> the -help- for xtabond2 is quiet comprehensive
ups, that should have been quite
- it is hard to tell why you loose so many instruments without knowing
your data. If you checked for collinearity in your regressors, e.g. just
running an OLS, my guess would be that the problem is associated with your
set of instruments
johannes
>
> these papers might be helpful:
>
> http://ideas.repec.org/p/cgd/wpaper/103.html
> www.nuff.ox.ac.uk/users/bond/cwp0209.pdf
>
> Regards,
> Johannes
>
>
> ----------------------
> Johannes Geyer
> Deutsches Institut f�r Wirtschaftsforschung (DIW Berlin)
> German Institute for Economic Research
> Department of Public Economics
> DIW Berlin
> Mohrenstra�e 58
> 10117 Berlin
> Tel: +49-30-89789-258
>
> [email protected] schrieb am 23/09/2008 06:18:15:
>
> > Dear stata users
> >
> > I'm a just beginner for xtabond2, so I don't know how to interpret
> > the result below especially regarding
> >
> > Arellano-Bond autocorrelation test, Sargan test and Hansen test.
> >
> > I'm not sure but my guess is that it says that there is both AR(1)
> > and AR(2), may be some IVs are correlated with error term. If my
> > guess is right, then what should I do?
> >
> > Please see my log below and help!!
> >
> >
> >
> > . xtabond2 dlcapx l1_dlcapx dls l1_xinter4 l1_minter4 y9* y0*,
> > gmm(l1_dlcapx dls) iv(l1_xinter4 l1_minter4 y9* y0*, equation(level))
> orth
> > > ogonal robust twostep
> > Favoring speed over space. To switch, type or click on mata: mata
> > set matafavor space, perm.
> > y90 dropped due to collinearity
> > y91 dropped due to collinearity
> > y92 dropped due to collinearity
> > y93 dropped due to collinearity
> > y94 dropped due to collinearity
> > y95 dropped due to collinearity
> > y96 dropped due to collinearity
> > y97 dropped due to collinearity
> > y07 dropped due to collinearity
> > Warning: Two-step estimated covariance matrix of moments is singular.
> > Using a generalized inverse to calculate optimal weighting matrix
> > for two-step estimation.
> > Difference-in-Sargan statistics may be negative.
> > Dynamic panel-data estimation, two-step system GMM
> >
>
------------------------------------------------------------------------------
> > Group variable: gvkey Number of obs =
> 3607
> > Time variable : year Number of groups =
> 874
> > Number of instruments = 218 Obs per group: min = 2
> > Wald chi2(13) = 211.52 avg =
> 4.13
> > Prob > chi2 = 0.000 max =
10
> >
>
------------------------------------------------------------------------------
> > | Corrected
> > dlcapx | Coef. Std. Err. z P>|z| [95%
> Conf.Interval]
> >
>
-------------+----------------------------------------------------------------
> > l1_dlcapx | -.2007464 .0302184 -6.64 0.000 -.2599734
> -.1415195
> > dls | .6778161 .0993139 6.82 0.000 .4831644
> .8724677
> > l1_xinter4 | -2.53827 1.47796 -1.72 0.086 -5.43502
> .3584791
> > l1_minter4 | 17.70894 5.754314 3.08 0.002 6.430696
> 28.98719
> > y98 | -.0185858 .2891494 -0.06 0.949 -.5853082
> .5481365
> > y99 | -.0792788 .2839134 -0.28 0.780 -.6357388
> .4771813
> > y00 | -.0249017 .2810219 -0.09 0.929 -.5756945
> .5258911
> > y01 | -.2103614 .2918474 -0.72 0.471 -.7823718
> .361649
> > y02 | -.2527464 .2846071 -0.89 0.375 -.8105661
> .3050734
> > y03 | -.0863709 .2797089 -0.31 0.757 -.6345903
> .4618485
> > y04 | .2565646 .2892443 0.89 0.375 -.3103438
> .8234729
> > y05 | .1678996 .2790313 0.60 0.547 -.3789918
> .7147909
> > y06 | .0993331 .2821207 0.35 0.725 -.4536133
> .6522794
> > _cons | -.0553731 .277753 -0.20 0.842 -.599759
> .4890129
> >
>
------------------------------------------------------------------------------
> > Instruments for orthogonal deviations equation
> > GMM-type (missing=0, separate instruments for each period unless
> collapsed)
> > L(1/.).(l1_dlcapx dls)
> > Instruments for levels equation
> > Standard
> > _cons
> > l1_xinter4 l1_minter4 y90 y91 y92 y93 y94 y95 y96 y97 y98 y99 y00
> y01 y02
> > y03 y04 y05 y06 y07
> > GMM-type (missing=0, separate instruments for each period unless
> collapsed)
> > D.(l1_dlcapx dls)
> >
>
------------------------------------------------------------------------------
> > Arellano-Bond test for AR(1) in first differences: z = -6.72 Pr > z
=
> 0.000
> > Arellano-Bond test for AR(2) in first differences: z = -3.23 Pr > z
=
> 0.001
> >
>
------------------------------------------------------------------------------
> > Sargan test of overid. restrictions: chi2(204) = 621.40 Prob > chi2
=
> 0.000
> > (Not robust, but not weakened by many instruments.)
> > Hansen test of overid. restrictions: chi2(204) = 238.63 Prob > chi2
=
> 0.049
> > (Robust, but can be weakened by many instruments.)
> > Difference-in-Hansen tests of exogeneity of instrument subsets:
> > GMM instruments for levels
> > Hansen test excluding group: chi2(184) = 216.29 Prob > chi2
=
> 0.052
> > Difference (null H = exogenous): chi2(20) = 22.35 Prob > chi2
=
> 0.322
> > iv(l1_xinter4 l1_minter4 y90 y91 y92 y93 y94 y95 y96 y97 y98 y99
> > y00 y01 y02 y03 y04 y05 y06 y07, eq(level))
> > Hansen test excluding group: chi2(193) = 227.63 Prob > chi2
=
> 0.045
> > Difference (null H = exogenous): chi2(11) = 11.00 Prob > chi2
=
> 0.443
> >
> >
> > I really appreciate your cooperation!!
> >
> > Caleb
> >
> >
> > *
> > * 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/
*
* For searches and help try:
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* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
