Experiences With Indirect Seasonal Adjustment
Kathleen M. McDonald-Johnson, Catherine C. Harvill Hood, Roxanne Feldpausch
U.S. Census Bureau, HENDYPLAN Luxembourg, U.S. Census Bureau
kathleen.m.mcdonald.johnson@census.gov
Abstract
Many published seasonally adjusted series are composites
of individual seasonally adjusted series: for instance,
subcategories sum to main categories and regions sum to
the U.S. total. Many seasonal adjusters who publish these
indirect totals use seasonal adjustment programs to adjust
the individual series and then combine them using
separate software. The U.S. Census Bureau uses
X-12-ARIM A
to perform seasonal
adjustment.
X-12-ARIMA, like X-11-ARIMA before it, has the
capability to combine adjusted series and provide indirect
adjustment diagnostics that are not available when the
individual adjustments are combined using outside
programs. Further expansions to the program will allow
users to perform model-based seasonal decomposition as
well as the traditional moving-average method of X-11.
We investigated the issues involved when performing
indirect
seasonal
adjustments under different
circumstances including subjective prior adjustments for
individual series and totals with mixed decomposition
types (multiplicative vs. additive and semiparametric vs.
model-based adjustments). From our experiences we
describe what users should know before performing
indirect seasonal adjustment.
Keywords: RegARIMA model, Time series
1. Background and Motivation
X-12-ARIMA is the latest U.S. Census Bureau seasonal
adjustment program (Findley, Monsell, Bell, Otto, and
Chen 1998, U.S. Census Bureau 2002). It follows
X-11 (Shiskin, Young, and Musgrave 1967) and
X-11-ARIMA and its later developments from Statistics
Canada (Dagum 1980, 1988). The Census Bureau is
preparing to release new features in a program that in this
paper we will call X-13 (U.S. Census Bureau 2005).
Features such as the sliding spans (Findley, Monsell,
Shulman, and Pugh 1990) and revision history diagnostics
that we used