Module BUSI54330: Econometric Methods and Applications

Department: Business School (Business)

BUSI54330: Econometric Methods and Applications

Prerequisites

• None

Corequisites

• As specified in the Special Regulations

Excluded Combination of Modules

• None.

Aims

• 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.

Content

• 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

Learning Outcomes

• 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

• 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.

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

• 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.

Teaching Methods and Learning Hours

Summative Assessment

Formative Assessment:

Two assignments equivalent to 2,000 word essays..

■ 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