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Title:On seasonal error correction when the processes include different numbers of unit roots PDF Logo
Authors:Lyhagen, Johan
Löf, Mårten
Issue Date:2001
Series/Report no.:SSE/EFI Working Paper Series in Economics and Finance 418
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.
Subjects:Seasonal cointegration
forecasting
JEL:C32
C53
Document Type:Working Paper
Appears in Collections:SSE/EFI Working Paper Series in Economics and Finance, EFI - The Economic Research Institute, Stockholm School of Economics

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