The VARMAX Procedure

OUTEST= Data Set

The OUTEST= data set contains estimation results of the fitted model produced by the VARMAX statement. The following output variables can be created:

the BY variables
NAME, a character variable that contains the name of endogenous (dependent) variables or the name of the parameters for the covariance of the matrix of the parameter estimates if the OUTCOV option is specified
TYPE, a character variable that contains the value EST for parameter estimates, the value STD for standard error of parameter estimates, and the value COV for the covariance of the matrix of the parameter estimates if the OUTCOV option is specified
CONST, a numeric variable that contains the estimates of constant parameters and their standard errors
SEASON $\_ i$ , a numeric variable that contains the estimates of seasonal dummy parameters and their standard errors, where $i=1,\ldots , (nseason-1)$ , and is based on the NSEASON= option
LTREND, a numeric variable that contains the estimates of linear trend parameters and their standard errors
QTREND, a numeric variable that contains the estimates of quadratic trend parameters and their standard errors
XL $l\_ i$ , numeric variables that contain the estimates of exogenous parameters and their standard errors, where is the lag th coefficient matrix and $i=1,\ldots , r$ , where is the number of exogenous variables
AR $l\_ i$ , numeric variables that contain the estimates of autoregressive parameters and their standard errors, where is the lag th coefficient matrix and $i=1,\ldots , k$ , where is the number of endogenous variables
MA $l\_ i$ , numeric variables that contain the estimates of moving-average parameters and their standard errors, where is the lag th coefficient matrix and $i=1,\ldots , k$ , where is the number of endogenous variables
ACH $l\_ i$ are numeric variables that contain the estimates of the ARCH parameters of the covariance matrix and their standard errors, where is the lag th coefficient matrix and $i=1,\ldots , k$ for BEKK and CCC representations, where is the number of endogenous variables.
GCH $l\_ i$ are numeric variables that contain the estimates of the GARCH parameters of the covariance matrix and their standard errors, where is the lag th coefficient matrix and $i=1,\ldots , k$ for BEKK and CCC representations, where is the number of endogenous variables.
GCHC $\_ i$ are numeric variables that contain the estimates of the constant parameters of the covariance matrix and their standard errors, where $i=1,\ldots , k$ for BEKK representation, is the number of endogenous variables, and for CCC representation.
CCC $\_ i$ are numeric variables that contain the estimates of the conditional constant correlation parameters for CCC representation where $i=2,\ldots , k$ .

The OUTEST= data set contains the values shown Table 36.5 for a bivariate case.

Table 36.5: OUTEST= Data Set

Obs	NAME	TYPE	CONST	AR1_1	AR1_2	AR2_1	AR2_2
1	y1	EST	$\delta _1$	$\phi _{1,11}$	$\phi _{1,12}$	$\phi _{2,11}$	$\phi _{2,12}$
2		STD	se( $\delta _1$ )	se( $\phi _{1,11}$ )	se( $\phi _{1,12}$ )	se( $\phi _{2,11}$ )	se( $\phi _{2,12}$ )
3	y2	EST	$\delta _2$	$\phi _{1,21}$	$\phi _{1,22}$	$\phi _{2,21}$	$\phi _{2,22}$
4		STD	se( $\delta _2$ )	se( $\phi _{1,21}$ )	se( $\phi _{1,22}$ )	se( $\phi _{2,21}$ )	se( $\phi _{2,22}$ )

Consider the following example:

proc varmax data=simul2 outest=est;
   model y1 y2 / p=2 noint
                 ecm=(rank=1 normalize=y1)
                 noprint;
run;

proc print data=est;
run;

The output in Figure 36.67 shows the results of the OUTEST= data set.

Figure 36.67: OUTEST= Data Set

Obs	NAME	TYPE	AR1_1	AR1_2	AR2_1	AR2_2
1	y1	EST	-0.46680	0.91295	-0.74332	-0.74621
2		STD	0.04786	0.09359	0.04526	0.04769
3	y2	EST	0.10667	-0.20862	0.40493	-0.57157
4		STD	0.05146	0.10064	0.04867	0.05128