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EC902: Quantitative Methods: Econometrics A

  • Gianna Boero

    Module Leader
  • Manuel Bagues

    Module Lecturer
50 CATS - Department of Economics
Spring Module
Autumn Module

Principal Aims

The aim of the module is to equip students with the necessary skills required for research, including both the acquisition of habits of thought and knowledge of the techniques of modern mathematics, statistics and econometrics. The module does not aim to go beyond the development of these fundamental professional skills to cover more advanced techniques.

Principal Learning Outcomes

By the end of the module the student should be able to: demonstrate an understanding of fundamental concepts in mathematics and statistics relevant to the other core modules and be able to apply these concepts to economics; demonstrate a deep understanding of material needed for empirical quantitative analysis, demonstrate a full knowledge of the theory and practice of modern econometrics, particularly applied econometrics; demonstrate the development of the habit of thought, knowledge and understanding to be able to carry out good quality applied econometric research with confidence and authority; develop the critical insight to appraise econometric results obtained by other researchers.


Pre-sessional Introductory Mathematics and Statistics: topics covered will include linear algebra, multivariate calculus and constrained optimisation, differential and difference equations, basic probability theory and hypothesis testing.

Econometrics: The first term will cover Linear Regression Model (LRM), Maximum Likelihood Estimation (MLE), hypothesis testing, model diagnostics, limited dependent variable models, measurement error, simultaneity bias, endogeneity, instrumental variables, and Generalised Method of Moments (GMM). The second term covers the econometric modelling of economic and financial time-series data. This will include time series models, modelling univariate time series, unit root processes, multivariate time series, autoregressive conditional heteroskedasticity, and panel data.


Optional Core Module
L1P6 - Year 1, L1P7 - Year 1
Pre or Co-requisites
Technical prerequisites (besides a first degree in economics) are elementary probability and statistics, mathematics for economists and algebraic facility.


Assessment Method
Coursework (45%) + 3 hour exam (55%)
Coursework Details
1 x 1 hour test (4%) and 1 x 2 hour test (6%)on pre-sessional Introductory Mathematics and Statistics and 1 x 1 hour test (10%) + 3000 word project (25%)
Exam Timing

Exam Rubric

Time Allowed: 3 Hours plus 15 minutes reading time during which notes may be made (on the question paper only) BUT NO ANSWERS MAY BE BEGUN.

Answer ALL SIX questions in Section A (10 marks each); ONE question from Section B (20 marks) and ONE question from Section C (20 marks). Answer Section A questions in one booklet, Section B questions in a separate booklet and Section C questions in a separate booklet.

Approved pocket calculators are allowed. Statistical Tables are provided.

Read carefully the instructions on the answer book provided and make sure that the particulars required are entered on each answer book. If you answer more questions than are required and do not indicate which answers should be ignored, we will mark the requisite number of answers in the order in which they appear in the answer book(s): answers beyond that number will not be considered.

Previous exam papers can be found in the University’s past papers archive. Please note that previous exam papers may not have operated under the same exam rubric or assessment weightings as those for the current academic year. The content of past papers may also be different.

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