Module overview
This module shows economic analysis at work in several areas of policy concern and explores simple models and empirical methodologies that help us to understand central problems of economic policy analysis and evaluate alternative policy options.
Aims and Objectives
Learning Outcomes
Knowledge and Understanding
Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:
- Microeconomic data and the output produced by econometric software packages
- Economic and econometric methodologies used in empirical work
- Economic principles as applied in different contexts and their uses in designing effective policies
Subject Specific Intellectual and Research Skills
Having successfully completed this module you will be able to:
- Combine economic principles with empirical evidence to inform policy decisions
- Analyse and interpret microeconomic data
- Identify strengths and limitations of econometric methodologies used in empirical work
Transferable and Generic Skills
Having successfully completed this module you will be able to:
- Use econometric software to compute summary statistics and perform basic regression analysis
Syllabus
An indicative syllabus is as follows:
* Part 1 - Introduction to Econometric Analysis
- Methodology, types of data, types of variables
- Hypothesis testing and application
- t-stats, critical values and p-values, one and two-sided tests, example application
- Simple linear regression, multiple linear regression, example application
- Interaction terms and interpretation of regressions in involving logs
* Part 2 - Applied Topics (indicative list)
- Labour Economics (Gender pay gap)
- Health Economics (Obesity)
- Economics of Addiction
- Environmental Economics
- Economics of Crime
Note that Part 2 will draw on Part 1 as well as developing students’ understanding through practical applications that cover common empirical issues such as endogeneity, autocorrelation and unobserved heterogeneity, and appropriate techniques for dealing with these issues (2SLS and instrumental variables, difference-in-difference estimation, and panel data regression)
Learning and Teaching
Teaching and learning methods
Lectures, tutorials, and private study.
| Type | Hours |
|---|---|
| Teaching | 24 |
| Independent Study | 126 |
| Total study time | 150 |
Resources & Reading list
General Resources
Lecture notes provided during class; academic published articles on relevant topics.
Assessment
Assessment strategy
The final course grade is determined by: A two hours end of semester exam (70%), assessing student's understanding of both the theoretical, empirical and practical aspects of economic analysis. One take-home problem set is distributed during the semester (10%). Online quizzes are taking place during the semester (20%). This is accompanied by continuous formative assessment through problem sets. This is the same for internal repeats. Referral and external repeat assessment are through 100% final exam.Summative
This is how we’ll formally assess what you have learned in this module.
| Method | Percentage contribution |
|---|---|
| Coursework assignment(s) | 10% |
| Online test | 20% |
| Exam | 70% |
Referral
This is how we’ll assess you if you don’t meet the criteria to pass this module.
| Method | Percentage contribution |
|---|---|
| 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 |
|---|---|
| Exam | 100% |
Repeat Information
Repeat type: Internal & External