The first question refers to the table above of estimated regressions from S&W, computed using data on employees. The data set consists of information on over 10000 full-time, full-year workers. The highest educational achievement for each worker was either a high school diploma or a bachelor’s degree. The workers’ ages ranged from 25 to 40 years. The data set also contains information on the region of the country where the person lived, and the individual’s gender and age. For the purposes of these exercises, let
AWE = logarithm of average weekly earnings (in 2007 units)
High school = binary variable (1 if High school, 0 if less)
Male = binary variable (1 if male, 0 if female)
Age = age (in years)
North = binary variable (1 if Region = North, 0 otherwise)
East = binary variable (1 if Region = East, 0 otherwise)
South = binary variable (1 if Region = South, 0 otherwise)
West = binary variable (1 if Region = West, 0 otherwise)
Exercise 1.1
For each of the three regressions, add * (5% level) and ** (1% level) to the table to indicate the statistical significance of the coefficients.
Exercise 1.2 Use the regression results in column (1):
a) Is the college-high school earnings difference estimated from this regression statistically significant at the 5% level? Construct a 95% confidence interval of the difference.
b) Is the male-female earnings difference statistically significant at the 5% level? Construct a 95% confidence interval for the difference.
Exercise 1.3 Using the regression results in column (2):
a) Is age an important determinant of earnings? Use an appropriate statistical test and/or confidence interval to explain your answer.
b) Suppose Alvo is a 30-year-old male college graduate, and Kal is a 40-year-old male college graduate. Construct a 95% confidence interval for the expected difference between their earnings.
Exercise 1.4 Using the regression results in column (3):
a) Are there any important regional differences? Use an appropriate hypothesis test to explain your answer.
b) Juan is a 32-year-old male college graduate from the North. Mel is a 32-year-old male college graduate from the West. Ari is a 32-year-old male college graduate from the East.
(i) Construct a 95% confidence interval for the difference in expected earnings between Juan and Mel.
(ii) Explain how you would construct a 95% confidence interval for the difference in expected earnings between Juan and Ari. (Hint: What would happen if you included West and excluded East from the regression?)
Exercise 1.5
In all of the regressions in the previous Exercises, the coefficient of male is positive, large, and statistically significant. Do you believe this provides strong statistical evidence of gender discrimination?
QUESTION TWO
The data file TeachingRatings contains data on course evaluations, course characteristics and professor characteristics for 463 courses at the University of Texas at Austin. A detailed description is given in TeachingRatings_Description. One of the characteristics is an index of the professor’s “beauty” as rated by a panel of six judges. In this exercise, you will investigate how course evaluations are related to the professor’s beauty. In all regressions use the robust option.
a. Run a regression of average course evaluations (Course_Eval) on the professor’s beauty (Beauty).
b. Run a regression of Course_Eval on Beauty, including some additional variables to control for the type of course and professor characteristics: Intro, OneCredit, Female, Minority, and NNEnglish. Would you conclude that the regression in a. suffers from important omitted variable bias?
QUESTION THREE
The data file CollegeDistance contains data from a random sample of high school seniors interviewed in 1980 and re-interviewed in 1986. In this exercise, you will use the data to investigate the relationship between the number of completed years of education for young adults and the distance from each student’s high school to the nearest four-year college. (Proximity to college lowers the cost of education, so that students who live closer to a four-year college should, on average, complete more years of higher education. It is assumed that students go to a high school close to their home.) A detailed description of the data is given in CollegeDistance_Description. In all regressions use the robust option.
a. Run a regression of years of completed education (ED) on distance to the nearest college (Dist), where Dist is measured in tens of miles.
b. Run a regression of ED on Dist and some additional regressors to control for the characteristics of the student, the student’s family, and the local labour market: Bytest, Female, Black, Hispanic, Incomehi, Ownhome, DadColl, MomColl, Cue80 and Stwnfg80. What is the estimated effect of Dist on ED?
c. Comparing the results of a. and b., does a. suffer from omitted variable bias?
d. What does the coefficient on DadColl measure? Is the positive sign expected?
e. Explain why Cue80 and Stwnfg80 appear in the regression? Are their signs expected? Interpret the magnitude of the coefficients.
f. Bob is a black male. His high school was 20 miles from the nearest college. His base-year composite test score (Bytest) was 58. His family income in 1980 was $26000, and his family owned a home. His mother attended college, but his father did not. The unemployment rate in his county was 7.5%, and the state average manufacturing hourly wage was $9.75. Predict Bob’s years of completed schooling using the regression in b.
g. “Controlling for other factors, blacks and Hispanics complete more college than whites”. Is this statement consistent with the results in b.?
CS 340 Milestone One Guidelines and Rubric Overview: For this assignment, you will implement the fundamental operations of create, read, update,
Retail Transaction Programming Project Project Requirements: Develop a program to emulate a purchase transaction at a retail store. This
7COM1028 Secure Systems Programming Referral Coursework: Secure
Create a GUI program that:Accepts the following from a user:Item NameItem QuantityItem PriceAllows the user to create a file to store the sales receip
CS 340 Final Project Guidelines and Rubric Overview The final project will encompass developing a web service using a software stack and impleme
