Hi again. I tried interacting my xs with country specific dummies and
running them in a single equation as suggested. Stata is dropping the
country dummies, even though I specify the nocons option. (I remember
now that this was why I had originally run it in 30 different equations
- it works fine that way, but not if I put them all into one equation.)
Am I doing something wrong? It could be because xsq is the square of
x, but I don't understand why stata would let me do it for an individual
country but not together. Sorry for being obtuse. -Rachel
>>> [email protected] 09/13/05 4:50 PM >>>
a possible solution could be to run in a single model the equation
(1) y = b1 x + b2 xsq
interacting your x's with country specific dummies.
In other words, you could run a fully interactive model which is
equivalent to running 30 different regressions but in a single
equation. (make sure you include the country specific dummies too that
would account for the constant in your separate regressions and
specify the nocons option).
hope this helps.
robert
On 9/13/05, Rachel Bouvier <[email protected]> wrote:
> Dear statalisters *
>
> I am confronting a problem much like that described by James Hardin
in volume 2, issue 3 of the Stata Journal, "The robust variance
estimator for two-stage models," where he gave an illustration of Stata
code to construct the Murphy-Topel variance estimator.
>
> I am using a variable (call it yhat), predicted in a first (series
of) equations, as a regressor in my second equation.
>
> In other words, my first (series of) regressions looked like this:
> (1) y = b1 x + b2 xsq
>
> Then, I predicted yhat from that regression, and used that in a
second regression:
> (2) z = b1 yhat + b2 x2 + b2 x3*
>
> I say "series of" regressions because I have a panel of 30 countries.
Rather than run one panel data regression and predict each country's
yhat from that, I ran each country as a separate regression, not wanting
to assume that they could be pooled. In other words, I ran equation (1)
30 different times, for each country in the dataset. (It seemed to make
sense at the time, to both me and my committee!)
>
> Therein lies my problem. I would like to adjust the standard errors
for the fact that I predicted yhat, but as I ran a different regression
for each country, the solution is not as easy as constructing the
Murphy-Topel estimator. Does anyone have any suggestions? Any help
would be much appreciated, before I dive into something that is
undoubtedly over my head. Thanks.
>
>
>
> *
> * For searches and help try:
> * http://www.stata.com/support/faqs/res/findit.html
> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
>
*
* For searches and help try:
* http://www.stata.com/support/faqs/res/findit.html
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
*
* For searches and help try:
* http://www.stata.com/support/faqs/res/findit.html
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
