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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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  1. Athanasopoulos, George & Guillén, Osmani Teixeira de Carvalho & Issler, João Victor & Vahid, Farshid, 2010. "Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions," Economics Working Papers (Ensaios Economicos da EPGE) 704, FGV/EPGE Escola Brasileira de Economia e Finanças, Getulio Vargas Foundation (Brazil).
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  26. Engle, Robert F & Granger, Clive W J, 1987. "Co-integration and Error Correction: Representation, Estimation, and Testing," Econometrica, Econometric Society, vol. 55(2), pages 251-76, March.
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  28. Christopher A. Sims & Tao Zha, 1996. "Bayesian methods for dynamic multivariate models," Working Paper 96-13, Federal Reserve Bank of Atlanta.
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  31. Aznar, Antonio & Salvador, Manuel, 2002. "Selecting The Rank Of The Cointegration Space And The Form Of The Intercept Using An Information Criterion," Econometric Theory, Cambridge University Press, vol. 18(04), pages 926-947, August.
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