I wish to estimate expenditure on a sub-sample, and use the estimates to predict expenditure for the entire sample. So in the first stage, I regress:
proc reg data=InputData outest=estimates;
model Exp = lnY lnY_2 &ivset ;
where Exp ge 100;
output out=Pred_Exp p=predexp;
run;
The problem is I then have to manually use the parameter estimates to predict expenditure for the cases with Exp<100. Is there a shorter way to do this than manually using the parameter estimates that I have saved to the dataset estimates?
In the input dataset, create a variable (call it Exp1).
data inputdata;
set inputdata;
if exp >= 100 then exp1=exp;
else exp1=.;
run;
then run proc reg as follows:
proc reg data=InputData outest=estimates;
model Exp1 = lnY lnY_2 &ivset ;
output out=Pred_Exp p=predexp;
run;
The estimates dataset will have predicted values for all of the data. This use of missing for the dependent variable is a good trick to know.
Steve Denham
In the input dataset, create a variable (call it Exp1).
data inputdata;
set inputdata;
if exp >= 100 then exp1=exp;
else exp1=.;
run;
then run proc reg as follows:
proc reg data=InputData outest=estimates;
model Exp1 = lnY lnY_2 &ivset ;
output out=Pred_Exp p=predexp;
run;
The estimates dataset will have predicted values for all of the data. This use of missing for the dependent variable is a good trick to know.
Steve Denham
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