Example 7.3 on page 165 using fringe.dta.
use http://www.stata.com/data/jwooldridge/eacsap/fringe sureg ( hrearn educ exper expersq tenure tenuresq union south nrtheast nrthcen married white male) ( hrbens educ exper expersq tenure tenuresq union south nrtheast nrthcen married white male) Seemingly unrelated regression ---------------------------------------------------------------------- Equation Obs Parms RMSE "R-sq" chi2 P ---------------------------------------------------------------------- hrearn 616 12 4.3089 0.2051 158.93 0.0000 hrbens 616 12 .5152603 0.3987 408.40 0.0000 ---------------------------------------------------------------------- ------------------------------------------------------------------------------ | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- hrearn | educ | .4588139 .068393 6.71 0.000 .3247662 .5928617 exper | -.0758428 .0567371 -1.34 0.181 -.1870455 .0353598 expersq | .0039945 .0011655 3.43 0.001 .0017102 .0062787 tenure | .1100846 .0829207 1.33 0.184 -.052437 .2726062 tenuresq | -.0050706 .0032422 -1.56 0.118 -.0114252 .0012839 union | .8079933 .4034789 2.00 0.045 .0171892 1.598797 south | -.4566222 .5458508 -0.84 0.403 -1.52647 .6132258 nrtheast | -1.150759 .5993283 -1.92 0.055 -2.32542 .0239032 nrthcen | -.6362663 .5501462 -1.16 0.247 -1.714533 .4420005 married | .6423882 .4133664 1.55 0.120 -.167795 1.452571 white | 1.140891 .6054474 1.88 0.060 -.0457639 2.327546 male | 1.784702 .3937853 4.53 0.000 1.012897 2.556507 _cons | -2.632127 1.215291 -2.17 0.030 -5.014054 -.2501997 -------------+---------------------------------------------------------------- hrbens | educ | .0767924 .0081785 9.39 0.000 .0607629 .0928219 exper | .0225649 .0067846 3.33 0.001 .0092673 .0358626 expersq | -.0004734 .0001394 -3.40 0.001 -.0007465 -.0002002 tenure | .0535556 .0099157 5.40 0.000 .0341212 .07299 tenuresq | -.0011636 .0003877 -3.00 0.003 -.0019235 -.0004038 union | .3659085 .0482482 7.58 0.000 .2713438 .4604733 south | -.0226865 .0652731 -0.35 0.728 -.1506195 .1052464 nrtheast | -.0567468 .071668 -0.79 0.428 -.1972135 .0837198 nrthcen | -.0379984 .0657867 -0.58 0.564 -.1669381 .0909413 married | .0578626 .0494306 1.17 0.242 -.0390195 .1547447 white | .0901582 .0723997 1.25 0.213 -.0517426 .232059 male | .2683383 .047089 5.70 0.000 .1760454 .3606311 _cons | -.8897471 .1453251 -6.12 0.000 -1.174579 -.6049151 ------------------------------------------------------------------------------
Example 7.7 on page 172 using jtrain1.dta.
use http://www.stata.com/data/jwooldridge/eacsap/jtrain1, clear reg lscrap d89 d88 grant grant_1 Source | SS df MS Number of obs = 162 -------------+------------------------------ F( 4, 157) = 0.69 Model | 6.15830732 4 1.53957683 Prob > F = 0.5989 Residual | 349.586781 157 2.2266674 R-squared = 0.0173 -------------+------------------------------ Adj R-squared = -0.0077 Total | 355.745089 161 2.20959682 Root MSE = 1.4922 ------------------------------------------------------------------------------ lscrap | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- d89 | -.4965236 .3379281 -1.47 0.144 -1.163996 .1709483 d88 | -.2393704 .3108639 -0.77 0.442 -.8533854 .3746446 grant | .2000197 .3382846 0.59 0.555 -.4681564 .8681958 grant_1 | .0489357 .4360663 0.11 0.911 -.8123778 .9102492 _cons | .5974341 .203063 2.94 0.004 .1963462 .9985219 ------------------------------------------------------------------------------ xtgls lscrap d89 d88 grant grant_1, i(fcode) Cross-sectional time-series FGLS regression Coefficients: generalized least squares Panels: homoskedastic Correlation: no autocorrelation Estimated covariances = 1 Number of obs = 162 Estimated autocorrelations = 0 Number of groups = 54 Estimated coefficients = 5 Time periods = 3 Wald chi2(4) = 2.85 Log likelihood = -292.1696 Prob > chi2 = 0.5826 ------------------------------------------------------------------------------ lscrap | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- d89 | -.4965236 .3326723 -1.49 0.136 -1.148549 .1555021 d88 | -.2393704 .306029 -0.78 0.434 -.8391763 .3604354 grant | .2000197 .3330233 0.60 0.548 -.4526939 .8527332 grant_1 | .0489357 .4292842 0.11 0.909 -.7924458 .8903172 _cons | .5974341 .1999048 2.99 0.003 .2056279 .9892402 ------------------------------------------------------------------------------
Example 7.8 on page 173 and example 7.9 on page 177 using gpa.dta.
