Hello,
I'm trying to regress "by hand" a model with two endogeneous variables.
Themodel is:
epop = lpsii + lpsie + lfirm_size + lpop_24_39s + i.anno + i.cod_reg
I instrumented:
lpsii with l(1/2).ss_psii
lpsie with l(1/2).ss_psie
I run first stage for both endog. var
xi: reg lpsii (1/2).ss_psii lfirm_size lpop_24_39s i.anno i.cod_reg [aw=pop] if !missing(epop), robust
Linear regression Number of obs = 320
F(38, 281) = 51.45
Prob > F = 0.0000
R-squared = 0.7800
Root MSE = .01752
------------------------------------------------------------------------------
| Robust
lpsii | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
ss_psii |
L1. | .7247137 .2402307 3.02 0.003 .2518336 1.197594
L2. | -.7198853 .2432504 -2.96 0.003 -1.19871 -.2410611
|
lfirm_size | -.0792648 .0102154 -7.76 0.000 -.0993732 -.0591564
lpop_24_39s | -.109989 .0534149 -2.06 0.040 -.2151331 -.0048449
_Ianno_1996 | 0 (omitted)
_Ianno_1997 | -.0043584 .0075517 -0.58 0.564 -.0192236 .0105067
_Ianno_1998 | -.0106296 .0062644 -1.70 0.091 -.0229607 .0017016
_Ianno_1999 | -.0027024 .0067627 -0.40 0.690 -.0160143 .0106095
_Ianno_2000 | 0 (omitted)
_Ianno_2001 | .0031099 .0068731 0.45 0.651 -.0104193 .0166391
_Ianno_2002 | .0149494 .0052642 2.84 0.005 .004587 .0253117
_Ianno_2003 | .0134928 .0054524 2.47 0.014 .0027601 .0242254
_Ianno_2004 | .0193359 .0061592 3.14 0.002 .0072119 .03146
_Ianno_2005 | .0191661 .0056653 3.38 0.001 .0080143 .0303179
_Ianno_2006 | .0159195 .0066751 2.38 0.018 .0027798 .0290591
_Ianno_2007 | .0179534 .0069837 2.57 0.011 .0042064 .0317004
_Ianno_2008 | .0138767 .0069477 2.00 0.047 .0002006 .0275528
_Ianno_2009 | .0139265 .0080145 1.74 0.083 -.0018496 .0297025
_Ianno_2010 | .0138802 .0095941 1.45 0.149 -.0050052 .0327656
_Ianno_2011 | .0120539 .0106242 1.13 0.258 -.0088592 .0329669
_Ianno_2012 | .0056357 .0135135 0.42 0.677 -.0209648 .0322361
_Icod_reg_2 | -.1340776 .0570259 -2.35 0.019 -.2463299 -.0218254
_Icod_reg_3 | .2395039 .0720244 3.33 0.001 .097728 .3812797
_Icod_reg_4 | -.0350432 .0515073 -0.68 0.497 -.1364323 .0663459
_Icod_reg_5 | .0326686 .010967 2.98 0.003 .0110807 .0542566
_Icod_reg_6 | -.0535436 .047657 -1.12 0.262 -.1473536 .0402665
_Icod_reg_7 | -.1722646 .0370754 -4.65 0.000 -.2452454 -.0992838
_Icod_reg_8 | .008232 .0090183 0.91 0.362 -.00952 .025984
_Icod_reg_9 | -.0672753 .0162613 -4.14 0.000 -.0992847 -.0352659
_Icod_reg_10 | -.1487513 .0498286 -2.99 0.003 -.2468361 -.0506666
_Icod_reg_11 | -.1314829 .0390207 -3.37 0.001 -.208293 -.0546729
_Icod_reg_12 | .0691197 .0271877 2.54 0.012 .0156023 .1226371
_Icod_reg_13 | -.162832 .0404185 -4.03 0.000 -.2423935 -.0832705
_Icod_reg_14 | -.2227549 .0501466 -4.44 0.000 -.3214656 -.1240442
_Icod_reg_15 | -.09211 .0303344 -3.04 0.003 -.1518216 -.0323985
_Icod_reg_16 | -.1283991 .0137749 -9.32 0.000 -.1555143 -.101284
_Icod_reg_17 | -.2069975 .045368 -4.56 0.000 -.2963018 -.1176932
_Icod_reg_18 | -.1992918 .0324488 -6.14 0.000 -.2631654 -.1354181
_Icod_reg_19 | -.1478067 .0210216 -7.03 0.000 -.1891866 -.1064268
_Icod_reg_20 | -.1966161 .0295534 -6.65 0.000 -.2547903 -.1384419
_cons | 1.508403 .0867295 17.39 0.000 1.337681 1.679125
------------------------------------------------------------------------------
