EC2C1     
Econometrics II

This information is for the 2024/25 session.

Teacher responsible

Dr Marcia Schafgans, SAL 4.12

Professor Steve Pischke, SAL.2.16

Availability

This course is compulsory on the BSc in Econometrics and Mathematical Economics, BSc in Economics and MSc in Economics (2 Year Programme). This course is not available as an outside option nor to General Course students.

Pre-requisites

Students must have completed Methods in Calculus and Linear Algebra (MA108) or Mathematical Methods (MA100), or equivalent. Students must also have completed Elementary Statistical Theory I (ST109) and Econometrics I (EC1C1), or equivalent.

MSc in Economics (2 Year Programme) students can take either Mathematical Methods (MA100) or Further Mathematical Methods (MA212) alongside EC2C1.

Course content

This course builds on the knowledge learned in Econometrics I (EC1C1). In the AT part of the course, the focus is an introduction to the theory of econometrics. You will study in detail various estimators common in the literature: the least squares estimator, the instrumental variable estimator, and the maximum likelihood estimator. You will discuss how (and whether) these estimators can be used for inference purposes under a range of assumptions underlying the data generating process. Topics include the derivation of finite sample properties (unbiasedness, precision (standard error) and efficiency), asymptotic properties (consistency and asymptotic distribution), confidence intervals and hypothesis testing. Most discussions will pertain to the use of cross-sectional data and the linear model. We will consider the binary choice model as an example of a nonlinear model and will cover some aspects of time series data. Various discussions make use of matrix algebra.

In the WT part of the course, you will learn more econometric techniques, including difference-in-differences, and regression discontinuity designs that make use of panel data and you will revisit the instrumental variable technique. Teaching in WT will be based on empirical examples and you will find out how to conduct your own empirical investigation. As part of the course, you will work on an empirical project and write an individual report about your analysis and findings.

Teaching

30 hours of lectures, 10 hours of classes and 10 hours of help sessions in the AT. 20 hours of lectures and 10 hours of classes in the WT.

There will be a reading week in Week 6 of WT, during which there will be no lectures or classes.

Student learning will be supported through the EC2C1 Support Lab and through a dedicated discussion forum.

Formative coursework

During AT, there are weekly assignments and feedback will be given on two.

During WT, there will be four homework assignments. Students are expected to give a progress report on their individual project and are given feedback on this.

Indicative reading

• J. Wooldridge Introductory Econometrics. A Modern Approach, Cengage

• J. D. Angrist and J. S. Pischke Mastering ‘Metrics. The Path from Cause to Effect, Princeton University Press.

Assessment

Exam (45%, duration: 2 hours, reading time: 15 minutes) in the January exam period.
Project (45%, 2500 words) in the ST.
Continuous assessment (10%) in the AT and WT.

Key facts

Department: Economics

Total students 2023/24: 302

Average class size 2023/24: 17

Capped 2023/24: No

Value: One Unit

Guidelines for interpreting course guide information

Course selection videos

Some departments have produced short videos to introduce their courses. Please refer to the course selection videos index page for further information.

Personal development skills

  • Self-management
  • Team working
  • Problem solving
  • Application of information skills
  • Communication
  • Application of numeracy skills
  • Specialist skills