On Feb 4, 2008 5:50 PM, William Bishop <[email protected]> wrote:
> Scott and Austin:
>
> Thank you both for your help with the rolling regression. That did
> what I was hoping to accomplish.
>
> BTW, when I modified Scott's code to be time<`i' instead of time<=`i'
> it stopped making predictions. I assume that has to do with the
> e(sample) line, which I am unfamiliar with - will have to look into
> that.
It is tied to the -if e(sample)-. This condition restricts the
predictions to the estimation sample.
In my example, it not generating the one-step ahead prediction, which
is what I think you want but the fitted value for the last observation
of the estimation sample. It could modified to generate the one-step
ahead prediction as:
webuse grunfeld,clear
qui {
gen predict = .
levelsof com, loc(levels)
foreach l of local levels {
forv i = 5/20 {
reg invest kstock if com == `l' & time <`i'
predict foo if com == `l' & time <=`i'
replace predict = foo if com == `l' & time == `i'
drop foo
}
}
}
Scott
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