Stata The Stata listserver
[Date Prev][Date Next][Thread Prev][Thread Next][Date index][Thread index]

Re: st: XTIVREG2


From   Tinna <statalist@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: XTIVREG2
Date   Mon, 19 Sep 2005 17:34:26 -0400

Thanks Mark, 
I wasn't the one asking the question, but it did help me as I have
been in the same situation as Joana is in now.
Tinna

On 9/19/05, Mark Schaffer <M.E.Schaffer@hw.ac.uk> wrote:
> Joana,
> 
> I have a working version of "xtivreg2", but it does only fixed effects
> estimation.
> 
> However, I'm not sure that you actually have a problem.  When doing a
> Hausman test for endogeneity in IV estimation, the differenced variance
> matrix typically isn't of full rank.  -hausman- will print out a warning
> that "(V_b-V_B is not positive definite)", but it doesn't indicate that
> anything is actually wrong.
> 
> If you try doing the endogeneity test for simple IV estimation that is in
> the manuals somewhere, you'll probably find that the same warning message
> appears.
> 
> Hope this helps.
> 
> Cheers,
> Mark
> 
> > Tinna,
> >
> > Thank you for your suggestion. Unfortunately, when I tried ivendog I
> > got the error message:
> >
> > ivendog works only after ivreg, ivreg2; use dmexogxt after xtivreg
> > last estimates not found
> > r(301);
> >
> > I found a post by Steven Stillman
> > (http://www.stata.com/statalist/archive/2003-02/msg00266.html) where
> > he said:
> >
> > "Pedro,
> > At this point, your best bet is to transform your data using xtdata, fe
> > and
> > use ivreg2 to estimate a fixed-effect iv model.   As the default for
> > ivreg2
> > is to produce large sample estimates, your test results and standard
> > errors
> > will not be affected by the transformation.  This will not work for
> > estimating a random effects iv model.  Writing an xtivreg2 program which
> > does this all automatically is on my to-do list but I am not sure how soon
> > I
> > will have time to do it.
> > Steve"
> >
> > I was hoping Steven (or someone) else had written an xtivreg2 programme.
> >
> >
> > On 19/09/05, Tinna <statalist@gmail.com> wrote:
> >> I had a similar problem the other day.
> >> I was using ivreg and ivreg7, but what worked for me was the
> >> post-estimation command ivendog
> >> You may want to try that.
> >>
> >> xtivreg loda_pc lgdp_pc_d lpop  trade_gdp  polityp  us_un_friend_p
> >> japan_un_friend_p Pperiod* y_colony (corrupt=ethnic), re
> >>
> >> ivendog
> >>
> >> Hope this helps
> >> Tinna
> >>
> >> On 9/18/05, Joana Quina <joana.quina@gmail.com> wrote:
> >> > Dear all,
> >> >
> >> > I am using xtivreg to estimate a random effects panel data model.  I
> >> > have one endogenous variable and one excluded instrument.  In order to
> >> > test for endogeneity, I am using the Hausman test with the sigmamore
> >> > option. When I do this, the Hausman test says that V_b-V_B is not
> >> > positive definite.
> >> >
> >> > I would like to know your thoughts on the following:
> >> > 1- What can be done to correct this?
> >> > 2- Is there an "xtivreg2"?
> >> >
> >> > Thank you for your help,
> >> >
> >> > Joana
> >> >
> >> > I enclose the output:
> >> >
> >> > -------------output-----------------------
> >> > . xtivreg loda_pc lgdp_pc_d lpop  trade_gdp  polityp  us_un_friend_p
> >> > japan_un_friend_p Pperiod*
> >> > >  y_colony (corrupt=ethnic), re
> >> >
> >> > G2SLS random-effects IV regression              Number of obs      =
> >>     111
> >> > Group variable: id                              Number of groups   =
> >>      31
> >> >
> >> > R-sq:  within  = 0.5063                         Obs per group: min =