predict pfit_psii if e(sample)
and then
xi: reg lpsie l(1/2).ss_psie lfirm_size lpop_24_39s i.anno i.cod_reg [aw=pop] if !missing(epop), robust
Linear regression Number of obs = 320
F(38, 281) = 56.35
Prob > F = 0.0000
R-squared = 0.8638
Root MSE = .00971
------------------------------------------------------------------------------
| Robust
lpsie | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
ss_psie |
L1. | -.1074692 .1461551 -0.74 0.463 -.395167 .1802285
L2. | -.2745178 .1376171 -1.99 0.047 -.5454091 -.0036264
|
lfirm_size | .0571818 .0081166 7.05 0.000 .0412047 .0731588
lpop_24_39s | -.0129859 .0249251 -0.52 0.603 -.0620495 .0360777
_Ianno_1996 | 0 (omitted)
_Ianno_1997 | -.0314253 .0036362 -8.64 0.000 -.038583 -.0242675
_Ianno_1998 | -.0123424 .0033891 -3.64 0.000 -.0190137 -.005671
_Ianno_1999 | -.0037496 .0034212 -1.10 0.274 -.010484 .0029848
_Ianno_2000 | 0 (omitted)
_Ianno_2001 | .0093614 .0038876 2.41 0.017 .0017089 .0170139
_Ianno_2002 | .0076189 .0037587 2.03 0.044 .0002201 .0150176
_Ianno_2003 | .0047611 .003895 1.22 0.223 -.002906 .0124282
_Ianno_2004 | -.0016387 .0036087 -0.45 0.650 -.0087421 .0054648
_Ianno_2005 | -.0057575 .0034448 -1.67 0.096 -.0125384 .0010234
_Ianno_2006 | -.0041239 .0032942 -1.25 0.212 -.0106084 .0023606
_Ianno_2007 | -.012279 .0039064 -3.14 0.002 -.0199685 -.0045895
_Ianno_2008 | -.0193379 .0041737 -4.63 0.000 -.0275535 -.0111223
_Ianno_2009 | -.0199492 .0045883 -4.35 0.000 -.0289809 -.0109175
_Ianno_2010 | -.0113798 .0050764 -2.24 0.026 -.0213725 -.0013871
_Ianno_2011 | -.0006004 .0057996 -0.10 0.918 -.0120167 .0108158
_Ianno_2012 | .0091853 .0060123 1.53 0.128 -.0026496 .0210201
_Icod_reg_2 | .1228962 .0272386 4.51 0.000 .0692786 .1765138
_Icod_reg_3 | .0145383 .031756 0.46 0.647 -.0479716 .0770482
_Icod_reg_4 | .1359688 .0225897 6.02 0.000 .0915023 .1804354
_Icod_reg_5 | .0999907 .0081228 12.31 0.000 .0840014 .11598
_Icod_reg_6 | .0736364 .0196587 3.75 0.000 .0349394 .1123334
_Icod_reg_7 | .0404451 .0185563 2.18 0.030 .0039182 .0769721
_Icod_reg_8 | .0151753 .0041976 3.62 0.000 .0069126 .023438
_Icod_reg_9 | .0810378 .0090972 8.91 0.000 .0631306 .098945
_Icod_reg_10 | .0735432 .0213829 3.44 0.001 .0314521 .1156343
_Icod_reg_11 | .1149439 .0200981 5.72 0.000 .075382 .1545059
_Icod_reg_12 | .0472788 .0100347 4.71 0.000 .027526 .0670316
_Icod_reg_13 | .1054868 .0194751 5.42 0.000 .0671512 .1438225
_Icod_reg_14 | .1293964 .0259309 4.99 0.000 .078353 .1804398
_Icod_reg_15 | .0892384 .0164751 5.42 0.000 .0568081 .1216686
_Icod_reg_16 | .1233747 .0125323 9.84 0.000 .0987055 .1480438
_Icod_reg_17 | .0927368 .0232373 3.99 0.000 .0469956 .138478
_Icod_reg_18 | .1178288 .0194373 6.06 0.000 .0795676 .15609
_Icod_reg_19 | .0609906 .0146284 4.17 0.000 .0321956 .0897857
_Icod_reg_20 | .0325883 .0170428 1.91 0.057 -.0009594 .066136
_cons | 1.268046 .0532937 23.79 0.000 1.16314 1.372951
------------------------------------------------------------------------------
predict pfit_psie if e(sample)
Then the second stage:
xi: reg epop pfit_psii pfit_psie lfirm_size lpop_24_39s i.anno i.cod_reg [aw=pop] , robust
Linear regression Number of obs = 320
F(38, 281) = 297.29
Prob > F = 0.0000
R-squared = 0.9767
