EC1C1      Half Unit
Econometrics I

This information is for the 2021/22 session.

Teacher responsible

To be confirmed.

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 Quantitative Methods (Mathematics) (MA107).

Economics (EC1P1) 

The new half-unit version of ST102

Course content

This course is an applied introduction to econometrics. Its aim is to introduce you to the principles of estimation and 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 “what-if” questions (e.g., “What is the effect of monetary policy on output?”) and prediction problems.

Topics include: randomised experiments; program evaluation; matching; simple and multiple regression analysis; omitted variable bias; functional form; measurement error; sampling and estimation; statistical inference, standard errors, and hypothesis testing.

Teaching

20 hours of lectures and 10 hours of lectures in the LT.

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