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VARs, Cointegration and Common Cycle Restrictions

  • Heather M Anderson

    ()

  • Farshid Vahid

    ()

This paper argues that VAR models with cointegration and common cycles can be usefully viewed as observable factor models. The factors are linear combinations of lagged levels and lagged differences, and as such, these observable factors have potential for forecasting. We illustrate this forecast potential in both a Monte Carlo and empirical setting, and demonstrate the difficulties in developing forecasting "rules of thumb" for forecasting in multivariate systems.

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File URL: http://www.buseco.monash.edu.au/ebs/pubs/wpapers/2010/wp14-10.pdf
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Paper provided by Monash University, Department of Econometrics and Business Statistics in its series Monash Econometrics and Business Statistics Working Papers with number 14/10.

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Length: 50 pages
Date of creation: May 2010
Date of revision:
Handle: RePEc:msh:ebswps:2010-14
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  24. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
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