`1 the stata output shows the result of a semilogarithmic regression of earnings on highest...

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`1 The Stata output shows the result of a semilogarithmic regression of earnings on highest educational qualification obtained, work experience, and the sex of the respondent, the educational qualifications being a professional degree, a PhD, a Master’s degree, a Bachelor’s degree, an Associate of Arts degree, and no qualification (high school drop-out). The high school diploma was the reference category. Provide an interpretation of the coefficients and perform t tests. EXERCISE 5.5

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Page 1: `1 The Stata output shows the result of a semilogarithmic regression of earnings on highest educational qualification obtained, work experience, and the

`1

The Stata output shows the result of a semilogarithmic regression of

earnings on highest educational qualification obtained, work

experience, and the sex of the respondent, the educational

qualifications being a professional degree, a PhD, a Master’s degree,

a Bachelor’s degree, an Associate of Arts degree, and no

qualification (high school drop-out). The high school diploma was

the reference category. Provide an interpretation of the coefficients

and perform t tests.

EXERCISE 5.5

Page 2: `1 The Stata output shows the result of a semilogarithmic regression of earnings on highest educational qualification obtained, work experience, and the

2

. reg LGEARN EDUCPROF EDUCMAST EDUCPHD EDUCBA EDUCAA EDUCDO EXP MALE

Source | SS df MS Number of obs = 540-------------+------------------------------ F( 8, 531) = 29.64 Model | 57.6389757 8 7.20487196 Prob > F = 0.0000 Residual | 129.068668 531 .243067171 R-squared = 0.3087-------------+------------------------------ Adj R-squared = 0.2983 Total | 186.707643 539 .34639637 Root MSE = .49302

------------------------------------------------------------------------------ LGEARN | Coef. Std. Err. t P>|t| [95% Conf. Interval]-------------+---------------------------------------------------------------- EDUCPROF | 1.59193 .2498069 6.37 0.000 1.101199 2.082661 EDUCPHD | .3089521 .4943698 0.62 0.532 -.6622084 1.280113 EDUCMAST | .6280672 .0993222 6.32 0.000 .4329546 .8231798 EDUCBA | .5053643 .0561215 9.00 0.000 .3951168 .6156118 EDUCAA | .170838 .0765684 2.23 0.026 .0204238 .3212522 EDUCDO | -.2527803 .08179 -3.09 0.002 -.413452 -.0921085 EXP | .0230536 .0050845 4.53 0.000 .0130654 .0330419 MALE | .2755451 .0437642 6.30 0.000 .189573 .3615173 _cons | 2.125885 .0915997 23.21 0.000 1.945943 2.305828------------------------------------------------------------------------------

The answer is given on the next slide. Remember that the dependent variable is the (natural) logarithm of hourly earnings.

EXERCISE 5.5

Page 3: `1 The Stata output shows the result of a semilogarithmic regression of earnings on highest educational qualification obtained, work experience, and the

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. reg LGEARN EDUCPROF EDUCMAST EDUCPHD EDUCBA EDUCAA EDUCDO EXP MALE

Source | SS df MS Number of obs = 540-------------+------------------------------ F( 8, 531) = 29.64 Model | 57.6389757 8 7.20487196 Prob > F = 0.0000 Residual | 129.068668 531 .243067171 R-squared = 0.3087-------------+------------------------------ Adj R-squared = 0.2983 Total | 186.707643 539 .34639637 Root MSE = .49302

------------------------------------------------------------------------------ LGEARN | Coef. Std. Err. t P>|t| [95% Conf. Interval]-------------+---------------------------------------------------------------- EDUCPROF | 1.59193 .2498069 6.37 0.000 1.101199 2.082661 EDUCPHD | .3089521 .4943698 0.62 0.532 -.6622084 1.280113 EDUCMAST | .6280672 .0993222 6.32 0.000 .4329546 .8231798 EDUCBA | .5053643 .0561215 9.00 0.000 .3951168 .6156118 EDUCAA | .170838 .0765684 2.23 0.026 .0204238 .3212522 EDUCDO | -.2527803 .08179 -3.09 0.002 -.413452 -.0921085 EXP | .0230536 .0050845 4.53 0.000 .0130654 .0330419 MALE | .2755451 .0437642 6.30 0.000 .189573 .3615173 _cons | 2.125885 .0915997 23.21 0.000 1.945943 2.305828------------------------------------------------------------------------------

The regression results indicate that those with professional degrees earn 159 percent more than high school graduates, or 391 percent more if calculated as 100(e1.592 – 1), the coefficient being significant at the 0.1 percent level.

