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 retired from the U. S. Census Bureau.
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
