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Assignment #1
ECON 323: Econometric Analysis 2 - Winter 2020
Due January 23, 2020, 10am in class
Instructions: While cooperating on the assignment is encouraged, plagiarism
is not. I will only accept hand written assignment submitted in
person. DO NOT SUBMIT YOUR ASSIGNMENT ELECTRONICALLY.
No late assignment will be accepted; late assignments (after 8:30am on the
due date) will receive a mark of zero. Show your work as no marks will be
allocated for the final answer alone.
Use Stata or R to do these. If you choose to use another software, please
get my approval at least a week before the assignment is due.
Question 1
Using the Retirement Survey 1975 available from Odesi, answer the following
questions.
(a) Regress whether the indivdidual receives a pension from their employer
(consider this to be a continuous and normally distributed variable for
the purposes of this question at this stage) on marital status, the province of
residence, gender and the age the individual was when they left their longest
employer . Report your results in equation form.
(b) Together, how much of the variation in marital status and procvince
of residence explain?
(c) If an observation in the sample is such that the individual is a married
female that lives in quebec and stayed with their longest ever employer until
the age of 65, what is the predicted probability that they receive a pension
from an employer?
(d) This individual receives a pension. Calculate the residual.
(e) Perform a t-test of the equality of the coefficient of age to 0.01 at 5%
of statistical significance.
(f) Should you include gender and age in your regression? Discuss.
(g) Is heteroskedasticity present in this model?
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(h) Now treat whether individuals have a pension from their employer as
the type of variable it should be and go back to assuming homoskedasticity,
regardless of your results in (g). Repeat questions (a), (e), and (f) using
the correct estimation method and report the “new answers”. Has anything
changed? Why?
(i) What is the average marginal effect for age at which they left their
longest employer in this regression? Why should you consider the AME
rather than the coefficient in this situation?
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