Course:FRE529

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Estimating Econometric Models
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FRE 529
Section:
Instructor: Dr. Michael Johnson
Email: mjohnson@mail.ubc.ca
Office: MCML 231
Office Hours: TBA
Class Schedule: Tuesday, Thursday 12:30 - 1:50 PM
Classroom: TBA
Important Course Pages
Syllabus
Lecture Notes
Assignments
Course Discussion

Course Description

In this course we study some econometric topics that are not covered in the Applied Econometrics course (FRE 528) that are useful for economists working in the food and resource sectors. Topics can include instrument variables (IV) estimation, difference-in-difference estimation, panel data methods (basic models, dynamic panel model and difference-in-differences), qualitative and limited dependent variable models and time series methods. The focus of the course will be on the application of these methods in econometric modeling rather than on theoretical proofs.

Course Goals

  • To learn various advanced econometric methods, estimation methods and related econometric theories
  • To apply these methods to data or econometric modelling techniques to estimate models using real world data
  • To be able to write a code in Stata to estimate econometric models and replicate results from published econometrics research
  • To be capable of interpreting econometric estimates, analyzing the results and critically evaluating published econometric research that use advanced econometrics methods.

Course Format

14 lectures of 1.5 hours, twice a week for 7 weeks.

Course Requirements (Subject to changes)

Activity Date Percent of Grade
Assignments Assigned approximately every two weeks 30%
Team Paper Presentation To be announced. 20%
Final exam To be announced. 40%
Class Participation Contributions to class discussions. 10%
Total: 100%

Assignments

The assignments will consist of an applied problem that will allow the students to apply the various techniques and topics covered in class using real life data sets. In addition, they will get practice in the use of the statistical software Stata.

Class Participation

The class participation grade depends on your contribution to class discussions. All contribution is appreciated, even questions asking the instructor to clarify previously taught material. The sole aim of assigning a participation grade is to encourage active learning for everyone. The instructor will ascertain and assign this part.

Academic Dishonesty

Please review the UBC Calendar “Academic regulations” for the university policy on cheating, plagiarism, and other forms of academic dishonesty. Academic dishonesty will be dealt with very seriously in this course.

Online Course Material

Available at Connect: http://www.connect.ubc.ca. You are required to regularly login to your course page for FRE 526. Your syllabus, course-lecture slides, additional material, announcements, assignments, and grades are available.

Textbook and Resources

  • Verbeek, M. (2012). A Modern Guide to Econometrics, Fourth Edition. John Wiley & Sons.
  • R. Carter Hill, William E. Griffiths and Guay C. Lim, Principles of Econometrics, Fourth Edition, Wiley, 20.
  • A Stata guide for the textbook is also on reserve at the same location: Using Stata for Principles of Econometrics, 4th edition by Lee C. Adkins and R. Carter Hill. 2011.
  • Various journal articles (links provided later).

Tentative Lecture Schedule (to be finalized)

Date Topic Assignment
Week 1 Tue: Course Introduction; Endogeneity


Thu: IV estimation: Agricultural productivity measurement

Week 2 Tue: Difference in difference estimation (waste disposal)


Thu: Panel Data: Introduction. Student Team Presentation #1

Tue: Assignment 1 given.
Week 3 Tue: Panel Data: Fixed Effects (school lunch policy)


Thu: Panel Data: Random Effects Models

Week 4 Tue: Panel Data: Issues and Extensions (GMM)


Thu: Limited Dependent Variables models. Student Team Presentation #2.

Thu: Assignment 2 given
Week 5 Tue: Limited Dependent Variables models (Outdoor Recreation demand)


Thu: Time Series; Tools; Stationarity and Cointegration

Week 6 Tue: Time Series; ARIMA (Box-Jenkins Methodology)


Thu: Time Series; ARIMA (Box-Jenkins Methodology), ARMAX

Tue: Assignment 3 given.
Week 7 Tue: Presentations (Teams 3, 4 and 5)


Thu: Final Exam