Instrumental variables (2SLS) regression
Number of obs = 603
F( 5, 597) = 41.96
Prob > F = 0.0000
R-squared = 0.1386
Root MSE = .26523
|
logwage | Coef. Std. Err. t P>|t| [95% Conf. Interval]
higher | .2566441 .1030163 2.49 0.013 .0543257 .4589625
age | -.0054228 .0055142 -0.98 0.326 -.0162524 .0054068
age2 | .0000223 .0000675 0.33 0.741 -.0001103 .0001549
urban | .2587201 .0304102 8.51 0.000 .1989962 .3184441
rural | -.0207374 .0296745 -0.70 0.485 -.0790164 .0375417
_cons | 2.370127 .1065349 22.25 0.000 2.160899 2.579356
Instrumented: higher
Instruments: age age2 metropolitan rural father_educated
I am doing an assignment titled does expansion of higher education improve the earnings? The case of Russia
Regression has been run as shown above, the regression model is based on the widely used Mincer Model with minor modification and proxy to it.
Can anyone of you who are kind enough to assist in term of what do you think of the model and its output? And how would you interpret the output?