JSM 2004 - Toronto

Abstract #300804

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Activity Number: 178
Type: Topic Contributed
Date/Time: Tuesday, August 10, 2004 : 8:30 AM to 10:20 AM
Sponsor: Business and Economics Statistics Section
Abstract - #300804
Title: Variance Estimation for X11 via Model-based Spectral Approach under Additive and Multiplicative Decompositions
Author(s): Zhao-Guo Chen*+
Companies: Statistics Canada
Address: 17-H, R.H.Coats Bldg., Ottawa, ON, K1A 0T6, Canada
Keywords: seasonal adjustment ; component of time series ; spectral density ; autocovariance
Abstract:

The X-11 seasonal adjustment procedures and its enhancements, X-11-ARIMA and X-12-ARIMA, have been widely used throughout the world. A long-standing problem is how to estimate the variances of the errors of the output components. Statisticians have proposed some solutions, but they are lack of reliability in real applications. Following Pfeffermann (1994), Pfeffermann and Scott (1997), and Pfeffermann, Morry, and Wong (1995), who provided with solutions via the moment approach, we proposed some procedures for estimating these variances via the model-based spectrum approach under the additive and the multiplicative decompositions. Many advantages of the spectrum approach are demonstrated by simulation and the procedures are tested by using some Labour Force Survey series and Wholesale Trade series.

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