--------------------------------------------------------------------------------- name: log: C:\Users\LabProf01\Documents\03_11.log log type: text opened on: 3 Nov 2022, 15:45:03 . reg wage educ exper female Source | SS df MS Number of obs = 526 -------------+---------------------------------- F(3, 522) = 77.92 Model | 2214.74206 3 738.247353 Prob > F = 0.0000 Residual | 4945.67223 522 9.47446788 R-squared = 0.3093 -------------+---------------------------------- Adj R-squared = 0.3053 Total | 7160.41429 525 13.6388844 Root MSE = 3.0781 ------------------------------------------------------------------------------ wage | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- educ | .6025802 .0511174 11.79 0.000 .5021591 .7030012 exper | .0642417 .0104003 6.18 0.000 .0438101 .0846734 female | -2.155517 .2703055 -7.97 0.000 -2.686537 -1.624497 _cons | -1.734481 .7536203 -2.30 0.022 -3.214982 -.2539797 ------------------------------------------------------------------------------ . display .6025802 /.0511174 11.788162 . test (educ=0.55) ( 1) educ = .55 F( 1, 522) = 1.06 Prob > F = 0.3041 . test (educ=0.5) ( 1) educ = .5 F( 1, 522) = 4.03 Prob > F = 0.0453 . test educ exper ( 1) educ = 0 ( 2) exper = 0 F( 2, 522) = 73.17 Prob > F = 0.0000 . reg wage female Source | SS df MS Number of obs = 526 -------------+---------------------------------- F(1, 524) = 68.54 Model | 828.220467 1 828.220467 Prob > F = 0.0000 Residual | 6332.19382 524 12.0843394 R-squared = 0.1157 -------------+---------------------------------- Adj R-squared = 0.1140 Total | 7160.41429 525 13.6388844 Root MSE = 3.4763 ------------------------------------------------------------------------------ wage | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- female | -2.51183 .3034092 -8.28 0.000 -3.107878 -1.915782 _cons | 7.099489 .2100082 33.81 0.000 6.686928 7.51205 ------------------------------------------------------------------------------ . display (( 0.3093-0.1157)/2)/(1-0.3093)/(522) .00026848 . display (( 0.3093-0.1157)/2)/((1-0.3093)/(522)) 73.157087 . sum educ Variable | Obs Mean Std. Dev. Min Max -------------+--------------------------------------------------------- educ | 526 12.56274 2.769022 0 18 . display .6025802/12.56274 .04796567 . reg wage educ exper female Source | SS df MS Number of obs = 526 -------------+---------------------------------- F(3, 522) = 77.92 Model | 2214.74206 3 738.247353 Prob > F = 0.0000 Residual | 4945.67223 522 9.47446788 R-squared = 0.3093 -------------+---------------------------------- Adj R-squared = 0.3053 Total | 7160.41429 525 13.6388844 Root MSE = 3.0781 ------------------------------------------------------------------------------ wage | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- educ | .6025802 .0511174 11.79 0.000 .5021591 .7030012 exper | .0642417 .0104003 6.18 0.000 .0438101 .0846734 female | -2.155517 .2703055 -7.97 0.000 -2.686537 -1.624497 _cons | -1.734481 .7536203 -2.30 0.022 -3.214982 -.2539797 ------------------------------------------------------------------------------ . test educ exper female ( 1) educ = 0 ( 2) exper = 0 ( 3) female = 0 F( 3, 522) = 77.92 Prob > F = 0.0000 . test (female<0) < not found r(111); . reg wage educ exper female Source | SS df MS Number of obs = 526 -------------+---------------------------------- F(3, 522) = 77.92 Model | 2214.74206 3 738.247353 Prob > F = 0.0000 Residual | 4945.67223 522 9.47446788 R-squared = 0.3093 -------------+---------------------------------- Adj R-squared = 0.3053 Total | 7160.41429 525 13.6388844 Root MSE = 3.0781 ------------------------------------------------------------------------------ wage | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- educ | .6025802 .0511174 11.79 0.000 .5021591 .7030012 exper | .0642417 .0104003 6.18 0.000 .0438101 .0846734 female | -2.155517 .2703055 -7.97 0.000 -2.686537 -1.624497 _cons | -1.734481 .7536203 -2.30 0.022 -3.214982 -.2539797 ------------------------------------------------------------------------------ . test (female<0) < not found r(111); . predict wagehat (option xb assumed; fitted values) . gen resid=wage-wagehat . sum Variable | Obs Mean Std. Dev. Min Max -------------+--------------------------------------------------------- wage | 526 5.896103 3.693086 .53 24.98 educ | 526 12.56274 2.769022 0 18 exper | 526 17.01711 13.57216 1 51 tenure | 526 5.104563 7.224462 0 44 nonwhite | 526 .1026616 .3038053 0 1 -------------+--------------------------------------------------------- female | 526 .4790875 .500038 0 1 married | 526 .608365 .4885804 0 1 numdep | 526 1.043726 