A Nonparametric Test for Assessing Spectral Peaks
Tucker S. McElroy and Scott Holan
KEY WORDS: seasonal adjustment, spectral density, nonparametric kernel methods
ABSTRACT
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.
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