Postgraduate Programme and Module Handbook 2024-2025
Module ECON41515: ECONOMETRIC ANALYSIS
Department: Economics
ECON41515: ECONOMETRIC ANALYSIS
| Type | Tied | Level | 4 | Credits | 15 | Availability | Available in 2024/2025 | Module Cap |
|---|
| Tied to | L1T109 |
|---|---|
| Tied to | L1T409 |
| Tied to | L1T609 |
| Tied to | N3K709 |
Prerequisites
- One econometrics module or equivalent quantitative module covering basic statistics and probability theory including distributions as well as hypothesis testing.
Corequisites
- None
Excluded Combination of Modules
- Econometric Methods (FINN41715); Financial Modelling and Business Forecasting (FINN41615)
Aims
- to provide students with some of the econometrics skills necessary to pursue empirical research in economics and/or finance;
- to provide a basis for understanding more advanced econometric techniques to be taught in the second term of the MSc programme.
Content
- Linear Regression Model using Matrix Algebra, Gauss-Markov, Identification, OLS, finite sample properties of the OLS estimator
- Hypothesis testing and Confidence intervals
- Asymptotic properties of the OLS estimated
- Misspecification and dummy variables
- GLS, autocorrelation and heteroskedasticity
- Endogeneity, Simultaneity, Instrumental Variables (IV) estimation
- Generalized Methods of Moments (GMM)
- Maximum Likelihood (ML)
Learning Outcomes
Subject-specific Knowledge:
- By the end of the module, students should:
- have a thorough knowledge of the key econometric concepts, principles and methods.
Subject-specific Skills:
- By the end of the module, students should:
- have the ability to apply econometric methods and interpret the results at an advanced level;
- be able to use a range of econometric tools to conduct their own empirical investigations;
- have problem solving skills and have practised the use of econometric software.
Key Skills:
- Written Communication;
- Planning, Organisation and Time Management;
- Problem Solving and Analysis;
- Using Initiative;
- Numeracy;
- Computer Literacy.
Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module
- A combination of lectures, workshops, computer classes and guided reading will contribute to achieving the aims and learning outcomes of this module.
- The summative assessment comprises a two-hour examination to rest students' knowledge of key econometrics concepts, methods and principles, and their problem solving skills, plus a short project to test their ability to apply these methods and interpret the results.
Teaching Methods and Learning Hours
| Activity | Number | Frequency | Duration | Total/Hours | |
|---|---|---|---|---|---|
| Lectures | 9 | 1 per week | 2 hours | 18 | |
| Revision | 1 | Once | 2 hours | 2 | |
| Workshops | 4 | 2 hours | 8 | ■ | |
| Computer classes | 4 | 2 hours | 8 | ■ | |
| Preparation and reading | 114 | ||||
| Total | 150 |
Summative Assessment
| Component: Examination | Component Weighting: 75% | ||
|---|---|---|---|
| Element | Length / duration | Element Weighting | Resit Opportunity |
| One in-person written examination | 2 hours | 100% | Same |
| Component: Project | Component Weighting: 25% | ||
| Element | Length / duration | Element Weighting | Resit Opportunity |
| Project | 1000 words (maximum) | 100% | Same |
Formative Assessment:
One formative assessment to prepare students for the summative examination.
■ Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University