BUSI54330: Econometric Methods and Applications

• None

• As specified in the Special Regulations

• None.

• The aim of this module is to provide students with an advanced level of understanding of modern econometric theories, practices and the tools (econometric software) required to predict, model and analyse economic variables and their associated behaviour.

• 1st Term:
• Introduction
• Classical Linear Regression Model
• Classical Hypothesis Tests for Specification Error
• Maximum Likelihood (ML), Generalised Least Squares (GLS) and Instrumental Variable (IV) Estimators
• Heteroscedasticity and Autocorrelation
• 2nd Term:
• Time Series Models: Autoregressive Models, Moving Average Models
• Vector Autoregressions. Modelling, Impulse response functions
• Stationarity. Unit roots, Order of Integration
• cointegration. Engle Granter two step procedure, Johansen's cointegration VAR
• Limited Dependent Variable and Related Models
• Panel Data

Subject-specific Knowledge:

• Developed an advanced level of knowledge of the econometric tools.
• Appreciate how econometrics is used in the current applied literature on economic modelling and forecasting
• Been enabled to use their econometrical tools to conduct their own empirical investigations
• Acquired the following critical, analytical and key skills

Subject-specific Skills:

Key Skills:

• Written communication, via formative and summative assessment
• Planning and organising, via preparation for workshops, meeting formative assessment deadlines, and co-ordinating the data collection, econometric analysis, sustained independent study of the the literature, and writing up of their summative project by the deadline
• Problem solving, via understanding the technical problems assessed by the formative and summative work, as well as the analytical and quantitative skills of econometrics
• Initiative, in searching the relevant literature, choosing from a range of techniques the most appropriate for the problem at hand, interpreting results and drawing conclusions
• Numeracy, required for understanding and applying the mathematical and statistical tools which underpin econometric analysis
• IT skills, via usage of econometric software for the statistical analysis of data, and word-processing, required for the presentation of the summative work.

• A combination of lectures, seminars and guided reading will be used to convey the basic theories and concepts and to enhance students' understanding and ability to apply them.
• The summative assignment will test students' knowledge and understanding of the subject matter, and their ability to apply what they have learned in a particular context.

If you have a question about Durham's modular degree programmes, please visit our Help page. If you have a question about modular programmes that is not covered by the Help page, or a query about the on-line Postgraduate Module Handbook, please contact us.

Prospective Students: If you have a query about a specific module or degree programme, please Ask Us.

Current Students: Please contact your department.