Consider the example in class, where we have data on workers Earning, College diploma and Gender....
Consider the example in class, where we have data on workers Earning, College diploma and Gender. And the model is specified as:
Earning=β0 +β1C+β2G+β3(C·G)+u
where the model satisfies the 4 assumptions. And C=1 if the worker has college education, G=1 if the worker is female.
(1) What is the average earning difference between male workers who has a college diploma and who has not a college diploma.(Hint: E(Earning|C = 1, G = 0) − E(Earning|C = 0,G = 0))
(2) What is the average earning difference between female workers who has a college diploma and who has not a college diploma.(Hint: E(Earning|C = 1, G = 1) − E(Earning|C = 0,G = 1))
(3) What is the average earning difference between male worker who has a college diploma and female worker who also has a college diploma.(Hint: E(Earning|C = 1, G = 0) − E(Earning|C = 1, G = 1))
(4) What is the average earning difference between male worker who has no college diploma and female worker who also has no college diploma.(Hint: E(Earning|C = 0, G = 0) − E(Earning|C = 0, G = 1))
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Consider the example in class, where we have data on workers
Earning, College diploma and Gender....
Consider the example in class, where we have data on workers Earning, Schooling years and Gender....
Consider the example in class, where we have data on workers Earning, Schooling years and Gender. And the model is specified as: Earning = β0 + β1Schooling + β2G + u where the model satisfies the 4 assumptions. And G=1 if the worker is female. (1) Interpret the effect of schooling years on male worker’s earning. (Hint: E(Earning|G = 0)) (2) Interpret the effect of schooling years on female worker’s earning.
You are a male who just graduated from college with a bachelor's degree You have a job paying $50,780.00/yr. a....
You are a male who just graduated from college with a bachelor's degree You have a job paying $50,780.00/yr. a. How does your salary compare to the yearly median earnings for a male with a bachelor's degree? b. What is the difference between the yearly median earnings for a male with a bachelor's degree compared to a male who does not attend college after earning a high school diploma? Be sure to include in your response: e the answer to...
The data set consists of information on 3700 full-time full-year workers. The highest educational achievement for...
The data set consists of information on 3700 full-time full-year workers. The highest educational achievement for each worker was either a high school diploma or a bachelor's degree. The worker's ages ranged from 25 to 45 years. The data set also contained information on the region of the country where the person lived, marital status, and number of children. For the purposes of these exercises, let AHE = average hourly earnings (in 2005 dollars) College = binary variable (1 if...
The data set consists of information on 4900 full-time full-year workers. The highest educational achievement for...
The data set consists of information on 4900 full-time full-year workers. The highest educational achievement for each worker was either a high school diploma or a bachelor's degree. The worker's ages ranged from 25 to 45 years. The data set also contained information on the region of the country where the person lived, marital status, and number of children. For the purposes of these exercises, let AHE = average hourly earnings (in 2005 dollars) College = binary variable (1 if...
Table 1: 2012 Current Population Survey Data Dependent Variable: Av Hourly Eaming 8.31 0.2 3.85 0.2...
Table 1: 2012 Current Population Survey Data Dependent Variable: Av Hourly Eaming 8.31 0.2 3.85 0.2 8.34 8.32 0.22 3.81 0.22 0.51 0.04 College (X) Female (X2) Age (X3) Northeast (x) Midwest (L.) South (Xs) Intercept 3.80 0.52 04 0.18 36 1.23 31 0.43 30 2.05 17.02 1.87 Forthis question, refer to the table of estimated regressions in Table 1, computed using data from the 2012 CPS. The dataset contains information on 7,440 full-time, full-year workers. The highest educational achievement...
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QUESTION 5 Suppose that a researcher, using wage data on 250 randomly selected male workers and 280 female workers, estimates the OLS regression: Wage 12.52 + 2.12 x Male, R2 0.06, SER 4.2 (0.23) (0.36) where Wage is measured in dollars per hour and Male is a binary variable that is equal to 1 if the person is a male and O if the person is a female. Define the wage gender gap as the difference in the mean earnings...
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Suppose that we have data on ECON 333 test scores (Yi), duration for which student i studies for exam (Xi), and the major of the student, call it Di, where Di =( 1, if economics major 0, if non economics major Consider the following model: Yi = β0 + β1Xi + β2Di + β3DiXi + ui (1) where Assumption 1 holds: E (ui|Xi,Di) = 0. (2) Yi is the score between 0 and 100. Xi is the duration studied in...
