luca Benati, 2013. "Unconventional Monetary Policy and the Great Recession: Estimating the Macroeconomic Effects of a Spread Compression at the Zero Lower Bound," International Journal of Central Banking, International Journal of Central Banking, vol. 9(2), pages 165-212, June.
    7. Ivana Komunjer & Serena Ng, 2011. "Dynamic Identification of Dynamic Stochastic General Equilibrium Models," Econometrica, Econometric Society, vol. 79(6), pages 1995-2032, November.
    8. Sungbae An & Frank Schorfheide, 2007. "Bayesian Analysis of DSGE Models," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 113-172.
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    Cited by:

    1. Fisher, Lance A. & Huh, Hyeon-seung, 2019. "An IV framework for combining sign and long-run parametric restrictions in SVARs," Journal of Macroeconomics, Elsevier, vol. 61(C), pages 1-1.
    2. Małgorzata Skibińska, 2018. "Transmission of monetary policy and exchange rate shocks under foreign currency lending," Post-Communist Economies, Taylor & Francis Journals, vol. 30(4), pages 506-525, July.
    3. Fisher Lance A. & Huh Hyeon-seung, 2020. "Combining sign and parametric restrictions in SVARs by utilising Givens rotations," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(3), pages 1-19, June.
    4. Lance A. Fisher & Hyeon-seung Huh, 2018. "Combining sign and parametric restrictions in SVARs by Givens Rotations," Working papers 2018rwp-122, Yonsei University, Yonsei Economics Research Institute.
    5. Domit, Sílvia & Monti, Francesca & Sokol, Andrej, 2016. "A Bayesian VAR benchmark for COMPASS," Bank of England working papers 583, Bank of England.

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    More about this item

    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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • E12 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Keynes; Keynesian; Post-Keynesian; Modern Monetary Theory

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