IGARCH effect on autoregressive lag length selection and causality tests
Using Monte Carlo experiments, we show how information criteria determine, in the presence of GARCH errors, an optimal lag length in univariate time series and causality tests. We illustrate the simulations by testing the presence of serial correlation in exchange rates as well as Granger-causality between interest rates.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 3 (1996)
Issue (Month): 5 ()
|Contact details of provider:|| Web page: http://www.tandfonline.com/RAEL20|
|Order Information:||Web: http://www.tandfonline.com/pricing/journal/RAEL20|