use http://www.stata.com/data/jwooldridge/eacsap/gpa, clear reg trmgpa spring cumgpa crsgpa frstsem season sat verbmath hsperc hssize black female Source | SS df MS Number of obs = 732 -------------+------------------------------ F( 11, 720) = 70.64 Model | 218.156689 11 19.8324263 Prob > F = 0.0000 Residual | 202.140267 720 .280750371 R-squared = 0.5191 -------------+------------------------------ Adj R-squared = 0.5117 Total | 420.296956 731 .574961636 Root MSE = .52986 ------------------------------------------------------------------------------ trmgpa | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- spring | -.0121568 .0464813 -0.26 0.794 -.1034118 .0790983 cumgpa | .3146158 .0404916 7.77 0.000 .2351201 .3941115 crsgpa | .9840371 .0960343 10.25 0.000 .7954964 1.172578 frstsem | .7691192 .1204162 6.39 0.000 .5327104 1.005528 season | -.0462625 .0470985 -0.98 0.326 -.1387292 .0462042 sat | .0014097 .0001464 9.63 0.000 .0011223 .0016972 verbmath | -.112616 .1306157 -0.86 0.389 -.3690491 .1438171 hsperc | -.0066014 .0010195 -6.48 0.000 -.0086029 -.0045998 hssize | -.0000576 .0000994 -0.58 0.562 -.0002527 .0001375 black | -.2312855 .0543347 -4.26 0.000 -.3379589 -.1246122 female | .2855528 .0509641 5.60 0.000 .1854967 .3856089 _cons | -2.067599 .3381007 -6.12 0.000 -2.731381 -1.403818 ------------------------------------------------------------------------------ xtgls trmgpa spring cumgpa crsgpa frstsem season sat verbmath hsperc hssize black female, i(id) Cross-sectional time-series FGLS regression Coefficients: generalized least squares Panels: homoskedastic Correlation: no autocorrelation Estimated covariances = 1 Number of obs = 732 Estimated autocorrelations = 0 Number of groups = 366 Estimated coefficients = 12 Time periods = 2 Wald chi2(11) = 790.00 Log likelihood = -567.6874 Prob > chi2 = 0.0000 ------------------------------------------------------------------------------ trmgpa | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- spring | -.0121568 .0460987 -0.26 0.792 -.1025086 .078195 cumgpa | .3146158 .0401583 7.83 0.000 .2359069 .3933247 crsgpa | .9840371 .0952439 10.33 0.000 .7973625 1.170712 frstsem | .7691192 .1194251 6.44 0.000 .5350503 1.003188 season | -.0462625 .0467108 -0.99 0.322 -.137814 .045289 sat | .0014097 .0001452 9.71 0.000 .0011251 .0016943 verbmath | -.112616 .1295406 -0.87 0.385 -.366511 .1412789 hsperc | -.0066014 .0010111 -6.53 0.000 -.0085831 -.0046196 hssize | -.0000576 .0000986 -0.58 0.559 -.0002508 .0001356 black | -.2312855 .0538875 -4.29 0.000 -.336903 -.125668 female | .2855528 .0505447 5.65 0.000 .186487 .3846185 _cons | -2.067599 .3353179 -6.17 0.000 -2.724811 -1.410388 ------------------------------------------------------------------------------ predict res, res sort id term by id: gen res1 = res[_n-1] (366 missing values generated) reg trmgpa cumgpa crsgpa season sat verbmath hsperc hssize black female res1 Source | SS df MS Number of obs = 366 -------------+------------------------------ F( 10, 355) = 56.83 Model | 133.915693 10 13.3915693 Prob > F = 0.0000 Residual | 83.6475687 355 .235626954 R-squared = 0.6155 -------------+------------------------------ Adj R-squared = 0.6047 Total | 217.563261 365 .59606373 Root MSE = .48541 ------------------------------------------------------------------------------ trmgpa | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- cumgpa | .3488556 .0720263 4.84 0.000 .2072037 .4905075 crsgpa | 1.00062 .117679 8.50 0.000 .7691844 1.232056 season | -.0271035 .0579515 -0.47 0.640 -.141075 .086868 sat | .0014126 .0001991 7.09 0.000 .001021 .0018042 verbmath | -.1136652 .1702718 -0.67 0.505 -.4485335 .2212032 hsperc | -.0049537 .0014175 -3.49 0.001 -.0077415 -.002166 hssize | -.0000843 .0001289 -0.65 0.513 -.0003378 .0001691 black | -.2407423 .0706801 -3.41 0.001 -.3797466 -.101738 female | .291915 .0732572 3.98 0.000 .1478423 .4359876 res1 | .1941929 .0612068 3.17 0.002 .0738194 .3145664 _cons | -2.266297 .4246611 -5.34 0.000 -3.101465 -1.431129 ------------------------------------------------------------------------------