Root MSE = .0094
------------------------------------------------------------------------------
| Robust
epop | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
pfit_psii | .2358414 .091728 2.57 0.011 .0552802 .4164027
pfit_psie | -.4149383 .0956592 -4.34 0.000 -.6032379 -.2266387
lfirm_size | .0427791 .0124005 3.45 0.001 .0183694 .0671888
lpop_24_39s | .1799566 .0259106 6.95 0.000 .128953 .2309602
_Ianno_1996 | 0 (omitted)
_Ianno_1997 | -.0206548 .0052333 -3.95 0.000 -.0309562 -.0103533
_Ianno_1998 | -.0085564 .0032341 -2.65 0.009 -.0149225 -.0021902
_Ianno_1999 | -.0058562 .0037618 -1.56 0.121 -.013261 .0015486
_Ianno_2000 | 0 (omitted)
_Ianno_2001 | .0035494 .0031516 1.13 0.261 -.0026543 .0097532
_Ianno_2002 | .0048665 .0028696 1.70 0.091 -.0007822 .0105152
_Ianno_2003 | .0094868 .0038949 2.44 0.015 .0018199 .0171537
_Ianno_2004 | .0069519 .0039357 1.77 0.078 -.0007953 .0146992
_Ianno_2005 | .0100091 .0035326 2.83 0.005 .0030553 .0169629
_Ianno_2006 | .0124815 .0039918 3.13 0.002 .0046239 .0203392
_Ianno_2007 | .0135786 .0048336 2.81 0.005 .0040638 .0230933
_Ianno_2008 | .0114223 .0048713 2.34 0.020 .0018334 .0210113
_Ianno_2009 | .0020939 .0054095 0.39 0.699 -.0085543 .0127422
_Ianno_2010 | .0121772 .0054132 2.25 0.025 .0015215 .0228328
_Ianno_2011 | .0192951 .0050863 3.79 0.000 .009283 .0293072
_Ianno_2012 | .0261781 .0043826 5.97 0.000 .0175513 .034805
_Icod_reg_2 | .136094 .0270163 5.04 0.000 .082914 .189274
_Icod_reg_3 | -.221716 .0367209 -6.04 0.000 -.2939989 -.1494331
_Icod_reg_4 | .1128991 .0185332 6.09 0.000 .0764176 .1493805
_Icod_reg_5 | -.0223788 .0075917 -2.95 0.003 -.0373226 -.0074351
_Icod_reg_6 | .1234655 .0175965 7.02 0.000 .0888277 .1581033
_Icod_reg_7 | .0981712 .022442 4.37 0.000 .0539953 .1423471
_Icod_reg_8 | .04124 .0049691 8.30 0.000 .0314586 .0510214
_Icod_reg_9 | .0241817 .0112287 2.15 0.032 .0020787 .0462848
_Icod_reg_10 | .1079929 .0241054 4.48 0.000 .0605429 .155443
_Icod_reg_11 | .1163244 .0198072 5.87 0.000 .0773351 .1553137
_Icod_reg_12 | -.1326795 .0097054 -13.67 0.000 -.151784 -.1135749
_Icod_reg_13 | .1049326 .0242091 4.33 0.000 .0572784 .1525867
_Icod_reg_14 | .1469945 .0336123 4.37 0.000 .0808306 .2131584
_Icod_reg_15 | -.1046795 .020581 -5.09 0.000 -.1451921 -.0641669
_Icod_reg_16 | -.0144742 .0210911 -0.69 0.493 -.0559909 .0270425
_Icod_reg_17 | .1213383 .0301117 4.03 0.000 .0620651 .1806115
_Icod_reg_18 | .0825412 .0292151 2.83 0.005 .025033 .1400494
_Icod_reg_19 | -.0619536 .0209169 -2.96 0.003 -.1031273 -.0207799
_Icod_reg_20 | .0690379 .0250951 2.75 0.006 .0196397 .1184362
_cons | -.0606449 .1594047 -0.38 0.704 -.3744238 .253134
------------------------------------------------------------------------------
Then I run
xi: ivreg epop (lpsii lpsie = l(1/2).ss_netai l(1/2).ss_netae ) lfirm_size lpop_24_39s i.anno i.cod_reg [aw=pop], robust
Instrumental variables (2SLS) regression Number of obs = 320
F(38, 281) = 134.19
Prob > F = 0.0000
R-squared = 0.9017
Root MSE = .01932
------------------------------------------------------------------------------
| Robust
epop | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
lpsii | .9091019 .7136576 1.27 0.204 -.4956918 2.313896
lpsie | .8603814 .8226458 1.05 0.297 -.7589493 2.479712