EXERCISE 5.5

Page 4: `1 The Stata output shows the result of a semilogarithmic regression of earnings on highest educational qualification obtained, work experience, and the

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. reg LGEARN EDUCPROF EDUCMAST EDUCPHD EDUCBA EDUCAA EDUCDO EXP MALE

Source | SS df MS Number of obs = 540-------------+------------------------------ F( 8, 531) = 29.64 Model | 57.6389757 8 7.20487196 Prob > F = 0.0000 Residual | 129.068668 531 .243067171 R-squared = 0.3087-------------+------------------------------ Adj R-squared = 0.2983 Total | 186.707643 539 .34639637 Root MSE = .49302

------------------------------------------------------------------------------ LGEARN | Coef. Std. Err. t P>|t| [95% Conf. Interval]-------------+---------------------------------------------------------------- EDUCPROF | 1.59193 .2498069 6.37 0.000 1.101199 2.082661 EDUCPHD | .3089521 .4943698 0.62 0.532 -.6622084 1.280113 EDUCMAST | .6280672 .0993222 6.32 0.000 .4329546 .8231798 EDUCBA | .5053643 .0561215 9.00 0.000 .3951168 .6156118 EDUCAA | .170838 .0765684 2.23 0.026 .0204238 .3212522 EDUCDO | -.2527803 .08179 -3.09 0.002 -.413452 -.0921085 EXP | .0230536 .0050845 4.53 0.000 .0130654 .0330419 MALE | .2755451 .0437642 6.30 0.000 .189573 .3615173 _cons | 2.125885 .0915997 23.21 0.000 1.945943 2.305828------------------------------------------------------------------------------

The table gives the corresponding figures for all the educational qualifications.

EXERCISE 5.5

Professional 159.2 391.3 0.1%PhD 30.9 36.2 not sig.Master’s 62.8 87.4 0.1%Bachelor’s 50.5 65.7 0.1%Associate’s 17.1 18.6 5%Drop-out –25.3 –22.4 1%

Page 5: `1 The Stata output shows the result of a semilogarithmic regression of earnings on highest educational qualification obtained, work experience, and the

5

. reg LGEARN EDUCPROF EDUCMAST EDUCPHD EDUCBA EDUCAA EDUCDO EXP MALE

Source | SS df MS Number of obs = 540-------------+------------------------------ F( 8, 531) = 29.64 Model | 57.6389757 8 7.20487196 Prob > F = 0.0000 Residual | 129.068668 531 .243067171 R-squared = 0.3087-------------+------------------------------ Adj R-squared = 0.2983 Total | 186.707643 539 .34639637 Root MSE = .49302

------------------------------------------------------------------------------ LGEARN | Coef. Std. Err. t P>|t| [95% Conf. Interval]-------------+---------------------------------------------------------------- EDUCPROF | 1.59193 .2498069 6.37 0.000 1.101199 2.082661 EDUCPHD | .3089521 .4943698 0.62 0.532 -.6622084 1.280113 EDUCMAST | .6280672 .0993222 6.32 0.000 .4329546 .8231798 EDUCBA | .5053643 .0561215 9.00 0.000 .3951168 .6156118 EDUCAA | .170838 .0765684 2.23 0.026 .0204238 .3212522 EDUCDO | -.2527803 .08179 -3.09 0.002 -.413452 -.0921085 EXP | .0230536 .0050845 4.53 0.000 .0130654 .0330419 MALE | .2755451 .0437642 6.30 0.000 .189573 .3615173 _cons | 2.125885 .0915997 23.21 0.000 1.945943 2.305828------------------------------------------------------------------------------

Males earn 27.6 percent (31.8 percent) more than females, and every year of work experience increases earnings by 2.3 percent.

EXERCISE 5.5

Page 6: `1 The Stata output shows the result of a semilogarithmic regression of earnings on highest educational qualification obtained, work experience, and the

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. reg LGEARN EDUCPROF EDUCMAST EDUCPHD EDUCBA EDUCAA EDUCDO EXP MALE

Source | SS df MS Number of obs = 540-------------+------------------------------ F( 8, 531) = 29.64 Model | 57.6389757 8 7.20487196 Prob > F = 0.0000 Residual | 129.068668 531 .243067171 R-squared = 0.3087-------------+------------------------------ Adj R-squared = 0.2983 Total | 186.707643 539 .34639637 Root MSE = .49302

------------------------------------------------------------------------------ LGEARN | Coef. Std. Err. t P>|t| [95% Conf. Interval]-------------+---------------------------------------------------------------- EDUCPROF | 1.59193 .2498069 6.37 0.000 1.101199 2.082661 EDUCPHD | .3089521 .4943698 0.62 0.532 -.6622084 1.280113 EDUCMAST | .6280672 .0993222 6.32 0.000 .4329546 .8231798 EDUCBA | .5053643 .0561215 9.00 0.000 .3951168 .6156118 EDUCAA | .170838 .0765684 2.23 0.026 .0204238 .3212522 EDUCDO | -.2527803 .08179 -3.09 0.002 -.413452 -.0921085 EXP | .0230536 .0050845 4.53 0.000 .0130654 .0330419 MALE | .2755451 .0437642 6.30 0.000 .189573 .3615173 _cons | 2.125885 .0915997 23.21 0.000 1.945943 2.305828------------------------------------------------------------------------------

The coefficients of those with professional degrees and PhDs should be treated cautiously since there were only six individuals in the former category and three in the latter. For the other categories the numbers of observations were: masters 31; bachelor’s 98; associate’s 48; high school diploma (or GED) 297; and drop-out 46.

EXERCISE 5.5

Professional n = 6 Associate’s n = 48PhD n = 3 High school diploma n = 297Master’s n = 31 High school drop-out n = 46Bachelor’s n = 98

Page 7: `1 The Stata output shows the result of a semilogarithmic regression of earnings on highest educational qualification obtained, work experience, and the

Copyright Christopher Dougherty 2000–2007. This slideshow may be freely copied for personal use.

16.11.07