Seasonal adjusters need to know when a time series candidate for
seasonal adjustment has trading day effects and when its adjustment
for trading day effects has failed to adequately remove these
effects. The Census Bureau's X-12-ARIMA seasonal adjustment program
calculates several spectra in order to facilitate detection of
seasonal and trading day effects that require the adjuster's
attention. This paper summarizes the results of a study based on
real and simulated time series that led to the current choices made
for X-12-ARIMA's trading day spectral diagnostics, including the
criteria for warning messages. The features and advantages of the
spectrum of the model residuals, which is a new addition to
X-12-ARIMA output, are described.
Seasonal Adjustment, Trading day, Spectral analysis, Time
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