VAR Modeling and Business Cycle Analysis: A Taxonomy of Errors
In this article we investigate the theoretical behaviour of finite lag VAR(n) models fitted to time series that in truth come from an infinite order VAR(?) data generating mechanism. We show that overall error can be broken down into two basic components, an estimation error that stems from the difference between the parameter estimates and their population ensemble VAR(n) counterparts, and an approximation error that stems from the difference between the VAR(n) and the true VAR(?). The two sources of error are shown to be present in other performance indicators previously employed in the literature to characterize, so called, truncation effects. Our theoretical analysis indicates that the magnitude of the estimation error exceeds that of the approximation error, but experimental results based upon a prototypical real business cycle model indicate that in practice the approximation error approaches its asymptotic position far more slowly than does the estimation error, their relative orders of magnitude notwithstanding. The experimental results suggest that with sample sizes and lag lengths like those commonly employed in practice VAR(n) models are likely to exhibit serious errors of both types when attempting to replicate the dynamics of the true underlying process and that inferences based on VAR(n) models can be very untrustworthy.
|Date of creation:||19 Apr 2012|
|Date of revision:|
|Contact details of provider:|| Postal: |
Phone: +61 3 99052489
Fax: +61 3 99055474
Web page: http://business.monash.edu/econometrics-and-business-statistics
More information through EDIRC
|Order Information:|| Web: http://business.monash.edu/econometrics-and-business-statistics Email: |
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.:
- Christopher Erceg & Luca Guerrieri & Christopher Gust, 2004.
"Can long-run restrictions identify technology shocks?,"
International Finance Discussion Papers
792, Board of Governors of the Federal Reserve System (U.S.).
- Christopher J. Erceg & Luca Guerrieri & Christopher Gust, 2005. "Can Long-Run Restrictions Identify Technology Shocks?," Journal of the European Economic Association, MIT Press, vol. 3(6), pages 1237-1278, December.
- Christopher J. Erceg & Luca Guerrieri, 2004. "Can Long-Run Restrictions Identify Technology Shocks?," Computing in Economics and Finance 2004 3, Society for Computational Economics.
- Marco Lippi & Lucrezia Reichlin, 1994.
"VAR analysis, non-fundamental representations, Blashke matrices,"
ULB Institutional Repository
2013/10151, ULB -- Universite Libre de Bruxelles.
- Lippi, Marco & Reichlin, Lucrezia, 1994. "VAR analysis, nonfundamental representations, blaschke matrices," Journal of Econometrics, Elsevier, vol. 63(1), pages 307-325, July.
- Mittnik, Stefan, 1987. "Non-recursive methods for computing the coefficients of the autoregressive and the moving-average representation of mixed ARMA processes," Economics Letters, Elsevier, vol. 23(3), pages 279-284.
- Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2006.
"Assessing structural VARs,"
International Finance Discussion Papers
866, Board of Governors of the Federal Reserve System (U.S.).
- Christian Kascha & Karel Mertens, 2006.
"Business Cycle Analysis and VARMA models,"
Economics Working Papers
ECO2006/37, European University Institute.
- Kapetanios, G. & Pagan, A. & Scott, A., 2007.
"Making a match: Combining theory and evidence in policy-oriented macroeconomic modeling,"
Journal of Econometrics,
Elsevier, vol. 136(2), pages 565-594, February.
- Alasdair Scott & George Kapetanios & Adrian Pagan, 2005. "Making a match: combining theory and evidence in policy-oriented macroeconomic modelling," Computing in Economics and Finance 2005 462, Society for Computational Economics.
- Poskitt, Don S, 2000. "Strongly Consistent Determination of Cointegrating Rank via Canonical Correlations," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(1), pages 77-90, January.
When requesting a correction, please mention this item's handle: RePEc:msh:ebswps:2012-11. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dr Xibin Zhang)
If references are entirely missing, you can add them using this form.