ECON 2220 A Winter 2024
Simon Power
A ssignment 3: Due April 10
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PLEASE BE SURE TO READ THE DOCUMENT ENTITLED“GENERAL ASSIGNMENT
GUIDELINES” BEFORE Y OU BEGIN THIS ASSIGNMENT. ALL REFERENCES ARE TO
THE 7th EDITION OF STUDENMUND. UNLESS SPECIFIED OTHERWISE, USE A 5%
SIGNIFICA NCE LEV EL FOR ALL TESTS. ASSIGNMENTS SHOULD BE SUBMITTED
THROUGH BRIGHTSPACE EITHER ON OR BEFORE THE DUE DATE.
IF IN DOUBT, PROVIDE MORE DETAIL IN Y OUR ANSWERS, RATHER THAN LESS.
NOTE: If a statistical table does not give an entry for the appropriate number(s) of degrees of
freedom, then use the closest number(s) of degrees of freedom available.
1. Professor Loganberry has recently developed a new wage model, which can be stated as
follows:
where the underlying variables are defined as follows:
WAGE =current hourly wage in $
MALE =1 if male, 0 otherwise
MARRIED =1 if married, 0 otherwise
S =years of schooling
AGE =age in years
a) Do you bel i eve that thi s is a good model of wage determination? Caref ul l y expl ai n your
reasoning.
b) Using STATA, together with the A3Q1.dta dataset, estimate the model and then copy and
paste the output into your assignment. Be sure to include ALL your STATA commands in this
output.
c) Using STATA, obtain basic summary statistics for the set of explanatory variables which
appear in the model and then copy and paste the output into your assignment.
d) Using STATA, compute the correlation matrix for the set of explanatory variables which
appear in the model and then copy and paste this correlation matrix into your assignment.
e) Using STATA to run the relevant regressions, calculate the VIFs for this model using the steps
outlined on p. 234 in Section 8.3, together with the formula given in equation (8.16).
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f) Check your answer to part e), by using the STATA vif post-estimation command. Be sure to
copy and paste the relevant output into your assignment.
g) Using Klein’s Rule of Thumb (discussed in footnote 6 on p. 235 in Section 8.3), do any of the
푅2 values from the auxiliary regressions run in part e) suggest the presence of mul ti col l i neari ty?
Expl ai n.
h) Review your answers to parts b), c), d), e), f), and g) and then draw an overall conclusion as to
whether there is any evidence of a significant degree of multicollinearity in the model. Explain.
i) Can you suggest a remedy for the multicollinearity issue, if any, in this model? Explain.
2. Consider the following time-series demand function model for flowers and seeds:
where the variables are defined as follows:
FLOWS =consumer expenditure on flowers and seeds
DPI =aggregate disposable personal i ncome
RPFLOWS =relative price index for flowers and seeds
PCFLOWS =nominal price index for flowers and seeds
PTPE =nominal price index for total personal expenditures
together with the dataset A3Q2.dta, which is available in Brightspace.
a) Using an appropriate set of STA TA commands, estimate this model, and then copy and paste
the output into your assignment. Be sure to include ALL your STATA commands in this output.
NOTE: At the beginning of your STATA program, be sure to tell STA TA that this is a time-
series regression and that “TIME” is the time variable. (See p. 9-1 in Chapter 9 of Using
STA TA : A Practical Gui de.)
b) Using STATA, plot the residuals from your estimated regression equation in a line graph
against TIME. (To produce a line graph in STATA, you can just replace “scatter” with “line” in
the graph command which I discussed in class.) Copy and paste your line graph into your
assignment. Does your graph exhibit any signs of seri al correlation? Explain.
