Principles of Econometrics
This information is for the 2021/22 session.
Dr Canh Thien Dang, (MT) and Dr. Marcia Schafgans 32L 4.12 (LT)
This course is compulsory on the BSc in Econometrics and Mathematical Economics. This course is available on the BSc in Business Mathematics and Statistics, BSc in Economics, BSc in Economics with Economic History, BSc in Finance, BSc in Mathematics and Economics, BSc in Mathematics with Economics, BSc in Mathematics, Statistics and Business, BSc in Philosophy and Economics, BSc in Philosophy, Politics and Economics and MSc in Economics (2 Year Programme). This course is available with permission as an outside option to students on other programmes where regulations permit and to General Course students.
Students must have completed Mathematical Methods (MA100) and Elementary Statistical Theory (ST102).
This course is a more advanced introduction to econometrics; it aims to present the theory and practice of empirical research in economics. Compared to EC220, in LT this course puts more emphasis on the underlying statistical theory and uses matrix algebra extensively.
In MT, the focus of the course is on empirical questions and students will work with the econometrics software packages R or Stata analysing actual data sets. Students will learn how various tools are used to answer causal “what-if” questions (e.g., “What is the effect of monetary policy on output?”) and prediction problems.
In LT, the focus of the course is on the underlying econometric theory: estimation, properties of estimators (unbiasedness, efficiency, sampling distribution, consistency) and hypothesis testing.
Topics include randomised experiments; program evaluation; matching; simple and multiple regression analysis; omitted variable bias; functional form; heteroskedasticity and weighted least squares; endogeneity (omitted variables and simultaneity); instrumental variables and two-stage least squares; MLE and binary choice models and Trinity of Testing; and time series analysis.
30 hours of lectures and 10 hours of classes in the MT. 30 hours of lectures and 9 hours of classes in the LT. 1 hour of classes in the ST.
There will be a reading week in Week 6 of LT only (no lectures or classes that week).
This course is delivered through a combination of classes and lectures totalling a minimum of 80 hours across Michaelmas Term and Lent Term. This year, some or all of this teaching will be delivered through a combination of virtual classes, live streamed (recorded) lectures, and some flipped content delivered as short online videos.
EC221.B for graduate students
Exercises are provided each week and are discussed in the classes. (MT) Students are required to hand in written answers to the exercises for feedback. (LT) While students are expected to attempt the weekly problem sets before each class, students will receive formal feedback on 4 occasions.
J. W. Wooldridge Introductory Econometrics. A Modern Approach, 6th Edition, South-Western.
J. D. Angrist and J. S. Pischke Mastering ‘Metrics. The Path from Cause to Effect, Princeton University Press.
Further materials will be available on the Moodle website.
Other useful texts include: W. Greene, Econometric Analysis, 7th Edition, Pearson; J. Johnston and J. Dinardo, Econometric Methods, 4th Edition, McGraw-Hill; G.S. Maddala and K. Lahiri, Introduction to Econometrics, 4th Edition, John Wiley; J.H. Stock and M.W. Watson, Introduction to Econometrics, 3rd Edition, Pearson ; C. Heij et al., Econometric methods with Applications in Business and Economics, Oxford University Press.
Exam (25%, duration: 1 hour, reading time: 15 minutes) in the January exam period.
Exam (75%, duration: 3 hours, reading time: 15 minutes) in the summer exam period.
The Lent term examination is based 100% on the Michaelmas term syllabus, and the Summer exam on 33% of the Michaelmas term syllabus and 67% of the Lent term syllabus.
Total students 2020/21: 191
Average class size 2020/21: 18
Capped 2020/21: No
Value: One Unit
Personal development skills
- Problem solving
- Application of information skills
- Application of numeracy skills