Skip to main content

Unit information: MRes Econometrics 1 in 2015/16

Please note: you are viewing unit and programme information for a past academic year. Please see the current academic year for up to date information.

Unit name MRes Econometrics 1
Unit code EFIMM0021
Credit points 15
Level of study M/7
Teaching block(s) Teaching Block 1 (weeks 1 - 12)
Unit director Professor. Windmeijer
Open unit status Not open



MRes Mathematics for Economics

School/department School of Economics
Faculty Faculty of Social Sciences and Law

Description including Unit Aims

This unit aims to broaden and deepen knowledge and understanding of basic econometrics. Topics will include the general linear regression model, asymptotic distribution theory, instrumental variables estimation and maximum likelihood estimation. In addition, the course will introduce and make extensive use of linear/matrix algebra, differential calculus and statistical inference techniques. The unit aims to build in students the ability to know, understand, and evaluate these tools and to apply them when undertaking novel research. Applications will highlight the scope and limitations of these tools.

Intended Learning Outcomes

This unit provides a thorough and in-depth treatment of the basic concepts in econometrics and introduces fundamental analytic paradigms rigorously, with a view to equip the students with sufficient foundational understanding of the discipline to be able to access the journal articles first-hand, to evaluate them critically and to start independent research projects at basic levels. Students will also learn to the application of statistical software to these tools, its scope and limitations.

Teaching Information

There are two lectures and one exercise class per week. Coursework will consist of weekly exercises which will be used for course assessment.

Lectures will introduce and explain the different concepts and methods as well as their application and limitation whereas exercise classes will provide the opportunity to practice the selection and use of these methods as well as the application, scope and limitation of statistical software.

Contact Hours Per Week 3

Student Input

20 hours lectures

10 hours tutorials

15 hours preparation of weekly exercises for assessment

3 hours final exam

102 hours individual study

Assessment Information

Summative assessment: 3-hour written exam (85%), weekly exercises on the various topics (15%). The exam will test the knowledge, selection, application and evaluation of tools and methods, whereas the exercises will incentivize the students to learn to use, apply and evaluate these methods as well as computational software while getting feedback on their progress.

Formative assessment: class participation and discussion in tutorials. These will provide further opportunities for feedback on the students’ progress.

Reading and References

R. Davidson & J.G. MacKinnon, Econometric Theory and Methods, OUP

W. Greene, Econometric Analysis, (Seventh Ed.), Prentice Hall

P. Ruud, An Introduction to Classical Econometric Theory, OUP

M. Verbeek, A Guide to Modern Econometrics, (Fourth Ed.), J. Wiley and Sons.