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Re: st: Is there a way to use ivreg2 without running the first stage


From   Mark Schaffer <M.E.Schaffer@hw.ac.uk>
To   statalist@hsphsun2.harvard.edu, Gregory Dybalski <DybalskiG@gao.gov>
Subject   Re: st: Is there a way to use ivreg2 without running the first stage
Date   Wed, 24 Nov 2004 21:29:49 +0000 (GMT)

Greg,

Quoting Gregory Dybalski <DybalskiG@gao.gov>:

> Prof. Mark E. Schaffer,
>  
> Again, I appreciate your assistance.  I'm sorry if my prior
> submission was unclear.
>  
> The fitted values, fittedt1 & fittedt2, are obtained from the
> regression of the endogenous regressor on the included and excluded
> variables.  To obtain these estimates I  use,
> xtreg y1 x1 x2 z1 z2, fe
> The predicted values from this regression are then interacted with the
> year dummy variables to obtain the variables fittedt1 and fittedt2. A
> similar interaction is done for the y1 variables to obtain y1_t1  y1_t2.
>  
> These values are used in the instrumental variable estimation.
> ivreg2 y x1 x2 (y1_t1  y1_t2 =  fittedt1  fittedt2)

If I understand correctly, you can think of the two procedures as variations
of how to use your instruments x1, x2, z1, z2, and t.

In the procedure I suggested, you interact 3 variables - t, with z1 and z2 -
to get two more excluded IVs to add to your original 4 IVs (x1, x2, z1 and
z2).  These are multiplicative (i.e., nonlinear) interactions.  The first
stage of 2SLS gets you linear projections of y1_t1 and y1_t2 on these 6
variables (plus a constant).

In your procedure, you regress y1 on x1, x2, z1, and z2, and get yhat (say).
 yhat is a linear combination of these 4 IVs (plus a constant).  You then
interact this linear combination with t to get two new variables that are
now nonlinear combinations of the original 5 variables (x1, x2, z1, x2, and
t).  The first stage of 2SLS then gets you linear projections of y1_t1 and
y1_t2 on 4 variables: these 2 nonlinear combinations plus x1 and x2 (and
again a constant).

The parallel that you raised with IV and probit seems to me to be a good
one.  The motivation there was to use a probit to generate nonlinear
combinations of variables that are superior instruments because they are
better predictors - are more "relevant" in the first-stage regression - than
using the variables separately to get linear projections as in standard IV.

I think the same thing is going on here - if your procedure gives you a
first-stage regression (where you assess "relevance") that looks superior to
the procedure that I suggested, then there's no reason why you shouldn't use
it.  Of course, it might instead give you a first-stage regression that
looks worse. :)

