Re: st: 2-way Fixed Effects model

[Lucas <lucaselastic@gmail.com>]

Thanks, I'll try it.  FYI, my understanding is this is the dummy variable trap:

1) Y=b0 + b1 Male + b2 Female.

If you dump b0 you can estimate:

2) Y=b1 Male + b2 Female

But, you still can't estimate:

3) Y=b1 Male + b2 Female + b3 White + b4 Nonwhite

Equation 3 reflects the dummy variable trap.

Sam

On Wed, Sep 5, 2012 at 1:03 AM, Ulrich Kohler <kohler@wzb.eu> wrote:
> Another way would be
>
> . iis company
> . xtreg y x* i.county, fe
> . predict u, u
>
> Variable u then holds the coefficients of the dummy-variables for
> company centered at their mean. Note that this is just another way to
> access the dummy variable coefs. Austins remark concerning the
> reliability of the coefs remains to be true, therefore.
>
> I don't know waht the "dummy variable trap" is.
>
> Uli
>
> Am Dienstag, den 04.09.2012, 17:19 -0700 schrieb Lucas:
>> Austin,
>>
>> Thanks for your note.  I know I can do this for a one-way OLS fixed
>> effects model with the -noconstant- option. However, in a two-way
>> fixed effects model this should produce a dummy variable.  That's what
>> I expect with the reg command.  Am I mistaken?  Also, does the iv2reg
>> prevent the dummy variable trap?
>>
>> Sam
>>
>> On Tue, Sep 4, 2012 at 10:13 AM, Austin Nichols <austinnichols@gmail.com> wrote:
>> > Lucas <lucaselastic@gmail.com> :
>> > Just use -regress- e.g.
>> >   reg y x* i.company i.county
>> > but you will need many obs per company-cluster pair to trust those coefs.
>> >
>> > Also see -ivreg2- on SSC for one implementation of 2-way cluster-robust SE
>> > [ http://www.stata.com/meeting/boston10/boston10_baum.pdf ]
>> > and compare SEs on x vars (not SE on fixed effects)
>> > using OIM, het-robust, and cluster-robust SEs.
>> >
>> > On Tue, Sep 4, 2012 at 1:02 PM, Lucas <lucaselastic@gmail.com> wrote:
>> >> Dear Statalisters,
>> >>
>> >> I thought this was a simple issue, estimating a 2-way fixed effects
>> >> model, but, alas, I cannot figure it out. I see several stata and
>> >> user-written commands, but I am not certain any of them will work in
>> >> my situation.
>> >>
>> >> My data is that I have dozens of companies crossed with dozens of
>> >> jurisdictions (e.g., counties).  For substantive reasons I need to
>> >> obtain the coefficients for each company and for each county (which
>> >> makes areg not quite what I need).
>> >>
>> >> FYI, there is no time element here, so lags, AR processes, and such
>> >> are not relevant.
>> >>
>> >> Any guidance anyone can offer is greatly appreciated.
>> >>
>> >> Sam
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