lfirm_size | -.0118972 .0252974 -0.47 0.639 -.0616937 .0378994
lpop_24_39s | .3203446 .1232532 2.60 0.010 .0777278 .5629614
_Ianno_1996 | 0 (omitted)
_Ianno_1997 | .0190754 .027496 0.69 0.488 -.0350489 .0731997
_Ianno_1998 | .0055286 .0110932 0.50 0.619 -.0163078 .027365
_Ianno_1999 | -.0007961 .0065186 -0.12 0.903 -.0136277 .0120354
_Ianno_2000 | 0 (omitted)
_Ianno_2001 | -.0111714 .0135732 -0.82 0.411 -.0378895 .0155467
_Ianno_2002 | -.0033945 .0100741 -0.34 0.736 -.0232246 .0164357
_Ianno_2003 | .0046783 .0094677 0.49 0.622 -.0139584 .023315
_Ianno_2004 | .0103969 .0082897 1.25 0.211 -.005921 .0267147
_Ianno_2005 | .0206976 .0064176 3.23 0.001 .008065 .0333303
_Ianno_2006 | .0192685 .0058959 3.27 0.001 .0076628 .0308743
_Ianno_2007 | .0380677 .0141523 2.69 0.008 .0102097 .0659257
_Ianno_2008 | .0471119 .0214921 2.19 0.029 .0048061 .0894178
_Ianno_2009 | .037064 .0205106 1.81 0.072 -.00331 .0774379
_Ianno_2010 | .038358 .014858 2.58 0.010 .0091108 .0676052
_Ianno_2011 | .0345034 .0103816 3.32 0.001 .0140677 .054939
_Ianno_2012 | .0370685 .0117115 3.17 0.002 .0140152 .0601219
_Icod_reg_2 | .1588486 .0616133 2.58 0.010 .0375664 .2801307
_Icod_reg_3 | -.4052782 .1867365 -2.17 0.031 -.7728581 -.0376983
_Icod_reg_4 | .0844678 .0284314 2.97 0.003 .0285023 .1404333
_Icod_reg_5 | -.1176386 .0722806 -1.63 0.105 -.2599187 .0246415
_Icod_reg_6 | .156386 .0404542 3.87 0.000 .0767542 .2360178
_Icod_reg_7 | .1675713 .0944739 1.77 0.077 -.0183952 .3535377
_Icod_reg_8 | .0352516 .0105846 3.33 0.001 .0144163 .0560868
_Icod_reg_9 | -.0273416 .0263477 -1.04 0.300 -.0792056 .0245223
_Icod_reg_10 | .1531845 .0750137 2.04 0.042 .0055245 .3008446
_Icod_reg_11 | .1519783 .0628168 2.42 0.016 .0283271 .2756296
_Icod_reg_12 | -.168665 .042485 -3.97 0.000 -.2522942 -.0850357
_Icod_reg_13 | .1003397 .0541662 1.85 0.065 -.0062834 .2069628
_Icod_reg_14 | .1322341 .0718851 1.84 0.067 -.0092676 .2737357
_Icod_reg_15 | -.2306039 .064923 -3.55 0.000 -.3584011 -.1028066
_Icod_reg_16 | -.1337238 .0561179 -2.38 0.018 -.2441887 -.023259
_Icod_reg_17 | .1343958 .0780656 1.72 0.086 -.0192719 .2880634
_Icod_reg_18 | .0018361 .0502198 0.04 0.971 -.0970187 .100691
_Icod_reg_19 | -.1352422 .0354738 -3.81 0.000 -.2050702 -.0654141
_Icod_reg_20 | .0941452 .0787132 1.20 0.233 -.0607973 .2490876
_cons | -2.091859 1.707764 -1.22 0.222 -5.453495 1.269776
------------------------------------------------------------------------------
Instrumented: lpsii lpsie
Instruments: lfirm_size lpop_24_39s _Ianno_1996 _Ianno_1997 _Ianno_1998
_Ianno_1999 _Ianno_2000 _Ianno_2001 _Ianno_2002 _Ianno_2003
_Ianno_2004 _Ianno_2005 _Ianno_2006 _Ianno_2007 _Ianno_2008
_Ianno_2009 _Ianno_2010 _Ianno_2011 _Ianno_2012 _Icod_reg_2
_Icod_reg_3 _Icod_reg_4 _Icod_reg_5 _Icod_reg_6 _Icod_reg_7
_Icod_reg_8 _Icod_reg_9 _Icod_reg_10 _Icod_reg_11
_Icod_reg_12 _Icod_reg_13 _Icod_reg_14 _Icod_reg_15
_Icod_reg_16 _Icod_reg_17 _Icod_reg_18 _Icod_reg_19
_Icod_reg_20 L.ss_netai L2.ss_netai L.ss_netae L2.ss_netae
------------------------------------------------------------------------------
but the coeffieicent for psii and psie are different from those of the second stage pfit_psii pfit_psie
Any suggestions?
