EC1C1      Half Unit
Econometrics I

This information is for the 2021/22 session.

Teacher responsible

Dr Michael Callen 32L.3.18

Availability

This course is compulsory on the BSc in Econometrics and Mathematical Economics and BSc in Economics. This course is not available as an outside option nor to General Course students.

Pre-requisites

Students must have completed Economics (EC1P1) and Elementary Statistical Theory I (ST109).

Students must also either have completed Quantitative Methods (Mathematics) (MA107) or else be taking Mathematical Methods (MA100) alongside.

Course content

This course is an applied introduction to econometrics. Its aim is to introduce students to the principles of estimation, statistical inference, and the central tool of regression. The course draws heavily on empirical questions and you will work with statistical software analysing actual data sets and learn some basic programming and data handling skills in the process. You will learn how statistical tools can be used to answer causal questions (e.g., “What is the causal effect of electing a better educated politician on the quality of service delivery?”). as well as prediction problems (e.g., "what individual characteristics, such as income or education, predict who political parties select to run for office?").

Topics include: program evaluation; randomised experiments; univariate regression; omitted variable bias; selection bias; sampling fluctuation; statistical inference; standard errors; and hypothesis testing.

Teaching

20 hours of lectures and 10 hours of lectures in the LT. 1 hour of lectures 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 30 hours across 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.

Formative coursework

There are weekly assignments and feedback will be given on two.

Indicative reading

  • J. D. Angrist and J. S. Pischke Mastering ‘Metrics. The Path from Cause to Effect, Princeton University Press.
  • J. H. Stock and M. Watson Introduction to Econometrics, Pearson

Assessment

Exam (85%, duration: 2 hours) in the summer exam period.
Coursework (15%) in the LT.

Key facts

Department: Economics

Total students 2020/21: Unavailable

Average class size 2020/21: Unavailable

Capped 2020/21: No

Value: Half Unit

Guidelines for interpreting course guide information

Personal development skills

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