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Re: AW: st: RE: wald tests with mfx


From   Maarten buis <maartenbuis@yahoo.co.uk>
To   statalist@hsphsun2.harvard.edu
Subject   Re: AW: st: RE: wald tests with mfx
Date   Tue, 14 Jul 2009 06:44:06 +0000 (GMT)

--- On Mon, 13/7/09, Rich Steinberg wrote:
> What I want is the vce of the marginal effects at the mean
> of various subsamples of the data.  I had thought, like
> you, that if two marginal effects are statistically
> different in the tobit evaluated at the mean of the full
> sample, the same would be true when evaluated for any
> subsample.  But when I run mfx on various subsamples,
> the Z scores of each coefficient are sensitive to the
> subsample.  More is going on than simply applying the
> McDonald and Moffitt decomposition to a different level of
> censorship when I run that mfx command.  Maybe that is
> a bug, but my more sophisticated friend thinks that mfx at a
> subsample mean is computing correctly and I am
> misunderstanding how to apply it to subsamples.  Thus
> my current query.
> 
> Martin, and anyone else who is curious, here is the
> research problem that generated this strategy.  We are
> seeing whether the marginal propensity to make charitable
> donations differs with the source of income (or annuitized
> equivalent for wealth variables), among other things,
> testing the implicit assumption of economists that money is
> money and consumption behavior of individuals does not
> depend on where that money came from.  So for example,
> we want to know if the marginal propensity to give out of
> welfare transfer payments equals that out of earned income,
> annuitized inheritance income, etc.  A single tobit
> evaluation tells us whether the coefficients on these
> various income measures are equal around the mean of our
> full sample.  But there are no observations where the
> respondent received welfare income and had the mean level of
> other income sources, so the comparison at the mean has no
> clear interpretation of the sort we want.  In our base
> model, we therefore test for the equality of coefficients
> within each of 7 subsample means (defined by having positive
> levels of each of our 7 income variables).  (We hope to
> have more advanced estimates accounting for unmeasured
> heterogeneity that makes a person receiving welfare
> different from a person receiving an inheritance, but we are
> not there yet).  Maybe we should estimate the entire
> tobit separately for each subsample, but as some of the
> subsamples are small (particularly our main income source of
> interest, inheritances) we were hoping those regressions
> could be pooled because the slopes with respect to the
> latent dependent variable were not significantly different
> in the subsamples.

The marginal effect depends on where you evaluate it. More, 
specifically it will become less when you evaluate at a point 
closer to the cut-off point. So if you evaluate the marginal 
effects of different groups at different means you will add a 
source of variation in results between these groups that you 
may not want, because now you are not comparing like with like.

I can think of two suggestions: 
1) Maybe the overall median lies within the range of all 
sub-groups. In that case you could avoid the entire problem by 
estimating the marginal effects at this value.
2) You could compare the effects on the latent variable, as 
these effects are linear, and thus not depend on where you 
evaluate them.

Hope this helps,
Maarten

-----------------------------------------
Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen
Germany

http://home.fsw.vu.nl/m.buis/
-----------------------------------------


> 
> Martin Weiss wrote:
> > <>
> > 
> > You are more than welcome! I did not endorse your
> research strategy as I do
> > not think that what you are attempting is necessary,
> but on a technical
> > level, you can get your hands on the desired returned
> result in this
> > fashion.
> > 
> > Stata provides a full array of postestimation tools
> for every estimation
> > command, and this list is usually exhaustive. If you
> want the -vce- of the
> > original estimation, you can get it like this:
> > 
> > ***
> > sysuse auto, clear
> > generate wgt=weight/1000
> > tobit mpg wgt gear_ratio, ll(17)
> > estat vce
> > ***
> > 
> > HTH
> > Martin
> > 
> > -----Ursprüngliche Nachricht-----
> > Von: owner-statalist@hsphsun2.harvard.edu
> > [mailto:owner-statalist@hsphsun2.harvard.edu]
> Im Auftrag von Rich Steinberg
> > Gesendet: Montag, 13. Juli 2009 22:51
> > An: statalist@hsphsun2.harvard.edu
> > Betreff: Re: st: RE: wald tests with mfx
> > 
> > Thanks for responding, and so quickly.  Good
> answer, but I learned from following your advice that this
> reproduces only the standard errors, not the covariances I
> would need for a Wald test.  I don't see an e( ) that
> saves the vce.  And I can't use the vce from the
> original tobit because the sample is changing.
> > 
> > Martin Weiss wrote:
> >   
> >> <>
> >> 
> >> " For the latter, I know from the Help file that
> mfx saves what I need as e(Xmfx_se_dydx), but I can't figure
> out how to see that."
> >> 
> >> ***
> >> sysuse auto, clear
> >> generate wgt = weight/100
> >> tobit mpg wgt len tu head, /*
> >> */ ll(17) ul(24)
> >> 
> >> mfx compute, /*
> >> */ predict(e(17,24))
> >> 
> >> mat l e(Xmfx_se_dydx)
> >> mat A=  e(Xmfx_se_dydx)
> >> matrix list A
> >> 
> >> di A[1,3]
> >> ***
> >> 
> >> HTH
> >> Martin
> >> 
> >> -----Original Message-----
> >> From: owner-statalist@hsphsun2.harvard.edu
> >> [mailto:owner-statalist@hsphsun2.harvard.edu]
> On Behalf Of Rich Steinberg
> >> Sent: Montag, 13. Juli 2009 22:10
> >> To: statalist@hsphsun2.harvard.edu
> >> Subject: st: wald tests with mfx
> >> 
> >> As a relatively unsophisticated user, I have tried
> for a few hours and failed to solve the following
> problem.  After running tobit, I want to test for the
> equality of marginal effects for the unconditional
> observable dependent variable.  No problem with mfx or
> dtobit.  But I don't want to evaluate these marginal
> effects test at the mean, median or zero of the full sample
> prior to testing.  Instead, I want to use the estimates
> from the full sample, but evaluate the marginal effect at
> means of various subsamples.  So I have, for example:
> >> 
> >> tobit totgiv $income $control, ll vce(cluster
> fid68)
> >> mfx if welfare01>0, pred(ystar(0,.))
> >> 
> >> Now, I want to test for the equality of two
> elements of $income in this subsample.  But everything
> I try works on the tobit coefficients, not the mfx
> output.  So how do I retrieve this for a "test" command
> (ideally) or even display the vce from the mfx to do the
> test by hand? 
> >> For the latter, I know from the Help file that mfx
> saves what I need as e(Xmfx_se_dydx), but I can't figure out
> how to see that. This should be easy, but stumped me.
> >> 
> >> Thanks everyone.
> >> 
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> 
> -- Rich Steinberg
> Department of Economics, 516 Cavanaugh Hall
> IUPUI
> Indianapolis, IN 46202-5140
> 317-278-7221
> 
> "Unanswered email since 1955"
> 
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> 


      

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