Introduction to Econometrics
This information is for the 2020/21 session.
Dr Canh Thien Dang 32L.4.29 and Prof Steve Pischke 32L.2.16 (MT), Prof Taisuke Otsu 32L 4.25 and Dr. Marcia Schafgans 32L 4.12 (LT)
This course is available on the BSc in Accounting and Finance, BSc in Economics, BSc in Economics and Economic History, BSc in Economics with Economic History, BSc in Finance, BSc in Geography with Economics, BSc in Government and Economics, BSc in International Social and Public Policy and Economics, BSc in Philosophy and Economics, BSc in Philosophy, Politics and Economics, BSc in Politics and Economics, BSc in Social Policy and Economics, Diploma in Accounting and Finance 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.
Availability to General Course students is with the permission of the lecturer.
Students must have completed Elementary Statistical Theory (ST102).
Those who have taken MA107/ST107 should consider taking EC220 only if they have obtained marks of 65 or better on both courses
This course is an introduction to econometrics; it aims to present the theory and practice of empirical research in economics. Compared to EC221, in LT this course relies on calculus instead of matrix algebra and follows Wooldridge closely.
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, standard error formula, 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; binary choice models; 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.
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.
There will be a reading week in Week 6 of LT only (no lectures or classes that week).
EC220.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 EC220 Moodle page.
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.
Important information in response to COVID-19
Please note that during 2020/21 academic year some variation to teaching and learning activities may be required to respond to changes in public health advice and/or to account for the situation of students in attendance on campus and those studying online during the early part of the academic year. For assessment, this may involve changes to mode of delivery and/or the format or weighting of assessments. Changes will only be made if required and students will be notified about any changes to teaching or assessment plans at the earliest opportunity.
Total students 2019/20: 315
Average class size 2019/20: 12
Capped 2019/20: No
Value: One Unit
Personal development skills
- Problem solving
- Application of numeracy skills