Thank you kit for your answer,
but it is not exactly what i want to do.
I try to explain it better then. I didi my regressione, kept my b. Now
there is a x variable in which I did a variation (I took one of its
observation and I modify it, saying doing a 1% variation. I want then
to know how the predicted values are going to change).
Because I am here I'd like to ask you other two stupid things.
1. with xtabond2 how is it possible to get the R^2?
2. Is that possible that using difference gmm, I get coefficients
estimates much higher in magnitude than applying saying an OLS?
3. Which is the difference between one step and twostep gmm? Is it
possible with xtabond2 to get the first stage estimtes??
really thanks a lot for your help
alessia
2007/5/22, Kit Baum <[email protected]>:
sacrificial cabbage
Alessia said
I hope some of you can help me...
I estimate a regression and I saved the coefficients e(b) in the
corresponding matrix. Now I would like to apply these coefficients
estimates to the same set of x's variables, but for one that I want to
substitute with another and calculate the predicted values (to see
which is the variation in the rpedicted values using this other
variables). Anyone of you knows how to do this?
I tried creating a matrix with the new x's variables, but my n=2400
and so the matsize set does not allow me to create such a matrix.
Just create additional observations in your x matrix for the
observations for which you want to predict 'out of sample'. When you
run the regression, those observations will be ignored as their value
of y is missing. Then
predict double oos if ~e(sample)
will generate predictions (using the default , xb) for the
observations that are not in the regression sample.
Kit Baum, Boston College Economics and DIW Berlin
http://ideas.repec.org/e/pba1.html
An Introduction to Modern Econometrics Using Stata:
http://www.stata-press.com/books/imeus.html
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