(7.1b-e) Suppose we are able to collect a random sample of data on economics majors at...
(7.1b-e) Suppose we are able to collect a random sample of data on economics majors at a large university. Further suppose that, for those entering the workforce, we observe their employment status and salary 5 years after graduation. Let SAL S salary for those employed, GPA grade point average on a 4.0 scale during their undergraduate program, with METRICS- 1 if student took econometrics, METRICS0 otherwise. Assuming β2 and β3 are positive, draw a sketch of E(SALGPA, METRICS) β2GPA-BMETRICS. a....
The data set consists of information on 3800 full-time fll-erworkers. The highest educational achievement for each...
The data set consists of information on 3800 full-time fll-erworkers. The highest educational achievement for each worker was either a high school diploma or a bachelors degree. The workers ages ranged from 25 to 45 years. The data set also contained information on the region of the country where the person lived, marital status, and number of children. For the purposes of these exercises, let AHEaverage hourly earnings (in 2005 dollars) Collegebinary variable (1 if college, O if high school)...
Suppose we are working on the same data set. Two multiple linear regressions have been done...
Suppose we are working on the same data set. Two multiple linear regressions have been done with following Printout, where “ “ means blank space. Analysis of Variance Table 1 Response: y Df Sum Sq Mean Sq F value Pr(>F) x1 1 --------- ---------- -------- ------------- *** x2 1 80.206 80.206 17.892 0.0001474 *** Residuals 37 165.864 4.483 Analysis of Variance Table 2 Response: y Df Sum Sq Mean Sq F...
You are a male who just graduated from college with a bachelor's degree You have a job paying $50,780.00/yr. a. How does your salary compare to the yearly median earnings for a male with a bachelor's degree? b. What is the difference between the yearly median earnings for a male with a bachelor's degree compared to a male who does not attend college after earning a high school diploma? Be sure to include in your response: e the answer to...
The data set consists of information on 3700 full-time full-year workers. The highest educational achievement for each worker was either a high school diploma or a bachelor's degree. The worker's ages ranged from 25 to 45 years. The data set also contained information on the region of the country where the person lived, marital status, and number of children. For the purposes of these exercises, let AHE = average hourly earnings (in 2005 dollars) College = binary variable (1 if...
The data set consists of information on 4900 full-time full-year workers. The highest educational achievement for each worker was either a high school diploma or a bachelor's degree. The worker's ages ranged from 25 to 45 years. The data set also contained information on the region of the country where the person lived, marital status, and number of children. For the purposes of these exercises, let AHE = average hourly earnings (in 2005 dollars) College = binary variable (1 if...
Table 1: 2012 Current Population Survey Data Dependent Variable: Av Hourly Eaming 8.31 0.2 3.85 0.2 8.34 8.32 0.22 3.81 0.22 0.51 0.04 College (X) Female (X2) Age (X3) Northeast (x) Midwest (L.) South (Xs) Intercept 3.80 0.52 04 0.18 36 1.23 31 0.43 30 2.05 17.02 1.87 Forthis question, refer to the table of estimated regressions in Table 1, computed using data from the 2012 CPS. The dataset contains information on 7,440 full-time, full-year workers. The highest educational achievement...
QUESTION 5 Suppose that a researcher, using wage data on 250 randomly selected male workers and 280 female workers, estimates the OLS regression: Wage 12.52 + 2.12 x Male, R2 0.06, SER 4.2 (0.23) (0.36) where Wage is measured in dollars per hour and Male is a binary variable that is equal to 1 if the person is a male and O if the person is a female. Define the wage gender gap as the difference in the mean earnings...
(7.1b-e) Suppose we are able to collect a random sample of data on economics majors at a large university. Further suppose that, for those entering the workforce, we observe their employment status and salary 5 years after graduation. Let SAL S salary for those employed, GPA grade point average on a 4.0 scale during their undergraduate program, with METRICS- 1 if student took econometrics, METRICS0 otherwise. Assuming β2 and β3 are positive, draw a sketch of E(SALGPA, METRICS) β2GPA-BMETRICS. a....
The data set consists of information on 3800 full-time fll-erworkers. The highest educational achievement for each worker was either a high school diploma or a bachelors degree. The workers ages ranged from 25 to 45 years. The data set also contained information on the region of the country where the person lived, marital status, and number of children. For the purposes of these exercises, let AHEaverage hourly earnings (in 2005 dollars) Collegebinary variable (1 if college, O if high school)...
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