The overall aim of this course is to provide students with an advanced understanding of the principles underlying estimation methods and hypothesis tests in econometrics. The course first covers basic probability theory, then introduces asymtotic approximation theory, and finally moves to statistics and econometrics. To focus on general ideas, the course abstracts from real-world issues and turns to the laboratory/sandbox called mathematics. In addition to mathematical derivations, the properties of certain techniques may be investigated through computer simulation.

On successful completion of this course, students will be able to:

• demonstrate understanding of the foundational concepts of econometric theory
• exhibit familiarity with key tools from probability theory and mathematical statistics as they apply to econometrics
• explain the relationship between many of the core models used in econometrics, and their advantages and disadvantages
• determine appropriate modelling strategies in different applied settings
• write simple programs in the R programming language

The assessment consists of three parts; assignments, a mid-session exam and a final exam.

See course outline on RSE website for weighting.

Two lectures and one tutorial per week.

EMET2008 Econometrics II: Econometric Modelling.

For further information please refer to course website