hw4s2016 answer

8/16/2019 Hw4S2016 Answer

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Estimation of log (wage )= β0+ β1 school+u (for women)

_cons .4590116 .0691256 6.64 0.000 .323469 .5945542

school .0949798 .0052552 18.07 0.000 .0846754 .1052842

lwage Coef. Std. Err. t P!t! "95# Conf. $nter%al&

'otal 1265.33498 2790 .453525082 (oot )SE * .63728

+d, (-s/ared * 0.1045 (esd/al 1132.67363 2789 .406121776 (-s/ared * 0.1048

)odel 132.661347 1 132.661347 Pro * 0.0000

1 2789 * 326.65

So/rce SS df )S /er of os * 2791

. regress lwage school f ale**0

l wage=0.4590116+0.0949798 school

Estimation of log (wage )= β0+ β1 school+u (for men)

_cons 1.01669 .0640046 15.88 0.000 .8911944 1.142186

school .0710905 .0050211 14.16 0.000 .0612455 .0809354


'otal 1519.02623 3106 .489061889 (oot )SE * .6779

+d, (-s/ared * 0.0603

(esd/al 1426.90429 3105 .459550497 (-s/ared * 0.0606

)odel 92.1219323 1 92.1219323 Pro * 0.0000

1 3105 * 200.46


. regress lwage school f ale**1

l wage=1.01669+0 .0710905 school

Estimation of log (wage )=γ 0+γ 1 school+γ 2male+γ 3 school×male+u(for both)

_cons .4590116 .0714809 6.42 0.000 .3188828 .5991404

schoolale -.0238893 .0073045 -3.27 0.001 -.0382088 -.0095699

ale .5576785 .0947668 5.88 0.000 .3719009 .7434561

school .0949798 .0054342 17.48 0.000 .0843267 .1056329


'otal 2853.71961 5897 .483927354 (oot )SE * .65899

+d, (-s/ared * 0.1026

(esd/al 2559.57793 5894 .434268396 (-s/ared * 0.1031

)odel 294.141681 3 98.047227 Pro * 0.0000

3 5894 * 225.78


. regress lwage school ale schoolale

lwage¿0.490116+0.0949798 school+0.5576785male−0.0238893 school × male

8/16/2019 Hw4S2016 Answer

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a) The intercept parameter of the pooled model (third model) implies that, holding all other

factors constant, the log of wages will be 0.490116. This parameter is statistically

significant at all leels gien that its p!al"e (0.000) is less than these leels of

significance (1#, $#, 10#).

The coefficient of school (0.0949%9&) means that an increase in years of school

by one "nit (ceteris parib"s) with increase the wage rate by 9.49%9. The coefficient is

statistically significant at 1#, $#, and 10# gien that its p!al"e (0.000) is less than

these leels of significance.

The coefficient of male (0.$$%6%&$) means that a man earns $.$%6%&$# more

than a female co"nterpart, holding years of schooling constant. This coefficient is

statistically significant at 1#, $#, and 10# since its p!al"e (0.000) is less than these

leels.

The coefficient of school'male (!0.0&&9) implies the effect of a "nit increase

in schooling on wage rate is less in men than in women by .&&9#. The coefficient is

statistically significant at all leels since its p!al"e (0.001) is less than 1#, $# and 10#. b) *e can recoer the coefficients of the first two models from the third model by

s"bstit"ting the al"e of male in the third model as follows.To obtain the first model we replace male with 0

lwage¿0.490116+0.0949798 school+0.5576785×0−0.0238893 school ×0*e remain with

lwage¿0.490116+0.0949798 school This is the model for women as earlier estimated

To obtain the nd model we replace male with 1 in the third modellwage¿0.490116+0.0949798 school+0.5576785×1−0.0238893 school ×1lwage¿(0.490116+0.5576785)+(0.0949798−0.0238893)schoollwage¿1.0477945+0.0710905 school

c)

d) +sing the stata command test-, the following o"tp"t was obtained

Pro * 0.0761

1 3105 * 3.15

1 school * .08

. test _"school&*0.08

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ien that the p!al"e (0.0%61) is greater than $# (0.0$), we fail to re/ect the n"ll

hypothesis and concl"de that a year of ed"cation for men increases wages by .e) erforming a test similar to the one in d) aboe b"t "sing the first model gies the

following o"tp"t.

Pro * 0.0044

1 27895 * 8.13

15 school * .08

. test _"school&*0.08

y obsering the p!al"e (0.0044), we reali2e that it is less than $# (0.0$). 3or this reason, we

re/ect the n"ll hypothesis and concl"de that a year of ed"cation for women doesn-t increase

wages by .

hw4s2016 answer

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