a. Write the results from specification (1) that are presented in figure (2) in the format of a fitted line (round the decimals places up to 2). b. After adding variable abil to the model (Figure 3), what happened to the standard error of the coefficient of educ? Discuss. c. Are the coefficients of fatheduc and motheduc individually significant at 5% level? d.Will you keep the two variables that control for parental education in the model? Explain your answer.

ENGR.ECONOMIC ANALYSIS
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Chapter1: Making Economics Decisions
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1

2.Use the Stata outputs presented in handout (1) to answer the following
questions.
a. Write the results from specification (1) that are presented in figure (2) in
the format of a fitted line (round the decimals places up to 2).
b. After adding variable abil to the model (Figure 3), what happened to the
standard error of the coefficient of educ? Discuss.
c. Are the coefficients of fatheduc and motheduc individually significant at
5% level?
d.Will you keep the two variables that control for parental education in the model? Explain
your answer.
re (1) – variable descriptions
VAR NAME
DESCRIPTION
WAGE
hourly wage
ABIL
a score to measure abilily
completed years of education for the
respondent
mother's completed years of education
EDUC
МОTHEDUC
FATHEDUC
father's completed years of education
Figure (2) – Stata output for specification 1
• reg wage educ exper
Source
df
MS
Number of obs
1,230
111.44
F(2, 1227)
Model
15582.8718
2
7791.4359
Prob > F
e.0000
Residual
R-squared
Adj R-squared
85787.2083
1,227
69.9162252
0.1537
0.1523
Total
101370.08
1,229 82.4817576
Root MSE
8.3616
wage
Coef.
Std. Err.
P>|t|
[95% Conf. Interval]
educ
1.94783
.1389974
14.01
0.000
1.675131
2.220529
exper
.6142872
.1051414
5.84
0.000
.4080103
.8205641
_cons
-18.70484
2.723747
-6.87
0.000
- 24.04856
-13.36112
Transcribed Image Text:2.Use the Stata outputs presented in handout (1) to answer the following questions. a. Write the results from specification (1) that are presented in figure (2) in the format of a fitted line (round the decimals places up to 2). b. After adding variable abil to the model (Figure 3), what happened to the standard error of the coefficient of educ? Discuss. c. Are the coefficients of fatheduc and motheduc individually significant at 5% level? d.Will you keep the two variables that control for parental education in the model? Explain your answer. re (1) – variable descriptions VAR NAME DESCRIPTION WAGE hourly wage ABIL a score to measure abilily completed years of education for the respondent mother's completed years of education EDUC МОTHEDUC FATHEDUC father's completed years of education Figure (2) – Stata output for specification 1 • reg wage educ exper Source df MS Number of obs 1,230 111.44 F(2, 1227) Model 15582.8718 2 7791.4359 Prob > F e.0000 Residual R-squared Adj R-squared 85787.2083 1,227 69.9162252 0.1537 0.1523 Total 101370.08 1,229 82.4817576 Root MSE 8.3616 wage Coef. Std. Err. P>|t| [95% Conf. Interval] educ 1.94783 .1389974 14.01 0.000 1.675131 2.220529 exper .6142872 .1051414 5.84 0.000 .4080103 .8205641 _cons -18.70484 2.723747 -6.87 0.000 - 24.04856 -13.36112
Figure (3) – Stata output for specification 2
• reg wage educ exper abil
Source
df
MS
Number of obs
1,230
F(3, 1226)
79.35
3 5494.14037
1,226 69.2395261
Model
16482.4211
Prob > F
0.0000
Residual
84887.659
R-squared
Adj R-squared
0.1626
0.1605
Total
101370.08
1,229 82.4817576
Root MSE
8.321
wage
Coef.
Std. Err.
t
P>|t|
[95% Conf. Interval]
educ
1.701564
.1542768
11.03
0.000
1.398889
2.00424
.6393264
.1048617
6.10
0.000
.4335981
.8450547
exper
abil
.4879376
.135372
3.60
0.000
.2223512
.753524
_cons
-16.63977
2.770423
-6.01
0.000
-22.07506
-11.20447
Figure (4) – Stata output for specification 2
reg wage educ exper abil fatheduc motheduc
Source
df
MS
Number of obs
1,230
F(5, 1224)
Prob > F
48.98
5 3380.07315
Model
Residual
16900.3658
e.0000
84469.7143
R-squared
Adj R-squared
Root MSE
1,224 69.0112045
0.1667
%3D
%3D
0.1633
Total
101370.08
1,229 82.4817576
8.3073
Coef.
Std. Err.
P>|t|
[95% Conf. Interval]
wage
t
educ
1.626432
.158765
10.24
e.000
1.314951
1.937914
.6577769
.1050186
6.26
e.000
.4517405
.8638132
exper
abil
.4283876
.1374382
3.12
0.002
.158747
.6980281
fatheduc
.2366884
.1306607
1.81
0.070
-.0196555
.4930322
motheduc
.0964206
.1304291
0.74
0.460
-.1594688
.35231
_cons
-19.47246
3.00298
-6.48
0.000
-25.36401
-13.5809
Transcribed Image Text:Figure (3) – Stata output for specification 2 • reg wage educ exper abil Source df MS Number of obs 1,230 F(3, 1226) 79.35 3 5494.14037 1,226 69.2395261 Model 16482.4211 Prob > F 0.0000 Residual 84887.659 R-squared Adj R-squared 0.1626 0.1605 Total 101370.08 1,229 82.4817576 Root MSE 8.321 wage Coef. Std. Err. t P>|t| [95% Conf. Interval] educ 1.701564 .1542768 11.03 0.000 1.398889 2.00424 .6393264 .1048617 6.10 0.000 .4335981 .8450547 exper abil .4879376 .135372 3.60 0.000 .2223512 .753524 _cons -16.63977 2.770423 -6.01 0.000 -22.07506 -11.20447 Figure (4) – Stata output for specification 2 reg wage educ exper abil fatheduc motheduc Source df MS Number of obs 1,230 F(5, 1224) Prob > F 48.98 5 3380.07315 Model Residual 16900.3658 e.0000 84469.7143 R-squared Adj R-squared Root MSE 1,224 69.0112045 0.1667 %3D %3D 0.1633 Total 101370.08 1,229 82.4817576 8.3073 Coef. Std. Err. P>|t| [95% Conf. Interval] wage t educ 1.626432 .158765 10.24 e.000 1.314951 1.937914 .6577769 .1050186 6.26 e.000 .4517405 .8638132 exper abil .4283876 .1374382 3.12 0.002 .158747 .6980281 fatheduc .2366884 .1306607 1.81 0.070 -.0196555 .4930322 motheduc .0964206 .1304291 0.74 0.460 -.1594688 .35231 _cons -19.47246 3.00298 -6.48 0.000 -25.36401 -13.5809
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