To better examine the factors affecting a person's wage, you control for the following additional individual...

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To better examine the factors affecting a person's wage, you control for the following additional individual characteristics: Female (fem,): binary variable (=1 if individual is female, =0 otherwise). Experience (exp): years of labour market experience. Tenure (ten,): years with their current employer. You estimate the model using the natural logarithm of hourly wages (Inwage,) as the dependent variable, as well as adding a quadratic of exp, and an interaction between ten, and fem,. You obtain the following results (standard errors are reported in parentheses): Inwage, = 0.42 + 0.08educ, (0.10) (0.01) 0.30fem, + 0.03exp,-0.0006exp? + 0. 03ten, + (0.0001) %3D (0.04) (0.005) (0.007) [3] + 0.0006ten, fem, (0.0002) R?=0.44 32. Please interpret the estimated model reported in equation [3]. [40 points] You also performed a Breusch-Pagan/Cook-Weisberg test for heteroskedasticity and Ramsey's RESET test for functional misspecification on the estimations presented in equation [3]. The results of these tests are presented below: Breusch-Pagan/Cook-Weisberg test for heteroskedasticity Ho: Constant variance Variables: fitted values of Inwage Chi2(1) %3D 150.15 Prob>chi2 = 0.0000 Ramsey RESET test using powers of the fitted values of Inwage Ho: Model has no omitted variables F(3, 3139) Prob > F 5.25 0.00 %3D %3D Briefly explain the intuition behind the tests for heteroskedasticity and functional misspecification. What can you conclude based on the test results? Please provide potential solutions to any problems you identify. Is there any other test(s) you would perform on the estimations presented in equation [3]? 33. [20 points] To better examine the factors affecting a person's wage, you control for the following additional individual characteristics: Female (fem,): binary variable (=1 if individual is female, =0 otherwise). Experience (exp): years of labour market experience. Tenure (ten,): years with their current employer. You estimate the model using the natural logarithm of hourly wages (Inwage,) as the dependent variable, as well as adding a quadratic of exp, and an interaction between ten, and fem,. You obtain the following results (standard errors are reported in parentheses): Inwage, = 0.42 + 0.08educ, (0.10) (0.01) 0.30fem, + 0.03exp,-0.0006exp? + 0. 03ten, + (0.0001) %3D (0.04) (0.005) (0.007) [3] + 0.0006ten, fem, (0.0002) R?=0.44 32. Please interpret the estimated model reported in equation [3]. [40 points] You also performed a Breusch-Pagan/Cook-Weisberg test for heteroskedasticity and Ramsey's RESET test for functional misspecification on the estimations presented in equation [3]. The results of these tests are presented below: Breusch-Pagan/Cook-Weisberg test for heteroskedasticity Ho: Constant variance Variables: fitted values of Inwage Chi2(1) %3D 150.15 Prob>chi2 = 0.0000 Ramsey RESET test using powers of the fitted values of Inwage Ho: Model has no omitted variables F(3, 3139) Prob > F 5.25 0.00 %3D %3D Briefly explain the intuition behind the tests for heteroskedasticity and functional misspecification. What can you conclude based on the test results? Please provide potential solutions to any problems you identify. Is there any other test(s) you would perform on the estimations presented in equation [3]? 33. [20 points] To better examine the factors affecting a person's wage, you control for the following additional individual characteristics: Female (fem,): binary variable (=1 if individual is female, =0 otherwise). Experience (exp): years of labour market experience. Tenure (ten,): years with their current employer. You estimate the model using the natural logarithm of hourly wages (Inwage,) as the dependent variable, as well as adding a quadratic of exp, and an interaction between ten, and fem,. You obtain the following results (standard errors are reported in parentheses): Inwage, = 0.42 + 0.08educ, (0.10) (0.01) 0.30fem, + 0.03exp,-0.0006exp? + 0. 03ten, + (0.0001) %3D (0.04) (0.005) (0.007) [3] + 0.0006ten, fem, (0.0002) R?=0.44 32. Please interpret the estimated model reported in equation [3]. [40 points] You also performed a Breusch-Pagan/Cook-Weisberg test for heteroskedasticity and Ramsey's RESET test for functional misspecification on the estimations presented in equation [3]. The results of these tests are presented below: Breusch-Pagan/Cook-Weisberg test for heteroskedasticity Ho: Constant variance Variables: fitted values of Inwage Chi2(1) %3D 150.15 Prob>chi2 = 0.0000 Ramsey RESET test using powers of the fitted values of Inwage Ho: Model has no omitted variables F(3, 3139) Prob > F 5.25 0.00 %3D %3D Briefly explain the intuition behind the tests for heteroskedasticity and functional misspecification. What can you conclude based on the test results? Please provide potential solutions to any problems you identify. Is there any other test(s) you would perform on the estimations presented in equation [3]? 33. [20 points] To better examine the factors affecting a person's wage, you control for the following additional individual characteristics: Female (fem,): binary variable (=1 if individual is female, =0 otherwise). Experience (exp): years of labour market experience. Tenure (ten,): years with their current employer. You estimate the model using the natural logarithm of hourly wages (Inwage,) as the dependent variable, as well as adding a quadratic of exp, and an interaction between ten, and fem,. You obtain the following results (standard errors are reported in parentheses): Inwage, = 0.42 + 0.08educ, (0.10) (0.01) 0.30fem, + 0.03exp,-0.0006exp? + 0. 03ten, + (0.0001) %3D (0.04) (0.005) (0.007) [3] + 0.0006ten, fem, (0.0002) R?=0.44 32. Please interpret the estimated model reported in equation [3]. [40 points] You also performed a Breusch-Pagan/Cook-Weisberg test for heteroskedasticity and Ramsey's RESET test for functional misspecification on the estimations presented in equation [3]. The results of these tests are presented below: Breusch-Pagan/Cook-Weisberg test for heteroskedasticity Ho: Constant variance Variables: fitted values of Inwage Chi2(1) %3D 150.15 Prob>chi2 = 0.0000 Ramsey RESET test using powers of the fitted values of Inwage Ho: Model has no omitted variables F(3, 3139) Prob > F 5.25 0.00 %3D %3D Briefly explain the intuition behind the tests for heteroskedasticity and functional misspecification. What can you conclude based on the test results? Please provide potential solutions to any problems you identify. Is there any other test(s) you would perform on the estimations presented in equation [3]? 33. [20 points]

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32 As we can see from the estimated model education experience tenure and tenurefem have a positive ... View the full answer