Assignment 02 (Target CLO 1, 2 & 3)
Fundamentals of Econometrics (ECO-215)BBA 2K22 (Section A &B) BST&H 2k22
All Questions are mandatory to attempt.
Deadline: 19th March 2023
Type all questions in a Word document, upload on LMS, and submit the printed copy to the office
For typesetting, please type in a formal way; learn how to write mathematical expressions. Wrong
expression/typesetting will result in the deduction of marks. Precise contextual should be preferred unless specified.
Do NOT use the plastic file folders, which will also result in the deduction of marks.
Use the appropriate commands on STATA to find the desired outputs, you may import output results screenshots from
STATA.
Answer the following questions.
TASK 1
The median starting salary for new law school graduates is determined by
log(𝑠𝑎𝑙𝑎𝑟𝑦) = 𝛽0 + 𝛽1 𝐿𝑆𝐴𝑇 + 𝛽2 𝐺𝑃𝐴 + 𝛽3 log(𝑙𝑖𝑏𝑣𝑜𝑙) + 𝛽4 log(𝑐𝑜𝑠𝑡) + 𝛽5 𝑟𝑎𝑛𝑘 + 𝑢
where LSAT is the median LSAT score for the graduating class, GPA is the median college GPA for the class, libvol is
the number of volumes in the law school library, cost is the annual cost of attending law school, and rank is a law school
ranking (with rank = 1 being the best)
[i]. Explain why we expect 𝛽5 ≤ 0.
[ii]. What signs do you expect for the other slop parameters? Justify your answers
[iii]. Using the data LAWSCH85, estimate the equation
[iv]. What is the predicted ceteris paribus difference in salary for schools with a median GPA different by one point?
(Report your answer as a percentage.)
[v]. Interpret the coefficient on the variable log(𝑙𝑖𝑏𝑣𝑜𝑙)
[vi]. Would you say it is better to attend a higher ranked law school? How much is a difference in ranking of 20 worth
in terms of predicted starting salary?
TASK 2
In a study relating college grade point average to time spent in various activities, you distribute a survey to several
students. The students are asked how many hours they spend each week in four activities: studying, sleeping, working, and
leisure. Any activity is put into one of the four categories, so that
for each student, the sum of hours in the four activities must be 168.
[i]. In this model,
𝐺𝑃𝐴 = 𝛽0 + 𝛽1 𝑠𝑡𝑢𝑑𝑦 + 𝛽2 𝑠𝑙𝑒𝑒𝑝 + 𝛽3 𝑤𝑜𝑟𝑘 + 𝛽4 𝑙𝑒𝑖𝑢𝑟𝑒 + 𝑢
Does it make sense to keep sleep, work, and leisure fixed while changing your study schedule?
[ii]. Explain why this model violates the assumption of multicollinearity. Give your supported answer.
[iii]. How could you reformulate the model so that its parameters have a useful interpretation and it satisfies
Assumption MLR-4?
TASK 3
Use the data in ATTEND for this exercise.
[i]. Obtain the minimum, maximum, and average values for the variables atndrte, priGPA, and ACT.
[ii]. Estimate the model
𝑎𝑡𝑛𝑑𝑟𝑡𝑒 = 𝛽0 + 𝛽1 𝑝𝑟𝑖𝐺𝑃𝐴 + 𝛽2 𝐴𝐶𝑇 + 𝑢
write the results in equation form. Interpret the intercept. Does it have a useful meaning?
[iii]. Discuss the estimated slope coefficients. Are there any surprises?
[iv]. What is the predicted atndrte if priGPA = 3.65 and ACT = 20? What do you make of this result? Are there any
students in the sample with these values of the explanatory variables?
[v]. If Student A has priGPA = 3.1 and ACT = 21 and Student B has priGPA = 2.1 and ACT = 26, what is the
predicted difference in their attendance rates?
TASK 4
Consider the estimated equation below , which can be used to study the effects of skipping class on college GPA:
[i]. Using the standard normal approximation, find the 95% confidence interval for 𝛽ℎ𝑠𝐺𝑃𝐴 ?
[ii]. Can you reject the hypothesis 𝐻0 : 𝛽ℎ𝑠𝐺𝑃𝐴 = 0.4 against the two-sided alternative at 5% level?
[iii]. Can you reject the hypothesis 𝐻0 : 𝛽ℎ𝑠𝐺𝑃𝐴 = 1 against the two-sided alternative at 5% level?
TASK 5
Use the data in WAGE2 for this exercise
[i]. Consider the standard wage equation
log(𝑤𝑎𝑔𝑒) = 𝛽0 + 𝛽1 𝑒𝑑𝑢𝑐 + 𝛽2 𝑒𝑥𝑝𝑒𝑟 + 𝛽3 𝑡𝑒𝑛𝑢𝑟𝑒 + 𝑢
State the null hypothesis that another year of general workforce experience has the same effect
on log(wage) as another year of tenure with the current employer.
[ii]. Test the null hypothesis in part (i) against a two-sided alternative, at the 5% significance level, by constructing a
95% confidence interval. What do you conclude?