ECO 374H1S: Applied Econometrics (for Commerce)
Winter 2011
Department of Economics, University of Toronto
Link to course material at Blackboard (UTORid required)
Basic course information:
Instructor: Prof. Martin Burda
Office: Department of Economics, room 234, at 150 St. George St.
Phone: 416-978-4479
E-mail: martin.burda@utoronto.ca
Lectures: Tuesday 10:00 am – 12:00 pm, Woodsworth College, room 126
Tutorials: Friday 12:00 – 1:00 pm (same location)
Office hours: Tuesday 1:00 – 3:00 pm
Teaching Assistant: Wang, Siyu [Sophia]
Office: Department of Economics, room TBA, at 150 St. George St.
E-mail: sophie.wang@utoronto.ca
Office hours: Monday 12:00 – 2:00 pm, Department of Economics, room 040 (150 St. George St.)
Syllabus ECO 374 H1S (pdf)
Econometrics combines elements of Economic Theory, Statistics, Probability Theory, and Mathematics. The primary objective of the course is to provide students with a solid theoretical and practical foundation for the interpretation of empirical evidence in economics. The course is built around the statistical foundations, and economic application, of the multiple regression model and time series analysis. Key examples will be drawn from business and financial economics. Students will gain practical experience working with economic and financial data, making extensive use of statistical software.
Prerequisites: (i) ECO200Y1 or ECO204Y1 or ECO206Y1
(ii) ECO220Y1 (70%) or ECO227Y1 or STA257H1+STA261H1
Recommended:
MAT223H1 or MAT240H1
Exclusion: ECO375H1, STA302H1
The prerequisites are checked by the Department of Economics and students will be removed from the course list if the prerequisites are not met.
"Forecasting, Time Series, and Regression" by Bowerman, O’Connell, and Koehler, 2005, 4th edition, Brooks / Cole (Cengage Learning).
ISBN-13: 9780534409777 ISBN-10: 0534409776
The book will be available at the University of Toronto Textbook Store, or can be purchased from various online bookstores. Make sure that the book you buy contains a CD with software and data.
We will make regular use of statistical functions and add-ins of Excel throughout the course. Excel can perform the same operations as alternative expensive software packages for the material covered in the course and should be generally accessible anywhere.