Thanks
I'm trying to regress "by hand" a model with two endogeneous variables.
Themodel is:
epop = lpsii + lpsie + lfirm_size + lpop_24_39s + i.anno + i.cod_reg
I instrumented:
lpsii with l(1/2).ss_psii
lpsie with l(1/2).ss_psie
I run first stage for both endog. var
xi: reg lpsii (1/2).ss_psii lfirm_size lpop_24_39s i.anno i.cod_reg [aw=pop] if !missing(epop), robust
Linear regression Number of obs = 320
F(38, 281) = 51.45
Prob > F = 0.0000
R-squared = 0.7800
Root MSE = .01752
------------------------------------------------------------------------------
| Robust
lpsii | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
ss_psii |
L1. | .7247137 .2402307 3.02 0.003 .2518336 1.197594
L2. | -.7198853 .2432504 -2.96 0.003 -1.19871 -.2410611
|
lfirm_size | -.0792648 .0102154 -7.76 0.000 -.0993732 -.0591564
lpop_24_39s | -.109989 .0534149 -2.06 0.040 -.2151331 -.0048449
_Ianno_1996 | 0 (omitted)
_Ianno_1997 | -.0043584 .0075517 -0.58 0.564 -.0192236 .0105067
_Ianno_1998 | -.0106296 .0062644 -1.70 0.091 -.0229607 .0017016
_Ianno_1999 | -.0027024 .0067627 -0.40 0.690 -.0160143 .0106095
_Ianno_2000 | 0 (omitted)
_Ianno_2001 | .0031099 .0068731 0.45 0.651 -.0104193 .0166391
_Ianno_2002 | .0149494 .0052642 2.84 0.005 .004587 .0253117
_Ianno_2003 | .0134928 .0054524 2.47 0.014 .0027601 .0242254
_Ianno_2004 | .0193359 .0061592 3.14 0.002 .0072119 .03146
_Ianno_2005 | .0191661 .0056653 3.38 0.001 .0080143 .0303179
_Ianno_2006 | .0159195 .0066751 2.38 0.018 .0027798 .0290591
_Ianno_2007 | .0179534 .0069837 2.57 0.011 .0042064 .0317004
_Ianno_2008 | .0138767 .0069477 2.00 0.047 .0002006 .0275528
_Ianno_2009 | .0139265 .0080145 1.74 0.083 -.0018496 .0297025
_Ianno_2010 | .0138802 .0095941 1.45 0.149 -.0050052 .0327656
_Ianno_2011 | .0120539 .0106242 1.13 0.258 -.0088592 .0329669
_Ianno_2012 | .0056357 .0135135 0.42 0.677 -.0209648 .0322361
_Icod_reg_2 | -.1340776 .0570259 -2.35 0.019 -.2463299 -.0218254
_Icod_reg_3 | .2395039 .0720244 3.33 0.001 .097728 .3812797
_Icod_reg_4 | -.0350432 .0515073 -0.68 0.497 -.1364323 .0663459
_Icod_reg_5 | .0326686 .010967 2.98 0.003 .0110807 .0542566
_Icod_reg_6 | -.0535436 .047657 -1.12 0.262 -.1473536 .0402665
_Icod_reg_7 | -.1722646 .0370754 -4.65 0.000 -.2452454 -.0992838
_Icod_reg_8 | .008232 .0090183 0.91 0.362 -.00952 .025984
_Icod_reg_9 | -.0672753 .0162613 -4.14 0.000 -.0992847 -.0352659
_Icod_reg_10 | -.1487513 .0498286 -2.99 0.003 -.2468361 -.0506666
_Icod_reg_11 | -.1314829 .0390207 -3.37 0.001 -.208293 -.0546729
_Icod_reg_12 | .0691197 .0271877 2.54 0.012 .0156023 .1226371
_Icod_reg_13 | -.162832 .0404185 -4.03 0.000 -.2423935 -.0832705
_Icod_reg_14 | -.2227549 .0501466 -4.44 0.000 -.3214656 -.1240442
_Icod_reg_15 | -.09211 .0303344 -3.04 0.003 -.1518216 -.0323985
_Icod_reg_16 | -.1283991 .0137749 -9.32 0.000 -.1555143 -.101284
_Icod_reg_17 | -.2069975 .045368 -4.56 0.000 -.2963018 -.1176932
_Icod_reg_18 | -.1992918 .0324488 -6.14 0.000 -.2631654 -.1354181
_Icod_reg_19 | -.1478067 .0210216 -7.03 0.000 -.1891866 -.1064268
_Icod_reg_20 | -.1966161 .0295534 -6.65 0.000 -.2547903 -.1384419
_cons | 1.508403 .0867295 17.39 0.000 1.337681 1.679125
------------------------------------------------------------------------------
