RE: st: RE: Hausman-Taylor and Autocorrelation

["Wooldridge, Jeffrey" <wooldri1@msu.edu>]

The transformation used by HT is the same as that used by RE, it's just that the former uses IV. In Stata, RE has a "theta" option so that you can see what fraction of the mean is subtracted off (which is the same for all i with a balanced panel). Unfortunately, it is not an option with HT.

You can compute it from the HT output: it depends on sigmasq(u), sigmasq(e), and T. I call it lambda (unfortunately) in both editions of my book. Greene's book and Baltagi's must have it, too. If you get this estimate, you can compute the quasi-demeaned data by hand (tedious) and then use pooled 2SLS. With a "cluster" option the standard errors will be fully robust.

Jeff

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of May Ster
Sent: Tuesday, March 08, 2011 2:04 PM
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: RE: Hausman-Taylor and Autocorrelation

Thank you JW,

I so far haven't managed to get that version of your MIT pressbook
yet. I will try to get one asap.

However, I am not quite sure what do you mean by firstly "Obtain the
quasi-demeaned data using theta (just as with random effects)"
Does that mean i shall use ...

xtreg y x1 x2 x3, re

then what shall then be next steps?.

I have to apologise if my question is somewhat not too advanced as i'm
very new to STATA.
Please help. Thanks.




On Mon, Mar 7, 2011 at 11:42 AM, Wooldridge, Jeffrey <wooldri1@msu.edu> wrote:
>
> Actually, autocorrelation does not cause inconsistency in the betahats.
> The Hausman-Taylor estimator is a generalized IV estimator and, like
> GLS, it is consistent even if the second moments are misspecified. Of
> course, the instruments need to be strictly exogenous.
>
> The main issue is how to obtain robust standard errors for the
> Hausman-Taylor approach. It can be programmed in Stata without too much
> trouble, but there is a way to use Stata commands, too. Obtain the
> quasi-demeaned data using theta (just as with random effects) and then
> use ivreg on the pooled, quasi-demeaned data. Clustering at the id level
> then produces valid standard errors.
>
> I discuss this in 2e of my MIT Press book.
>
> JW
>
> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu
> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of May Ster
> Sent: Sunday, March 06, 2011 8:13 PM
> To: statalist@hsphsun2.harvard.edu
> Subject: st: Hausman-Taylor and Autocorrelation
>
> Dear all,
>
> Under the panel framework,I've used the Hausman-Taylor as an
> estimator. However, i can't find the way to check whether there's
> autocorrelation in residual after using -xthtaylor-.
>
>
> If i'm not wrong, if autocorrelation is the case here, the estimates
> i've obtained so far are not consistent. And, i have to find a way to
> tackle that later.
>
> Please help. Thanks.
> *
> *   For searches and help try:
> *   http://www.stata.com/help.cgi?search
> *   http://www.stata.com/support/statalist/faq
> *   http://www.ats.ucla.edu/stat/stata/
>
> *
> *   For searches and help try:
> *   http://www.stata.com/help.cgi?search
> *   http://www.stata.com/support/statalist/faq
> *   http://www.ats.ucla.edu/stat/stata/

*
*   For searches and help try:
*   http://www.stata.com/help.cgi?search
*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/

*
*   For searches and help try:
*   http://www.stata.com/help.cgi?search
*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/