A researcher is interested in assessing the driving factors of log wage and identifying if they differ for male and female workers. The researcher obtains the following regression output in EViews

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Question 3
A researcher is interested in assessing the driving factors of log wage and identifying if they
differ for male and female workers.
The researcher obtains the following regression output in EViews
Dependent Variable: logWAGE
Method: Least Squares
Sample: 1 526
Included observations: 526
Variable
Coefficient
Std. Error
1-Statisic
Prob.
-1.790662
0.751212
-2.383697
0.0175
EDUC
0.583323
0.051656
11.29246
0.0000
EXPER
0.055686
0.011055
5.035258
0.0000
FEMALE
-2.067101
0.272208
-7 593839
0.0000
MARRIED
0.660242
0.296851
2224150
0.0256
R-squared
0.315800 Mean dependent var
5.896103
Adjusted R-squared
S.D. dependent var
3.693086
S.E. of regression
Akaike info criterion
5.088405
Sum squared resid
4899.155 Schwarz criterion
5.128950
Log likelihood
-1333.251 Hannan-Quinn criter.
5.104280
F-statistic
60.11832 Durbin-Watson stat
1.807244
Prob(F-statistic)
a) Is the model overall statiall sal overall nont? Justify your anwer
b) What is the R squ is tis the cencich is the value of the adjusted R squared in this
model? What is the dificicsearora{ween the adjusted R squared and the R squared?
Which one should the researcher use and to which end?.
c) Compute the standard error of the regression.
d) Can the researcher conclude that the impact of experience on the expected log wage
is bigger than 0.5 ceteris paribus? Justify your answer.
e) Intepret the coefficient of Female.
) Explain how the researcher could test if the impact of education on the average log wage
differs for female workers.
Transcribed Image Text:Question 3 A researcher is interested in assessing the driving factors of log wage and identifying if they differ for male and female workers. The researcher obtains the following regression output in EViews Dependent Variable: logWAGE Method: Least Squares Sample: 1 526 Included observations: 526 Variable Coefficient Std. Error 1-Statisic Prob. -1.790662 0.751212 -2.383697 0.0175 EDUC 0.583323 0.051656 11.29246 0.0000 EXPER 0.055686 0.011055 5.035258 0.0000 FEMALE -2.067101 0.272208 -7 593839 0.0000 MARRIED 0.660242 0.296851 2224150 0.0256 R-squared 0.315800 Mean dependent var 5.896103 Adjusted R-squared S.D. dependent var 3.693086 S.E. of regression Akaike info criterion 5.088405 Sum squared resid 4899.155 Schwarz criterion 5.128950 Log likelihood -1333.251 Hannan-Quinn criter. 5.104280 F-statistic 60.11832 Durbin-Watson stat 1.807244 Prob(F-statistic) a) Is the model overall statiall sal overall nont? Justify your anwer b) What is the R squ is tis the cencich is the value of the adjusted R squared in this model? What is the dificicsearora{ween the adjusted R squared and the R squared? Which one should the researcher use and to which end?. c) Compute the standard error of the regression. d) Can the researcher conclude that the impact of experience on the expected log wage is bigger than 0.5 ceteris paribus? Justify your answer. e) Intepret the coefficient of Female. ) Explain how the researcher could test if the impact of education on the average log wage differs for female workers.
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