Module overview
This module provides an introduction to the nature and use of empirical investigation in economics. The module will familiarise students with the basic concepts in econometrics as well as outline the statistical theory underpinning econometrics and statistical inference. The module will cover the specification of econometric models and their estimation and testing using available data. It will consider the nature of economic data, the methods by which they are compiled and some problems they may present for the econometrician
Aims and Objectives
Learning Outcomes
Subject Specific Intellectual and Research Skills
Having successfully completed this module you will be able to:
- use data for statistical inference on the quantitative or qualitative workings of economic mechanisms.
- organise, analyse and present economic data in an informative manner.
- apply logical analysis using econometric models to address economic questions, for instance by setting up statistical tests
- abstract the essential features of complex systems and specify econometric models to assess the effects of exogenous changes.
Knowledge and Understanding
Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:
- fundamental econometric methods to analyse economic data.
- statistical methods used in economics for small and large datasets, such as the classical linear regression model.
Transferable and Generic Skills
Having successfully completed this module you will be able to:
- use quantitative reasoning and analyse and interpret data using standard statistical software.
Syllabus
Topics covered are:
- Revision of basic probability concepts and the simple linear regression model.
- An introduction to econometric modelling of economic data.
- Least squares inference in the simple linear regression model.
- The multiple regression model: Testing and models specification.
This module will cover both techniques of estimation and methods for testing and evaluating results. Emphasis is placed on providing you with practical experience of working with actual economic datasets and using a standard econometric package (such as Stata) for data analysis.
Learning and Teaching
Teaching and learning methods
Lectures, masterclasses and computer-based tutorial sessions.
| Type | Hours |
|---|---|
| Independent Study | 122 |
| Tutorial | 8 |
| Lecture | 20 |
| Total study time | 150 |
Resources & Reading list
Textbooks
L. Adkins, R.C. Hill (2015). Using Stata for the Principles of Econometrics. John Wiley.
R.C. Hill, W.E. Griffiths, G.C. Lim (2018). Principles of Econometrics. John Wiley.
Assessment
Assessment strategy
Coursework in form of problem sets and data analysis assignments during the semester and a final exam, supported by continuous formative assessment in form of problem sets and data analysis exercises. This is the same for an internal repeat. Assessment for external repeat and referral is thorugh final exam only.
Summative
This is how we’ll formally assess what you have learned in this module.
| Method | Percentage contribution |
|---|---|
| Final Exam | 80% |
| Coursework assignment(s) | 10% |
| Coursework assignment(s) | 10% |
Referral
This is how we’ll assess you if you don’t meet the criteria to pass this module.
| Method | Percentage contribution |
|---|---|
| Final Exam | 100% |
Repeat
An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.
| Method | Percentage contribution |
|---|---|
| Final Exam | 100% |
Repeat Information
Repeat type: Internal & External