st: RE: RE: RE: RE: xtivreg2: orthog option

["Fitzgerald, James" <J.Fitzgerald2@ucc.ie>]

________________________________________
From: owner-statalist@hsphsun2.harvard.edu [owner-statalist@hsphsun2.harvard.edu] on behalf of Schaffer, Mark E [M.E.Schaffer@hw.ac.uk]
Sent: 04 July 2012 22:17
To: statalist@hsphsun2.harvard.edu
Subject: st: RE: RE: RE: xtivreg2: orthog option

James,

> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu
> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of
> Fitzgerald, James
> Sent: 04 July 2012 20:08
> To: statalist@hsphsun2.harvard.edu
> Subject: st: RE: RE: xtivreg2: orthog option
>
> Mark,
>
> Thank you for your reply. I understand what you are saying
> with regards to the orthogonality of a regressor being
> dependent on the model specified.
>
> I think maybe my understanding of excluded instruments is
> incorrect. Do the instruments listed as excluded affect the
> error term? I was working on the presumption that they did
> not

If by "error term" you mean the true error and not the estimated
residual, then you are right, of course.  But if you mean the residual,
it's a different story.

I was referring to the residual. You'll have to excuse my ignorance with regards econometrics. I'm very much a beginner!

> (and I have no real basis for this presumption except
> that they are "excluded" from the model specification).
>
> My reason for implementing xtivreg2 is to investigate whether
> or not any of my regressors are still endogenous after having
> controlled for firm specific time invariant effects and firm
> invariant time specific effects (two way fe model). The only
> way I know how do to this is to find a set of valid
> instruments and use the orthog or endog options in xtivreg2.
> I decided to use lags of my regressors as potential
> instruments, and found that some are valid and some are not.

Which means, I think, that you are using multiple lags as instruments so
that the model is overidentified.

I'm actually only using the first lag of each regressor. I assumed that thet would not all be endogenous, and thus I would not need additional lags to ensure the model is overidentified. 
I use the orthog option specifying only one regressor to be tested at a time i.e. 
xtivreg2 ltdbv lnsale tang itang itangdum tax prof mtb capexsa liq ndts yr* (=l.lnsale l.tang l.itang l.itangdum l.tax l.prof l.mtb l.capexsa l.liq l.ndts) if (I put a term in here to specify the sub-sample), fe cluster(firm) gmm2s orthog(lnsale) (I repeat this replacing lnsale with tang, itang, etc.)
I then conclude a regressor may be endogenous if the C-Stat is high (p-value low)

(However, before I test the included instruments for orthogonality I test each individual excluded instrument i.e. same as above but with orthog(l.lnsale), and then l.tang etc. I do this because xtivreg2 file said that the null of no endogeneity of the difference in Hansen test can only be rejected if the Hansen J Stat of the smaller equation without the suspect instruments is low. This way I have a set of excluded instruments that generate a Hansen J stat > say, 0.5, and thus when i test the othogonality of the included instruments I can safely accept or reject the null.) Is this completely wrong?? As I said below, I get very different C - Stats for my included instruments depending on the set of excluded instruments that I use, even though the different sets of excluded instruments have relatively low Hansen J stats.

These tests can also be cast in terms of vector-of-contrast tests.  So
you are doing two sorts of tests:

(1) Are the coeffs on the endogenous regressors different depending on
which lags are used as instruments, i.e., do the different lags identify
different betas?  These are your overid tests/orthog of excluded IVs
tests.

(2) Are the coeffs on the regressors different depending on whether you
treat them as endogenous or exogenous?  These are your endogeneity
tests.

> My problem though is that I am estimating my model on a
> number of sub-samples from my whole sample. I find that the
> set of valid instruments changes within each sub-sample, and
> hence the reason for all the orthogonality tests of both
> excluded and included instruments within each sub-sample

This sounds a little dubious, but maybe it's OK.  What defines your
subsamples?

The values each observation takes for two particular variables i.e. small & low profit

> Is my methodology wrong? Is there any way to test for
> endogeneity without specifying excluded instruments i.e with
> either xtreg or xtivreg2?

If you mean what I think you mean, the answer is no.  The way to test
for endogeneity is, in effect, (2) above - compare the estimated coeff
when you treat the regressor as exogenous with the est coeff when you
treat it as endogenous.  If they're similar, you conclude the regressor
is exogenous.  If they're different, you conclude it's endogenous.  Of
course, for this test to work, the instruments that enable you to get an
estimate have to be valid.

By valid do you mean that the Hansen J stat should be low?

> Would I be better off assuming my regressors are exogenous,
> as I do not have any strong theoretical justification to
> believe they are not (and also given that I have controlled
> for firm and time effects)?

What are the results of your endogeneity tests?  That is, once you think
you have a reasonable specification when the regressor is treated as
endogenous, does the endog test say you can treat it as exogenous?

