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# st: AW: Problem with xtivreg2

 From "Martin Weiss" To Subject st: AW: Problem with xtivreg2 Date Thu, 17 Dec 2009 13:36:14 +0100

```<>

Have you -trace-d the error yet?

HTH
Martin

-----Ursprüngliche Nachricht-----
Von: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von Nils Braakmann
Gesendet: Donnerstag, 17. Dezember 2009 13:27
An: statalist@hsphsun2.harvard.edu
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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