Question

1.The following computer output shows an estimated equation. Here; W: Weekly wage. MALE: Gender, takes the value of 1 if the worker is male and 0 if female. EDU: Education Level, EDU1=1 if the worker has no formal educationand 0 otherwise, EDU2=1 if the worker has primary educationand 0 otherwise, EDU3=1 if the worker has secondary and high school degree and 0 otherwise, EDU4=1 if the worker hasbachelor, master, and/or Ph.D. degree and 0 otherwise. EXP: Experience (the number of years being employed). Dependent Variable: W Method: Least Squares Date: 01/02/21. Time: 09:15 Sample: 1 935 Included observations: 935 Variable Coefficient Std. Error t-Statistic Prob. C 508.7969 49.56471 10.26531 0.0000 MALE 486.2831 20.27897 23.97967 0.0000 EDU2 37.93184 35.58875 1.065838 0.2868 EDU3 153.9977 40.51264 3.801225 0.0002 EDU4 251.2214 40.92353 6.138799 0.0000 EXP 10.28997 2.548076 4.038331 0.0001 R-squared 0.461610 Mean dependent var 957.9455 Adjusted R-squared 0.458713 S.D. dependent var 404.3608 S.E. of regression 297.4973 Akaike info criterion 14.23508 Sum squared resid 82220789 Schwarz criterion 14.26615 Log likelihood -6648.902 Hannan-Quinn criter. 14.24693 F-statistic 159.3033 Durbin-Watson stat 0.446774 Prob(F-statistic) 0.000000 a)Write out the estimated wage model below(use 1-digit for decimal): b)Check the statistical significance of EXP, and EDU2 at 5 % level respectively (hypothesis tests) below: c)Interpret the coefficientof determinationbelow: d)Interpret the coefficients of MALE, EDU3, and EXPbelow

          1.The following computer output shows an estimated equation. Here; W: Weekly
wage. MALE: Gender, takes the value of 1 if the worker is male and 0 if female.
EDU: Education Level, EDU1=1 if the worker has no formal educationand 0
otherwise, EDU2=1 if the worker has primary educationand 0 otherwise, EDU3=1
if the worker has secondary and high school degree and 0 otherwise, EDU4=1 if
the worker hasbachelor, master, and/or Ph.D. degree and 0 otherwise. EXP:
Experience (the number of years being employed).

Dependent Variable: W
Method: Least Squares
Date: 01/02/21. Time: 09:15
Sample: 1 935
Included observations: 935

Variable Coefficient Std. Error t-Statistic Prob.
C 508.7969 49.56471 10.26531 0.0000
MALE 486.2831 20.27897 23.97967 0.0000
EDU2 37.93184 35.58875 1.065838 0.2868
EDU3 153.9977 40.51264 3.801225 0.0002
EDU4 251.2214 40.92353 6.138799 0.0000
EXP 10.28997 2.548076 4.038331 0.0001

R-squared 0.461610 Mean dependent var 957.9455
Adjusted R-squared 0.458713 S.D. dependent var 404.3608
S.E. of regression 297.4973 Akaike info criterion 14.23508
Sum squared resid 82220789 Schwarz criterion 14.26615
Log likelihood -6648.902 Hannan-Quinn criter. 14.24693
F-statistic 159.3033 Durbin-Watson stat 0.446774
Prob(F-statistic) 0.000000

a)Write out the estimated wage model below(use 1-digit for decimal):
b)Check the statistical significance of EXP, and EDU2 at 5 % level respectively
(hypothesis tests) below:
c)Interpret the coefficientof determinationbelow:
d)Interpret the coefficients of MALE, EDU3, and EXPbelow

1.The following computer output shows an estimated equation. Here; W: Weekly
wage. MALE: Gender, takes the value of 1 if the worker is male and 0 if female.
EDU: Education Level, EDU1=1 if the worker has no formal educationand 0
otherwise, EDU2=1 if the worker has primary educationand 0 otherwise, EDU3=1
if the worker has secondary and high school degree and 0 otherwise, EDU4=1 if
the worker hasbachelor, master, and/or Ph.D. degree and 0 otherwise. EXP:
Experience (the number of years being employed).

Dependent Variable: W
Method: Least Squares
Date: 01/02/21. Time: 09:15
Sample: 1 935
Included observations: 935

Variable Coefficient Std. Error t-Statistic Prob.
C 508.7969 49.56471 10.26531 0.0000
MALE 486.2831 20.27897 23.97967 0.0000
EDU2 37.93184 35.58875 1.065838 0.2868
EDU3 153.9977 40.51264 3.801225 0.0002
EDU4 251.2214 40.92353 6.138799 0.0000
EXP 10.28997 2.548076 4.038331 0.0001

R-squared 0.461610 Mean dependent var 957.9455
Adjusted R-squared 0.458713 S.D. dependent var 404.3608
S.E. of regression 297.4973 Akaike info criterion 14.23508
Sum squared resid 82220789 Schwarz criterion 14.26615
Log likelihood -6648.902 Hannan-Quinn criter. 14.24693
F-statistic 159.3033 Durbin-Watson stat 0.446774
Prob(F-statistic) 0.000000

a)Write out the estimated wage model below(use 1-digit for decimal):
b)Check the statistical significance of EXP, and EDU2 at 5 % level respectively
(hypothesis tests) below:
c)Interpret the coefficientof determinationbelow:
d)Interpret the coefficients of MALE, EDU3, and EXPbelow

Added by David S.

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