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RE: st: RE: ivreg2 2sls, gmm2s and autocorrelation test
Marie-Helen,
> -----Original Message-----
> From: [email protected]
> [mailto:[email protected]] On Behalf Of
> Marie-Hélène Felt
> Sent: Tuesday, October 21, 2008 6:34 PM
> To: [email protected]
> Subject: Re: st: RE: ivreg2 2sls, gmm2s and autocorrelation test
>
> I'm sorry I didn't mention it:
> I have:
> c:\ado\plus\i\ivreg2.ado
> *! ivreg2 2.2.08 15oct2007
> *! authors cfb & mes
> *! see end of file for version comments
>
> c:\ado\plus\a\abar.ado
> *! abar 1.1.0 9 Nov 2007
> *! David Roodman, Center for Global Development, Washington,
> DC, www.cgdev.org
>
> would a question of version explain these results?
Possibly. Updating is a good idea anyway, so you should probably update and see if the problem goes away.
--Mark
> Selon "Schaffer, Mark E" <[email protected]>, 21.10.2008:
>
> > Marie-Helene,
> >
> > > -----Original Message-----
> > > From: [email protected]
> > > [mailto:[email protected]] On Behalf Of
> > > Marie-Hélène Felt
> > > Sent: Tuesday, October 21, 2008 5:14 PM
> > > To: [email protected]
> > > Subject: st: ivreg2 2sls, gmm2s and autocorrelation test
> > >
> > > hello,
> > >
> > > I'm using IVREG2 to estimate a regression with one endogenous
> > > regressor.
> > > I noticed that the results of -abar- (test for AC) are really
> > > different after a
> > > 2SLS H robust estimation and a GMM2S H robust estimation.
> > > After 2SLS it seems
> > > that I have AC, but not after GMM2S...but it's the same
> equation I'm
> > > estimating!!
> >
> > The first step in these things is always to check that you
> have the latest
> > versions installed (and also to tell us which version of
> Stata you're using).
> >
> > I have
> >
> > . which ivreg2
> > c:\ado10\plus\i\ivreg2.ado
> > *! ivreg2 2.2.09 17jul2008
> > *! authors cfb & mes
> > *! see end of file for version comments
> >
> > . which abar
> > c:\ado10\plus\a\abar.ado
> > *! abar 1.1.0 9 Nov 2007
> > *! David Roodman, Center for Global Development, Washington, DC,
> > www.cgdev.org
> >
> > What about you?
> >
> > --Mark
> >
> > > I'm working with time series, and not with cross sectional
> > > time series, so I'm
> > > wondering if I'm allowed to use -abar- after both ivreg2
> > > estimations (2sls and
> > > gmm2s).
> > > If indeed I'm allowed to use it, how should I understand
> > > these results?
> > > Would you suggest to use -ivactest- rather than -abar-??
> > >
> > > I report hereafter my results.
> > >
> > > Thank you for your help,
> > >
> > > Marie Helene
> > >
> > > . ivreg2 lnpda lntxus lnpvus lntxca lnpvca lnipja
> > > (lnqda=lntxda lnpvda), robust
> > >
> > > IV (2SLS) estimation
> > > --------------------
> > >
> > > Estimates efficient for homoskedasticity only
> > > Statistics robust to heteroskedasticity
> > >
> > > Number
> > > of obs = 148
> > > F( 6,
> > > 141) = 4.96
> > > Prob >
> > > F = 0.0001
> > > Total (centered) SS = 1.439041186
> > > Centered R2 = -0.0540
> > > Total (uncentered) SS = 26084.88825
> > > Uncentered R2 = 0.9999
> > > Residual SS = 1.516815821 Root
> > > MSE = .1012
> > >
> > > --------------------------------------------------------------
> > > ----------------
> > > | Robust
> > > lnpda | Coef. Std. Err. z P>|z|
> > > [95% Conf. Interval]
> > > -------------+------------------------------------------------
> > > ----------------
> > > lnqda | -.0943358 .0205959 -4.58 0.000
> > > -.1347031 -.0539685
> > > lntxus | .3162592 .3225253 0.98 0.327
> > > -.3158787 .9483971
> > > lnpvus | .1865913 .2975095 0.63 0.531
> > > -.3965166 .7696993
> > > lntxca | -.2562668 .3309884 -0.77 0.439
> > > -.9049921 .3924585
> > > lnpvca | -.1924842 .3003962 -0.64 0.522
> > > -.7812501 .3962816
> > > lnipja | .2326394 .2220086 1.05 0.295
> > > -.2024894 .6677681
> > > _cons | 12.7047 1.322835 9.60 0.000
> > > 10.11199 15.29741
> > > --------------------------------------------------------------
> > > ----------------
> > > Underidentification test (Kleibergen-Paap rk LM statistic):
> > > 13.650
> > > Chi-sq(2)
> > > P-val = 0.0011
> > > --------------------------------------------------------------
> > > ----------------
> > > Weak identification test (Kleibergen-Paap rk Wald F
> > > statistic): 8.977
> > > Stock-Yogo weak ID test critical values: 10% maximal IV size
> > > 19.93
> > > 15% maximal IV size
> > > 11.59
> > > 20% maximal IV size
> > > 8.75
> > > 25% maximal IV size
> > > 7.25
> > > Source: Stock-Yogo (2005). Reproduced by permission.
> > > NB: Critical values are for Cragg-Donald F statistic and
> > > i.i.d. errors.
