<p>STATA SESSION ON WAGE DETERMINATION-DATA 6-4 ------log: C:\Stata8\data6-4.smcl log type: smcl opened on: 4 Oct 2006, 18:30:01</p><p>. generate float lnwage=log(wage) lnwage already defined r(110);</p><p>. des</p><p>Contains data from C:\Stata8\data6-4.dta obs: 49 vars: 5 4 Oct 2006 18:27 size: 637 (99.9% of memory free) ------storage display value variable name type format label variable label ------wage int %8.0g WAGE educ byte %8.0g EDUC exper byte %8.0g EXPER age byte %8.0g AGE lnwage float %9.0g ------Sorted by: Note: dataset has changed since last saved</p><p>. generate float educsq= educ^2</p><p>. des</p><p>Contains data from C:\Stata8\data6-4.dta obs: 49 vars: 6 4 Oct 2006 18:27 size: 833 (99.9% of memory free) ------storage display value variable name type format label variable label ------wage int %8.0g WAGE educ byte %8.0g EDUC exper byte %8.0g EXPER age byte %8.0g AGE lnwage float %9.0g educsq float %9.0g ------Sorted by: Note: dataset has changed since last saved</p><p>. generate float expersq=exper^2</p><p>. generate float agesq=age^2</p><p>. reg lnwage educ exper age educsq expersq agesq</p><p>Source | SS df MS Number of obs = 49 ------+------F( 6, 42) = 4.30 Model | 1.7868824 6 .297813734 Prob > F = 0.0018 Residual | 2.90784361 42 .069234372 R-squared = 0.3806 ------+------Adj R-squared = 0.2921 Total | 4.69472601 48 .097806792 Root MSE = .26312</p><p>------lnwage | Coef. Std. Err. t P>|t| [95% Conf. Interval] ------+------educ | -.0930409 .0863849 -1.08 0.288 -.2673727 .0812909 exper | .0138633 .0244844 0.57 0.574 -.0355482 .0632749 age | -.0004261 .0338212 -0.01 0.990 -.06868 .0678279 educsq | .0115248 .0062737 1.84 0.073 -.0011361 .0241857 expersq | .0004293 .0011187 0.38 0.703 -.0018284 .0026869 agesq | .0000211 .0003814 0.06 0.956 -.0007485 .0007908 _cons | 7.329324 .8091775 9.06 0.000 5.696338 8.962311 ------</p><p>. test agesq age</p><p>( 1) agesq = 0 ( 2) age = 0</p><p>F( 2, 42) = 0.06 Prob > F = 0.9376</p><p>. reg lnwage educ exper educsq expersq</p><p>Source | SS df MS Number of obs = 49 ------+------F( 4, 44) = 6.71 Model | 1.77795242 4 .444488105 Prob > F = 0.0003 Residual | 2.91677359 44 .066290309 R-squared = 0.3787 ------+------Adj R-squared = 0.3222 Total | 4.69472601 48 .097806792 Root MSE = .25747 ------lnwage | Coef. Std. Err. t P>|t| [95% Conf. Interval] ------+------educ | -.0882585 .0825358 -1.07 0.291 -.2545985 .0780814 exper | .0148466 .0237473 0.63 0.535 -.0330129 .0627062 educsq | .0111537 .0059725 1.87 0.068 -.000883 .0231905 expersq | .0004242 .0010872 0.39 0.698 -.001767 .0026154 _cons | 7.330007 .2909088 25.20 0.000 6.743719 7.916295 ------</p><p>. test exper expersq</p><p>( 1) exper = 0 ( 2) expersq = 0</p><p>F( 2, 44) = 7.46 Prob > F = 0.0016</p><p>. reg lnwage educ exper age educsq agesq</p><p>Source | SS df MS Number of obs = 49 ------+------F( 5, 43) = 5.24 Model | 1.77668884 5 .355337768 Prob > F = 0.0008 Residual | 2.91803717 43 .06786133 R-squared = 0.3784 ------+------Adj R-squared = 0.3062 Total | 4.69472601 48 .097806792 Root MSE = .2605</p><p>------lnwage | Coef. Std. Err. t P>|t| [95% Conf. Interval] ------+------educ | -.0900861 .0851836 -1.06 0.296 -.2618751 .0817029 exper | .0228825 .0067863 3.37 0.002 .0091966 .0365685 age | .001079 .0332582 0.03 0.974 -.0659925 .0681506 educsq | .0114553 .0062086 1.85 0.072 -.0010656 .0239761 agesq | 4.15e-06 .000375 0.01 0.991 -.0007521 .0007604 _cons | 7.252815 .7764107 9.34 0.000 5.687034 8.818596 ------</p><p>. reg lnwage educ exper age educsq</p><p>Source | SS df MS Number of obs = 49 ------+------F( 4, 44) = 6.70 Model | 1.77668054 4 .444170134 Prob > F = 0.0003 Residual | 2.91804548 44 .066319215 R-squared = 0.3784 ------+------Adj R-squared = 0.3219 Total | 4.69472601 48 .097806792 Root MSE = .25753</p><p>------lnwage | Coef. Std. Err. t P>|t| [95% Conf. Interval] ------+------educ | -.0899311 .0830632 -1.08 0.285 -.2573339 .0774717 exper | .022876 .0066833 3.42 0.001 .0094068 .0363452 age | .0014443 .0039605 0.36 0.717 -.0065376 .0094262 educsq | .0114427 .0060331 1.90 0.064 -.0007162 .0236016 _cons | 7.244874 .2925907 24.76 0.000 6.655196 7.834552 ------</p><p>. reg lnwage educ exper educsq </p><p>Source | SS df MS Number of obs = 49 ------+------F( 3, 45) = 9.06 Model | 1.767861 3 .589286999 Prob > F = 0.0001 Residual | 2.92686502 45 .065041445 R-squared = 0.3766 ------+------Adj R-squared = 0.3350 Total | 4.69472601 48 .097806792 Root MSE = .25503</p><p>------lnwage | Coef. Std. Err. t P>|t| [95% Conf. Interval] ------+------educ | -.0859429 .081543 -1.05 0.298 -.2501789 .0782931 exper | .0237915 .0061339 3.88 0.000 .0114372 .0361458 educsq | .0111344 .0059157 1.88 0.066 -.0007805 .0230493 _cons | 7.286796 .2664567 27.35 0.000 6.750125 7.823468 ------</p><p>. reg lnwage exper educsq</p><p>Source | SS df MS Number of obs = 49 ------+------F( 2, 46) = 13.00 Model | 1.69561118 2 .847805588 Prob > F = 0.0000 Residual | 2.99911484 46 .065198149 R-squared = 0.3612 ------+------Adj R-squared = 0.3334 Total | 4.69472601 48 .097806792 Root MSE = .25534</p><p>------lnwage | Coef. Std. Err. t P>|t| [95% Conf. Interval] ------+------exper | .0236809 .0061404 3.86 0.000 .011321 .0360408 educsq | .0050225 .001171 4.29 0.000 .0026654 .0073796 _cons | 7.023367 .0924574 75.96 0.000 6.83726 7.209474 ------</p>