Econometric Theory

This information is for the 2016/17 session.

Teacher responsible

Dr Tatiana Komarova 32L4.24 and Prof Francisco Hidalgo 32L4.20


This course is compulsory on the MSc in Econometrics and Mathematical Economics (2 Year Programme). This course is available on the BSc in Econometrics and Mathematical Economics and BSc in Mathematics and Economics. This course is available with permission as an outside option to students on other programmes where regulations permit and to General Course students.


Students must have completed Principles of Econometrics (EC221).

A good knowledge of linear algebra, calculus and statistical theory is essential, and therefore MA100 and ST102 or equivalent is required. Students taking this course who are not in BSc Econometrics and Mathematical Economics or BSc Mathematics and Economics must consult with Dr. Komarova before selecting this course

Course content

Introduction to the asymptotic theory of estimation and inference of economic models; Basics of large sample theory; Estimation of linear regression models (OLS, GMM, GLS); Testing hypotheses and model specifications; Estimation of nonlinear models (MLE, Nonlinear least squares); systems of equations; time series analysis.


15 hours of lectures and 10 hours of classes in the MT. 15 hours of lectures and 10 hours of classes in the LT.

Formative coursework

Written answers to set problems will be expected on a weekly basis.

Indicative reading

The main text for the lectures is R Davidson & J G MacKinnon, Econometric Theory and Methods,Oxford University Press (2004). Other useful texts include Davidson (2000), Econometric Theory Amemiya (1985), Advanced Econometrics; and Hayashi (2000), Econometrics.


Exam (100%, duration: 3 hours, reading time: 15 minutes) in the main exam period.

Key facts

Department: Economics

Total students 2015/16: 18

Average class size 2015/16: 17

Capped 2015/16: No

Value: One Unit

Guidelines for interpreting course guide information

PDAM skills

  • Self-management
  • Problem solving
  • Application of numeracy skills