New Capabilities and Methods of the X-12-ARIMA Seasonal Adjustment Program (1)
David F. Findley (2),
Brian C. Monsell (3),
William R. Bell (4),
Mark C. Otto (5) and
Bor-Chung Chen (6)
ABSTRACT:
X-12-ARIMA is the Census Bureau's new seasonal adjustment
program. It provides four types of enhancements to X-11-ARIMA:
- Alternative seasonal, trading day, and holiday effect
adjustment capabilities that include adjustments for effects
estimated with user-defined regressors, additional seasonal and
trend filter options, and an alternative seasonal-trend-irregular
decomposition.
- New diagnostics of the quality and stability of the adjustments
achieved under the options selected.
- Extensive time series modeling and model selection capabilities
for linear regression models with ARIMA errors, with optional
robust estimation of coefficients.
- A new user interface with features to facilitate batch
processing large numbers of series.
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Preprint
version, without comments and rejoinder, of article in Journal of
Business and Economic Statistics, vol. 16 (1998), No. 2, pp.
127-157
David F. Findley is formerly the Senior Mathematical Statistican for Time Series and now a consultant,
U. S. Census Bureau, 4600 Silver Hill Road, Washington,
DC 20233. email :
david.f.findley@census.gov
Brian
C. Monsell is Mathematical Statistican, Statistical Research
Division, U. S. Census Bureau, 4600 Silver Hill Road,
Washington, DC 20233. email :
brian.c.monsell@census.gov
William
R. Bell is Senior Mathematical Statistician for Small Area
Estimation, U. S. Census Bureau, 4600 Silver Hill Road,
Washington, DC 20233. email :
william.r.bell@census.gov
Mark C.
Otto is Mathematical Statistician, U. S. Fish and Wildlife
Service, 11500 American Holly Drive, Laurel, MD 20708-4016 email :
mark_otto@fws.gov
Bor
Chung-Chen is Mathematical Statistician, Statistical Research
Division, U. S. Census Bureau, 4600 Silver Hill Road,
Washington, DC 20233. email :
bor.chung.hilary.chen@census.gov
