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Re: st: RE: omitted constant with ivregress 2sls but not with ivregress gmm or ivreg


From   pablo martinelli <pab.martinelli@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: RE: omitted constant with ivregress 2sls but not with ivregress gmm or ivreg
Date   Tue, 29 Oct 2013 17:53:22 +0100

Hi everyone again.

No, ivreg2 does not drop the constant.

Yes, sure, Mark. Here are my command lines the results i get. Since I
have many variables, and tehre is a limit to the message's size we can
send, I will split them.

First, ivregress.

. ivregress 2sls lnrtw240w tpr eshare avrentp sharecrop tenant
nonagremp wheatshare wheatyield piemontevalledaosta liguria lombardia
trentinoaltoadige veneto emilia toscana lazio abruzzi campania pugli
> e lucania calabria sicilia sardegna avmrain cvavmrain rainwin rainspr rainsum rainaut rainwin2 rainspr2 rainsum2 rainaut2 cvrainwin cvrainspr cvrainsum cvrainaut rainintwin rainintspr rainintsum rain
> intaut cvrainintwin cvrainintspr cvrainintsum cvrainintaut height1 dislivello newslope latitude (LabnewLand3=lnpop31land), first robust

First-stage regressions
-----------------------

                                                  Number of obs   =        727
                                                  F(  50,    676) =     368.73
                                                  Prob > F        =     0.0000
                                                  R-squared       =     0.9367
                                                  Adj R-squared   =     0.9320
                                                  Root MSE        =     0.1811

------------------------------
------------------------------------------------
             |               Robust
 LabnewLand3 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         tpr |  -.0752534    .030686    -2.45   0.014    -.1355048   -.0150021
      eshare |  -.2042971   .0787484    -2.59   0.010     -.358918   -.0496762
     avrentp |   2.59e-06   7.47e-06     0.35   0.729    -.0000121    .0000173
   sharecrop |   .1223223   .0690329     1.77   0.077    -.0132225    .2578671
      tenant |   .1070509   .1124441     0.95   0.341    -.1137308    .3278327
   nonagremp |  -.0185542   .0009113   -20.36   0.000    -.0203435   -.0167649
  wheatshare |   .2611341   .0944493     2.76   0.006     .0756848    .4465834
  wheatyield |   .0077474   .0026325     2.94   0.003     .0025786    .0129162
piemonteva~a |   .1687091   .0581959     2.90   0.004     .0544426    .2829756
     liguria |   .1656128   .0810158     2.04   0.041     .0065398    .3246857
   lombardia |    .051234   .0601551     0.85   0.395    -.0668793    .1693473
trentinoal~e |   .1392318   .0809547     1.72   0.086     -.019721    .2981846
      veneto |  -.0195738   .0605925    -0.32   0.747    -.1385459    .0993983
      emilia |  -.0295481   .0423374    -0.70   0.485    -.1126767    .0535805
     toscana |   .0268248   .0436844     0.61   0.539    -.0589485    .1125982
       lazio |   .0405166   .0498447     0.81   0.417    -.0573524    .1383856
     abruzzi |  -.1850101   .0471699    -3.92   0.000    -.2776273   -.0923929
    campania |   -.007703   .0852096    -0.09   0.928    -.1750103    .1596043
      puglie |  -.2555594   .0761643    -3.36   0.001    -.4051065   -.1060124
     lucania |  -.1024758   .0858727    -1.19   0.233    -.2710851    .0661336
    calabria |  -.2699014   .0986603    -2.74   0.006    -.4636189    -.076184
     sicilia |  -.4293593   .1652127    -2.60   0.010     -.753751   -.1049676
    sardegna |  -.4646977   .0892632    -5.21   0.000    -.6399643   -.2894312
     avmrain |  -.0081846   .0161084    -0.51   0.612    -.0398132     .023444
   cvavmrain |   .0811425    .192954     0.42   0.674    -.2977187    .4600036
     rainwin |   .0013707    .001745     0.79   0.432    -.0020556     .004797
     rainspr |  -.0015337   .0015158    -1.01   0.312      -.00451    .0014426
     rainsum |    .001587   .0014179     1.12   0.263    -.0011969     .004371
     rainaut |   .0022904   .0014189     1.61   0.107    -.0004955    .0050763
    rainwin2 |   1.97e-07   8.11e-07     0.24   0.808    -1.40e-06    1.79e-06
    rainspr2 |   1.39e-06   5.14e-07     2.71   0.007     3.83e-07    2.40e-06
    rainsum2 |  -2.37e-07   6.17e-07    -0.38   0.701    -1.45e-06    9.75e-07
    rainaut2 |  -2.03e-06   8.34e-07    -2.43   0.015    -3.67e-06   -3.93e-07
   cvrainwin |  -.1337135   .0910987    -1.47   0.143    -.3125838    .0451569
   cvrainspr |  -.0919449   .1411574    -0.65   0.515    -.3691047    .1852148
   cvrainsum |   .0620552   .0583617     1.06   0.288    -.0525368    .1766472
   cvrainaut |  -.0228216   .1275591    -0.18   0.858    -.2732812     .227638
  rainintwin |  -.0038742     .01052    -0.37   0.713      -.02453    .0167816
  rainintspr |    .025346   .0082647     3.07   0.002     .0091184    .0415735
  rainintsum |  -.0158319   .0053415    -2.96   0.003    -.0263199   -.0053438
  rainintaut |  -.0026335    .008307    -0.32   0.751    -.0189442    .0136772
cvrainintwin |   .1142515   .1082358     1.06   0.292    -.0982673    .3267703
cvrainintspr |  -.1338668    .071614    -1.87   0.062    -.2744795    .0067459
cvrainintsum |  -.0174779   .0458837    -0.38   0.703    -.1075696    .0726138
cvrainintaut |   -.047752   .0917345    -0.52   0.603    -.2278708    .1323668
     height1 |  -.0000976   .0000593    -1.65   0.100    -.0002141    .0000189
  dislivello |  -.0001469   .0001313    -1.12   0.263    -.0004047    .0001108
    newslope |   36.73272   10.35384     3.55   0.000     16.40318    57.06227
    latitude |   .0000167   .0002471     0.07   0.946    -.0004684    .0005018
 lnpop31land |   .8216411   .0354665    23.17   0.000     .7520034    .8912789
       _cons |  -.5036778     1.1633    -0.43   0.665    -2.787793    1.780437
------------------------------------------------------------------------------


