4. The STATA output below uses the Educational Attainment and Wage Equations (EAWE) data similar to what we have investigated in class: reg EARNINGS S FEMALE ASVABC ETHHISP ETHWHITE MARRIED EXP TENURE 500 Source | df Number of obs SS MS omitted F (8, 491) Model | 11567.0578 8. omitted Prob > F omitted omitted Residual 55379.8233 491 R-squared Adj R-squared 0.1728 0.1593 Total | 10.62 66946.8811 499 134.162086 Root MSE P> |t| EARNINGS | Std. Err. [95% Conf. Interval] Coef. 5.13 1.282268 .2499762 0.000 .7911128 1.773423 0.012 -.5480824 3.428481 FEMALE | ASVABC | -2.457466 .9717918 -2.53 -4.36685 2.206915 .6217233 3.55 0.000 .9853484 1.985396 0.685 3.094036 ETHHISP -.8068838 -0.41 -4.707804 ETHWHITE | MARRIED | 1.670643 -0.98 0.329 -1.63153 -4.91402 1.650961 1.720857 .9850864 1.75 0.081 -.2146475 3.656362 . 4396207 EXP | 3.99 .8659335 .2169744 0.000 1.292246 .3597575 .1895722 1.90 0.058 -.0127153 .7322303 TENURE -6.210424 2.704951 4.537532 -1.37 0.172 -15.1258 cons Assume the true model of the relationship is EARNINGS = ß1 + B2S + B3FEMALE + B4ASV ABC + В-ЕТНHISP + BsЕТHWHITE + B-MARRIED + B3EXP + B9TENURE + u where EARNINGS is hourly earnings in dollars, S is years of schooling, FEMALE is a dummy variable for women, ASVABC is a measure of cognitive ability, ETHHISP is a dummy for Hispanic people, ETHWHITE is a dummy for White people, MARRIED is a dummy variable for the married, EXP is of job experience after the graduation, and TENURE is years after one's job was tenured. (to.05,491 years = 1.6479629 to.025,491 1.9648027, and Fo.05(8, 491) = 1.9572532) Interpret the estimated coefficients. (Answer briefly) Based on the regression output above, are there any differences in hourly earnings by race? Based on the regression output above, are there any differences in hourly earnings by gender? Test the overall significance of the regression model at the 5% level of significance. Define the relevant hypotheses and compute the F-statistic for the test. What would be the conclusion of the test? Explain the result. How do you check the heteroskedasticity? Explain the relevant test procedure with the model above. (a) (b) (c) (d) (e) (f) Assume that you detected the heteroskedasticity from the given regression model. How can you possibly resolve the problem? Explain.

4. The STATA output below uses the Educational Attainment and Wage Equations (EAWE) data similar to what we have investigated in class: reg EARNINGS S FEMALE ASVABC ETHHISP ETHWHITE MARRIED EXP TENURE 500 Source | df Number of obs SS MS omitted F (8, 491) Model | 11567.0578 8. omitted Prob > F omitted omitted Residual 55379.8233 491 R-squared Adj R-squared 0.1728 0.1593 Total | 10.62 66946.8811 499 134.162086 Root MSE P> |t| EARNINGS | Std. Err. [95% Conf. Interval] Coef. 5.13 1.282268 .2499762 0.000 .7911128 1.773423 0.012 -.5480824 3.428481 FEMALE | ASVABC | -2.457466 .9717918 -2.53 -4.36685 2.206915 .6217233 3.55 0.000 .9853484 1.985396 0.685 3.094036 ETHHISP -.8068838 -0.41 -4.707804 ETHWHITE | MARRIED | 1.670643 -0.98 0.329 -1.63153 -4.91402 1.650961 1.720857 .9850864 1.75 0.081 -.2146475 3.656362 . 4396207 EXP | 3.99 .8659335 .2169744 0.000 1.292246 .3597575 .1895722 1.90 0.058 -.0127153 .7322303 TENURE -6.210424 2.704951 4.537532 -1.37 0.172 -15.1258 cons Assume the true model of the relationship is EARNINGS = ß1 + B2S + B3FEMALE + B4ASV ABC + В-ЕТНHISP + BsЕТHWHITE + B-MARRIED + B3EXP + B9TENURE + u where EARNINGS is hourly earnings in dollars, S is years of schooling, FEMALE is a dummy variable for women, ASVABC is a measure of cognitive ability, ETHHISP is a dummy for Hispanic people, ETHWHITE is a dummy for White people, MARRIED is a dummy variable for the married, EXP is of job experience after the graduation, and TENURE is years after one's job was tenured. (to.05,491 years = 1.6479629 to.025,491 1.9648027, and Fo.05(8, 491) = 1.9572532) Interpret the estimated coefficients. (Answer briefly) Based on the regression output above, are there any differences in hourly earnings by race? Based on the regression output above, are there any differences in hourly earnings by gender? Test the overall significance of the regression model at the 5% level of significance. Define the relevant hypotheses and compute the F-statistic for the test. What would be the conclusion of the test? Explain the result. How do you check the heteroskedasticity? Explain the relevant test procedure with the model above. (a) (b) (c) (d) (e) (f) Assume that you detected the heteroskedasticity from the given regression model. How can you possibly resolve the problem? Explain.

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter10: Statistics

Section10.3: Measures Of Spread

Problem 1GP

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