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pap
Calcite | Level 5 pap
Calcite | Level 5

Hi – I want to run a time-series linear regression model with time-varying betas using the SSM approach (see attached for equations). The dependent variable is stationary (through differencing). I looked into SAS PROC SSM but I am not clear of the right syntax to use. Given the expertise in this community, I thought you may have a quick answer to my question. I would greatly appreciate your help. I am using SAS v 9.4 on Windows 10.

 

Regards, -Pappe

1 ACCEPTED SOLUTION

Accepted Solutions
rselukar
SAS Employee

You can easily do this in SSM.  However you must lag your C variables prior to using them in the SSM procedure (in a DATA step).  Even though SSM procedure permits DATA step statements, the LAG and DIF operations are not permitted.  Suppose X = Lag( C ) and there are three X variables X1 X2 X3 (so beta is three dimensional).  Then you can use the following syntax:

 

Proc ssm data=test;

   State beta(3) type=rw cov(g); /* this assumes epsilon_t is three dimensional noise with full covariance */

   Comp regEffect = (X1 X2 X3)*beta;

   Irregular eta;

   Model y = regEffect eta;

Run;

 

I have shown syntax for univariate Y.  Your Y can be multivariate.  You will need to read the SSM syntax and DOC examples for these more involved cases.  For univariate Y you can also use the RANDOMREG statement in PROC UCM, which might be even easier.

 

See SSM and UCM procedure docs at http://support.sas.com/documentation/onlinedoc/ets/indexproc.html#ets143

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1 REPLY 1
rselukar
SAS Employee

You can easily do this in SSM.  However you must lag your C variables prior to using them in the SSM procedure (in a DATA step).  Even though SSM procedure permits DATA step statements, the LAG and DIF operations are not permitted.  Suppose X = Lag( C ) and there are three X variables X1 X2 X3 (so beta is three dimensional).  Then you can use the following syntax:

 

Proc ssm data=test;

   State beta(3) type=rw cov(g); /* this assumes epsilon_t is three dimensional noise with full covariance */

   Comp regEffect = (X1 X2 X3)*beta;

   Irregular eta;

   Model y = regEffect eta;

Run;

 

I have shown syntax for univariate Y.  Your Y can be multivariate.  You will need to read the SSM syntax and DOC examples for these more involved cases.  For univariate Y you can also use the RANDOMREG statement in PROC UCM, which might be even easier.

 

See SSM and UCM procedure docs at http://support.sas.com/documentation/onlinedoc/ets/indexproc.html#ets143

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