---------------------------------------------------------------------------------- name: log: C:\Users\LabProf01\Desktop\IV_log.log log type: text opened on: 17 May 2023, 16:21:33 . reg lwage educ exper expersq Source | SS df MS Number of obs = 428 -------------+---------------------------------- F(3, 424) = 26.29 Model | 35.0222967 3 11.6740989 Prob > F = 0.0000 Residual | 188.305144 424 .444115906 R-squared = 0.1568 -------------+---------------------------------- Adj R-squared = 0.1509 Total | 223.327441 427 .523015084 Root MSE = .66642 ------------------------------------------------------------------------------ lwage | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- educ | .1074896 .0141465 7.60 0.000 .0796837 .1352956 exper | .0415665 .0131752 3.15 0.002 .0156697 .0674633 expersq | -.0008112 .0003932 -2.06 0.040 -.0015841 -.0000382 _cons | -.5220406 .1986321 -2.63 0.009 -.9124667 -.1316144 ------------------------------------------------------------------------------ . ivreg lwage (educ= motheduc fatheduc) exper expersq, first First-stage regressions ----------------------- Source | SS df MS Number of obs = 428 -------------+---------------------------------- F(4, 423) = 28.36 Model | 471.620998 4 117.90525 Prob > F = 0.0000 Residual | 1758.57526 423 4.15738833 R-squared = 0.2115 -------------+---------------------------------- Adj R-squared = 0.2040 Total | 2230.19626 427 5.22294206 Root MSE = 2.039 ------------------------------------------------------------------------------ educ | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- exper | .0452254 .0402507 1.12 0.262 -.0338909 .1243417 expersq | -.0010091 .0012033 -0.84 0.402 -.0033744 .0013562 motheduc | .157597 .0358941 4.39 0.000 .087044 .2281501 fatheduc | .1895484 .0337565 5.62 0.000 .1231971 .2558997 _cons | 9.10264 .4265614 21.34 0.000 8.264196 9.941084 ------------------------------------------------------------------------------ Instrumental variables (2SLS) regression Source | SS df MS Number of obs = 428 -------------+---------------------------------- F(3, 424) = 8.14 Model | 30.3074256 3 10.1024752 Prob > F = 0.0000 Residual | 193.020015 424 .455235885 R-squared = 0.1357 -------------+---------------------------------- Adj R-squared = 0.1296 Total | 223.327441 427 .523015084 Root MSE = .67471 ------------------------------------------------------------------------------ lwage | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- educ | .0613966 .0314367 1.95 0.051 -.0003945 .1231878 exper | .0441704 .0134325 3.29 0.001 .0177679 .0705729 expersq | -.000899 .0004017 -2.24 0.026 -.0016885 -.0001094 _cons | .0481003 .4003281 0.12 0.904 -.7387744 .834975 ------------------------------------------------------------------------------ Instrumented: educ Instruments: exper expersq motheduc fatheduc ------------------------------------------------------------------------------ . reg educ motheduc fatheduc exper expersq Source | SS df MS Number of obs = 753 -------------+---------------------------------- F(4, 748) = 66.52 Model | 1025.94324 4 256.48581 Prob > F = 0.0000 Residual | 2884.0966 748 3.85574412 R-squared = 0.2624 -------------+---------------------------------- Adj R-squared = 0.2584 Total | 3910.03984 752 5.19952106 Root MSE = 1.9636 ------------------------------------------------------------------------------ educ | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- motheduc | .1856173 .0259869 7.14 0.000 .1346014 .2366331 fatheduc | .1845745 .0244979 7.53 0.000 .1364817 .2326674 exper | .085378 .0255485 3.34 0.001 .0352228 .1355333 expersq | -.0018564 .0008276 -2.24 0.025 -.0034812 -.0002317 _cons | 8.366716 .2667111 31.37 0.000 7.843125 8.890307 ------------------------------------------------------------------------------ . test motheduc fatheduc ( 1) motheduc = 0 ( 2) fatheduc = 0 F( 2, 748) = 124.76 Prob > F = 0.0000 . predict resid_firststage, res . ivreg lwage (educ= motheduc fatheduc) exper expersq resid_firststage Instrumental variables (2SLS) regression Source | SS df MS Number of obs = 428 -------------+---------------------------------- F(4, 423) = 20.53 Model | 36.306365 4 9.07659124 Prob > F = 0.0000 Residual | 187.021076 423 .442130203 