Cheers,
Mark

> Sincerely,
>  
> Greg Dybalski
> 
>  
> >Greg,
> >
> >Date sent:       Wed, 24 Nov 2004 10:31:59 -0500
> >From:            "Gregory Dybalski" <DybalskiG@gao.gov>
> >To:              <statalist@hsphsun2.harvard.edu>
> >Subject:         st: Is there a way to use ivreg2 without running
> the
> first stage
> > regression?
> >Send reply to:   statalist@hsphsun2.harvard.edu 
> >
> >> Prof. Mark E. Schaffer,
> >> 
> >>  I appreciate your reply, it was quite helpful.  Your method
> should
> >> work.
> >> 
> >> I have an similar alternative method that I would like you to
> comment
> >> on.  I referred to the archaic '2SLS' method because I am
> switching
> from
> >> Limdep (ver 8), which, in fact, forces the user to perform IV
> estimation
> >> in two steps.  I originally estimated the model in Limdep because
> it
> had
> >> a procedure to estimate a fixed effects model using IV that
> corrects
> for
> >> autocorrelation.  Your recent changes to the ivreg2 procedure
> now
> >> provide for such estimation.
> >> 
> >> Background
> >> 
> >> You correctly stated the basic model that I want to estimate
> using
> >> Stata,
> >> ivreg2 y x1 x2 (y1=z1 z2)
> >> 
> >> I have 17 years of data for each group and want to examine if
> the
> >> coefficient for the y1 variable is different for earlier years
> than
> the
> >> later years.  To estimate this revised model in Limdep I created
> 4
> >> variables: y1_t1 & y1_t2 (the interaction between y1 and the
> dummy
> >> variable for the time periods) and fittedt1 & fittedt2 (the
> interaction
> >> between the estimated 1st stage values and the dummy variable
> for
> the
> >> time periods).  I used Limdep regression command with 2
> endogenous
> >> regressors and their fitted values.
> >> 
> >> To estimate this model in Stata you suggested that I create
> additional
> >> variables by interacting the y1 and the excluded instruments with
> a
> >> dummy variable.  Your method interacts the excluded instruments
> with
> the
> >> dummy variable but does not interact the included exogenous
> variables,
> >> x1 & x2, with the dummy.  Your method & mine will not result in
> the
> same
> >> estimated values, but I am not sure that it matters.  
> >
> >It's entirely up to you.  If you think that the coefficients on x1
> 
> >and x2 may also have changed, then you can also interact these with
> 
> >the time dummy, then test etc.  Or if you want to maintain the 
> >assumed constancy of these coefficients, then don't interact.
> >
> >> Proposed Alternative Method 
> >> 
> >> I have an alternative method that I would like you to comment on.
> 
> What
> >> happens if I substitute the '1st stage' fitted values for the
> excluded
> >> exogenous variables in the ivreg2 command instead of the z1 and
> z2
> >> variables?  The ivreg2 command would then become,
> >> ivreg2 y x1 x2 (y1_t1  y1_t2 =  fittedt1  fittedt2)
> >
> >I don't understand what fittedt1 and fittedt2 are.  You call them
> the
> 
> >first stage fitted values for the the excluded IVs, but excluded 
> >exogenous variables never get "fitted" when you do 2SLS - what
> would 
> >you regress z1 and z2 on?
> >
> >--Mark
> >
> >> This method should also provide suitable estimates.  
> >> 
> >> I have reviewed some of the past postings to the Stata list and
> found
> >> this method proposed when the endogenous regression was based on
> a
> >> probit model.   I assume that your proposed method and this
> alternative
> >> would result in suitable estimates.  Is there any reason to
> prefer
> one
> >> method over another.  For example, using your method would
> provide
> >> meaningful output for the test statistics regarding the
> overidenfying
> >> restrictions.  
> >> 
> >> Greg Dybalski
> >> 
> >> >Gregory,
> >> >
> >> >I'm not quite sure I understand what you're asking for.
> >> >
> >> >ivreg2 does standard IV.  Internally, there is only one stage,
> which 
> >> >I suppose is standard for packages these days - "2SLS" is a
> somewhat 
> >> >archaic term and it isn't common to do IV in two steps any
> more.
> >> >
> >> >In any case, if it's standard IV that you want to do, you should
> be
> 
> >> >able to write down a model that can be estimate in one stage;