> > > --------------------------------------------------------------
> > > ----------------
> > > Hansen J statistic (overidentification test of all
> > > instruments): 0.533
> > > Chi-sq(1)
> > > P-val = 0.4653
> > > --------------------------------------------------------------
> > > ----------------
> > > Instrumented: lnqda
> > > Included instruments: lntxus lnpvus lntxca lnpvca lnipja
> > > Excluded instruments: lntxda lnpvda
> > > --------------------------------------------------------------
> > > ----------------
> > >
> > > . abar, lags(6)
> > > Warning: The Arellano-Bond test is only valid for time series
> > > only if they are
> > > ergodic.
> > > Arellano-Bond test for AR(1): z = 5.77 Pr > z = 0.0000
> > > Arellano-Bond test for AR(2): z = 4.34 Pr > z = 0.0000
> > > Arellano-Bond test for AR(3): z = 3.48 Pr > z = 0.0005
> > > Arellano-Bond test for AR(4): z = 2.02 Pr > z = 0.0437
> > > Arellano-Bond test for AR(5): z = 0.47 Pr > z = 0.6380
> > > Arellano-Bond test for AR(6): z = 0.96 Pr > z = 0.3350
> > >
> > > . ivreg2 lnpda lntxus lnpvus lntxca lnpvca lnipja
> > > (lnqda=lntxda lnpvda), gmm2s
> > > robust
> > >
> > > 2-Step GMM estimation
> > > ---------------------
> > >
> > > Estimates efficient for arbitrary heteroskedasticity
> > > Statistics robust to heteroskedasticity
> > >
> > > Number
> > > of obs = 148
> > > F( 6,
> > > 141) = 4.89
> > > Prob >
> > > F = 0.0001
> > > Total (centered) SS = 1.439041186
> > > Centered R2 = -0.0525
> > > Total (uncentered) SS = 26084.88825
> > > Uncentered R2 = 0.9999
> > > Residual SS = 1.514566079 Root
> > > MSE = .1012
> > >
> > > --------------------------------------------------------------
> > > ----------------
> > > | Robust
> > > lnpda | Coef. Std. Err. z P>|z|
> > > [95% Conf. Interval]
> > > -------------+------------------------------------------------
> > > ----------------
> > > lnqda | -.0941792 .0205948 -4.57 0.000
> > > -.1345443 -.0538141
> > > lntxus | .3132924 .3224997 0.97 0.331
> > > -.3187954 .9453801
> > > lnpvus | .1590178 .2951029 0.54 0.590
> > > -.4193732 .7374088
> > > lntxca | -.2397403 .3302135 -0.73 0.468
> > > -.8869469 .4074662
> > > lnpvca | -.163539 .2977688 -0.55 0.583
> > > -.7471551 .4200772
> > > lnipja | .2394675 .2218115 1.08 0.280
> > > -.1952751 .6742101
> > > _cons | 12.61117 1.316618 9.58 0.000
> > > 10.03065 15.19169
> > > --------------------------------------------------------------
> > > ----------------
> > > Underidentification test (Kleibergen-Paap rk LM statistic):
> > > 13.650
> > > Chi-sq(2)
> > > P-val = 0.0011
> > > --------------------------------------------------------------
> > > ----------------
> > > Weak identification test (Kleibergen-Paap rk Wald F
> > > statistic): 8.977
> > > Stock-Yogo weak ID test critical values: 10% maximal IV size
> > > 19.93
> > > 15% maximal IV size
> > > 11.59
> > > 20% maximal IV size
> > > 8.75
> > > 25% maximal IV size
> > > 7.25
> > > Source: Stock-Yogo (2005). Reproduced by permission.
> > > NB: Critical values are for Cragg-Donald F statistic and
> > > i.i.d. errors.
> > > --------------------------------------------------------------
> > > ----------------
> > > Hansen J statistic (overidentification test of all
> > > instruments): 0.533
> > > Chi-sq(1)
> > > P-val = 0.4653
> > > --------------------------------------------------------------
> > > ----------------
> > > Instrumented: lnqda
> > > Included instruments: lntxus lnpvus lntxca lnpvca lnipja
> > > Excluded instruments: lntxda lnpvda
> > > --------------------------------------------------------------
> > > ----------------
> > >
> > > . abar, lags(6)
> > > Warning: The Arellano-Bond test is only valid for time series
> > > only if they are
> > > ergodic.
> > > Arellano-Bond test for AR(1): z = 0.99 Pr > z = 0.3202
> > > Arellano-Bond test for AR(2): z = 0.99 Pr > z = 0.3203
> > > Arellano-Bond test for AR(3): z = 0.99 Pr > z = 0.3232
> > > Arellano-Bond test for AR(4): z = 0.99 Pr > z = 0.3233
> > > Arellano-Bond test for AR(5): z = 0.83 Pr > z = 0.4050
> > > Arellano-Bond test for AR(6): z = 0.85 Pr > z = 0.3944
> > >
> > > *
> > > * For searches and help try:
> > > * http://www.stata.com/help.cgi?search
> > > * http://www.stata.com/support/statalist/faq
> > > * http://www.ats.ucla.edu/stat/stata/
> > >
> >
> >
> > --
> > Heriot-Watt University is a Scottish charity
> > registered under charity number SC000278.
> >
> >
> > *
> > * For searches and help try:
> > * http://www.stata.com/help.cgi?search
> > * http://www.stata.com/support/statalist/faq
> > * http://www.ats.ucla.edu/stat/stata/
> >
> >
>
>
> *
> * For searches and help try:
> * http://www.stata.com/help.cgi?search
> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
>
--
Heriot-Watt University is a Scottish charity
registered under charity number SC000278.
*
* For searches and help try:
* http://www.stata.com/help.cgi?search
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/