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Structural VARs, deterministic and stochastic trends: how much detrending matters for shock identification

  • Varang Wiriyawit and Benjamin Wong EMAIL logo
Published/Copyright: October 17, 2015
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Studies in Nonlinear Dynamics & Econometrics
From the journal Studies in Nonlinear Dynamics & Econometrics Volume 20 Issue 2

Abstract

Detrending within structural vector autoregressions (SVAR) is directly linked to the shock identification. We investigate the consequences of trend misspecification in an SVAR using both standard real business cycle models and bi-variate SVARs as data generating processes. Our bias decomposition reveals biases arising directly from trend misspecification are not trivial when compared to other widely studied misspecifications. Misspecifying the trend also distorts impulse response functions of even the correctly detrended variable within the SVAR system. Pretesting for unit roots mitigates trend misspecification to some extent. We also find that while practitioners can specify high lag order VARs to mitigate trend misspecification, relying on common information criterion such as the Akaike information criterion (AIC) or Bayesian information criterion (BIC) may choose a lag order that is too low.

Keywords: bias; detrending; identification; structural VAR
Corresponding author: Benjamin Wong, Reserve Bank of New Zealand, 2, The Terrace, Wellington 6011, New Zealand; and Centre for Applied Macroeconomic Analysis, The Australian National University

Acknowledgments

We thank Bruce Mizrach (Editor), James Morley (Associate Editor), two anonymous referees, Efrem Castelnuovo, Punnoose Jacob, Timothy Kam, Adrian Pagan, Andrea Pescatori, Christie Smith, Rodney Strachan, Sen Xue, Wenying Yao and participants of the 22nd Symposium of the Society of Nonlinear Dynamics and Econometrics, the 2014 Econometric Society Australasian Meeting, the 2014 Workshop of the Australian Macroeconomics Society and the 2015 International Meeting of the Western Economic Association and seminars at the Reserve Bank of New Zealand, the Australian National University and the Victoria University of Wellington for helpful comments and suggestions. All errors and omissions are our responsibility. The views expressed do not necessarily reflect those of the Reserve Bank of New Zealand.

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Supplemental Material:

The online version of this article (DOI: 10.1515/snde-2015-0030) offers supplementary material, available to authorized users.

Published Online: 2015-10-17
Published in Print: 2016-4-1

©2016 by De Gruyter

Articles in the same Issue

  1. Frontmatter
  2. Testing cointegration in quantile regressions with an application to the term structure of interest rates
  3. Multi-criteria classification for pricing European options
  4. Structural VARs, deterministic and stochastic trends: how much detrending matters for shock identification
  5. Common time variation of parameters in reduced-form macroeconomic models
  6. Equilibrium pricing of currency options under a discontinuous model in a two-country economy
  7. Revisiting the statistical specification of near-multicollinearity in the logistic regression model
https://doi.org/10.1515/snde-2015-0030
Keywords for this article
bias; detrending; identification; structural VAR

Articles in the same Issue

  1. Frontmatter
  2. Testing cointegration in quantile regressions with an application to the term structure of interest rates
  3. Multi-criteria classification for pricing European options
  4. Structural VARs, deterministic and stochastic trends: how much detrending matters for shock identification
  5. Common time variation of parameters in reduced-form macroeconomic models
  6. Equilibrium pricing of currency options under a discontinuous model in a two-country economy
  7. Revisiting the statistical specification of near-multicollinearity in the logistic regression model
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