> if
> you 
> >> >can't, then it isn't IV.
> >> >
> >> >In your case, say for example you have two periods.  You have
> one 
> >> >endogenous variable and a set of excluded instruments that I
> suppose 
> >> >are also time-varying.  You want to know if the coeff on the
> endog
> 
> >> >regressor changes over time.  What's wrong with the following?
> >> >
> >> >- say the equation in the original form has 3 regressors, one of
> 
> >> >which is endogenous, and 2 excluded instruments:
> >> >
> >> >ivreg2 y x1 x2 (y1=z1 z2)
> >> >
> >> >- Interact your endog regressor y1 with time so that you have
> two 
> >> >such regressors, y1_t1 and y1_t2
> >> >
> >> >- Interact your excluded instruments with time to get four
> such
> IVs, 
> >> >z1_t1 z1_t2 z2_t1 z2_t2
> >> >
> >> >- Estimate
> >> >
> >> >ivreg2 y x1 x2 (y1_t1 y1_t2 = z1_t1 z1_t2 z2_t1 z2_t2)
> >> >
> >> >and test the equality of the coefficients on y1_t1 and y1_t2.
> >> >
> >> >Probably there's something wrong with this, but a specific
> example
> 
> >> >might help to clarify the question.
> >> >
> >> >--Mark
> >> >
> >> >Date sent:       Tue, 23 Nov 2004 11:14:53 -0500
> >> >From:            "Gregory Dybalski" <DybalskiG@gao.gov>
> >> >To:              <statalist@hsphsun2.harvard.edu>
> >> >Subject:         st: Is there a way to use ivreg2 without
> running
> >> the first stage
> >> > regression?
> >> >Send reply to:   statalist@hsphsun2.harvard.edu 
> >> >
> >> >> Hi,
> >> >>  
> >> >> I am estimating an instrumental variable model having one
> >> endogenous
> >> >> variable on the right hand side (RHS) of the equation.  The
> model
> >> is
> >> >> estimated from panel data, having fixed effects, and
> correcting
> for
> >> >> autocorrelation; heteroscedasicity does not appear to be much
> of
> a
> >> >> problem.  
> >> >>  
> >> >> Now, I want to re-examine the model where the coefficient
> for
> the
> >> RHS
> >> >> endogenous variable varies over several time periods.  The
> simplest
> >> way
> >> >> to do this would be to take the fitted values from the
> first-stage
> >> and
> >> >> generate the needed instruments.  For example, the values
> for
> the
> >> >> instrument in the initial time period would be equal to the
> >> original
> >> >> fitted values and zero for the other time periods.  The
> remaining
> >> >> instruments would be generated similarly.  What I want to do
> is
> use
> >> >> ivreg2 without running the '1st stage regression'.  So, is
> there
> a
> >> way
> >> >> where I can enter the actual and fitted values for the RHS
> >> endogenous
> >> >> variable into ivreg2?  Or is there another Stata procedure
> that
> >> could
> >> >> estimate the model having these above features.
> >> >>  
> >> >> Obviously, I can estimate the model with the fitted values
> using
> a
> >> >> regression procedure, and the model coefficients would be
> properly
> >> >> estimated, but the variances would not be.  
> >> >>  
> >> >> Greg
> >> >>  
> >> >> 
> >> >> *
> >> >> *   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/ 
> >> >
> >> >Prof. Mark E. Schaffer
> >> >Director
> >> >Centre for Economic Reform and Transformation
> >> >Department of Economics
> >> >School of Management & Languages
> >> >Heriot-Watt University, Edinburgh EH14 4AS  UK
> >> >44-131-451-3494 direct
> >> >44-131-451-3008 fax
> >> >44-131-451-3485 CERT administrator
> >> >http://www.som.hw.ac.uk/cert 
> >> >
> >> 
> >> *
> >> *   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/ 
> >
> >Prof. Mark E. Schaffer
> >Director
> >Centre for Economic Reform and Transformation
> >Department of Economics
> >School of Management & Languages
> >Heriot-Watt University, Edinburgh EH14 4AS  UK
> >44-131-451-3494 direct
> >44-131-451-3008 fax
> >44-131-451-3485 CERT administrator
> >http://www.som.hw.ac.uk/cert 
> >
> 
> *
> *   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/
> 



Prof. Mark Schaffer
Director, CERT
Department of Economics
School of Management & Languages
Heriot-Watt University, Edinburgh EH14 4AS
tel +44-131-451-3494 / fax +44-131-451-3008
email: m.e.schaffer@hw.ac.uk
web: http://www.sml.hw.ac.uk/ecomes
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