Generalized Impulse Response Analysis: General or Extreme?
AbstractThis note discusses a pitfall of using the generalized impulse response function (GIRF) in vector autoregressive (VAR) models (Pesaran and Shin, 1998). The GIRF is general because it is invariant to the ordering of the variables in the VAR. The GIRF, in fact, is extreme because it yields a set of response functions that are based on extreme identifying assumptions that contradict each other, unless the covariance matrix is diagonal. With an empirical example, the present note demonstrates that the GIRF may yield quite misleading economic inferences.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 17014.
Date of creation: Apr 2009
Date of revision:
Generalized Impulse Response Function; Orthogonalized Impulse Response Function; Vector Autoregressive Models;
Other versions of this item:
- Hyeongwoo Kim, 2012. "Generalized Impulse Response Analysis: General or Extreme?," Auburn Economics Working Paper Series auwp2012-04, Department of Economics, Auburn University.
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
This paper has been announced in the following NEP Reports:
- NEP-ALL-2009-09-05 (All new papers)
- NEP-ECM-2009-09-05 (Econometrics)
- NEP-ETS-2009-09-05 (Econometric Time Series)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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