Module overview
The module will enable you to apply statistical and econometric techniques to the estimation and testing of economic models and for causal inference. It will thereby provide you with the skills necessary both to undertake your own empirical studies and to evaluate empirical work in the published literature.
Linked modules
Pre-reqs: ECON2043 OR ECON2041
Aims and Objectives
Learning Outcomes
Subject Specific Intellectual and Research Skills
Having successfully completed this module you will be able to:
- apply statistical techniques to empirical data for statistical inference on the effects of economic policies and testing economic models.
- identify violations of the assumptions of classical linear regression and propose adequate solutions.
- analyse and interpret economic data in an informative manner using econometric methods.
- abstract the essential features of economic systems into a statistical model
Transferable and Generic Skills
Having successfully completed this module you will be able to:
- use quantitative reasoning and analyse and interpret data, using output from standard statistical software.
- communicate the results and conclusions of data analyis thorugh an executive summary.
- successfully collaborate with others in a team on data analysis problems.
Knowledge and Understanding
Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:
- statistical tests for the empirical evaluation of economic policy.
- statistical tools for economic analysis that account for violations of classical linear regression assumptions.
Syllabus
This module extends the discussion of econometrics presented in the first semester of the second year, focusing on issues that arise in applying the classical linear regression model to actual economic data. We examine the problems associated with specifying economic models in forms which are amenable to estimation and testing using available economic data. Consideration is given to the nature of economic data - the methods by which it is collected and compiled and the difficulties these may present for the applied economist interested in the evaluation of economic policies or the testing of theoretical hypotheses. Methods for testing model specification and alternative techniques for handling problems of misspecification are discussed. The module provides practical experience of applying econometric techniques to economic data using standard statistical software.
Learning and Teaching
Teaching and learning methods
Lectures, (computer-based) tutorials.
Type | Hours |
---|---|
Lecture | 20 |
Independent Study | 122 |
Tutorial | 8 |
Total study time | 150 |
Resources & Reading list
Textbooks
R.C. Hill, W.E. Griffiths and G.C. Lim (2018). Principles of Econometrics. John Wiley.
J. Wooldridge (2015). Introductory Econometrics: A Modern Approach. South-Western Cengage Learning.
Assessment
Assessment strategy
Two take-home coursework assignments during the semester and a final written exam, supported by continuous formative assessment in form of problem sets. This is the same for internal repeat. Assessment for referral and external repeat is through final written exam only.
Summative
This is how we’ll formally assess what you have learned in this module.
Method | Percentage contribution |
---|---|
Coursework assignment(s) | 15% |
Coursework assignment(s) | 15% |
Final Exam | 70% |
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