Nope. In fact, I would like to avoid having to do this if possible.
The code runs in a research data center, which means that all output
has to be checked for confidentiality, and I am not sure whether they
would allow me to use -trace- (using it obviously increases their work
load by a lot). I'll try to recreate the error using data I have on my
pc, but I'm not sure if this works. I basically hoped for an easy
solution in the spirit of "Your variable name is too long", but if
this problem turns out to be more difficult, I'll have to think of
something else...
Best,
Nils
On Thu, Dec 17, 2009 at 1:36 PM, Martin Weiss <[email protected]> wrote:
>
> <>
>
> Have you -trace-d the error yet?
>
>
>
> HTH
> Martin
>
>
> -----Ursprüngliche Nachricht-----
> Von: [email protected]
> [mailto:[email protected]] Im Auftrag von Nils Braakmann
> Gesendet: Donnerstag, 17. Dezember 2009 13:27
> An: [email protected]
> Betreff: st: Problem with xtivreg2
>
> Dear all,
>
> I am just revisiting an old paper (running under version control for
> version 9.2 under a version 10.2 maching in a research data center)
> and encounter a strange problem with xtivreg2.
>
> In february I ran the following code:
>
> xtivreg2 `depvar' `indepvars' `exovars' (overall_coeff_var
> overall_coeff_var_sq = L.overall_coeff_var L.overall_coeff_var_sq
> L2.overall_coeff_var L2.overall_coeff_var_sq), fd gmm robust
>
> and got the following results:
>
> Warning - collinearities detected
> Vars dropped: D.year_d7 D.year_d6 D.year_d5
>
> FIRST DIFFERENCES ESTIMATION
> ----------------------------
> Number of groups = 1022 Obs per group: min =
> 1
> avg =
> 2.6
> max =
> 7
>
> 2-Step GMM estimation
> ---------------------
>
> Statistics robust to heteroskedasticity
>
> Number of obs =
> 2627
> F( 24, 2602) =
> 4.62
> Prob > F =
> 0.0000
> Total (centered) SS = 113.3549125 Centered R2 =
> -0.0026
> Total (uncentered) SS = 113.83846 Uncentered R2 =
> 0.0017
> Residual SS = 113.6464909 Root MSE =
> .208
>
> ----------------------------------------------------------------------------
> --
> | Robust
> D. |
> log_return~d | Coef. Std. Err. z P>|z| [95% Conf.
> Interval]
> -------------+--------------------------------------------------------------
> --
> overall_co~q |
> D1. | 6.448465 5.537348 1.16 0.244 -4.404538
> 17.30147
> overall_co~r |
> D1. | -4.672704 3.66052 -1.28 0.202 -11.84719
> 2.501784
> year_d13 |
> D1. | .1064509 .1903947 0.56 0.576 -.2667159
> .4796177
> year_d12 |
> D1. | .0660634 .1644337 0.40 0.688 -.2562208
> .3883475
> year_d11 |
> D1. | .085434 .1305051 0.65 0.513 -.1703513
> .3412193
> year_d10 |
> D1. | .0852973 .0898904 0.95 0.343 -.0908845
> .2614792
> year_d9 |
> D1. | .053293 .0615972 0.87 0.387 -.0674353
> .1740213
> year_d8 |
> D1. | .0145953 .0313659 0.47 0.642 -.0468806
> .0760713
> work_council |
> D1. | .0044819 .0428912 0.10 0.917 -.0795833
> .0885471
> bargain_firm |
> D1. | -.0117102 .022009 -0.53 0.595 -.054847
> .0314266
> bargain_br~h |
> D1. | .0176108 .0160317 1.10 0.272 -.0138109
> .0490324
> share_women |
> D1. | -.3123268 .3655674 -0.85 0.393 -1.028826
> .4041721
> invest_head |
> D1. | 3.60e-07 3.37e-07 1.07 0.286 -3.02e-07
> 1.02e-06
> share_acad~c |
> D1. | -.1039652 .6003136 -0.17 0.863 -1.280558
> 1.072628
> share_other |
> D1. | -.6331339 .5519297 -1.15 0.251 -1.714896
> .4486285
> share_whit~l |
> D1. | .2077333 .4054792 0.51 0.608 -.5869912
> 1.002458
> share_unsk~d |
