Econometric Analysis

Module title	Econometric Analysis
Module code	BEE3015
Academic year	2019/0
Credits	30
Module staff	Dr Sebastian Kripfganz (Convenor)

Duration: Term	1	2	3
Duration: Weeks	11	11

Number students taking module (anticipated)	20

Module description

Summary:

This module covers more advanced modelling and statistical inference techniques for single and multi-equation systems and the use of these techniques for prediction and model evaluation.

Additional Information:

Internationalisation

This module presents a mixture of econometric theory and applications with an emphasis on understanding the theory, but it is broadly a mathematical module. Since mathematics is an international language, the course content is relevant across the globe in theory and in practice.

Employability

Students are given tough material to master which helps them acquire advanced mathematical and numeracy skills which are highly valued by the majority of employers.

Sustainability

All the resources for the module are available on the ELE (Exeter Learning Environment).

Module aims - intentions of the module

This module aims to provide a thorough grounding in the modern theory of econometrics, together with working knowledge of the most important topics in econometric estimation and inference. Econometrics is now so large a subject that it is impossible to cover all areas of interest in one course. Coverage of econometric methods has to be selective. However, one essential objective is to achieve a sound, critical understanding of the theory of econometric inference – in other words, to know what claims can and cannot be made legitimately about the properties of estimates, tests and forecasts. This is more important in the long run than mastering a litany of formulae and techniques. Students will have the opportunity to apply the methods learned to real-world problems on the computer and learn to use econometric software packages.

Intended Learning Outcomes (ILOs)

ILO: Module-specific skills

On successfully completing the module you will be able to...

1. demonstrate a comprehensive knowledge of the theory of econometric inference
2. apply their understanding of econometrics to undertake empirical economic analysis and show the potential to contribute to knowledge, through original research

ILO: Discipline-specific skills

On successfully completing the module you will be able to...

3. demonstrate a clear understanding of the mathematical and statistical background of applied economics
4. demonstrate the ability to critically assess, and carry out, empirical studies in economics
5. use a computer for estimation and simulation exercise

ILO: Personal and key skills

On successfully completing the module you will be able to...

6. communicate effectively, using appropriate technical terms, in a variety of forms
7. demonstrate a confident and flexible approach to identifying and defining complex problems and apply appropriate knowledge and methods to solve them
8. analyse data and situations without guidance, using a range of appropriate techniques

Syllabus plan

Term 1

Revision of Matrix Algebra and Statistical Theory
The Linear Regression Model
Specification Testing
Asymptotic Theory

Term 2

Instrumental Variables / Generalized Method of Moments Estimation
Maximum Likelihood Estimation
Linear Regression with Time-Series Data
Linear Regression with Panel Data

Learning activities and teaching methods (given in hours of study time)

Scheduled Learning and Teaching Activities	Guided independent study	Placement / study abroad
40	260	0

Details of learning activities and teaching methods

Category	Hours of study time	Description
Contact hours	40

Formative assessment

Form of assessment	Size of the assessment (eg length / duration)	ILOs assessed	Feedback method
Tutorial questions	1 hour/ 2 weeks	1-4, 6-8	In class discussion

Summative assessment (% of credit)

Coursework	Written exams	Practical exams
30	70	0

Details of summative assessment

Form of assessment	% of credit	Size of the assessment (eg length / duration)	ILOs assessed	Feedback method
Homework assignment (Term 1) in the form of algebraic problems and data analyses	15	3-5 problems (of which 1 or 2 are computer exercises)	1-8	Class discussion
Homework assignment (Term 2) in the form of algebraic problems and data analyses	15	3-5 problems (of which 1 or 2 are computer exercises)	1-8	Class discussion
Examination	70	3 hours	1,3,4,6,7	Written feedback as requested

Details of re-assessment (where required by referral or deferral)

Original form of assessment	Form of re-assessment	ILOs re-assessed	Timescale for re-assessment
Homework assignment (term 1 - 15%)	Homework assignment (term 1 - 15%)	1-8	To be decided when original work returned
Homework assignment (term 2 - 15%)	Homework assignment (term 2 - 15%)	1-8	To be decided when original work returned
Examination	Examination	1,3,4,6,7	August examination period

Indicative learning resources - Basic reading

Basic reading:

The course will not follow any single text, and you are recommended to read widely. The recommended one for purchase and thorough study this year is:

Verbeek, M. (2012) A Guide to Modern Econometrics (4th Edition) Chichester: Wiley

Other texts which may be recommended during the module are:

Davidson, J. (2000) Econometric Theory, Oxford: Blackwell
Davidson, R. and MacKinnon, J. (2004) Econometric Theory and Methods, Oxford: OUP
Greene, W. (2012) Econometric Analysis, 7th edition, Pearson Education/Prentice Hall
Johnston, J. and DiNardo, J. (1997) Econometric Methods, New York: McGraw Hill
Judge, G., Griffiths, W., Carter-Hill, R., Luetkepohl, H. and Lee, T. (1998) The Theory and Practice of Econometrics, 2nd edition, Chichester: Wiley
Wooldridge, J. M. (2016) Introductory Econometrics: A Modern Approach, 6th edition, Boston: Cengage Learning

Credit value	30
Module ECTS	15
Module pre-requisites	BEE2031 (BEE2006) and BEE2020
Module co-requisites	None
NQF level (module)	6
Available as distance learning?	No
Origin date	01/09/1998
Last revision date	20/08/2018