. xi: regress lninct lnage i.wbho female i.ed2 i.wbho _Iwbho_1-4 (naturally coded; _Iwbho_1 omitted) i.ed2 _Ied2_1-6 (naturally coded; _Ied2_1 omitted)
Source | SS df MS Number of obs = 1917265 -------------+------------------------------ F( 10,1917254) =70138.14
Model | 746252.953 10 74625.2953 Prob > F = 0.0000
Residual | 2039912.041917254 1.06397589 R-squared = 0.2678 -------------+------------------------------ Adj R-squared = 0.2678
Total | 2786164.991917264 1.45319841 Root MSE = 1.0315
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lninct | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+----------------------------------------------------------------
lnage | .6809353 .0018016 377.96 0.000 .6774042 .6844664
_Iwbho_2 | -.1009164 .0025144 -40.13 0.000 -.1058446 -.0959882
_Iwbho_3 | .067665 .0026772 25.27 0.000 .0624178 .0729122
_Iwbho_4 | -.106419 .0034298 -31.03 0.000 -.1131414 -.0996967
female | -.5884933 .0014952 -393.59 0.000 -.5914238 -.5855627
_Ied2_2 | .101995 .0035272 28.92 0.000 .0950818 .1089082
_Ied2_3 | .6848738 .003237 211.58 0.000 .6785294 .6912182
_Ied2_4 | .9233323 .0032727 282.13 0.000 .9169178 .9297467
_Ied2_5 | 1.377962 .0035755 385.39 0.000 1.370954 1.38497
_Ied2_6 | 1.617381 .0039739 407.00 0.000 1.609592 1.62517
_cons | 6.74084 .0078632 857.27 0.000 6.725429 6.756252 ------------------------------------------------------------------------------
Even this regression can only explain 27% of the variation of U.S. personal income. Yet age comes up highly significant. Only sex and higher ed (college and grad/professional school) come up as more significant than age.
But, you may say, age comes up so significant because you include children, who're not in the labor force. Okay, let me drop those in ages below the labor force min:
. drop if age < 16 (647801 observations deleted)
. xi: regress lninct lnage i.wbho female i.ed2 i.wbho _Iwbho_1-4 (naturally coded; _Iwbho_1 omitted) i.ed2 _Ied2_1-6 (naturally coded; _Ied2_1 omitted)
Source | SS df MS Number of obs = 1908799 -------------+------------------------------ F( 10,1908788) =66456.15
Model | 694711.961 10 69471.1961 Prob > F = 0.0000
Residual | 1995387.771908788 1.04536898 R-squared = 0.2582 -------------+------------------------------ Adj R-squared = 0.2582
Total | 2690099.731908798 1.40931609 Root MSE = 1.0224
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lninct | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+----------------------------------------------------------------
lnage | .6350648 .0018162 349.67 0.000 .6315052 .6386245
_Iwbho_2 | -.1121831 .002499 -44.89 0.000 -.1170811 -.1072852
_Iwbho_3 | .040356 .0026666 15.13 0.000 .0351296 .0455824
_Iwbho_4 | -.115744 .0034079 -33.96 0.000 -.1224234 -.1090646
female | -.5889234 .0014854 -396.47 0.000 -.5918348 -.586012
_Ied2_2 | .056953 .0035532 16.03 0.000 .0499888 .0639172
_Ied2_3 | .6201275 .0032624 190.08 0.000 .6137333 .6265218
_Ied2_4 | .854046 .0033024 258.61 0.000 .8475733 .8605186
_Ied2_5 | 1.310026 .0035962 364.28 0.000 1.302978 1.317074
_Ied2_6 | 1.554936 .0039808 390.61 0.000 1.547134 1.562739
_cons | 6.982544 .0079991 872.92 0.000 6.966866 6.998222 ------------------------------------------------------------------------------
The t drops a little, but same basic result.