This is an archived handbook for a previous year. The current undergraduate and postgraduate handbooks can be viewed using the links above.
Postgraduate Handbook 2025-2026 (archived)
Module ECON41515: Econometric Analysis
Department: Economics
ECON41515: Econometric Analysis
| Type | Level | Credits | Availability | Module Cap | Location |
|---|---|---|---|---|---|
| Tied | 4 | 15 | Available in 2025/2026 | None. | Durham |
Tied To
- L1T109: Economics
- L1T409: Environmental & Natural Resource Economics
- L1T609: Behavioural Economics
- N3K709: Finance (Economics and Finance)
Pre-requisites
- One econometrics module or equivalent quantitative module covering basic statistics and probability theory including distributions as well as hypothesis testing.
Corequisites
- None
Excluded Combinations
- 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 | Attendance Monitored |
|---|---|---|---|---|---|
| Lectures | 9 | 1 per week | 2 hours | 18 | Yes |
| Revision Classes | 1 | Once | 2 hours | 2 | |
| Workshops | 4 | 2 hours | 8 | Yes | |
| Computer Classes | 4 | 2 hours | 8 | Yes | |
| Preparation and Reading | 114 | ||||
| Total | 150 | ||||
Summative Assessment
| Component | Component Weighting | Element | Length/Duration | Element Weighting | Resit Opportunity |
|---|---|---|---|---|---|
| Examination | 75% | On Campus Written Examination | 2 hours | 100% | |
| Project | 25% | Project | 1000 words (maximum) | 100% |
Formative Assessment
One formative assessment to prepare students for the summative examination.
Students who do not attend monitored activities shown under Teaching Methods
and Learning Hours, or who fail to complete the summative or formative
assessment(s) specified above, may be subject to the Academic Progress
procedures defined in the University's General Regulation V, and may be
required to leave the University.