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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 17:54:54 +0100
Now, with ivregress and small sample adjustment.
. ivregress gmm lnrtw240w 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 raini
> ntaut cvrainintwin cvrainintspr cvrainintsum cvrainintaut height1 dislivello newslope latitude (LabnewLand3=lnpop31land), first robust small
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 (GMM) regression Number of obs = 727
F( 50, 676) = 140.06
Prob > F = 0.0000
R-squared = 0.8935
Adj R-squared = 0.8857
GMM weight matrix: Robust Root MSE = .33169
------------------------------------------------------------------------------
| Robust
lnrtw240w | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
LabnewLand3 | .7296731 .0497567 14.66 0.000 .631977 .8273693
tpr | .150806 .0334861 4.50 0.000 .0850568 .2165553
eshare | -.5659457 .1519374 -3.72 0.000 -.8642715 -.2676198
avrentp | .0001132 .0000138 8.20 0.000 .0000861 .0001403
sharecrop | -.3001512 .1206596 -2.49 0.013 -.5370638 -.0632387
tenant | -.0879874 .189356 -0.46 0.642 -.459784 .2838091
nonagremp | .0044146 .0010269 4.30 0.000 .0023983 .0064309
wheatshare | .2725696 .2060365 1.32 0.186 -.1319787 .677118
wheatyield | .013572 .0050023 2.71 0.007 .0037501 .0233938
piemonteva~a | .3870626 .1256582 3.08 0.002 .1403354 .6337899
liguria | -.7231312 .177222 -4.08 0.000 -1.071103 -.3751595
lombardia | .0804358 .1303098 0.62 0.537 -.1754248 .3362963
trentinoal~e | .4460556 .1978474 2.25 0.024 .0575863 .8345249
veneto | .200405 .1295511 1.55 0.122 -.053966 .4547759
emilia | -.1549017 .0837739 -1.85 0.065 -.3193899 .0095866
toscana | -.2256237 .0758452 -2.97 0.003 -.3745442 -.0767033
lazio | .2176652 .0869598 2.50 0.013 .0469214 .388409
abruzzi | .4261649 .0871011 4.89 0.000 .2551437 .597186
campania | .5052329 .1388043 3.64 0.000 .2326936 .7777722
puglie | .7343379 .1361629 5.39 0.000 .4669849 1.001691
lucania | .1794245 .1694788 1.06 0.290 -.1533436 .5121925
calabria | .2868967 .2000426 1.43 0.152 -.1058828 .6796763
sicilia | .4136089 .3240687 1.28 0.202 -.2226934 1.049911
sardegna | -.1242169 .1776566 -0.70 0.485 -.473042 .2246081
avmrain | .0922622 .0309448 2.98 0.003 .0315027 .1530217
cvavmrain | .1573777 .2889331 0.54 0.586 -.4099365 .7246919
rainwin | -.0085693 .0029066 -2.95 0.003 -.0142763 -.0028624
rainspr | -.00659 .0029553 -2.23 0.026 -.0123927 -.0007873
rainsum | -.0082152 .0028471 -2.89 0.004 -.0138055 -.002625
rainaut | -.0064073 .0028704 -2.23 0.026 -.0120433 -.0007713
rainwin2 | 7.00e-07 1.46e-06 0.48 0.632 -2.17e-06 3.57e-06
rainspr2 | -1.61e-06 1.45e-06 -1.11 0.269 -4.46e-06 1.24e-06
rainsum2 | -6.10e-07 1.41e-06 -0.43 0.665 -3.37e-06 2.15e-06
rainaut2 | -1.55e-06 1.44e-06 -1.07 0.284 -4.39e-06 1.29e-06
cvrainwin | .4861783 .1804904 2.69 0.007 .1317891 .8405675
cvrainspr | -.2146707 .216391 -0.99 0.322 -.6395499 .2102085
cvrainsum | -.0934008 .1334395 -0.70 0.484 -.3554065 .1686048
cvrainaut | -.1363144 .2152489 -0.63 0.527 -.5589511 .2863223
rainintwin | -.0395274 .0195334 -2.02 0.043 -.0778809 -.001174
rainintspr | .0195541 .0189044 1.03 0.301 -.0175643 .0566724
rainintsum | -.0010367 .0127531 -0.08 0.935 -.0260772 .0240038
rainintaut | .0029407 .016421 0.18 0.858 -.0293015 .035183
cvrainintwin | -.2216308 .1724045 -1.29 0.199 -.5601434 .1168818
cvrainintspr | .1727809 .1478761 1.17 0.243 -.1175708 .4631327
cvrainintsum | .1093444 .095904 1.14 0.255 -.0789611 .2976499
cvrainintaut | -.0724951 .1758545 -0.41 0.680 -.4177818 .2727916
height1 | -.0005161 .0001081 -4.77 0.000 -.0007284 -.0003038
dislivello | -.0000686 .0002501 -0.27 0.784 -.0005596 .0004224
newslope | -4.832518 18.35956 -0.26 0.792 -40.88113 31.21609
latitude | .0000422 .0004502 0.09 0.925 -.0008417 .0009262
_cons | -2.906064 2.088086 -1.39 0.164 -7.005977 1.193849
------------------------------------------------------------------------------
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
2013/10/29 pablo martinelli <[email protected]>:
> This fact is even more puzzling when one
> considers the following results with gmm:
>
>
> . ivregress gmm lnrtw240w 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 raini
