SSE/EFI Working Paper Series in Economics and Finance
No 418:
On seasonal error correction when the processes include different numbers of unit roots
Johan Lyhagen ()
and Mårten Löf ()
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.
Keywords: Seasonal cointegration; forecasting; (follow links to similar papers)
JEL-Codes: C32; C53; (follow links to similar papers)
17 pages, December 13, 2000, Revised March 15, 2001
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