Thanks Austin for mentioning my -clogithet- module and paper. I'm
afraid, however, that -clogithet- does not estimate a fixed effects
logit with heteroscedasticity but McFadden's choice model with het -
although Stata's -clogit- command can estimate homoscedastic versions
of both of these -clogithet- only does the latter unfortunately.
What you could do is estimate a hetersocedastic binary logit model
with het using -clogithet- with cluster-robust standard errors, along
the lines of AttaUllah Shah's suggestion. You can also use -hetprob-
in this manner if you prefer a probit model.
Arne
On 06/07/07, Austin Nichols <[email protected]> wrote:
> Jessica <[email protected]> :
> I don't know about the tests for het or clustering after -xtprobit-
> and -xttobit- (perhaps someone else on the list can address these).
> -ssc install clogithet- gives you a test for heteroskedasticity in a
> fixed-effects logit model, described in
>
> Hole, A.R., 2006. Small-sample properties of tests for
> heteroscedasticity in the conditional logit model. Economics Bulletin
> 3, 1-14.
> http://economicsbulletin.vanderbilt.edu/2006/volume3/EB-06C20063A.pdf
>
> However, it seems to me your reviewer missed the main problem, that
> -xttobit- is the wrong model. You seem to be estimating ln(real y + 1)
> as a function of X with a lower limit of 1. But ln(1)=0 --how many
> left-censored observations does Stata report? Is it the same as the
> number of obs where y=0?. Or perhaps you are estimating ln(real y +
> exp(1)) as a function of X with a lower limit of 1, where the lower
> limit makes more sense for a depvar y>=0. This still assumes that
> the values observed at zero really should be mostly negative, and the
> underlying distribution is normal, but this is unlikely to be the
> case. What you really want is a GLM model or -poisson- type model,
> right? See e.g.
> http://www.stata.com/statalist/archive/2007-04/msg00549.html
> http://www.stata.com/statalist/archive/2006-12/msg00466.html
> I would recommend you replace -xttobit- using lnreal1 as the depvar
> with -xtpoisson- using real as the depvar.
>
> In general, adding some number to y, taking the log, and running a
> -tobit- type model is unjustifiable. For one, your estimates will
> differ depending on what number you specify, and there is rarely a
> theoretical justification for one number over another.
>
> On a more substnantive point, are there no fixed time effects in your
> model? To the extent that marginal tax rates and the deductability of
> giving varies over time, you would at least want to include year
> effects, I think, even if you can't estimate first-dollar marginal tax
> rates for individuals (to get a plausibly exogenous tax-price of
> giving).
>
>
> On 7/6/07, Holmes, Jessica <[email protected]> wrote:
> > Hope someone can help! I am using a panel data set that looks at
> > charitable giving for 22,000 individuals over 15 years.
> >
> > I use a random effects Probit to predict whether an individual donates
> > in a given year and a random effects Tobit to predict how much he/she
> > gives each year:
> >
> > xtprobit donate male yrsgrad yrsgradsq mar alumnicloserelative
> > med_income artsent bankfin commedia comptech consulting education
> > environmental govtpp healthcaremed intlang law nonprofitsocialservices
> > profservicesbus salesmarketing ownbusiness mileslt250 reunion soc
> > affinity acad devug arts campus sports otheract socsci natsci art
> > nongrad loans_z grants_z finaid_miss djia_pctch campaignyr hock_pc rank
> > hock_pc_male hock_pc_yrsgrad hock_pc_sports rank_male rank_yrsgrad if
> > stillug==0, i(pidm)
> >
> > xttobit lnreal1 male yrsgrad yrsgradsq mar alumnicloserelative
> > med_income artsent bankfin commedia comptech consulting education
> > environmental govtpp healthcaremed intlang law nonprofitsocialservices
> > profservicesbus salesmarketing ownbusiness mileslt250 reunion soc
> > affinity acad devug arts campus sports otheract socsci natsci art
> > nongrad loans_z grants_z finaid_miss djia_pctch campaignyr hock_pc rank
> > hock_pc_male hock_pc_yrsgrad hock_pc_sports rank_male rank_yrsgrad if
> > stillug==0, ll(1) i(pidm)
> >
> >
> > I have been asked by a referee to
> >
> > 1) test for hetereoskedasticity and correct if necessary
> >
> > and
> >
> > 2) test for serial correlaton and correct if necessary.
> >
> > Stata does not seem to have any commands to detect and/or correct for
> > hetereoskedasticity and serial correlation for xtprobit or xttobit. Any
> > suggestions would be most appreciated...
> >
> > Thanks,
> >
> > Jessica
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