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Assignment
ECON 323: Econometric Analysis
Instructions: While cooperating on the assignment is encouraged, pla-
giarism is not. I will only accept hand written assignment submitted in
person. DO NOT SUBMIT YOUR ASSIGNMENT ELECTRONICALLY.
Late assignments will receive a 10% penalty per day that it is late, up to
the time that it is corrected in class, after which they will receive a mark
of zero. Show your work as no marks will be allocated for the final an-
swer alone. For the intermediate deadlines, the weight will be transferred
to the final submission upon the upload of a vif to VIF.uwaterloo.ca or the
self-declaration of an absence. No late assignments will be accepted for the
intermediate deadlines.
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
Use the following series available on Statistics Canada’s website except
where specified otherwise. Use all series for Canada as a whole using a
monthly frequency.
• New motor vehicle sales, units, unadjusted (Table: 20-10-0001-01)
• Consumer Price Index, all items, (Table: 18-10-0004-01)
1
• Residential Mortgage loans held in charter banks (Table: 36-10-0639-
01)
• Population, 15+ y o (Table: 14-10-0017-01)
Use the longest common time period available to do the assignment, but
only collect data up to and including October 2023.
(a) Report the summary statistics for the series mentioned above. Graph
them and report all results.
(b) Calculate the inflation rate and report summary statistics for the
series.
(c) Should you seasonally adjust your series? Why or why not? If you
think that you should, calculate the new series and report their summary
statistics.
(d) Regress the number of new cars sold on the residential mortgage
loans, population and the inflation rate. Report and interpret your results.
(e) Should you control for trends? Justify and modify your answers in
(d) as you see fit.
(f) Introduce a lag of your dependent variable in your model. Why did
you do this? What can you conclude from your results?
(g) How many lags do you think would be optimal? Using methods
covered in class, test your hypothesis.
(h) Is serial correlation of the errors present in this model? Use two
tests for different lag orders to determine this and only include 1 lag of the
dependent variable in your model.
(i) How can you correct for serial correlation of the errors of order 1?
Either do it if you found that it existed in the previous question and discuss
the change in your results or explain how it would affect your results if it
had been present and why you think that it isn’t in your model.