>> ntaut 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 (GMM) regression Number of obs = 727
> Wald chi2(50) = 7531.25
> Prob > chi2 = 0.0000
> R-squared = 0.8935
> GMM weight matrix: Robust Root MSE = .31984
>
> ------------------------------------------------------------------------------
> | Robust
> lnrtw240w | Coef. Std. Err. z P>|z| [95% Conf. Interval]
> -------------+----------------------------------------------------------------
> LabnewLand3 | .7296731 .0479797 15.21 0.000 .6356347 .8237115
> tpr | .150806 .0322902 4.67 0.000 .0875184 .2140937
> eshare | -.5659457 .1465112 -3.86 0.000 -.8531023 -.2787891
> avrentp | .0001132 .0000133 8.51 0.000 .0000871 .0001393
> sharecrop | -.3001512 .1163504 -2.58 0.010 -.5281938 -.0721086
> tenant | -.0879874 .1825934 -0.48 0.630 -.445864 .2698891
> nonagremp | .0044146 .0009902 4.46 0.000 .0024738 .0063554
> wheatshare | .2725696 .1986782 1.37 0.170 -.1168325 .6619717
> wheatyield | .013572 .0048236 2.81 0.005 .0041179 .023026
> piemonteva~a | .3870626 .1211705 3.19 0.001 .1495729 .6245524
> liguria | -.7231312 .1708928 -4.23 0.000 -1.058075 -.3881875
> lombardia | .0804358 .125656 0.64 0.522 -.1658454 .326717
> trentinoal~e | .4460556 .1907816 2.34 0.019 .0721305 .8199806
> veneto | .200405 .1249244 1.60 0.109 -.0444424 .4452523
> emilia | -.1549017 .080782 -1.92 0.055 -.3132315 .0034282
> toscana | -.2256237 .0731365 -3.08 0.002 -.3689686 -.0822789
> lazio | .2176652 .0838542 2.60 0.009 .053314 .3820164
> abruzzi | .4261649 .0839904 5.07 0.000 .2615467 .590783
> campania | .5052329 .1338471 3.77 0.000 .2428974 .7675684
> puglie | .7343379 .1313001 5.59 0.000 .4769945 .9916814
> lucania | .1794245 .1634261 1.10 0.272 -.1408848 .4997337
> calabria | .2868967 .1928984 1.49 0.137 -.0911772 .6649707
> sicilia | .4136089 .3124951 1.32 0.186 -.1988704 1.026088
> sardegna | -.1242169 .1713119 -0.73 0.468 -.459982 .2115482
> avmrain | .0922622 .0298397 3.09 0.002 .0337775 .1507469
> cvavmrain | .1573777 .2786143 0.56 0.572 -.3886963 .7034517
> rainwin | -.0085693 .0028028 -3.06 0.002 -.0140627 -.003076
> rainspr | -.00659 .0028498 -2.31 0.021 -.0121755 -.0010046
> rainsum | -.0082152 .0027455 -2.99 0.003 -.0135962 -.0028343
> rainaut | -.0064073 .0027679 -2.31 0.021 -.0118322 -.0009823
> rainwin2 | 7.00e-07 1.41e-06 0.50 0.619 -2.06e-06 3.46e-06
> rainspr2 | -1.61e-06 1.40e-06 -1.15 0.251 -4.35e-06 1.14e-06
> rainsum2 | -6.10e-07 1.36e-06 -0.45 0.653 -3.27e-06 2.05e-06
> rainaut2 | -1.55e-06 1.39e-06 -1.11 0.266 -4.28e-06 1.18e-06
> cvrainwin | .4861783 .1740445 2.79 0.005 .1450574 .8272992
> cvrainspr | -.2146707 .2086629 -1.03 0.304 -.6236425 .1943011
> cvrainsum | -.0934008 .1286739 -0.73 0.468 -.345597 .1587954
> cvrainaut | -.1363144 .2075616 -0.66 0.511 -.5431277 .2704988
> rainintwin | -.0395274 .0188358 -2.10 0.036 -.0764449 -.00261
> rainintspr | .0195541 .0182292 1.07 0.283 -.0161746 .0552827
> rainintsum | -.0010367 .0122977 -0.08 0.933 -.0251396 .0230663
> rainintaut | .0029407 .0158345 0.19 0.853 -.0280944 .0339758
> cvrainintwin | -.2216308 .1662473 -1.33 0.182 -.5474696 .104208
> cvrainintspr | .1727809 .142595 1.21 0.226 -.1067001 .4522619
> cvrainintsum | .1093444 .0924789 1.18 0.237 -.071911 .2905998
> cvrainintaut | -.0724951 .1695741 -0.43 0.669 -.4048543 .2598641
> height1 | -.0005161 .0001042 -4.95 0.000 -.0007204 -.0003118
> dislivello | -.0000686 .0002411 -0.28 0.776 -.0005412 .000404
> newslope | -4.832518 17.70387 -0.27 0.785 -39.53147 29.86644
> latitude | .0000422 .0004341 0.10 0.922 -.0008086 .0008931
> _cons | -2.906064 2.013513 -1.44 0.149 -6.852477 1.040349
> ------------------------------------------------------------------------------
> 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
>
> Additionally, at this point, I have another question. Does anyone know
> why the F-statistic is substituted for a Wald statistic in the second
> stage? If I adjust for small samples, I get again the F-statistic.
> However, I don't see why one should adjust for small amples with
> n=727...
>
> 2013/10/29 pablo martinelli <[email protected]>:
>> 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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*
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