Instrumental variables (2SLS) regression               Number of obs =     727
                                                       Wald chi2(50) =20562.26
                                                       Prob > chi2   =  0.0000
                                                       R-squared     =  0.8932
                                                       Root MSE      =  .32042

------------------------------------------------------------------------------
             |               Robust
   lnrtw240w |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
 LabnewLand3 |   .7267861   .0450934    16.12   0.000     .6384046    .8151675
         tpr |   .1458045    .032423     4.50   0.000     .0822565    .2093525
      eshare |  -.5817712   .1438029    -4.05   0.000    -.8636196   -.2999228
     avrentp |   .0001137   .0000132     8.63   0.000     .0000879    .0001395
   sharecrop |  -.2948938    .115277    -2.56   0.011    -.5208325   -.0689551
      tenant |  -.0748224   .1830473    -0.41   0.683    -.4335884    .2839437
   nonagremp |   .0045094   .0009825     4.59   0.000     .0025837    .0064351
  wheatshare |    .268118   .1990714     1.35   0.178    -.1220547    .6582907
  wheatyield |   .0150569   .0046811     3.22   0.001      .005882    .0242317
piemonteva~a |    .457105   .1139754     4.01   0.000     .2337173    .6804928
     liguria |  -.6659745   .1643922    -4.05   0.000    -.9881773   -.3437717
   lombardia |   .1699226   .1148089     1.48   0.139    -.0550987    .3949439
trentinoal~e |   .5750365   .1708428     3.37   0.001     .2401908    .9098822
      veneto |   .3072996   .1069846     2.87   0.004     .0976137    .5169855
      emilia |  -.0965144   .0759654    -1.27   0.204    -.2454038     .052375
     toscana |  -.2014353    .068682    -2.93   0.003    -.3360495   -.0668211
       lazio |   .1704884   .0814061     2.09   0.036     .0109354    .3300414
     abruzzi |   .3654339   .0807196     4.53   0.000     .2072264    .5236413
    campania |     .38231   .1131769     3.38   0.001     .1604874    .6041327
      puglie |   .6174175   .1138966     5.42   0.000     .3941843    .8406508
     lucania |   .0233558   .1259724     0.19   0.853    -.2235455    .2702572
    calabria |   .0643192   .1278942     0.50   0.615    -.1863488    .3149872
     sicilia |   .0892816   .1851743     0.48   0.630    -.2736534    .4522166
    sardegna |  -.2924706   .1315056    -2.22   0.026    -.5502168   -.0347244
     avmrain |    .091309   .0299047     3.05   0.002     .0326968    .1499212
   cvavmrain |   .0704218   .2632369     0.27   0.789    -.4455132    .5863567
     rainwin |  -.0085437   .0027881    -3.06   0.002    -.0140082   -.0030791
     rainspr |  -.0065773   .0028433    -2.31   0.021      -.01215   -.0010046
     rainsum |  -.0078591   .0027321    -2.88   0.004     -.013214   -.0025043
     rainaut |  -.0064453   .0027802    -2.32   0.020    -.0118943   -.0009963
    rainwin2 |   8.42e-07   1.35e-06     0.62   0.534    -1.81e-06    3.50e-06
    rainspr2 |  -1.64e-06   1.41e-06    -1.17   0.244    -4.40e-06    1.12e-06
    rainsum2 |  -7.44e-07   1.30e-06    -0.57   0.568    -3.30e-06    1.81e-06
    rainaut2 |  -1.36e-06   1.39e-06    -0.98   0.328    -4.08e-06    1.36e-06
   cvrainwin |   .5463342   .1663811     3.28   0.001     .2202332    .8724353
   cvrainspr |  -.1413404   .1943371    -0.73   0.467    -.5222341    .2395533
   cvrainsum |  -.0781232   .1270969    -0.61   0.539    -.3272285    .1709822
   cvrainaut |  -.1209869    .209468    -0.58   0.564    -.5315367    .2895629
  rainintwin |  -.0434683   .0193887    -2.24   0.025    -.0814695   -.0054672
  rainintspr |   .0229036   .0185125     1.24   0.216    -.0133803    .0591875
  rainintsum |     -.0028   .0119597    -0.23   0.815    -.0262406    .0206406
  rainintaut |   .0026536   .0160065     0.17   0.868    -.0287186    .0340258
cvrainintwin |  -.1953799   .1654534    -1.18   0.238    -.5196627    .1289029
cvrainintspr |   .1423667   .1475175     0.97   0.335    -.1467623    .4314956
cvrainintsum |   .0937196   .0911865     1.03   0.304    -.0850026    .2724418
cvrainintaut |   -.072203   .1696257    -0.43   0.670    -.4046632    .2602572
     height1 |   -.000493   .0001032    -4.78   0.000    -.0006953   -.0002908
  dislivello |  -.0001017     .00021    -0.48   0.628    -.0005132    .0003099
    newslope |          0   .0039293     0.00   1.000    -.0077012    .0077012
    latitude |  -.0005574    .000063    -8.85   0.000    -.0006808   -.0004339
       _cons |  (omitted)
------------------------------------------------------------------------------
Instrumented:  LabnewLand3
Instruments:   tpr eshare avrentp sharecrop tenant nonagremp wheatshare
               wheatyield piemontevalledaosta liguria lombardia
               trentinoaltoadige veneto emilia toscana lazio abruzzi
               campania puglie lucania calabria sicilia sardegna avmrain
               cvavmrain rainwin rainspr rainsum rainaut rainwin2 rainspr2
               rainsum2 rainaut2 cvrainwin cvrainspr cvrainsum cvrainaut
               rainintwin rainintspr rainintsum rainintaut cvrainintwin
               cvrainintspr cvrainintsum cvrainintaut height1 dislivello
               newslope latitude lnpop31land

