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 education and 0 otherwise,EDU2=1 if the worker has primary education and 0 otherwise, EDU3=1 if the workerhas 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 (thenumber of years being employed).Dependent Variable: WMethod: Least SquaresDate: 01/02/21 Time: 09:15Sample: 1 935Included observations: 935Variable Coefficient Std. Error t-Statistic Prob.C 508.7969 49.56471 10.26531 0.0000MALE 486.2831 20.27897 23.97967 0.0000EDU2 37.93184 35.58875 1.065838 0.2868EDU3 153.9977 40.51264 3.801225 0.0002EDU4 251.2214 40.92353 6.138799 0.0000EXP 10.28997 2.548076 4.038331 0.0001R-squared 0.461610 Mean dependent var 957.9455Adjusted R-squared 0.458713 S.D. dependent var 404.3608S.E. of regression 297.4973 Akaike info criterion 14.23508Sum squared resid 82220789 Schwarz criterion 14.26615Log likelihood -6648.902 Hannan-Quinn criter. 14.24693F-statistic 159.3033 Durbin-Watson stat 0.446774Prob(F-statistic) 0.000000a) 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: 6c) Interpret the coefficient of determination below: d) Interpret the coefficients of MALE, EDU3, and EXP below:

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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 education and 0 otherwise,EDU2=1 if the worker has primary education and 0 otherwise, EDU3=1 if the workerhas 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 (thenumber of years being employed).Dependent Variable: WMethod: Least SquaresDate: 01/02/21 Time: 09:15Sample: 1 935Included observations: 935Variable Coefficient Std. Error t-Statistic Prob.C 508.7969 49.56471 10.26531 0.0000MALE 486.2831 20.27897 23.97967 0.0000EDU2 37.93184 35.58875 1.065838 0.2868EDU3 153.9977 40.51264 3.801225 0.0002EDU4 251.2214 40.92353 6.138799 0.0000EXP 10.28997 2.548076 4.038331 0.0001R-squared 0.461610 Mean dependent var 957.9455Adjusted R-squared 0.458713 S.D. dependent var 404.3608S.E. of regression 297.4973 Akaike info criterion 14.23508Sum squared resid 82220789 Schwarz criterion 14.26615Log likelihood -6648.902 Hannan-Quinn criter. 14.24693F-statistic 159.3033 Durbin-Watson stat 0.446774Prob(F-statistic) 0.000000a) 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: 6c) Interpret the coefficient of determination below: d) Interpret the coefficients of MALE, EDU3, and EXP below:

Posavkah6qnsz · Accepted Answer

a)From the given output the estimated wag model is given asWeekly wage = 508.8 + 486.3 Male + 37.9 (EDU32) + 154.0 (EDU3) + 251.2 (EDU4) + 10.3 (EXP)b)Significance test for variable EXPHypothesis:      H    0    :      β          E      x      p        =  0        H    1    :      β          E      x      p        ≠  0From the output p-value=0.0001Decision rule:If the p-value is greater than the significance level, there is no evidence to reject the null hypothesis.If the p-value is lesser than the significance level, the hypothesis is rejected.Conclusion:The p-value (0.0001) is less than the significance (0.05)Thus, the null hypothesis is rejected.There is a relation between the experience of the worker and the weekly wages.Thus, the variable Exp is significant at a 5% level of significance.Significance test for variable EDU2 Hypothesis:      H    0    :      β          E      d      u      2        =  0        H    1    :      β          E      d      u      2        ≠  0From the output p-value=0.2868Decision rule:If the p-value is greater than the significance level, there is no evidence to reject the null hypothesis.If the p-value is lesser than the significance level, the hypothesis is rejected.Conclusion:The p-value (0.2868) is greater than the significance (0.05)Thus, there is no evidence to reject the null hypothesis.There is no relation between the primary education of the worker and the weekly wages.Thus, the variable EDU2  is not significant at a 5% level of significance.c)From the given output coefficient of determination R-squared = 0.461610.This means that 46% variation in the dependent variable is explained by the independent variable.46% of the data fit the regression model.The strength of the relationship of the model is 46%

giratsozsb · Accepted Answer

d)The coefficient of the male is 486.2831 The positive regression coefficient means that after considering all other variables male have 486.2831  more weekly wages than the female.The coefficient of the EDU3 is 153.9977The positive regression coefficient means that after considering all other variables the worker who has a secondary and high school degree has 486.2831 more weekly wages than the others.The coefficient of the EXP is 10.28997This means that for every unit change in the experience of the worker the mean change in the weekly wages of the worker is 10.28997.The positive coefficient implies that there is a positive correlation between the experience of the worker and the weekly wages of the worker. This means that if the experience of the worker increases the wages of the worker also increases

The following computer output shows an estimated equation. Here; W: Weekly wage. MALE: Gender, ta

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