> Daniele Gori <[email protected]>:
> It's not really clear to me what you want from the question. Try
> framing it in terms of a small dataset we can see, and results that
> can be read easily in an email. Is this in the right vein?
>
> webuse grunfeld, clear
> tsset
> loc tv "`r(timevar)'"
> levelsof `tv', loc(tl)
> foreach v in pred cons curi lagi {
> g double `v'=.
> }
> foreach t of local tl {
> cap reg mval inv l.inv if `tv'==`t'
> qui if _rc==0 {
> tempvar pt
> predict double `pt'
> replace pred=`pt' if e(sample)
> replace cons=_b[_cons] if e(sample)
> replace curi=_b[inv] if e(sample)
> replace lagi=_b[L1.] if e(sample)
> drop `pt'
> }
> }
>
> On 10/18/07, Daniele Gori <[email protected]> wrote:
> > Dear all,
> >
> > I have a large (but incomplete) panel database of firm level data and many variable, from 1995 to 2005. I would like to adopt the cross-section average estimation technique. My goal is to compute time-varying predicted values of the dependent variable. In particular, in my case I wish to estimate the following equation:
> >
> > yi = x1i + x2i + ui (1)
> >
> *
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>
*
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