> D1. | -.5069874 .2573503 -1.97 0.049 -1.011385
> -.00259
> share_azubi |
> D1. | -.4534471 1.215144 -0.37 0.709 -2.835085
> 1.928191
> share_age50 |
> D1. | .1681527 .3965507 0.42 0.672 -.6090725
> .9453778
> share_a~4050 |
> D1. | .2137222 .3380754 0.63 0.527 -.4488933
> .8763378
> share_age30 |
> D1. | -.3064232 .4795452 -0.64 0.523 -1.246315
> .6334681
> firmsize_sq |
> D1. | 3.84e-08 1.06e-08 3.61 0.000 1.76e-08
> 5.91e-08
> firmsize |
> D1. | -.0005478 .0001474 -3.72 0.000 -.0008367
> -.0002589
> avg_wage |
> D1. | .0032925 .0037199 0.89 0.376 -.0039983
> .0105834
> _cons | -.003982 .0268464 -0.15 0.882 -.0566
> .048636
> ----------------------------------------------------------------------------
> --
> Anderson canon. corr. LR statistic (underidentification test):
> 108.788
> Chi-sq(3) P-val =
> 0.0000
> Test statistic(s) not robust
> ----------------------------------------------------------------------------
> --
> Cragg-Donald F statistic (weak identification test):
> 27.483
> Stock-Yogo weak ID test critical values: 5% maximal IV relative bias
> 11.04
> 10% maximal IV relative bias
> 7.56
> 20% maximal IV relative bias
> 5.57
> 30% maximal IV relative bias
> 4.73
> 10% maximal IV size
> 16.87
> 15% maximal IV size
> 9.93
> 20% maximal IV size
> 7.54
> 25% maximal IV size
> 6.28
> Test statistic(s) not robust
> Source: Stock-Yogo (2005). Reproduced by permission.
> ----------------------------------------------------------------------------
> --
> Hansen J statistic (overidentification test of all instruments):
> 1.761
> Chi-sq(2) P-val =
> 0.4147
> ----------------------------------------------------------------------------
> --
> Instrumented: D.overall_coeff_var_sq D.overall_coeff_var
> Included instruments: D.year_d13 D.year_d12 D.year_d11 D.year_d10 D.year_d9
> D.year_d8 D.work_council D.bargain_firm
> D.bargain_branch
> D.share_women D.invest_head D.share_academic
> D.share_other
> D.share_whitecol D.share_unskilled D.share_azubi
> D.share_age50 D.share_age4050 D.share_age30
> D.firmsize_sq
> D.firmsize D.avg_wage
> Excluded instruments: L2D.overall_coeff_var_sq L2D.overall_coeff_var
> LD.overall_coeff_var_sq LD.overall_coeff_var
> Dropped collinear: D.year_d7 D.year_d6 D.year_d5
> ----------------------------------------------------------------------------
> --
>
>
>
> Some days ago, I changed the instruments from lagged first and second
> differences to lagged second and third differences, gmm to 2sls and
> added clustered standard errors and the option -first- to have a look
> at the first stage results. In other words, I ran the following code:
> xtivreg2 `depvar' `indepvars' `exovars' (overall_coeff_var
> overall_coeff_var_sq = L2.overall_coeff_var L2.overall_coeff_var_sq
> L3.overall_coeff_var L3.overall_coeff_var_sq), fd cluster(idnum) first
>
> This time I get an error message:
>
> D.overall_coeff_v invalid name
> r(198); t=8.63 11:10:53
>
> As far as I know neither the Stata Version, nor the dataset used have
> been changed in the meantime. SAme applies to the macros used for the
> dependent and independent variables.
>
> I'd greatly appreciate any input on this issue as I am a bit (well,
> really) lost at present.
>
> Best,
> Nils
> *
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>
>
> *
> * For searches and help try:
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> * http://www.ats.ucla.edu/stat/stata/
>
*
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