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Re: st: RE: omitted constant with ivregress 2sls but not with ivregress gmm or ivreg
From
pablo martinelli <[email protected]>
To
[email protected]
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 <[email protected]>:
> 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: [email protected] [mailto:owner-
>> [email protected]] On Behalf Of pablo martinelli
>> Sent: 28 October 2013 15:22
>> To: [email protected]
>> 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
>> *
>> * For searches and help try:
>> * http://www.stata.com/help.cgi?search
>> * http://www.stata.com/support/faqs/resources/statalist-faq/
>> * http://www.ats.ucla.edu/stat/stata/
>
>
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