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Re: st: RE: ivreg2 2sls, gmm2s and autocorrelation test


From   Marie-Hélène Felt <marie-helene.felt.1@ulaval.ca>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: RE: ivreg2 2sls, gmm2s and autocorrelation test
Date   Tue, 21 Oct 2008 13:34:19 -0400

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?



Selon "Schaffer, Mark E" <M.E.Schaffer@hw.ac.uk>, 21.10.2008:

> Marie-Helene,
>
> > -----Original Message-----
> > From: owner-statalist@hsphsun2.harvard.edu
> > [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of
> > Marie-Hélène Felt
> > Sent: Tuesday, October 21, 2008 5:14 PM
> > To: statalist@hsphsun2.harvard.edu
> > 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/
>
>


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