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On seasonal error correction when the processes include different numbers of unit roots

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  • Lyhagen, Johan

    ()
    (Dept. of Economic Statistics, Stockholm School of Economics)

  • Löf, Mårten

    ()
    (Dept. of Economic Statistics, Stockholm School of Economics)

Abstract

We propose a seasonal cointegration model [SECM] for quarterly data which includes variables with different numbers of unit roots and thus needs to be transformed in different ways in order to yield stationarity. A Monte Carlo simulation is carried out to investigate the consequences of specifying a SECM with all variables in annual diffrerences in this situation. The SECM in annual differences is compared to the correctly specified model. Pre-testing for unit roots using two different approaches, and where the models are specified according to the unit root test results, is also considered. The forecast mean squared error criterion and certain parameter estimation results indicate that, in practice, a cointegration model where all variables are transformed with the annual difference filter is more robust than one obtained by pre-testing for a smaller number of unit roots. The second best choice, when the true model is not known and when the aim is to forecast, is an ordinary VAR model, also in annual differences.

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Bibliographic Info

Paper provided by Stockholm School of Economics in its series Working Paper Series in Economics and Finance with number 0418.

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Length: 17 pages
Date of creation: 13 Dec 2000
Date of revision: 15 Mar 2001
Handle: RePEc:hhs:hastef:0418

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Keywords: Seasonal cointegration; forecasting;

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Cited by:
  1. Carmine Pappalardo & Gianfranco Piras, 2004. "Vector-Autoregression Approach to Forecast Italian Imports," ISAE Working Papers 42, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).

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