Abstract Details
Activity Number:
|
119
|
Type:
|
Topic Contributed
|
Date/Time:
|
Monday, August 5, 2013 : 8:30 AM to 10:20 AM
|
Sponsor:
|
Business and Economic Statistics Section
|
Abstract - #308872 |
Title:
|
An Appraisal of Multivariate Seasonal Adjustment
|
Author(s):
|
Tucker S. McElroy*+
|
Companies:
|
U.S. Census Bureau
|
Keywords:
|
Signal extraction ;
Dynamic factor models ;
Vector time series ;
Trends ;
Seasonality
|
Abstract:
|
There has been persistent interest among economists for statistical agencies to research and implement a multivariate seasonal adjustment procedure. Recent advances in vector time series modeling -- including dynamic factor models and vector structural time series models -- make such a project possible. Our research first examines the dimension reduction techniques available, and how the resulting lower-dimensional factor time series can be jointly modeled. Several approaches are developed and discussed, allowing for an X-11 type of treatment, based upon forecast extension with a fixed moving average filter, as well as a fully model-based treatment. Practical issues, such as model identification and estimation, are also discussed, and the proposed methods are tested upon Census Bureau retail, manufacturing, and construction series.
|
Authors who are presenting talks have a * after their name.
Back to the full JSM 2013 program
|
2013 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Continuing Education program, please contact the Education Department.
The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Copyright © American Statistical Association.