The lowest p-value I have gotten for a C-stat was the one I reported below (0.0392), but as I mentioned below this is dependent on the set of excluded instruments used (first e-mail). The rest of the p-values for each included variable in each sub-sample are >0.1000 

--Mark

>
> Any advice you could give me is greatly appreciated. I'm a
> bit lost as to what to do!
>
> Thanks
>
> James
> ________________________________________
> From: owner-statalist@hsphsun2.harvard.edu
> [owner-statalist@hsphsun2.harvard.edu] on behalf of Schaffer,
> Mark E [M.E.Schaffer@hw.ac.uk]
> Sent: 04 July 2012 18:59
> To: statalist@hsphsun2.harvard.edu
> Subject: st: RE: xtivreg2: orthog option
>
> James,
>
> > -----Original Message-----
> > From: owner-statalist@hsphsun2.harvard.edu
> > [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of
> Fitzgerald,
> > James
> > Sent: 03 July 2012 17:44
> > To: statalist@hsphsun2.harvard.edu
> > Subject: st: xtivreg2: orthog option
> >
> > Hi Statalist users,
> >
> > I am estimating the following model in STATA 11.2:
> >
> > xtivreg2 ltdbv lnsale tang itang itangdum tax prof mtb capexsa liq
> > ndts yr* (=l.lnsale l.tang l.itang l.itangdum l.tax l.prof l.mtb
> > l.capexsa l.liq l.ndts) if profsubs>0 &
> > capexsasubs>0, fe cluster(firm) gmm2s
> >
> > In order to ensure my excuded instruments are orthogonal, I use the
> > orthog option to test the orthogonality of each excluded
> variable i.e.
> > orthog(l.lnsale) and so on.
> >
> > Once I have a set of excluded instruments that are orthogonal
>
> I am not sure, but the problem might be here.
>
> You write as if your instruments can have a property called
> "orthogonality" in some abstract sense, separate from the
> model you have specified.
>
> But that's not how it works.  The orthogonality of Z means
> E(Zu)=0, where u is the ("true") disturbance term for a
> specified model.  If you change the model, you change the
> definition of u (u is, in a sense, by definition everything
> that is not in the model).  It's quite possible for E(Zu)=0
> for one model but then not be true if you change the model by
> adding or dropping regressors.
>
> Apologies if this obvious and not what you meant.  HTH in any case.
>
> Cheers,
> Mark
>
> > (say Hansen J Stat p-value >0.5000), I then test the
> orthogonality of
> > each of my included instruments i.e.
> > orthog(lnsale) and so on.
> >
> > However, I am finding that the C-Stat for some of the included
> > instruments depends on the set of excluded instruments,
> even though in
> > each case the set of excluded instruments appears orthogonal.
> >
> > For example, when I run the following:
> >
> > xtivreg2 ltdbv lnsale tang itang itangdum tax prof mtb capexsa liq
> > ndts yr* (=l.itang l.prof l.mtb l.capexsa l.liq
> > l.ndts) if profsubs>0 & capexsasubs>0, fe cluster(firm) gmm2s
> > orthog(tang)
> >
> > I get the following results in relation to orthogonality tests:
> >
> > Hansen J statistic (Lagrange multiplier test of excluded
> > instruments):   5.104 Chi-sq(6) P-val =    0.5306
> > -orthog- option:
> > Hansen J statistic (eqn. excluding suspect orthog.
> > conditions):          0.853 Chi-sq(5) P-val =    0.9735
> > C statistic (exogeneity/orthogonality of suspect
> > instruments):           4.250 Chi-sq(1) P-val =    0.0392
> > Instruments tested:   tang
> > Included instruments: lnsale tang itang itangdum tax prof
> mtb capexsa
> > liq ndts yr90 yr91 yr92 yr93 yr94 yr95 yr96 yr97 yr98
> > yr99 yr00
> > yr01 yr02 yr03 yr04 yr05 yr06 yr07
> > Excluded instruments: L.itang L.prof L.mtb L.capexsa L.liq L.ndts
> > Dropped collinear:    yr08
> >
> > However, when I drop l.capexsa and l.liq from the set of excluded
> > instruments I get:
> >
> >
> > Hansen J statistic (Lagrange multiplier test of excluded
> > instruments):   0.970 Chi-sq(4) P-val =    0.9143
> > -orthog- option:
> > Hansen J statistic (eqn. excluding suspect orthog.
> > conditions):          0.570 Chi-sq(3) P-val =    0.9033
> > C statistic (exogeneity/orthogonality of suspect
> > instruments):           0.400 Chi-sq(1) P-val =    0.5271
> > Instruments tested:   tang
> > Included instruments: lnsale tang itang itangdum tax prof
> mtb capexsa
> > liq ndts yr90 yr91 yr92 yr93 yr94 yr95 yr96 yr97 yr98
> > yr99 yr00
> > yr01 yr02 yr03 yr04 yr05 yr06 yr07
> > Excluded instruments: L.itang L.prof L.mtb L.ndts
> > Dropped collinear:    yr08
> >
> >
> > Can anyone tell me why I experience such a large change in
> the C stat
> > for tang?
> >
> > Best regards
> >
> > James
> > *
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> >
>
>
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--
Heriot-Watt University is the Sunday Times
Scottish University of the Year 2011-2012

Heriot-Watt University is a Scottish charity
registered under charity number SC000278.


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