PROC VARMAX: OUTSTAT= Data Set :: SAS/ETS(R) 9.22 User's Guide

The VARMAX Procedure

OUTSTAT= Data Set

The OUTSTAT= data set contains estimation results of the fitted model produced by the VARMAX statement. The following output variables can be created. The subindex $\text{[math]}$ is $\text{[math]}$ , where $\text{[math]}$ is the number of endogenous variables.

the BY variables
NAME, a character variable that contains the name of endogenous (dependent) variables
SIGMA $\text{[math]}$ , numeric variables that contain the estimate of the innovation covariance matrix
AICC, a numeric variable that contains the corrected Akaike’s information criterion value
HQC, a numeric variable that contains the Hannan-Quinn’s information criterion value
AIC, a numeric variable that contains the Akaike’s information criterion value
SBC, a numeric variable that contains the Schwarz Bayesian’s information criterion value
FPEC, a numeric variable that contains the final prediction error criterion value
FValue, a numeric variable that contains the $\text{[math]}$ statistics
PValue, a numeric variable that contains $\text{[math]}$ -value for the $\text{[math]}$ statistics

If the JOHANSEN= option is specified, the following items are added:

Eigenvalue, a numeric variable that contains eigenvalues for the cointegration rank test of integrated order 1
RestrictedEigenvalue, a numeric variable that contains eigenvalues for the cointegration rank test of integrated order 1 when the NOINT option is not specified
Beta $\text{[math]}$ , numeric variables that contain long-run effect parameter estimates, $\text{[math]}$
Alpha $\text{[math]}$ , numeric variables that contain adjustment parameter estimates, $\text{[math]}$

If the JOHANSEN=(IORDER=2) option is specified, the following items are added:

EValueI2 $\text{[math]}$ , numeric variables that contain eigenvalues for the cointegration rank test of integrated order 2
EValueI1, a numeric variable that contains eigenvalues for the cointegration rank test of integrated order 1
Eta $\text{[math]}$ , numeric variables that contain the parameter estimates in integrated order 2, $\text{[math]}$
Xi $\text{[math]}$ , numeric variables that contain the parameter estimates in integrated order 2, $\text{[math]}$

The OUTSTAT= data set contains the values shown Table 32.7 for a bivariate case.

Table 32.7 OUTSTAT= Data Set
Obs	NAME	SIGMA_1	SIGMA_2	AICC	RSquare	FValue	PValue
1	y1	$\text{[math]}$	$\text{[math]}$	$\text{[math]}$	$\text{[math]}$	$\text{[math]}$	$\text{[math]}$
2	y2	$\text{[math]}$	$\text{[math]}$	.	$\text{[math]}$	$\text{[math]}$	$\text{[math]}$

Obs	EValueI2_1	EValueI2_2	EValueI1	Beta_1	Beta_2
1	$\text{[math]}$	$\text{[math]}$	$\text{[math]}$	$\text{[math]}$	$\text{[math]}$
2	$\text{[math]}$	.	$\text{[math]}$	$\text{[math]}$	$\text{[math]}$

Obs	Alpha_1	Alpha_2	Eta_1	Eta_2	Xi_1	Xi_2
1	$\text{[math]}$	$\text{[math]}$	$\text{[math]}$	$\text{[math]}$	$\text{[math]}$	$\text{[math]}$
2	$\text{[math]}$	$\text{[math]}$	$\text{[math]}$	$\text{[math]}$	$\text{[math]}$	$\text{[math]}$

Consider the following example:

proc varmax data=simul2 outstat=stat;
   model y1 y2 / p=2 noint
                 cointtest=(johansen=(iorder=2))
                 ecm=(rank=1 normalize=y1)
                 noprint;
run;

proc print data=stat;
run;

The output in Figure 32.69 shows the results of the OUTSTAT= data set.

Figure 32.69 OUTSTAT= Data Set

Obs	NAME	SIGMA_1	SIGMA_2	AICC	HQC	AIC	SBC	FPEC	RSquare	FValue	PValue	EValueI2_1	EValueI2_2	EValueI1	Beta_1	Beta_2	Alpha_1	Alpha_2	Eta_1	Eta_2	Xi_1	Xi_2
1	y1	94.7557	4.527	9.37221	9.43236	9.36834	9.52661	11712.14	0.93900	482.308	6.1637E-57	0.98486	0.95079	0.50864	1.00000	1.00000	-0.46680	0.007937	-0.012307	0.027030	54.1606	-52.3144
2	y2	4.5268	109.570	.	.	.	.	.	0.93912	483.334	5.6124E-57	0.81451	.	0.01108	-1.95575	-1.33622	0.10667	0.033530	0.015555	0.023086	-79.4240	-18.3308

Top of Page