> >>       1
> >> >       between = 0.6333                                        avg =
> >>    3.6
> >> >       overall = 0.6213                                        max =
> >>      4
> >> >
> >> >                                                Wald chi2(11)      =
> >> 113.34
> >> > corr(u_i, X)       = 0 (assumed)                Prob > chi2        =
> >>  0.0000
> >> >
> >> > ------------------------------------------------------------------------------
> >> >     loda_pc |      Coef.   Std. Err.      z    P>|z|     [95% Conf.
> >> Interval]
> >> > -------------+----------------------------------------------------------------
> >> >     corrupt |  -.0429657   .1066427    -0.40   0.687    -.2519815
> >> .1660502
> >> >   lgdp_pc_d |   .0428328   .1272094     0.34   0.736    -.2064931
> >> .2921586
> >> >        lpop |   -.510157    .104499    -4.88   0.000    -.7149711
> >> -.3053428
> >> >   trade_gdp |   .0053404   .0024281     2.20   0.028     .0005813
> >> .0100994
> >> >     polityp |   .0140851   .0081874     1.72   0.085    -.0019619
> >> .0301322
> >> > us_un_frie~p |  -.5324777   .4733456    -1.12   0.261    -1.460218
> >> .3952627
> >> > japan_un_f~p |   2.920518   .8081029     3.61   0.000     1.336666
> >> 4.504371
> >> >   Pperiod_1 |   .4201038   .2109389     1.99   0.046     .0066712
> >> .8335365
> >> >   Pperiod_2 |   .0078534   .1087593     0.07   0.942    -.2053109
> >> .2210178
> >> >   Pperiod_4 |  -.2225596   .2035832    -1.09   0.274    -.6215754
> >> .1764562
> >> >    y_colony |   .0006514   .0069568     0.09   0.925    -.0129837
> >> .0142864
> >> >       _cons |  -.8395967   1.498147    -0.56   0.575    -3.775911
> >> 2.096718
> >> > -------------+----------------------------------------------------------------
> >> >     sigma_u |  .58004628
> >> >     sigma_e |  .28688419
> >> >         rho |  .80345955   (fraction of variance due to u_i)
> >> > ------------------------------------------------------------------------------
> >> > Instrumented:   corrupt
> >> > Instruments:    lgdp_pc_d lpop trade_gdp polityp us_un_friend_p
> >> > japan_un_friend_p Pperiod_1
> >> >                Pperiod_2 Pperiod_4 y_colony ethnic
> >> >
> >> > . est store ivrandom
> >> >
> >> > . xtreg loda_pc lgdp_pc_d lpop  trade_gdp  polityp  us_un_friend_p
> >> > japan_un_friend_p corrupt Pp
> >> > > eriod* y_colony , re
> >> >
> >> > Random-effects GLS regression                   Number of obs      =
> >>     111
> >> > Group variable (i): id                          Number of groups   =
> >>      31
> >> >
> >> > R-sq:  within  = 0.5303                         Obs per group: min =
> >>       1
> >> >       between = 0.6426                                        avg =
> >>    3.6
> >> >       overall = 0.6435                                        max =
> >>      4
> >> >
> >> > Random effects u_i ~ Gaussian                   Wald chi2(11)      =
> >>  128.55
> >> > corr(u_i, X)       = 0 (assumed)                Prob > chi2        =
> >>  0.0000
> >> >
> >> > ------------------------------------------------------------------------------
> >> >     loda_pc |      Coef.   Std. Err.      z    P>|z|     [95% Conf.
> >> Interval]
> >> > -------------+----------------------------------------------------------------
> >> >   lgdp_pc_d |   .0181293   .1191414     0.15   0.879    -.2153837
> >> .2516422
> >> >        lpop |  -.5275332    .102472    -5.15   0.000    -.7283747
> >> -.3266917
> >> >   trade_gdp |   .0048886   .0022066     2.22   0.027     .0005637
> >> .0092135
> >> >     polityp |   .0143393   .0079024     1.81   0.070    -.0011491