predict pfit_psii if e(sample)
and then
xi: reg lpsie l(1/2).ss_psie lfirm_size lpop_24_39s i.anno i.cod_reg [aw=pop] if !missing(epop), robust
Linear regression Number of obs = 320
F(38, 281) = 56.35
Prob > F = 0.0000
R-squared = 0.8638
Root MSE = .00971
------------------------------------------------------------------------------
| Robust
lpsie | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
ss_psie |
L1. | -.1074692 .1461551 -0.74 0.463 -.395167 .1802285
L2. | -.2745178 .1376171 -1.99 0.047 -.5454091 -.0036264
|
lfirm_size | .0571818 .0081166 7.05 0.000 .0412047 .0731588
lpop_24_39s | -.0129859 .0249251 -0.52 0.603 -.0620495 .0360777
_Ianno_1996 | 0 (omitted)
_Ianno_1997 | -.0314253 .0036362 -8.64 0.000 -.038583 -.0242675
_Ianno_1998 | -.0123424 .0033891 -3.64 0.000 -.0190137 -.005671
_Ianno_1999 | -.0037496 .0034212 -1.10 0.274 -.010484 .0029848
_Ianno_2000 | 0 (omitted)
_Ianno_2001 | .0093614 .0038876 2.41 0.017 .0017089 .0170139
_Ianno_2002 | .0076189 .0037587 2.03 0.044 .0002201 .0150176
_Ianno_2003 | .0047611 .003895 1.22 0.223 -.002906 .0124282
_Ianno_2004 | -.0016387 .0036087 -0.45 0.650 -.0087421 .0054648
_Ianno_2005 | -.0057575 .0034448 -1.67 0.096 -.0125384 .0010234
_Ianno_2006 | -.0041239 .0032942 -1.25 0.212 -.0106084 .0023606
_Ianno_2007 | -.012279 .0039064 -3.14 0.002 -.0199685 -.0045895
_Ianno_2008 | -.0193379 .0041737 -4.63 0.000 -.0275535 -.0111223
_Ianno_2009 | -.0199492 .0045883 -4.35 0.000 -.0289809 -.0109175
_Ianno_2010 | -.0113798 .0050764 -2.24 0.026 -.0213725 -.0013871
_Ianno_2011 | -.0006004 .0057996 -0.10 0.918 -.0120167 .0108158
_Ianno_2012 | .0091853 .0060123 1.53 0.128 -.0026496 .0210201
_Icod_reg_2 | .1228962 .0272386 4.51 0.000 .0692786 .1765138
_Icod_reg_3 | .0145383 .031756 0.46 0.647 -.0479716 .0770482
_Icod_reg_4 | .1359688 .0225897 6.02 0.000 .0915023 .1804354
_Icod_reg_5 | .0999907 .0081228 12.31 0.000 .0840014 .11598
_Icod_reg_6 | .0736364 .0196587 3.75 0.000 .0349394 .1123334
_Icod_reg_7 | .0404451 .0185563 2.18 0.030 .0039182 .0769721
_Icod_reg_8 | .0151753 .0041976 3.62 0.000 .0069126 .023438
_Icod_reg_9 | .0810378 .0090972 8.91 0.000 .0631306 .098945
_Icod_reg_10 | .0735432 .0213829 3.44 0.001 .0314521 .1156343
_Icod_reg_11 | .1149439 .0200981 5.72 0.000 .075382 .1545059
_Icod_reg_12 | .0472788 .0100347 4.71 0.000 .027526 .0670316
_Icod_reg_13 | .1054868 .0194751 5.42 0.000 .0671512 .1438225
_Icod_reg_14 | .1293964 .0259309 4.99 0.000 .078353 .1804398
_Icod_reg_15 | .0892384 .0164751 5.42 0.000 .0568081 .1216686
_Icod_reg_16 | .1233747 .0125323 9.84 0.000 .0987055 .1480438
_Icod_reg_17 | .0927368 .0232373 3.99 0.000 .0469956 .138478
_Icod_reg_18 | .1178288 .0194373 6.06 0.000 .0795676 .15609
_Icod_reg_19 | .0609906 .0146284 4.17 0.000 .0321956 .0897857
_Icod_reg_20 | .0325883 .0170428 1.91 0.057 -.0009594 .066136
_cons | 1.268046 .0532937 23.79 0.000 1.16314 1.372951
------------------------------------------------------------------------------
predict pfit_psie if e(sample)
Then the second stage:
xi: reg epop pfit_psii pfit_psie lfirm_size lpop_24_39s i.anno i.cod_reg [aw=pop] , robust
Linear regression Number of obs = 320
F(38, 281) = 297.29
Prob > F = 0.0000
R-squared = 0.9767
Root MSE = .0094
