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Effects of Forecasts on the Revisions of Concurrent Seasonally Adjusted Data using the X-11 Seasonal Adjustment Procedure
Effects of Forecasts on the Revisions of Concurrent Seasonally Adjusted Data using the X-11 Seasonal Adjustment Procedure
Working Paper Number RR90-09
Abstract
Three ARIMA forecast extension procedures for Census Bureau X-11 concurrent seasonal adjustment were empirically tested. Forecasts were obtained from fitted seasonal ARIMA models augmented with regression terms for outliers, trading day effects, and Easter effects. Revisions between initial and final seasonally adjusted values were computed. Ranked ANOVAs were used on various revision measures to determine the statistical significance of the differences between the extension procedures. The main conclusion was that extending the series with enough forecasts to apply a symmetric filter reduced the revisions over not extending the series and using asymmetric filters. This result held whether the model used was one carefully fit by the analyst or was a simple default model. Extension of the series with only one year of forecasts was also examined.
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Statistical Research Reports and Studies
Page Last Revised - October 28, 2021
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