> >> .0298277
> >> > us_un_frie~p |  -.4735392   .4488587    -1.05   0.291    -1.353286
> >> .4062077
> >> > japan_un_f~p |   3.167958   .6942995     4.56   0.000     1.807156
> >> 4.52876
> >> >     corrupt |  -.1162393    .033678    -3.45   0.001    -.1822469
> >> -.0502316
> >> >   Pperiod_1 |   .5098709   .1617323     3.15   0.002     .1928815
> >> .8268603
> >> >   Pperiod_2 |   .0336761   .0990239     0.34   0.734    -.1604072
> >> .2277594
> >> >   Pperiod_4 |  -.2379928   .1948569    -1.22   0.222    -.6199053
> >> .1439197
> >> >    y_colony |  -.0014819   .0065505    -0.23   0.821    -.0143206
> >> .0113568
> >> >       _cons |  -.5709694   1.406288    -0.41   0.685    -3.327243
> >> 2.185304
> >> > -------------+----------------------------------------------------------------
> >> >     sigma_u |  .57088029
> >> >     sigma_e |  .26203147
> >> >         rho |  .82598424   (fraction of variance due to u_i)
> >> > ------------------------------------------------------------------------------
> >> >
> >> > . est store random
> >> >
> >> > . hausman ivrandom random, sigmamore
> >> >
> >> >                 ---- Coefficients ----
> >> >             |      (b)          (B)            (b-B)
> >> sqrt(diag(V_b-V_B))
> >> >             |    ivrandom      random       Difference          S.E.
> >> > -------------+----------------------------------------------------------------
> >> >     corrupt |   -.0429657    -.1162393        .0732736        .0281962
> >> >   lgdp_pc_d |    .0428328     .0181293        .0247035               .
> >> >        lpop |    -.510157    -.5275332        .0173762               .
> >> >   trade_gdp |    .0053404     .0048886        .0004518               .
> >> >     polityp |    .0140851     .0143393       -.0002542               .
> >> > us_un_frie~p |   -.5324777    -.4735392       -.0589386
> >> .
> >> > japan_un_f~p |    2.920518     3.167958       -.2474397
> >> .
> >> >   Pperiod_1 |    .4201038     .5098709       -.0897671               .
> >> >   Pperiod_2 |    .0078534     .0336761       -.0258227               .
> >> >   Pperiod_4 |   -.2225596    -.2379928        .0154332               .
> >> >    y_colony |    .0006514    -.0014819        .0021332               .
> >> > ------------------------------------------------------------------------------
> >> >                         b = consistent under Ho and Ha; obtained from
> >> xtivreg
> >> >            B = inconsistent under Ha, efficient under Ho; obtained
> >> from xtreg
> >> >
> >> >    Test:  Ho:  difference in coefficients not systematic
> >> >
> >> >                 chi2(11) = (b-B)'[(V_b-V_B)^(-1)](b-B)
> >> >                          =        6.74
> >> >                Prob>chi2 =      0.8201
> >> >                (V_b-V_B is not positive definite)
> >> >
> >> > -------
> >> >
> >> > *
> >> > *   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/
> >
> 
> 
> Prof. Mark Schaffer
> Director, CERT
> Department of Economics
> School of Management & Languages
> Heriot-Watt University, Edinburgh EH14 4AS
> tel +44-131-451-3494 / fax +44-131-451-3294
> email: m.e.schaffer@hw.ac.uk
> web: http://www.sml.hw.ac.uk/ecomes
> 
> 
> 
> __________________________________________________________________
> 
> DISCLAIMER:
> 
> This e-mail message is subject to http://www.hw.ac.uk/disclaim.htm
> __________________________________________________________________
> 
> *
> *   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/



© Copyright 1996–2014 StataCorp LP   |   Terms of use   |   Privacy   |   Contact us   |   What's new   |   Site index