Applied Econometrics

Important Announcements/News

• Feb. 15: I added a simple example of Maximum Likelihood Estimation problem in the readings below.
• Feb. 9: I have put online a paper that we will cover in class once we get back from the reading week. Please read it.
• Feb. 8: Revised slides for week five are now availlable below. I have made some changes regarding the ADF test. We will cover this during next week's tutorial.
• Feb. 7: My office hours changed from thursdays after class to tuesdays after class (11h30 to 13h00). Feel free to send me an email anytime, though.
• Jan. 17: Revised slides for week 2 are availlable below. Some minor errors were corrected. I have also added stars (*) to persons without partners in the page about groups. This might help if you are still looking for a partner.
• Jan. 16: The department's dropboxes are actually open until 15:00 for homeworks. All homeworks deposited after this time will be placed in a recycle bin after this hour.
• Jan. 12: Groups for laboratories have been made. You can look at the list here (with some likely misspell of your name).
• Jan. 11: I have put online some revised notes for week one. Tomorrow morning, I ask for your preferences regarding laboratories groups.
• Jan. 10: I have heard of only one conflict for holding tutorials on wednesdays 10:00. Since the group will be split in two, we will keep this period. (Note that there is no tutorial session this week.)
• Jan. 10: The homework and reports should be submitted in the drop-boxes on the second floor of Dunning. Keep in mind that the building/drop-boxes is/are open from 8:30 to 15:00, so you should plan accordingly.
• Jan. 9: Both the homework and the first set of lecture notes are availlable online.
• Jan. 3: Students can choose to work in pairs for their reports. The group is likely to be split in two for teaching laboratory sessions. Students willing to do so should thus rapidly find a partner so they can be in the same session.
• Jan. 3: The Syllabus is now availlable below.

Syllabus

This course is intended for persons willing to perform meaningful time series analysis after they graduate. The semester will be divided in two periods. In the first one, there will be classes about the theory of time series as well as applied examples. Tutorials will cover an introduction to a statistical software. In the second period, Students will have to apply theory to a project of their own (and there will thus be no formal classes).

There will be no midterm or final exam. Most of the grades will be given according to a final essay based on students projects as well as an intermediary report. Some additional grades for class attendance and an homework will be given.

Course Slides

1. Week one (revised).
2. Week two (revised).
3. Week three.
4. Week four (and perhaps five, depending on how it goes).
5. Week five (revised).
6. Week six.
7. (reading week).
8. A paper that we will discuss in week 8 and some lecture notes.

Laboratories Files

1. First laboratory: an introduction to Stata. (Note that ".do" files can be opened with any text editor.)
2. Second laboratory: (first do-file), (second do-file).
3. Third laboratory: use the dataset for tutorial 3 below. My do-file and my log-file (pabsta).
4. Fourth laboratory: some discussions about what should be in a report.
5. Fifth laboratory: we will deal with stationarity issues on the GDP and the CPI/TSX datasets (below): do-file for the GDP (pabsta), do-file for the TSX.
6. Sixth Laboratory: Forecasting, building nice graphs and nice tables.

Homework (due March 9th)

Some Datasets Used

1. Dataset for question 2 of the homework.
2. An AR(1) process: someAR1.dta.
3. Canadian Business Cycles (.csv file)
4. Dataset for the second part of tutorial 2.
5. Dataset for tutorial 3.
6. Consumer Price Index Dataset, monthly.
7. Seasonally Adjusted Gross Domestic Product, quarterly.
8. Toronto Stock Exchange, Closing Value, Monthly Average

Some Useful Readings

• Princeton DSS help file about Stata.
• A nice (but incomplete) introduction to Stata.
• Stata's time-series manual.
• How to read Stata's output from the command regress (file taken from M. Abbott's webpage).
• Major steps for writing an empirical research report (file taken from M. Abbott's webpage).
• Some possible signs of overdifferencing.
• Writing Tips for PhD Students (and you!)
• Screenshot of Stata being unable to compute any estimate.
• A great overview of prediction commands with Stata.
• A great webpage about graphs in Stata.
• An example of a report paper.
• A Simple Example Of Maximum Likelihood Estimation

Copyright of Course Material

The material on this webpage is copyrighted and is for the sole use of students registered in ECON452 at Queen's University. The material on this webpage may be downloaded for a registered student’s personal use, but shall not be distributed or disseminated to anyone other than students registered in ECON452 at Queen's University. Failure to abide by these conditions is a breach of copyright, and may also constitute a breach of academic integrity under the University Senate’s Academic Integrity Policy Statement.