First, I want to thank everyone for their helpful responses to my query.
You all have been a fantastic resource!
Austin: thanks for your recommendations regarding the specification of
the model (e.g., -poisson- and year effects). Those are terrific
suggestions. Thank you.
Attaulla: With regard to using -robust- to correct for
heteroscedasticity and autocorrelation, it is an invalid option for
xtprobit and xttobit in Stata 9. I have asked for an upgrade to Stata 10
in the hopes that this option is available for -xtprobit-, -xttobit- and
now -xtpoisson- in the new release.
Arne: thanks for the recommendation on -oglm-, -clogithet-, -hetprob-.
My concern with the these commands is that I need to provide
user-defined variables as sources of the heteroscedasticity. I don't
have any priors on what these variables might be--but I am happy to go
through my list and use the LM test to test for heteroscedasticity.
I am still stuck on a test for autocorrelation, but this has been a
great help. If the -robust- standard errors correct for both
heteroscedasticity and autocorrelation and they are available in Stata
10, perhaps my problem is solved?
Thanks all!
Jessica
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Arne Risa
Hole
Sent: Saturday, July 07, 2007 6:24 AM
To: [email protected]
Subject: Re: st: hetereoskedasticity/serial correlation with RE xtprobit
xttobit?
In my rush yesterday I forgot to mention Richard Williams' -oglm-
module which can also be used to estimate heteroscedastic logit and
probit models with cluster-robust SEs. This is an easier option for
estimating the heteroscedastic binary logit than -clogithet- since you
won't have to reshape your data.
Arne
On 06/07/07, Arne Risa Hole <[email protected]> wrote:
> 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
> > *
> > * 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/
> >
>
*
* 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/
*
* 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/
