From UBC Wiki
Jump to: navigation, search
Applied Econometrics
FRE 528
Instructor: Michael Johnson
Juan Fercovic (Course support); Email:
Office: Room: McMl 231
Office Hours: Tuesdays following class for 1 hour (Room: McMl 231)
Class Schedule: Lecture: Tuesday 3:00 to 4:30pm, Thurs 3:00 to 4:30pm

Lab: Thurs 4:30 – 5:30pm

Classroom: Lecture: McMl 154 (Tuesday), Macleod 242 (Thursday)

Lab: Room 192 MacMillan

Important Course Pages
Lecture Notes
Course Discussion

Course Overview

This course will provide the necessary foundations and experience for students to conduct sound empirical research in Food and Resource Economics. The course will review the foundations of data and regression analysis and the common problems encountered by applied researchers (data constraints and econometric challenges) along with potential solutions to these problems. Students will be expected to manipulate data and apply the models presented in class on a weekly basis with assignments and lab sessions. Additionally, students will carry out a team assignment and presentation to further contribute to the understanding and application of applied econometrics.

Course Website:


R. Carter Hill, William E. Griffiths and Guay C. Lim, Principles of Econometrics, Fourth Edition, Wiley, 2011. (This textbook is on course reserve in Koerner Library, reserve collection, 3rd floor, Call Number: HB139 .H548 2011).

A Stata guide for the textbook is also on reserve at the same location: Using Stata for Principles of Econometrics, 4 th edition by Lee C. Adkins and R. Carter Hill.

Required Calculator

Any 2-variable Statistics (Sharp EL 531 or equivalent). Your calculator must be able to perform simple linear regression (least squares method). Programmable calculators are not allowed during examinations.


Assignments 20%
Team Assignment and Presentation 15%
Midterm Exam (Tue Oct 24th) 25%
Final Exam 30%
Participation (Individual and Team-based Exercises): 5%
TBL (Individual and Team-based Exercises): 5%

Makeup Exams or Tests

There will be NO makeup exams or quizzes. If you miss an exam, you will receive zero marks. Exceptions may be made for documented medical reasons or extenuating circumstances. In such a case, it is the responsibility of the student to inform the instructor immediately (not after the exam has taken place). Notification after the examination date is not acceptable.

Team Assignment and Presentation (15%)

Student will be placed in one of ten teams and will be asked to critically review an applied research paper that utilizes econometric modeling. This is a form of mini-research project that is put together and presented to the class. The aim is to understand the integration of theory and the application of econometric models, by examining a research paper(s) that uses a particular econometric modeling technique and sharing it with the entire class. As econometrics is a vast area of research, papers selected for this presentation should focus on ordinary least squares (simple regression or multiple regression) or models using limited dependent variables (logistic/probit/etc models). All papers need to be approved by the instructor at least one week prior to the presentation date. The presentation should summarize, critique and distill the essence of the research paper(s) and the econometric model(s) presented. The format of the presentations should typically be as follows:

  • Duration 20 to 30 minutes, everyone in the group participates.
  • Presentation style is relaxed yet professional.
  • Introduce the research topic, theory or question discussed. The topic should be something of interest to the class in the area of food and resource economics or

another area of interest for the team (sports, finance etc).

  • Discuss the econometric model(s) that was developed or used. Discuss the data source that was used. Explain some of the more important underlying properties of the model and critically analyze any underlying theoretical assumptions of the model (Have the authors provided information to support them? What evidence do they provide? Is information missing? How would you improve the models developed?). Discuss the application and limitations of the model(s) presented.
  • Discuss the results of the study and its implications.
  • Summarize the key learning points of the econometric model and its application for the class.
  • Everyone who is not presenting is expected to have read the journal paper and to come prepared to contribute and ask questions.
  • The class will ask questions and discuss your presentation. The research paper must be provided to Mike via email 1 week prior to the presentation to allow class members the opportunity to read the paper in advance. One day prior to the presentation, the team’s powerpoint slide should be emailed to Mike so he can

post the slides in Canvas. The evaluation of this project will consist of both a team mark, an individual grade and a peer evaluation. The team grade will be based on the information presented (content, clarity, ability to add value to class discussion and its content). The individual grade is based on your individual ability to communicate the details of your paper and answer questions while presenting. After the presentation, a peer evaluation will be provided to all team members to evaluate your contribution to the research project and the presentation. Team presentations will take place during the following weeks:

  • Week 9: Three teams to present
  • Week 13: Seven teams to present

Statistical Software

Both Excel and Stata will be used in this course. Stata will also be demonstrated in this class as an additional econometric software to use. Lecture examples, problem sets and assignments will be presented using either Excel or Stata (or both), depending on the application. Stata can be found in the Buchanan B101 Drop-in Lab, and Buchanan B125/B126 but it is recommended to purchase your own license for $45 online at: Note: If your intention is to take FRE 529 (Econometric Models) in Term 2, you may want to consider purchasing a yearly license.

Attendance: Required

Required Attendance is mandatory at ALL class. The course will be conducted using a Team-Based Learning (TBL) format, to develop both your leadership and team-building skills, while enhancing your learning beyond individual study. Your team will require access to a laptop computer during classes during TBL exercises. “Getting to know you” Written Exercise: Please complete this first exercise and hand it directly to Mike during this week’s class on Thursday. Please bring a hard copy only - not emailed.

Academic Integrity

The academic enterprise is founded on honesty, civility, and integrity. As members of this enterprise, all students are expected to know, understand, and follow the codes of conduct regarding academic integrity. At the most basic level, this means submitting only original work done by you and acknowledging all sources of information or ideas and attributing them to others as required. This also means you should not cheat, copy, or mislead others about what is your work. Violations of academic integrity (i.e., misconduct) lead to the breakdown of the academic enterprise, and therefore serious consequences arise and harsh sanctions are imposed. For example, incidences of plagiarism or cheating may result in a mark of zero on the assignment or exam and more serious consequences may apply if the matter is referred to the President’s Advisory Committee on Student Discipline. Careful records are kept in order to monitor and prevent recurrences. A more detailed description of academic integrity, including the University’s policies and procedures, may be found in the Academic Calendar at,54,111,0

Tentative Schedule

Week Lecture Topics Team Presentation Readings
1 - Sept 4 Introduction to course and econometrics
2 - Sept 11 Class survey. Review of inferential statistics; estimation; hypothesis testing and Excel (Data Analysis Toolpak). Handouts
3 - Sept 18 Pivot Table Analysis. Excel/Stata. Introduction to regression. Handouts
4 - Sept 25 Regression Basics: the simple linear regression model Hill Chapt 1-4
5 - Oct 2 Regression Basics: interval estimation and hypothesis testing; prediction; goodness of fit; functional forms; interpretation and modeling issues Hill Chapt 1-4
6 – Oct 9 Regression Basics: case study. Hill Chapt 1-4
7 – Oct 16 Multivariate Regression (Introduction to multivariate analysis) Hill Chapt 5
8 - Oct 23 Tues Oct 24th – MIDTERM EXAM
9 – Oct 30 Team Presentations (3 Teams) – October 31st Multivariate Regression Hill Chapt 6-8
10 - Nov 6 Multivariate Regression Hill Chapt 6-8
11 - Nov 13 Multivariate Regression; start of Qualitative and Limited Dependent Variables Hill Chapt 6-8
12 - Nov 20 Qualitative and Limited Dependent Variables Hill Chapt 16
13 - Nov 27 Team Presentations (7 Teams)