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Re: st: Fixed Effects estimation with time-invariant variables


From   Joana Quina <[email protected]>
To   [email protected]
Subject   Re: st: Fixed Effects estimation with time-invariant variables
Date   Thu, 28 Jul 2005 09:01:00 +0100

I am using Stata 8 - is it possible to get -xtmixed-, or do I need
Stata 9 for this?

Thanks,
Joana

On 26/07/05, Darby Jack <[email protected]> wrote:
> I think something analogous to the SAS command you reference is
> implemented in Stata 9 as -xtmixed-
> 
>  From the online help:
> 
>  -xtmixed- fits linear mixed models.  Mixed models are characterized
> as containing both fixed effects and random effects.  The fixed
> effects are analogous to standard regression coefficients and are
> estimated directly.  The random effects are not directly estimated,
> but summarized according to their estimated variances and
> covariances.  Random effects may take the form of either random
> intercepts or random coefficients, and the grouping structure of the
> data may consist of multiple levels of nested groups.  The error
> distribution of the linear mixed model is assumed to be Gaussian.
> 
> On Jul 26, 2005, at 11:12 AM, [email protected] wrote:
> 
> > Joana:
> > The model you are trying to apply is generally known as a mixed
> > model. It is possible to use time invariant variables and what
> > would be the equivalent of a fixed effect model in SAS, the
> > procedure is called Proc mixed.  The terminology is not the same
> > (random and fixed can mean different things), but it basically
> > allows you to create an intercept for each country, and then
> > "extract" from that intercept the explanatory power of your
> > variables.  Concerning your question about random and fixed
> > effects, there is a theory reason and a mathematical one.  The
> > theory reason for random effects is that the relationship between
> > the two variables it�s different for each country (basically, a
> > different beta), while the fixed effect assumes just a change in
> > the intercept for each country.  The mathematical reason for using
> > random effects is that the independent variables you are using are
> > not correlated with belonging to a particular country (the country
> > you belong to does not change the !
> >  probability of having a particular value in one of your
> > independent variables).  This is a strong assumption (called
> > orthogonal).  If you use random effects under conditions in which
> > the country determines, even partially, the value of your
> > independent variables, then you will have specification bias and
> > your results will not be thrustworthy.  There is also the GLAMM
> > procedure in STata, but I never had good luck with it (it requires
> > too much processing power).
> >
> > Hope this helps.
> >
> > Martha Martinez.
> >
> >
> >
> >
> >
> > Quoting Joana Quina <[email protected]>:
> >
> >
> >> Thank you Mark.  I was told that Hausman and Taylor have an
> >> Econometrica paper where they tackle the problem of time-invariant
> >> variables and fixed-effects. Are you familiar with this?
> >> Regarding whether it is acceptable to use random effects, my
> >> supervisor has a strong view that in this case it would be wrong.
> >> Could you tell me why you say it is not obviously wrong to do so?
> >>
> >> Thank you again,
> >> Joana
> >>
> >> On 26/07/05, Mark Schaffer <[email protected]> wrote:
> >>
> >>> Joana,
> >>>
> >>> Date sent:              Tue, 26 Jul 2005 13:56:55 +0100
> >>> From:                   Joana Quina <[email protected]>
> >>> To:                     [email protected]
> >>> Subject:                st: Fixed Effects estimation with time-
> >>> invariant
> >>>
> >> variables
> >>
> >>> Send reply to:          [email protected]
> >>>
> >>>
> >>>> Fixed Effects estimation with time-invariant variables
> >>>>
> >>>> I have a problem and I wonder whether anyone can help. I have a
> >>>> panel
> >>>> dataset of 32 Sub-Saharan African countries and four time periods
> >>>> (N=32, T=4). I am looking at the determinants of aid for these
> >>>> countries. Given that they are not randomly selected countries,
> >>>> I am
> >>>> using Fixed Effects. However, I have a few time-invariant variables
> >>>> that are important but that get dropped because of using FE.  Is
> >>>> there
> >>>> any way of obtaining estimates for these time-invariant
> >>>> variables and
> >>>> still use FE?
> >>>>
> >>>
> >>> No.  The fixed effects are perfectly collinear with the time-
> >>> invariant variables.  There's nothing you can do about this if you
> >>> want to use fixed effects.
> >>>
> >>>
> >>>> Also, given the data I'm using, is there any
> >>>> justification for using Random Effects?
> >>>>
> >>>
> >>> It's not obviously wrong to try random effects, especially as you
> >>> can
> >>> use a Hausman test to check whether random effects can be accepted.
> >>> The fact that the time-invariant variables aren't included in the FE
> >>> estimation doesn't prevent you from using the test.
> >>>
> >>> Hope this helps.
> >>>
> >>> Cheers,
> >>> Mark
> >>>
> >>>
> >>>> Any comments would be much appreciated.
> >>>>
> >>>> Thanks.
> >>>> Joana
> >>>>
> >>>> *
> >>>> *   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/
> >>>>
> >>>
> >>> Prof. Mark E. Schaffer
> >>> Director
> >>> Centre for Economic Reform and Transformation
> >>> Department of Economics
> >>> School of Management & Languages
> >>> Heriot-Watt University, Edinburgh EH14 4AS  UK
> >>> 44-131-451-3494 direct
> >>> 44-131-451-3296 fax
> >>> 44-131-451-3485 CERT administrator
> >>> http://www.sml.hw.ac.uk/cert
> >>>
> >>> *
> >>> *   For searches and help try:
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> >>>
> >>>
> >>
> >> *
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> >>
> >>
> >
> >
> > *
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> >
> 
> 
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>

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