1.261891 0 6 smsa | 526 .7224335 .4482246 0 1 northcen | 526 .2509506 .4339728 0 1 -------------+--------------------------------------------------------- south | 526 .3555133 .4791242 0 1 west | 526 .1692015 .3752867 0 1 construc | 526 .0456274 .2088743 0 1 ndurman | 526 .1140684 .318197 0 1 trcommpu | 526 .0437262 .20468 0 1 -------------+--------------------------------------------------------- trade | 526 .2870722 .4528262 0 1 services | 526 .1007605 .3012978 0 1 profserv | 526 .2585551 .4382574 0 1 profocc | 526 .3669202 .4824233 0 1 clerocc | 526 .1673004 .3735991 0 1 -------------+--------------------------------------------------------- servocc | 526 .1406844 .3480267 0 1 lwage | 526 1.623268 .5315382 -.6348783 3.218076 expersq | 526 473.4354 616.0448 1 2601 tenursq | 526 78.15019 199.4347 0 1936 wagehat | 526 5.896103 2.053912 -2.47668 10.97497 -------------+--------------------------------------------------------- resid | 526 -1.09e-08 3.069255 -6.385552 14.82172 . gen resid2=resid^2 . predict teste, res . reg resid2 educ exper female Source | SS df MS Number of obs = 526 -------------+---------------------------------- F(3, 522) = 13.13 Model | 22587.9406 3 7529.31352 Prob > F = 0.0000 Residual | 299359.524 522 573.485679 R-squared = 0.0702 -------------+---------------------------------- Adj R-squared = 0.0648 Total | 321947.465 525 613.233267 Root MSE = 23.948 ------------------------------------------------------------------------------ resid2 | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- educ | 1.881484 .3976971 4.73 0.000 1.1002 2.662767 exper | .2694904 .0809153 3.33 0.001 .1105307 .4284501 female | -6.365282 2.102997 -3.03 0.003 -10.49666 -2.233904 _cons | -15.77059 5.863223 -2.69 0.007 -27.289 -4.252173 ------------------------------------------------------------------------------ . test educ exper female ( 1) educ = 0 ( 2) exper = 0 ( 3) female = 0 F( 3, 522) = 13.13 Prob > F = 0.0000 . gen educ2=educ^2 . gen exper2=exper^2 . gen educ_exper=educ*exper . gen educ_female=educ*female . gen exper_female=exper*female . reg resid2 educ exper female educ2 exper2 educ_exper educ_female exper_female Source | SS df MS Number of obs = 526 -------------+---------------------------------- F(8, 517) = 8.86 Model | 38813.8288 8 4851.72861 Prob > F = 0.0000 Residual | 283133.636 517 547.647265 R-squared = 0.1206 -------------+---------------------------------- Adj R-squared = 0.1070 Total | 321947.465 525 613.233267 Root MSE = 23.402 ------------------------------------------------------------------------------ resid2 | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- educ | -9.233883 2.824169 -3.27 0.001 -14.78214 -3.685624 exper | -.3134812 .5880671 -0.53 0.594 -1.468776 .8418137 female | -.6432169 11.72631 -0.05 0.956 -23.6803 22.39387 educ2 | .3862927 .0934033 4.14 0.000 .2027961 .5697893 exper2 | -.0105922 .0065141 -1.63 0.105 -.0233897 .0022052 educ_exper | .0968493 .0341546 2.84 0.005 .0297505 .1639481 educ_female | -.0165577 .832958 -0.02 0.984 -1.652956 1.619841 exper_female | -.2823034 .1596004 -1.77 0.078 -.5958485 .0312417 _cons | 54.84404 22.08168 2.48 0.013 11.46319 98.2249 ------------------------------------------------------------------------------ . gen wagehat2=wagehat^2 . reg resid2 wagehat wagehat2 Source | SS df MS Number of obs = 526 -------------+---------------------------------- F(2, 523) = 27.74 Model | 30878.5205 2 15439.2602 Prob > F = 0.0000 Residual | 291068.944 523 556.537179 R-squared = 0.0959 -------------+---------------------------------- Adj R-squared = 0.0925 Total | 321947.465 525 613.233267 Root MSE = 23.591 ------------------------------------------------------------------------------ resid2 | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- wagehat | -4.664488 2.035402 -2.29 0.022 -8.663055 -.6659209 wagehat2 | .671918 .1693937 3.97 0.000 .3391423 1.004694 _cons | 10.71701 5.923432 1.81 0.071 -.9196321 22.35365 ------------------------------------------------------------------------------ . reg wage educ exper female, robust Linear regression Number of obs = 526 F(3, 522) = 51.41 Prob > F = 0.0000 R-squared = 0.3093 Root MSE = 3.0781 ------------------------------------------------------------------------------ | Robust wage | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- educ | .6025802 .0641895 9.39 0.000 .4764786 .7286817 exper | .0642417 .010044 6.40 0.000 .0445102 .0839733 female | -2.155517 .2591294 -8.32 0.000 -2.664582 -1.646453 _cons | -1.734481 .8577554 -2.02 0.044 -3.419558 -.0494042 ------------------------------------------------------------------------------ . reg wage educ exper female, rob Linear regression Number of obs = 526 F(3, 522) = 51.41 Prob > F = 0.0000 R-squared = 0.3093 Root MSE = 3.0781 ------------------------------------------------------------------------------ | Robust wage | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- educ | .6025802 .0641895 9.39 0.000 .4764786 .7286817 exper | .0642417 .010044 6.40 0.000 .0445102 .0839733 female | -2.155517 .2591294 -8.32 0.000 -2.664582 -1.646453 _cons | -1.734481 .8577554 -2.02 0.044 -3.419558 -.0494042 ------------------------------------------------------------------------------ . estat hettest, rhs iid hettest not appropriate after robust cluster() r(498); . reg wage educ exper female Source | SS df MS Number of obs = 526 -------------+---------------------------------- F(3, 522) = 77.92 Model | 2214.74206 3 738.247353 Prob > F = 0.0000 Residual | 4945.67223 522 9.47446788 R-squared = 0.3093 -------------+---------------------------------- Adj R-squared = 0.3053 Total | 7160.41429 525 13.6388844 Root MSE = 3.0781 ------------------------------------------------------------------------------ wage | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- educ | .6025802 .0511174 11.79 0.000 .5021591 .7030012 exper | .0642417 .0104003 6.18 0.000 .0438101 .0846734 female | -2.155517 .2703055 -7.97 0.000 -2.686537 -1.624497 _cons | -1.734481 .7536203 -2.30 0.022 -3.214982 -.2539797 ------------------------------------------------------------------------------ . estat hettest, rhs iid Breusch-Pagan / Cook-Weisberg test for heteroskedasticity Ho: Constant variance Variables: educ exper female chi2(3) = 36.90 Prob > chi2 = 0.0000 . estat imtest, preserve white White's test for Ho: homoskedasticity against Ha: unrestricted heteroskedasticity chi2(8) = 63.41 Prob > chi2 = 0.0000 Cameron & Trivedi's decomposition of IM-test --------------------------------------------------- Source | chi2 df p ---------------------+----------------------------- Heteroskedasticity | 63.41 8 0.0000 Skewness | 31.28 3 0.0000 Kurtosis | 9.61 1 0.0019 ---------------------+----------------------------- Total | 104.31 12 0.0000 --------------------------------------------------- . twoway (scatter wage educ, sort) . twoway (scatter wage educ, sort) (lfit wage educ) . twoway (scatter wage educ, sort) (lfit wage educ) (qfit wage educ) . twoway (scatter wage educ, sort) (lfit wage educ) (qfit wage educ) . twoway (scatter wage educ, sort) (lfit wage educ) (qfit wage educ) . reg wage educ exper female Source | SS df MS Number of obs = 526 -------------+---------------------------------- F(3, 522) = 77.92 Model | 2214.74206 3 738.247353 Prob > F = 0.0000 Residual | 4945.67223 522 9.47446788 R-squared = 0.3093 -------------+---------------------------------- Adj R-squared = 0.3053 Total | 7160.41429 525 13.6388844 Root MSE = 3.0781 ------------------------------------------------------------------------------ wage | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- educ | .6025802 .0511174 11.79 0.000 .5021591 .7030012 exper | .0642417 .0104003 6.18 0.000 .0438101 .0846734 female | -2.155517 .2703055 -7.97 0.000 -2.686537 -1.624497 _cons | -1.734481 .7536203 -2.30 0.022 -3.214982 -.2539797 ------------------------------------------------------------------------------ . display -1.734481 +(-2.155517*1) -3.889998 . reg wage educ exper female educ_female exper_female Source | SS df MS Number of obs = 526 -------------+---------------------------------- F(5, 520) = 53.18 Model | 2422.6316 5 484.526319 Prob > F = 0.0000 Residual | 4737.7827 520 9.11112057 R-squared = 0.3383 -------------+---------------------------------- Adj R-squared = 0.3320 Total | 7160.41429 525 13.6388844 Root MSE = 3.0185 ------------------------------------------------------------------------------ wage | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- educ | .7254958 .0653954 11.09 0.000 .5970242 .8539674 exper | .1128012 .0145464 7.75 0.000 .0842243 .141378 female | 2.585399 1.449019 1.78 0.075 -.261252 5.432049 educ_female | -.2494 .1026407 -2.43 0.015 -.4510414 -.0477586 exper_female | -.0947253 .0204177 -4.64 0.000 -.1348366 -.054614 _cons | -4.158992 .9770286 -4.26 0.000 -6.0784 -2.239584 ------------------------------------------------------------------------------ . display .7254958 -.2494 .4760958 . display .1128012 -.0947253 .0180759 . log close name: log: C:\Users\LabProf01\Documents\03_11.log log type: text closed on: 3 Nov 2022, 16:43:42 ---------------------------------------------------------------------------------