R-squared = 0.1626 -------------+---------------------------------- Adj R-squared = 0.1547 Total | 223.327441 427 .523015084 Root MSE = .66493 --------------------------------------------------------------------------------- lwage | Coef. Std. Err. t P>|t| [95% Conf. Interval] ----------------+---------------------------------------------------------------- educ | .0639033 .0292123 2.19 0.029 .0064841 .1213226 exper | .0463071 .0134368 3.45 0.001 .0198959 .0727183 expersq | -.0009444 .0004001 -2.36 0.019 -.0017308 -.000158 resid_firstst~e | .0558771 .032788 1.70 0.089 -.0085706 .1203248 _cons | -.011404 .3592486 -0.03 0.975 -.7175388 .6947307 --------------------------------------------------------------------------------- Instrumented: educ Instruments: exper expersq resid_firststage motheduc fatheduc --------------------------------------------------------------------------------- . ****teste hausman . reg lwage (educ= motheduc fatheduc) exper expersq parentheses unbalanced r(132); . ivreg lwage (educ= motheduc fatheduc) exper expersq Instrumental variables (2SLS) regression Source | SS df MS Number of obs = 428 -------------+---------------------------------- F(3, 424) = 8.14 Model | 30.3074256 3 10.1024752 Prob > F = 0.0000 Residual | 193.020015 424 .455235885 R-squared = 0.1357 -------------+---------------------------------- Adj R-squared = 0.1296 Total | 223.327441 427 .523015084 Root MSE = .67471 ------------------------------------------------------------------------------ lwage | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- educ | .0613966 .0314367 1.95 0.051 -.0003945 .1231878 exper | .0441704 .0134325 3.29 0.001 .0177679 .0705729 expersq | -.000899 .0004017 -2.24 0.026 -.0016885 -.0001094 _cons | .0481003 .4003281 0.12 0.904 -.7387744 .834975 ------------------------------------------------------------------------------ Instrumented: educ Instruments: exper expersq motheduc fatheduc ------------------------------------------------------------------------------ . reg lwage educ exper expersq Source | SS df MS Number of obs = 428 -------------+---------------------------------- F(3, 424) = 26.29 Model | 35.0222967 3 11.6740989 Prob > F = 0.0000 Residual | 188.305144 424 .444115906 R-squared = 0.1568 -------------+---------------------------------- Adj R-squared = 0.1509 Total | 223.327441 427 .523015084 Root MSE = .66642 ------------------------------------------------------------------------------ lwage | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- educ | .1074896 .0141465 7.60 0.000 .0796837 .1352956 exper | .0415665 .0131752 3.15 0.002 .0156697 .0674633 expersq | -.0008112 .0003932 -2.06 0.040 -.0015841 -.0000382 _cons | -.5220406 .1986321 -2.63 0.009 -.9124667 -.1316144 ------------------------------------------------------------------------------ . ivreg lwage (educ= motheduc fatheduc) exper expersq Instrumental variables (2SLS) regression Source | SS df MS Number of obs = 428 -------------+---------------------------------- F(3, 424) = 8.14 Model | 30.3074256 3 10.1024752 Prob > F = 0.0000 Residual | 193.020015 424 .455235885 R-squared = 0.1357 -------------+---------------------------------- Adj R-squared = 0.1296 Total | 223.327441 427 .523015084 Root MSE = .67471 ------------------------------------------------------------------------------ lwage | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- educ | .0613966 .0314367 1.95 0.051 -.0003945 .1231878 exper | .0441704 .0134325 3.29 0.001 .0177679 .0705729 expersq | -.000899 .0004017 -2.24 0.026 -.0016885 -.0001094 _cons | .0481003 .4003281 0.12 0.904 -.7387744 .834975 ------------------------------------------------------------------------------ Instrumented: educ Instruments: exper expersq motheduc fatheduc ------------------------------------------------------------------------------ . test overid overid not found r(111); . estat overid estat overid not valid r(321); . ivreg lwage (educ= motheduc fatheduc) exper expersq Instrumental variables (2SLS) regression Source | SS df MS Number of obs = 428 -------------+---------------------------------- F(3, 424) = 8.14 Model | 30.3074256 3 10.1024752 Prob > F = 0.0000 Residual | 193.020015 424 .455235885 R-squared = 0.1357 -------------+---------------------------------- Adj R-squared = 0.1296 Total | 223.327441 427 .523015084 Root MSE = .67471 ------------------------------------------------------------------------------ lwage | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- educ | .0613966 .0314367 1.95 0.051 -.0003945 .1231878 exper | .0441704 .0134325 3.29 0.001 .0177679 .0705729 expersq | -.000899 .0004017 -2.24 0.026 -.0016885 -.0001094 _cons | .0481003 .4003281 0.12 0.904 -.7387744 .834975 ------------------------------------------------------------------------------ Instrumented: educ Instruments: exper expersq motheduc fatheduc ------------------------------------------------------------------------------ . estat overid estat overid not valid r(321); . estat overid estat overid not valid r(321); . ivregress 2sls lwage (educ= motheduc fatheduc) exper expersq Instrumental variables (2SLS) regression Number of obs = 428 Wald chi2(3) = 24.65 Prob > chi2 = 0.0000 R-squared = 0.1357 Root MSE = .67155 ------------------------------------------------------------------------------ lwage | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- educ | .0613966 .0312895 1.96 0.050 .0000704 .1227228 exper | .0441704 .0133696 3.30 0.001 .0179665 .0703742 expersq | -.000899 .0003998 -2.25 0.025 -.0016826 -.0001154 _cons | .0481003 .398453 0.12 0.904 -.7328532 .8290538 ------------------------------------------------------------------------------ Instrumented: educ Instruments: exper expersq motheduc fatheduc . estat overid Tests of overidentifying restrictions: Sargan (score) chi2(1) = .378071 (p = 0.5386) Basmann chi2(1) = .373985 (p = 0.5408) . ***pvalue>0.05 => as condicoes de sobreidentificacao nao sao rejeitadas, ha indi > cio de sobreidentificacao do modelo . ivreg lwage (educ= motheduc fatheduc huseduc) exper expersq, first First-stage regressions ----------------------- Source | SS df MS Number of obs = 428 -------------+---------------------------------- F(5, 422) = 63.30 Model | 955.830608 5 191.166122 Prob > F = 0.0000 Residual | 1274.36565 422 3.01982382 R-squared = 0.4286 -------------+---------------------------------- Adj R-squared = 0.4218 Total | 2230.19626 427 5.22294206 Root MSE = 1.7378 ------------------------------------------------------------------------------ educ | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- exper | .0374977 .0343102 1.09 0.275 -.0299424 .1049379 expersq | -.0006002 .0010261 -0.58 0.559 -.0026171 .0014167 motheduc | .1141532 .0307835 3.71 0.000 .0536452 .1746613 fatheduc | .1060801 .0295153 3.59 0.000 .0480648 .1640955 huseduc | .3752548 .0296347 12.66 0.000 .3170049 .4335048 _cons | 5.538311 .4597824 12.05 0.000 4.634562 6.44206 ------------------------------------------------------------------------------ Instrumental variables (2SLS) regression Source | SS df MS Number of obs = 428 -------------+---------------------------------- F(3, 424) = 11.52 Model | 33.3927368 3 11.1309123 Prob > F = 0.0000 Residual | 189.934704 424 .447959208 R-squared = 0.1495 -------------+---------------------------------- Adj R-squared = 0.1435 Total | 223.327441 427 .523015084 Root MSE = .6693 ------------------------------------------------------------------------------ lwage | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- educ | .0803918 .021774 3.69 0.000 .0375934 .1231901 exper | .0430973 .0132649 3.25 0.001 .0170242 .0691704 expersq | -.0008628 .0003962 -2.18 0.030 -.0016415 -.0000841 _cons | -.1868572 .2853959 -0.65 0.513 -.7478242 .3741097 ------------------------------------------------------------------------------ Instrumented: educ Instruments: exper expersq motheduc fatheduc huseduc ------------------------------------------------------------------------------ . reg educ motheduc fatheduc huseduc exper expersq Source | SS df MS Number of obs = 753 -------------+---------------------------------- F(5, 747) = 130.16 Model | 1820.49038 5 364.098077 Prob > F = 0.0000 Residual | 2089.54946 747 2.79725496 R-squared = 0.4656 -------------+---------------------------------- Adj R-squared = 0.4620 Total | 3910.03984 752 5.19952106 Root MSE = 1.6725 ------------------------------------------------------------------------------ educ | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- motheduc | .130004 .0223789 5.81 0.000 .086071 .1739371 fatheduc | .1013613 .0214423 4.73 0.000 .059267 .1434556 huseduc | .3715645 .0220465 16.85 0.000 .3282839 .414845 exper | .0532406 .0218443 2.44 0.015 .0103571 .0961241 expersq | -.0007403 .000708 -1.05 0.296 -.0021303 .0006497 _cons | 5.115778 .298017 17.17 0.000 4.530727 5.700828 ------------------------------------------------------------------------------ . predict res_first, res . ivreg lwage (educ= motheduc fatheduc huseduc) exper expersq res_first res_first Instrumental variables (2SLS) regression Source | SS df MS Number of obs = 428 -------------+---------------------------------- F(4, 423) = 20.52 Model | 36.2853595 4 9.07133987 Prob > F = 0.0000 Residual | 187.042081 423 .442179861 R-squared = 0.1625 -------------+---------------------------------- Adj R-squared = 0.1546 Total | 223.327441 427 .523015084 Root MSE = .66497 ------------------------------------------------------------------------------ lwage | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- educ | .0801296 .0214782 3.73 0.000 .0379122 .122347 exper | .0438739 .0132172 3.32 0.001 .0178945 .0698534 expersq | -.0008708 .000394 -2.21 0.028 -.0016452 -.0000964 res_first | .0478873 .028334 1.69 0.092 -.0078056 .1035803 res_first | 0 (omitted) _cons | -.2008035 .2746073 -0.73 0.465 -.7405683 .3389612 ------------------------------------------------------------------------------ Instrumented: educ Instruments: exper expersq res_first res_first motheduc fatheduc huseduc ------------------------------------------------------------------------------ . ivreg lwage (educ= motheduc fatheduc huseduc) exper expersq res_first Instrumental variables (2SLS) regression Source | SS df MS Number of obs = 428 -------------+---------------------------------- F(4, 423) = 20.52 Model | 36.2853595 4 9.07133987 Prob > F = 0.0000 Residual | 187.042081 423 .442179861 R-squared = 0.1625 -------------+---------------------------------- Adj R-squared = 0.1546 Total | 223.327441 427 .523015084 Root MSE = .66497 ------------------------------------------------------------------------------ lwage | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- educ | .0801296 .0214782 3.73 0.000 .0379122 .122347 exper | .0438739 .0132172 3.32 0.001 .0178945 .0698534 expersq | -.0008708 .000394 -2.21 0.028 -.0016452 -.0000964 res_first | .0478873 .028334 1.69 0.092 -.0078056 .1035803 _cons | -.2008035 .2746073 -0.73 0.465 -.7405683 .3389612 ------------------------------------------------------------------------------ Instrumented: educ Instruments: exper expersq res_first motheduc fatheduc huseduc ------------------------------------------------------------------------------ . ivregress 2sls lwage (educ= motheduc fatheduc huseduc ) exper expersq Instrumental variables (2SLS) regression Number of obs = 428 Wald chi2(3) = 34.90 Prob > chi2 = 0.0000 R-squared = 0.1495 Root MSE = .66616 ------------------------------------------------------------------------------ lwage | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- educ | .0803918 .021672 3.71 0.000 .0379155 .1228681 exper | .0430973 .0132027 3.26 0.001 .0172204 .0689742 expersq | -.0008628 .0003943 -2.19 0.029 -.0016357 -.0000899 _cons | -.1868572 .2840591 -0.66 0.511 -.7436029 .3698885 ------------------------------------------------------------------------------ Instrumented: educ Instruments: exper expersq motheduc fatheduc huseduc . estat overid Tests of overidentifying restrictions: Sargan (score) chi2(2) = 1.11504 (p = 0.5726) Basmann chi2(2) = 1.10228 (p = 0.5763) . log off name: log: C:\Users\LabProf01\Desktop\IV_log.log log type: text paused on: 17 May 2023, 17:07:47 ---------------------------------------------------------------------------------- ---------------------------------------------------------------------------------- name: log: C:\Users\LabProf01\Desktop\IV_log.log log type: text resumed on: 17 May 2023, 17:07:57 . log close name: log: C:\Users\LabProf01\Desktop\IV_log.log log type: text closed on: 17 May 2023, 17:08:05 ----------------------------------------------------------------------------------