Module Synopsis
Module Introduction
This module is currently a core offering to full-time students on courses on the MSc Economics suite, including MSc Business Economics and MSc Financial Economics degree programmes.
Module Synopsis
This module will introduce you to some of the key skills and knowledge required by those seeking to become practitioners in banking, investment, consulting and financial markets and economics more generally. It aims to offer a thorough grounding in the theory and practice of conventional techniques used in econometrics and applies these to develop solutions to common economics problems.
Learning Strategy
Generally, a two hour lecture and seminar combination willoccur each week. The lectures will provide you with knowledge of the key skills and the seminars will allow you to consider applications of these skills to real world business and economic problems. Your learning will be supported by reference to online resources as well as standard text books. Some student-centred learning will be expected and this includes (but is not limited to) consultation of recommended books and articles.
Seminars will also require you to demonstrate the skills and competencies outlined above and to discuss relevant issues learnedly and confidently via group situations.
Learning Outcomes
Knowledge and Understanding Outcomes
On completion of this module students will:
1. Develop a critical understanding of the theoretical foundations of econometrics.
2. Demonstrate a critical appreciation of competing techniques in econometrics.
3. Critique and assess the relevance of different techniques to solving economic problems.
4. Acquire a detailed understanding of the mathematical and statistical foundations of macroeconomics and microeconomics.
Ability Outcomes
On completion of this module students will be able to:
1. Critically assess the relevance of econometric theories to pressing economic concerns
2. Appraise and assess the impact of newly emerging econometric techniques to the solution of economic policy concerns.
3. Offer detailed and in-depth descriptions of key concepts such as serial correlation, maximum likelihood and heteroskedasticity.
4. Apply the findings of empirical evidence to measure the performance of econometric methods.
5. Remain abreast of recent developments in the theory and practice of econometrics.
Assessment Strategy
In order to pass the module all forms of assessment must be attempted.
Formative assessment
A range of formative devices; typically in-class reviews and feedback on participation within a seminar environment.
Summative Assessment
Assessment tasks (including assessment weightings)
A 4,000 work individual applied econometric research report; weighting 100% (all learning outcomes are assessed by this assessment.)
Not marked anonymously. This course work is eligible for tutor reassessment. This is the final piece of assessment. Due for submission on 11th April 2014
The project title will be announced shortly
Assessment Criteria
The assessment for criteria is as set out in the Huddersfield University Business School Assessment Guidelines. The guidelines provide criteria for the assessment of both coursework and examinations.
See below for guidance on criteria for the report:
CRITERIA EXCELLENT
(70%+) GOOD
(60 – 69%) SATISFACTORY
(50 – 59%) WEAK
(40 – 49%) POOR
(<40%)
Quality of research
Excellent use of sources. Extensive use made of appropriate journal articles
Good use of sources. Wide range of High quality sources used.
Satisfactory use of a range of sources. Relies on small number of sources.
Evidence of some research. Limited sources used
Little use of sources beyond key textbooks
Knowledge and understanding
Authoritative handling of complex material
Skilled, demonstrates sound knowledge
Satisfactory knowledge and understanding of main issues
Some knowledge and understanding of main issues and concepts
Little knowledge or understanding of the issues and concepts
Argument – how well you develop an argument
Well focused, convincing argument which demonstrates precision of thought
Logical, justified argument and effective writing style
Logical, clear presentation with competent style of writing
Attempt made to meet objectives. May lack balance or ability to develop an argument
Little evidence of analysis or development of an argument
Structure and clarity
Well structured and easily understood.
Coherent, soundly structured.
Adequately structured Reasonably easy to understand.
Some attempt to structure. Lacks clarity in some areas.
Very little understanding of how to structure. Very poor in terms of clarity
Ability in handling of quotations and references
High degree of skill in use of references
Skilled use of references .
Adequate use of references
Limited use of references
Very little or no reference to the literature
Originality
Demonstrates excellent insight and creativity
Demonstrates insight and individual thought
Demonstrates synthesis of knowledge
Limited evidence of thought or originality
No originality
Outline Programme
Please see Delivery schedule under Learning Resources on the UniLearn module page for latest details
The provisional schedule for the semester is below. The dates and content are subject to change.
Lecture notes will be available in advance of the lectures and printed copies of slides will not be provided. Lectures and seminars take place on Wednesdays at 9:15 in BSG/16.
Week Lecture Date Lecture Title Seminar
1 RON LF 22ndJanuary Introduction to the module
Introduction to module project
Introduction to data types Introduction to data types
2 LF 29th January Linear regression and correlation Solving regression equations
3 LF 5th February Model evaluation
Hypothesis testing Practice problems
4 LF 12th February Using the regression equation
Regression Diagnostics Article discussion
5 LF 19th February Multiple regression Does size matter? Regression in practice
6 LF 26th February Data transformations
7RON LF 5th March Eviews Introduction (This class will be held in BS2/39) Project briefing
8 RON 12th March Univariate time series modelling: serial autocorrelation & moving averages
Constructing an ARMA model
9 RON 19th March Heteroscedasticity& generalised least squares Examples of heteroscedasticity/GLS in finance and house price models
10 RON 26th March Stationary and non-stationary time series
How to test for a unit root in a time series?
11 RON 2nd April Estimation issues in econometrics: GMM, Maximum Likelihood and instrumental variables (2hrs)
12 RON LF 9th April Cointegration and error correction models Course roundup/ Q&A session
.
The date for submission of the assessed project will be 11th April 2014, via electronic submission.
Eviews
Eviews 8 is available for student use in room BS2/39 & BSG/25. It can be accessed from the start menu in the folder SBUS software and the sub-folder Eviews 8
Module References
Asteriou, D. and Hall, S. Applied Econometrics: A Modern Approach Palgrave Macmillan
Greene, W. Econometric Analysis Pearson
A number of other readings and source material arealso beheld on the module UniLearn site.
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