Peaks in the spectrum of a stationary process are indicative of the presence of a periodic phenomenon, such as a seasonal effect or business cycle. This work proposes to measure and test for the presence of such spectral peaks via assessing their aggregate acceleration and velocity. Our method is developed nonparametrically, and thus may be useful in a preliminary analysis of a series. The technique is also useful for detecting the presence of residual seasonality in seasonally adjusted data. The diagnostic is investigated through simulation and two data examples.
seasonal adjustment, spectral density, nonparametric kernel methods
(2) Scott Holan is a professor in the Department of Statistics, University of Missouri-Columbia.
This symbol indicates a link to a non-government web site. Our linking to these sites does not constitute an endorsement of any products, services or the information found on them. Once you link to another site you are subject to the policies of the new site.