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st: re: list X matrix
Christopher Baum <Baum@bc.edu>
st: re: list X matrix
Mon, 29 Mar 2010 14:23:01 -0400
Thanks but the question was not on how to compute the R^2 but on how
to compute Xb,
so the Statlist FAQ would not have helped.
On Mon, Mar 29, 2010 at 6:29 AM, Nick Cox <email@example.com> wrote:
> The approach that Kit recommends is spelled out at greater length in
> FAQ . . . . . . . . . . . . . . . . . . . . . . . Do-it-yourself
> . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . N.
> J. Cox
> 9/03 How can I get an R-squared value when a Stata command
> does not supply one?
> The Statalist FAQ does draw attention to the FAQs as a way of answering
> many questions. -search- does search the FAQs as well.
> Kit Baum replied to Richard Boylan
> Richard Boylan
> The problem was as follows.
> The regression is y = x b + e. (1)
> However, to estimate it (b/c of a variety of issues such
> autocorrelation, system of equation with correlated errors), the model
> that I end up estimating is
> yt = xt b + z c + v, (2)
> where yt is a transformation of y, xt is a transformation of x, and z
> are variables from the other regressions.
> So, what I need to do is to get the estimates of b from (2) and plug
> back into (1) to compute my R^2.
> Kit Baum
> An R^2 measure for any model can almost always be computed from the
> simple correlation between Y and Yhat, so if you can construct a
> predicted value from the equation you estimate "if e(sample)" for yt,
> and apply the inverse transformation that gets you back to yhat, just
> compute the square of that correlation.
But you said you estimated (2). If you estimated it with Stata, the command almost surely has a predict option. The predictions of yt are related to the predictions of y by the inverse transformation. So use predict after estimating (2) to compute yt-hats, transform them back to y space. You then have yhats.
You did say you wanted to compute an R^2, and this is how to do it. Compute the squared correlation of y and yhat.
Kit Baum | Boston College Economics and DIW Berlin | http://ideas.repec.org/e/pba1.html
An Introduction to Stata Programming | http://www.stata-press.com/books/isp.html
An Introduction to Modern Econometrics Using Stata | http://www.stata-press.com/books/imeus.html
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