------------------------------------------------------------------------------
| Robust
epop | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
pfit_psii | .2358414 .091728 2.57 0.011 .0552802 .4164027
pfit_psie | -.4149383 .0956592 -4.34 0.000 -.6032379 -.2266387
lfirm_size | .0427791 .0124005 3.45 0.001 .0183694 .0671888
lpop_24_39s | .1799566 .0259106 6.95 0.000 .128953 .2309602
_Ianno_1996 | 0 (omitted)
_Ianno_1997 | -.0206548 .0052333 -3.95 0.000 -.0309562 -.0103533
_Ianno_1998 | -.0085564 .0032341 -2.65 0.009 -.0149225 -.0021902
_Ianno_1999 | -.0058562 .0037618 -1.56 0.121 -.013261 .0015486
_Ianno_2000 | 0 (omitted)
_Ianno_2001 | .0035494 .0031516 1.13 0.261 -.0026543 .0097532
_Ianno_2002 | .0048665 .0028696 1.70 0.091 -.0007822 .0105152
_Ianno_2003 | .0094868 .0038949 2.44 0.015 .0018199 .0171537
_Ianno_2004 | .0069519 .0039357 1.77 0.078 -.0007953 .0146992
_Ianno_2005 | .0100091 .0035326 2.83 0.005 .0030553 .0169629
_Ianno_2006 | .0124815 .0039918 3.13 0.002 .0046239 .0203392
_Ianno_2007 | .0135786 .0048336 2.81 0.005 .0040638 .0230933
_Ianno_2008 | .0114223 .0048713 2.34 0.020 .0018334 .0210113
_Ianno_2009 | .0020939 .0054095 0.39 0.699 -.0085543 .0127422
_Ianno_2010 | .0121772 .0054132 2.25 0.025 .0015215 .0228328
_Ianno_2011 | .0192951 .0050863 3.79 0.000 .009283 .0293072
_Ianno_2012 | .0261781 .0043826 5.97 0.000 .0175513 .034805
_Icod_reg_2 | .136094 .0270163 5.04 0.000 .082914 .189274
_Icod_reg_3 | -.221716 .0367209 -6.04 0.000 -.2939989 -.1494331
_Icod_reg_4 | .1128991 .0185332 6.09 0.000 .0764176 .1493805
_Icod_reg_5 | -.0223788 .0075917 -2.95 0.003 -.0373226 -.0074351
_Icod_reg_6 | .1234655 .0175965 7.02 0.000 .0888277 .1581033
_Icod_reg_7 | .0981712 .022442 4.37 0.000 .0539953 .1423471
_Icod_reg_8 | .04124 .0049691 8.30 0.000 .0314586 .0510214
_Icod_reg_9 | .0241817 .0112287 2.15 0.032 .0020787 .0462848
_Icod_reg_10 | .1079929 .0241054 4.48 0.000 .0605429 .155443
_Icod_reg_11 | .1163244 .0198072 5.87 0.000 .0773351 .1553137
_Icod_reg_12 | -.1326795 .0097054 -13.67 0.000 -.151784 -.1135749
_Icod_reg_13 | .1049326 .0242091 4.33 0.000 .0572784 .1525867
_Icod_reg_14 | .1469945 .0336123 4.37 0.000 .0808306 .2131584
_Icod_reg_15 | -.1046795 .020581 -5.09 0.000 -.1451921 -.0641669
_Icod_reg_16 | -.0144742 .0210911 -0.69 0.493 -.0559909 .0270425
_Icod_reg_17 | .1213383 .0301117 4.03 0.000 .0620651 .1806115
_Icod_reg_18 | .0825412 .0292151 2.83 0.005 .025033 .1400494
_Icod_reg_19 | -.0619536 .0209169 -2.96 0.003 -.1031273 -.0207799
_Icod_reg_20 | .0690379 .0250951 2.75 0.006 .0196397 .1184362
_cons | -.0606449 .1594047 -0.38 0.704 -.3744238 .253134
------------------------------------------------------------------------------
Then I run
xi: ivreg epop (lpsii lpsie = l(1/2).ss_netai l(1/2).ss_netae ) lfirm_size lpop_24_39s i.anno i.cod_reg [aw=pop], robust
Instrumental variables (2SLS) regression Number of obs = 320
F(38, 281) = 134.19
Prob > F = 0.0000
R-squared = 0.9017
Root MSE = .01932
------------------------------------------------------------------------------
| Robust
epop | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
lpsii | .9091019 .7136576 1.27 0.204 -.4956918 2.313896
lpsie | .8603814 .8226458 1.05 0.297 -.7589493 2.479712
