The X12 Procedure
- Overview
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Getting Started
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SyntaxFunctional SummaryPROC X12 StatementADJUST StatementARIMA StatementAUTOMDL StatementBY StatementCHECK StatementESTIMATE StatementEVENT StatementFORECAST StatementID StatementIDENTIFY StatementINPUT StatementOUTLIER StatementOUTPUT StatementPICKMDL StatementREGRESSION StatementSEATSDECOMP StatementTABLES StatementTRANSFORM StatementUSERDEFINED StatementVAR StatementX11 Statement
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DetailsData RequirementsMissing ValuesSAS Predefined EventsUser-Defined Regression VariablesCombined Test for the Presence of Identifiable SeasonalityComputationsPICKMDL Model SelectionSEATS DecompositionDisplayed Output, ODS Table Names, and OUTPUT Tablename KeywordsUsing Auxiliary Variables to Subset Output Data SetsODS GraphicsOUT= Data SetSEATSDECOMP OUT= Data SetSpecial Data Sets
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ExamplesARIMA Model IdentificationModel EstimationSeasonal AdjustmentRegARIMA Automatic Model SelectionAutomatic Outlier DetectionUser-Defined RegressorsMDLINFOIN= and MDLINFOOUT= Data SetsSetting Regression ParametersCreating an MDLINFO= Data Set for Use with the PICKMDL StatementIllustration of ODS GraphicsAUXDATA= Data Set
- References
EVENT Statement
EVENT variables < / options > ;
The EVENT statement specifies events to be included in the regression portion of the regARIMA model. Multiple EVENT statements can be specified. Dummy variable values for EVENT variables are generated by the X12 procedure, however, the EVENT variables are input as user-defined regression effects to the X-12-ARIMA method. Thus, the EVENT variables are treated in the same manner as it treats variables specified in the USERVAR= option in the REGRESSION statement. If a MDLINFOIN= data set is not specified in the PROC X12 statement, then all variables specified in the EVENT statements are applied to all BY groups and all time series that are processed. If a MDLINFOIN= data set is specified, then the EVENT statements apply only if no regression information for the BY group and series is available in the MDLINFOIN= data set. The events specified in the EVENT statements either must be SAS predefined events or must be defined in the data set specified in the INEVENT= option in the PROC X12 statement. For a summary of SAS predefined events, see the section SAS Predefined Events.
The EVENT statement can also be used to include outlier, level shift, and temporary change regressors that are available as predefined U.S. Census Bureau variables in the X-12-ARIMA program. For example, the following statements specify an additive outlier in January 1970 and a level shift that begins in July 1971:
proc x12 data=ICMETI seasons=12 start=jan1968;
event AO01JAN1970D CBLS01JUL1971D;
The following statements specify an additive outlier in the second quarter 1970 and a temporary change that begins in the fourth quarter 1971:
proc x12 data=ICMETI seasons=4 start='1970q1';
event AO01APR1970D TC01OCT1971D;
The following options can appear in the EVENT statement:
- B=(value <F> …)
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specifies initial or fixed values for the EVENT parameters in the order in which they appear in variables. Each B= list applies to the variable list that immediately precedes the slash.
For example, the following statements set an initial value of 1 for the event,
x:event y ; event x / b=1 2 ;
In this example, the B= option applies only to the second EVENT statement. The value 2 is discarded because there is only one variable in the variable list.
To assign an initial value of 1 to the
yregressor and 2 to thexregressor, use the following statements:event y / b=1; event x / b=2 ;
An F immediately following the numerical value indicates that this is not an initial value, but a fixed value. See Example 38.8 for an example that uses fixed parameters. In PROC X12, individual parameters can be fixed while other parameters in the same model are estimated.
- USERTYPE=(values)
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enables a user-defined variable to be processed in the same manner as a U.S. Census predefined variable. You can specify the following values: AO, CONSTANT, EASTER, HOLIDAY, LABOR, LOM, LOMSTOCK, LOQ, LPYEAR, LS, RP, SCEASTER, SEASONAL, TC, TD, TDSTOCK, THANKS, or USER. For example, the U.S. Census Bureau EASTER(
) regression effects are included the “RegARIMA Holiday Component” table (A7). Specify USERTYPE=EASTER to include an event variable that is processed exactly as the U.S. Census predefined
EASTER() variable, including inclusion in the A7 table. The NOAPPLY= option in the REGRESSION statement also changes the processing of variables based on the USERTYPE= value. Table 38.4 shows the regression types that are associated with each regression effects table.
Each USERTYPE= list applies to the variable list that immediately precedes the slash. The same rules for assigning B= values to regression variables apply for USERTYPE= options. For example, the following statements specify that the event in the variable
MyEasterbe processed exactly as the U.S. Census predefined LOM variable:event MyLOM; event MyEaster / usertype=LOM EASTER;
In this example, the USERTYPE= option applies only to the
MyEastervariable in the second EVENT statement. The USERTYPE value EASTER is discarded because there is only one variable in the variable list.To assign the USERTYPE value LOM to the
MyLOMvariable and EASTER to theMyEastervariable, use the following statements:event MyLOM / usertype=LOM; event MyEaster / usertype=EASTER;
The following USERTYPE= options specify that the regression effect be removed from the seasonally adjusted series: EASTER, HOLIDAY, LABOR, LOM, LOMSTOCK, LOQ, LPYEAR, SCEASTER, SEASONAL, TD, TDSTOCK, THANKS, and USER. When a regression effect is removed from the seasonally adjusted series, the level (mean) of the seasonally adjusted series can be altered. It is often desirable to use a zero-mean (mean-adjusted) regressor for effects that are to be removed from the seasonally adjusted series. See Example 38.6 for an example showing the effects of specifying a zero-mean regressor.