Estimating Variance in X-11 Seasonal Adjustment

Authored by: Stuart Scott , Danny Pfeffermann , Michail Sverchkov

Economic Time Series

Print publication date:  March  2012
Online publication date:  March  2012

Print ISBN: 9781439846575
eBook ISBN: 9781439846582
Adobe ISBN:

10.1201/b11823-12

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Abstract

Obtaining measures of uncertainty for seasonal adjustment is a long-standing problem (President’s Committee to Appraise Employment and Unemployment statistics, 1962). Wolter and Monsour (1981) propose two variance measures for X-11 seasonal adjustment that account for sampling error (SE), one better suited for the typical case of nonstationary time series. Pfeffermann (1994) and Bell and Kramer (1999) develop measures capturing additional uncertainty. Pfeffermann, Morry, and Wong (1995) apply the Pfeffermann method with ARIMA (autoregressive-integrated-moving average) extrapolation and the multiplicative mode of adjustment. Pfeffermann and Scott (1997) further extend the method by proposing modifications that use all the X-11 irregular terms, not just the central ones, and simplify the equations for estimating the error variances when SE autocovariances are available. Scott, Sverchkov, and Pfeffermann (2005) treat month-to-month change where the series are similar to many index series.

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