Completed in Stata, R, Python and Julia
Completed in Stata, R, Python and Julia
Covariate means in the NSW and observational control samples
NSW Treat | NSW Control | Full CPS-1 | Full CPS-3 | P-score CPS-1 | P-score CPS-3 | |
---|---|---|---|---|---|---|
Age | 25.82 | 25.05 | 33.23 | 28.03 | 25.63 | 25.97 |
Years of schooling | 10.35 | 10.09 | 12.03 | 10.24 | 10.49 | 10.42 |
Black | 0.84 | 0.83 | 0.07 | 0.2 | 0.96 | 0.52 |
Hispanic | 0.06 | 0.11 | 0.07 | 0.14 | 0.03 | 0.2 |
Dropout | 0.71 | 0.83 | 0.3 | 0.6 | 0.6 | 0.63 |
Married | 0.19 | 0.15 | 0.71 | 0.51 | 0.26 | 0.29 |
1974 earnings | 2,096 | 2,107 | 14,017 | 5,619 | 2,821 | 2,969 |
1975 earnings | 1,532 | 1,267 | 13,651 | 2,466 | 1,950 | 1,859 |
Number of Obs. | 185 | 260 | 15,992 | 429 | 352 | 157 |
/* Old-fashioned standard errors */
Source | SS df MS Number of obs = 329509
-------------+------------------------------ F( 1,329507) =43782.56
Model | 17808.83 1 17808.83 Prob > F = 0.0000
Residual | 134029.045329507 .406756292 R-squared = 0.1173
-------------+------------------------------ Adj R-squared = 0.1173
Total | 151837.875329508 .460801788 Root MSE = .63777
------------------------------------------------------------------------------
lwklywge | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
educ | .070851 .0003386 209.24 0.000 .0701874 .0715147
_cons | 4.995182 .0044644 1118.88 0.000 4.986432 5.003932
------------------------------------------------------------------------------
/* Robust standard errors */
Linear regression Number of obs = 329509
F( 1,329507) =34577.15
Prob > F = 0.0000
R-squared = 0.1173
Root MSE = .63777
------------------------------------------------------------------------------
| Robust
lwklywge | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
educ | .070851 .000381 185.95 0.000 .0701042 .0715978
_cons | 4.995182 .0050739 984.49 0.000 4.985238 5.005127
------------------------------------------------------------------------------
/* Old-fashioned standard errors */
Source | SS df MS Number of obs = 21
-------------+------------------------------ F( 1, 19) = 485.23
Model | 1.13497742 1 1.13497742 Prob > F = 0.0000
Residual | .04444186 19 .002339045 R-squared = 0.9623
-------------+------------------------------ Adj R-squared = 0.9603
Total | 1.17941928 20 .058970964 Root MSE = .04836
------------------------------------------------------------------------------
lwklywge | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
educ | .070851 .0032164 22.03 0.000 .064119 .0775831
_cons | 4.995183 .0424075 117.79 0.000 4.906423 5.083943
------------------------------------------------------------------------------
/* Robust standard errors */
Linear regression Number of obs = 21
F( 1, 19) = 231.81
Prob > F = 0.0000
R-squared = 0.9623
Root MSE = .04836
------------------------------------------------------------------------------
| Robust
lwklywge | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
educ | .070851 .0046535 15.23 0.000 .0611112 .0805908
_cons | 4.995183 .0479533 104.17 0.000 4.894815 5.09555
------------------------------------------------------------------------------