I know, scaling might be a problem. In particular, if I multiply all
the values of the variable newslope for 100 or 1000, I get a
coefficient that is not 0 and a p-value that is not 1 (though is not
statistically significant). Everything else, remains the same. So the
problem is not  lack of variation in newslope, as one may be tempted
to think having a look at the results just above. However, the
omission of the variable happens only when the 3 variables height1,
dislivello and newslope (which are correlated) are entered as
regressors, although I am not able to conceptually find the reason for
the constant being dropped.

2013/10/28 Schaffer, Mark E <M.E.Schaffer@hw.ac.uk>:
> Pablo,
>
> You need to give us more details, such as the command lines used.  Also, you say
>
>> A potential explanation is that the original ivreg code estimated IV by default
>> with gmm
>
> but that's impossible, because Stata's official -ivreg- never implemented GMM.
>
> Does -ivreg2- with and without -gmm2s- keep or drop the constant?
>
> --Mark
>
>> -----Original Message-----
>> From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-
>> statalist@hsphsun2.harvard.edu] On Behalf Of pablo martinelli
>> Sent: 28 October 2013 15:22
>> To: statalist@hsphsun2.harvard.edu
>> Subject: st: omitted constant with ivregress 2sls but not with ivregress gmm or
>> ivreg
>>
>> Hi all,
>> I am having some difficulties for replicating some results I get in 2011 with an
>> earlier version of Stata (I think it was Stata 7 but I am not sure). Now I am using
>> Stata 11.
>> The problem is the following.
>> When I use ivregress 2sls, Stata omits the constant, even though it is not
>> perfectly collinear with any exogenous or endogenous variables. The
>> coefficients are slightly modified with respect to the original results.
>> (the problem doesn't happen when I use ols).
>> If I use ivregress gmm with robust standard errors I get the original resulst I get
>> in 2011, except for the constant whose estimated value is somewhat different
>> from the orginal. F-statistics, R2, etc are also the same. I obtain the same
>> results with either ivreg and ivreg2.
>> A potential explanation is that the original ivreg code estimated IV by default
>> with gmm, though I have not been able to find confirmation of this point.
>> Some of the regressors are certainly correlated, but not perfectly.
>> Anyway, I cannot figure out why should the constant be ommited with ivregress
>> 2sls and not with ivregress gmm. What is the econometric problem here? And
>> why should in that case any of the two methods (2sls or gmm) preferable to the
>> other?
>> Any explanation, suggestion or hint would be highly appreciated.
>> Best,
>> Pablo Martinelli
>> *
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>> *   http://www.ats.ucla.edu/stat/stata/
>
>
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