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 <[email protected]> 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 <[email protected]> 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 <[email protected]> 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: [email protected]
> 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:
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> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
>
*
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