Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/107640
Authors: 
Leschinski, Christian
Sibbertsen, Philipp
Year of Publication: 
2014
Series/Report no.: 
Discussion Paper, Wirtschaftswissenschaftliche Fakultät, Leibniz University of Hannover 535
Abstract: 
We propose an automatic model order selection procedure for k-factor GARMA processes. The procedure is based on sequential tests of the maximum of the periodogram and semiparametric estimators of the model parameters. As a byproduct, we introduce a generalized version of Walker's large sample g-test that allows to test for persistent periodicity in stationary ARMA processes. Our simulation studies show that the procedure performs well in identifying the correct model order under various circumstances. An application to Californian electricity load data illustrates its value in empirical analyses and allows new insights into the periodicity of this process that has been subject of several forecasting exercises.
Subjects: 
Seasonal Long Memory
k-factor GARMA processes
Model selection
Electricity loads
JEL: 
C22
C52
Document Type: 
Working Paper

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