EC902: Quantitative Methods: Econometrics A

Subham Kailthya
Module Leader
Manuel Bagues
Module Lecturer

45 CATS - Department of Economics

Summer Module

Spring Module

Autumn Module

Introduction

EC902-45 Quantitative Methods: Econometrics A

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

Subject Knowledge and Understanding: 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.

Subject Knowledge and Understanding: demonstrate a deep understanding of material needed for empirical quantitative analysis.

Subject Knowledge and Understanding: demonstrate a full knowledge of the theory and practice of modern econometrics, particularly applied econometrics.

Subject Specific and Professional Skills: 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.

Cognitive Skills: develop the critical insight to appraise econometric results obtained by other researchers.

Syllabus

The syllabus for this module will be based on the following topics; however this list is not limited to those listed below and does not infer all of these topics will be studied in the module.

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

Econometrics:

Term 1 will cover Randomized control trials, Identification based on observables (e.g. OLS), Instrumental variables Differences-in-differences, Regression discontinuity design.

Term 2 will cover 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.

Context

Optional Core Module: L1P6 - Year 1, L1P7 - Year 1
Optional Module: V7L2 - Year 1, V7L3 - 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

Assessment Method: Coursework (45%) + In-person Examination (55%)
Coursework Details: Group Project (25%) , In-person Examination (55%) , Test 1 (4%) , Test 2 (6%) , Test 3 (10%)
Exam Timing: Summer

Exam Rubric

Time Allowed: 3 Hours, plus 15 minutes reading time during which you may make notes on the question paper. You must not start writing in your answer booklet until you are instructed.

Read all instructions carefully - and read through the entire paper at least once before you start entering your answers.

There are FOUR sections in this paper. Answer ALL THREE questions in Section A (10 marks each), ONE question in Section B (20 marks), ALL THREE questions in Section C (10 marks each) and ONE question in Section D (20 marks).

Answer each whole question in a separate booklet.

Approved scientific (non-graphical) pocket calculators are allowed.

You should not submit answers to more than the required number of questions. If you do, we will mark the questions in the order that they appear, up to the required number of questions in each section.

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.