However, I'm still having some issues using the FD filter. Thanks for the excellent suggestion, Trubador! The Frequency-Domain (FD) filter by Corbae and Ouliaris seems to perform much better than an HP/BK/CF filter, all of which suffer from end-point problems. Any advice on this topic would also be appreciated. Yet, there are no references to what a reasonably large or small value of lambda might be - no rule of thumb, if you will. Any suggestions?Īdditionally, some of the literature references the double HP filter in which a large and then small value of lambda are used (to detrend and then smooth, respectively). It is unclear to me how to change this in EViews, at least using the menu commands (I'm afraid I'm not terribly experienced in using code). However, research suggests using a wider window of 12-120 months (see the OECD Methodology for Cycle Extraction). If I understand correctly, the HP filter uses default cut-off values of 18-96. I struggle to understand how to determine the ideal window-length, however. Harvey and Trimbur (2008) explain the risk in using a too-small smoothing parameter (lambda), though I have yet to find research explaining the risk of using too-large of a smooth parameter, other than the trend becomes increasingly linear and less sensitive to recent data. There is additional research that suggests using a power of 4 instead of 2. Lambda = 100*(number of periods in a year)^2
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