EC902: Quantitative Methods: Econometrics A
Manuel Bagues
Module Leader
Introduction
EC902-45 Quantitative Methods: Econometrics APrincipal 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%) + Centrally-timetabled examination (On-campus) (55%)
- Coursework Details
- Centrally-timetabled examination (On-campus) (55%) , Group Project (25%) , Test 1 (4%) , Test 2 (6%) , Test 3 (10%)
- Exam Timing
- Summer