lfirm_size | -.0118972 .0252974 -0.47 0.639 -.0616937 .0378994
lpop_24_39s | .3203446 .1232532 2.60 0.010 .0777278 .5629614
_Ianno_1996 | 0 (omitted)
_Ianno_1997 | .0190754 .027496 0.69 0.488 -.0350489 .0731997
_Ianno_1998 | .0055286 .0110932 0.50 0.619 -.0163078 .027365
_Ianno_1999 | -.0007961 .0065186 -0.12 0.903 -.0136277 .0120354
_Ianno_2000 | 0 (omitted)
_Ianno_2001 | -.0111714 .0135732 -0.82 0.411 -.0378895 .0155467
_Ianno_2002 | -.0033945 .0100741 -0.34 0.736 -.0232246 .0164357
_Ianno_2003 | .0046783 .0094677 0.49 0.622 -.0139584 .023315
_Ianno_2004 | .0103969 .0082897 1.25 0.211 -.005921 .0267147
_Ianno_2005 | .0206976 .0064176 3.23 0.001 .008065 .0333303
_Ianno_2006 | .0192685 .0058959 3.27 0.001 .0076628 .0308743
_Ianno_2007 | .0380677 .0141523 2.69 0.008 .0102097 .0659257
_Ianno_2008 | .0471119 .0214921 2.19 0.029 .0048061 .0894178
_Ianno_2009 | .037064 .0205106 1.81 0.072 -.00331 .0774379
_Ianno_2010 | .038358 .014858 2.58 0.010 .0091108 .0676052
_Ianno_2011 | .0345034 .0103816 3.32 0.001 .0140677 .054939
_Ianno_2012 | .0370685 .0117115 3.17 0.002 .0140152 .0601219
_Icod_reg_2 | .1588486 .0616133 2.58 0.010 .0375664 .2801307
_Icod_reg_3 | -.4052782 .1867365 -2.17 0.031 -.7728581 -.0376983
_Icod_reg_4 | .0844678 .0284314 2.97 0.003 .0285023 .1404333
_Icod_reg_5 | -.1176386 .0722806 -1.63 0.105 -.2599187 .0246415
_Icod_reg_6 | .156386 .0404542 3.87 0.000 .0767542 .2360178
_Icod_reg_7 | .1675713 .0944739 1.77 0.077 -.0183952 .3535377
_Icod_reg_8 | .0352516 .0105846 3.33 0.001 .0144163 .0560868
_Icod_reg_9 | -.0273416 .0263477 -1.04 0.300 -.0792056 .0245223
_Icod_reg_10 | .1531845 .0750137 2.04 0.042 .0055245 .3008446
_Icod_reg_11 | .1519783 .0628168 2.42 0.016 .0283271 .2756296
_Icod_reg_12 | -.168665 .042485 -3.97 0.000 -.2522942 -.0850357
_Icod_reg_13 | .1003397 .0541662 1.85 0.065 -.0062834 .2069628
_Icod_reg_14 | .1322341 .0718851 1.84 0.067 -.0092676 .2737357
_Icod_reg_15 | -.2306039 .064923 -3.55 0.000 -.3584011 -.1028066
_Icod_reg_16 | -.1337238 .0561179 -2.38 0.018 -.2441887 -.023259
_Icod_reg_17 | .1343958 .0780656 1.72 0.086 -.0192719 .2880634
_Icod_reg_18 | .0018361 .0502198 0.04 0.971 -.0970187 .100691
_Icod_reg_19 | -.1352422 .0354738 -3.81 0.000 -.2050702 -.0654141
_Icod_reg_20 | .0941452 .0787132 1.20 0.233 -.0607973 .2490876
_cons | -2.091859 1.707764 -1.22 0.222 -5.453495 1.269776
------------------------------------------------------------------------------
Instrumented: lpsii lpsie
Instruments: lfirm_size lpop_24_39s _Ianno_1996 _Ianno_1997 _Ianno_1998
_Ianno_1999 _Ianno_2000 _Ianno_2001 _Ianno_2002 _Ianno_2003
_Ianno_2004 _Ianno_2005 _Ianno_2006 _Ianno_2007 _Ianno_2008
_Ianno_2009 _Ianno_2010 _Ianno_2011 _Ianno_2012 _Icod_reg_2
_Icod_reg_3 _Icod_reg_4 _Icod_reg_5 _Icod_reg_6 _Icod_reg_7
_Icod_reg_8 _Icod_reg_9 _Icod_reg_10 _Icod_reg_11
_Icod_reg_12 _Icod_reg_13 _Icod_reg_14 _Icod_reg_15
_Icod_reg_16 _Icod_reg_17 _Icod_reg_18 _Icod_reg_19
_Icod_reg_20 L.ss_netai L2.ss_netai L.ss_netae L2.ss_netae
------------------------------------------------------------------------------
but the coeffieicent for psii and psie are different from those of the second stage pfit_psii pfit_psie
Any suggestions?
Thanks
Comment